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Sample records for self-organization scenario grounded

  1. Self-organization scenario grounded on new experimental results

    Energy Technology Data Exchange (ETDEWEB)

    Lozneanu, E. [Complex System Laboratory, Al. I. Cuza University, Blvd Carol I, No. 11, Iasi 700506 (Romania); Sanduloviciu, M. [Complex System Laboratory, Al. I. Cuza University, Blvd Carol I, No. 11, Iasi 700506 (Romania)], E-mail: msandu@uaic.ro

    2009-05-30

    Recently published experimental results proving that well-located plasma created in air by quick injection of energy naturally evolves into a coherent, apparently stable and luminous gaseous body, dubbed fireball, are explained considering a new scenario of self-organization. Bordered by a functional double layer emerged by direct conversion of thermal energy into electric field energy through a mechanism exploiting collective effects of quantum processes, the fireball survives for durations that depend on the environmental conditions. Based on this scenario of self-organization that evolves in a time span in which the second law of thermodynamics ceases to work, enigmas as the ball lightning and the origin of life becomes potentially explainable.

  2. Postprocessing of Accidental Scenarios by Semi-Supervised Self-Organizing Maps

    Directory of Open Access Journals (Sweden)

    Francesco Di Maio

    2017-01-01

    Full Text Available Integrated Deterministic and Probabilistic Safety Analysis (IDPSA of dynamic systems calls for the development of efficient methods for accidental scenarios generation. The necessary consideration of failure events timing and sequencing along the scenarios requires the number of scenarios to be generated to increase with respect to conventional PSA. Consequently, their postprocessing for retrieving safety relevant information regarding the system behavior is challenged because of the large amount of generated scenarios that makes the computational cost for scenario postprocessing enormous and the retrieved information difficult to interpret. In the context of IDPSA, the interpretation consists in the classification of the generated scenarios as safe, failed, Near Misses (NMs, and Prime Implicants (PIs. To address this issue, in this paper we propose the use of an ensemble of Semi-Supervised Self-Organizing Maps (SSSOMs whose outcomes are combined by a locally weighted aggregation according to two strategies: a locally weighted aggregation and a decision tree based aggregation. In the former, we resort to the Local Fusion (LF principle for accounting the classification reliability of the different SSSOM classifiers, whereas in the latter we build a classification scheme to select the appropriate classifier (or ensemble of classifiers, for the type of scenario to be classified. The two strategies are applied for the postprocessing of the accidental scenarios of a dynamic U-Tube Steam Generator (UTSG.

  3. Sorted patterned ground: Numerical models exhibiting self-organization

    OpenAIRE

    Kessler, Mark A.

    2002-01-01

    Sorted patterned ground, decimeter- to meter-scale patterns of circular, polygonal, striped and labyrinthine stone and soil domains, form in Arctic, sub­Arctic and high alpine environments where the surface ground layer, the active layer, experiences cyclic freezing and thawing that drives transport by frost heave, which is soil expansion via ice lens formation. In numerical models encapsulating observed and inferred active layer processes, all forms of sorted patterned ground emerge from an ...

  4. Interactive image data labeling using self-organizing maps in an augmented reality scenario.

    Science.gov (United States)

    Bekel, Holger; Heidemann, Gunther; Ritter, Helge

    2005-01-01

    We present an approach for the convenient labeling of image patches gathered from an unrestricted environment. The system is employed for a mobile Augmented Reality (AR) gear: while the user walks around with the head-mounted AR-gear, context-free modules for focus-of-attention permanently sample the most 'interesting' image patches. After this acquisition phase, a Self-Organizing Map (SOM) is trained on the complete set of patches, using combinations of MPEG-7 features as a data representation. The SOM allows visualization of the sampled patches and an easy manual sorting into categories. With very little effort, the user can compose a training set for a classifier, thus, unknown objects can be made known to the system. We evaluate the system for COIL-imagery and demonstrate that a user can reach satisfying categorization within few steps, even for image data sampled from walking in an office environment. (An abbreviated version of some portions of this article appeared in [Bekel, H., Heidemann, G., & Ritter, H. (2005). SOM Based Image Data Structuring in an Augmented Reality Scenario. In Proceedings of the International Joint Conference on Neural Networks, Montreal, Canada.], as part of the IJCNN 2005 conference proceedings, published under the IEEE copyright).

  5. [A possible scenario for spatial and temporal evolution of self-organizing biophysical structures].

    Science.gov (United States)

    Shestopalov, V P

    2001-01-01

    The stationary diffraction theory, the spectral theory of open systems, and the theory of Morse critical points of dispersion equations made it possible, when applied to bounded self-organizing biological media, to formulate the analytical dispersion laws and construct nonlinear evolution equations describing local space and time processes in a biomacromolecular continuum. By the simplest examples of the solution of the nonlinear evolution equations for planar medium interfaces, a variety of dynamical phenomena occurring in the self-organization of macromolecules are shown.

  6. Sorted bed forms as self-organized patterns: 2. complex forcing scenarios

    Science.gov (United States)

    Coco, Giovanni; Murray, A. Brad; Green, Malcom O.; Thieler, E. Robert; Hume, T.M.

    2007-01-01

    We employ a numerical model to study the development of sorted bed forms under a variety of hydrodynamic and sedimentary conditions. Results indicate that increased variability in wave height decreases the growth rate of the features and can potentially give rise to complicated, a priori unpredictable, behavior. This happens because the system responds to a change in wave characteristics by attempting to self-organize into a patterned seabed of different geometry and spacing. The new wavelength might not have enough time to emerge before a new change in wave characteristics occurs, leading to less regular seabed configurations. The new seabed configuration is also highly dependent on the preexisting morphology, which further limits the possibility of predicting future behavior. For the same reasons, variability in the mean current magnitude and direction slows down the growth of features and causes patterns to develop that differ from classical sorted bed forms. Spatial variability in grain size distribution and different types of net sediment aggradation/degradation can also result in the development of sorted bed forms characterized by a less regular shape. Numerical simulations qualitatively agree with observed geometry (spacing and height) of sorted bed forms. Also in agreement with observations is that at shallower depths, sorted bed forms are more likely to be affected by changes in the forcing conditions, which might also explain why, in shallow waters, sorted bed forms are described as ephemeral features. Finally, simulations indicate that the different sorted bed form shapes and patterns observed in the field might not necessarily be related to diverse physical mechanisms. Instead, variations in sorted bed form characteristics may result from variations in local hydrodynamic and/or sedimentary conditions.

  7. SOLO: Self Organizing Live Objects

    Science.gov (United States)

    2008-12-01

    1 SOLO: Self Organizing Live Objects Qi Huang1, 2 (contact, tel. +16073519956), Ken Birman2 1School of Computer Science & Technology...levels of performance, relia- bility, or other QoS objectives. Here, we describe SOLO, a new platform we’re constructing as part of Cornell’s Live ...scenarios that would be expected in wide-area environments. Category: Regular paper for the PDS track (5700 words). Keywords: Self-organization, Live

  8. Artificial intelligence costs, benefits, and risks for selected spacecraft ground system automation scenarios

    Science.gov (United States)

    Truszkowski, Walter F.; Silverman, Barry G.; Kahn, Martha; Hexmoor, Henry

    1988-01-01

    In response to a number of high-level strategy studies in the early 1980s, expert systems and artificial intelligence (AI/ES) efforts for spacecraft ground systems have proliferated in the past several years primarily as individual small to medium scale applications. It is useful to stop and assess the impact of this technology in view of lessons learned to date, and hopefully, to determine if the overall strategies of some of the earlier studies both are being followed and still seem relevant. To achieve that end four idealized ground system automation scenarios and their attendant AI architecture are postulated and benefits, risks, and lessons learned are examined and compared. These architectures encompass: (1) no AI (baseline); (2) standalone expert systems; (3) standardized, reusable knowledge base management systems (KBMS); and (4) a futuristic unattended automation scenario. The resulting artificial intelligence lessons learned, benefits, and risks for spacecraft ground system automation scenarios are described.

  9. Artificial intelligence costs, benefits, risks for selected spacecraft ground system automation scenarios

    Science.gov (United States)

    Truszkowski, Walter F.; Silverman, Barry G.; Kahn, Martha; Hexmoor, Henry

    1988-01-01

    In response to a number of high-level strategy studies in the early 1980s, expert systems and artificial intelligence (AI/ES) efforts for spacecraft ground systems have proliferated in the past several years primarily as individual small to medium scale applications. It is useful to stop and assess the impact of this technology in view of lessons learned to date, and hopefully, to determine if the overall strategies of some of the earlier studies both are being followed and still seem relevant. To achieve that end four idealized ground system automation scenarios and their attendant AI architecture are postulated and benefits, risks, and lessons learned are examined and compared. These architectures encompass: (1) no AI (baseline), (2) standalone expert systems, (3) standardized, reusable knowledge base management systems (KBMS), and (4) a futuristic unattended automation scenario. The resulting artificial intelligence lessons learned, benefits, and risks for spacecraft ground system automation scenarios are described.

  10. Self-organizing networks

    DEFF Research Database (Denmark)

    Marchetti, Nicola; Prasad, Neeli R.; Johansson, Johan

    2010-01-01

    In this paper, a general overview of Self-Organizing Networks (SON), and the rationale and state-of-the-art of wireless SON are first presented. The technical and business requirements are then briefly treated, and the research challenges within the field of SON are highlighted. Thereafter......, the relation between SON and Cognitive Networks (CN) is covered. At last, the application of Algorithmic Information Theory (AIT) as a possible theoretical tool to support SON in addressing the growing complexity of networks is discussed....

  11. Ground motion modeling of Hayward fault scenario earthquakes II:Simulation of long-period and broadband ground motions

    Energy Technology Data Exchange (ETDEWEB)

    Aagaard, B T; Graves, R W; Rodgers, A; Brocher, T M; Simpson, R W; Dreger, D; Petersson, N A; Larsen, S C; Ma, S; Jachens, R C

    2009-11-04

    We simulate long-period (T > 1.0-2.0 s) and broadband (T > 0.1 s) ground motions for 39 scenarios earthquakes (Mw 6.7-7.2) involving the Hayward, Calaveras, and Rodgers Creek faults. For rupture on the Hayward fault we consider the effects of creep on coseismic slip using two different approaches, both of which reduce the ground motions compared with neglecting the influence of creep. Nevertheless, the scenario earthquakes generate strong shaking throughout the San Francisco Bay area with about 50% of the urban area experiencing MMI VII or greater for the magnitude 7.0 scenario events. Long-period simulations of the 2007 Mw 4.18 Oakland and 2007 Mw 4.5 Alum Rock earthquakes show that the USGS Bay Area Velocity Model version 08.3.0 permits simulation of the amplitude and duration of shaking throughout the San Francisco Bay area, with the greatest accuracy in the Santa Clara Valley (San Jose area). The ground motions exhibit a strong sensitivity to the rupture length (or magnitude), hypocenter (or rupture directivity), and slip distribution. The ground motions display a much weaker sensitivity to the rise time and rupture speed. Peak velocities, peak accelerations, and spectral accelerations from the synthetic broadband ground motions are, on average, slightly higher than the Next Generation Attenuation (NGA) ground-motion prediction equations. We attribute at least some of this difference to the relatively narrow width of the Hayward fault ruptures. The simulations suggest that the Spudich and Chiou (2008) directivity corrections to the NGA relations could be improved by including a dependence on the rupture speed and increasing the areal extent of rupture directivity with period. The simulations also indicate that the NGA relations may under-predict amplification in shallow sedimentary basins.

  12. Within-Event and Between-Events Ground Motion Variability from Earthquake Rupture Scenarios

    Science.gov (United States)

    Crempien, Jorge G. F.; Archuleta, Ralph J.

    2017-09-01

    Measurement of ground motion variability is essential to estimate seismic hazard. Over-estimation of variability can lead to extremely high annual hazard estimates of ground motion exceedance. We explore different parameters that affect the variability of ground motion such as the spatial correlations of kinematic rupture parameters on a finite fault and the corner frequency of the moment-rate spectra. To quantify the variability of ground motion, we simulate kinematic rupture scenarios on several vertical strike-slip faults and compute ground motion using the representation theorem. In particular, for the entire suite of rupture scenarios, we quantify the within-event and the between-events ground motion variability of peak ground acceleration (PGA) and response spectra at several periods, at 40 stations—all approximately at an equal distance of 20 and 50 km from the fault. Both within-event and between-events ground motion variability increase when the slip correlation length on the fault increases. The probability density functions of ground motion tend to truncate at a finite value when the correlation length of slip decreases on the fault, therefore, we do not observe any long-tail distribution of peak ground acceleration when performing several rupture simulations for small correlation lengths. Finally, for a correlation length of 6 km, the within-event and between-events PGA log-normal standard deviations are 0.58 and 0.19, respectively, values slightly smaller than those reported by Boore et al. (Earthq Spectra, 30(3):1057-1085, 2014). The between-events standard deviation is consistently smaller than the within-event for all correlations lengths, a feature that agrees with recent ground motion prediction equations.

  13. Hybrid Broadband Ground-Motion Simulation Using Scenario Earthquakes for the Istanbul Area

    KAUST Repository

    Reshi, Owais A.

    2016-04-13

    Seismic design, analysis and retrofitting of structures demand an intensive assessment of potential ground motions in seismically active regions. Peak ground motions and frequency content of seismic excitations effectively influence the behavior of structures. In regions of sparse ground motion records, ground-motion simulations provide the synthetic seismic records, which not only provide insight into the mechanisms of earthquakes but also help in improving some aspects of earthquake engineering. Broadband ground-motion simulation methods typically utilize physics-based modeling of source and path effects at low frequencies coupled with high frequency semi-stochastic methods. I apply the hybrid simulation method by Mai et al. (2010) to model several scenario earthquakes in the Marmara Sea, an area of high seismic hazard. Simulated ground motions were generated at 75 stations using systematically calibrated model parameters. The region-specific source, path and site model parameters were calibrated by simulating a w4.1 Marmara Sea earthquake that occurred on November 16, 2015 on the fault segment in the vicinity of Istanbul. The calibrated parameters were then used to simulate the scenario earthquakes with magnitudes w6.0, w6.25, w6.5 and w6.75 over the Marmara Sea fault. Effects of fault geometry, hypocenter location, slip distribution and rupture propagation were thoroughly studied to understand variability in ground motions. A rigorous analysis of waveforms reveal that these parameters are critical for determining the behavior of ground motions especially in the near-field. Comparison of simulated ground motion intensities with ground-motion prediction quations indicates the need of development of the region-specific ground-motion prediction equation for Istanbul area. Peak ground motion maps are presented to illustrate the shaking in the Istanbul area due to the scenario earthquakes. The southern part of Istanbul including Princes Islands show high amplitudes

  14. Ground state of the hydrogen atom via Dirac equation in a minimal-length scenario

    Energy Technology Data Exchange (ETDEWEB)

    Antonacci Oakes, T.L.; Francisco, R.O.; Fabris, J.C.; Nogueira, J.A. [Universidade Federal do Espirito Santo, Departamento de Fisica, Vitoria (Brazil)

    2013-07-15

    In this work we calculate the correction to the ground state energy of the hydrogen atom due to contributions arising from the presence of a minimal length. The minimal-length scenario is introduced by means of modifying the Dirac equation through a deformed Heisenberg algebra (Kempf algebra). With the introduction of the Coulomb potential in the new Dirac energy operator, we calculate the energy shift of the ground state of the hydrogen atom in first order of the parameter related to the minimal length via perturbation theory. (orig.)

  15. Ground motion modeling of the 1906 San Francisco earthquake II: Ground motion estimates for the 1906 earthquake and scenario events

    Energy Technology Data Exchange (ETDEWEB)

    Aagaard, B; Brocher, T; Dreger, D; Frankel, A; Graves, R; Harmsen, S; Hartzell, S; Larsen, S; McCandless, K; Nilsson, S; Petersson, N A; Rodgers, A; Sjogreen, B; Tkalcic, H; Zoback, M L

    2007-02-09

    We estimate the ground motions produced by the 1906 San Francisco earthquake making use of the recently developed Song et al. (2008) source model that combines the available geodetic and seismic observations and recently constructed 3D geologic and seismic velocity models. Our estimates of the ground motions for the 1906 earthquake are consistent across five ground-motion modeling groups employing different wave propagation codes and simulation domains. The simulations successfully reproduce the main features of the Boatwright and Bundock (2005) ShakeMap, but tend to over predict the intensity of shaking by 0.1-0.5 modified Mercalli intensity (MMI) units. Velocity waveforms at sites throughout the San Francisco Bay Area exhibit characteristics consistent with rupture directivity, local geologic conditions (e.g., sedimentary basins), and the large size of the event (e.g., durations of strong shaking lasting tens of seconds). We also compute ground motions for seven hypothetical scenarios rupturing the same extent of the northern San Andreas fault, considering three additional hypocenters and an additional, random distribution of slip. Rupture directivity exerts the strongest influence on the variations in shaking, although sedimentary basins do consistently contribute to the response in some locations, such as Santa Rosa, Livermore, and San Jose. These scenarios suggest that future large earthquakes on the northern San Andreas fault may subject the current San Francisco Bay urban area to stronger shaking than a repeat of the 1906 earthquake. Ruptures propagating southward towards San Francisco appear to expose more of the urban area to a given intensity level than do ruptures propagating northward.

  16. Scenarios

    NARCIS (Netherlands)

    Pérez-Soba, Marta; Maas, Rob

    2015-01-01

    We cannot predict the future with certainty, but we know that it is influenced by our current actions, and that these in turn are influenced by our expectations. This is why future scenarios have existed from the dawn of civilization and have been used for developing military, political and economic

  17. Self-Organized Transport System

    Science.gov (United States)

    2009-09-28

    This report presents the findings of the simulation model for a self-organized transport system where traffic lights communicate with neighboring traffic lights and make decisions locally to adapt to traffic conditions in real time. The model is insp...

  18. Ground Motion Simulations of Scenario Earthquake Ruptures of the Hayward Fault

    Science.gov (United States)

    Aagaard, B.; Graves, R.; Larsen, S.; Ma, S.; Rodgers, A.; Brocher, T.; Graymer, R.; Harris, R.; Lienkaemper, J.; Ponce, D.; Schwartz, D.; Simpson, R.; Spudich, P.; Dreger, D.; Petersson, A.; Boatwright, J.

    2008-12-01

    We compute ground motions in the San Francisco Bay area for a suite of 35 magnitude 6.7--7.2 scenario earthquake ruptures involving the Hayward fault. The suite of scenarios encompasses variability in rupture length, hypocenter, distribution of slip, rupture speed, and rise time. The five rupture lengths include the Hayward fault and portions thereof, as well as combined rupture of the Hayward and Rodgers Creek faults and the Hayward and Calaveras faults. For most rupture lengths, we consider three hypocenters, yielding north-to-south rupture, bilateral rupture, and south-to-north rupture. We also consider multiple random realizations of the slip distribution, accounting for creeping patches (Funning et al., 2007) either through simple assumptions about how creep reduces coseismic slip or a slip-predictable approach. The kinematic rupture models include local variations in rupture speed and use a ray-tracing algorithm to propagate the rupture front. Although we are not attempting to simulate the 1868 Hayward fault earthquake in detail, a few of the scenarios are designed to have source parameters that might be similar to this event. This collaborative effort involves four modeling groups, using different wave propagation codes and domains of various sizes and resolutions, computing long-period (T > 1--2 s) or broadband (T > 0.1 s) synthetic ground motions for overlapping subsets of the suite of scenarios. The simulations incorporate the 3-D geologic structure as described by the USGS 3-D Geologic Model (Jachens et al., 2006; Watt et al., 2007) and USGS Bay Area Velocity Model (Brocher et al., 2007). The simulations illustrate the dramatic increase in intensity of shaking for a magnitude 7.0 bilateral rupture of the entire Hayward fault compared with a magnitude 6.8 bilateral rupture of the southern two-thirds of the fault; the area subjected to shaking stronger than MMI VII increases from about 10% to more than 40% of the San Francisco Bay urban area. For a given

  19. Self-organized Learning Environments

    DEFF Research Database (Denmark)

    Dalsgaard, Christian; Mathiasen, Helle

    2007-01-01

    The purpose of the paper is to discuss the potentials of using a conference system in support of a project based university course. We use the concept of a self-organized learning environment to describe the shape of the course. In the paper we argue that educational technology, such as conference...... systems, has a potential to support students’ development of self-organized learning environments and facilitate self-governed activities in higher education. The paper is based on an empirical study of two project groups’ use of a conference system. The study showed that the students used the conference...... system actively. The two groups used the system in their own way to support their specific activities and ways of working. The paper concludes that self-organized learning environments can strengthen the development of students’ academic as well as social qualifications. Further, the paper identifies...

  20. Estimation of Seismic Loss for a Portfolio of Buildings under Bidirectional Horizontal Ground Motions due to a Scenario Cascadia Event

    Directory of Open Access Journals (Sweden)

    Taojun Liu

    2017-10-01

    Full Text Available Earthquake ground motions induced by a scenario event are spatially (partially correlated and (partially coherent. Simulated ground motion records can be used to carry out nonlinear inelastic time history analysis for a portfolio of buildings to estimate the seismic loss, which is advantageous as there is no need to develop and apply empirical ground motion prediction equations and the ductility demand rules, or to search the scenario-compatible recorded records at selected sites that may not exist. Further, if the structures being considered are sensitive to the orientation of the excitation, multiple-component ground motion records are needed. For the simulation of such ground motion records, previous studies have shown that correlation and coherency between any pair of ground motion components need to be incorporated. In this study, the seismic loss of a portfolio of hypothetical buildings in downtown Vancouver under bidirectional horizontal ground motions due to a scenario Cascadia event is estimated by using simulated bidirectional ground motion records that include realistic correlation and coherency characteristics. The hysteretic behaviors of the buildings are described by bidirectional Bouc–Wen model. The results show that the use of unidirectional ground motions and single-degree-of-freedom system structural model may underestimate the aggregated seismic loss.

  1. Earthquake Strong Ground Motion Scenario at the 2008 Olympic Games Sites, Beijing, China

    Science.gov (United States)

    Liu, L.; Rohrbach, E. A.; Chen, Q.; Chen, Y.

    2006-12-01

    Historic earthquake record indicates mediate to strong earthquakes have been frequently hit greater Beijing metropolitan area where is going to host the 2008 summer Olympic Games. For the readiness preparation of emergency response to the earthquake shaking for a mega event in a mega city like Beijing in summer 2008, this paper tries to construct the strong ground motion scenario at a number of gymnasium sites for the 2008 Olympic Games. During the last 500 years (the Ming and Qing Dynasties) in which the historic earthquake record are thorough and complete, there are at least 12 earthquake events with the maximum intensity of VI or greater occurred within 100 km radius centered at the Tiananmen Square, the center of Beijing City. Numerical simulation of the seismic wave propagation and surface strong ground motion is carried out by the pseudospectral time domain methods with viscoelastic material properties. To improve the modeling efficiency and accuracy, a multi-scale approach is adapted: the seismic wave propagation originated from an earthquake rupture source is first simulated by a model with larger physical domain with coarser grids. Then the wavefield at a given plane is taken as the source input for the small-scale, fine grid model for the strong ground motion study at the sites. The earthquake source rupture scenario is based on two particular historic earthquake events: One is the Great 1679 Sanhe-Pinggu Earthquake (M~8, Maximum Intensity XI at the epicenter and Intensity VIII in city center)) whose epicenter is about 60 km ENE of the city center. The other one is the 1730 Haidian Earthquake (M~6, Maximum Intensity IX at the epicenter and Intensity VIII in city center) with the epicentral distance less than 20 km away from the city center in the NW Haidian District. The exist of the thick Tertiary-Quaternary sediments (maximum thickness ~ 2 km) in Beijing area plays a critical role on estimating the surface ground motion at the Olympic Games sites, which

  2. Hybrid Map-Based Navigation Method for Unmanned Ground Vehicle in Urban Scenario

    Directory of Open Access Journals (Sweden)

    Huiyan Chen

    2013-07-01

    Full Text Available To reduce the data size of metric map and map matching computational cost in unmanned ground vehicle self-driving navigation in urban scenarios, a metric-topological hybrid map navigation system is proposed in this paper. According to the different positioning accuracy requirements, urban areas are divided into strong constraint (SC areas, such as roads with lanes, and loose constraint (LC areas, such as intersections and open areas. As direction of the self-driving vehicle is provided by traffic lanes and global waypoints in the road network, a simple topological map is fit for the navigation in the SC areas. While in the LC areas, the navigation of the self-driving vehicle mainly relies on the positioning information. Simultaneous localization and mapping technology is used to provide a detailed metric map in the LC areas, and a window constraint Markov localization algorithm is introduced to achieve accurate position using laser scanner. Furthermore, the real-time performance of the Markov algorithm is enhanced by using a constraint window to restrict the size of the state space. By registering the metric maps into the road network, a hybrid map of the urban scenario can be constructed. Real unmanned vehicle mapping and navigation tests demonstrated the capabilities of the proposed method.

  3. Projected global ground-level ozone impacts on vegetation under different emission and climate scenarios

    Directory of Open Access Journals (Sweden)

    P. Sicard

    2017-10-01

    Full Text Available The impact of ground-level ozone (O3 on vegetation is largely under-investigated at the global scale despite large areas worldwide that are exposed to high surface O3 levels. To explore future potential impacts of O3 on vegetation, we compared historical and projected surface O3 concentrations simulated by six global atmospheric chemistry transport models on the basis of three representative concentration pathways emission scenarios (i.e. RCP2.6, 4.5, 8.5. To assess changes in the potential surface O3 threat to vegetation at the global scale, we used the AOT40 metric. Results point out a significant exceedance of AOT40 in comparison with the recommendations of UNECE for the protection of vegetation. In fact, many areas of the Northern Hemisphere show that AOT40-based critical levels will be exceeded by a factor of at least 10 under RCP8.5. Changes in surface O3 by 2100 worldwide range from about +4–5 ppb in the RCP8.5 scenario to reductions of about 2–10 ppb in the most optimistic scenario, RCP2.6. The risk of O3 injury for vegetation, through the potential O3 impact on photosynthetic assimilation, decreased by 61 and 47 % under RCP2.6 and RCP4.5, respectively, and increased by 70 % under RCP8.5. Key biodiversity areas in southern and northern Asia, central Africa and North America were identified as being at risk from high O3 concentrations.

  4. Projected global ground-level ozone impacts on vegetation under different emission and climate scenarios

    Science.gov (United States)

    Sicard, Pierre; Anav, Alessandro; De Marco, Alessandra; Paoletti, Elena

    2017-10-01

    The impact of ground-level ozone (O3) on vegetation is largely under-investigated at the global scale despite large areas worldwide that are exposed to high surface O3 levels. To explore future potential impacts of O3 on vegetation, we compared historical and projected surface O3 concentrations simulated by six global atmospheric chemistry transport models on the basis of three representative concentration pathways emission scenarios (i.e. RCP2.6, 4.5, 8.5). To assess changes in the potential surface O3 threat to vegetation at the global scale, we used the AOT40 metric. Results point out a significant exceedance of AOT40 in comparison with the recommendations of UNECE for the protection of vegetation. In fact, many areas of the Northern Hemisphere show that AOT40-based critical levels will be exceeded by a factor of at least 10 under RCP8.5. Changes in surface O3 by 2100 worldwide range from about +4-5 ppb in the RCP8.5 scenario to reductions of about 2-10 ppb in the most optimistic scenario, RCP2.6. The risk of O3 injury for vegetation, through the potential O3 impact on photosynthetic assimilation, decreased by 61 and 47 % under RCP2.6 and RCP4.5, respectively, and increased by 70 % under RCP8.5. Key biodiversity areas in southern and northern Asia, central Africa and North America were identified as being at risk from high O3 concentrations.

  5. Self-organization as a possible route to fusion energy

    Energy Technology Data Exchange (ETDEWEB)

    Sanduloviciu, M.; Lozneanu, E.; Popescu, S. [Department of Plasma Physics, ' Al.I.Cuza' University, Iasi (Romania)

    2000-07-01

    The generation of a ball lightning-like complex structure by sudden injection of matter and energy proves the presence of a cascading self-organization scenario in an experimental device containing a collisional plasma. Based on these results, we suggest the possibility to replicate, under controlled laboratory conditions, the ball lightning-like structures with potential fusion applications. (author)

  6. PREFACE: Self-organized nanostructures

    Science.gov (United States)

    Rousset, Sylvie; Ortega, Enrique

    2006-04-01

    In order to fabricate ordered arrays of nanostructures, two different strategies might be considered. The `top-down' approach consists of pushing the limit of lithography techniques down to the nanometre scale. However, beyond 10 nm lithography techniques will inevitably face major intrinsic limitations. An alternative method for elaborating ultimate-size nanostructures is based on the reverse `bottom-up' approach, i.e. building up nanostructures (and eventually assemble them to form functional circuits) from individual atoms or molecules. Scanning probe microscopies, including scanning tunnelling microscopy (STM) invented in 1982, have made it possible to create (and visualize) individual structures atom by atom. However, such individual atomic manipulation is not suitable for industrial applications. Self-assembly or self-organization of nanostructures on solid surfaces is a bottom-up approach that allows one to fabricate and assemble nanostructure arrays in a one-step process. For applications, such as high density magnetic storage, self-assembly appears to be the simplest alternative to lithography for massive, parallel fabrication of nanostructure arrays with regular sizes and spacings. These are also necessary for investigating the physical properties of individual nanostructures by means of averaging techniques, i.e. all those using light or particle beams. The state-of-the-art and the current developments in the field of self-organization and physical properties of assembled nanostructures are reviewed in this issue of Journal of Physics: Condensed Matter. The papers have been selected from among the invited and oral presentations of the recent summer workshop held in Cargese (Corsica, France, 17-23 July 2005). All authors are world-renowned in the field. The workshop has been funded by the Marie Curie Actions: Marie Curie Conferences and Training Courses series named `NanosciencesTech' supported by the VI Framework Programme of the European Community, by

  7. Ground motion prediction and earthquake scenarios in the volcanic region of Mt. Etna (Southern Italy

    Science.gov (United States)

    Langer, Horst; Tusa, Giuseppina; Luciano, Scarfi; Azzaro, Raffaela

    2013-04-01

    One of the principal issues in the assessment of seismic hazard is the prediction of relevant ground motion parameters, e. g., peak ground acceleration, radiated seismic energy, response spectra, at some distance from the source. Here we first present ground motion prediction equations (GMPE) for horizontal components for the area of Mt. Etna and adjacent zones. Our analysis is based on 4878 three component seismograms related to 129 seismic events with local magnitudes ranging from 3.0 to 4.8, hypocentral distances up to 200 km, and focal depth shallower than 30 km. Accounting for the specific seismotectonic and geological conditions of the considered area we have divided our data set into three sub-groups: (i) Shallow Mt. Etna Events (SEE), i.e., typically volcano-tectonic events in the area of Mt. Etna having a focal depth less than 5 km; (ii) Deep Mt. Etna Events (DEE), i.e., events in the volcanic region, but with a depth greater than 5 km; (iii) Extra Mt. Etna Events (EEE), i.e., purely tectonic events falling outside the area of Mt. Etna. The predicted PGAs for the SEE are lower than those predicted for the DEE and the EEE, reflecting their lower high-frequency energy content. We explain this observation as due to the lower stress drops. The attenuation relationships are compared to the ones most commonly used, such as by Sabetta and Pugliese (1987)for Italy, or Ambraseys et al. (1996) for Europe. Whereas our GMPEs are based on small earthquakes, the magnitudes covered by the two above mentioned attenuation relationships regard moderate to large magnitudes (up to 6.8 and 7.9, respectively). We show that the extrapolation of our GMPEs to magnitues beyond the range covered by the data is misleading; at the same time also the afore mentioned relationships fail to predict ground motion parameters for our data set. Despite of these discrepancies, we can exploit our data for setting up scenarios for strong earthquakes for which no instrumental recordings are

  8. Simulated ground motion in Santa Clara Valley, California, and vicinity from M≥6.7 scenario earthquakes

    Science.gov (United States)

    Harmsen, Stephen C.; Hartzell, Stephen

    2008-01-01

    Models of the Santa Clara Valley (SCV) 3D velocity structure and 3D finite-difference software are used to predict ground motions from scenario earthquakes on the San Andreas (SAF), Monte Vista/Shannon, South Hayward, and Calaveras faults. Twenty different scenario ruptures are considered that explore different source models with alternative hypocenters, fault dimensions, and rupture velocities and three different velocity models. Ground motion from the full wave field up to 1 Hz is exhibited as maps of peak horizontal velocity and pseudospectral acceleration at periods of 1, 3, and 5 sec. Basin edge effects and amplification in sedimentary basins of the SCV are observed that exhibit effects from shallow sediments with relatively low shear-wave velocity (330 m/sec). Scenario earthquakes have been simulated for events with the following magnitudes: (1) M 6.8–7.4 Calaveras sources, (2) M 6.7–6.9 South Hayward sources, (3) M 6.7 Monte Vista/Shannon sources, and (4) M 7.1–7.2 Peninsula segment of the SAF sources. Ground motions are strongly influenced by source parameters such as rupture velocity, rise time, maximum depth of rupture, hypocenter, and source directivity. Cenozoic basins also exert a strong influence on ground motion. For example, the Evergreen Basin on the northeastern side of the SCV is especially responsive to 3–5-sec energy from most scenario earthquakes. The Cupertino Basin on the southwestern edge of the SCV tends to be highly excited by many Peninsula and Monte Vista fault scenarios. Sites over the interior of the Evergreen Basin can have long-duration coda that reflect the trapping of seismic energy within this basin. Plausible scenarios produce predominantly 5-sec wave trains with greater than 30 cm/sec sustained ground-motion amplitude with greater than 30 sec duration within the Evergreen Basin.

  9. Future Residential Water Heating Prospects in Brazil: A Scenario Building Ground Analysis

    Directory of Open Access Journals (Sweden)

    Felipe de Albuquerque Sgarbi

    2014-12-01

    Full Text Available In Brazil, electricity is the prime energy carrier for bath shower heating purposes. However, since analyses indicate that expansion of the country´s electricity generation capacity shall spruce from an increased non-renewable sources’ stake in detriment to that of hydroelectricity, high electricity consumption rates that spring from home end uses of the kind have drawn the attention of those who are involved with local energy planning. Furthermore, massive use of electric showers in a short timeframe largely drive electricity demands to culminate in peak loads. For water heating purposes, this context has favoured an alternative to electricity, deemed feasible from both an efficiency and energy infrastructure standpoint: promote fuel gas consumption (liquefied petroleum gas and natural gas in particular. A scenario methodology is herein employed to map electric shower use related variables and players and assess the future behaviour of the core elements that condition resorting to this technology. Thereafter, strategies and opportunities to promote the rational consumption of the country´s power sources ground on the increased use of fuel gases for residential water heating purposes are discussed.

  10. Measuring the Complexity of Self-Organizing Traffic Lights

    Directory of Open Access Journals (Sweden)

    Darío Zubillaga

    2014-04-01

    Full Text Available We apply measures of complexity, emergence, and self-organization to an urban traffic model for comparing a traditional traffic-light coordination method with a self-organizing method in two scenarios: cyclic boundaries and non-orientable boundaries. We show that the measures are useful to identify and characterize different dynamical phases. It becomes clear that different operation regimes are required for different traffic demands. Thus, not only is traffic a non-stationary problem, requiring controllers to adapt constantly; controllers must also change drastically the complexity of their behavior depending on the demand. Based on our measures and extending Ashby’s law of requisite variety, we can say that the self-organizing method achieves an adaptability level comparable to that of a living system.

  11. Losing ground - scenarios of land loss as consequence of shifting sediment budgets in the Mekong Delta

    Science.gov (United States)

    Schmitt, R. J. P.; Rubin, Z.; Kondolf, G. M.

    2017-10-01

    With changing climate and rising seas, proliferation of hydroelectric dams, instream sand mining, dyking of floodplains, accelerated subsidence from groundwater pumping, accelerated sea-level rise, and other anthropic impacts, it is certain that the Mekong Delta will undergo large changes in the coming decades. These changes will threaten the very existence of the landform itself. The multiplicity of compounding drivers and lack of reliable data lead to large uncertainties in forecasting changes in the sediment budget of the Mekong Delta, its morphology, and the ecosystems and human livelihoods it supports. We compile information on key drivers affecting the sediment budget of the Mekong Delta and compare them to quantify the magnitude of effects from different drivers. We develop a set of likely scenarios for the future development of these drivers and quantify implications for the future of the Mekong Delta using a simplified model of the delta's geometry. If sediment supply to the delta is nearly completely cut off, as would be the case with full buildout of planned dams and current rates of sediment mining, and with continued groundwater pumping at current rates, our model forecasts that the delta will almost completely disappear by the end of this century due to increased rates of delta subsidence and rising sea levels. While local management cannot prevent global sea level rise, model results suggest that there are important management steps that could prolong the persistence of the delta ecosystem and the livelihoods it supports, including a reduction in ground water pumping and maintaining sediment connectivity between the basin and the delta.

  12. Simulated water-level responses, ground-water fluxes, and storage changes for recharge scenarios along Rillito Creek, Tucson, Arizona

    Science.gov (United States)

    Hoffmann, John P.; Leake, Stanley A.

    2005-01-01

    A local ground-water flow model is used to simulate four recharge scenarios along Rillito Creek in northern Tucson to evaluate mitigating effects on ground-water deficits and water-level declines in Tucson's Central Well Field. The local model, which derives boundary conditions from a basin-scale model, spans the 12-mile reach of Rillito Creek and extends 9 miles south into the Central Well Field. Recharge scenarios along Rillito Creek range from 5,000 to 60,000 acre-feet per year and are simulated to begin in 2005 and extend through 2225 to estimate long-term changes in ground-water level, ground-water storage, ground-water flux, and evapotranspiration. The base case for comparison of simulated water levels and flows, referred to as scenario A, uses a long-term recharge rate of 5,000 acre-feet per year to 2225. Scenario B, which increases the recharge along Rillito Creek by 9,500 acre-feet per year, has simulated water-level rises beneath Rillito Creek that range from about 53 feet to 86 feet. Water-level rises within the Central Well Field range from about 60 feet to 80 feet. More than half of these rises occur by 2050, and more than 95 percent occur by 2188. Scenario C, which increases the recharge along Rillito Creek by 16,700 acre-feet per year relative to scenario A, has simulated water-level rises beneath Rillito Creek that range from about 71 feet to 102 feet. Water-level rises within the Central Well Field range from about 80 feet to 95 feet. More than half of the rises occur by 2036, and more than 95 percent occur by 2100. Scenario D, which initially increases the recharge rate by about 55,000 acre-feet per year relative to scenario A, resulted in simulated water levels that rise to land surface along Rillito Creek. This rise in water level resulted in rejected recharge. As the water table continued to rise, the area of stream-channel surface intersected by the water table increased causing continual decline in the recharge rate until a long-term recharge

  13. Hierarchical organization versus self-organization

    OpenAIRE

    Busseniers, Evo

    2014-01-01

    In this paper we try to define the difference between hierarchical organization and self-organization. Organization is defined as a structure with a function. So we can define the difference between hierarchical organization and self-organization both on the structure as on the function. In the next two chapters these two definitions are given. For the structure we will use some existing definitions in graph theory, for the function we will use existing theory on (self-)organization. In the t...

  14. Self-organization through decoupling

    Directory of Open Access Journals (Sweden)

    Romar Correa

    2000-01-01

    Full Text Available In one line of research, the transition from Fordism to flexible specialisation is explained by the infeasibility of a mode of regulation that relied on central controls. According to another explanation, which we favour, the disintegration of vertically integrated production is unpredictable. The concept of self-organization is often recommended to model the transition from hierarchical organizational forms to flatter structures. Formally, a conditionally stable nonlinear system of differential equations is examined. In the first thesis, the characteristic roots with positive real parts play the role of ‘order’ parameters which can become unstable modes. The rest of the variables refer to stable modes. The strategy is to show that the stable modes can be expressed in terms of the unstable modes so that the former can be eliminated from the system. On the other hand, we provide a theorem showing that a coupled set of differential equations can become uncoupled and vice versa as an argument in favour of the second thesis. The path of evolution can turn both ways.

  15. Emergence, Self-Organization and Prime Numbers

    Science.gov (United States)

    Berezin, Alexander A.

    1998-04-01

    Pattern of primes (PP) is critical for dynamics of universal emergence, self-organization and complexity ascendance [1-3]. Due to gradual logarithmic dilution of primes (prime number theorem), PP gives only base envelop for above effects. More informative are full factorizational spectra (FS) of all intermediate composites. Tower exponential mappings like f(N) = 10(N)10 with (N) indicating N vertical arrows [4] lead to infinite fractal-like hierarchy of integer trails; say, FS of intervals between f(N) and f(N+1). This allows FAPP-infinite informational content of PP and FS be "used" as catalyzer of emergence dynamics. This is "Platonic pressure effect" (physical embodiments of PP and FS). Said effect may provide more direct picture for cosmogenesis than traditional quantum tunneling ("Big Bang") and/or inflationary scenarios. Furthermore, we can speculate that metrics of (Mega)universe at tower exponential scales becomes asymptotically Euclidean (multi or infinitely dimensional), due to unchangability of PP and FS. - [1] Arnold Arnold, "The Corrupted Sciences", Paladin (Harper Collins), 1992; [2] Peter Plichta, "God's Secret Formula: Deciphering the Riddle of the Universe and the Prime Number Code", Element, 1997; [3] Alexander Berezin, URAM Journal, 20, 72 (1997); [4] Donald E. Knuth, Science, 194, 1235, 17 Dec 1976. abstract.

  16. Self-Steered Self-Organization

    NARCIS (Netherlands)

    Keijzer, Fred; Tschacher, W.; Dauwalder, J.P.

    2003-01-01

    Self-organization has become a well-established phenomenon in physics. It is now also propagated as an important phenomenon in psychology. What is the difference between these two forms of self-organization? One important way in which these two forms are distinguished is by the additional presence

  17. Quantum control spectroscopy of vibrational modes: Comparison of control scenarios for ground and excited states in {beta}-carotene

    Energy Technology Data Exchange (ETDEWEB)

    Hauer, Juergen; Buckup, Tiago [Fachbereich Chemie, Physikalische Chemie, Philipps-Universitaet Marburg, Hans-Meerwein-Strasse, D-35043 Marburg (Germany); Motzkus, Marcus [Fachbereich Chemie, Physikalische Chemie, Philipps-Universitaet Marburg, Hans-Meerwein-Strasse, D-35043 Marburg (Germany)], E-mail: motzkus@staff.uni-marburg.de

    2008-06-23

    Quantum control spectroscopy (QCS) is used as a tool to study, address selectively and enhance vibrational wavepacket motion in large solvated molecules. By contrasting the application of Fourier-limited and phase-modulated excitation on different electronic states, the interplay between the controllability of vibrational coherence and electronic resonance is revealed. We contrast control on electronic ground and excited state by introducing an additional pump beam prior to a DFWM-sequence (Pump-DFWM). Via phase modulation of this initial pump pulse, coherent control is extended to structural evolution on the vibrationally hot ground state (hot-S{sub 0}) and lowest lying excited state (S{sub 1}) of {beta}-carotene. In an open loop setup, the control scenarios for these different electronic states are compared in their effectiveness and mechanism.

  18. Partial Ambiguity Resolution for Ground and Space-Based Applications in a GPS+Galileo scenario: A simulation study

    Science.gov (United States)

    Nardo, A.; Li, B.; Teunissen, P. J. G.

    2016-01-01

    Integer Ambiguity Resolution (IAR) is the key to fast and precise GNSS positioning. The proper diagnostic metric for successful IAR is provided by the ambiguity success rate being the probability of correct integer estimation. In this contribution we analyse the performance of different GPS+Galileo models in terms of number of epochs needed to reach a pre-determined success rate, for various ground and space-based applications. The simulation-based controlled model environment enables us to gain insight into the factors contributing to the ambiguity resolution strength of the different GPS+Galileo models. Different scenarios of modernized GPS+Galileo are studied, encompassing the long baseline ground case as well as the medium dynamics case (airplane) and the space-based Low Earth Orbiter (LEO) case. In our analyses of these models the capabilities of partial ambiguity resolution (PAR) are demonstrated and compared to the limitations of full ambiguity resolution (FAR). The results show that PAR is generally a more efficient way than FAR to reduce the time needed to achieve centimetre-level positioning precision. For long single baselines, PAR can achieve time reductions of fifty percent to achieve such precision levels, while for multiple baselines it even becomes more effective, reaching reductions up to eighty percent for four station networks. For a LEO, the rapidly changing observation geometry does not even allow FAR, while PAR is then still possible for both dual- and triple-frequency scenarios. With the triple-frequency GPS+Galileo model the availability of precise positioning improves by fifteen percent with respect to the dual-frequency scenario.

  19. An Empirically grounded Agent Based simulator for the Air Traffic Management in the SESAR scenario

    CERN Document Server

    Gurtner, Gérald; Ducci, Marco; Miccichè, Salvatore

    2016-01-01

    In this paper we present a simulator allowing to perform policy experiments relative to the air traffic management. Different SESAR solutions can be implemented in the model to see the reaction of the different stakeholders as well as other relevant metrics (delays, safety, etc). The model describes both the strategic phase associated to the planning of the flight trajectories and the tactical modifications occurring in the en-route phase. An implementation of the model is available as open-source and freely accessible by any user. More specifically, different procedures related to business trajectories and free-routing are tested and we illustrate the capabilities of the model on airspace implementing these concepts. After performing numerical simulations with the model, we show that in a free-routing scenario the controllers perform less operations although they are dispersed over a larger portion of the airspace. This can potentially increase the complexity of conflict detection and resolution for controll...

  20. Complex Systems and Self-organization Modelling

    CERN Document Server

    Bertelle, Cyrille; Kadri-Dahmani, Hakima

    2009-01-01

    The concern of this book is the use of emergent computing and self-organization modelling within various applications of complex systems. The authors focus their attention both on the innovative concepts and implementations in order to model self-organizations, but also on the relevant applicative domains in which they can be used efficiently. This book is the outcome of a workshop meeting within ESM 2006 (Eurosis), held in Toulouse, France in October 2006.

  1. Estimation of Seismic Ground Motions and Attendant Potential Human Fatalities from Scenario Earthquakes on the Chishan Fault in Southern Taiwan

    Directory of Open Access Journals (Sweden)

    Kun-Sung Liu

    2017-01-01

    Full Text Available The purpose of this study is to estimate maximum ground motions in southern Taiwan as well as to assess potential human fatalities from scenario earthquakes on the Chishan active faults in this area. The resultant Shake Map patterns of maximum ground motion in a case of Mw 7.2 show the areas of PGA above 400 gals are located in the northeastern, central and northern parts of southwestern Kaohsiung as well as the southern part of central Tainan, as shown in the regions inside the yellow lines in the corresponding figure. Comparing cities with similar distances located in Tainan, Kaohsiung, and Pingtung to the Chishan fault, the cities in Tainan area have relatively greater PGA and PGV, due to large site response factors in Tainan area. Furthermore, seismic hazards in terms of PGA and PGV in the vicinity of the Chishan fault are not completely dominated by the Chishan fault. The main reason is that some areas located in the vicinity of the Chishan fault are marked with low site response amplification values from 0.55 - 1.1 and 0.67 - 1.22 for PGA and PGV, respectively. Finally, from estimation of potential human fatalities from scenario earthquakes on the Chishan active fault, it is noted that potential fatalities increase rapidly in people above age 45. Total fatalities reach a high peak in age groups of 55 - 64. Another to pay special attention is Kaohsiung City has more than 540 thousand households whose residences over 50 years old. In light of the results of this study, I urge both the municipal and central governments to take effective seismic hazard mitigation measures in the highly urbanized areas with a large number of old buildings in southern Taiwan.

  2. Quantifying self-organization in fusion plasmas

    Science.gov (United States)

    Rajković, M.; Milovanović, M.; Škorić, M. M.

    2017-05-01

    A multifaceted framework for understanding self-organization in fusion plasma dynamics is presented which concurrently manages several important issues related to the nonlinear and multiscale phenomena involved, namely,(1) it chooses the optimal template wavelet for the analysis of temporal or spatio-temporal plasma dynamics, (2) it detects parameter values at which bifurcations occur, (3) it quantifies complexity and self-organization, (4) it enables short-term prediction of nonlinear dynamics, and (5) it extracts coherent structures in turbulence by separating them from the incoherent component. The first two aspects including the detection of changes in the dynamics of a nonlinear system are illustrated by analyzing Stimulated Raman Scattering in a bounded, weakly dissipative plasma. Self-organization in the fusion plasma is quantitatively analyzed based on the numerical simulations of the Gyrokinetic-Vlasov (GKV) model of plasma dynamics. The parameters for the standard and inward shifted magnetic configurations, relevant for the Large Helical Device, were used in order to quantitatively compare self-organization and complexity in the two configurations. Finally, self-organization is analyzed for three different confinement regimes of the MAST device.

  3. Self-Organized Topological State with Majorana Fermions

    Science.gov (United States)

    Vazifeh, M. M.; Franz, M.

    2013-11-01

    Most physical systems known to date tend to resist entering the topological phase and must be fine-tuned to reach that phase. Here, we introduce a system in which a key dynamical parameter adjusts itself in response to the changing external conditions so that the ground state naturally favors the topological phase. The system consists of a quantum wire formed of individual magnetic atoms placed on the surface of an ordinary s-wave superconductor. It realizes the Kitaev paradigm of topological superconductivity when the wave vector characterizing the emergent spin helix dynamically self-tunes to support the topological phase. We call this phenomenon a self-organized topological state.

  4. Protein Folding and Self-Organized Criticality

    Science.gov (United States)

    Bajracharya, Arun; Murray, Joelle

    Proteins are known to fold into tertiary structures that determine their functionality in living organisms. However, the complex dynamics of protein folding and the way they consistently fold into the same structures is not fully understood. Self-organized criticality (SOC) has provided a framework for understanding complex systems in various systems (earthquakes, forest fires, financial markets, and epidemics) through scale invariance and the associated power law behavior. In this research, we use a simple hydrophobic-polar lattice-bound computational model to investigate self-organized criticality as a possible mechanism for generating complexity in protein folding.

  5. Self-organizing sensing and actuation for automatic control

    Science.gov (United States)

    Cheng, George Shu-Xing

    2017-07-04

    A Self-Organizing Process Control Architecture is introduced with a Sensing Layer, Control Layer, Actuation Layer, Process Layer, as well as Self-Organizing Sensors (SOS) and Self-Organizing Actuators (SOA). A Self-Organizing Sensor for a process variable with one or multiple input variables is disclosed. An artificial neural network (ANN) based dynamic modeling mechanism as part of the Self-Organizing Sensor is described. As a case example, a Self-Organizing Soft-Sensor for CFB Boiler Bed Height is presented. Also provided is a method to develop a Self-Organizing Sensor.

  6. Self-organization of linear nanochannel networks

    NARCIS (Netherlands)

    Annabattula, R. K.; Veenstra, J. M.; Mei, Y. F.; Schmidt, O. G.; Onck, P. R.

    2010-01-01

    A theoretical study has been conducted to explore the mechanics of self-organizing channel networks with dimensions in the submicron range and nanorange. The channels form by the partial release and bond back of prestressed thin films. In the release phase, the film spontaneously buckles into

  7. Self-organized criticality in fragmenting

    DEFF Research Database (Denmark)

    Oddershede, L.; Dimon, P.; Bohr, J.

    1993-01-01

    The measured mass distributions of fragments from 26 fractured objects of gypsum, soap, stearic paraffin, and potato show evidence of obeying scaling laws; this suggests the possibility of self-organized criticality in fragmenting. The probability of finding a fragment scales inversely to a power...

  8. Self-organized critical pinball machine

    DEFF Research Database (Denmark)

    Flyvbjerg, H.

    2004-01-01

    The nature of self-organized criticality (SOC) is pin-pointed with a simple mechanical model: a pinball machine. Its phase space is fully parameterized by two integer variables, one describing the state of an on-going game, the other describing the state of the machine. This is the simplest possi...

  9. The Self-Organization of Human Interaction

    DEFF Research Database (Denmark)

    Dale, Rick; Fusaroli, Riccardo; Duran, Nicholas

    2013-01-01

    , processes, and contexts can be integrated into a broader account of human interaction. By introducing and utilizing basic concepts of self-organization and synergy, we review empirical work that shows how human interaction is flexible and adaptive and structures itself incrementally during unfolding...

  10. Information Driven Ecohydrologic Self-Organization

    Directory of Open Access Journals (Sweden)

    Benjamin L. Ruddell

    2010-09-01

    Full Text Available Variability plays an important role in the self-organized interaction between vegetation and its environment, yet the principles that characterize the role of the variability in these interactions remain elusive. To address this problem, we study the dependence between a number of variables measured at flux towers by quantifying the information flow between the different variables along with the associated time lag. By examining this network of feedback loops for seven ecosystems in different climate regions, we find that: (1 the feedback tends to maximize information production in the entire system, and the latter increases with increasing variability within the whole system; and (2 variables that participate in feedback exhibit moderated variability. Self-organization arises as a tradeoff where the ability of the total system to maximize information production through feedback is limited by moderate variability of the participating variables. This relationship between variability and information production leads to the emergence of ordered organization.

  11. Hierarchical Self-organization of Complex Systems

    Institute of Scientific and Technical Information of China (English)

    CHAI Li-he; WEN Dong-sheng

    2004-01-01

    Researches on organization and structure in complex systems are academic and industrial fronts in modern sciences. Though many theories are tentatively proposed to analyze complex systems, we still lack a rigorous theory on them. Complex systems possess various degrees of freedom, which means that they should exhibit all kinds of structures. However, complex systems often show similar patterns and structures. Then the question arises why such similar structures appear in all kinds of complex systems. The paper outlines a theory on freedom degree compression and the existence of hierarchical self-organization for all complex systems is found. It is freedom degree compression and hierarchical self-organization that are responsible for the existence of these similar patterns or structures observed in the complex systems.

  12. Self-Organization and Associative Memory

    Science.gov (United States)

    Kohonen, Teuvo

    This monograph gives a tutorial treatment of new approaches to self-organization, adaptation, learning and memory. It is based on recent research results, both mathematical and computer simulations, and lends itself to graduate and postgraduate courses in the natural sciences. The book presents new formalisms of pattern processing: orthogonal projectors, optimal associative mappings, novelty filters, subspace methods, feature-sensitive units, and self-organization of topological maps, with all their computable algorithms. The main objective is to provide an understanding of the properties of information representations from a general point of view and of their use in pattern information processing, as well as an understanding of many functions of the brain. In the second edition two new chapters on neural computing and optical associative memories have been added.

  13. SELF-ORGANIZED CRITICALITY AND CELLULAR AUTOMATA

    Energy Technology Data Exchange (ETDEWEB)

    CREUTZ,M.

    2007-01-01

    Cellular automata provide a fascinating class of dynamical systems based on very simple rules of evolution yet capable of displaying highly complex behavior. These include simplified models for many phenomena seen in nature. Among other things, they provide insight into self-organized criticality, wherein dissipative systems naturally drive themselves to a critical state with important phenomena occurring over a wide range of length and the scales. This article begins with an overview of self-organized criticality. This is followed by a discussion of a few examples of simple cellular automaton systems, some of which may exhibit critical behavior. Finally, some of the fascinating exact mathematical properties of the Bak-Tang-Wiesenfeld sand-pile model [1] are discussed.

  14. Tactical games & behavioral self-organization

    OpenAIRE

    Juriev, Denis V.

    1999-01-01

    The interactive game theoretical approach to tactics and behavioral self-organization is developed. Though it uses the interactive game theoretical formalization of dialogues as psycholinguistic phenomena, the crucial role is played by the essentially new concept of a tactical game. Applications to the perception processes and related subjects (memory, recollection, image understanding, imagination) are discussed together with relations to the computer vision and pattern recognition (the dyna...

  15. Self-Steered Self-Organization

    Science.gov (United States)

    Keijzer, Fred

    Self-organization has become a well-established phenomenon in physics, now also propagated as an important phenomenon in the case of psychology. This addition to ordinary self-organization may be called self-steering (through internal control parameters). Self-steering is conceptualized in a biological context (DNA, neurocognition of the visuomotor system) and in psychology. The major conceptual problem is to avoid that self-steering turns into the invocation of an unexplained intentional force that may fall victim to the problems related to regular representation-based cognitive science. Kelso's understanding of intention is discussed and criticized in this respect. It is proposed that the steering factors may be like representations, but have no meaning or existence apart from the self-organizing processes that they help to regulate. In this respect there remains a major difference with traditional representational theories. Compared to intentionality, self-steering is a more basic concept that applies to much lower levels of organization as well.

  16. Concept and Feasibility Study of Self-Organized Electrochemical Devices

    National Research Council Canada - National Science Library

    Moorehead, William

    2002-01-01

    .... In this work, using attractive and repulsive London-van der Waals forces, a self-organized, interpenetrating, separator-free rechargeable lithium ion battery called a self-organized battery system (SBS) is proposed...

  17. Self-Organization of Blood Pressure Regulation: Experimental Evidence

    OpenAIRE

    Jacques-Olivier eFortrat; Thibaud eLevrard; sandrine ecourcinous; jacques evictor

    2016-01-01

    Blood pressure regulation is a prime example of homeostatic regulation. However, some characteristics of the cardiovascular system better match a non-linear self-organized system than a homeostatic one. To determine whether blood pressure regulation is self-organized, we repeated the seminal demonstration of self-organized control of movement, but applied it to the cardiovascular system. We looked for two distinctive features peculiar to self-organization: non-equilibrium phase transitions an...

  18. Self-Organization Activities of College Students: Challenges and Opportunities

    Science.gov (United States)

    Shmurygina, Natalia; Bazhenova, Natalia; Bazhenov, Ruslan; Nikolaeva, Natalia; Tcytcarev, Andrey

    2016-01-01

    The article provides the analysis of self-organization activities of college students related to their participation in youth associations activities. The purpose of research is to disclose a degree of students' activities demonstration based on self-organization processes, assessment of existing self-organization practices of the youth,…

  19. Robin Hood as self-organized criticality

    Science.gov (United States)

    Zaitsev, S. I.

    1992-11-01

    It is shown that a wide class of physical processes named low-temperature creep (or Robin Hood systems) has to demonstrate self-organized criticality. At least “real” and “toy” models (1D and 2D) demonstrate long range (restricted by the model size only) spatial correlation in Monte Carlo simulation. The models can be used for investigation of such phenomena as dislocation glide, movement of flux in superconductors, movement of domain walls in magnetics, grain boundaries in polycrystals, plastic deformation and so on.

  20. Self-organization in semiconductor physics.

    Science.gov (United States)

    Parisi, J

    1997-01-01

    Non-equilibrium dissipative systems from semiconductor physics have prevailed as a paradigmatic testing field for complex non-linear dynamics during the last decade. Especially, low-temperature impact ionization breakdown in extrinsic germanium crystals displays a variety of interesting nonlinear phenomena, such as spontaneous oscillations and filamentary patterns of the current flow. We report on recent experimental results concerning the interplay between spatial and temporal degrees of freedom during the onset of semiconductor breakdown. Quantitative evaluation of characteristic scaling properties supports the applicability of the model of self-organized criticality.

  1. Non-Equilibrium Nanoscale Self-Organization

    Energy Technology Data Exchange (ETDEWEB)

    Aziz, Michael J

    2006-03-09

    Self-organized one- and two-dimensional arrays of nanoscale surface features ("ripples" and "dots") sometimes form spontaneously on initially flat surfaces eroded by a directed ion beam in a process called "sputter patterning". Experiments on this sputter patterning process with focused and unfocused ion beams, combined with theoretical advances, have been responsible for a number of scientific advances. Particularly noteworthy are (i) the discovery of propagative, rather than dissipative, behavior under some ion erosion conditions, permitting a pattern to be fabricated at a large length scale and propagated over large distances while maintaining, or even sharpening, the sharpest features; (ii) the first demonstration of guided self-organization of sputter patterns, along with the observation that defect density is minimized when the spacing between boundaries is near an integer times the natural spatial period; and (iii) the discovery of metastability of smooth surfaces, which contradicts the nearly universally accepted linear stability theory that predicts that any surface is linearly unstable to sinusoidal perturbations of some wave vector.

  2. Scenario-Based Seismic Risk Analysis: An Engineering Approach to the Development of Source and Site-Specific Ground Motion Time Histories in Areas of Low Seismicity

    Science.gov (United States)

    Klügel, Jens-Uwe; Attinger, Richard

    2011-01-01

    Modern engineering design methods require ground motion time histories as input for non-linear dynamic structural analysis. Non-linear dynamic methods of analysis are increasingly applied in the context of probabilistic risk assessments and for cost-effective design of critical infrastructures. In current engineering practice artificial time histories matching deterministic design spectra or probabilistic uniform hazard spectra are most frequently used for engineering analysis. The intermediate step of generation of response spectra can lead to a biased estimate of the potential damage from earthquakes because of insufficient consideration of the true energy content and strong motion duration of earthquakes. Thus, assessment of seismic risk may seem unrealistic. An engineering approach to the development of three-component ground motion time histories has been established which enables consideration of the typical characteristics of seismic sources, regional ground motion attenuation, and the main geotechnical characteristics of the target site. Therefore, the approach is suitable for use in scenario-based risk analysis a larger number of time histories are required for representation of the seismic hazard. Near-field effects are implemented in the stochastic source model using engineering approximations. The approach is suggested for use in areas of low seismicity where ground motion records of larger earthquakes are not available. Uncertainty analysis indicates that ground motions generated by individual earthquakes are well constrained and that the usual lognormal model is not the best choice for predicting the upper tail of the distribution of the ground motions.

  3. Feedback, Lineages and Self-Organizing Morphogenesis.

    Directory of Open Access Journals (Sweden)

    Sameeran Kunche

    2016-03-01

    Full Text Available Feedback regulation of cell lineage progression plays an important role in tissue size homeostasis, but whether such feedback also plays an important role in tissue morphogenesis has yet to be explored. Here we use mathematical modeling to show that a particular feedback architecture in which both positive and negative diffusible signals act on stem and/or progenitor cells leads to the appearance of bistable or bi-modal growth behaviors, ultrasensitivity to external growth cues, local growth-driven budding, self-sustaining elongation, and the triggering of self-organization in the form of lamellar fingers. Such behaviors arise not through regulation of cell cycle speeds, but through the control of stem or progenitor self-renewal. Even though the spatial patterns that arise in this setting are the result of interactions between diffusible factors with antagonistic effects, morphogenesis is not the consequence of Turing-type instabilities.

  4. Self-organized criticality in a nutshell.

    Science.gov (United States)

    Nagler, J; Hauert, C; Schuster, H G

    1999-09-01

    In order to gain insight into the nature of self-organized criticality (SOC), we present a minimal model exhibiting this phenomenon. In this analytically solvable model, the state of the system is fully described by a single-integer variable. The system organizes in its critical state without external tuning. We derive analytically the probability distribution of durations of disturbances propagating through the system. As required by SOC, this distribution is scale invariant and follows a power law over several orders of magnitude. Our solution also reproduces the exponential tail of the distribution due to finite size effects. Moreover, we show that large avalanches are suppressed when stabilizing the system in its critical state. Interestingly, avalanches are affected in a similar way when driving the system away from the critical state. With this model, we have reduced SOC dynamics to a leveling process as described by Ehrenfest's famous flea model.

  5. Control of self-organizing nonlinear systems

    CERN Document Server

    Klapp, Sabine; Hövel, Philipp

    2016-01-01

    The book summarizes the state-of-the-art of research on control of self-organizing nonlinear systems with contributions from leading international experts in the field. The first focus concerns recent methodological developments including control of networks and of noisy and time-delayed systems. As a second focus, the book features emerging concepts of application including control of quantum systems, soft condensed matter, and biological systems. Special topics reflecting the active research in the field are the analysis and control of chimera states in classical networks and in quantum systems, the mathematical treatment of multiscale systems, the control of colloidal and quantum transport, the control of epidemics and of neural network dynamics.

  6. Feedback, Lineages and Self-Organizing Morphogenesis

    Science.gov (United States)

    Calof, Anne L.; Lowengrub, John S.; Lander, Arthur D.

    2016-01-01

    Feedback regulation of cell lineage progression plays an important role in tissue size homeostasis, but whether such feedback also plays an important role in tissue morphogenesis has yet to be explored. Here we use mathematical modeling to show that a particular feedback architecture in which both positive and negative diffusible signals act on stem and/or progenitor cells leads to the appearance of bistable or bi-modal growth behaviors, ultrasensitivity to external growth cues, local growth-driven budding, self-sustaining elongation, and the triggering of self-organization in the form of lamellar fingers. Such behaviors arise not through regulation of cell cycle speeds, but through the control of stem or progenitor self-renewal. Even though the spatial patterns that arise in this setting are the result of interactions between diffusible factors with antagonistic effects, morphogenesis is not the consequence of Turing-type instabilities. PMID:26989903

  7. Self-organized criticality and urban development

    Directory of Open Access Journals (Sweden)

    Michael Batty

    1999-01-01

    Full Text Available Urban society is undergoing as profound a spatial transformation as that associated with the emergence of the industrial city two centuries ago. To describe and measure this transition, we introduce a new theory based on the concept that large-scale, complex systems composed of many interacting elements, show a surprising degree of resilience to change, holding themselves at critical levels for long periods until conditions emerge which move the system, often abruptly, to a new threshold. This theory is called ‘self-organized criticality’; it is consistent with systems in which global patterns emerge from local action which is the hallmark of self-organization, and it is consistent with developments in system dynamics and their morphology which find expression in fractal geometry and weak chaos theory. We illustrate the theory using a unique space–time series of urban development for Buffalo, Western New York, which contains the locations of over one quarter of a million sites coded by their year of construction and dating back to 1773, some 60 years before the city began to develop. We measure the emergence and growth of the city using urban density functions from which measures of fractal dimension are used to construct growth paths of the way the city has grown to fill its region. These phase portraits suggest the existence of transitions between the frontier, the settled agricultural region, the centralized industrial city and the decentralized postindustrial city, and our analysis reveals that Buffalo has maintained itself at a critical threshold since the emergence of the automobile city some 70 years ago. Our implied speculation is: how long will this kind of urban form be maintained in the face of seemingly unstoppable technological change?

  8. Self-organization in the development of plant spatial patterns

    OpenAIRE

    Cartenì, Fabrizio

    2014-01-01

    The study of self-organization is a relatively new field that received great attention in the last decades related to the study of complex systems. In particular, self-organizing properties of some systems are particularly important in the development of spatial patterns, and their analysis could lead to interesting insights into their functioning. Self-organization is a process in which pattern at the global level of a system emerges solely from the interactions among the lower-level compone...

  9. Parameters of self-organization in Hydra aggregates

    OpenAIRE

    Technau, Ulrich; Cramer von Laue, Christoph; Rentzsch, Fabian; Luft, Susanne; Hobmayer, Bert; Bode, Hans R.; Holstein, Thomas W.

    2000-01-01

    Self-organization has been demonstrated in a variety of systems ranging from chemical-molecular to ecosystem levels, and evidence is accumulating that it is also fundamental for animal development. Yet, self-organization can be approached experimentally in only a few animal systems. Cells isolated from the simple metazoan Hydra can aggregate and form a complete animal by self-organization. By using this experimental system, we found that clusters of 5–15 epithelial ...

  10. ROBUSTNESS OF GUIDED SELF-ORGANIZATION AGAINST SENSORIMOTOR DISRUPTIONS

    OpenAIRE

    GEORG MARTIUS

    2013-01-01

    Self-organizing processes are crucial for the development of living beings. Practical applications in robots may benefit from the self-organization of behavior, e.g., to increase fault tolerance and enhance flexibility, provided that external goals can also be achieved. We present results on the guidance of self-organizing control by visual target stimuli and show a remarkable robustness to sensorimotor disruptions. In a proof of concept study an autonomous wheeled robot is learning an object...

  11. Physics-Based Long-Period Ground Motion Scenarios in and Around the Po Plain Sedimentary Basin (Northern Italy)

    Science.gov (United States)

    Molinari, I.; Morelli, A.; Casarotti, E.

    2014-12-01

    Unexpected large and prolonged shaking (> 80s) associated with long-period ground motion has been observed inside the Po Plain sedimentary basin (Northern Italy) during the two M~6, May 20-29, 2012, earthquakes. Long-period ground motion impacts on the seismic response of taller structures. It is hence important to understand the characteristics of long-period ground motion associated with the 3D structure and finite fault properties, in particular in those regions with deep sedimentary basins and a complex geological context. We implement a recent high resolution model of the Po basin (MAMBo), derived from geological constraints, in spectral-element code SPECFEM3D_cartesian (Peter et al., 2012). The simulations are numerically accurate for periods of 2 sec and longer, and incorporate complex 3D basin structure and topography as well as the spatial and temporal heterogeneity of source rupture. The response of our basin model has been evaluated for several instrumental earthquakes. Synthetics seismograms reproduce well amplitude and long duration, as well as envelope and coda, observed in paths that travel through sediments. We also evaluate ground motion produced by plausible earthquakes inferred from historical data, such as the Modena (1501) and Verona (1117) events that caused well-documented strong effects in a unusually wide areas with lengths of hundreds of kilometers. We test different representations of the seismic source, from point source to finite sources with different rupture histories, evaluating the impact on shaking amplitude. We compare our results with damage maps (when available) and with the GMPEs currently adopted for this area, evaluating the effects of finite fault and 3D propagation on ground shaking. We show that deterministic ground motion calculation can indeed provide information to be actively used to mitigate the effects of destructive earthquakes on critical infrastructures.

  12. Self-organized Segregation on the Grid

    Science.gov (United States)

    Omidvar, Hamed; Franceschetti, Massimo

    2017-12-01

    We consider an agent-based model with exponentially distributed waiting times in which two types of agents interact locally over a graph, and based on this interaction and on the value of a common intolerance threshold τ , decide whether to change their types. This is equivalent to a zero-temperature ising model with Glauber dynamics, an asynchronous cellular automaton with extended Moore neighborhoods, or a Schelling model of self-organized segregation in an open system, and has applications in the analysis of social and biological networks, and spin glasses systems. Some rigorous results were recently obtained in the theoretical computer science literature, and this work provides several extensions. We enlarge the intolerance interval leading to the expected formation of large segregated regions of agents of a single type from the known size ɛ >0 to size ≈ 0.134 . Namely, we show that for 0.433behavior is reminiscent of supercritical percolation, where small clusters of empty sites can be observed within any sufficiently large region of the occupied percolation cluster. The exponential bounds that we provide also imply that complete segregation, where agents of a single type cover the whole grid, does not occur with high probability for p=1/2 and the range of intolerance considered.

  13. LSOT: A Lightweight Self-Organized Trust Model in VANETs

    Directory of Open Access Journals (Sweden)

    Zhiquan Liu

    2016-01-01

    Full Text Available With the advances in automobile industry and wireless communication technology, Vehicular Ad hoc Networks (VANETs have attracted the attention of a large number of researchers. Trust management plays an important role in VANETs. However, it is still at the preliminary stage and the existing trust models cannot entirely conform to the characteristics of VANETs. This work proposes a novel Lightweight Self-Organized Trust (LSOT model which contains trust certificate-based and recommendation-based trust evaluations. Both the supernodes and trusted third parties are not needed in our model. In addition, we comprehensively consider three factor weights to ease the collusion attack in trust certificate-based trust evaluation, and we utilize the testing interaction method to build and maintain the trust network and propose a maximum local trust (MLT algorithm to identify trustworthy recommenders in recommendation-based trust evaluation. Furthermore, a fully distributed VANET scenario is deployed based on the famous Advogato dataset and a series of simulations and analysis are conducted. The results illustrate that our LSOT model significantly outperforms the excellent experience-based trust (EBT and Lightweight Cross-domain Trust (LCT models in terms of evaluation performance and robustness against the collusion attack.

  14. Intrusion Detection System using Self Organizing Map: A Survey

    Directory of Open Access Journals (Sweden)

    Kruti Choksi

    2014-12-01

    Full Text Available Due to usage of computer every field, Network Security is the major concerned in today’s scenario. Every year the number of users and speed of network is increasing, along with it online fraud or security threats are also increasing. Every day a new attack is generated to harm the system or network. It is necessary to protect the system or networks from various threats by using Intrusion Detection System which can detect “known” as well as “unknown” attack and generate alerts if any unusual behavior in the traffic. There are various approaches for IDS, but in this paper, survey is focused on IDS using Self Organizing Map. SOM is unsupervised, fast conversion and automatic clustering algorithm which is able to handle novelty detection. The main objective of the survey is to find and address the current challenges of SOM. Our survey shows that the existing IDS based on SOM have poor detection rate for U2R and R2L attacks. To improve it, proper normalization technique should be used. During the survey we also found that HSOM and GHSOM are advance model of SOM which have their own unique feature for better performance of IDS. GHSOM is efficient due to its low computation time. This survey is beneficial to design and develop efficient SOM based IDS having less computation time and better detection rate.

  15. Physico-chemical analysis of ground water samples of coastal areas of south Chennai in the post-Tsunami scenario.

    Science.gov (United States)

    Rajendran, A; Mansiya, C

    2015-11-01

    The study of changes in ground water quality on the east coast of chennai due to the December 26, 2004 tsunami and other subsequent disturbances is a matter of great concern. The post-Tsunami has caused considerable plant, animal, material and ecological changes in the entire stretch of chennai coastal area. Being very close to sea and frequently subjected to coastal erosion, water quality has been a concern in this coastal strip, and especially after the recent tsunami this strip seems to be more vulnerable. In the present investigation, ten ground water samples were collected from various parts of south chennai coastal area. Physico-chemical parameters such as pH, temperature, Biochemical oxygen demand (BOD), Dissolved oxygen (DO), total solids; turbidity and fecal coliform were analyzed. The overall Water quality index (WQI) values for all the samples were found to be in the range of 68.81-74.38 which reveals a fact that the quality of all the samples is only medium to good and could be used for drinking and other domestic uses only after proper treatment. The long term adverse impacts of tsunami on ground water quality of coastal areas and the relationships that exist and among various parameters are carefully analyzed. Local residents and corporation authorities have been made aware of the quality of their drinking water and the methods to conserve the water bodies. Copyright © 2015 Elsevier Inc. All rights reserved.

  16. Self-organizing maps: A tool to ascertain taxonomic relatedness ...

    Indian Academy of Sciences (India)

    MADHU

    Self-organizing maps: A tool to ascertain taxonomic relatedness based on features derived from 16S rDNA sequence617 ... dimensional scaling; PCA, principal component analysis; PE, processing element; SOM, self-organizing map; VQ, vector quantization ...... absolute consensus of methods for three isolates (No. 2.

  17. Self-organization and complexity in historical landscape patterns

    Science.gov (United States)

    Janine Bolliger; Julien C. Sprott; David J. Mladenoff

    2003-01-01

    Self-organization describes the evolution process of complex structures where systems emerge spontaneously, driven internally by variations of the system itself. Self-organization to the critical state is manifested by scale-free behavior across many orders of magnitude (Bak et al. 1987, Bak 1996, Sole et a1. 1999). Spatial scale-free behavior implies fractal...

  18. Derivation of the Cramér-Rao Bound in the GNSS-Reflectometry Context for Static, Ground-Based Receivers in Scenarios with Coherent Reflection.

    Science.gov (United States)

    Ribot, Miguel Angel; Botteron, Cyril; Farine, Pierre-André

    2016-12-05

    The use of the reflected Global Navigation Satellite Systems' (GNSS) signals in Earth observation applications, referred to as GNSS reflectometry (GNSS-R), has been already studied for more than two decades. However, the estimation precision that can be achieved by GNSS-R sensors in some particular scenarios is still not fully understood yet. In an effort to partially fill this gap, in this paper, we compute the Cramér-Rao bound (CRB) for the specific case of static ground-based GNSS-R receivers and scenarios where the coherent component of the reflected signal is dominant. We compute the CRB for GNSS signals with different modulations, GPS L1 C/A and GPS L5 I/Q, which use binary phase-shift keying, and Galileo E1 B/C and E5, using the binary offset carrier. The CRB for these signals is evaluated as a function of the receiver bandwidth and different scenario parameters, such as the height of the receiver or the properties of the reflection surface. The CRB computation presented considers observation times of up to several tens of seconds, in which the satellite elevation angle observed changes significantly. Finally, the results obtained show the theoretical benefit of using modern GNSS signals with GNSS-R techniques using long observation times, such as the interference pattern technique.

  19. Basis for the development of a scenario for ground water risk assessment of plant protection products to banana crop in the frame work of regulation 1107/2009

    Science.gov (United States)

    Alonso-Prados, Elena; Fernández-Getino, Ana Patricia; Alonso-Prados, Jose Luis

    2014-05-01

    The risk assessment to ground water of pesticides and their main metabolites is a data requirement under regulation 1107/2009, concerning the placing of plant protection products on the market. Predicted environmental concentrations (PEC) are calculated according to the recommendations of Forum for the Co-ordination of pesticide fate models and Their Use (FOCUS). The FOCUS groundwater working group developed scenarios for the main crops in European Union. However there are several crops which grow under specific agro-environmental conditions not covered by these scenarios and it is frequent to use the defined scenarios as surrogates. This practice adds an uncertainty factor in the risk assessment. One example is represented by banana crop which in Europe is limited to sub-tropical environmental conditions and with specific agronomic practices. The Canary Islands concentrates the higher production of banana in the European Union characterized by volcanic soils. Banana is located at low altitudes where soils have been eroded or degraded, and it is a common practice to transport soil materials from the high-mid altitudes to the low lands for cultivation. These cultivation plots are locally named "sorribas". These volcanic soils, classified as Andosols according to the FAO classification, have special physico-chemical properties due to noncrystalline materials and layer silicates. The good stability of these soils and their high permeability to water make them relatively resistant to water erosion. Physical properties of volcanic clayey soils are strongly affected by allophone and Fe and Al oxyhidroxides. The rapid weathering of porous volcanic material results in accumulation of stable organo-mineral complexes and short-range-order mineral such as allophane, imogolite and ferrihydrite. These components induce strong aggregation that partly favors properties such as: reduced swelling, increased aggregate stability of clay minerals, high soil water retention capacity

  20. Designed self-organization for molecular optoelectronics

    Science.gov (United States)

    Norton, Michael; Neff, David; Towler, Ian; Day, Scott; Grambos, Zachary; Shremshock, Mikala; Butts, Heather; Meadows, Christiaan; Samiso, Yuko; Cao, Huan; Rahman, Mashiur

    2006-05-01

    The convergence of terahertz spectroscopy and single molecule experimentation offer significant promise of enhancement in sensitivity and selectivity in molecular recognition, identification and quantitation germane to military and security applications. This presentation reports the results of experiments which address fundamental barriers to the integration of large, patterned bio-compatible molecular opto-electronic systems with silicon based microelectronic systems. The central thrust of this approach is sequential epitaxy on surface bound single stranded DNA one-dimensional substrates. The challenge of producing highly structured macromolecular substrates, which are necessary in order to implement molecular nanolithography, has been addressed by combining "designer" synthetic DNA with biosynthetically derived plasmid components. By design, these one dimensional templates are composed of domains which contain sites which are recognized, and therefore addressable by either complementary DNA sequences and/or selected enzymes. Such design is necessary in order to access the nominal 2 nm linewidth potential resolution of nanolithography on these one-dimensional substrates. The recognition and binding properties of DNA ensure that the lithographic process is intrinsically self-organizing, and therefore self-aligning, a necessity for assembly processes at the requisite resolution. Another requirement of this molecular epitaxy approach is that the substrate must be immobilized. The challenge of robust surface immobilization is being addressed via the production of the equivalent of molecular tube sockets. In this application, multi-valent core-shell fluorescent quantum dots provide a mechanism to prepare surface attachment sites with a pre-determined 1:1 attachment site : substrate (DNA) molecule ratio.

  1. Self-organized stationary states of tokamaks

    Science.gov (United States)

    Jardin, Stephen

    2015-11-01

    We report here on a nonlinear mechanism that forms and maintains a self-organized stationary (sawtooth free) state in tokamaks. This process was discovered by way of extensive long-time simulations using the M3D-C1 3D extended MHD code in which new physics diagnostics have been added. It is well known that most high-performance modes of tokamak operation undergo ``sawtooth'' cycles, in which the peaking of the toroidal current density triggers a periodic core instability which redistributes the current density. However, certain modes of operation are known, such as the ``hybrid'' mode in DIII-D, ASDEX-U, JT-60U and JET, and the long-lived modes in NSTX and MAST, which do not experience this cycle of instability. Empirically, it is observed that these modes maintain a non-axisymmetric equilibrium which somehow limits the peaking of the toroidal current density. The physical mechanism responsible for this has not previously been understood, but is often referred to as ``flux-pumping,'' in which poloidal flux is redistributed in order to maintain q0 >1. In this talk, we show that in long-time simulations of inductively driven plasmas, a steady-state magnetic equilibrium may be obtained in which the condition q0 >1 is maintained by a dynamo driven by a stationary marginal core interchange mode. This interchange mode, unstable because of the pressure gradient in the ultra-low shear region in the center region, causes a (1,1) perturbation in both the electrostatic potential and the magnetic field, which nonlinearly cause a (0,0) component in the loop voltage that acts to sustain the configuration. This hybrid mode may be a preferred mode of operation for ITER. We present parameter scans that indicate when this sawtooth-free operation can be expected.

  2. Self-organization criticality of debris flow rheology

    Institute of Scientific and Technical Information of China (English)

    WANG Yuyi; JAN Chyandeng; CHEN Xiaoqing; HAN Wenliang

    2003-01-01

    Based on the viewpoint of stress and strain self-organization criticality of debris flow mass, this paper probes into inter-nonlinear action between different factors in the thixotropic liquefaction system of loose clastic soil onslope to make clastic soil in slope develop naturally towards critical stress status, and slope debris flow finally occurs under trigging by rainstorm. Also according to observation and analysis of self-organization criticality of sedimentrunoff system of viscous debris flow surges in ravines and power relation between magnitude and frequency of debris flows, this paper expounds similarity of the self-organized structure of debris flow mass. The self-organized critical system is a weak chaotic system. Debris flow occurrences can be predicted accordingly by means of observation at certain time scale and analysis of self-organization criticality of magnitude, frequency and time interval of debris flows.

  3. Ground Motion Prediction for M7+ scenarios on the San Andreas Fault using the Virtual Earthquake Approach

    Science.gov (United States)

    Denolle, M.; Dunham, E. M.; Prieto, G.; Beroza, G. C.

    2013-05-01

    There is no clearer example of the increase in hazard due to prolonged and amplified shaking in sedimentary, than the case of Mexico City in the 1985 Michoacan earthquake. It is critically important to identify what other cities might be susceptible to similar basin amplification effects. Physics-based simulations in 3D crustal structure can be used to model and anticipate those effects, but they rely on our knowledge of the complexity of the medium. We propose a parallel approach to validate ground motion simulations using the ambient seismic field. We compute the Earth's impulse response combining the ambient seismic field and coda-wave enforcing causality and symmetry constraints. We correct the surface impulse responses to account for the source depth, mechanism and duration using a 1D approximation of the local surface-wave excitation. We call the new responses virtual earthquakes. We validate the ground motion predicted from the virtual earthquakes against moderate earthquakes in southern California. We then combine temporary seismic stations on the southern San Andreas Fault and extend the point source approximation of the Virtual Earthquake Approach to model finite kinematic ruptures. We confirm the coupling between source directivity and amplification in downtown Los Angeles seen in simulations.

  4. Intergroup Joint Scheduling for Mitigating Asymmetric Uplink Interference in Self-Organizing Virtual Cell Networks

    Directory of Open Access Journals (Sweden)

    Ohyun Jo

    2016-01-01

    Full Text Available We introduce the concept of self-organizing VCN (virtual cell network. Here self-organizing VCN topology for efficient operation will be configured, and the functions of the each element will be defined. Also, the operation scenarios of VCN will be described. Then, we propose an efficient scheduling algorithm that considers the asymmetry of interference between downlink and uplink to mitigate intercell interference with little computing overhead. The basic concept is to construct scheduling groups that consist of several users. Each user in a scheduling group is affiliated with a different cell. Then, the intercell groups are managed efficiently in the proposed VCNs. There is no need for the exchange of a lot of information among base stations to schedule the users over the entire network.

  5. Two possible mechanisms for vortex self-organization

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The vortex self-organization is investigated in this paper by four groups of numerical experiments within the framework of quasi-geostrophic model, and based on the experimental results two types of possible mechanisms for vortex self-organization are suggested. The meso-scale topography may enable separated vortices to merge into a larger scale vortex; and the interaction of meso-γand meso-β scale systems may make separated vortices to self organize a typhoon-like vortex circulation.

  6. Evolution of Self-Organized Task Specialization in Robot Swarms

    Science.gov (United States)

    Ferrante, Eliseo; Turgut, Ali Emre; Duéñez-Guzmán, Edgar; Dorigo, Marco; Wenseleers, Tom

    2015-01-01

    Division of labor is ubiquitous in biological systems, as evidenced by various forms of complex task specialization observed in both animal societies and multicellular organisms. Although clearly adaptive, the way in which division of labor first evolved remains enigmatic, as it requires the simultaneous co-occurrence of several complex traits to achieve the required degree of coordination. Recently, evolutionary swarm robotics has emerged as an excellent test bed to study the evolution of coordinated group-level behavior. Here we use this framework for the first time to study the evolutionary origin of behavioral task specialization among groups of identical robots. The scenario we study involves an advanced form of division of labor, common in insect societies and known as “task partitioning”, whereby two sets of tasks have to be carried out in sequence by different individuals. Our results show that task partitioning is favored whenever the environment has features that, when exploited, reduce switching costs and increase the net efficiency of the group, and that an optimal mix of task specialists is achieved most readily when the behavioral repertoires aimed at carrying out the different subtasks are available as pre-adapted building blocks. Nevertheless, we also show for the first time that self-organized task specialization could be evolved entirely from scratch, starting only from basic, low-level behavioral primitives, using a nature-inspired evolutionary method known as Grammatical Evolution. Remarkably, division of labor was achieved merely by selecting on overall group performance, and without providing any prior information on how the global object retrieval task was best divided into smaller subtasks. We discuss the potential of our method for engineering adaptively behaving robot swarms and interpret our results in relation to the likely path that nature took to evolve complex sociality and task specialization. PMID:26247819

  7. Modelling the self-organization and collapse of complex networks

    Indian Academy of Sciences (India)

    Modelling the self-organization and collapse of complex networks. Sanjay Jain Department of Physics and Astrophysics, University of Delhi Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore Santa Fe Institute, Santa Fe, New Mexico.

  8. Self-Organization in Embedded Real-Time Systems

    CERN Document Server

    Brinkschulte, Uwe; Rettberg, Achim

    2013-01-01

    This book describes the emerging field of self-organizing, multicore, distributed and real-time embedded systems.  Self-organization of both hardware and software can be a key technique to handle the growing complexity of modern computing systems. Distributed systems running hundreds of tasks on dozens of processors, each equipped with multiple cores, requires self-organization principles to ensure efficient and reliable operation. This book addresses various, so-called Self-X features such as self-configuration, self-optimization, self-adaptation, self-healing and self-protection. Presents open components for embedded real-time adaptive and self-organizing applications; Describes innovative techniques in: scheduling, memory management, quality of service, communications supporting organic real-time applications; Covers multi-/many-core embedded systems supporting real-time adaptive systems and power-aware, adaptive hardware and software systems; Includes case studies of open embedded real-time self-organizi...

  9. Mobile Anomaly Detection Based on Improved Self-Organizing Maps

    National Research Council Canada - National Science Library

    Yin, Chunyong; Zhang, Sun; Kim, Kwang-jun

    2017-01-01

    .... The introduction of data mining has made leaps forward in this field. Self-organizing maps, one of famous clustering algorithms, are affected by initial weight vectors and the clustering result is unstable...

  10. Optical electronics self-organized integration and applications

    CERN Document Server

    Yoshimura, Tetsuzo

    2012-01-01

    IntroductionFrom Electronics to Optical ElectronicsAnalysis Tools for Optical CircuitsSelf-Organized Optical Waveguides: Theoretical AnalysisSelf-Organized Optical Waveguides: Experimental DemonstrationsOptical Waveguide Films with Vertical Mirrors 3-D Optical Circuits with Stacked Waveguide Films Heterogeneous Thin-Film Device IntegrationOptical Switches OE Hardware Built by Optical ElectronicsIntegrated Solar Energy Conversion SystemsFuture Challenges.

  11. Extending Particle Swarm Optimisers with Self-Organized Criticality

    DEFF Research Database (Denmark)

    Løvbjerg, Morten; Krink, Thiemo

    2002-01-01

    Particle swarm optimisers (PSOs) show potential in function optimisation, but still have room for improvement. Self-organized criticality (SOC) can help control the PSO and add diversity. Extending the PSO with SOC seems promising reaching faster convergence and better solutions.......Particle swarm optimisers (PSOs) show potential in function optimisation, but still have room for improvement. Self-organized criticality (SOC) can help control the PSO and add diversity. Extending the PSO with SOC seems promising reaching faster convergence and better solutions....

  12. Clustering analysis of malware behavior using Self Organizing Map

    DEFF Research Database (Denmark)

    Pirscoveanu, Radu-Stefan; Stevanovic, Matija; Pedersen, Jens Myrup

    2016-01-01

    For the time being, malware behavioral classification is performed by means of Anti-Virus (AV) generated labels. The paper investigates the inconsistencies associated with current practices by evaluating the identified differences between current vendors. In this paper we rely on Self Organizing...... accurate results based on the clusters created by competitive and cooperative algorithms like Self Organizing Map that better describe the behavioral profile of malware....

  13. Deliberative Self-Organizing Traffic Lights with Elementary Cellular Automata

    Directory of Open Access Journals (Sweden)

    Jorge L. Zapotecatl

    2017-01-01

    Full Text Available Self-organizing traffic lights have shown considerable improvements compared to traditional methods in computer simulations. Self-organizing methods, however, use sophisticated sensors, increasing their cost and limiting their deployment. We propose a novel approach using simple sensors to achieve self-organizing traffic light coordination. The proposed approach involves placing a computer and a presence sensor at the beginning of each block; each such sensor detects a single vehicle. Each computer builds a virtual environment simulating vehicle movement to predict arrivals and departures at the downstream intersection. At each intersection, a computer receives information across a data network from the computers of the neighboring blocks and runs a self-organizing method to control traffic lights. Our simulations showed a superior performance for our approach compared with a traditional method (a green wave and a similar performance (close to optimal compared with a self-organizing method using sophisticated sensors but at a lower cost. Moreover, the developed sensing approach exhibited greater robustness against sensor failures.

  14. Self-organization without conservation: true or just apparent scale-invariance?

    Science.gov (United States)

    Bonachela, Juan A.; Muñoz, Miguel A.

    2009-09-01

    The existence of true scale-invariance in slowly driven models of self-organized criticality without a conservation law, such as forest-fires or earthquake automata, is scrutinized in this paper. By using three different levels of description—(i) a simple mean field, (ii) a more detailed mean-field description in terms of a (self-organized) branching processes, and (iii) a full stochastic representation in terms of a Langevin equation—it is shown on general grounds that non-conserving dynamics does not lead to bona fide criticality. Contrary to the case for conserving systems, a parameter, which we term the 're-charging' rate (e.g. the tree-growth rate in forest-fire models), needs to be fine-tuned in non-conserving systems to obtain criticality. In the infinite-size limit, such a fine-tuning of the loading rate is easy to achieve, as it emerges by imposing a second separation of timescales but, for any finite size, a precise tuning is required to achieve criticality and a coherent finite-size scaling picture. Using the approaches above, we shed light on the common mechanisms by which 'apparent criticality' is observed in non-conserving systems, and explain in detail (both qualitatively and quantitatively) the difference with respect to true criticality obtained in conserving systems. We propose to call this self-organized quasi-criticality (SOqC). Some of the reported results are already known and some of them are new. We hope that the unified framework presented here will help to elucidate the confusing and contradictory literature in this field. In a forthcoming paper, we shall discuss the implications of the general results obtained here for models of neural avalanches in neuroscience for which self-organized scale-invariance in the absence of conservation has been claimed.

  15. An Evolutionary Game Theoretic Approach to Multi-Sector Coordination and Self-Organization

    Directory of Open Access Journals (Sweden)

    Fernando P. Santos

    2016-04-01

    Full Text Available Coordination games provide ubiquitous interaction paradigms to frame human behavioral features, such as information transmission, conventions and languages as well as socio-economic processes and institutions. By using a dynamical approach, such as Evolutionary Game Theory (EGT, one is able to follow, in detail, the self-organization process by which a population of individuals coordinates into a given behavior. Real socio-economic scenarios, however, often involve the interaction between multiple co-evolving sectors, with specific options of their own, that call for generalized and more sophisticated mathematical frameworks. In this paper, we explore a general EGT approach to deal with coordination dynamics in which individuals from multiple sectors interact. Starting from a two-sector, consumer/producer scenario, we investigate the effects of including a third co-evolving sector that we call public. We explore the changes in the self-organization process of all sectors, given the feedback that this new sector imparts on the other two.

  16. Self-Organized Construction with Continuous Building Material

    DEFF Research Database (Denmark)

    Heinrich, Mary Katherine; Wahby, Mostafa; Divband Soorati, Mohammad

    2016-01-01

    Self-organized construction with continuous, structured building material, as opposed to modular units, offers new challenges to the robot-based construction process and lends the opportunity for increased flexibility in constructed artifact properties, such as shape and deformation. As an example...... investigation, we look at continuous filaments organized into braided structures, within the context of bio-hybrids constructing architectural artifacts. We report the result of an early swarm robot experiment. The robots successfully constructed a braid in a self-organized process. The construction process can...... be extended by using different materials and by embedding sensors during the self-organized construction directly into the braided structure. In future work, we plan to apply dedicated braiding robot hardware and to construct sophisticated 3-d structures with local variability in patterns of filament...

  17. Self-Organization during Friction in Complex Surface Engineered Tribosystems

    Directory of Open Access Journals (Sweden)

    Ben D. Beake

    2010-02-01

    Full Text Available Self-organization during friction in complex surface engineered tribosystems is investigated. The probability of self-organization in these complex tribosystems is studied on the basis of the theoretical concepts of irreversible thermodynamics. It is shown that a higher number of interrelated processes within the system result in an increased probability of self-organization. The results of this thermodynamic model are confirmed by the investigation of the wear performance of a novel Ti0.2Al0.55Cr0.2Si0.03Y0.02N/Ti0.25Al0.65Cr0.1N (PVD coating with complex nano-multilayered structure under extreme tribological conditions of dry high-speed end milling of hardened H13 tool steel.

  18. 9th Workshop on Self-Organizing Maps

    CERN Document Server

    Príncipe, José; Zegers, Pablo

    2013-01-01

    Self-organizing maps (SOMs) were developed by Teuvo Kohonen in the early eighties. Since then more than 10,000 works have been based on SOMs. SOMs are unsupervised neural networks useful for clustering and visualization purposes. Many SOM applications have been developed in engineering and science, and other fields. This book contains refereed papers presented at the 9th Workshop on Self-Organizing Maps (WSOM 2012) held at the Universidad de Chile, Santiago, Chile, on December 12-14, 2012. The workshop brought together researchers and practitioners in the field of self-organizing systems. Among the book chapters there are excellent examples of the use of SOMs in agriculture, computer science, data visualization, health systems, economics, engineering, social sciences, text and image analysis, and time series analysis. Other chapters present the latest theoretical work on SOMs as well as Learning Vector Quantization (LVQ) methods.

  19. Atmospheric Convective Organization: Self-Organized Criticality or Homeostasis?

    Science.gov (United States)

    Yano, Jun-Ichi

    2015-04-01

    Atmospheric convection has a tendency organized on a hierarchy of scales ranging from the mesoscale to the planetary scales, with the latter especially manifested by the Madden-Julian oscillation. The present talk examines two major possible mechanisms of self-organization identified in wider literature from a phenomenological thermodynamic point of view by analysing a planetary-scale cloud-resolving model simulation. The first mechanism is self-organized criticality. A saturation tendency of precipitation rate with the increasing column-integrated water, reminiscence of critical phenomena, indicates self-organized criticality. The second is a self-regulation mechanism that is known as homeostasis in biology. A thermodynamic argument suggests that such self-regulation maintains the column-integrated water below a threshold by increasing the precipitation rate. Previous analyses of both observational data as well as cloud-resolving model (CRM) experiments give mixed results. A satellite data analysis suggests self-organized criticality. Some observational data as well as CRM experiments support homeostasis. Other analyses point to a combination of these two interpretations. In this study, a CRM experiment over a planetary-scale domain with a constant sea-surface temperature is analyzed. This analysis shows that the relation between the column-integrated total water and precipitation suggests self-organized criticality, whereas the one between the column-integrated water vapor and precipitation suggests homeostasis. The concurrent presence of these two mechanisms are further elaborated by detailed statistical and budget analyses. These statistics are scale invariant, reflecting a spatial scaling of precipitation processes. These self-organization mechanisms are most likely be best theoretically understood by the energy cycle of the convective systems consisting of the kinetic energy and the cloud-work function. The author has already investigated the behavior of this

  20. Self-Organizing Map Models of Language Acquisition

    Directory of Open Access Journals (Sweden)

    Ping eLi

    2013-11-01

    Full Text Available Connectionist models have had a profound impact on theories of language. While most early models were inspired by the classic PDP architecture, recent models of language have explored various other types of models, including self-organizing models for language acquisition. In this paper we aim at providing a review of the latter type of models, and highlight a number of simulation experiments that we have conducted based on these models. We show that self-organizing connectionist models can provide significant insights into long-standing debates in both monolingual and bilingual language development.

  1. Self-organized criticality in a cold plasma

    Science.gov (United States)

    Alex, Prince; Carreras, Benjamin Andres; Arumugam, Saravanan; Sinha, Suraj Kumar

    2017-12-01

    We present direct evidence for the existence of self-organized critical behavior in cold plasma. A multiple anodic double layer structure generated in a double discharge plasma setup shows critical behavior for the anode bias above a threshold value. Analysis of the floating potential fluctuations reveals the existence of long-range time correlations and power law behavior in the tail of the probability distribution function of the fluctuations. The measured Hurst exponent and the power law tail in the rank function are strong indication of the self-organized critical behavior of the system and hence provide a condition under which complexities arise in cold plasma.

  2. Self-Organization and Annealed Disorder in a Fracturing Process

    DEFF Research Database (Denmark)

    Caldarelli, Guido; Di Tolla, Francesco; Petri, Alberto

    1996-01-01

    the breaking threshold in the neighborhood of a bond broken by the stress, with a process similar to self-organized criticality. A further comparison with experimental results of acoustic emission (AE), shows that the stability of the elastic potential energy of the system in the AE regime is a sufficient......We show that a vectorial model for inhomogeneous elastic media self-organizes under external stress. An onset of crack avalanches of every duration and length scale compatible with the lattice size is observed. The behavior is driven by the introduction of annealed disorder, i.e., by lowering...

  3. 5G heterogeneous networks self-organizing and optimization

    CERN Document Server

    Rong, Bo; Kadoch, Michel; Sun, Songlin; Li, Wenjing

    2016-01-01

    This SpringerBrief provides state-of-the-art technical reviews on self-organizing and optimization in 5G systems. It covers the latest research results from physical-layer channel modeling to software defined network (SDN) architecture. This book focuses on the cutting-edge wireless technologies such as heterogeneous networks (HetNets), self-organizing network (SON), smart low power node (LPN), 3D-MIMO, and more. It will help researchers from both the academic and industrial worlds to better understand the technical momentum of 5G key technologies.

  4. Unsupervised learning via self-organization a dynamic approach

    CERN Document Server

    Kyan, Matthew; Jarrah, Kambiz; Guan, Ling

    2014-01-01

    To aid in intelligent data mining, this book introduces a new family of unsupervised algorithms that have a basis in self-organization, yet are free from many of the constraints typical of other well known self-organizing architectures. It then moves through a series of pertinent real world applications with regards to the processing of multimedia data from its role in generic image processing techniques such as the automated modeling and removal of impulse noise in digital images, to problems in digital asset management, and its various roles in feature extraction, visual enhancement, segmentation, and analysis of microbiological image data.

  5. Is bioluminescent turbulence an example of self-organized critically?

    Science.gov (United States)

    Noever, David; Cronise, Raymond

    1994-06-01

    When mechanically stimulated by flow, some marine cells react by flashing blue light or bioluminescing. The flash response give a relatively non-invasive measure of turbulent behavior which lends itself readily and quantitatively to statistical models of fluid structure. We report substantial agreement between a series of experiments performed using stimulated light from the bioluminescence of seawater flowing through a glass pipe and theoretical predictions based on models proposed for describing a self-organized critical phenomenon. In this way, bioluminescent turbulent flow can be taken as a natural and potentially robust example connecting long-held scaling problems in turbulence to recent thinking on fractals and self-organized critically.

  6. A Novel Multi-Objective Self-Organizing Migrating Algorithm

    Directory of Open Access Journals (Sweden)

    P. Kadlec

    2011-12-01

    Full Text Available In the paper, a novel stochastic Multi-Objective Self Organizing Migrating Algorithm (MOSOMA is introduced. For the search of optima, MOSOMA employs a migration technique used in a single-objective Self Organizing Migrating Algorithm (SOMA. In order to obtain a uniform distribution of Pareto optimal solutions, a novel technique considering Euclidian distances among solutions is introduced. MOSOMA performance was tested on benchmark problems and selected electromagnetic structures. MOSOMA performance was compared with the performance of the Non-dominated Sorting Genetic Algorithm II (NSGA-II and the Strength Pareto Evolutionary Algorithm 2 (SPEA2. MOSOMA excels in the uniform distribution of solutions and their completeness.

  7. 10th Workshop on Self-Organizing Maps

    CERN Document Server

    Schleif, Frank-Michael; Kaden, Marika; Lange, Mandy

    2014-01-01

    The book collects the scientific contributions presented at the 10th Workshop on Self-Organizing Maps (WSOM 2014) held at the University of Applied Sciences Mittweida, Mittweida (Germany, Saxony), on July 2–4, 2014. Starting with the first WSOM-workshop 1997 in Helsinki this workshop focuses on newest results in the field of supervised and unsupervised vector quantization like self-organizing maps for data mining and data classification.   This 10th WSOM brought together more than 50 researchers, experts and practitioners in the beautiful small town Mittweida in Saxony (Germany) nearby the mountains Erzgebirge to discuss new developments in the field of unsupervised self-organizing vector quantization systems and learning vector quantization approaches for classification. The book contains the accepted papers of the workshop after a careful review process as well as summaries of the invited talks.   Among these book chapters there are excellent examples of the use of self-organizing maps in agriculture, ...

  8. Self-organization of intense light within erosive gas discharges

    Energy Technology Data Exchange (ETDEWEB)

    Torchigin, V.P. [Institute of Informatics Problems, Russian Academy of Sciences, Nakhimovsky prospect 36/1, 119278 Moscow (Russian Federation)]. E-mail: v_torchigin@mail.ru; Torchigin, A.V. [Institute of Informatics Problems, Russian Academy of Sciences, Nakhimovsky prospect 36/1, 119278 Moscow (Russian Federation)

    2007-01-22

    Process of appearance of fire balls at gas discharges is considered. It is shown that the intense white light radiated by atoms excited at gas discharge is subject to self-organization in such a way that miniature ball lightnings appear.

  9. Comparative investigation of two different self-organizing map ...

    African Journals Online (AJOL)

    Purpose: To demonstrate the ability and investigate the performance of two different wavelength selection approaches based on self-organizing map (SOM) technique in partial least-squares (PLS) regression for analysis of pharmaceutical binary mixtures with strongly overlapping spectra. Methods: Two different variable ...

  10. Strain relaxation and self-organization phenomena in heteroepitaxial systems

    DEFF Research Database (Denmark)

    Shiryaev, Sergey Y; Hansen, J. Lundsgaard; Larsen, A. Nylandsted

    1995-01-01

    populations. Striking analogies between the Seeger-Frank treatment of dislocation ordering in solids and the model of self-adjustment of misfit dislocations are elaborated. The graded Si1-xGex/Si system will be shown to constitute a convenient model case for studying self-organization in crystalline material....

  11. Tokamak plasma self-organization-synergetics of magnetic trap plasmas

    NARCIS (Netherlands)

    Razumova, K. A.; Andreev, V. F.; Eliseev, L. G.; Kislov, A. Y.; La Haye, R. J.; Lysenko, S. E.; Melnikov, A. V.; Notkin, G. E.; Pavlov, Y. D.; Kantor, M. Y.

    2011-01-01

    Analysis of a wide range of experimental results in plasma magnetic confinement investigations shows that in most cases, plasmas are self-organized. In the tokamak case, it is realized in the self-consistent pressure profile, which permits the tokamak plasma to be macroscopically MHD stable.

  12. Self-organized structures in soft confined thin films

    Indian Academy of Sciences (India)

    These very small scale, highly confined systems are inherently unstable and thus self-organize into ordered structures which can be exploited for MEMS, sensors, opto-electronic devices and a host of other nanotechnology applications. In particular, mesomechanics requires incorporation of intermolecular interactions and ...

  13. Self-Organized Criticality and Mass Extinction in Evolutionary Algorithms

    DEFF Research Database (Denmark)

    Krink, Thiemo; Thomsen, Rene

    2001-01-01

    at a critical state between chaos and order, known as self-organized criticality (SOC). Based on this background, we used SOC to control the size of spatial extinction zones in a diffusion model. The SOC selection process was easy to implement and implied only negligible computational costs. Our results show...

  14. Electrochemical studies of redox probes in self-organized lyotropic ...

    Indian Academy of Sciences (India)

    Administrator

    quinone|hydroquinone, methyl viologen and ferrocenemethanol probes in a lyotropic hexagonal columnar phase (H1 phase) using cyclic .... Electrochemical studies of redox probes in self-organized lyotropic liquid crystalline systems. 631. Figure 2. ..... can occupy the inter-columnar space of the micelle. As a result, the ...

  15. A self-organized internal models architecture for coding sensory-motor schemes

    Directory of Open Access Journals (Sweden)

    Esaú eEscobar Juárez

    2016-04-01

    Full Text Available Cognitive robotics research draws inspiration from theories and models on cognition, as conceived by neuroscience or cognitive psychology, to investigate biologically plausible computational models in artificial agents. In this field, the theoretical framework of Grounded Cognition provides epistemological and methodological grounds for the computational modeling of cognition. It has been stressed in the literature that textit{simulation}, textit{prediction}, and textit{multi-modal integration} are key aspects of cognition and that computational architectures capable of putting them into play in a biologically plausible way are a necessity.Research in this direction has brought extensive empirical evidencesuggesting that textit{Internal Models} are suitable mechanisms forsensory-motor integration. However, current Internal Models architectures show several drawbacks, mainly due to the lack of a unified substrate allowing for a true sensory-motor integration space, enabling flexible and scalable ways to model cognition under the embodiment hypothesis constraints.We propose the Self-Organized Internal ModelsArchitecture (SOIMA, a computational cognitive architecture coded by means of a network of self-organized maps, implementing coupled internal models that allow modeling multi-modal sensory-motor schemes. Our approach addresses integrally the issues of current implementations of Internal Models.We discuss the design and features of the architecture, and provide empirical results on a humanoid robot that demonstrate the benefits and potentialities of the SOIMA concept for studying cognition in artificial agents.

  16. Self-Organization of Blood Pressure Regulation: Experimental Evidence.

    Science.gov (United States)

    Fortrat, Jacques-Olivier; Levrard, Thibaud; Courcinous, Sandrine; Victor, Jacques

    2016-01-01

    Blood pressure regulation is a prime example of homeostatic regulation. However, some characteristics of the cardiovascular system better match a non-linear self-organized system than a homeostatic one. To determine whether blood pressure regulation is self-organized, we repeated the seminal demonstration of self-organized control of movement, but applied it to the cardiovascular system. We looked for two distinctive features peculiar to self-organization: non-equilibrium phase transitions and hysteresis in their occurrence when the system is challenged. We challenged the cardiovascular system by means of slow, 20-min Tilt-Up and Tilt-Down tilt table tests in random order. We continuously determined the phase between oscillations at the breathing frequency of Total Peripheral Resistances and Heart Rate Variability by means of cross-spectral analysis. We looked for a significant phase drift during these procedures, which signed a non-equilibrium phase transition. We determined at which head-up tilt angle it occurred. We checked that this angle was significantly different between Tilt-Up and Tilt-Down to demonstrate hysteresis. We observed a significant non-equilibrium phase transition in nine healthy volunteers out of 11 with significant hysteresis (48.1 ± 7.5° and 21.8 ± 3.9° during Tilt-Up and Tilt-Down, respectively, p < 0.05). Our study shows experimental evidence of self-organized short-term blood pressure regulation. It provides new insights into blood pressure regulation and its related disorders.

  17. Self-organization and fractality in a metabolic processes of the Krebs cycle.

    Science.gov (United States)

    Grytsay, V I; Musatenko, I V

    2013-01-01

    The metabolic processes of the Krebs cycle is studied with the help of a mathematical model. The autocatalytic processes resulting in both the formation of the self-organization in the Krebs cycle and the appearance of a cyclicity of its dynamics are determined. Some structural-functional connections creating the synchronism of an autoperiodic functioning at the transport in the respiratory chain and the oxidative phosphorylation are investigated. The conditions for breaking the synchronization of processes, increasing the multiplicity of cyclicity, and for the appearance of chaotic modes are analyzed. The phase-parametric diagram of a cascade of bifurcations showing the transition to a chaotic mode by the Feigenbaum scenario is obtained. The fractal nature of the revealed cascade of bifurcations is demonstrated. The strange attractors formed as a result of the folding are obtained. The results obtained give the idea of structural-functional connections, due to which the self-organization appears in the metabolism running in a cell. The constructed mathematical model can be applied to the study of the toxic and allergic effects of drugs and various substances on cell metabolism.

  18. Self-organizing phenomena at membrane level and low-level laser therapy of rhinitis

    Science.gov (United States)

    Ailioaie, Laura; Ailioaie, C.; Topoliceanu, Fl.

    2000-06-01

    Allergic rhinitis is the most common allergic disease affecting many people worldwide. Low level laser therapy (LLLT) was applied as monotherapy to 32 children, under placebo controlled conditions. There have been used two GaAlAs diode lasers. The density of energy and the frequency 2 sessions daily - were applied under a special experimental protocol of treatment, including endonasal regions treated with an optical fiber and the extrameridian acupuncture points for rhinitis, 10 days monthly, three months consecutively. The initial investigations with fiberoptic rhinoscope revealed a swollen, pale and edematous mucosa, with increased nasal sections, which may be watery to mucoid. At the end of LLLT, the symptoms of rhinitis like sneezing, nasal congestion, stuffy nose, mouth breathing, snoring - have disappeared and the aspect of nasal mucosa was normal. The results could be explained in the new scenario of self-organizing phenomena at membrane level. The physiological beneficial effects may be correlated and possibly explained by self-organizing paradigms. Our result warrant that LLL is a very good therapy modality for children suffering from allergic rhinitis.

  19. Self-organizing map models of language acquisition

    Science.gov (United States)

    Li, Ping; Zhao, Xiaowei

    2013-01-01

    Connectionist models have had a profound impact on theories of language. While most early models were inspired by the classic parallel distributed processing architecture, recent models of language have explored various other types of models, including self-organizing models for language acquisition. In this paper, we aim at providing a review of the latter type of models, and highlight a number of simulation experiments that we have conducted based on these models. We show that self-organizing connectionist models can provide significant insights into long-standing debates in both monolingual and bilingual language development. We suggest future directions in which these models can be extended, to better connect with behavioral and neural data, and to make clear predictions in testing relevant psycholinguistic theories. PMID:24312061

  20. Self-Organized Criticality of Rainfall in Central China

    Directory of Open Access Journals (Sweden)

    Zhiliang Wang

    2012-01-01

    Full Text Available Rainfall is a complexity dynamics process. In this paper, our objective is to find the evidence of self-organized criticality (SOC for rain datasets in China by employing the theory and method of SOC. For this reason, we analyzed the long-term rain records of five meteorological stations in Henan, a central province of China. Three concepts, that is, rain duration, drought duration, accumulated rain amount, are proposed to characterize these rain events processes. We investigate their dynamics property by using scale invariant and found that the long-term rain processes in central China indeed exhibit the feature of self-organized criticality. The proposed theory and method may be suitable to analyze other datasets from different climate zones in China.

  1. Self-organized service negotiation for collaborative decision making.

    Science.gov (United States)

    Zhang, Bo; Huang, Zhenhua; Zheng, Ziming

    2014-01-01

    This paper proposes a self-organized service negotiation method for CDM in intelligent and automatic manners. It mainly includes three phases: semantic-based capacity evaluation for the CDM sponsor, trust computation of the CDM organization, and negotiation selection of the decision-making service provider (DMSP). In the first phase, the CDM sponsor produces the formal semantic description of the complex decision task for DMSP and computes the capacity evaluation values according to participator instructions from different DMSPs. In the second phase, a novel trust computation approach is presented to compute the subjective belief value, the objective reputation value, and the recommended trust value. And in the third phase, based on the capacity evaluation and trust computation, a negotiation mechanism is given to efficiently implement the service selection. The simulation experiment results show that our self-organized service negotiation method is feasible and effective for CDM.

  2. Self-organization of gold nanoparticles on silanated surfaces.

    Science.gov (United States)

    Kyaw, Htet H; Al-Harthi, Salim H; Sellai, Azzouz; Dutta, Joydeep

    2015-01-01

    The self-organization of monolayer gold nanoparticles (AuNPs) on 3-aminopropyltriethoxysilane (APTES)-functionalized glass substrate is reported. The orientation of APTES molecules on glass substrates plays an important role in the interaction between AuNPs and APTES molecules on the glass substrates. Different orientations of APTES affect the self-organization of AuNps on APTES-functionalized glass substrates. The as grown monolayers and films annealed in ultrahigh vacuum and air (600 °C) were studied by water contact angle measurements, atomic force microscopy, X-ray photoelectron spectroscopy, UV-visible spectroscopy and ultraviolet photoelectron spectroscopy. Results of this study are fundamentally important and also can be applied for designing and modelling of surface plasmon resonance based sensor applications.

  3. Self-organizing map models of language acquisition.

    Science.gov (United States)

    Li, Ping; Zhao, Xiaowei

    2013-11-19

    Connectionist models have had a profound impact on theories of language. While most early models were inspired by the classic parallel distributed processing architecture, recent models of language have explored various other types of models, including self-organizing models for language acquisition. In this paper, we aim at providing a review of the latter type of models, and highlight a number of simulation experiments that we have conducted based on these models. We show that self-organizing connectionist models can provide significant insights into long-standing debates in both monolingual and bilingual language development. We suggest future directions in which these models can be extended, to better connect with behavioral and neural data, and to make clear predictions in testing relevant psycholinguistic theories.

  4. SOUNET: Self-Organized Underwater Wireless Sensor Network.

    Science.gov (United States)

    Kim, Hee-Won; Cho, Ho-Shin

    2017-02-02

    In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the timevarying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment.

  5. Energy sources, self-organization, and the origin of life.

    Science.gov (United States)

    Boiteau, Laurent; Pascal, Robert

    2011-02-01

    The emergence and early developments of life are considered from the point of view that contingent events that inevitably marked evolution were accompanied by deterministic driving forces governing the selection between different alternatives. Accordingly, potential energy sources are considered for their propensity to induce self-organization within the scope of the chemical approach to the origin of life. Requirements in terms of quality of energy locate thermal or photochemical activation in the atmosphere as highly likely processes for the formation of activated low-molecular weight organic compounds prone to induce biomolecular self-organization through their ability to deliver quanta of energy matching the needs of early biochemical pathways or the reproduction of self-replicating entities. These lines of reasoning suggest the existence of a direct connection between the free energy content of intermediates of early pathways and the quanta of energy delivered by available sources of energy.

  6. Self-organization of gold nanoparticles on silanated surfaces

    Directory of Open Access Journals (Sweden)

    Htet H. Kyaw

    2015-12-01

    Full Text Available The self-organization of monolayer gold nanoparticles (AuNPs on 3-aminopropyltriethoxysilane (APTES-functionalized glass substrate is reported. The orientation of APTES molecules on glass substrates plays an important role in the interaction between AuNPs and APTES molecules on the glass substrates. Different orientations of APTES affect the self-organization of AuNps on APTES-functionalized glass substrates. The as grown monolayers and films annealed in ultrahigh vacuum and air (600 °C were studied by water contact angle measurements, atomic force microscopy, X-ray photoelectron spectroscopy, UV–visible spectroscopy and ultraviolet photoelectron spectroscopy. Results of this study are fundamentally important and also can be applied for designing and modelling of surface plasmon resonance based sensor applications.

  7. 11th Workshop on Self-Organizing Maps

    CERN Document Server

    Mendenhall, Michael; O'Driscoll, Patrick

    2016-01-01

    This book contains the articles from the international conference 11th Workshop on Self-Organizing Maps 2016 (WSOM 2016), held at Rice University in Houston, Texas, 6-8 January 2016. WSOM is a biennial international conference series starting with WSOM'97 in Helsinki, Finland, under the guidance and direction of Professor Tuevo Kohonen (Emeritus Professor, Academy of Finland). WSOM brings together the state-of-the-art theory and applications in Competitive Learning Neural Networks: SOMs, LVQs and related paradigms of unsupervised and supervised vector quantization. The current proceedings present the expert body of knowledge of 93 authors from 15 countries in 31 peer reviewed contributions. It includes papers and abstracts from the WSOM 2016 invited speakers representing leading researchers in the theory and real-world applications of Self-Organizing Maps and Learning Vector Quantization: Professor Marie Cottrell (Universite Paris 1 Pantheon Sorbonne, France), Professor Pablo Estevez (University of Chile and ...

  8. Self-Organizing OFDMA System for Broadband Communication

    Science.gov (United States)

    Roy, Aloke (Inventor); Anandappan, Thanga (Inventor); Malve, Sharath Babu (Inventor)

    2016-01-01

    Systems and methods for a self-organizing OFDMA system for broadband communication are provided. In certain embodiments a communication node for a self organizing network comprises a communication interface configured to transmit data to and receive data from a plurality of nodes; and a processing unit configured to execute computer readable instructions. Further, computer readable instructions direct the processing unit to identify a sub-region within a cell, wherein the communication node is located in the sub-region; and transmit at least one data frame, wherein the data from the communication node is transmitted at a particular time and frequency as defined within the at least one data frame, where the time and frequency are associated with the sub-region.

  9. SOUNET: Self-Organized Underwater Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Hee-won Kim

    2017-02-01

    Full Text Available In this paper, we propose an underwater wireless sensor network (UWSN named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the timevarying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR, and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment.

  10. Universal Quantification for Self-Organized Criticality in Atmospheric Flows

    CERN Document Server

    Selvam, A M

    1997-01-01

    Atmospheric flows exhibit selfsimilar fluctuations on all scales(space-time) ranging from climate(kilometers/years) to turbulence(millimeters/seconds) manifested as fractal geometry to the global cloud cover pattern concomitant with inverse power law form for power spectra of temporal fluctuations. Selfsimilar fluctuations implying long-range correlations are ubiquitous to dynamical systems in nature and are identified as signatures of self-organized criticality in atmospheric flows. Also, mathematical models for simulation and prediction of atmospheric flows are nonlinear and computer realizations give unrealistic solutions because of deterministic chaos, a direct consequence of finite precision round-off error doubling for each iteration of iterative computations incorporated in long-term numerical integration schemes used for model solutions An alternative non-deterministic cell dynamical system model predicts, (a): the observed self organized criticality as a consequence of quantumlike mechanics governing...

  11. Evolution as a self-organized critical phenomenon

    Energy Technology Data Exchange (ETDEWEB)

    Sneppen, K. [Princeton Univ., Princeton, NJ (United States); Bak, P. [Brookhaven National Laboratory, Upton, NY (United States)]|[Isaac Newton Institute for Mathematical Sciences, Cambridge (United Kingdom); Flyvbjerg, H. [Isaac Newton Institute for Mathematical Sciences, Cambridge (United Kingdom)]|[HLRZ, Juelich (Germany); Jensen, M.H. [Niels Bohr Institute, Copenhagen (Denmark)

    1995-05-23

    We present a simple mathematical model of biological macroevolution. The model describes an ecology of adapting, interacting species. The environment of any given species is affected by other evolving species; hence, it is not constant in time. The ecology as a whole evolves to a {open_quotes}self-organized critical{close_quotes} state where periods of stasis alternate with avalanches of casually connected evolutionary changes. This characteristic behavior of natural history, known as {open_quotes}punctuated equilibrium,{close_quotes} thus finds a theoretical explanation as a self-organized critical phenomenon. The evolutionary behavior of single species is intermittent. Also, large bursts of apparently simultaneous evolutionary activity require no external cause. Extinctions of all sizes, including mass extinctions, may be a simple consequence of ecosystem dynamics. Our results are compared with data from the fossil record. 35 refs., 7 figs.

  12. Evolution as a Self-Organized Critical Phenomenon

    Science.gov (United States)

    Sneppen, Kim; Bak, Per; Flyvbjerg, Henrik; Jensen, Mogens H.

    1995-05-01

    We present a simple mathematical model of biological macroevolution. The model describes an ecology of adapting, interacting species. The environment of any given species is affected by other evolving species; hence, it is not constant in time. The ecology as a whole evolves to a "self-organized critical" state where periods of stasis alternate with avalanches of causally connected evolutionary changes. This characteristic behavior of natural history, known as "punctuated equilibrium," thus finds a theoretical explanation as a self-organized critical phenomenon. The evolutionary behavior of single species is intermittent. Also, large bursts of apparently simultaneous evolutionary activity require no external cause. Extinctions of all sizes, including mass extinctions, may be a simple consequence of ecosystem dynamics. Our results are compared with data from the fossil record

  13. How nature works the science of self-organized criticality

    CERN Document Server

    Bak, Per

    1996-01-01

    This is an acclaimed book intended for the general reader who is interested in science. The author is a physicist who is well-known for his development of the property called "self-organized criticality", a property or phenomenon that lies at the heart of large dynamical systems. It can be used to analyse systems that are complicated, and which are part of the new science of complexity. It is a unifying concept that can be used to study phenomena in fields as diverse as economics, astronomy, the earth sciences, and physics. The author discusses his discovery of self-organized criticality; its relation to the world of classical physics; computer simulations and experiments which aid scientists' understanding of the property; and the relation of the subject to popular areas such as fractal geometry and power laws; cellular automata, and a wide range of practical applications.

  14. Self-organizing Complex Networks: individual versus global rules.

    Science.gov (United States)

    Mahmoodi, Korosh; West, Bruce J; Grigolini, Paolo

    2017-01-01

    We introduce a form of Self-Organized Criticality (SOC) inspired by the new generation of evolutionary game theory, which ranges from physiology to sociology. The single individuals are the nodes of a composite network, equivalent to two interacting subnetworks, one leading to strategy choices made by the individuals under the influence of the choices of their nearest neighbors and the other measuring the Prisoner's Dilemma Game payoffs of these choices. The interaction between the two networks is established by making the imitation strength K increase or decrease according to whether the last two payoffs increase or decrease upon increasing or decreasing K. Although each of these imitation strengths is selected selfishly, and independently of the others as well, the social system spontaneously evolves toward the state of cooperation. Criticality is signaled by temporal complexity, namely the occurrence of non-Poisson renewal events, the time intervals between two consecutive crucial events being given by an inverse power law index μ = 1.3 rather than by avalanches with an inverse power law distribution as in the original form of SOC. This new phenomenon is herein labeled self-organized temporal criticality (SOTC). We compare this bottom-up self-organization process to the adoption of a global choice rule based on assigning to all the units the same value K, with the time evolution of common K being determined by consciousness of the social benefit, a top-down process implying the action of a leader. In this case self-organization is impeded by large intensity fluctuations and the global social benefit turns out to be much weaker. We conclude that the SOTC model fits the requests of a manifesto recently proposed by a number of European social scientists.

  15. LSOT: A Lightweight Self-Organized Trust Model in VANETs

    OpenAIRE

    Zhiquan Liu; Jianfeng Ma; Zhongyuan Jiang; Hui Zhu; Yinbin Miao

    2016-01-01

    With the advances in automobile industry and wireless communication technology, Vehicular Ad hoc Networks (VANETs) have attracted the attention of a large number of researchers. Trust management plays an important role in VANETs. However, it is still at the preliminary stage and the existing trust models cannot entirely conform to the characteristics of VANETs. This work proposes a novel Lightweight Self-Organized Trust (LSOT) model which contains trust certificate-based and recommendation-ba...

  16. Self-organizing Complex Networks: individual versus global rules

    Directory of Open Access Journals (Sweden)

    Korosh Mahmoodi

    2017-07-01

    Full Text Available We introduce a form of Self-Organized Criticality (SOC inspired by the new generation of evolutionary game theory, which ranges from physiology to sociology. The single individuals are the nodes of a composite network, equivalent to two interacting subnetworks, one leading to strategy choices made by the individuals under the influence of the choices of their nearest neighbors and the other measuring the Prisoner's Dilemma Game payoffs of these choices. The interaction between the two networks is established by making the imitation strength K increase or decrease according to whether the last two payoffs increase or decrease upon increasing or decreasing K. Although each of these imitation strengths is selected selfishly, and independently of the others as well, the social system spontaneously evolves toward the state of cooperation. Criticality is signaled by temporal complexity, namely the occurrence of non-Poisson renewal events, the time intervals between two consecutive crucial events being given by an inverse power law index μ = 1.3 rather than by avalanches with an inverse power law distribution as in the original form of SOC. This new phenomenon is herein labeled self-organized temporal criticality (SOTC. We compare this bottom-up self-organization process to the adoption of a global choice rule based on assigning to all the units the same value K, with the time evolution of common K being determined by consciousness of the social benefit, a top-down process implying the action of a leader. In this case self-organization is impeded by large intensity fluctuations and the global social benefit turns out to be much weaker. We conclude that the SOTC model fits the requests of a manifesto recently proposed by a number of European social scientists.

  17. [PhD Thesis] Self-organization versus hierarchical organization

    OpenAIRE

    Evo Busseniers

    2017-01-01

    Self-organization versus hierarchical organization a mathematical investigation of the anarchist philosophy of social organization In combining anarchist theory with mathematics, this thesis wishes to better understand what power and hierarchy are in order to explore how we can live without coercion. My motivation to study these concepts stems from observing a lack of freedom in contemporary society despite a lack of obvious coercion or clear hierarchical structure. I di...

  18. Knowledge Management in Edaphology Using Self Organizing Map (Som)

    OpenAIRE

    Meenakshi, A.; Mohan, V

    2012-01-01

    In this paper, we propose a proficient method for knowledge management in Edaphology using self organizing map (SOM). The method will assist the edaphologists and those related with agriculture in a big way by finding out the plants apt for the input query. The method has three phases namely dataset processing, neuron training and testing phase. The input data is first converted and normalized in the data processing phase. The SOM is constructed from the processed dataset after the neuron tr...

  19. A conciliation mechanism for self-organizing dynamic small groups

    OpenAIRE

    Ren, Minglun; Hu, Zhongfeng; Jain, Hemant

    2016-01-01

    A group of individuals, organizations or things in internet of things (IoT) often dynamically self-organizes in small groups to accomplish certain tasks. This is common in virtual organization, social networks and the evolving field of IoT. These small groups have different behavioral characteristics than large groups. Members individually have some requirements and contribute some resources to the group. The organization and operation of such a group requires dynamic identification of group ...

  20. Architectural Patterns for Self-Organizing Systems-of-Systems

    Science.gov (United States)

    2011-05-01

    show that they are necessary for self-organization to occur. Common Purpose Abraham Maslow proposed a theory on human motivation based on a hierarchy...http://www.hole-in-the-wall.com/abouthiwel.html (accessed October 28, 2010). 21. Maslow , Abraham . 1943. A theory of human motivation. In Psychological...in-the-wall Education Ltd. http://www.hole- in-the-wall.com/abouthiwel.html (accessed October 28, 2010). 22. Maslow , Abraham . 1943. A theory of human

  1. Tissue regeneration: from synthetic scaffolds to self-organizing morphogenesis.

    Science.gov (United States)

    Chen, Ting-Hsuan

    2014-01-01

    Regenerative medicine offers therapeutic approaches to treating non-regenerative diseases such as spinal cord injury and heart disease. Owing to the limited donor tissue available, cell-based therapy using cultured cells with supporting scaffolds has been proposed to rebuild damaged tissue. Early attempts at repairing skin and cartilage achieved significant success thanks to the simplicity of the tissue architecture, which later fueled enthusiasm for applying the same strategy to other types of tissue. However, more complex tissue functions require a more extensive vasculature and heterogeneous cell arrangements, which together constitute a significant hurdle in practical applications. Accordingly, recent years an increased interest has been in the use of decellularized matrices that retain the natural microarchitecture as the scaffold. However, although a number of engineering approaches have been suggested, self-organizing behavior such as cell proliferation, migration, and differentiation may still disorganize and frustrate the artificial attempts. This mini-review first provides examples of the early history of tissue engineering using skin and cartilage as examples, and then elaborates on the key technologies used to fabricate synthetic acellular scaffolds and cell/scaffold constructs with more complicated architectures. It also summarizes the progress achieved in the use of decellularized matrices for cell seeding as well as the recent success seen in self-organizing two- and three-dimensional tissue formation with the aid of biomathematical modeling. The review concludes by proposing the future integration of biomathematics, developmental biology, and engineering in concert with the self-organization approach to tissue regeneration.

  2. Self-organization at the frictional interface for green tribology.

    Science.gov (United States)

    Nosonovsky, Michael

    2010-10-28

    Despite the fact that self-organization during friction has received relatively little attention from tribologists so far, it has the potential for the creation of self-healing and self-lubricating materials, which are important for green or environment-friendly tribology. The principles of the thermodynamics of irreversible processes and of the nonlinear theory of dynamical systems are used to investigate the formation of spatial and temporal structures during friction. The transition to the self-organized state with low friction and wear occurs through destabilization of steady-state (stationary) sliding. The criterion for destabilization is formulated and several examples are discussed: the formation of a protective film, microtopography evolution and slip waves. The pattern formation may involve self-organized criticality and reaction-diffusion systems. A special self-healing mechanism may be embedded into the material by coupling the corresponding required forces. The analysis provides the structure-property relationship, which can be applied for the design optimization of composite self-lubricating and self-healing materials for various ecologically friendly applications and green tribology.

  3. Innovative Mechanism of Rural Organization Based on Self-Organization

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    The paper analyzes the basic situation of the formation of innovative rural organizations with the form of self-organization;reveals the features of self-organization,including the four aspects of openness of rural organization,innovation of rural organization far away from equilibrium,the non-linear response mechanism of rural organization innovation and the random rise and fall of rural organization innovation.The evolution mechanism of rural organization innovation is revealed according to the growth stage,the ideal stage,the decline and the fall stage.The paper probes into the basic restriction mechanism of the self-organization evaluation of rural organization from three aspects,including target recognition,path dependence and knowledge sharing.The basic measures on cultivating the innovative mechanism of rural organization are put forward.Firstly,constructing the dissipative structure of rural organization innovation;secondly,cultivating the dynamic study capability of rural organization innovation system;thirdly,selecting the step-by-step evolution strategy of rural organization innovation system.

  4. Self-organization without conservation: are neuronal avalanches generically critical?

    Science.gov (United States)

    Bonachela, Juan A.; de Franciscis, Sebastiano; Torres, Joaquín J.; Muñoz, Miguel A.

    2010-02-01

    Recent experiments on cortical neural networks have revealed the existence of well-defined avalanches of electrical activity. Such avalanches have been claimed to be generically scale invariant—i.e. power law distributed—with many exciting implications in neuroscience. Recently, a self-organized model has been proposed by Levina, Herrmann and Geisel to explain this empirical finding. Given that (i) neural dynamics is dissipative and (ii) there is a loading mechanism progressively 'charging' the background synaptic strength, this model/dynamics is very similar in spirit to forest-fire and earthquake models, archetypical examples of non-conserving self-organization, which have recently been shown to lack true criticality. Here we show that cortical neural networks obeying (i) and (ii) are not generically critical; unless parameters are fine-tuned, their dynamics is either subcritical or supercritical, even if the pseudo-critical region is relatively broad. This conclusion seems to be in agreement with the most recent experimental observations. The main implication of our work is that, if future experimental research on cortical networks were to support the observation that truly critical avalanches are the norm and not the exception, then one should look for more elaborate (adaptive/evolutionary) explanations, beyond simple self-organization, to account for this.

  5. On modeling complex interplay in small-scale self-organized socio-hydrological systems

    Science.gov (United States)

    Muneepeerakul, Rachata

    2017-04-01

    Successful and sustainable socio-hydrological systems, as in any coupled natural human-systems, require effective governance, which depends on the existence of proper infrastructure (both hard and soft). Recent work has addressed systems in which resource users and the organization responsible for maintaining the infrastructure are separate entities. However, many socio-hydrological systems, especially in developing countries, are small and without such formal division of labor; rather, such division of labor typically arises from self-organization within the population. In this work, we modify and mathematically operationalize a conceptual framework by developing a system of differential equations that capture the strategic behavior within such a self-organized population, its interplay with infrastructure characteristics and hydrological dynamics, and feedbacks between these elements. The model yields a number of insightful conditions related to long-term sustainability and collapse of the socio-hydrological system in the form of relationships between biophysical and social factors. These relationships encapsulate nonlinear interactions of these factors. The modeling framework is grounded in a solid conceptual foundation upon which additional modifications and realism can be built for potential reconciliation between socio-hydrology with other related fields and further applications.

  6. Theoretical model for mesoscopic-level scale-free self-organization of functional brain networks.

    Science.gov (United States)

    Piersa, Jaroslaw; Piekniewski, Filip; Schreiber, Tomasz

    2010-11-01

    In this paper, we provide theoretical and numerical analysis of a geometric activity flow network model which is aimed at explaining mathematically the scale-free functional graph self-organization phenomena emerging in complex nervous systems at a mesoscale level. In our model, each unit corresponds to a large number of neurons and may be roughly seen as abstracting the functional behavior exhibited by a single voxel under functional magnetic resonance imaging (fMRI). In the course of the dynamics, the units exchange portions of formal charge, which correspond to waves of activity in the underlying microscale neuronal circuit. The geometric model abstracts away the neuronal complexity and is mathematically tractable, which allows us to establish explicit results on its ground states and the resulting charge transfer graph modeling functional graph of the network. We show that, for a wide choice of parameters and geometrical setups, our model yields a scale-free functional connectivity with the exponent approaching 2, which is in agreement with previous empirical studies based on fMRI. The level of universality of the presented theory allows us to claim that the model does shed light on mesoscale functional self-organization phenomena of the nervous system, even without resorting to closer details of brain connectivity geometry which often remain unknown. The material presented here significantly extends our previous work where a simplified mean-field model in a similar spirit was constructed, ignoring the underlying network geometry.

  7. Epithelial self-organization in fruit fly embryogenesis

    Science.gov (United States)

    Hutson, M. Shane

    2010-03-01

    During fruit fly embryogenesis, there are several morphogenetic events in which sheets of epithelial cells expand, contract and bend due to coordinated intra- and intercellular forces. This tissue-level reshaping is accompanied by changes in the shape and arrangement of individual cells -- changes that can be measured quantitatively and dynamically using modern live-cell imaging techniques. Such data sets represent rich targets for computational modeling of self-organization; however, reproducing the observed cell- and tissue-level reshaping is not enough. The inverse problem of using cell shape changes to determine cell-level forces is ill-posed -- yielding non-unique solutions that cannot discriminate between active changes in cell shape and passive deformation. These non-unique solutions can be tested experimentally using in vivo laser-microsurgery -- i.e., cutting a targeted region of an epithelium and carefully tracking the temporal and spatial dependence of the subsequent strain relaxation. This technique uses a variety of incisions (hole, line or closed curve) to probe different aspects of epithelial mechanics: the local mesoscopic strain; the distribution of intracellular forces; changes in the cell-level power-law rheology; and the question of active versus passive deformation. I will discuss my group's work using laser-microsurgery to investigate two morphogenetic events in fruit fly embryogenesis: germband retraction and dorsal closure. In both cases, we find a substantial active mechanical role for the amnioserosa -- an epithelium that undergoes apoptosis near the end of embryogenesis and makes no part of the fly larva -- in reshaping an adjacent epithelium that becomes the larval epidermis. In these examples, self-organization of the fly embryo relies not only on self-organization of individual tissues, but also on the mechanical interactions between tissues.

  8. Growth and self-organization of SiGe nanostructures

    Energy Technology Data Exchange (ETDEWEB)

    Aqua, J.-N., E-mail: aqua@insp.jussieu.fr [Institut des Nanosciences de Paris, Université Pierre et Marie Curie Paris 6 and CNRS UMR 7588, 4 place Jussieu, 75252 Paris (France); Berbezier, I., E-mail: isabelle.berbezier@im2np.fr [Institut Matériaux Microélectronique Nanoscience de Provence, Aix-Marseille Université, UMR CNRS 6242, 13997 Marseille (France); Favre, L. [Institut Matériaux Microélectronique Nanoscience de Provence, Aix-Marseille Université, UMR CNRS 6242, 13997 Marseille (France); Frisch, T. [Institut Non Linéaire de Nice, Université de Nice Sophia Antipolis, UMR CNRS 6618, 1361 routes des Lucioles, 06560 Valbonne (France); Ronda, A. [Institut Matériaux Microélectronique Nanoscience de Provence, Aix-Marseille Université, UMR CNRS 6242, 13997 Marseille (France)

    2013-01-01

    Many recent advances in microelectronics would not have been possible without the development of strain induced nanodevices and bandgap engineering, in particular concerning the common SiGe system. In this context, a huge amount of literature has been devoted to the growth and self-organization of strained nanostructures. However, even if an overall picture has been drawn out, the confrontation between theories and experiments is still, under various aspects, not fully satisfactory. The objective of this review is to present a state-of-the-art of theoretical concepts and experimental results on the spontaneous formation and self-organization of SiGe quantum dots on silicon substrates. The goal is to give a comprehensive overview of the main experimental results on the growth and long time evolution of these dots together with their morphological, structural and compositional properties. We also aim at describing the basis of the commonly used thermodynamic and kinetic models and their recent refinements. The review covers the thermodynamic theory for different levels of elastic strain, but focuses also on the growth dynamics of SiGe quantum dots in several experimental circumstances. The strain driven kinetically promoted instability, which is the main form of instability encountered in the epitaxy of SiGe nanostructures at low strain, is described. Recent developments on its continuum description based on a non-linear analysis particularly useful for studying self-organization and coarsening are described together with other theoretical frameworks. The kinetic evolution of the elastic relaxation, island morphology and film composition are also extensively addressed. Theoretical issues concerning the formation of ordered island arrays on a pre-patterned substrate, which is governed both by equilibrium ordering and kinetically-controlled ordering, are also reported in connection with the experimental results for the fabrication technology of ordered arrays of Si

  9. Self-Organization in Integrated Conservation and Development Initiatives

    Directory of Open Access Journals (Sweden)

    Cristiana Simão Seixas

    2007-11-01

    Full Text Available This paper uses a cooking metaphor to explore key elements (i.e., ingredients for a great meal that contribute to self-organization processes in the context of successful community-based conservation (CBC or integrated conservation and development projects (ICDP. We pose two major questions: (1 What are the key factors that drive peoples' and/or organizations' willingness to take responsibilities and to act? (2 What contributes to community self-organization? In other words, how conservation-development projects originate, evolve, survive or disappear? In order to address these questions we examine trigger events and catalytic elements in several cases among the Equator Prize finalists and short-listed nominees, from both the 2002 and 2004 awards. The Prize recognizes efforts in integrating biodiversity conservation and poverty reduction. We use secondary data in our analysis, including data from several technical reports and scientific papers written about the Equator Prize finalists and short-listed nominees. We observed common ingredients in most projects including: (1 involvement and commitment of key players (including communities, (2 funding, (3 strong leadership, (4 capacity building, (5 partnership with supportive organizations and government, and (6 economic incentives (including alternative livelihood options. We also observed that CBC and ICDP initiatives opportunistically evolve in a multi-level world, in which local communities establish linkages with people and organizations at different political levels, across different geographical scales and for different purposes. We conclude that there is no right 'recipe' to promote community self-organization but often a mix of some of these six ingredients need to come together for 'success' and that one or two ingredients are not sufficient to ensure success. Also the existence of these six ingredients does not guarantee a great meal - the 'chef's' creativity also is critical. That is

  10. Global self-organization of the cellular metabolic structure.

    Directory of Open Access Journals (Sweden)

    Ildefonso M De La Fuente

    Full Text Available BACKGROUND: Over many years, it has been assumed that enzymes work either in an isolated way, or organized in small catalytic groups. Several studies performed using "metabolic networks models" are helping to understand the degree of functional complexity that characterizes enzymatic dynamic systems. In a previous work, we used "dissipative metabolic networks" (DMNs to show that enzymes can present a self-organized global functional structure, in which several sets of enzymes are always in an active state, whereas the rest of molecular catalytic sets exhibit dynamics of on-off changing states. We suggested that this kind of global metabolic dynamics might be a genuine and universal functional configuration of the cellular metabolic structure, common to all living cells. Later, a different group has shown experimentally that this kind of functional structure does, indeed, exist in several microorganisms. METHODOLOGY/PRINCIPAL FINDINGS: Here we have analyzed around 2.500.000 different DMNs in order to investigate the underlying mechanism of this dynamic global configuration. The numerical analyses that we have performed show that this global configuration is an emergent property inherent to the cellular metabolic dynamics. Concretely, we have found that the existence of a high number of enzymatic subsystems belonging to the DMNs is the fundamental element for the spontaneous emergence of a functional reactive structure characterized by a metabolic core formed by several sets of enzymes always in an active state. CONCLUSIONS/SIGNIFICANCE: This self-organized dynamic structure seems to be an intrinsic characteristic of metabolism, common to all living cellular organisms. To better understand cellular functionality, it will be crucial to structurally characterize these enzymatic self-organized global structures.

  11. Action-Amplitude Approach to Controlled Entropic Self-Organization

    Directory of Open Access Journals (Sweden)

    Vladimir Ivancevic

    2014-05-01

    Full Text Available Motivated by the notion of perceptual error, as a core concept of the perceptual control theory, we propose an action-amplitude model for controlled entropic self-organization (CESO. We present several aspects of this development that illustrate its explanatory power: (i a physical view of partition functions and path integrals, as well as entropy and phase transitions; (ii a global view of functional compositions and commutative diagrams; (iii a local geometric view of the Kähler–Ricci flow and time-evolution of entropic action; and (iv a computational view using various path-integral approximations.

  12. Context, Specificity, and Self-Organization in Auxin Response

    Science.gov (United States)

    Del Bianco, Marta; Kepinski, Stefan

    2011-01-01

    Auxin is a simple molecule with a remarkable ability to control plant growth, differentiation, and morphogenesis. The mechanistic basis for this versatility appears to stem from the highly complex nature of the networks regulating auxin metabolism, transport and response. These heavily feedback-regulated and inter-dependent mechanisms are complicated in structure and complex in operation giving rise to a system with self-organizing properties capable of generating highly context-specific responses to auxin as a single, generic signal. PMID:21047914

  13. Self-organized periodic lattices of chaotic defects

    CERN Document Server

    Willeboordse, F H; Frederick H Willeboordse; Kunihiko Kaneko

    1994-01-01

    A novel type of self-organized lattice in which chaotic defects are arranged periodically is reported for a coupled map model of open flow. We find that temporally chaotic defects are followed by spatial relaxation to an almost periodic state when suddenly a next defect appears. The distance between successive defects is found to be generally predetermined and diverging logarithmically when approaching a certain critical point. The phenomena are analyzed and shown to be explicable as the results of a boundary crisis for the spatially extended system.

  14. Self-Organizing Maps for Fingerprint Image Quality Assessment

    DEFF Research Database (Denmark)

    Olsen, Martin Aastrup; Tabassi, Elham; Makarov, Anton

    2013-01-01

    machine learning techniques. We train a self-organizing map (SOM) to cluster blocks of fingerprint images based on their spatial information content. The output of the SOM is a high-level representation of the finger image, which forms the input to a Random Forest trained to learn the relationship between...... and identification of individuals). Measuring and reporting quality allows processing enhancements to increase probability of detection and track accuracy while decreasing probability of false alarms. Aside from predictive capabilities with respect to the recognition performance, another important design criteria...

  15. Turbulence and Self-Organization Modeling Astrophysical Objects

    CERN Document Server

    Marov, Mikhail Ya

    2013-01-01

    This book focuses on the development of continuum models of natural turbulent media. It provides a theoretical approach to the solutions of different problems related to the formation, structure and evolution of astrophysical and geophysical objects. A stochastic modeling approach is used in the mathematical treatment of these problems, which reflects self-organization processes in open dissipative systems. The authors also consider examples of ordering for various objects in space throughout their evolutionary processes. This volume is aimed at graduate students and researchers in the fields of mechanics, astrophysics, geophysics, planetary and space science.

  16. Self-organizing migrating algorithm methodology and implementation

    CERN Document Server

    Zelinka, Ivan

    2016-01-01

    This book brings together the current state of-the-art research in Self Organizing Migrating Algorithm (SOMA) as a novel population-based evolutionary algorithm, modeled on the predator-prey relationship, by its leading practitioners. As the first ever book on SOMA, this book is geared towards graduate students, academics and researchers, who are looking for a good optimization algorithm for their applications. This book presents the methodology of SOMA, covering both the real and discrete domains, and its various implementations in different research areas. The easy-to-follow and implement methodology used in the book will make it easier for a reader to implement, modify and utilize SOMA. .

  17. Self-organized criticality in MHD driven plasma edge turbulence

    Energy Technology Data Exchange (ETDEWEB)

    Santos Lima, G.Z. dos, E-mail: gzampier@ect.ufrn.br [Escola de Ciências e Tecnologia, Universidade Federal do Rio Grande do Norte, 59014-615, Natal, RN (Brazil); Iarosz, K.C.; Batista, A.M. [Programa de Pós-Graduação em Física, Universidade Estadual de Ponta Grossa, 84030-900, Ponta Grossa, PR (Brazil); Caldas, I.L. [Instituto de Física, Universidade de São Paulo, 05508-090, SP (Brazil); Guimarães-Filho, Z.O. [IIFS/PIIM, Université de Provence (France); Viana, R.L.; Lopes, S.R. [Departamento de Física, Universidade Federal do Paraná, 81531-990, Curitiba, PR (Brazil); Nascimento, I.C.; Kuznetsov, Yu.K. [Instituto de Física, Universidade de São Paulo, 05508-090, SP (Brazil)

    2012-01-16

    We analyze long-range time correlations and self-similar characteristics of the electrostatic turbulence at the plasma edge and scrape-off layer in the Tokamak Chauffage Alfvén Brésillien (TCABR), with low and high Magnetohydrodynamics (MHD) activity. We find evidence of self-organized criticality (SOC), mainly in the region near the tokamak limiter. Comparative analyses of data before and during the MHD activity reveals that during the high MHD activity the Hurst parameter decreases. Finally, we present a cellular automaton whose parameters are adjusted to simulate the analyzed turbulence SOC change with the MHD activity variation. -- Highlights: ► We analyze time correlations of the electrostatic turbulence in plasma. ► We study self-similar characteristics with low and high magnetohydrodynamics activity. ► We find evidence of self-organized criticality (SOC) behavior. ► SOC behavior is pronounced close to radial positions just after the limiter. ► We present a cellular automata that simulate the analyzed turbulence.

  18. Attitudes and the Self as Self-Organizing Systems

    Science.gov (United States)

    Eiser, J. Richard

    This paper considers how conventional theories of attitudes and the self may be reconceptualized from the perspective of chaos theory and work on self-organization. Within attitude theory, there has been a long tradition of research that has treated attitudes as single points on a bipolar evaluative continuum. More recent approaches to attitudes treat attitudes as structures of evaluative associations stored in memory (Fazio, 1990). This work can be linked to chaos theory by regarding attitudes as attractors (Eiser, 1994) within a phase space whose dimensions correspond broadly to features of the attitude object and its context and which is contoured by previous and concurrent associative learning Specifically, it is proposed that attractors are laid down through processes of association. such as may be simulated through connectionist, or parallel distributed processing, systems. Associative learning and memory processes also are implicated in our concept of self, linking with the philosophy of Hume and contemporary research on interactive models of personality (Mischel & Shoda, 1995). Speculatively, it is suggested that consciousness involves representation of the self within a patterned (i.e. self-organized) environment.

  19. Ice Shape Characterization Using Self-Organizing Maps

    Science.gov (United States)

    McClain, Stephen T.; Tino, Peter; Kreeger, Richard E.

    2011-01-01

    A method for characterizing ice shapes using a self-organizing map (SOM) technique is presented. Self-organizing maps are neural-network techniques for representing noisy, multi-dimensional data aligned along a lower-dimensional and possibly nonlinear manifold. For a large set of noisy data, each element of a finite set of codebook vectors is iteratively moved in the direction of the data closest to the winner codebook vector. Through successive iterations, the codebook vectors begin to align with the trends of the higher-dimensional data. In information processing, the intent of SOM methods is to transmit the codebook vectors, which contains far fewer elements and requires much less memory or bandwidth, than the original noisy data set. When applied to airfoil ice accretion shapes, the properties of the codebook vectors and the statistical nature of the SOM methods allows for a quantitative comparison of experimentally measured mean or average ice shapes to ice shapes predicted using computer codes such as LEWICE. The nature of the codebook vectors also enables grid generation and surface roughness descriptions for use with the discrete-element roughness approach. In the present study, SOM characterizations are applied to a rime ice shape, a glaze ice shape at an angle of attack, a bi-modal glaze ice shape, and a multi-horn glaze ice shape. Improvements and future explorations will be discussed.

  20. The Self-Organized Archive: SPASE, PDS and Archive Cooperatives

    Science.gov (United States)

    King, T. A.; Hughes, J. S.; Roberts, D. A.; Walker, R. J.; Joy, S. P.

    2005-05-01

    Information systems with high quality metadata enable uses and services which often go beyond the original purpose. There are two types of metadata: annotations which are items that comment on or describe the content of a resource and identification attributes which describe the external properties of the resource itself. For example, annotations may indicate which columns are present in a table of data, whereas an identification attribute would indicate source of the table, such as the observatory, instrument, organization, and data type. When the identification attributes are collected and used as the basis of a search engine, a user can constrain on an attribute, the archive can then self-organize around the constraint, presenting the user with a particular view of the archive. In an archive cooperative where each participating data system or archive may have its own metadata standards, providing a multi-system search engine requires that individual archive metadata be mapped to a broad based standard. To explore how cooperative archives can form a larger self-organized archive we will show how the Space Physics Archive Search and Extract (SPASE) data model will allow different systems to create a cooperative and will use Planetary Data System (PDS) plus existing space physics activities as a demonstration.

  1. SELF-ORGANIZATION OF LEAD SULFIDE QUANTUM DOTS INTO SUPERSTRUCTURES

    Directory of Open Access Journals (Sweden)

    Elena V. Ushakova

    2014-11-01

    Full Text Available The method of X-ray structural analysis (X-ray scattering at small angles is used to show that the structures obtained by self-organization on a substrate of lead sulfide (PbS quantum dots are ordered arrays. Self-organization of quantum dots occurs at slow evaporation of solvent from a cuvette. The cuvette is a thin layer of mica with teflon ring on it. The positions of peaks in SAXS pattern are used to calculate crystal lattice of obtained ordered structures. Such structures have a primitive orthorhombic crystal lattice. Calculated lattice parameters are: a = 21,1 (nm; b = 36,2 (nm; c = 62,5 (nm. Dimensions of structures are tens of micrometers. The spectral properties of PbS QDs superstructures and kinetic parameters of their luminescence are investigated. Absorption band of superstructures is broadened as compared to the absorption band of the quantum dots in solution; the luminescence band is slightly shifted to the red region of the spectrum, while its bandwidth is not changed much. Luminescence lifetime of obtained structures has been significantly decreased in comparison with the isolated quantum dots in solution, but remained the same for the lead sulfide quantum dots close-packed ensembles. Such superstructures can be used to produce solar cells with improved characteristics.

  2. Macromolecular target prediction by self-organizing feature maps.

    Science.gov (United States)

    Schneider, Gisbert; Schneider, Petra

    2017-03-01

    Rational drug discovery would greatly benefit from a more nuanced appreciation of the activity of pharmacologically active compounds against a diverse panel of macromolecular targets. Already, computational target-prediction models assist medicinal chemists in library screening, de novo molecular design, optimization of active chemical agents, drug re-purposing, in the spotting of potential undesired off-target activities, and in the 'de-orphaning' of phenotypic screening hits. The self-organizing map (SOM) algorithm has been employed successfully for these and other purposes. Areas covered: The authors recapitulate contemporary artificial neural network methods for macromolecular target prediction, and present the basic SOM algorithm at a conceptual level. Specifically, they highlight consensus target-scoring by the employment of multiple SOMs, and discuss the opportunities and limitations of this technique. Expert opinion: Self-organizing feature maps represent a straightforward approach to ligand clustering and classification. Some of the appeal lies in their conceptual simplicity and broad applicability domain. Despite known algorithmic shortcomings, this computational target prediction concept has been proven to work in prospective settings with high success rates. It represents a prototypic technique for future advances in the in silico identification of the modes of action and macromolecular targets of bioactive molecules.

  3. Self-organizing map classifier for stressed speech recognition

    Science.gov (United States)

    Partila, Pavol; Tovarek, Jaromir; Voznak, Miroslav

    2016-05-01

    This paper presents a method for detecting speech under stress using Self-Organizing Maps. Most people who are exposed to stressful situations can not adequately respond to stimuli. Army, police, and fire department occupy the largest part of the environment that are typical of an increased number of stressful situations. The role of men in action is controlled by the control center. Control commands should be adapted to the psychological state of a man in action. It is known that the psychological changes of the human body are also reflected physiologically, which consequently means the stress effected speech. Therefore, it is clear that the speech stress recognizing system is required in the security forces. One of the possible classifiers, which are popular for its flexibility, is a self-organizing map. It is one type of the artificial neural networks. Flexibility means independence classifier on the character of the input data. This feature is suitable for speech processing. Human Stress can be seen as a kind of emotional state. Mel-frequency cepstral coefficients, LPC coefficients, and prosody features were selected for input data. These coefficients were selected for their sensitivity to emotional changes. The calculation of the parameters was performed on speech recordings, which can be divided into two classes, namely the stress state recordings and normal state recordings. The benefit of the experiment is a method using SOM classifier for stress speech detection. Results showed the advantage of this method, which is input data flexibility.

  4. Field theory of self-organized fractal etching.

    Science.gov (United States)

    Gabrielli, A; Muñoz, M A; Sapoval, B

    2001-07-01

    We propose a phenomenological field theoretical approach to the chemical etching of a disordered solid. The theory is based on a recently proposed dynamical etching model. Through the introduction of a set of Langevin equations for the model evolution, we are able to map the problem into a field theory related to isotropic percolation. To the best of the author's knowledge, this constitutes the first application of field theory to a problem of chemical dynamics. By using this mapping, many of the etching process critical properties are seen to be describable in terms of the percolation renormalization group fixed point. The emerging field theory has the peculiarity of being self-organized in the sense that without any parameter fine tuning the system develops fractal properties up to a certain scale controlled solely by the volume V of the etching solution. In the limit V-->infinity the upper cutoff goes to infinity and the system becomes scale invariant. We present also a finite size scaling analysis and discuss the relation of this particular etching mechanism to gradient percolation. Finally, the possibility of considering this mechanism as a generic path to self-organized criticality is analyzed, with the characteristics of being closely related to a real physical system and therefore more directly accessible to experiments.

  5. Self-Organizing Hidden Markov Model Map (SOHMMM).

    Science.gov (United States)

    Ferles, Christos; Stafylopatis, Andreas

    2013-12-01

    A hybrid approach combining the Self-Organizing Map (SOM) and the Hidden Markov Model (HMM) is presented. The Self-Organizing Hidden Markov Model Map (SOHMMM) establishes a cross-section between the theoretic foundations and algorithmic realizations of its constituents. The respective architectures and learning methodologies are fused in an attempt to meet the increasing requirements imposed by the properties of deoxyribonucleic acid (DNA), ribonucleic acid (RNA), and protein chain molecules. The fusion and synergy of the SOM unsupervised training and the HMM dynamic programming algorithms bring forth a novel on-line gradient descent unsupervised learning algorithm, which is fully integrated into the SOHMMM. Since the SOHMMM carries out probabilistic sequence analysis with little or no prior knowledge, it can have a variety of applications in clustering, dimensionality reduction and visualization of large-scale sequence spaces, and also, in sequence discrimination, search and classification. Two series of experiments based on artificial sequence data and splice junction gene sequences demonstrate the SOHMMM's characteristics and capabilities. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. Self-organization of multivalent counterions in polyelectrolyte brushes

    Science.gov (United States)

    Wu, Jianzhong

    2013-03-01

    The structure and interfacial properties of a polyelectrolyte brush (PEB) depend on a broad range of parameters such as the polymer charge and grafting density, counterion valence, salt concentration, and solvent conditions. These properties are of fundamental importance in technological applications of PEBs including colloid stabilization, surface modification and lubrication, and in functioning of biological systems such as genome packaging in single-strand DNA/RNA viruses. Despite intensive studies by experiments, molecular simulations, and myriad analytical methods including scaling analyses, self-consistent-field theory, and most recently density functional theory, the behavior of PEBs in the presence of multivalent counterions remains poorly understood. In this talk, I will present a density functional method for polyelectrolyte brushes and discuss self-organization of multivalent counterions within highly charged polyelectrolyte brushes. The counterion-mediated attraction between polyions leads to a first-order phase transition similar to that for a neutral brush in a poor solvent. The self-organization of multivalent counterions results in a wavelike electrostatic potential and charge density that oscillate between positive and negative values.

  7. Modeling multisensory enhancement with self-organizing maps

    Directory of Open Access Journals (Sweden)

    Jacob G Martin

    2009-06-01

    Full Text Available Self-organization, a process by which the internal organization of a system changes without supervision, has been proposed as a possible basis for multisensory enhancement in the superior colliculus (Anastasio and Patton 2003. We simplify and extend these results by presenting a simulation using traditional self-organizing maps, intended to understand and simulate multisensory enhancement as it may generally occur throughout the central nervous system. This simulation of multisensory enhancement: 1 uses a standard unsupervised competitive learning algorithm, 2 learns from artificially generated activation levels corresponding to driven and spontaneous stimuli from separate and combined input channels, 3 uses a sigmoidal transfer function to generate quantifiable responses to separate inputs, 4 enhances the responses when those same inputs are combined, 5 obeys the inverse effectiveness principle of multisensory integration, and 6 can topographically congregate multisensory enhancement in a manner similar to that seen in cortex. Thus, the model provides a useful method for evaluating and simulating the development of enhanced interactions between responses to different sensory modalities.

  8. Is there a self-organization principle of river deltas?

    Science.gov (United States)

    Tejedor, Alejandro; Longjas, Anthony; Foufoula-Georgiou, Efi

    2017-04-01

    River deltas are known to possess a complex topological and flux-partitioning structure which has recently been quantified using spectral graph theory [Tejedor et al., 2015a,b]. By analysis of real and simulated deltas it has also been shown that there is promise in formalizing relationships between this topo-dynamic delta structure and the underlying delta forming processes [e.g., Tejedor et al., 2016]. The question we pose here is whether there exists a first order organizational principle behind the self-organization of river deltas and whether this principle can be unraveled from the co-evolving topo-dynamic structure encoded in the delta planform. To answer this question, we introduce a new metric, the nonlocal Entropy Rate (nER) that captures the information content of a delta network in terms of the degree of uncertainty in delivering fluxes from any point of the network to the shoreline. We hypothesize that if the "guiding principle" of undisturbed deltas is to efficiently and robustly build land by increasing the diversity of their flux pathways over the delta plane, then they would exhibit maximum nonlocal Entropy Rate at states at which geometry and flux dynamics are at equilibrium. At the same time, their nER would be non-optimal at transient states, such as before and after major avulsions during which topology and dynamics adjust to each other to reach a new equilibrium state. We will present our results for field and simulated deltas, which confirm this hypothesis and open up new ways of thinking about self-organization, complexity and robustness in river deltas. One particular connection of interest might have important implications since entropy rate and resilience are related by the fluctuation theorem [Demetrius and Manke, 2005], and therefore our results suggest that deltas might in fact self-organize to maximize their resilience to structural and dynamic perturbations. References: Tejedor, A., A. Longjas, I. Zaliapin, and E. Foufoula

  9. Self-Organized Behavior Generation for Musculoskeletal Robots

    Science.gov (United States)

    Der, Ralf; Martius, Georg

    2017-01-01

    With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors “waiting” to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self

  10. An analytical method to assess the damage and predict the residual strength of a ship in a shoal grounding accident scenario

    Directory of Open Access Journals (Sweden)

    Sun Bin

    2016-04-01

    Full Text Available In this paper, a simplified analytical method used to predict the residual ultimate strength of a ship hull after a shoal grounding accident is proposed. Shoal grounding accidents always lead to severe denting, though not tearing, of the ship bottom structure, which may threaten the global hull girder resistance and result in even worse consequences, such as hull collapse. Here, the degree of damage of the bottom structure is predicted by a series of analytical methods based on the plastic-elastic deformation mechanism. The energy dissipation of a ship bottom structure is obtained from individual components to determine the sliding distance of the seabed obstruction. Then, a new approach to assess the residual strength of the damaged ship subjected to shoal grounding is proposed based on the improved Smith's method. This analytical method is verified by comparing the results of the proposed method and those generated by numerical simulation using the software ABAQUS. The proposed analytical method can be used to assess the safety of a ship with a double bottom during its design phase and predict the residual ultimate strength of a ship after a shoal grounding accident occurs.

  11. Design Methodology for Self-organized Mobile Networks Based

    Directory of Open Access Journals (Sweden)

    John Petearson Anzola

    2016-06-01

    Full Text Available The methodology proposed in this article enables a systematic design of routing algorithms based on schemes of biclustering, which allows you to respond with timely techniques, clustering heuristics proposed by a researcher, and a focused approach to routing in the choice of clusterhead nodes. This process uses heuristics aimed at improving the different costs in communication surface groups called biclusters. This methodology globally enables a variety of techniques and heuristics of clustering that have been addressed in routing algorithms, but we have not explored all possible alternatives and their different assessments. Therefore, the methodology oriented design research of routing algorithms based on biclustering schemes will allow new concepts of evolutionary routing along with the ability to adapt the topological changes that occur in self-organized data networks.

  12. Self-Organization of Mobile Populations in Cyclic Competition

    CERN Document Server

    Reichenbach, Tobias; Frey, Erwin

    2008-01-01

    The formation of out-of-equilibrium patterns is a characteristic feature of spatially-extended, biodiverse, ecological systems. Intriguing examples are provided by cyclic competition of species, as metaphorically described by the `rock-paper-scissors' game. Both experimentally and theoretically, such non-transitive interactions have been found to induce self-organization of static individuals into noisy, irregular clusters. However, a profound understanding and characterization of such patterns is still lacking. Here, we theoretically investigate the influence of individuals' mobility on the spatial structures emerging in rock-paper-scissors games. We devise a quantitative approach to analyze the spatial patterns self-forming in the course of the stochastic time evolution. For a paradigmatic model originally introduced by May and Leonard, within an interacting particle approach, we demonstrate that the system's behavior - in the proper continuum limit - is aptly captured by a set of stochastic partial differe...

  13. Characterization of suicidal behaviour with self-organizing maps.

    Science.gov (United States)

    Leiva-Murillo, José M; López-Castromán, Jorge; Baca-García, Enrique

    2013-01-01

    The study of the variables involved in suicidal behavior is important from a social, medical, and economical point of view. Given the high number of potential variables of interest, a large population of subjects must be analysed in order to get conclusive results. In this paper, we describe a method based on self-organizing maps (SOMs) for finding the most relevant variables even when their relation to suicidal behavior is strongly nonlinear. We have applied the method to a cohort with more than 8,000 subjects and 600 variables and discovered four groups of variables involved in suicidal behavior. According to the results, there are four main groups of risk factors that characterize the population of suicide attempters: mental disorders, alcoholism, impulsivity, and childhood abuse. The identification of specific subpopulations of suicide attempters is consistent with current medical knowledge and may provide a new avenue of research to improve the management of suicidal cases.

  14. Self-organizing magnetic beads for biomedical applications

    CERN Document Server

    Gusenbauer, Markus; Reichel, Franz; Exl, Lukas; Bance, Simon; Ozelt, Harald; Schrefl, Thomas

    2011-01-01

    In the field of biomedicine magnetic beads are used for drug delivery and to treat hyperthermia. Here we propose to use self-organized bead structures to isolate circulating tumor cells using lab-on-chip technologies. Typically blood flows past microposts functionalized with antibodies for circulating tumor cells. Creating these microposts with interacting magnetic beads makes it possible to tune the geometry in size, position and shape. We developed a simulation tool that combines micromagnetics and discrete particle dynamics, in order to design micropost arrays made of interacting beads. The simulation takes into account the viscous drag of the blood flow, magnetostatic interactions between the magnetic beads and gradient forces from external aligned magnets. We developed a particle-particle particle-mesh method for effective computation of the magnetic force and torque acting on the particles.

  15. Self-organized global control of carbon emissions

    Science.gov (United States)

    Zhao, Zhenyuan; Fenn, Daniel J.; Hui, Pak Ming; Johnson, Neil F.

    2010-09-01

    There is much disagreement concerning how best to control global carbon emissions. We explore quantitatively how different control schemes affect the collective emission dynamics of a population of emitting entities. We uncover a complex trade-off which arises between average emissions (affecting the global climate), peak pollution levels (affecting citizens’ everyday health), industrial efficiency (affecting the nation’s economy), frequency of institutional intervention (affecting governmental costs), common information (affecting trading behavior) and market volatility (affecting financial stability). Our findings predict that a self-organized free-market approach at the level of a sector, state, country or continent can provide better control than a top-down regulated scheme in terms of market volatility and monthly pollution peaks. The control of volatility also has important implications for any future derivative carbon emissions market.

  16. A Language as a Self-Organized Critical System

    Directory of Open Access Journals (Sweden)

    Vasilii A. Gromov

    2017-01-01

    Full Text Available A natural language (represented by texts generated by native speakers is considered as a complex system, and the type thereof to which natural languages belong is ascertained. Namely, the authors hypothesize that a language is a self-organized critical system and that the texts of a language are “avalanches” flowing down its word cooccurrence graph. The respective statistical characteristics for distributions of the number of words in the texts of English and Russian languages are calculated; the samples were constructed on the basis of corpora of literary texts and of a set of social media messages (as a substitution to the oral speech. The analysis found that the number of words in the texts obeys power-law distribution.

  17. Modelling Financial Markets by Self-Organized Criticality

    CERN Document Server

    Biondo, A E; Rapisarda, A

    2015-01-01

    We present a financial market model, characterized by self-organized criticality, that is able to generate endogenously a realistic price dynamics and to reproduce well-known stylized facts. We consider a community of heterogeneous traders, composed by chartists and fundamentalists, and focus on the role of informative pressure on market participants, showing how the spreading of information, based on a realistic imitative behavior, drives contagion and causes market fragility. In this model imitation is not intended as a change in the agent's group of origin, but is referred only to the price formation process. We introduce in the community also a variable number of random traders in order to study their possible beneficial role in stabilizing the market, as found in other studies. Finally we also suggest some counterintuitive policy strategies able to dampen fluctuations by means of a partial reduction of information.

  18. Features of self-organized plasma physics in tokamaks

    Science.gov (United States)

    Razumova, K. A.

    2018-01-01

    The history of investigations the role of self-organization processes in tokamak plasma confinement is presented. It was experimentally shown that the normalized pressure profile is the same for different tokamaks. Instead of the conventional Fick equation, where the thermal flux is proportional to a pressure gradient, processes in the plasma are well described by the Dyabilanin’s energy balance equation, in which the heat flux is proportional to the difference of normalized gradients for self-consistent and real pressure profiles. The transport coefficient depends on the values of heat flux, which compensates distortion of the pressure profile with external impacts. Radiative cooling of the plasma edge decreases the heat flux and improves the confinement.

  19. Characterization of Suicidal Behaviour with Self-Organizing Maps

    Directory of Open Access Journals (Sweden)

    José M. Leiva-Murillo

    2013-01-01

    Full Text Available The study of the variables involved in suicidal behavior is important from a social, medical, and economical point of view. Given the high number of potential variables of interest, a large population of subjects must be analysed in order to get conclusive results. In this paper, we describe a method based on self-organizing maps (SOMs for finding the most relevant variables even when their relation to suicidal behavior is strongly nonlinear. We have applied the method to a cohort with more than 8,000 subjects and 600 variables and discovered four groups of variables involved in suicidal behavior. According to the results, there are four main groups of risk factors that characterize the population of suicide attempters: mental disorders, alcoholism, impulsivity, and childhood abuse. The identification of specific subpopulations of suicide attempters is consistent with current medical knowledge and may provide a new avenue of research to improve the management of suicidal cases.

  20. A self-organized critical model for evolution

    Energy Technology Data Exchange (ETDEWEB)

    Flyvbjerg, H.; Bak, P.; Jensen, M.H.; Sneppen, K.

    1996-01-01

    A simple mathematical model of biological macroevolution is presented. It describes an ecology of adapting, interacting species. Species evolve to maximize their individual fitness in their environment. The environment of any given species is affected by other evolving species; hence it is not constant in time. The ecology evolves to a ``self-organized critical`` state where periods of stasis alternate with avalanches of causally connected evolutionary changes. This characteristic intermittent behaviour of natural history, known as ``punctuated equilibrium,`` thus finds a theoretical explanation as a selforganized critical phenomenon. In particular, large bursts of apparently simultaneous evolutionary activity require no external cause. They occur as the less frequent result of the very same dynamics that governs the more frequent small-scale evolutionary activity. Our results are compared with data from the fossil record collected by J. Sepkoski, Jr., and others.

  1. Self-organized instability in graded-index multimode fibre

    CERN Document Server

    Wright, Logan G; Nolan, Daniel A; Li, Ming-Jun; Christodoulides, Demetrios N; Wise, Frank W

    2016-01-01

    Multimode fibres (MMFs) are attracting interest for complex spatiotemporal dynamics, and for ultrafast fibre sources, imaging and telecommunications. This new interest is based on three key properties: their high spatiotemporal complexity (information capacity), the important role of disorder, and complex intermodal interactions. To date, phenomena in MMFs have been studied only in limiting cases where one or more of these properties can be neglected. Here we study MMFs in a regime in which all these elements are integral. We observe a spatial beam-cleaning process preceding spatiotemporal modulation instability. We show that the origin of these processes is a universal unstable attractor in graded-index MMFs. Both the self-organization of the attractor, as well as its instability, are caused by intermodal interactions characterized by cooperating disorder, nonlinearity and dissipation. The demonstration of a disorder-enhanced nonlinear process in MMF has important implications for telecommunications, and the...

  2. A Self-organized MIMO-OFDM-based Cellular Network

    Science.gov (United States)

    Grünheid, Rainer; Fellenberg, Christian

    2012-05-01

    This paper presents a system proposal for a self-organized cellular network, which is based on the MIMO-OFDM transmission technique. Multicarrier transmission, combined with appropriate beamforming concepts, yields high bandwidth-efficiency and shows a robust behavior in multipath radio channels. Moreover, it provides a fine and tuneable granularity of space-time-frequency resources. Using a TDD approach and interference measurements in each cell, the Base Stations (BSs) decide autonomously which of the space-time-frequency resource blocks are allocated to the Mobile Terminals (MTs) in the cell, in order to fulfil certain Quality of Service (QoS) parameters. Since a synchronized Single Frequency Network (SFN), i.e., a re-use factor of one is applied, the resource blocks can be shared adaptively and flexibly among the cells, which is very advantageous in the case of a non-uniform MT distribution.

  3. Self-organization of progress across the century of physics

    Science.gov (United States)

    Perc, Matjaž

    2013-04-01

    We make use of information provided in the titles and abstracts of over half a million publications that were published by the American Physical Society during the past 119 years. By identifying all unique words and phrases and determining their monthly usage patterns, we obtain quantifiable insights into the trends of physics discovery from the end of the 19th century to today. We show that the magnitudes of upward and downward trends yield heavy-tailed distributions, and that their emergence is due to the Matthew effect. This indicates that both the rise and fall of scientific paradigms is driven by robust principles of self-organization. Data also confirm that periods of war decelerate scientific progress, and that the later is very much subject to globalisation.

  4. Modeling financial markets by self-organized criticality

    Science.gov (United States)

    Biondo, Alessio Emanuele; Pluchino, Alessandro; Rapisarda, Andrea

    2015-10-01

    We present a financial market model, characterized by self-organized criticality, that is able to generate endogenously a realistic price dynamics and to reproduce well-known stylized facts. We consider a community of heterogeneous traders, composed by chartists and fundamentalists, and focus on the role of informative pressure on market participants, showing how the spreading of information, based on a realistic imitative behavior, drives contagion and causes market fragility. In this model imitation is not intended as a change in the agent's group of origin, but is referred only to the price formation process. We introduce in the community also a variable number of random traders in order to study their possible beneficial role in stabilizing the market, as found in other studies. Finally, we also suggest some counterintuitive policy strategies able to dampen fluctuations by means of a partial reduction of information.

  5. Traffic instabilities in self-organized pedestrian crowds.

    Directory of Open Access Journals (Sweden)

    Mehdi Moussaïd

    Full Text Available In human crowds as well as in many animal societies, local interactions among individuals often give rise to self-organized collective organizations that offer functional benefits to the group. For instance, flows of pedestrians moving in opposite directions spontaneously segregate into lanes of uniform walking directions. This phenomenon is often referred to as a smart collective pattern, as it increases the traffic efficiency with no need of external control. However, the functional benefits of this emergent organization have never been experimentally measured, and the underlying behavioral mechanisms are poorly understood. In this work, we have studied this phenomenon under controlled laboratory conditions. We found that the traffic segregation exhibits structural instabilities characterized by the alternation of organized and disorganized states, where the lifetime of well-organized clusters of pedestrians follow a stretched exponential relaxation process. Further analysis show that the inter-pedestrian variability of comfortable walking speeds is a key variable at the origin of the observed traffic perturbations. We show that the collective benefit of the emerging pattern is maximized when all pedestrians walk at the average speed of the group. In practice, however, local interactions between slow- and fast-walking pedestrians trigger global breakdowns of organization, which reduce the collective and the individual payoff provided by the traffic segregation. This work is a step ahead toward the understanding of traffic self-organization in crowds, which turns out to be modulated by complex behavioral mechanisms that do not always maximize the group's benefits. The quantitative understanding of crowd behaviors opens the way for designing bottom-up management strategies bound to promote the emergence of efficient collective behaviors in crowds.

  6. Self-organization of topological defects for a triangular-lattice magnetic dots array subject to a perpendicular magnetic field

    Directory of Open Access Journals (Sweden)

    R.S. Khymyn

    2014-09-01

    Full Text Available The regular array of magnetic particles (magnetic dots of the form of a two-dimensional triangular lattice in the presence of external magnetic field demonstrates complicated magnetic structures. The magnetic symmetry of the ground state for such a system is lower than that for the underlying lattice. Long range dipole-dipole interaction leads to a specific antiferromagnetic order in small fields, whereas a set of linear topological defects appears with the growth of the magnetic field. Self-organization of such defects determines the magnetization process for a system within a wide range of external magnetic fields.

  7. Low-Frequency Seismic Ground Motion At The Pier Positions Of The Planned Messina Straits Bridge For A Realistic Earthquake Scenario

    Science.gov (United States)

    Gusev, A. A.; Pavlov, V.; Romanelli, F.; Panza, G.

    2008-07-01

    We estimated longer-period (period T>0.5 s) components of the ground motion at the piers of the planned Messina straits bridge. As the shortest fault-to-site distance is only 3-5 km, the kinematic earthquake rupture process has to be described in a realistic way and thus, the causative fault is represented by a dense grid of subfaults. To model the 1908 event, we assume a Mw = 7 earthquake, with a 40×20 km rectangular fault, and pure reverse dip-slip. The horizontal upper side of the rectangle is at 3-km depth, and the N corner of the rectangle is just between the piers. For the fault nucleation point, the least favorable place is assumed and a randomized rupture velocity is used in a particular run. In a typical simulation, the fault motion is initially represented by the time history of slip in each of the subfaults and by the distribution of the final seismic moment among the subsources (forming "asperities"), both generated as lognormal random functions. The time histories are then filtered in order to fit a chosen source spectral model. The parameters that are conditioning the random functions can be based on the bulk of published fault inversions, or reproduced from an earlier successful attempt to simulate ground motions in the epicentral zone of the 1994, M = 6.7 Northridge, California, earthquake. In the second step of calculations, the Green functions (for each subfault and pier combination) are calculated for a layered halfspace model of the pier foundation stratigraphy, using an advanced Green function calculator, that allows an accurate calculation over the entire relevant frequency band including static terms. Finally, the 3-components of the strong ground motion are obtained at the two piers through convolution and summation over the different subsources. We compare a set of response horizontal velocity spectra (PRV) obtained from our calculations with a reference PRV that is considered as a reasonable upper bound for the possible ground motion near

  8. Two Levels of Self-Organization in the Earth's Climate System

    CERN Document Server

    Maslov, Lev A

    2013-01-01

    It is shown that global long-term temperature variations can be considered a sum of two components: the auto-oscillation component and the convective component, representing two different but tightly interconnected processes. The auto-oscillation and the convective components represent two different types of self-organization of the Earth's climate system. The self-organization in the auto-oscillation process is the non-linear reaction of the Earth's climate system, as a whole, to the extremely powerful input of solar radiation. The self-organization in the convective component is the self-organized nonlinear critical process taking energy from and fluctuating around the regular auto-oscillating component of the temperature variations. As a whole, the Earth's climate can be characterized as an open, nonlinear, dissipative, self-organized dynamic system with two levels of self-organization. The astronomical cycles and variations of solar activity are considered to be the perturbing factors and additional trigg...

  9. Photochemical model evaluation of the ground-level ozone impacts on ambient air quality and vegetation health in the Alberta oil sands region: Using present and future emission scenarios

    Science.gov (United States)

    Vijayaraghavan, Krish; Cho, Sunny; Morris, Ralph; Spink, David; Jung, Jaegun; Pauls, Ron; Duffett, Katherine

    2016-09-01

    One of the potential environmental issues associated with oil sands development is increased ozone formation resulting from NOX and volatile organic compound emissions from bitumen extraction, processing and upgrading. To manage this issue in the Athabasca Oil Sands Region (AOSR) in northeast Alberta, a regional multi-stakeholder group, the Cumulative Environmental Management Association (CEMA), developed an Ozone Management Framework that includes a modelling based assessment component. In this paper, we describe how the Community Multi-scale Air Quality (CMAQ) model was applied to assess potential ground-level ozone formation and impacts on ambient air quality and vegetation health for three different ozone precursor cases in the AOSR. Statistical analysis methods were applied, and the CMAQ performance results met the U.S. EPA model performance goal at all sites. The modelled 4th highest daily maximum 8-h average ozone concentrations in the base and two future year scenarios did not exceed the Canada-wide standard of 65 ppb or the newer Canadian Ambient Air Quality Standards of 63 ppb in 2015 and 62 ppb in 2020. Modelled maximum 1-h ozone concentrations in the study were well below the Alberta Ambient Air Quality Objective of 82 ppb in all three cases. Several ozone vegetation exposure metrics were also evaluated to investigate the potential impact of ground-level ozone on vegetation. The chronic 3-months SUM60 exposure metric is within the CEMA baseline range (0-2000 ppb-hr) everywhere in the AOSR. The AOT40 ozone exposure metric predicted by CMAQ did not exceed the United Nations Economic Commission for Europe (UN/ECE) threshold of concern of 3000 ppb-hr in any of the cases but is just below the threshold in high-end future emissions scenario. In all three emission scenarios, the CMAQ predicted W126 ozone exposure metric is within the CEMA baseline threshold of 4000 ppb-hr. This study outlines the use of photochemical modelling of the impact of an industry (oil

  10. Electronic self-organization in layered transition metal dichalcogenides

    Energy Technology Data Exchange (ETDEWEB)

    Ritschel, Tobias

    2015-10-30

    The interplay between different self-organized electronically ordered states and their relation to unconventional electronic properties like superconductivity constitutes one of the most exciting challenges of modern condensed matter physics. In the present thesis this issue is thoroughly investigated for the prototypical layered material 1T-TaS{sub 2} both experimentally and theoretically. At first the static charge density wave order in 1T-TaS{sub 2} is investigated as a function of pressure and temperature by means of X-ray diffraction. These data indeed reveal that the superconductivity in this material coexists with an inhomogeneous charge density wave on a macroscopic scale in real space. This result is fundamentally different from a previously proposed separation of superconducting and insulating regions in real space. Furthermore, the X-ray diffraction data uncover the important role of interlayer correlations in 1T-TaS{sub 2}. Based on the detailed insights into the charge density wave structure obtained by the X-ray diffraction experiments, density functional theory models are deduced in order to describe the electronic structure of 1T-TaS{sub 2} in the second part of this thesis. As opposed to most previous studies, these calculations take the three-dimensional character of the charge density wave into account. Indeed the electronic structure calculations uncover complex orbital textures, which are interwoven with the charge density wave order and cause dramatic differences in the electronic structure depending on the alignment of the orbitals between neighboring layers. Furthermore, it is demonstrated that these orbital-mediated effects provide a route to drive semiconductor-to-metal transitions with technologically pertinent gaps and on ultrafast timescales. These results are particularly relevant for the ongoing development of novel, miniaturized and ultrafast devices based on layered transition metal dichalcogenides. The discovery of orbital textures

  11. Self-organization of muscle cell structure and function.

    Science.gov (United States)

    Grosberg, Anna; Kuo, Po-Ling; Guo, Chin-Lin; Geisse, Nicholas A; Bray, Mark-Anthony; Adams, William J; Sheehy, Sean P; Parker, Kevin Kit

    2011-02-01

    The organization of muscle is the product of functional adaptation over several length scales spanning from the sarcomere to the muscle bundle. One possible strategy for solving this multiscale coupling problem is to physically constrain the muscle cells in microenvironments that potentiate the organization of their intracellular space. We hypothesized that boundary conditions in the extracellular space potentiate the organization of cytoskeletal scaffolds for directed sarcomeregenesis. We developed a quantitative model of how the cytoskeleton of neonatal rat ventricular myocytes organizes with respect to geometric cues in the extracellular matrix. Numerical results and in vitro assays to control myocyte shape indicated that distinct cytoskeletal architectures arise from two temporally-ordered, organizational processes: the interaction between actin fibers, premyofibrils and focal adhesions, as well as cooperative alignment and parallel bundling of nascent myofibrils. Our results suggest that a hierarchy of mechanisms regulate the self-organization of the contractile cytoskeleton and that a positive feedback loop is responsible for initiating the break in symmetry, potentiated by extracellular boundary conditions, is required to polarize the contractile cytoskeleton.

  12. Fast CEUS image segmentation based on self organizing maps

    Science.gov (United States)

    Paire, Julie; Sauvage, Vincent; Albouy-Kissi, Adelaïde; Ladam Marcus, Viviane; Marcus, Claude; Hoeffel, Christine

    2014-03-01

    Contrast-enhanced ultrasound (CEUS) has recently become an important technology for lesion detection and characterization. CEUS is used to investigate the perfusion kinetics in tissue over time, which relates to tissue vascularization. In this paper, we present an interactive segmentation method based on the neural networks, which enables to segment malignant tissue over CEUS sequences. We use Self-Organizing-Maps (SOM), an unsupervised neural network, to project high dimensional data to low dimensional space, named a map of neurons. The algorithm gathers the observations in clusters, respecting the topology of the observations space. This means that a notion of neighborhood between classes is defined. Adjacent observations in variables space belong to the same class or related classes after classification. Thanks to this neighborhood conservation property and associated with suitable feature extraction, this map provides user friendly segmentation tool. It will assist the expert in tumor segmentation with fast and easy intervention. We implement SOM on a Graphics Processing Unit (GPU) to accelerate treatment. This allows a greater number of iterations and the learning process to converge more precisely. We get a better quality of learning so a better classification. Our approach allows us to identify and delineate lesions accurately. Our results show that this method improves markedly the recognition of liver lesions and opens the way for future precise quantification of contrast enhancement.

  13. Metabolic evolution and the self-organization of ecosystems.

    Science.gov (United States)

    Braakman, Rogier; Follows, Michael J; Chisholm, Sallie W

    2017-04-11

    Metabolism mediates the flow of matter and energy through the biosphere. We examined how metabolic evolution shapes ecosystems by reconstructing it in the globally abundant oceanic phytoplankter Prochlorococcus To understand what drove observed evolutionary patterns, we interpreted them in the context of its population dynamics, growth rate, and light adaptation, and the size and macromolecular and elemental composition of cells. This multilevel view suggests that, over the course of evolution, there was a steady increase in Prochlorococcus' metabolic rate and excretion of organic carbon. We derived a mathematical framework that suggests these adaptations lower the minimal subsistence nutrient concentration of cells, which results in a drawdown of nutrients in oceanic surface waters. This, in turn, increases total ecosystem biomass and promotes the coevolution of all cells in the ecosystem. Additional reconstructions suggest that Prochlorococcus and the dominant cooccurring heterotrophic bacterium SAR11 form a coevolved mutualism that maximizes their collective metabolic rate by recycling organic carbon through complementary excretion and uptake pathways. Moreover, the metabolic codependencies of Prochlorococcus and SAR11 are highly similar to those of chloroplasts and mitochondria within plant cells. These observations lead us to propose a general theory relating metabolic evolution to the self-amplification and self-organization of the biosphere. We discuss the implications of this framework for the evolution of Earth's biogeochemical cycles and the rise of atmospheric oxygen.

  14. Growth, collapse, and self-organized criticality in complex networks

    Science.gov (United States)

    Wang, Yafeng; Fan, Huawei; Lin, Weijie; Lai, Ying-Cheng; Wang, Xingang

    2016-04-01

    Network growth is ubiquitous in nature (e.g., biological networks) and technological systems (e.g., modern infrastructures). To understand how certain dynamical behaviors can or cannot persist as the underlying network grows is a problem of increasing importance in complex dynamical systems as well as sustainability science and engineering. We address the question of whether a complex network of nonlinear oscillators can maintain its synchronization stability as it expands. We find that a large scale avalanche over the entire network can be triggered in the sense that the individual nodal dynamics diverges from the synchronous state in a cascading manner within a relatively short time period. In particular, after an initial stage of linear growth, the network typically evolves into a critical state where the addition of a single new node can cause a group of nodes to lose synchronization, leading to synchronization collapse for the entire network. A statistical analysis reveals that the collapse size is approximately algebraically distributed, indicating the emergence of self-organized criticality. We demonstrate the generality of the phenomenon of synchronization collapse using a variety of complex network models, and uncover the underlying dynamical mechanism through an eigenvector analysis.

  15. Computer simulations of self-organized megaripples in the nearshore

    Science.gov (United States)

    Gallagher, E. L.

    2011-03-01

    Megaripples are bed forms with heights of 20-50 cm and lengths of 1-10 m that are common in the surf zone of natural beaches. They affect sediment transport, flow energy dissipation, and larger-scale hydro- and morphodynamics. They are thought to be dynamically similar to bed forms in deserts, rivers, and deeper marine environments. Here a self-organization model (similar to models for subaerial bed forms) is used to simulate the formation and development of megaripples in the surf zone. Sediment flux is determined from combined wave and current flows using stream power and bed shear stress formulations as well as a third formulation for transport based on simple rules, which represent sheet flow. Random bed irregularities, either imposed or resulting from small variations in transport representing turbulence, are necessary seeds for bed form development. Feedback between the bed and the flow, in the form of a shadow zone downstream of a bed form and increasing flow acceleration with elevation over the crests of bed forms, alter the transport such that organized bed forms emerge. Modeled bed form morphology (including cross-sectional shape and plan view) and dynamics (including growth and migration) are similar to natural megaripples. The model can be used to extend the field observations of Clarke and Werner (2004), which suggest that, if conditions remain the same, megaripples will continue to grow. Contrary to many bed form models, this model supports the idea that bed form spacing grows continually.

  16. Spatial self-organization favors heterotypic cooperation over cheating

    Science.gov (United States)

    Momeni, Babak; Waite, Adam James; Shou, Wenying

    2013-01-01

    Heterotypic cooperation—two populations exchanging distinct benefits that are costly to produce—is widespread. Cheaters, exploiting benefits while evading contribution, can undermine cooperation. Two mechanisms can stabilize heterotypic cooperation. In ‘partner choice’, cooperators recognize and choose cooperating over cheating partners; in ‘partner fidelity feedback’, fitness-feedback from repeated interactions ensures that aiding your partner helps yourself. How might a spatial environment, which facilitates repeated interactions, promote fitness-feedback? We examined this process through mathematical models and engineered Saccharomyces cerevisiae strains incapable of recognition. Here, cooperators and their heterotypic cooperative partners (partners) exchanged distinct essential metabolites. Cheaters exploited partner-produced metabolites without reciprocating, and were competitively superior to cooperators. Despite initially random spatial distributions, cooperators gained more partner neighbors than cheaters did. The less a cheater contributed, the more it was excluded and disfavored. This self-organization, driven by asymmetric fitness effects of cooperators and cheaters on partners during cell growth into open space, achieves assortment. DOI: http://dx.doi.org/10.7554/eLife.00960.001 PMID:24220506

  17. Identifying individual sperm whales acoustically using self-organizing maps

    Science.gov (United States)

    Ioup, Juliette W.; Ioup, George E.

    2005-09-01

    The Littoral Acoustic Demonstration Center (LADC) is a consortium at Stennis Space Center comprising the University of New Orleans, the University of Southern Mississippi, the Naval Research Laboratory, and the University of Louisiana at Lafayette. LADC deployed three Environmental Acoustic Recording System (EARS) buoys in the northern Gulf of Mexico during the summer of 2001 to study ambient noise and marine mammals. Each LADC EARS was an autonomous, self-recording buoy capable of 36 days of continuous recording of a single channel at an 11.7-kHz sampling rate (bandwidth to 5859 Hz). The hydrophone selected for this analysis was approximately 50 m from the bottom in a water depth of 800 m on the continental slope off the Mississippi River delta. This paper contains recent analysis results for sperm whale codas recorded during a 3-min period. Results are presented for the identification of individual sperm whales from their codas, using the acoustic properties of the clicks within each coda. The recorded time series, the Fourier transform magnitude, and the wavelet transform coefficients are each used separately with a self-organizing map procedure for 43 codas. All show the codas as coming from four or five individual whales. [Research supported by ONR.

  18. Regimes of self-organized criticality in the atmospheric convection

    CERN Document Server

    Spineanu, F; Palade, D

    2014-01-01

    Large scale organization in ensembles of events of atmospheric convection can be generated by the combined effect of forcing and of the interaction between the raising plumes and the environment. Here the "large scale" refers to the space extension that is larger or comparable with the basic resolved cell of a numerical weather prediction system. Under the action of external forcing like heating individual events of convection respond to the slow accumulation of vapor by a threshold-type dynamics. This is due to the a time-scale separation, between the slow drive and the fast convective response, expressed as the "quasi-equilibrium". When there is interaction between the convection plumes, the effect is a correlated response. We show that the correlated response have many of the characteristics of the self-organized criticality (SOC). It is suggested that from the SOC perspective, a description of the specific dynamics induced by "quasi-equilibrium" can be provided by models of "punctuated equilibrium". Indee...

  19. Surface self-organization in multilayer film coatings

    Science.gov (United States)

    Shuvalov, Gleb M.; Kostyrko, Sergey A.

    2017-12-01

    It is a recognized fact that during film deposition and subsequent thermal processing the film surface evolves into an undulating profile. Surface roughness affects many important aspects in the engineering application of thin film materials such as wetting, heat transfer, mechanical, electromagnetic and optical properties. To accurately control the morphological surface modifications at the micro- and nanoscale and improve manufacturing techniques, we design a mathematical model of the surface self-organization process in multilayer film materials. In this paper, we consider a solid film coating with an arbitrary number of layers under plane strain conditions. The film surface has a small initial perturbation described by a periodic function. It is assumed that the evolution of the surface relief is governed by surface and volume diffusion. Based on Gibbs thermodynamics and linear theory of elasticity, we present a procedure for constructing a governing equation that gives the amplitude change of the surface perturbation with time. A parametric study of the evolution equation leads to the definition of a critical undulation wavelength that stabilizes the surface. As a numerical result, the influence of geometrical and physical parameters on the morphological stability of an isotropic two-layered film coating is analyzed.

  20. Self-organization and positioning of bacterial protein clusters

    Science.gov (United States)

    Murray, Seán M.; Sourjik, Victor

    2017-10-01

    Many cellular processes require proteins to be precisely positioned within the cell. In some cases this can be attributed to passive mechanisms such as recruitment by other proteins in the cell or by exploiting the curvature of the membrane. However, in bacteria, active self-positioning is likely to play a role in multiple processes, including the positioning of the future site of cell division and cytoplasmic protein clusters. How can such dynamic clusters be formed and positioned? Here, we present a model for the self-organization and positioning of dynamic protein clusters into regularly repeating patterns based on a phase-locked Turing pattern. A single peak in the concentration is always positioned at the midpoint of the model cell, and two peaks are positioned at the midpoint of each half. Furthermore, domain growth results in peak splitting and pattern doubling. We argue that the model may explain the regular positioning of the highly conserved structural maintenance of chromosomes complexes on the bacterial nucleoid and that it provides an attractive mechanism for the self-positioning of dynamic protein clusters in other systems.

  1. Examining the NZESM Cloud representation with Self Organizing Maps

    Science.gov (United States)

    Schuddeboom, Alex; McDonald, Adrian; Parsons, Simon; Morgenstern, Olaf; Harvey, Mike

    2017-04-01

    Several different cloud regimes are identified from MODIS satellite data and the representation of these regimes within the New Zealand Earth System Model (NZESM) is examined. For the development of our cloud classification we utilize a neural network algorithm known as self organizing maps (SOMs) on MODIS cloud top pressure - cloud optical thickness joint histograms. To evaluate the representation of the cloud within NZESM, the frequency and geographical distribution of the regimes is compared between the NZESM and satellite data. This approach has the advantage of not only identifying differences, but also potentially giving additional information about the discrepancy such as in which regions or phases of cloud the differences are most prominent. To allow for a more direct comparison between datasets, the COSP satellite simulation software is applied to NZESM output. COSP works by simulating the observational processes linked to a satellite, within the GCM, so that data can be generated in a way that shares the particular observational bias of specific satellites. By taking the COSP joint histograms and comparing them to our existing classifications we can easily search for discrepancies between the observational data and the simulations without having to be cautious of biases introduced by the satellite. Preliminary results, based on data for 2008, show a significant decrease in overall cloud fraction in the NZESM compared to the MODIS satellite data. To better understand the nature of this discrepancy, the cloud fraction related to different cloud heights and phases were also analysed.

  2. Business Client Segmentation in Banking Using Self-Organizing Maps

    Directory of Open Access Journals (Sweden)

    Bach Mirjana Pejić

    2014-11-01

    Full Text Available Segmentation in banking for the business client market is traditionally based on size measured in terms of income and the number of employees, and on statistical clustering methods (e.g. hierarchical clustering, k-means. The goal of the paper is to demonstrate that self-organizing maps (SOM effectively extend the pool of possible criteria for segmentation of the business client market with more relevant criteria, including behavioral, demographic, personal, operational, situational, and cross-selling products. In order to attain the goal of the paper, the dataset on business clients of several banks in Croatia, which, besides size, incorporates a number of different criteria, is analyzed using the SOM-Ward clustering algorithm of Viscovery SOMine software. The SOM-Ward algorithm extracted three segments that differ with respect to the attributes of foreign trade operations (import/export, annual income, origin of capital, important bank selection criteria, views on the loan selection and the industry. The analyzed segments can be used by banks for deciding on the direction of further marketing activities.

  3. Self-Organized Platinum Nanoparticles Elevated on Freestanding Graphene

    Science.gov (United States)

    Ackerman, Matthew; Xu, Peng; Barber, Steven; Schoelz, James; Qi, Dejun; Thibado, Paul; Dong, Lifeng; Yu, Jianhua; Xu, Fangfang; Neek-Amal, Mehdi; Peeters, Francois

    2014-03-01

    Freestanding graphene membranes were successfully functionalized with platinum nanoparticles (Pt NPs) using a single-step sputtering deposition process. The membranes were imaged using high-resolution transmission electron microscopy, revealing a homogeneous distribution of uniformly sized, single-crystal Pt NPs that exhibit a preferred orientation and nearest-neighbor distance. The NPs were also found to be partially elevated by the graphene substrate, as deduced from atomic-resolution scanning tunneling microscopy (STM) images. Furthermore, the electrostatic force between the STM tip and sample was utilized to estimate the binding energy of the NPs to the suspended graphene. Local strain accumulation due to elevation during the growth process is thought to be the origin of the NP self-organization. Such detailed insight into the atomic nature of this functionalized system was only possible through the cooperation of dual microscopic techniques combined with molecular dynamics simulations. The findings are expected to shape future approaches to develop high-performance electronics based on nanoparticle-functionalized graphene as well as fuel cells using Pt NP catalysts. ONR Grant No. N00014-10-1-0181, NSF Grant No. DMR-0855358 and DMR-0821159, National Natural Science Foundation of China (51172113), Shandong Natural Science Foundation (JQ201118), Qingdao Municipal Science and Technology Commission (12-1-4-136-hz).

  4. Chapter 24: Computational modeling of self-organized spindle formation.

    Science.gov (United States)

    Schaffner, Stuart C; José, Jorge V

    2008-01-01

    In this chapter, we provide a derivation and computational details of a biophysical model we introduced to describe the self-organized mitotic spindle formation properties in the chromosome dominated pathway studied in Xenopus meiotic extracts. The mitotic spindle is a biological structure composed of microtubules. This structure forms the scaffold on which mitosis and cytokinesis occurs. Despite the seeming mechanical simplicity of the spindle itself, its formation and the way in which it is used in mitosis and cytokinesis is complex and not fully understood. Biophysical modeling of a system as complex as mitosis requires contributions from biologists, biochemists, mathematicians, physicists, and software engineers. This chapter is written for biologists and biochemists who wish to understand how biophysical modeling can complement a program of biological experimentation. It is also written for a physicist, computer scientist, or mathematician unfamiliar with this class of biological physics model. We will describe how we built such a mathematical model and its numerical simulator to obtain results that agree with many of the results found experimentally. The components of this system are large enough to be described in terms of coarse-grained approximations. We will discuss how to properly model such systems and will suggest effective tradeoffs between reliability, simulation speed, and accuracy. At all times we have in mind the realistic biophysical properties of the system we are trying to model.

  5. Mobile Anomaly Detection Based on Improved Self-Organizing Maps

    Directory of Open Access Journals (Sweden)

    Chunyong Yin

    2017-01-01

    Full Text Available Anomaly detection has always been the focus of researchers and especially, the developments of mobile devices raise new challenges of anomaly detection. For example, mobile devices can keep connection with Internet and they are rarely turned off even at night. This means mobile devices can attack nodes or be attacked at night without being perceived by users and they have different characteristics from Internet behaviors. The introduction of data mining has made leaps forward in this field. Self-organizing maps, one of famous clustering algorithms, are affected by initial weight vectors and the clustering result is unstable. The optimal method of selecting initial clustering centers is transplanted from K-means to SOM. To evaluate the performance of improved SOM, we utilize diverse datasets and KDD Cup99 dataset to compare it with traditional one. The experimental results show that improved SOM can get higher accuracy rate for universal datasets. As for KDD Cup99 dataset, it achieves higher recall rate and precision rate.

  6. Self-organization of intracellular gradients during mitosis

    Directory of Open Access Journals (Sweden)

    Fuller Brian G

    2010-01-01

    Full Text Available Abstract Gradients are used in a number of biological systems to transmit spatial information over a range of distances. The best studied are morphogen gradients where information is transmitted over many cell lengths. Smaller mitotic gradients reflect the need to organize several distinct events along the length of the mitotic spindle. The intracellular gradients that characterize mitosis are emerging as important regulatory paradigms. Intracellular gradients utilize intrinsic auto-regulatory feedback loops and diffusion to establish stable regions of activity within the mitotic cytosol. We review three recently described intracellular mitotic gradients. The Ran GTP gradient with its elaborate cascade of nuclear transport receptors and cargoes is the best characterized, yet the dynamics underlying the robust gradient of Ran-GTP have received little attention. Gradients of phosphorylation have been observed on Aurora B kinase substrates both before and after anaphase onset. In both instances the phosphorylation gradient appears to result from a soluble gradient of Aurora B kinase activity. Regulatory properties that support gradient formation are highlighted. Intracellular activity gradients that regulate localized mitotic events bare several hallmarks of self-organizing biologic systems that designate spatial information during pattern formation. Intracellular pattern formation represents a new paradigm in mitotic regulation.

  7. 25 Years of Self-organized Criticality: Numerical Detection Methods

    Science.gov (United States)

    McAteer, R. T. James; Aschwanden, Markus J.; Dimitropoulou, Michaila; Georgoulis, Manolis K.; Pruessner, Gunnar; Morales, Laura; Ireland, Jack; Abramenko, Valentyna

    2016-01-01

    The detection and characterization of self-organized criticality (SOC), in both real and simulated data, has undergone many significant revisions over the past 25 years. The explosive advances in the many numerical methods available for detecting, discriminating, and ultimately testing, SOC have played a critical role in developing our understanding of how systems experience and exhibit SOC. In this article, methods of detecting SOC are reviewed; from correlations to complexity to critical quantities. A description of the basic autocorrelation method leads into a detailed analysis of application-oriented methods developed in the last 25 years. In the second half of this manuscript space-based, time-based and spatial-temporal methods are reviewed and the prevalence of power laws in nature is described, with an emphasis on event detection and characterization. The search for numerical methods to clearly and unambiguously detect SOC in data often leads us outside the comfort zone of our own disciplines—the answers to these questions are often obtained by studying the advances made in other fields of study. In addition, numerical detection methods often provide the optimum link between simulations and experiments in scientific research. We seek to explore this boundary where the rubber meets the road, to review this expanding field of research of numerical detection of SOC systems over the past 25 years, and to iterate forwards so as to provide some foresight and guidance into developing breakthroughs in this subject over the next quarter of a century.

  8. Modularity and Self-Organized Functional Architectures in the Brain

    Science.gov (United States)

    Iyer, Laxmi; Minai, Ali A.; Doboli, Simona; Brown, Vincent R.

    It is generally believed that cognition involves the self-organization of coherent dy- namic functional networks across several brain regions in response to incoming stimulus and internal modulation. These context-dependent networks arise continually from the spatiotemporally multi-scale structural substrate of the brain configured by evolution, development and previous experience, persisting for 100-200 ms and generating re- sponses such as imagery, recall and motor action. In the current paper, we show that a system of interacting modular attractor networks can use a selective mechanism for assembling functional networks from the modular substrate. We use the approach to develop a model of idea-generation in the brain. Ideas are modeled as combinations of concepts organized in a recurrent network that reflects previous associations between them. The dynamics of this network, resulting in the transient co-activation of concept groups, is seen as a search through the space of ideas, and attractor dynamics is used to "shape" this search. The process is required to encompass both rapid retrieval of old ideas in familiar contexts and efficient search for novel ones in unfamiliar situations (or during brainstorming). The inclusion of an adaptive modulatory mechanism allows the network to balance the competing requirements of exploiting previous learning and exploring new possibilities as needed in different contexts.

  9. Self-organized instability in graded-index multimode fibres

    Science.gov (United States)

    Wright, Logan G.; Liu, Zhanwei; Nolan, Daniel A.; Li, Ming-Jun; Christodoulides, Demetrios N.; Wise, Frank W.

    2016-12-01

    Multimode fibres (MMFs) are attracting interest in the study of spatiotemporal dynamics as well as in the context of ultrafast fibre sources, imaging and telecommunications. This interest stems from three differences compared with single-mode fibre structures: their spatiotemporal complexity (information capacity), the role of disorder, and their complex intermodal interactions. To date, MMFs have been studied in limiting cases in which one or more of these properties can be neglected. Here, we study a regime in which all these elements are integral. We observe a spatial beam-cleaning phenomenon that precedes spatiotemporal modulation instability. We provide evidence that the origin of these processes is a universal unstable attractor in graded-index MMFs. The self-organization and instability of the attractor are both caused by intermodal interactions characterized by cooperating disorder, nonlinearity and dissipation. Disorder-enhanced nonlinear processes in MMFs have important implications for future telecommunications, and the multifaceted nature of the considered dynamics showcases MMFs as potential laboratories for a variety of topics in complexity science.

  10. A study of self organized criticality in ion temperature gradient mode driven gyrokinetic turbulence

    Energy Technology Data Exchange (ETDEWEB)

    Mavridis, M.; Isliker, H.; Vlahos, L. [Section of Astrophysics, Astronomy and Mechanics, Department of Physics, Aristotle University of Thessaloniki, GR-54124 Thessaloniki (Greece); Görler, T.; Jenko, F.; Told, D. [Max Planck Institute for Plasma Physics, Boltzmannstr. 2, 85748 Garching (Germany)

    2014-10-15

    An investigation on the characteristics of self organized criticality (Soc) in ITG mode driven turbulence is made, with the use of various statistical tools (histograms, power spectra, Hurst exponents estimated with the rescaled range analysis, and the structure function method). For this purpose, local non-linear gyrokinetic simulations of the cyclone base case scenario are performed with the GENE software package. Although most authors concentrate on global simulations, which seem to be a better choice for such an investigation, we use local simulations in an attempt to study the locally underlying mechanisms of Soc. We also study the structural properties of radially extended structures, with several tools (fractal dimension estimate, cluster analysis, and two dimensional autocorrelation function), in order to explore whether they can be characterized as avalanches. We find that, for large enough driving temperature gradients, the local simulations exhibit most of the features of Soc, with the exception of the probability distribution of observables, which show a tail, yet they are not of power-law form. The radial structures have the same radial extent at all temperature gradients examined; radial motion (transport) though appears only at large temperature gradients, in which case the radial structures can be interpreted as avalanches.

  11. Dynamic data association for multi-sensor using self-organizing FNN in clutter

    Science.gov (United States)

    Hsueh, Chi-Shun

    2017-05-01

    In this paper, improving data association process by increasing the probability of detecting valid data points (measurements obtained from ESM/RADAR system) in the presence of noise for location and target tracking are discussed. This develop a multisensor data association algorithm that fuses information from the multiple ESM receiver and surveillance RADAR. The develop a novel algorithm by self-organizing fuzzy neural network (SO-FNN) for multiple ESM-to-ESM (measurement-to-measurement data association) and ESMs-to-RADAR (track-to-track data association) problem in dense clutter environment. An adaptive search based on SO-FNN of the distance threshold measure is then used to detect valid filtered data point for data association. Simulation results demonstrate the effectiveness and better performance when compared to conventional algorithm. The paper is organized as follows. Section 1 is the problem formulation. Section 2 design the new data association algorithm based on SO-FNN data association system design. Section 3 describes ESM-to-ESM and ESM-to-RADAR (measurement-to-measurement data association and track-to-track data association) scenario and the simulation results are presented and discussed. The summary are drawn in section 4, respectively.

  12. Self-Organizing Wearable Device Platform for Assisting and Reminding Humans in Real Time

    Directory of Open Access Journals (Sweden)

    Yu Jin Park

    2016-01-01

    Full Text Available Most older persons would prefer “aging in my place,” that is, to remain in good health and live independently in their own home as long as possible. For assisting the independent living of older people, the ability to gather and analyze a user’s daily activity data would constitute a significant technical advance, enhancing their quality of life. However, the general approach based on centralized server has several problems such as the usage complexity, the high price of deployment and expansion, and the difficulty in identifying an individual person. To address these problems, we propose a wearable device platform for the life assistance of older persons that automatically records and analyzes their daily activity without intentional human intervention or a centralized server (i.e., cloud server. The proposed platform contains self-organizing protocols, Delay-Tolerant Messaging system, knowledge-based analysis and alerting for daily activities, and a hardware platform that provides low power consumption. We implemented a prototype smart watch, called Personal Activity Assisting and Reminding (PAAR, as a testbed for the proposed platform, and evaluated the power consumption and the service time of example scenarios.

  13. Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses.

    Directory of Open Access Journals (Sweden)

    Gabriel Koch Ocker

    2015-08-01

    Full Text Available The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their joint spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory for the evolution of network structure by combining fast spiking covariance with a slow evolution of synaptic weights. Through a finite-size expansion of network dynamics we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure.

  14. Scenario? Guilty!

    DEFF Research Database (Denmark)

    Kyng, Morten

    1992-01-01

    Robert Campbell categorizes the word "scenario" as a buzzword, identifies four major uses within HCI and suggests that we adopt new terms differentiating these four uses of the word. My first reaction to reading the article was definitely positive, but rereading it gave me enough second thoughts...

  15. When Self-Organization intersects with Urban Planning: Two Cases from Helsinki

    DEFF Research Database (Denmark)

    Horelli, Liisa; Saad-Sulonen, Joanna; Wallin, Sirkku

    2015-01-01

    Participation as self-organization has emerged as a new form of citizen activism, often supported by digital technology. A comparative qualitative analysis of two case studies in Helsinki indicates that the self-organization of citizens expands the practice of urban planning. Together, they enable...

  16. SoLoc: Self-organizing indoor localization for unstructured and dynamic environments

    NARCIS (Netherlands)

    Le Viet Duc, Duc Viet; Havinga, Paul J.M.

    2017-01-01

    Self-organization is critical to enable novel indoor Location-Based Services (LBSs) for users and businesses in large, complex and unstructured buildings. Inspired by high densities of smartphones in public indoor spaces, in this paper we propose a self-organizing indoor localization approach that

  17. Structural hierarchy in flow-aligned hexagonally self-organized microphases with parallel polyelectrolytic structures

    NARCIS (Netherlands)

    Ruotsalainen, T; Torkkeli, M; Serimaa, R; Makela, T; Maki-Ontto, R; Ruokolainen, J; ten Brinke, G; Ikkala, O; Mäkelä, Tapio; Mäki-Ontto, Riikka

    2003-01-01

    We report a novel structural hierarchy where a flow-aligned hexagonal self-organized structure is combined with a polyelectrolytic self-organization on a smaller length scale and where the two structures are mutually parallel. Polystyrene-block-poly(4-vinylpyridine) (PS-block-P4VP) is selected with

  18. Self-organization and Spatial Planning : Foundations, Challenges, Constraints and consequences

    NARCIS (Netherlands)

    de Roo, Gert; de Roo, Gert; Boelens, Luuk

    2016-01-01

    Does self-organization matter to planning? Spatial Planning and self-organization: the combination of these two themes is perhaps somewhat unexpected, one being the collective manifestation of ‘intentional’ action, the other representing ‘spontaneous’ phenomena. Spatial Planning labels itself a

  19. Hierarchical self-organization of non-cooperating individuals.

    Directory of Open Access Journals (Sweden)

    Tamás Nepusz

    Full Text Available Hierarchy is one of the most conspicuous features of numerous natural, technological and social systems. The underlying structures are typically complex and their most relevant organizational principle is the ordering of the ties among the units they are made of according to a network displaying hierarchical features. In spite of the abundant presence of hierarchy no quantitative theoretical interpretation of the origins of a multi-level, knowledge-based social network exists. Here we introduce an approach which is capable of reproducing the emergence of a multi-levelled network structure based on the plausible assumption that the individuals (representing the nodes of the network can make the right estimate about the state of their changing environment to a varying degree. Our model accounts for a fundamental feature of knowledge-based organizations: the less capable individuals tend to follow those who are better at solving the problems they all face. We find that relatively simple rules lead to hierarchical self-organization and the specific structures we obtain possess the two, perhaps most important features of complex systems: a simultaneous presence of adaptability and stability. In addition, the performance (success score of the emerging networks is significantly higher than the average expected score of the individuals without letting them copy the decisions of the others. The results of our calculations are in agreement with a related experiment and can be useful from the point of designing the optimal conditions for constructing a given complex social structure as well as understanding the hierarchical organization of such biological structures of major importance as the regulatory pathways or the dynamics of neural networks.

  20. 25 Years of Self-organized Criticality: Concepts and Controversies

    Science.gov (United States)

    Watkins, Nicholas W.; Pruessner, Gunnar; Chapman, Sandra C.; Crosby, Norma B.; Jensen, Henrik J.

    2016-01-01

    Introduced by the late Per Bak and his colleagues, self-organized criticality (SOC) has been one of the most stimulating concepts to come out of statistical mechanics and condensed matter theory in the last few decades, and has played a significant role in the development of complexity science. SOC, and more generally fractals and power laws, have attracted much comment, ranging from the very positive to the polemical. The other papers (Aschwanden et al. in Space Sci. Rev., 2014, this issue; McAteer et al. in Space Sci. Rev., 2015, this issue; Sharma et al. in Space Sci. Rev. 2015, in preparation) in this special issue showcase the considerable body of observations in solar, magnetospheric and fusion plasma inspired by the SOC idea, and expose the fertile role the new paradigm has played in approaches to modeling and understanding multiscale plasma instabilities. This very broad impact, and the necessary process of adapting a scientific hypothesis to the conditions of a given physical system, has meant that SOC as studied in these fields has sometimes differed significantly from the definition originally given by its creators. In Bak's own field of theoretical physics there are significant observational and theoretical open questions, even 25 years on (Pruessner 2012). One aim of the present review is to address the dichotomy between the great reception SOC has received in some areas, and its shortcomings, as they became manifest in the controversies it triggered. Our article tries to clear up what we think are misunderstandings of SOC in fields more remote from its origins in statistical mechanics, condensed matter and dynamical systems by revisiting Bak, Tang and Wiesenfeld's original papers.

  1. Spatial self-organization in hybrid models of multicellular adhesion

    Science.gov (United States)

    Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard

    2016-10-01

    Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.

  2. Self-organization in arrays of surface-grown nanoparticles: characterization, control, driving forces

    Energy Technology Data Exchange (ETDEWEB)

    Levchenko, I; Kumar, S; Yajadda, M M A; Han, Z J; Furman, S; Ostrikov, K, E-mail: Igor.Levchenko@csiro.au [Plasma Nanoscience Centre Australia (PNCA), CSIRO Materials Science and Engineering, PO Box 218, Lindfield, New South Wales 2070 (Australia)

    2011-05-04

    Some important issues related to the self-organization in the arrays of nanoparticles on solid surfaces exposed to the low-temperature plasma are analysed and discussed. The available tools for the characterization of the size and position uniformity in nanoarrays are examined. The technique capable of revealing the realistic adsorbed atom and adsorbed radical capture zone pattern based on the surface physics is indicated as the most promising characterization tool. The processes responsible for the self-organization are analysed, the main driving forces of the self-organization are discussed, and possible ways to control the self-organization by controlling the plasma parameters are introduced. A view on the possible ways to further improve the methods of nanoarray characterization and self-organization is presented as well.

  3. Behavioral self-organization underlies the resilience of a coastal ecosystem.

    Science.gov (United States)

    de Paoli, Hélène; van der Heide, Tjisse; van den Berg, Aniek; Silliman, Brian R; Herman, Peter M J; van de Koppel, Johan

    2017-07-25

    Self-organized spatial patterns occur in many terrestrial, aquatic, and marine ecosystems. Theoretical models and observational studies suggest self-organization, the formation of patterns due to ecological interactions, is critical for enhanced ecosystem resilience. However, experimental tests of this cross-ecosystem theory are lacking. In this study, we experimentally test the hypothesis that self-organized pattern formation improves the persistence of mussel beds (Mytilus edulis) on intertidal flats. In natural beds, mussels generate self-organized patterns at two different spatial scales: regularly spaced clusters of mussels at centimeter scale driven by behavioral aggregation and large-scale, regularly spaced bands at meter scale driven by ecological feedback mechanisms. To test for the relative importance of these two spatial scales of self-organization on mussel bed persistence, we conducted field manipulations in which we factorially constructed small-scale and/or large-scale patterns. Our results revealed that both forms of self-organization enhanced the persistence of the constructed mussel beds in comparison to nonorganized beds. Small-scale, behaviorally driven cluster patterns were found to be crucial for persistence, and thus resistance to wave disturbance, whereas large-scale, self-organized patterns facilitated reformation of small-scale patterns if mussels were dislodged. This study provides experimental evidence that self-organization can be paramount to enhancing ecosystem persistence. We conclude that ecosystems with self-organized spatial patterns are likely to benefit greatly from conservation and restoration actions that use the emergent effects of self-organization to increase ecosystem resistance to disturbance.

  4. Quantum gravity as an information network self-organization of a 4D universe

    Science.gov (United States)

    Trugenberger, Carlo A.

    2015-10-01

    I propose a quantum gravity model in which the fundamental degrees of freedom are information bits for both discrete space-time points and links connecting them. The Hamiltonian is a very simple network model consisting of a ferromagnetic Ising model for space-time vertices and an antiferromagnetic Ising model for the links. As a result of the frustration between these two terms, the ground state self-organizes as a new type of low-clustering graph with finite Hausdorff dimension 4. The spectral dimension is lower than the Hausdorff dimension: it coincides with the Hausdorff dimension 4 at a first quantum phase transition corresponding to an IR fixed point, while at a second quantum phase transition describing small scales space-time dissolves into disordered information bits. The large-scale dimension 4 of the universe is related to the upper critical dimension 4 of the Ising model. At finite temperatures the universe graph emerges without a big bang and without singularities from a ferromagnetic phase transition in which space-time itself forms out of a hot soup of information bits. When the temperature is lowered the universe graph unfolds and expands by lowering its connectivity, a mechanism I have called topological expansion. The model admits topological black hole excitations corresponding to graphs containing holes with no space-time inside and with "Schwarzschild-like" horizons with a lower spectral dimension.

  5. River delta self-organization via entropy rate analysis

    Science.gov (United States)

    Tejedor, A.; Longjas, A.; Foufoula-Georgiou, E.

    2016-12-01

    Previous work [Tejedor et al., 2015a,b; 2016] has shown that network topologic characteristics for a wide range of field and simulated delta channel networks vary significantly reflecting to some extend the different underlying physical processes. While more work remains to be done in this direction to advance quantitative delta classification, a problem of parallel interest is that of unraveling whether deltas evolve and attain topologies and flow partitions that are consistent with an underlying principle of optimization, as for example has been examined for tributary river networks. Here we study concepts of Entropy as applied to directed acyclic graphs such as river deltas, and specifically the concept of Entropy rate that measures the rate at which a stochastic process generates information. For deltas, Entropy rate can be interpreted as the amount of information we need to acquire at each time step to probabilistically track the position of the particles on the network. We propose a new Entropy metric, the non-local Entropy Rate (nER), which we argue is more pertinent to deltas as it captures the averaged information content of a delta network in terms of the degree of uncertainty in delivering fluxes from any point of the network to the shoreline. We interpret nER as measuring delta's capacity to optimally grow by spreading water and sediment over its delta top in a non-preferential way. We present results for field and simulated deltas, showing that conditional on a network topology, channel widths self-adjust such that the delivery of fluxes from the delta top to the shoreline has a maximal value of non-local Entropy Rate. Drawing on the connection between Entropy and resilience via the fluctuation theorem [Demetrius and Manke, 2005], we also suggest that deltas might in fact self-organize to maximize their resilience to perturbations. Tejedor, A., A. Longjas, I. Zaliapin, and E. Foufoula-Georgiou (2015), Water Resour. Res., 51, 3998-4018 Tejedor, A., A

  6. Expression cartography of human tissues using self organizing maps.

    Science.gov (United States)

    Wirth, Henry; Löffler, Markus; von Bergen, Martin; Binder, Hans

    2011-07-27

    Parallel high-throughput microarray and sequencing experiments produce vast quantities of multidimensional data which must be arranged and analyzed in a concerted way. One approach to addressing this challenge is the machine learning technique known as self organizing maps (SOMs). SOMs enable a parallel sample- and gene-centered view of genomic data combined with strong visualization and second-level analysis capabilities. The paper aims at bridging the gap between the potency of SOM-machine learning to reduce dimension of high-dimensional data on one hand and practical applications with special emphasis on gene expression analysis on the other hand. The method was applied to generate a SOM characterizing the whole genome expression profiles of 67 healthy human tissues selected from ten tissue categories (adipose, endocrine, homeostasis, digestion, exocrine, epithelium, sexual reproduction, muscle, immune system and nervous tissues). SOM mapping reduces the dimension of expression data from ten of thousands of genes to a few thousand metagenes, each representing a minicluster of co-regulated single genes. Tissue-specific and common properties shared between groups of tissues emerge as a handful of localized spots in the tissue maps collecting groups of co-regulated and co-expressed metagenes. The functional context of the spots was discovered using overrepresentation analysis with respect to pre-defined gene sets of known functional impact. We found that tissue related spots typically contain enriched populations of genes related to specific molecular processes in the respective tissue. Analysis techniques normally used at the gene-level such as two-way hierarchical clustering are better represented and provide better signal-to-noise ratios if applied to the metagenes. Metagene-based clustering analyses aggregate the tissues broadly into three clusters containing nervous, immune system and the remaining tissues. The SOM technique provides a more intuitive and

  7. Fluid forces enhance the performance of an aspirant leader in self-organized living groups.

    Directory of Open Access Journals (Sweden)

    Alessandro De Rosis

    Full Text Available In this paper, the performance of an individual aiming at guiding a self-organized group is numerically investigated. A collective behavioural model is adopted, accounting for the mutual repulsion, attraction and orientation experienced by the individuals. Moreover, these represent a set of solid particles which are supposed to be immersed in a fictitious viscous fluid. In particular, the lattice Boltzmann and Immersed boundary methods are used to predict the fluid dynamics, whereas the effect of the hydrodynamic forces on particles is accounted for by solving the equation of the solid motion through the time discontinuous Galerkin scheme. Numerical simulations are carried out by involving the individuals in a dichotomous process. On the one hand, an aspirant leader (AL additional individual is added to the system. AL is forced to move along a prescribed direction which intersects the group. On the other hand, these tend to depart from an obstacle represented by a rotating lamina which is placed in the fluid domain. A numerical campaign is carried out by varying the fluid viscosity and, as a consequence, the hydrodynamic field. Moreover, scenarios characterized by different values of the size of the group are investigated. In order to estimate the AL's performance, a proper parameter is introduced, depending on the number of individuals following AL. Present findings show that the sole collective behavioural equations are insufficient to predict the AL's performance, since the motion is drastically affected by the presence of the surrounding fluid. With respect to the existing literature, the proposed numerical model is enriched by accounting for the presence of the encompassing fluid, thus computing the hydrodynamic forces arising when the individuals move.

  8. Fluid forces enhance the performance of an aspirant leader in self-organized living groups.

    Science.gov (United States)

    De Rosis, Alessandro

    2014-01-01

    In this paper, the performance of an individual aiming at guiding a self-organized group is numerically investigated. A collective behavioural model is adopted, accounting for the mutual repulsion, attraction and orientation experienced by the individuals. Moreover, these represent a set of solid particles which are supposed to be immersed in a fictitious viscous fluid. In particular, the lattice Boltzmann and Immersed boundary methods are used to predict the fluid dynamics, whereas the effect of the hydrodynamic forces on particles is accounted for by solving the equation of the solid motion through the time discontinuous Galerkin scheme. Numerical simulations are carried out by involving the individuals in a dichotomous process. On the one hand, an aspirant leader (AL) additional individual is added to the system. AL is forced to move along a prescribed direction which intersects the group. On the other hand, these tend to depart from an obstacle represented by a rotating lamina which is placed in the fluid domain. A numerical campaign is carried out by varying the fluid viscosity and, as a consequence, the hydrodynamic field. Moreover, scenarios characterized by different values of the size of the group are investigated. In order to estimate the AL's performance, a proper parameter is introduced, depending on the number of individuals following AL. Present findings show that the sole collective behavioural equations are insufficient to predict the AL's performance, since the motion is drastically affected by the presence of the surrounding fluid. With respect to the existing literature, the proposed numerical model is enriched by accounting for the presence of the encompassing fluid, thus computing the hydrodynamic forces arising when the individuals move.

  9. Self-organization in the Earth climate system versus Milankovitch-Berger astronomical cycles

    CERN Document Server

    Maslov, Lev A

    2014-01-01

    The Late Pleistocene Antarctic temperature variation curve is decomposed into two parts: cyclic and stochastic. These two parts represent different but tightly interconnected processes and also represent two different types of self-organization of the Earth climate system. The self-organization in the cyclic component is the non-linear auto-oscillation reaction of the Earth climate system, as a whole, to the input of solar radiation. The self-organization in the stochastic component is a nonlinear critical process, taking energy from, and fluctuating around the cyclic component of the temperature variations. The system of ODEs is written to model the cyclic part of the temperature variation, and the multifractal spectrum of the stochastic part of the temperature variation is calculated. The Earth climate can be characterized as an open, complex, self-organized dynamical system with nonlinear reaction to the input of solar radiation.

  10. Spatial self-organization on intertidal mudflats through biophysical stress divergence

    NARCIS (Netherlands)

    Weerman, E.J.; Van de Koppel, J.; Eppinga, M.B.; Montserrat Trotsenburg, F.; Liu, Q.X.; Herman, P.M.J.

    2010-01-01

    In this study, we investigated the emergence of spatial self-organized patterns on intertidal flats, resulting from the interaction between biological and geomorphological processes. Autocorrelation analysis of aerial photographs revealed that diatoms occur in regularly spaced patterns consisting of

  11. Self-organization and oscillation of negatively charged dust particles in a 2-dimensional dusty plasma

    Energy Technology Data Exchange (ETDEWEB)

    Song, Y.L. [College of Science, China Agricultural University, Beijing 100083 (China); Huang, F., E-mail: huangfeng@cau.edu.cn [College of Science, China Agricultural University, Beijing 100083 (China); Chen, Z.Y., E-mail: chenzy@mail.buct.edu.cn [Department of Physics, Beijing University of Chemical Technology, Beijing 100029 (China); State Key Laboratory of Laser Propulsion & Application, Beijing 101416 (China); Liu, Y.H. [School of Physics and Optoelectronic Engineering, Ludong University, Yantai 264025 (China); Yu, M.Y. [Institute for Fusion Theory and Simulation, Zhejiang University, Hangzhou 310027 (China); Institute for Theoretical Physics I, Ruhr University, D-44801 Bochum (Germany)

    2016-02-22

    Negatively charged dust particles immersed in 2-dimensional dusty plasma system are investigated by molecular dynamics simulations. The effects of the confinement potential and attraction interaction potential on dust particle self-organization are studied in detail and two typical dust particle distributions are obtained when the system reaches equilibrium. The average radial velocity (ARV), average radial force (ARF) and radial mean square displacement are employed to analyze the dust particles' dynamics. Both ARVs and ARFs exhibit oscillation behaviors when the simulation system reaches equilibrium state. The relationships between the oscillation and confinement potential and attraction potential are studied in this paper. The simulation results are qualitatively similar to experimental results. - Highlights: • Self-organization and oscillation of a 2-dimensional dusty plasma is investigated. • Effect of the confinement potential on dust self-organization and oscillation is given. • Effect of the attraction potential on dust self-organization and oscillation is studied.

  12. Self-Organizing Neural Circuits for Sensory-Guided Motor Control

    National Research Council Canada - National Science Library

    Grossberg, Stephen

    1999-01-01

    The reported projects developed mathematical models to explain how self-organizing neural circuits that operate under continuous or intermittent sensory guidance achieve flexible and accurate control of human movement...

  13. Effects of Interactive Function Forms and Refractoryperiod in a Self-Organized Critical Model Based on Neural Networks

    Institute of Scientific and Technical Information of China (English)

    ZHOU Li-Ming; CHEN Tian-Lun

    2004-01-01

    Based on the standard self-organizing map neural network model and an integrate-and-tire mechanism, we investigate the effect of the nonlinear interactive function on the self-organized criticality in our model. Based on these we also investigate the effect of the refractoryperiod on the self-organized criticality of the system.

  14. Dendronized Metal Nanoparticles-Self-Organizing Building Blocks for the Design of New Functional Materials

    Science.gov (United States)

    2016-04-01

    AFRL-AFOSR-UK-TR-2016-0010 Dendronized metal nanoparticles - self-organizing building blocks for the design of new functional materials Bertrand...2015 4. TITLE AND SUBTITLE Dendronized metal nanoparticles - self-organizing building blocks for the design of new functional materials 5a. CONTRACT...restrictions or special markings are indicated, follow agency authorization procedures, e.g. RD/FRD, PROPIN, ITAR, etc. Include copyright

  15. Macro-Cell Placement for Custom-Chip Design Using Self-Organizing Fuzzy Technique

    OpenAIRE

    Ray-I Chang; Pei-Yung Hsiao

    1998-01-01

    In this paper, a new optimization technique called SOFT(self-organizing fuzzy technique) is proposed to solve the macro-cell placement problem. In SOFT, different criteria are simultaneously accounted by a novel fuzzy gain function which models expert knowledge to control the optimization process. The presented procedure is an adaptation of Kohonen's self-organization algorithm which is well suited for implementation on massively parallel architecture for fast computing. The MC...

  16. Nanoscience with liquid crystals from self-organized nanostructures to applications

    CERN Document Server

    Li, Quan

    2014-01-01

    This book focuses on the exciting topic of nanoscience with liquid crystals: from self-organized nanostructures to applications. The elegant self-organized liquid crystalline nanostructures, the synergetic characteristics of liquid crystals and nanoparticles, liquid crystalline nanomaterials, synthesis of nanomaterials using liquid crystals as templates, nanoconfinement and nanoparticles of liquid crystals are covered and discussed, and the prospect of fabricating functional materials is highlighted. Contributions, collecting the scattered literature of the field from leading and active player

  17. Identification of leader and self-organizing communities in complex networks

    OpenAIRE

    Jingcheng Fu; Weixiong Zhang; Jianliang Wu

    2017-01-01

    Community or module structure is a natural property of complex networks. Leader communities and self-organizing communities have been introduced recently to characterize networks and understand how communities arise in complex networks. However, identification of leader and self-organizing communities is technically challenging since no adequate quantification has been developed to properly separate the two types of communities. We introduced a new measure, called ratio of node degree varianc...

  18. Self organization of wireless sensor networks using ultra-wideband radios

    Science.gov (United States)

    Dowla, Farid U [Castro Valley, CA; Nekoogar, Franak [San Ramon, CA; Spiridon, Alex [Palo Alto, CA

    2009-06-16

    A novel UWB communications method and system that provides self-organization for wireless sensor networks is introduced. The self-organization is in terms of scalability, power conservation, channel estimation, and node synchronization in wireless sensor networks. The UWB receiver in the present invention adds two new tasks to conventional TR receivers. The two additional units are SNR enhancing unit and timing acquisition and tracking unit.

  19. Developmental word acquisition and grammar learning by humanoid robots through a self-organizing incremental neural network.

    Science.gov (United States)

    He, Xiaoyuan; Ogura, Tomotaka; Satou, Akihiro; Hasegawa, Osamu

    2007-10-01

    We present a new approach for online incremental word acquisition and grammar learning by humanoid robots. Using no data set provided in advance, the proposed system grounds language in a physical context, as mediated by its perceptual capacities. It is carried out using show-and-tell procedures, interacting with its human partner. Moreover, this procedure is open-ended for new words and multiword utterances. These facilities are supported by a self-organizing incremental neural network, which can execute online unsupervised classification and topology learning. Embodied with a mental imagery, the system also learns by both top-down and bottom-up processes, which are the syntactic structures that are contained in utterances. Thereby, it performs simple grammar learning. Under such a multimodal scheme, the robot is able to describe online a given physical context (both static and dynamic) through natural language expressions. It can also perform actions through verbal interactions with its human partner.

  20. Trend and Self Organizing Map Analysis of Snow Data of Northern Hemisphere for 1979-2014

    Science.gov (United States)

    Gan, T. Y. Y.; Scheepers, H.

    2016-12-01

    The 1979-2014, 25km-resolution snow water equivalent (SWE) monthly dataset of the Globsnow project of the European Space Agency prepared from combining Nimbus-7 SMMR, DMSP SSM/I-SSMIS SWE data with observations of ground-based synoptic weather stations was analyzed. The dataset covers the terrestrial non-mountainous regions of Northern Hemisphere except the Greenland. The monthly SWE dataset of October-May was analyzed for monotonic trends using the non-parametric Mann-Kendall test at 0.05 significant levels. Based on the total number of snow covered pixels analyzed, up to 15.5% (7.7%) of the pixels show statistically significant decreasing (increasing) trends. December has the largest snow cover extent and the greatest percentage of statistically significant decreasing trends, of which the majority are located north of 55° latitude which may reflect the effect of polar warming. April exhibits the greatest percentage of statistically significant positive trends and most of these are located in Asia. The mean trend magnitudes detected for October-May range from 0.18 to 1.42 mm/yr. Principle component analyses was performed on the SWE dataset and the leading components were correlated with temperature, precipitation, and climate indices such as El Niño Southern Oscillation (ENSO), Pacific Decadal (PDO), North Atlantic Oscillation (NAO), and others. The methods of self-organizing map and k-means clustering were also applied to delineate 20 regions in the Northern Hemisphere that exhibit similar SWE patterns.

  1. A cognitive-inspired model for self-organizing networks

    CERN Document Server

    Borkmann, Daniel; Massaro, Emanuele; Rudolph, Stefan

    2012-01-01

    In this work, we propose a computational scheme inspired by the workings of human cognition in order to embed some fundamental aspects of the human cognitive system such as the minimization of the computational resources, and the evolution of a dynamic knowledge network over time into computer networks. Such algorithm is capable of generating suitable strategies to explore networks like the Internet, which are too large and too dynamic to be ever perfectly known. The algorithm equips each node with a local information about the possible hubs which are present in its environment. Such information can be used by a node to change its connections whenever its fitness is not satisfying some given requirements. Finally, we compare our algorithm with a randomized approach within an ecological scenario for the ICT domain, where a network of nodes carries a certain set of objects, and each node retrieves a subset at a certain time, constrained with limited resources in terms of energy and bandwidth. We show that a cog...

  2. Brain Basis of Self: Self-Organization and Lessons from Dreaming

    Directory of Open Access Journals (Sweden)

    David eKahn

    2013-07-01

    Full Text Available Through dreaming a different facet of the self is created as a result of a self-organizing process in the brain. Self-organization in biological systems often happens as an answer to an environmental change for which the existing system cannot cope; self-organization creates a system that can cope in the newly changed environment. In dreaming, self-organization serves the function of organizing disparate memories into a dream since the dreamer herself is not able to control how individual memories become weaved into a dream. The self-organized dream provides, thereby, a wide repertoire of experiences; this expanded repertoire of experience results in an expansion of the self beyond that obtainable when awake. Since expression of the self is associated with activity in specific areas of the brain, the article also discusses the brain basis of the self by reviewing studies of brain injured patients, discussing brain imaging studies in normal brain functioning when focused, when daydreaming and when asleep and dreaming.

  3. Analysis of mass incident diffusion in Weibo based on self-organization theory

    Science.gov (United States)

    Pan, Jun; Shen, Huizhang

    2018-02-01

    This study introduces some theories and methods of self-organization system to the research of the diffusion mechanism of mass incidents in Weibo (Chinese Twitter). Based on the analysis on massive Weibo data from Songjiang battery factory incident happened in 2013 and Jiiangsu Qidong OJI PAPER incident happened in 2012, we find out that diffusion system of mass incident in Weibo satisfies Power Law, Zipf's Law, 1/f noise and Self-similarity. It means this system is the self-organization criticality system and dissemination bursts can be understood as one kind of Self-organization behavior. As the consequence, self-organized criticality (SOC) theory can be used to explain the evolution of mass incident diffusion and people may come up with the right strategy to control such kind of diffusion if they can handle the key ingredients of Self-organization well. Such a study is of practical importance which can offer opportunities for policy makers to have good management on these events.

  4. Identification of leader and self-organizing communities in complex networks.

    Science.gov (United States)

    Fu, Jingcheng; Zhang, Weixiong; Wu, Jianliang

    2017-04-06

    Community or module structure is a natural property of complex networks. Leader communities and self-organizing communities have been introduced recently to characterize networks and understand how communities arise in complex networks. However, identification of leader and self-organizing communities is technically challenging since no adequate quantification has been developed to properly separate the two types of communities. We introduced a new measure, called ratio of node degree variances, to distinguish leader communities from self-organizing communities, and developed a statistical model to quantitatively characterize the two types of communities. We experimentally studied the power and robustness of the new method on several real-world networks in combination of some of the existing community identification methods. Our results revealed that social networks and citation networks contain more leader communities whereas technological networks such as power grid network have more self-organizing communities. Moreover, our results also indicated that self-organizing communities tend to be smaller than leader communities. The results shed new lights on community formation and module structures in complex systems.

  5. Self-organization of two-dimensional incompressible viscous flow in a friction-free box

    Energy Technology Data Exchange (ETDEWEB)

    Kondoh, Y.; Yoshizawa, M.; Nakano, A. [Gunma Univ., Kiryu (Japan). Faculty of Engineering; Yabe, T.

    1995-10-01

    The process by which self-organization occurs for two-dimensional incompressible viscous flow in a friction-free box is investigated theoretically with the use of numerical simulations. It is shown by an eigenfunction spectrum analysis that two basic processes for the self-organization are the spectrum transfer by nonlinear couplings and the selective dissipation among the eigenmodes of the dissipative operator, and they yield spectrum accumulation at the lowest eigenmode. It is also clarified that an important process during nonlinear self-organization is an interchange between the dominant operators, which leads to a final self-similar coherent structure, determined uniquely by the lowest eigenmode of the dissipative operator. (author).

  6. Two-dimensional charge transport in self-organized, high-mobility conjugated polymers

    DEFF Research Database (Denmark)

    Sirringhaus, H.; Brown, P.J.; Friend, R.H.

    1999-01-01

    Self-organization in many solution-processed, semiconducting conjugated polymers results in complex microstructures, in which ordered microcrystalline domains are embedded in an amorphous matrix(I). This has important consequences for electrical properties of these materials: charge transport...... of the ordered microcrystalline domains in the conjugated polymer poly(3-hexylthiophene), P3HT, Self-organization in P3HT results in a lamella structure with two-dimensional conjugated sheets formed by interchain stacking. We find that, depending on processing conditions, the lamellae can adopt two different...... character of the polaronic charge carriers, which exhibit lower relaxation energies than the corresponding radical cations on isolated one-dimensional chains. The possibility of achieving high mobilities via two-dimensional transport in self-organized conjugated lamellae is important for applications...

  7. Origin and evolution of the self-organizing cytoskeleton in the network of eukaryotic organelles.

    Science.gov (United States)

    Jékely, Gáspár

    2014-09-02

    The eukaryotic cytoskeleton evolved from prokaryotic cytomotive filaments. Prokaryotic filament systems show bewildering structural and dynamic complexity and, in many aspects, prefigure the self-organizing properties of the eukaryotic cytoskeleton. Here, the dynamic properties of the prokaryotic and eukaryotic cytoskeleton are compared, and how these relate to function and evolution of organellar networks is discussed. The evolution of new aspects of filament dynamics in eukaryotes, including severing and branching, and the advent of molecular motors converted the eukaryotic cytoskeleton into a self-organizing "active gel," the dynamics of which can only be described with computational models. Advances in modeling and comparative genomics hold promise of a better understanding of the evolution of the self-organizing cytoskeleton in early eukaryotes, and its role in the evolution of novel eukaryotic functions, such as amoeboid motility, mitosis, and ciliary swimming. Copyright © 2014 Cold Spring Harbor Laboratory Press; all rights reserved.

  8. Mobility Model for Self-Organizing and Cooperative MSN and MANET Systems

    Directory of Open Access Journals (Sweden)

    Andrzej Sikora

    2012-03-01

    Full Text Available Self-organization mechanisms are used for building scalable systems consisting of a huge number of subsystems. In computer networks, self-organizing is especially important in ad hoc networking. A self-organizing ad hoc network is a collection of wireless devices that collaborate with each other to form a network system that adapts to achieve a goal or goals. Such network is often built from mobile devices that may spontaneously create a network and dynamically adapted to changes in an unknown environment. Mobility pattern is a critical element that influences the performance characteristics of mobile sensor networks (MSN and mobile ad hoc networks (MANET. In this paper, we survey main directions to mobility modeling. We describe a novel algorithm for calculating mobility patterns for mobile devices that is based on a cluster formation and an artificial potential function. Finally, we present the simulation results of its application to a rescue mission planning.

  9. Self-organizing control strategy for asteroid intelligent detection swarm based on attraction and repulsion

    Science.gov (United States)

    An, Meiyan; Wang, Zhaokui; Zhang, Yulin

    2017-01-01

    The self-organizing control strategy for asteroid intelligent detection swarm, which is considered as a space application instance of intelligent swarm, is developed. The leader-follower model for the asteroid intelligent detection swarm is established, and the further analysis is conducted for massive asteroid and small asteroid. For a massive asteroid, the leader spacecraft flies under the gravity field of the asteroid. For a small asteroid, the asteroid gravity is negligible, and a trajectory planning method is proposed based on elliptic cavity virtual potential field. The self-organizing control strategy for the follower spacecraft is developed based on a mechanism of velocity planning and velocity tracking. The simulation results show that the self-organizing control strategy is valid for both massive asteroid and small asteroid, and the exploration swarm forms a stable configuration.

  10. Interval data clustering using self-organizing maps based on adaptive Mahalanobis distances.

    Science.gov (United States)

    Hajjar, Chantal; Hamdan, Hani

    2013-10-01

    The self-organizing map is a kind of artificial neural network used to map high dimensional data into a low dimensional space. This paper presents a self-organizing map for interval-valued data based on adaptive Mahalanobis distances in order to do clustering of interval data with topology preservation. Two methods based on the batch training algorithm for the self-organizing maps are proposed. The first method uses a common Mahalanobis distance for all clusters. In the second method, the algorithm starts with a common Mahalanobis distance per cluster and then switches to use a different distance per cluster. This process allows a more adapted clustering for the given data set. The performances of the proposed methods are compared and discussed using artificial and real interval data sets. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. Subwavelength Microstructures Fabrication by Self-Organization Processes in Photopolymerizable Nanocomposite

    Directory of Open Access Journals (Sweden)

    I. Yu. Denisyuk

    2012-01-01

    Full Text Available This paper describes our research results on nanometers sizes subwavelength nanostructure fabrication by UV curing of special nanocomposite material with self-organization and light self-focusing effects. For this purpose, special UV curable nanocomposite material with a set of effects was developing: light self-focusing in the photopolymer with positive refractive index change, self-organization based on photo-induced nanoparticles transportation, and oxygen-based polymerization threshold. Both holographic and projection lithography writing methods application for microstructure making shows geometrical optical laws perturbation as result of nanocomposite self-organization effects with formation of nanometers-sized high-aspect-ratio structures. Obtained results will be useful for diffraction limit overcoming in projection lithography as well as for deep lithography technique.

  12. Self-organization in Complex Systems The Past, Present, and Future of Synergetics : International Symposium

    CERN Document Server

    Pelster, Axel

    2016-01-01

    This proceedings volume contains talks and poster presentations from the International Symposium "Self-Organization in Complex Systems: The Past, Present, and Future of Synergetics", which took place at Hanse-Wissenschaftskolleg, an Institute of Advanced Studies, in Delmenhorst, Germany, during the period November 13 - 16, 2012. The Symposium was organized in honour of Hermann Haken, who celebrated his 85th birthday in 2012. With his fundamental theory of Synergetics he had laid the mathematical-physical basis for describing and analyzing self-organization processes in a diversity of fields of research. The quest for common and universal principles of self-organization in complex systems was clearly covered by the wide range of interdisciplinary topics reported during the Symposium. These extended from complexity in classical systems and quantum systems over self-organisation in neuroscience even to the physics of finance. Moreover, by combining a historical view with a present status report the Symposium con...

  13. On the self-organizing process of large scale shear flows

    Energy Technology Data Exchange (ETDEWEB)

    Newton, Andrew P. L. [Department of Applied Maths, University of Sheffield, Sheffield, Yorkshire S3 7RH (United Kingdom); Kim, Eun-jin [School of Mathematics and Statistics, University of Sheffield, Sheffield, Yorkshire S3 7RH (United Kingdom); Liu, Han-Li [High Altitude Observatory, National Centre for Atmospheric Research, P. O. BOX 3000, Boulder, Colorado 80303-3000 (United States)

    2013-09-15

    Self organization is invoked as a paradigm to explore the processes governing the evolution of shear flows. By examining the probability density function (PDF) of the local flow gradient (shear), we show that shear flows reach a quasi-equilibrium state as its growth of shear is balanced by shear relaxation. Specifically, the PDFs of the local shear are calculated numerically and analytically in reduced 1D and 0D models, where the PDFs are shown to converge to a bimodal distribution in the case of finite correlated temporal forcing. This bimodal PDF is then shown to be reproduced in nonlinear simulation of 2D hydrodynamic turbulence. Furthermore, the bimodal PDF is demonstrated to result from a self-organizing shear flow with linear profile. Similar bimodal structure and linear profile of the shear flow are observed in gulf stream, suggesting self-organization.

  14. Secure eHealth-Care Service on Self-Organizing Software Platform

    Directory of Open Access Journals (Sweden)

    Im Y. Jung

    2014-01-01

    Full Text Available There are several applications connected to IT health devices on the self-organizing software platform (SoSp that allow patients or elderly users to be cared for remotely by their family doctors under normal circumstances or during emergencies. An evaluation of the SoSp applied through PAAR watch/self-organizing software platform router was conducted targeting a simple user interface for aging users, without the existence of extrasettings based on patient movement. On the other hand, like normal medical records, the access to, and transmission of, health information via PAAR watch/self-organizing software platform requires privacy protection. This paper proposes a security framework for health information management of the SoSp. The proposed framework was designed to ensure easy detection of identification information for typical users. In addition, it provides powerful protection of the user’s health information.

  15. MACHINE LEARNING FOR THE SELF-ORGANIZATION OF DISTRIBUTED SYSTEMS IN ECONOMIC APPLICATIONS

    Directory of Open Access Journals (Sweden)

    Jerzy Balicki

    2017-03-01

    Full Text Available In this paper, an application of machine learning to the problem of self-organization of distributed systems has been discussed with regard to economic applications, with particular emphasis on supervised neural network learning to predict stock investments and some ratings of companies. In addition, genetic programming can play an important role in the preparation and testing of several financial information systems. For this reason, machine learning applications have been discussed because some software applications can be automatically constructed by genetic programming. To obtain a competitive advantage, machine learning can be used for the management of self-organizing cloud computing systems performing calculations for business. Also the use of selected economic self-organizing distributed systems has been described, including some testing methods of predicting borrower reliability. Finally, some conclusions and directions for further research have been proposed.

  16. The USGS Earthquake Scenario Project

    Science.gov (United States)

    Wald, D. J.; Petersen, M. D.; Wald, L. A.; Frankel, A. D.; Quitoriano, V. R.; Lin, K.; Luco, N.; Mathias, S.; Bausch, D.

    2009-12-01

    The U.S. Geological Survey’s (USGS) Earthquake Hazards Program (EHP) is producing a comprehensive suite of earthquake scenarios for planning, mitigation, loss estimation, and scientific investigations. The Earthquake Scenario Project (ESP), though lacking clairvoyance, is a forward-looking project, estimating earthquake hazard and loss outcomes as they may occur one day. For each scenario event, fundamental input includes i) the magnitude and specified fault mechanism and dimensions, ii) regional Vs30 shear velocity values for site amplification, and iii) event metadata. A grid of standard ShakeMap ground motion parameters (PGA, PGV, and three spectral response periods) is then produced using the well-defined, regionally-specific approach developed by the USGS National Seismic Hazard Mapping Project (NHSMP), including recent advances in empirical ground motion predictions (e.g., the NGA relations). The framework also allows for numerical (3D) ground motion computations for specific, detailed scenario analyses. Unlike NSHMP ground motions, for ESP scenarios, local rock and soil site conditions and commensurate shaking amplifications are applied based on detailed Vs30 maps where available or based on topographic slope as a proxy. The scenario event set is comprised primarily by selection from the NSHMP events, though custom events are also allowed based on coordination of the ESP team with regional coordinators, seismic hazard experts, seismic network operators, and response coordinators. The event set will be harmonized with existing and future scenario earthquake events produced regionally or by other researchers. The event list includes approximate 200 earthquakes in CA, 100 in NV, dozens in each of NM, UT, WY, and a smaller number in other regions. Systematic output will include all standard ShakeMap products, including HAZUS input, GIS, KML, and XML files used for visualization, loss estimation, ShakeCast, PAGER, and for other systems. All products will be

  17. The Imbalance and Self-Organization in the Earth's Climate System (Invited)

    Science.gov (United States)

    Maslov, L.

    2013-12-01

    The increase in frequency and severity of storms, hurricanes and other atmospheric phenomena indicates a progressive imbalance in all planetary systems. Study of the temperature curve obtained from the Antarctic ice core showed that this data can be considered as a sum of two components: the 'cyclic' component and the 'stochastic' component, representing two different but tightly interconnected processes. The 'cyclic' and the 'stochastic' components represent two different types of self-organization of the Earth's climate system. The self-organization in the 'cyclic' process is a non-linear reaction of the Earth's climate system, as a whole, to the input of solar radiation. The self-organization in the 'stochastic' part is a self-organized nonlinear critical process, taking energy from, and fluctuating around the 'cyclic' part of the temperature variations. As a whole, the Earth's climate can be characterized as a nonlinear, self-organized, dynamic system with two levels of self-organization. This research can shed some light on the global climate imbalance and help us to understand the current trends in global weather and to predict global weather trends in the distant and not so distant future. First of all, global warming, as can be seen in repeated high temperature spikes in temperature cycles, has happened in every past climate cycle. The present interglacial period lasts a little bit longer than previous similar periods. This can be because of additional warming caused by human industrial activity. But, following the 'cyclic' pattern of glacial and interglacial temperature cycles, one can conclude that we are at the very beginning of a gradual cooling period to temperatures below freezing. This process is accompanied by sharp and intense fluctuations of temperature, represented by the 'stochastic' part of global temperature curve. Atmospheric temperature fluctuations are the direct result, and at the same time, a cause of atmospheric imbalance. It is

  18. Self-organized TiO{sub 2} nanotubes: Factors affecting their morphology and properties

    Energy Technology Data Exchange (ETDEWEB)

    Berger, Steffen; Hahn, Robert; Roy, Poulomi; Schmuki, Patrik [Department of Materials Science and Engineering, Chair for Surface Science and Corrosion (LKO), University of Erlangen-Nuernberg, Erlangen (Germany)

    2010-10-15

    Self-organized oxide nanostructures grown by controlled anodic oxidation of a metal substrate attracted wide scientific interest due to a broad number of potential applications. The present work gives an overview on growth principles and mechanistic aspects of self-organized TiO{sub 2} nanotubular layers and related transition metal oxide nanostructures. In particular, key electrochemical factors that control tube geometry and routes to fabricate advanced TiO{sub 2} nanotube geometries and morphologies are discussed. (Abstract Copyright [2010], Wiley Periodicals, Inc.)

  19. Self-organized control in cooperative robots using a pattern formation principle

    DEFF Research Database (Denmark)

    Starke, Jens; Ellsaesser, Carmen; Fukuda, Toshio

    2011-01-01

    Self-organized modular approaches proved in nature to be robust and optimal and are a promising strategy to control future concepts of flexible and modular manufacturing processes. We show how this can be applied to a model of flexible manufacturing based on time-dependent robot-target assignment...... problems where robot teams have to serve manufacturing targets such that an objective function is optimized. Feasibility of the self-organized solutions can be guaranteed even for unpredictable situations like sudden changes in the demands or breakdowns of robots. As example an uncrewed space mission...

  20. Femtosecond-laser generation of self-organized bubble patterns in fused silica.

    Science.gov (United States)

    Bellouard, Yves; Hongler, Max-Olivier

    2011-03-28

    By continuously scanning a femtosecond laser beam across a fused silica specimen, we demonstrate the formation of self-organized bubbles buried in the material. Rather than using high intensity pulses and high numerical aperture to induce explosions in the material, here bubbles form as a consequence of cumulative energy deposits. We observe a transition between chaotic and self-organized patterns at high scanning rate (above 10 mm/s). Through modeling the energy exchange, we outline the similarities of this phenomenon with other non-linear dynamical systems. Furthermore, we demonstrate with this method the high-speed writing of two- and three- dimensional bubble "crystals" in bulk silica.

  1. Self-Organized Bistability Associated with First-Order Phase Transitions

    Science.gov (United States)

    di Santo, Serena; Burioni, Raffaella; Vezzani, Alessandro; Muñoz, Miguel A.

    2016-06-01

    Self-organized criticality elucidates the conditions under which physical and biological systems tune themselves to the edge of a second-order phase transition, with scale invariance. Motivated by the empirical observation of bimodal distributions of activity in neuroscience and other fields, we propose and analyze a theory for the self-organization to the point of phase coexistence in systems exhibiting a first-order phase transition. It explains the emergence of regular avalanches with attributes of scale invariance that coexist with huge anomalous ones, with realizations in many fields.

  2. Self-organization leads to supraoptimal performance in public transportation systems.

    Science.gov (United States)

    Gershenson, Carlos

    2011-01-01

    The performance of public transportation systems affects a large part of the population. Current theory assumes that passengers are served optimally when vehicles arrive at stations with regular intervals. In this paper, it is shown that self-organization can improve the performance of public transportation systems beyond the theoretical optimum by responding adaptively to local conditions. This is possible because of a "slower-is-faster" effect, where passengers wait more time at stations but total travel times are reduced. The proposed self-organizing method uses "antipheromones" to regulate headways, which are inspired by the stigmergy (communication via environment) of some ant colonies.

  3. Does Prigogine’s Non-linear Thermodynamics Support Popular Philosophical Discussions of Self-Organization?

    OpenAIRE

    Alexander Pechenkin

    2015-01-01

    The article is concerned with the philosophical talks which became popular in the 1980s and have kept their popularity till now–the philosophical essays about self-organization. The author attempts to find out as to which extent are these essays founded on the scientific theory to which they regularly refer, that is, Ilya Prigogine’s non-linear thermodynamics. The author insists that the equivalent of self-organization in Prigogine’s theoretical physics is the concept of dissipative structure...

  4. From self-organization to emergence: Aesthetic implications of shifting ideas of organization

    Science.gov (United States)

    Hayles, N. Katherine

    1996-06-01

    From 1945-95, a shift took place within cybernetics from a paradigm emphasizing self-organization to one emphasizing emergence. Central in bringing about this shift was the spread of the microcomputer. With its greatly enhanced processing speed and memory capabilities, the microcomputer made simulations possible that could not have been done before. The microcomputer has also been instrumental in effecting a similar change within literary texts. To exemplify the aesthetic implications of the shift from self-organization to emergence, the chapter discusses Vladmir Nabokov's Pale Fire and Milorad Pavić's Dictionary of the Khazars: A Lexicon Novel in 100,000 Words.

  5. Life and Understanding: The Origins of "Understanding" in Self-Organizing Nervous Systems.

    Science.gov (United States)

    Yufik, Yan M; Friston, Karl

    2016-01-01

    This article is motivated by a formulation of biotic self-organization in Friston (2013), where the emergence of "life" in coupled material entities (e.g., macromolecules) was predicated on bounded subsets that maintain a degree of statistical independence from the rest of the network. Boundary elements in such systems constitute a Markov blanket ; separating the internal states of a system from its surrounding states. In this article, we ask whether Markov blankets operate in the nervous system and underlie the development of intelligence, enabling a progression from the ability to sense the environment to the ability to understand it. Markov blankets have been previously hypothesized to form in neuronal networks as a result of phase transitions that cause network subsets to fold into bounded assemblies, or packets (Yufik and Sheridan, 1997; Yufik, 1998a). The ensuing neuronal packets hypothesis builds on the notion of neuronal assemblies (Hebb, 1949, 1980), treating such assemblies as flexible but stable biophysical structures capable of withstanding entropic erosion. In other words, structures that maintain their integrity under changing conditions. In this treatment, neuronal packets give rise to perception of "objects"; i.e., quasi-stable (stimulus bound) feature groupings that are conserved over multiple presentations (e.g., the experience of perceiving "apple" can be interrupted and resumed many times). Monitoring the variations in such groups enables the apprehension of behavior; i.e., attributing to objects the ability to undergo changes without loss of self-identity. Ultimately, "understanding" involves self-directed composition and manipulation of the ensuing "mental models" that are constituted by neuronal packets, whose dynamics capture relationships among objects: that is, dependencies in the behavior of objects under varying conditions. For example, movement is known to involve rotation of population vectors in the motor cortex (Georgopoulos et al

  6. Research on Self-Organization in Resilient Recovery of Cluster Supply Chains

    Directory of Open Access Journals (Sweden)

    Liang Geng

    2013-01-01

    Full Text Available An effective way to deal with high-risk and low-probability disruptions is to create a resilient cluster supply chain, in which the study of resilience lies in its recovery mechanism when failures occur. First, the paper describes the representation method of cluster supply chain resilience. Second, a cluster supply chain network structure generation model is proposed. And based on cascading effect model, it makes analysis of dynamic evolution process when cluster supply chain failure happens. Then it focuses on the self-organization characteristic, which contributes to cluster supply chain emergence overall resilient recovery through local self-organization reconstruction behavior. We also make theoretical analysis of cluster supply chain network characteristics and its effect on the resilience, which helps to illustrate that the root of vulnerability lies in cascading failure while self-organization is the key to resilient recovery. Besides, with the study of self-organization characteristic, it provides theoretical guidance for local control and further achievement of overall resilient optimization.

  7. Pattern formation and self-organization in a simple precipitation system

    NARCIS (Netherlands)

    Volford, Andras; Izsak, F.; Ripzam, Matyas; Lagzi, Istvan

    Various types of pattern formation and self-organization phenomena can be observed in biological, chemical, and geochemical systems due to the interaction of reaction with diffusion. The appearance of static precipitation patterns was reported first by Liesegang in 1896. Traveling waves and

  8. Assessing self-organization of plant communities--A thermodynamic approach

    Science.gov (United States)

    Lin, H.; Cao, M.; Stoy, P.; Zhang, Y.

    2013-12-01

    Thermodynamics is a powerful tool for the study of system development and has the potential to be applied to studies of ecological complexity. Here, we develop a set of thermodynamic indicators including energy capture and energy dissipation to quantify plant community self-organization. The study ecosystems included a tropical seasonal rainforest, an artificial tropical rainforest, a rubber plantation, and two Chromolaena odorata (L.) R.M. King & H. Robinson communities aged 13 years and 1 year. The communities represent a complexity transect from primary vegetation, to transitional community, economic plantation, and fallows and are typical for Xishuangbanna, southwestern China. The indicators of ecosystem self-organization are sensitive to plant community type and seasonality, and demonstrate that the tropical seasonal rainforest is highly self-organized and plays an important role in local environmental stability via the land surface thermal regulation. The rubber plantation is at a very low level of self-organization as quantified by the thermodynamic indicators, especially during the dry season. The expansion of the area of rubber plantation and shrinkage of tropical seasonal rainforest would likely induce local surface warming and a larger daily temperature range.

  9. Self-organized flexible leadership promotes collective intelligence in human groups

    NARCIS (Netherlands)

    Kurvers, R.H.J.M.; Wolf, Max; Naguib, Marc; Krause, Jens

    2015-01-01

    Collective intelligence refers to the ability of groups to outperform individual decision-makers. At present, relatively little is known about the mechanisms promoting collective intelligence in natural systems. We here test a novel mechanism generating collective intelligence: self-organization

  10. Self-organization and natural selection in the evolution of complex despotic societies

    NARCIS (Netherlands)

    Hemelrijk, C.K.

    2002-01-01

    Differences between related species are usually explained as separate adaptations produced by individual selection. I discuss in this paper how related species, which differ in many respects, may evolve by a combination of individual selection, self-organization, and group-selection, requiring an

  11. Supervised self-organizing maps in crystal property and structure prediction

    NARCIS (Netherlands)

    Willighagen, E.L.; Wehrens, R.; Melssen, W.J.; Gelder, R. de; Buydens, L.M.C.

    2007-01-01

    This article shows, the use of supervised self-organizing maps (SOMs) to explore large numbers of experimental or simulated crystal structures and to visualize structure-property relationships. The examples show how powder diffraction patterns together with one or more structural properties, such as

  12. A Package for Measuring Emergence, Self-organization, and Complexity Based on Shannon Entropy

    OpenAIRE

    Santamaría-Bonfil, Guillermo; Gershenson, Carlos; Fernández, Nelson

    2017-01-01

    We present a set of Matlab/Octave functions to compute measures of emergence, self-organization, and complexity applied to discrete and continuous data. These measures are based on Shannon’s information and differential entropy. Examples from different datasets and probability distributions are provided to show how to use our proposed code.

  13. Grid cell hexagonal patterns formed by fast self-organized learning within entorhinal cortex.

    Science.gov (United States)

    Mhatre, Himanshu; Gorchetchnikov, Anatoli; Grossberg, Stephen

    2012-02-01

    Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. It has previously been shown how a self-organizing map can convert firing patterns across entorhinal grid cells into hippocampal place cells that are capable of representing much larger spatial scales. Can grid cell firing fields also arise during navigation through learning within a self-organizing map? This article describes a simple and general mathematical property of the trigonometry of spatial navigation which favors hexagonal patterns. The article also develops a neural model that can learn to exploit this trigonometric relationship. This GRIDSmap self-organizing map model converts path integration signals into hexagonal grid cell patterns of multiple scales. GRIDSmap creates only grid cell firing patterns with the observed hexagonal structure, predicts how these hexagonal patterns can be learned from experience, and can process biologically plausible neural input and output signals during navigation. These results support an emerging unified computational framework based on a hierarchy of self-organizing maps for explaining how entorhinal-hippocampal interactions support spatial navigation. Copyright © 2010 Wiley Periodicals, Inc.

  14. Relation between self-organized criticality and grain aspect ratio in granular piles

    NARCIS (Netherlands)

    Denisov, D.V.; Villanueva, Y. Y.; Lorincz-Nagy, K.; May, S.; Wijngaarden, R.J.

    2012-01-01

    We investigate experimentally whether self-organized criticality (SOC) occurs in granular piles composed of different grains, namely, rice, lentils, quinoa, and mung beans. These four grains were selected to have different aspect ratios, from oblong to oblate. As a function of aspect ratio, we

  15. Distributed Storage Management Using Dynamic Pricing in a Self-Organized Energy Community

    NARCIS (Netherlands)

    Negeri, E.; Baken, N.

    2012-01-01

    We consider a future self-organized energy community that is composed of “prosumer” households that can autonomously generate, store, import and export power, and also selfishly strive to minimize their cost by adjusting their load profiles using the flexibly of their distributed storage. In such

  16. Atomic structure of self-organizing iridium induced nanowires on Ge(001)

    NARCIS (Netherlands)

    Kabanov, Nikolai; Heimbuch, Rene; Zandvliet, Henricus J.W.; Saletsky, A.M.; Klavsyuk, A.L.

    2017-01-01

    The atomic structure of self-organizing iridium (Ir) induced nanowires on Ge(001) is studied by density functional theory (DFT) calculations and variable-temperature scanning tunneling microscopy. The Ir induced nanowires are aligned in a direction perpendicular to the Ge(001) substrate dimer rows,

  17. Actomyosin-based Self-organization of cell internalization during C. elegans gastrulation

    Directory of Open Access Journals (Sweden)

    Pohl Christian

    2012-11-01

    Full Text Available Abstract Background Gastrulation is a key transition in embryogenesis; it requires self-organized cellular coordination, which has to be both robust to allow efficient development and plastic to provide adaptability. Despite the conservation of gastrulation as a key event in Metazoan embryogenesis, the morphogenetic mechanisms of self-organization (how global order or coordination can arise from local interactions are poorly understood. Results We report a modular structure of cell internalization in Caenorhabditis elegans gastrulation that reveals mechanisms of self-organization. Cells that internalize during gastrulation show apical contractile flows, which are correlated with centripetal extensions from surrounding cells. These extensions converge to seal over the internalizing cells in the form of rosettes. This process represents a distinct mode of monolayer remodeling, with gradual extrusion of the internalizing cells and simultaneous tissue closure without an actin purse-string. We further report that this self-organizing module can adapt to severe topological alterations, providing evidence of scalability and plasticity of actomyosin-based patterning. Finally, we show that globally, the surface cell layer undergoes coplanar division to thin out and spread over the internalizing mass, which resembles epiboly. Conclusions The combination of coplanar division-based spreading and recurrent local modules for piecemeal internalization constitutes a system-level solution of gradual volume rearrangement under spatial constraint. Our results suggest that the mode of C. elegans gastrulation can be unified with the general notions of monolayer remodeling and with distinct cellular mechanisms of actomyosin-based morphogenesis.

  18. Patterning exergy of benthic macroinvertebrate communities using self-organizing maps

    NARCIS (Netherlands)

    Park, Y.S.; Lek, S.; Scardi, M.; Verdonschot, P.F.M.; Jørgensen, S.E.

    2006-01-01

    Exergy is a measure of the free energy of a system with contributions from all components including the energy of organisms, and it is used as an ecological indicator. In this study, we implemented a self-organizing map (SOM) for patterning exergy of benthic macroinvertebrate communities. The

  19. Topology assisted self-organization of colloidal nanoparticles: application to 2D large-scale nanomastering

    Directory of Open Access Journals (Sweden)

    Hind Kadiri

    2014-08-01

    Full Text Available Our aim was to elaborate a novel method for fully controllable large-scale nanopatterning. We investigated the influence of the surface topology, i.e., a pre-pattern of hydrogen silsesquioxane (HSQ posts, on the self-organization of polystyrene beads (PS dispersed over a large surface. Depending on the post size and spacing, long-range ordering of self-organized polystyrene beads is observed wherein guide posts were used leading to single crystal structure. Topology assisted self-organization has proved to be one of the solutions to obtain large-scale ordering. Besides post size and spacing, the colloidal concentration and the nature of solvent were found to have a significant effect on the self-organization of the PS beads. Scanning electron microscope and associated Fourier transform analysis were used to characterize the morphology of the ordered surfaces. Finally, the production of silicon molds is demonstrated by using the beads as a template for dry etching.

  20. Guided Self-Organization in a Dynamic Embodied System Based on Attractor Selection Mechanism

    Directory of Open Access Journals (Sweden)

    Surya G. Nurzaman

    2014-05-01

    Full Text Available Guided self-organization can be regarded as a paradigm proposed to understand how to guide a self-organizing system towards desirable behaviors, while maintaining its non-deterministic dynamics with emergent features. It is, however, not a trivial problem to guide the self-organizing behavior of physically embodied systems like robots, as the behavioral dynamics are results of interactions among their controller, mechanical dynamics of the body, and the environment. This paper presents a guided self-organization approach for dynamic robots based on a coupling between the system mechanical dynamics with an internal control structure known as the attractor selection mechanism. The mechanism enables the robot to gracefully shift between random and deterministic behaviors, represented by a number of attractors, depending on internally generated stochastic perturbation and sensory input. The robot used in this paper is a simulated curved beam hopping robot: a system with a variety of mechanical dynamics which depends on its actuation frequencies. Despite the simplicity of the approach, it will be shown how the approach regulates the probability of the robot to reach a goal through the interplay among the sensory input, the level of inherent stochastic perturbation, i.e., noise, and the mechanical dynamics.

  1. Intestinal epithelial organoids fuse to form self-organizing tubes in floating collagen gels

    NARCIS (Netherlands)

    Sachs, Norman; Tsukamoto, Yoshiyuki; Kujala, Pekka; Peters, Peter J; Clevers, Hans

    2017-01-01

    Multiple recent examples highlight how stem cells can self-organize in vitro to establish organoids that closely resemble their in vivo counterparts. Single Lgr5+ mouse intestinal stem cells can be cultured under defined conditions forming ever-expanding epithelial organoids that retain cell

  2. Schools of fish and flocks of birds : their shape and internal structure by self-organization

    NARCIS (Netherlands)

    Hemelrijk, Charlotte K.; Hildenbrandt, Hanno

    2012-01-01

    Models of self-organization have proved useful in revealing what processes may underlie characteristics of swarms. In this study, we review model-based explanations for aspects of the shape and internal structure of groups of fish and of birds travelling undisturbed (without predator threat). Our

  3. Processible conducting nanoscale cylinders due to self-organized polyaniline supra molecules

    NARCIS (Netherlands)

    Kosonen, H; Valkama, S; Ruokolainen, J; Knaapila, M; Torkkeli, M; Serimaa, R; Monkman, AP; ten Brinke, G; Ikkala, O

    2003-01-01

    Polyaniline sulphonates contain hydrogen bonding acceptor sites, which allow construction of supramolecules and self-organized structures. Here we have characterized the phase behavior of complexes of polyaniline, camphorsulphomc acid (CSA) and 4-hexylresorcinol (tires), PANI(CSA)(x)(Hres)(y), using

  4. Entropy in the Bak-Sneppen Model for Self-Organized Criticality

    Institute of Scientific and Technical Information of China (English)

    杨纯斌

    2003-01-01

    The distributions of fitness on the sites of one- and two-dimensional lattices are studied for the nearest-neighbour Bak-Sneppen model on self-organized criticality. The distributions show complicated behaviour showing that the system is far from equilibrium. By introducing the "energy" of a site, the entropy flow from the system to its environment is investigated.

  5. Autonomous distributed self-organizing and self-healing hardware architecture - The eDNA concept

    DEFF Research Database (Denmark)

    Boesen, Michael Reibel; Madsen, Jan; Keymeulen, Didier

    2011-01-01

    This paper presents the current state of the autonomous distributed self-organizing and self-healing electronic DNA (eDNA) hardware architecture (patent pending). In its current prototype state, the eDNA architecture is capable of responding to multiple injected faults by autonomously reconfiguring...... is implemented on the eDNA architecture....

  6. Neighborhoods in Development: Human Development Index and Self-Organizing Maps

    Science.gov (United States)

    Rende, Sevinc; Donduran, Murat

    2013-01-01

    The Human Development Index (HDI) has been instrumental in broadening the discussion of economic development beyond money-metric progress, in particular, by ranking a country against other countries in terms of the well being of their citizens. We propose self-organizing maps to explore similarities among countries using the components of the HDI…

  7. Controlled damaging and repair of self-organized nanostructures by atom manipulation at room temperature

    NARCIS (Netherlands)

    Gurlu, O.; van Houselt, Arie; Thijssen, W.H.A.; van Ruitenbeek, J.M.; Poelsema, Bene; Zandvliet, Henricus J.W.

    2007-01-01

    The possibility of controlled local demolition and repair of the recently discovered self-organized Pt nanowires on Ge(001) surfaces has been explored. These nanowires are composed of Pt dimers, which are found to be rather weakly bound to the underlying substrate. Using this property, we

  8. Self-organizing dynamic stability of far-from-equilibrium biological systems

    Science.gov (United States)

    Ivanitskii, G. R.

    2017-10-01

    One indication of the stability of a living system is the variation of the system’s characteristic time scales. Underlying the stability mechanism are the structural hierarchy and self-organization of systems, factors that give rise to a positive (accelerating) feedback and a negative (braking) feedback. Information processing in the brain cortex plays a special role in highly organized living organisms.

  9. Urban Land Changes as the Interaction Between Self-Organization and Institutions

    NARCIS (Netherlands)

    Zhang, Shuhai; de Roo, Gert; van Dijk, Theodorus

    2015-01-01

    There is interest among planners in autonomous behaviour and non-linear processes supporting urban development. Self-organization has attracted attention as a potential driver for urban transformations. This paper aims to explore the mechanisms behind urban land use patterns resulting from the

  10. The value of collective intentionality for understanding urban self-organization

    NARCIS (Netherlands)

    Hasanov, Mustafa; Beaumont, Justin

    2016-01-01

    Urban self-organization (USO) is an important topic within the field of contemporary participatory planning. This article aims to investigate the role of certain socio-psychological traits embedded within the notion of USO. We will argue that USO builds upon on the relationship between processes of

  11. Tokamak plasma self-organization and the possibility to have the peaked density profile in ITER

    NARCIS (Netherlands)

    Razumova, K. A.; Andreev, V. F.; Kislov, A. Y.; Kirneva, N. A.; Lysenko, S. E.; Pavlov, Y. D.; Shafranov, T. V.; Donne, A. J. H.; Hogeweij, G. M. D.; Spakman, G. W.; R. Jaspers,; Kantor, M.; Walsh, M.

    2009-01-01

    The self-organization of a tokamak plasma is a fundamental turbulent plasma phenomenon, which leads to the formation of a self-consistent pressure profile. This phenomenon has been investigated in several tokamaks with different methods of heating. It is shown that the normalized pressure profile

  12. Evidence for Self-Organized Sentence Processing: Digging-In Effects

    Science.gov (United States)

    Tabor, Whitney; Hutchins, Sean

    2004-01-01

    Dynamical, self-organizing models of sentence processing predict "digging-in" effects: The more committed the parser becomes to a wrong syntactic choice, the harder it is to reanalyze. Experiment 1 replicates previous grammaticality judgment studies (F. Ferreira & J. M. Henderson, 1991b, 1993), revealing a deleterious effect of lengthening the…

  13. Estimation of Maximum Ground Motions in the Form of ShakeMaps and Assessment of Potential Human Fatalities from Scenario Earthquakes on the Chishan Active Fault in southern Taiwan

    Science.gov (United States)

    Liu, Kun Sung; Huang, Hsiang Chi; Shen, Jia Rong

    2017-04-01

    Historically, there were many damaging earthquakes in southern Taiwan during the last century. Some of these earthquakes had resulted in heavy loss of human lives. Accordingly, assessment of potential seismic hazards has become increasingly important in southern Taiwan, including Kaohsiung, Tainan and northern Pingtung areas since the Central Geological Survey upgraded the Chishan active fault from suspected fault to Category I in 2010. In this study, we first estimate the maximum seismic ground motions in term of PGA, PGV and MMI by incorporating a site-effect term in attenuation relationships, aiming to show high seismic hazard areas in southern Taiwan. Furthermore, we will assess potential death tolls due to large future earthquakes occurring on Chishan active fault. As a result, from the maximum PGA ShakeMap for an Mw7.2 scenario earthquake on the Chishan active fault in southern Taiwan, we can see that areas with high PGA above 400 gals, are located in the northeastern, central and northern parts of southwestern Kaohsiung as well as the southern part of central Tainan. In addition, comparing the cities located in Tainan City at similar distances from the Chishan fault have relatively greater PGA and PGV than those in Kaohsiung City and Pingtung County. This is mainly due to large site response factors in Tainan. On the other hand, seismic hazard in term of PGA and PGV, respectively, show that they are not particular high in the areas near the Chishan fault. The main reason is that these areas are marked with low site response factors. Finally, the estimated fatalities in Kaohsiung City at 5230, 4285 and 2786, respectively, for Mw 7.2, 7.0 and 6.8 are higher than those estimated for Tainan City and Pingtung County. The main reason is high population density above 10000 persons per km2 are present in Fongshan, Zuoying, Sanmin, Cianjin, Sinsing, Yancheng, Lingya Districts and between 5,000 and 10,000 persons per km2 are present in Nanzih and Gushan Districts in

  14. 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

  15. Symbiotic intelligence: Self-organizing knowledge on distributed networks, driven by human interaction

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, N.; Joslyn, C.; Rocha, L.; Smith, S.; Kantor, M. [Los Alamos National Lab., NM (United States); Rasmussen, S. [Los Alamos National Lab., NM (United States)]|[Santa Fe Inst., NM (United States)

    1998-07-01

    This work addresses how human societies, and other diverse and distributed systems, solve collective challenges that are not approachable from the level of the individual, and how the Internet will change the way societies and organizations view problem solving. The authors apply the ideas developed in self-organizing systems to understand self-organization in informational systems. The simplest explanation as to why animals (for example, ants, wolves, and humans) are organized into societies is that these societies enhance the survival of the individuals which make up the populations. Individuals contribute to, as well as adapt to, these societies because they make life easier in one way or another, even though they may not always understand the process, either individually or collectively. Despite the lack of understanding of the how of the process, society during its existence as a species has changed significantly, from separate, small hunting tribes to a highly technological, globally integrated society. The authors combine this understanding of societal dynamics with self-organization on the Internet (the Net). The unique capability of the Net is that it combines, in a common medium, the entire human-technological system in both breadth and depth: breadth in the integration of heterogeneous systems of machines, information and people; and depth in the detailed capturing of the entire complexity of human use and creation of information. When the full diversity of societal dynamics is combined with the accuracy of communication on the Net, a phase transition is argued to occur in problem solving capability. Through conceptual examples, an experiment of collective decision making on the Net and a simulation showing the effect of noise and loss on collective decision making, the authors argue that the resulting symbiotic structure of humans and the Net will evolve as an alternative problem solving approach for groups, organizations and society. Self-organizing

  16. A distance weighted-based approach for self-organized aggregation in robot swarms

    KAUST Repository

    Khaldi, Belkacem

    2017-12-14

    In this paper, a Distance-Weighted K Nearest Neighboring (DW-KNN) topology is proposed to study self-organized aggregation as an emergent swarming behavior within robot swarms. A virtual physics approach is applied among the proposed neighborhood topology to keep the robots together. A distance-weighted function based on a Smoothed Particle Hydrodynamic (SPH) interpolation approach is used as a key factor to identify the K-Nearest neighbors taken into account when aggregating the robots. The intra virtual physical connectivity among these neighbors is achieved using a virtual viscoelastic-based proximity model. With the ARGoS based-simulator, we model and evaluate the proposed approach showing various self-organized aggregations performed by a swarm of N foot-bot robots.

  17. Colour segmentation of multi variants tuberculosis sputum images using self organizing map

    Science.gov (United States)

    Rulaningtyas, Riries; Suksmono, Andriyan B.; Mengko, Tati L. R.; Saptawati, Putri

    2017-05-01

    Lung tuberculosis detection is still identified from Ziehl-Neelsen sputum smear images in low and middle countries. The clinicians decide the grade of this disease by counting manually the amount of tuberculosis bacilli. It is very tedious for clinicians with a lot number of patient and without standardization for sputum staining. The tuberculosis sputum images have multi variant characterizations in colour, because of no standardization in staining. The sputum has more variants colour and they are difficult to be identified. For helping the clinicians, this research examined the Self Organizing Map method for colouring image segmentation in sputum images based on colour clustering. This method has better performance than k-means clustering which also tried in this research. The Self Organizing Map could segment the sputum images with y good result and cluster the colours adaptively.

  18. Self-Organized Criticality in Daily Incidence of Acute Myocardial Infarction

    CERN Document Server

    Selvam, A M; Mody, S M S

    1998-01-01

    Continuous periodogram power spectral analysis of daily incidence of acute myocardial infarction (AMI) reported at a leading hospital for cardiology in Pune, India for the two-year period June 1992 to May 1994 show that the power spectra follow the universal and unique inverse power law form of the statistical normal distribution. Inverse power law form for power spectra of space-time fluctuations are ubiquitous to dynamical systems in nature and have been identified as signatures of self-organized criticality. The unique quantification for self-organized criticality presented in this paper is shown to be intrinsic to quantumlike mechanics governing fractal space-time fluctuation patterns in dynamical systems. The results are consistent with El Naschie's concept of cantorian fractal spacetime characteristics for quantum systems.

  19. Self-organized control in cooperative robots using a pattern formation principle

    Energy Technology Data Exchange (ETDEWEB)

    Starke, Jens, E-mail: j.starke@mat.dtu.d [Department of Mathematics, Technical University of Denmark, Matematiktorvet, Building 303 S, DK-2800 Kongens Lyngby (Denmark); Ellsaesser, Carmen [Institute of Applied Mathematics and Interdisciplinary Center for Scientific Computing, University of Heidelberg, Im Neuenheimer Feld 294, D-69120 Heidelberg (Germany); Fukuda, Toshio [Center for Cooperative Research in Advanced Science and Technology, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603 (Japan)

    2011-05-23

    Self-organized modular approaches proved in nature to be robust and optimal and are a promising strategy to control future concepts of flexible and modular manufacturing processes. We show how this can be applied to a model of flexible manufacturing based on time-dependent robot-target assignment problems where robot teams have to serve manufacturing targets such that an objective function is optimized. Feasibility of the self-organized solutions can be guaranteed even for unpredictable situations like sudden changes in the demands or breakdowns of robots. As example an uncrewed space mission is visualized in a simulation where robots build a space station. - Highlights: Adapting a pattern formation principle to control cooperative robots in a robust way. Flexible manufacturing systems are modelled by time-dependent assignment problems. Coupled selection equations guarantee feasibility of solutions. Solution structure (permutations) is not destroyed by inhomogeneous growth rates. Example of an uncrewed space mission shows effectivity and robustness.

  20. Clustering of the Self-Organizing Map based Approach in Induction Machine Rotor Faults Diagnostics

    Directory of Open Access Journals (Sweden)

    Ahmed TOUMI

    2009-12-01

    Full Text Available Self-Organizing Maps (SOM is an excellent method of analyzingmultidimensional data. The SOM based classification is attractive, due to itsunsupervised learning and topology preserving properties. In this paper, theperformance of the self-organizing methods is investigated in induction motorrotor fault detection and severity evaluation. The SOM is based on motor currentsignature analysis (MCSA. The agglomerative hierarchical algorithms using theWard’s method is applied to automatically dividing the map into interestinginterpretable groups of map units that correspond to clusters in the input data. Theresults obtained with this approach make it possible to detect a rotor bar fault justdirectly from the visualization results. The system is also able to estimate theextent of rotor faults.

  1. Self-organization principles result in robust control of flexible manufacturing systems

    DEFF Research Database (Denmark)

    Nature shows us in our daily life how robust, flexible and optimal self-organized modular constructions work in complex physical, chemical and biological systems, which successfully adapt to new and unexpected situations. A promising strategy is therefore to use such self-organization and pattern...... problems with several autonomous robots and several targets are considered as model of flexible manufacturing systems. Each manufacturing target has to be served in a given time interval by one and only one robot and the total working costs have to be minimized (or total winnings maximized). A specifically...... on adapting pattern formation principles to these problems either no feasibility is guaranteed or only unrealistic toy problems like one-step problems, i.e. no sequences of tasks, are treated. These limitations are overcome in the present work where sequential manufacturing tasks in logical order are fully...

  2. Information and Self-Organization A Macroscopic Approach to Complex Systems

    CERN Document Server

    Haken, Hermann

    2006-01-01

    This book presents the concepts needed to deal with self-organizing complex systems from a unifying point of view that uses macroscopic data. The various meanings of the concept "information" are discussed and a general formulation of the maximum information (entropy) principle is used. With the aid of results from synergetics, adequate objective constraints for a large class of self-organizing systems are formulated and examples are given from physics, life and computer science. The relationship to chaos theory is examined and it is further shown that, based on possibly scarce and noisy data, unbiased guesses about processes of complex systems can be made and the underlying deterministic and random forces determined. This allows for probabilistic predictions of processes, with applications to numerous fields in science, technology, medicine and economics. The extensions of the third edition are essentially devoted to an introduction to the meaning of information in the quantum context. Indeed, quantum inform...

  3. Laser Control of Self-Organization Process in Microscopic Region and Fabrication of Fine Microporous Structure

    Directory of Open Access Journals (Sweden)

    Yukimasa Matsumura

    2012-01-01

    Full Text Available We present a controlling technique of microporous structure by laser irradiation during self-organization process. Self-organization process is fabrication method of microstructure. Polymer solution was dropped on the substrate at high humid condition. Water in air appears dropping air temperature below the dew point. The honeycomb structure with regularly aligned pores on the film was fabricated by attaching water droplets onto the solution surface. We demonstrate that it was possible to prevent forming pores at the region of laser irradiation and flat surface was fabricated. We also demonstrated that a combination structure with two pore sizes and flat surface was produced by a single laser-pulse irradiation. Our method is a unique microfabrication processing technique that combines the advantages of bottom-up and top-down techniques. This method is a promising technique that can be applied to produce for photonic crystals, biological cell culturing, surface science and electronics fields, and so forth.

  4. Probing nanofriction and Aubry-type signatures in a finite self-organized system

    Science.gov (United States)

    Kiethe, J.; Nigmatullin, R.; Kalincev, D.; Schmirander, T.; Mehlstäubler, T. E.

    2017-05-01

    Friction in ordered atomistic layers plays a central role in various nanoscale systems ranging from nanomachines to biological systems. It governs transport properties, wear and dissipation. Defects and incommensurate lattice constants markedly change these properties. Recently, experimental systems have become accessible to probe the dynamics of nanofriction. Here, we present a model system consisting of laser-cooled ions in which nanofriction and transport processes in self-organized systems with back action can be studied with atomic resolution. We show that in a system with local defects resulting in incommensurate layers, there is a transition from sticking to sliding with Aubry-type signatures. We demonstrate spectroscopic measurements of the soft vibrational mode driving this transition and a measurement of the order parameter. We show numerically that both exhibit critical scaling near the transition point. Our studies demonstrate a simple, well-controlled system in which friction in self-organized structures can be studied from classical- to quantum-regimes.

  5. A Self-Organizing Approach to Subject-Verb Number Agreement.

    Science.gov (United States)

    Smith, Garrett; Franck, Julie; Tabor, Whitney

    2018-02-01

    We present a self-organizing approach to sentence processing that sheds new light on notional plurality effects in agreement attraction, using pseudopartitive subject noun phrases (e.g., a bottle of pills). We first show that notional plurality ratings (numerosity judgments for subject noun phrases) predict verb agreement choices in pseudopartitives, in line with the "Marking" component of the Marking and Morphing theory of agreement processing. However, no account to date has derived notional plurality values from independently needed principles of language processing. We argue on the basis of new experimental evidence and a dynamical systems model that the theoretical black box of notional plurality can be unpacked into objectively measurable semantic features. With these semantic features driving structure formation (and hence agreement choice), our model reproduces the human verb production patterns as a byproduct of normal processing. Finally, we discuss how the self-organizing approach might be extended to other agreement attraction phenomena. © 2018 Cognitive Science Society, Inc.

  6. On the Computational Power of Spiking Neural P Systems with Self-Organization

    Science.gov (United States)

    Wang, Xun; Song, Tao; Gong, Faming; Zheng, Pan

    2016-06-01

    Neural-like computing models are versatile computing mechanisms in the field of artificial intelligence. Spiking neural P systems (SN P systems for short) are one of the recently developed spiking neural network models inspired by the way neurons communicate. The communications among neurons are essentially achieved by spikes, i. e. short electrical pulses. In terms of motivation, SN P systems fall into the third generation of neural network models. In this study, a novel variant of SN P systems, namely SN P systems with self-organization, is introduced, and the computational power of the system is investigated and evaluated. It is proved that SN P systems with self-organization are capable of computing and accept the family of sets of Turing computable natural numbers. Moreover, with 87 neurons the system can compute any Turing computable recursive function, thus achieves Turing universality. These results demonstrate promising initiatives to solve an open problem arisen by Gh Păun.

  7. Self-Organized Criticality in Astrophysics The Statistics of Nonlinear Processes in the Universe

    CERN Document Server

    Aschwanden, Markus

    2011-01-01

    The concept of ‘self-organized criticality’ (SOC) has been applied to a variety of problems, ranging from population growth and traffic jams to earthquakes, landslides and forest fires. The technique is now being applied to a wide range of phenomena in astrophysics, such as planetary magnetospheres, solar flares, cataclysmic variable stars, accretion disks, black holes and gamma-ray bursts, and also to phenomena in galactic physics and cosmology. Self-organized Criticality in Astrophysics introduces the concept of SOC and shows that, due to its universality and ubiquity, it is a law of nature. The theoretical framework and specific physical models are described, together with a range of applications in various aspects of astrophyics. The mathematical techniques, including the statistics of random processes, time series analysis, time scale and waiting time distributions, are presented and the results are applied to specific observations of astrophysical phenomena.

  8. From self-organization to emergence: Aesthetic implications of shifting ideas of organization

    Energy Technology Data Exchange (ETDEWEB)

    Hayles, N.K. [English Department, University of California-Los Angeles, Los Angeles, California 90095-1530 (United States)

    1996-06-01

    From 1945{endash}95, a shift took place within cybernetics from a paradigm emphasizing self-organization to one emphasizing emergence. Central in bringing about this shift was the spread of the microcomputer. With its greatly enhanced processing speed and memory capabilities, the microcomputer made simulations possible that could not have been done before. The microcomputer has also been instrumental in effecting a similar change within literary texts. To exemplify the aesthetic implications of the shift from self-organization to emergence, the chapter discusses Vladmir Nabokov{close_quote}s {ital Pale} {ital Fire} and Milorad Pavi{acute c}{close_quote}s {ital Dictionary} {ital of} {ital the} {ital Khazars}: {ital A} {ital Lexicon} {ital Novel} {ital in} 100,000 {ital Words}. {copyright} {ital 1996 American Institute of Physics.}

  9. Social Media to Foster Self-organized Participatory Learning for Disengaged Learners

    OpenAIRE

    Pieter de Vries

    2013-01-01

    The reAct project described in this paper is an innovative learning approach developed and used to re-motivate the disengaged from education and learning to connect to lifelong learning practices. These youngsters constitute a considerable social problem in Europe and the aim of the project is to find ways to recover the intrinsic motivation to learn and thereby improve the opportunities for participation. Key in this innovative strategy is self-organized learning, the learner in control of t...

  10. Changes in the Entropy and Information Difference During Self-Organization of Nonextensive Systems in Parastatistics

    Science.gov (United States)

    Zaripov, R. G.

    2017-09-01

    On the basis of the method of Bose quantum states in parastatistics for quantum nonextensive systems, the evolution of the parametric entropy and the information difference under induced transitions between stationary states in the space of control parameters during self-organization is considered. S and I theorems on changes in renormalized measures under the Gibbs condition on the constancy of the total energy and the total number of particles are proven.

  11. An efficient approach to the travelling salesman problem using self-organizing maps.

    Science.gov (United States)

    Vieira, Frederico Carvalho; Dória Neto, Adrião Duarte; Costa, José Alfredo Ferreira

    2003-04-01

    This paper presents an approach to the well-known Travelling Salesman Problem (TSP) using Self-Organizing Maps (SOM). The SOM algorithm has interesting topological information about its neurons configuration on cartesian space, which can be used to solve optimization problems. Aspects of initialization, parameters adaptation, and complexity analysis of the proposed SOM based algorithm are discussed. The results show an average deviation of 3.7% from the optimal tour length for a set of 12 TSP instances.

  12. Controlling the dynamics of a self-organized structure using a rf-field

    Energy Technology Data Exchange (ETDEWEB)

    Talasman, S.J.; Ignat, M

    2004-03-15

    We investigate the influence of an external rf-field upon a plasma self-organized structure. We show that depending on the intensity of this field, though it is at very low values, the dynamics of the structure can be easily controlled over a wide range of the state parameters values. This could be considered as a non-feedback method of dynamics control.

  13. Self-organization in psychotherapy: testing the synergetic model of change processes

    Science.gov (United States)

    Schiepek, Günter K.; Tominschek, Igor; Heinzel, Stephan

    2014-01-01

    In recent years, models have been developed that conceive psychotherapy as a self-organizing process of bio-psycho-social systems. These models originate from the theory of self-organization (Synergetics), from the theory of deterministic chaos, or from the approach of self-organized criticality. This process-outcome study examines several hypotheses mainly derived from Synergetics, including the assumption of discontinuous changes in psychotherapy (instead of linear incremental gains), the occurrence of critical instabilities in temporal proximity of pattern transitions, the hypothesis of necessary stable boundary conditions during destabilization processes, and of motivation to change playing the role of a control parameter for psychotherapeutic self-organization. Our study was realized at a day treatment center; 23 patients with obsessive compulsive disorder (OCD) were included. Client self-assessment was performed by an Internet-based process monitoring (referred to as the Synergetic Navigation System), whereby daily ratings were recorded through administering the Therapy Process Questionnaire (TPQ). The process measures of the study were extracted from the subscale dynamics (including the dynamic complexity of their time series) of the TPQ. The outcome criterion was measured by the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) which was completed pre-post and on a bi-weekly schedule by all patients. A second outcome criterion was based on the symptom severity subscale of the TPQ. Results supported the hypothesis of discontinuous changes (pattern transitions), the occurrence of critical instabilities preparing pattern transitions, and of stable boundary conditions as prerequisites for such transitions, but not the assumption of motivation to change as a control parameter. PMID:25324801

  14. Evidence for self-organized criticality in the Bean critical state in superconductors

    Science.gov (United States)

    Aegerter, C. M.

    1998-08-01

    The time dependence of the magnetization of a type-II superconductor in the Bean critical state is studied. It is found that evolution occurs in the form of bursts, consistent with a model exhibiting self-organized criticality. The distribution of step sizes follows a power law with an exponent of α~= 2. At high temperatures the distribution is Gaussian-like, as would be expected in an equilibrium situation. This may allow the experimental study of the occurrence of criticality.

  15. Self-organization in the tornado: the new approach in the tornado description

    OpenAIRE

    Bystrai, G. P.; Lykov, I. A

    2012-01-01

    For the mathematical modeling of highly non-equilibrium and nonlinear processes in a tornado in this paper a new approach based on nonlinear equations of momentum transfer with function of sources and sinks is suggested. In constructing the model thermodynamic description is used, which is not entered before and allows discovering new principles of self-organization in a tornado. This approach gives fairly consistent physical results. This is an attempt to answer some fundamental questions co...

  16. Neurobiologically realistic determinants of self-organized criticality in networks of spiking neurons.

    Directory of Open Access Journals (Sweden)

    Mikail Rubinov

    2011-06-01

    Full Text Available Self-organized criticality refers to the spontaneous emergence of self-similar dynamics in complex systems poised between order and randomness. The presence of self-organized critical dynamics in the brain is theoretically appealing and is supported by recent neurophysiological studies. Despite this, the neurobiological determinants of these dynamics have not been previously sought. Here, we systematically examined the influence of such determinants in hierarchically modular networks of leaky integrate-and-fire neurons with spike-timing-dependent synaptic plasticity and axonal conduction delays. We characterized emergent dynamics in our networks by distributions of active neuronal ensemble modules (neuronal avalanches and rigorously assessed these distributions for power-law scaling. We found that spike-timing-dependent synaptic plasticity enabled a rapid phase transition from random subcritical dynamics to ordered supercritical dynamics. Importantly, modular connectivity and low wiring cost broadened this transition, and enabled a regime indicative of self-organized criticality. The regime only occurred when modular connectivity, low wiring cost and synaptic plasticity were simultaneously present, and the regime was most evident when between-module connection density scaled as a power-law. The regime was robust to variations in other neurobiologically relevant parameters and favored systems with low external drive and strong internal interactions. Increases in system size and connectivity facilitated internal interactions, permitting reductions in external drive and facilitating convergence of postsynaptic-response magnitude and synaptic-plasticity learning rate parameter values towards neurobiologically realistic levels. We hence infer a novel association between self-organized critical neuronal dynamics and several neurobiologically realistic features of structural connectivity. The central role of these features in our model may reflect

  17. Stochastic Resonance, Self-Organization and Information Dynamics in Multistable Systems

    Directory of Open Access Journals (Sweden)

    Grégoire Nicolis

    2016-05-01

    Full Text Available A class of complex self-organizing systems subjected to fluctuations of environmental or intrinsic origin and to nonequilibrium constraints in the form of an external periodic forcing is analyzed from the standpoint of information theory. Conditions under which the response of information entropy and related quantities to the nonequilibrium constraint can be optimized via a stochastic resonance-type mechanism are identified, and the role of key parameters is assessed.

  18. Authoring Tool for Identifying Learning Styles, Using Self-Organizing Maps on Mobile Devices

    Directory of Open Access Journals (Sweden)

    Ramón Zatarain Cabada

    2011-05-01

    Full Text Available This work explores a methodological proposal whose main objective is the identification of learning styles using a method of self-organizing maps designed to work, for the most part, on mobile devices. These maps can work in real time and without direct student interaction, which implies the absence of prior information. The results generated are an authoring tool for adaptive courses in Web 2.0 environments.

  19. Self organization of understanding, consciousness, emotions and knowledge: Cell, brain, mind, sex, life

    OpenAIRE

    Souček, Branko

    2008-01-01

    Background and Purpose: This work develops the new intelligence Self Organization, SO; theory and practice. Materials and Methods: The experimental data and the theoretical results come from the animal and human cell, brain, mind and sex: firefly, katydid, frog, bird, rodent, human prefrontal cortex. Results: SO is a never ending, chaotic process that grows from the bottom up, without the leader or central control. It combines the inherited instructions and rules into complex processes ...

  20. Student''s linguistic personality and multicultural self-organization through foreign language teaching

    OpenAIRE

    E. Isaev

    2015-01-01

    The article traces the features of linguistic personality's formation in the context of globalization processes in the world. Multicultural self-organization is notable for students' ability to build up the dialogue of cultures in their professional occupation and considered to be a triune person's education, arising as the result of integration of cross-cultural linguistic personality's sphere, global attitude to foreign culture and cultural self-determination. The inclusion of the term "lin...

  1. Biogenic gradients in algal density affect the emergent properties of spatially self-organized mussel beds.

    Science.gov (United States)

    Liu, Quan-Xing; Weerman, Ellen J; Gupta, Rohit; Herman, Peter M J; Olff, Han; van de Koppel, Johan

    2014-07-06

    Theoretical models highlight that spatially self-organized patterns can have important emergent effects on the functioning of ecosystems, for instance by increasing productivity and affecting the vulnerability to catastrophic shifts. However, most theoretical studies presume idealized homogeneous conditions, which are rarely met in real ecosystems. Using self-organized mussel beds as a case study, we reveal that spatial heterogeneity, resulting from the large-scale effects of mussel beds on their environment, significantly alters the emergent properties predicted by idealized self-organization models that assume homogeneous conditions. The proposed model explicitly considers that the suspended algae, the prime food for the mussels, are supplied by water flow from the seaward boundary of the bed, which causes in combination with consumption a gradual depletion of algae over the simulated domain. Predictions of the model are consistent with properties of natural mussel patterns observed in the field, featuring a decline in mussel biomass and a change in patterning. Model analyses reveal a fundamental change in ecosystem functioning when this self-induced algal depletion gradient is included in the model. First, no enhancement of secondary productivity of the mussels comparing with non-patterns states is predicted, irrespective of parameter setting; the equilibrium amount of mussels is entirely set by the input of algae. Second, alternate stable states, potentially present in the original (no algal gradient) model, are absent when gradual depletion of algae in the overflowing water layer is allowed. Our findings stress the importance of including sufficiently realistic environmental conditions when assessing the emergent properties of self-organized ecosystems.

  2. Self-organizing maps and its applications in sleep apnea research and molecular genetics

    OpenAIRE

    Guimaraes, Gabriela; Urfer, Wolfgang

    2000-01-01

    This paper presents the application of special unsupervised neural networks (self-organizing maps) to different domains, as sleep apnea discovery, protein sequences analysis and tumor classification. An enhancement of the original algorithm, as well as the introduction of several hierachical levels enables the discovery of complex structures as present in this type of applications. Furthermore, an integration of unsupervised neural networks with hidden markov models is proposed.

  3. Self-organization of a hybrid nanostructure consisting of a nanoneedle and nanodot.

    Science.gov (United States)

    Liu, Hai; Wu, Junsheng; Wang, Ying; Chow, Chee Lap; Liu, Qing; Gan, Chee Lip; Tang, Xiaohong; Rawat, Rajdeep Singh; Tan, Ooi Kiang; Ma, Jan; Huang, Yizhong

    2012-09-24

    A special materials system that allows the self-organization of a unique hybrid nanonipple structure is developed. The system consists of a nanoneedle with a small nanodot sitting on top. Such hybrid nanonipples provide building blocks to assemble functional devices with significantly improved performance. The application of the system to high-sensitivity gas sensors is also demonstrated. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Self-organization of spiking neural network that generates autonomous behavior in a real mobile robot.

    Science.gov (United States)

    Alnajjar, Fady; Murase, Kazuyuki

    2006-08-01

    In this paper, we propose self-organization algorithm of spiking neural network (SNN) applicable to autonomous robot for generation of adoptive and goal-directed behavior. First, we formulated a SNN model whose inputs and outputs were analog and the hidden unites are interconnected each other. Next, we implemented it into a miniature mobile robot Khepera. In order to see whether or not a solution(s) for the given task(s) exists with the SNN, the robot was evolved with the genetic algorithm in the environment. The robot acquired the obstacle avoidance and navigation task successfully, exhibiting the presence of the solution. After that, a self-organization algorithm based on a use-dependent synaptic potentiation and depotentiation at synapses of input layer to hidden layer and of hidden layer to output layer was formulated and implemented into the robot. In the environment, the robot incrementally organized the network and the given tasks were successfully performed. The time needed to acquire the desired adoptive and goal-directed behavior using the proposed self-organization method was much less than that with the genetic evolution, approximately one fifth.

  5. SOTXTSTREAM: Density-based self-organizing clustering of text streams.

    Directory of Open Access Journals (Sweden)

    Avory C Bryant

    Full Text Available A streaming data clustering algorithm is presented building upon the density-based self-organizing stream clustering algorithm SOSTREAM. Many density-based clustering algorithms are limited by their inability to identify clusters with heterogeneous density. SOSTREAM addresses this limitation through the use of local (nearest neighbor-based density determinations. Additionally, many stream clustering algorithms use a two-phase clustering approach. In the first phase, a micro-clustering solution is maintained online, while in the second phase, the micro-clustering solution is clustered offline to produce a macro solution. By performing self-organization techniques on micro-clusters in the online phase, SOSTREAM is able to maintain a macro clustering solution in a single phase. Leveraging concepts from SOSTREAM, a new density-based self-organizing text stream clustering algorithm, SOTXTSTREAM, is presented that addresses several shortcomings of SOSTREAM. Gains in clustering performance of this new algorithm are demonstrated on several real-world text stream datasets.

  6. Exponential Self-Organization and Moore’s Law: Measures and Mechanisms

    Directory of Open Access Journals (Sweden)

    Georgi Yordanov Georgiev

    2017-01-01

    Full Text Available The question of how complex systems become more organized and efficient with time is open. Examples are the formation of elementary particles from pure energy, the formation of atoms from particles, the formation of stars and galaxies, and the formation of molecules from atoms, of organisms, and of the society. In this sequence, order appears inside complex systems and randomness (entropy is expelled to their surroundings. Key features of self-organizing systems are that they are open and they are far away from equilibrium, with increasing energy flows through them. This work searches for global measures of such self-organizing systems, which are predictable and do not depend on the substrate of the system studied. Our results will help to understand the existence of complex systems and mechanisms of self-organization. In part we also provide insights, in this work, about the underlying physical essence of Moore’s law and the multiple logistic growth observed in technological progress.

  7. Self-organization vs Watchmaker: stochastic gene expression and cell differentiation.

    Science.gov (United States)

    Kurakin, Alexei

    2005-01-01

    Cell differentiation and organism development are traditionally described in deterministic terms of program and design, echoing a conventional clockwork perception of the cell on another scale. However, the current experimental reality of stochastic gene expression and cell plasticity is poorly consistent with the ideas of design, purpose and determinism, suggesting that the habit of classico-mechanistic interpretation of life phenomena may handicap our ability to adequately comprehend and model biological systems. An alternative conceptualization of cell differentiation and development is proposed where the developing organism is viewed as a dynamic self-organizing system of adaptive interacting agents. This alternative interpretation appears to be more consistent with the probabilistic nature of gene expression and the phenomena of cell plasticity, and is coterminous with the novel emerging image of the cell as a self-organizing molecular system. I suggest that stochasticity, as a principle of differentiation and adaptation, and self-organization, as a concept of emergence, have the potential to provide an interpretational framework that unites phenomena across different scales of biological organization, from molecules to societies.

  8. Does Prigogine’s Non-linear Thermodynamics Support Popular Philosophical Discussions of Self-Organization?

    Directory of Open Access Journals (Sweden)

    Alexander Pechenkin

    2015-10-01

    Full Text Available The article is concerned with the philosophical talks which became popular in the 1980s and have kept their popularity till now–the philosophical essays about self-organization. The author attempts to find out as to which extent are these essays founded on the scientific theory to which they regularly refer, that is, Ilya Prigogine’s non-linear thermodynamics. The author insists that the equivalent of self-organization in Prigogine’s theoretical physics is the concept of dissipative structure. The concept of selforganization, as it is used in philosophical literature, presupposes a sequence of extrapolations, the first extrapolation being conducted by Prigogine and his coauthors. They became to use the concept of dissipative structure beyond the rigorous theory of this phenomenon. The subsequent step was that the scientific term “dissipative structure” was replaced by the vague concept “self-organization” in many popular and semi-popular books and papers. The author also emphasizes that by placing the concept of self-organization into the framework of philosophical concepts (the picture of the world, the ideals of scientific thought, the contemporary scientific revolution, etc. a philosopher conducts the extrapolation of extrapolation and comes to a kind of what Edmund Husserl called Weltanschauung (‘worldview’ philosophy.

  9. Formation of self-organized nanoporous anodic oxide from metallic gallium.

    Science.gov (United States)

    Pandey, Bipin; Thapa, Prem S; Higgins, Daniel A; Ito, Takashi

    2012-09-25

    This paper reports the formation of self-organized nanoporous gallium oxide by anodization of solid gallium metal. Because of its low melting point (ca. 30 °C), metallic gallium can be shaped into flexible structures, permitting the fabrication of nanoporous anodic oxide monoliths within confined spaces like the inside of a microchannel. Here, solid gallium films prepared on planar substrates were employed to investigate the effects of anodization voltage (1, 5, 10, 15 V) and H(2)SO(4) concentration (1, 2, 4, 6 M) on anodic oxide morphology. Self-organized nanopores aligned perpendicular to the film surface were obtained upon anodization of gallium films in ice-cooled 4 and 6 M aqueous H(2)SO(4) at 10 and 15 V. Nanopore formation could be recognized by an increase in anodic current after a current decrease reflecting barrier oxide formation. The average pore diameter was in the range of 18-40 nm with a narrow diameter distribution (relative standard deviation ca. 10-20%), and was larger at lower H(2)SO(4) concentration and higher applied voltage. The maximum thickness of nanoporous anodic oxide was ca. 2 μm. In addition, anodic formation of self-organized nanopores was demonstrated for a solid gallium monolith incorporated at the end of a glass capillary. Nanoporous anodic oxide monoliths formed from a fusible metal will lead to future development of unique devices for chemical sensing and catalysis.

  10. Intestinal epithelial organoids fuse to form self-organizing tubes in floating collagen gels.

    Science.gov (United States)

    Sachs, Norman; Tsukamoto, Yoshiyuki; Kujala, Pekka; Peters, Peter J; Clevers, Hans

    2017-03-15

    Multiple recent examples highlight how stem cells can self-organize in vitro to establish organoids that closely resemble their in vivo counterparts. Single Lgr5 + mouse intestinal stem cells can be cultured under defined conditions forming ever-expanding epithelial organoids that retain cell polarization, cell type diversity and anatomical organization of the in vivo epithelium. Although exhibiting a remarkable level of self-organization, the so called 'mini-guts' have a closed cystic structure of microscopic size. Here, we describe a simple protocol to generate macroscopic intestinal tubes from small cystic organoids. Embedding proliferating organoids within a contracting floating collagen gel allows them to align and fuse to generate macroscopic hollow structures ('tubes') that are lined with a simple epithelium containing all major cell types (including functional stem cells) of the small intestine. Cells lining the central contiguous lumen closely resemble the epithelial cells on luminal villi in vivo , whereas buds that protrude from the main tube into the surrounding matrix closely resemble crypts. Thus, the remarkable self-organizing properties of Lgr5 + stem cells extend beyond the level of the microscopic cystic organoid to the next, macroscopic, level of tube formation. © 2017. Published by The Company of Biologists Ltd.

  11. Self-organization is a dynamic and lineage-intrinsic property of mammary epithelial cells

    Energy Technology Data Exchange (ETDEWEB)

    Chanson, L. [Ecole Polytechnique Federale de Lausanne (Switzerland). Inst. of Bioengineering; Brownfield, D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Life Sciences Div.; Univ. of California, Berkeley, CA (United States). Dept. of Bioengineering; Garbe, J. C. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Life Sciences Div.; Kuhn, I. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Life Sciences Div.; Stampfer, M. R. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Life Sciences Div.; Bissell, M. J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Life Sciences Div.; LaBarge, M. A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Life Sciences Div.

    2011-02-07

    Loss of organization is a principle feature of cancers; therefore it is important to understand how normal adult multilineage tissues, such as bilayered secretory epithelia, establish and maintain their architectures. The self-organization process that drives heterogeneous mixtures of cells to form organized tissues is well studied in embryology and with mammalian cell lines that were abnormal or engineered. Here we used a micropatterning approach that confined cells to a cylindrical geometry combined with an algorithm to quantify changes of cellular distribution over time to measure the ability of different cell types to self-organize relative to each other. Using normal human mammary epithelial cells enriched into pools of the two principal lineages, luminal and myoepithelial cells, we demonstrated that bilayered organization in mammary epithelium was driven mainly by lineage-specific differential E-cadherin expression, but that P-cadherin contributed specifically to organization of the myoepithelial layer. Disruption of the actomyosin network or of adherens junction proteins resulted in either prevention of bilayer formation or loss of preformed bilayers, consistent with continual sampling of the local microenvironment by cadherins. Together these data show that self-organization is an innate and reversible property of communities of normal adult human mammary epithelial cells.

  12. Complexity and Self-Organized Criticality of Solid Earth System(Ⅰ)

    Institute of Scientific and Technical Information of China (English)

    1998-01-01

    The author puts forward the proposition of "Complexity and Self-Organized Criticality of Solid Earth System" in the light of: (1) the science of complexity studies the mechanisms of emergence of complexity and is the science of the 21st century, (2) the study of complexity of the earth system would be one of the growing points occupying a strategic position in the development of geosciences in the 21st century. By the proposition we try to cogitate from a new viewpoint the ancient yet ever-new solid earth system. The author abstracts the fundamental problem of the solid earth system from the essence of the generalized geological systems and processes which reads: "the complexity and self-organized criticality of the global nature, structure and dynamical behavior of the whole solid earth system emerging from the multiple coupling and superposition of non-linear interactions among the multicomponents of the earths material and the multiple generalized geological (geological, geophysical, and geochemical) processes". Starting from this cognizance the author proposes eight major themes and the methodology of researches on the complexity and self-organized criticality of the solid earth system.

  13. Complexity and Self-Organized Criticality of Solid Earth System(Ⅱ)

    Institute of Scientific and Technical Information of China (English)

    1998-01-01

    The author puts forward the proposition of "Complexity and Self-Organized Criticality of Solid Earth System" in the light of: (1) the science of complexity studies the mechanisms of emergence of complexity and is the science of the 21st century, (2) the study of complexity of the earth system would be one of the growing points occupying a strategic position in the development of geosciences in the 21st century. By the proposition we try to cogitate from a new viewpoint the ancient yet ever-new solid earth system. The author abstracts the fundamental problem of the solid earth system from the essence of the generalized geological systems and processes which reads: "the complexity and self-organized criticality of the global nature, structure and dynamical behavior of the whole solid earth system emerging from the multiple coupling and superposition of non-linear interactions among the multicomponents of the earths material and the multiple generalized geological (geological, geophysical, and geochemical) processes". Starting from this cognizance, the author proposes eight major themes and the methodology of researches on the complexity and self-organized criticality of the solid earth system.

  14. Hybrid Societies: Challenges and Perspectives in the Design of Collective Behavior in Self-organizing Systems

    Directory of Open Access Journals (Sweden)

    Heiko eHamann

    2016-04-01

    Full Text Available Hybrid societies are self-organizing, collective systems composed of different components, for example, natural and artificial parts (bio-hybrid or human beings interacting with and through technical systems (socio-technical. Many different disciplines investigate methods and systems closely related to the design of hybrid societies. A~stronger collaboration between these disciplines could allow for re-use of methods and create significant synergies. We identify three main areas of challenges in the design of self-organizing hybrid societies. First, we identify the formalization challenge. There is an urgent need for a generic model that allows a description and comparison of collective hybrid societies. Second, we identify the system design challenge. Starting from the formal specification of the system, we need to develop an integrated design process. Third, we identify the challenge of interdisciplinarity. Current research on self-organizing hybrid societies stretches over many different fields and hence requires the re-use and synthesis of methods at intersections between disciplines. We then conclude by presenting our perspective for future approaches with high potential in this area.

  15. Alternative mechanisms alter the emergent properties of self-organization in mussel beds.

    Science.gov (United States)

    Liu, Quan-Xing; Weerman, Ellen J; Herman, Peter M J; Olff, Han; van de Koppel, Johan

    2012-07-22

    Theoretical models predict that spatial self-organization can have important, unexpected implications by affecting the functioning of ecosystems in terms of resilience and productivity. Whether and how these emergent effects depend on specific formulations of the underlying mechanisms are questions that are often ignored. Here, we compare two alternative models of regular spatial pattern formation in mussel beds that have different mechanistic descriptions of the facilitative interactions between mussels. The first mechanism involves a reduced mussel loss rate at high density owing to mutual protection between the mussels, which is the basis of prior studies on the pattern formation in mussels. The second mechanism assumes, based on novel experimental evidence, that mussels feed more efficiently on top of mussel-generated hummocks. Model simulations point out that the second mechanism produces very similar types of spatial patterns in mussel beds. Yet the mechanisms predict a strikingly contrasting effect of these spatial patterns on ecosystem functioning, in terms of productivity and resilience. In the first model, where high mussel densities reduce mussel loss rates, patterns are predicted to strongly increase productivity and decrease the recovery time of the bed following a disturbance. When pattern formation is generated by increased feeding efficiency on hummocks, only minor emergent effects of pattern formation on ecosystem functioning are predicted. Our results provide a warning against predictions of the implications and emergent properties of spatial self-organization, when the mechanisms that underlie self-organization are incompletely understood and not based on the experimental study.

  16. Self-organized translational wheeling motion in stochastic self-assembling modules.

    Science.gov (United States)

    Miyashita, Shuhei; Nakajima, Kohei; Nagy, Zoltán; Pfeifer, Rolf

    2013-01-01

    Self-organization is a phenomenon found in biomolecular self-assembly by which proteins are spontaneously driven to assemble and attain various functionalities. This study reports on self-organized behavior in which distributed centimeter-sized modules stochastically aggregate and exhibit a translational wheeling motion. The system consists of two types of centimeter-sized water-floating modules: a triangular-shaped module that is equipped with a vibration motor and a permanent magnet (termed the active module), which can quasi-randomly rove around; and circular modules that are equipped with permanent magnets (termed passive modules). In its quasi-random movement in water, the active module picks up passive modules through magnetic attraction. The contacts between the modules induce a torque transfer from the active module to the passive modules. This results in rotational motion of the passive modules. As a consequence of the shape difference between the triangular module and the circular module, the passive modules rotate like wheels, being kept on the same edges as the active module. The motion of the active module is examined, as well as the characteristics and behavior of the self-organization process.

  17. Minimal agent based model for financial markets I. Origin and self-organization of stylized facts

    Science.gov (United States)

    Alfi, V.; Cristelli, M.; Pietronero, L.; Zaccaria, A.

    2009-02-01

    We introduce a minimal agent based model for financial markets to understand the nature and self-organization of the stylized facts. The model is minimal in the sense that we try to identify the essential ingredients to reproduce the most important deviations of price time series from a random walk behavior. We focus on four essential ingredients: fundamentalist agents which tend to stabilize the market; chartist agents which induce destabilization; analysis of price behavior for the two strategies; herding behavior which governs the possibility of changing strategy. Bubbles and crashes correspond to situations dominated by chartists, while fundamentalists provide a long time stability (on average). The stylized facts are shown to correspond to an intermittent behavior which occurs only for a finite value of the number of agents N. Therefore they correspond to finite size effects which, however, can occur at different time scales. We propose a new mechanism for the self-organization of this state which is linked to the existence of a threshold for the agents to be active or not active. The feedback between price fluctuations and number of active agents represents a crucial element for this state of self-organized intermittency. The model can be easily generalized to consider more realistic variants.

  18. Spatial self-organized patterning in seagrasses along a depth gradient of an intertidal ecosystem.

    Science.gov (United States)

    van der Heide, Tjisse; Bouma, Tjeerd J; van Nes, Egbert H; van de Koppel, Johan; Scheffer, Marten; Roelofs, Jan G M; van Katwijk, Marieke M; Smolders, Alfons J P

    2010-02-01

    The spatial structure of seagrass landscapes is typically ascribed to the direct influence of physical factors such as hydrodynamics, light, and sediment transport. We studied regularly interspaced banded patterns, formed by elongated patches of seagrass, in a small-scale intertidal ecosystem. We investigated (1) whether the observed spatial patterns may arise from feedback interactions between seagrass and its abiotic environment and (2) whether changes in abiotic conditions may lead to predictable changes in these spatial patterns. Field measurements, experiments, and a spatially explicit computer model identified a "scale-dependent feedback" (a mechanism for spatial self-organization) as a possible cause for the banded patterns. Increased protection from uprooting by improved anchoring with increasing seagrass density caused a local positive feedback. Sediment erosion around seagrass shoots increased with distance through the seagrass bands, hence causing a long-range negative feedback. Measurements across the depth gradient of the intertidal, together with model simulations, demonstrated that seagrass cover and mean patch size were predictably influenced by additional external stress caused by light limitation and desiccation. Thus, our study provides direct empirical evidence for a consistent response of spatial self-organized patterns to changing abiotic conditions, suggesting a potential use for self-organized spatial patterns as stress indicators in ecosystems.

  19. A novel approach, based on BLSOMs (Batch Learning Self-Organizing Maps), to the microbiome analysis of ticks

    National Research Council Canada - National Science Library

    Nakao, Ryo; Abe, Takashi; Nijhof, Ard M; Yamamoto, Seigo; Jongejan, Frans; Ikemura, Toshimichi; Sugimoto, Chihiro

    2013-01-01

    .... The resulting sequence reads were phylotyped using a Batch Learning Self-Organizing Map (BLSOM) program, which allowed phylogenetic estimation based on similarity of oligonucleotide frequencies, and functional annotation by BLASTX similarity searches...

  20. Early Front-End Innovation Decisions for Self-Organized Industrial Symbiosis Dynamics-A Case Study on Lignin Utilization

    National Research Council Canada - National Science Library

    Magdalena Gabriel; Josef-Peter Schöggl; Alfred Posch

    2017-01-01

    The emergence of self-organized industrial symbiosis (IS) is based on the expectations of industrial actors regarding financial and/or environmental benefits through symbiotic inter-company linkages...

  1. Evolution of self-organization in nano-structured PVD coatings under extreme tribological conditions

    Energy Technology Data Exchange (ETDEWEB)

    Fox-Rabinovich, G., E-mail: gfox@mcmaster.ca [Department of Mechanical Engineering, McMaster University, 1280 Main St. W., Hamilton, ON, Canada L8S 4L7 (Canada); Kovalev, A. [Surface Phenomena Researches Group, CNIICHERMET, 9/23, 2-nd Baumanskaya Street, Moscow 105005 (Russian Federation); Aguirre, M.H. [Laboratory of Advanced Microscopy, Institute of Nanoscience of Aragón, University of Zaragoza, 50018 Zaragoza (Spain); Yamamoto, K. [Materials Research Laboratory, Kobe Steel Ltd, 1-5-5 Takatsuda-dai, Nishi-ku, Kobe 651-2271, Hyogo (Japan); Veldhuis, S. [Department of Mechanical Engineering, McMaster University, 1280 Main St. W., Hamilton, ON, Canada L8S 4L7 (Canada); Gershman, I. [All-Russian Railway Research Institute, 10 Third Mytishchinskaya Street, Moscow 29851 (Russian Federation); Rashkovskiy, A. [Surface Phenomena Researches Group, CNIICHERMET, 9/23, 2-nd Baumanskaya Street, Moscow 105005 (Russian Federation); Endrino, J.L. [Albengoa Research, Energia Solar 1, Palmas Altas, Seville 41014 (Spain); Beake, B. [Micro Materials Limited, Willow House, Yale Business Village, Ellice Way, Wrexham LL13 7YL (United Kingdom); Dosbaeva, G. [Department of Mechanical Engineering, McMaster University, 1280 Main St. W., Hamilton, ON, Canada L8S 4L7 (Canada); Wainstein, D. [Surface Phenomena Researches Group, CNIICHERMET, 9/23, 2-nd Baumanskaya Street, Moscow 105005 (Russian Federation); Yuan, Junifeng; Bunting, J.W. [Department of Mechanical Engineering, McMaster University, 1280 Main St. W., Hamilton, ON, Canada L8S 4L7 (Canada)

    2014-04-01

    Highlights: • The evolution of self-organization under extreme frictional conditions has been studied. • Comprehensive characterization of the tribo-films was made using various surface analytical techniques. • During the running-in stage, mullite tribo-ceramics predominate on the surface of the nano-multilayer coating, establishing a functional hierarchy within the layer of tribo-films. • It is possible to control tribo-film evolution during self-organization by means of an increase in structural complexity and the non-equilibrium state of the surface engineered layer. - Abstract: The evolution of the self-organization process where dissipative structures are formed under the extreme frictional conditions associated with high performance dry machining of hardened steels has been studied in detail. The emphasis was on the progressive studies of surface transformations within multilayer and monolayer TiAlCrSiYN-based PVD coatings during the running-in stage of wear when self-organization process occurs. The coating layer was characterized by high resolution electron energy-loss spectroscopy (HREELS). It is shown that the nano-multilayer coating possesses higher non-equilibrium structure in comparison to the monolayer. Comprehensive studies of the tribo-films (dissipative structures) formed on the friction surface were made using a number of advanced surface characterization techniques such as X-ray photoelectron spectroscopy (XPS) and X-ray absorption near edge structure (XANES). The data obtained for the tribo-films was combined with the detailed TEM studies of the structural and phase transformations within the underlying coating layer. This data was related to the micro-mechanical characteristics of the coating layer and its wear resistance. It was demonstrated that the evolution of the self-organization process is strongly controlled by the characteristics of the tribo-films formed at different stages of the wear process. Within running-in stage (after

  2. Synchrotron X-ray Scattering from Self-organized Soft Nanostructures in Clays

    Science.gov (United States)

    Fossum, J. O.

    2009-04-01

    In the general context of self-organization of nanoparticles (in our case clay particles), and transitions in such structures, we study interconnected universal complex physical phenomena such as: (i) spontaneous gravitationally induced phase separation and nematic self-organization in systems of anisotropic clay nanoparticles in aqueous suspension, including studies of isotropic to nematic transitions [1,2] (ii) transitions from biaxial to uniaxial nematics by application of external magnetic field to self-organized systems of the same anisotropic (diamagnetic) clay nanoparticle systems [3,4] (iii) guided self-organization into chainlike structures of the same anisotropic clay nanoparticles in oil suspension when subjected to external electrical fields (electrorheological structures of polarized nanoparticles), and the stability of, and transitions of, such structures, when subjected to external mechanical stress [5,6] The experimental techniques used by us include synchrotron X-ray scattering, neutron scattering, rheometry. microscopy and magnetic resonance. We have demonstrated that clays may be used as good model systems for studies of universal physical phenomena and transitions in self-organized nanostructured soft and complex matter. Self-organization and related transitions in clay systems in particular, may have practical relevance for nano-patterning, properties of nanocomposites, and macroscopically anisotropic gels, among many other applications [7]. The synchrotron experiments have been performed at LNLS-Brazil, PLS- Korea, BNL-USA and ESRF-France. Acknowledgments: Collaborators, postdocs and students at NTNU-Norway, UiO-Norway, IFE-Norway, BNL-USA, LNLS-Brazil, UFPE-Brazil, UnB-Brazil, Univ. Amsterdam-Netherlands, Univ.Paris 7-France and other places. This research has been supported by the Research Council of Norway (RCN), through the NANOMAT, SUP and FRINAT Programs. References 1. J.O. Fossum, E. Gudding, D.d.M. Fonseca, Y. Meheust, E. DiMasi, T

  3. Self-organizing systems in planetary physics: Harmonic resonances of planet and moon orbits

    Science.gov (United States)

    Aschwanden, Markus J.

    2018-01-01

    The geometric arrangement of planet and moon orbits into a regularly spaced pattern of distances is the result of a self-organizing system. The positive feedback mechanism that operates a self-organizing system is accomplished by harmonic orbit resonances, leading to long-term stable planet and moon orbits in solar or stellar systems. The distance pattern of planets was originally described by the empirical Titius-Bode law, and by a generalized version with a constant geometric progression factor (corresponding to logarithmic spacing). We find that the orbital periods Ti and planet distances Ri from the Sun are not consistent with logarithmic spacing, but rather follow the quantized scaling (Ri + 1 /Ri) =(Ti + 1 /Ti) 2 / 3 =(Hi + 1 /Hi) 2 / 3 , where the harmonic ratios are given by five dominant resonances, namely (Hi + 1 :Hi) =(3 : 2) ,(5 : 3) ,(2 : 1) ,(5 : 2) ,(3 : 1) . We find that the orbital period ratios tend to follow the quantized harmonic ratios in increasing order. We apply this harmonic orbit resonance model to the planets and moons in our solar system, and to the exo-planets of 55 Cnc and HD 10180 planetary systems. The model allows us a prediction of missing planets in each planetary system, based on the quasi-regular self-organizing pattern of harmonic orbit resonance zones. We predict 7 (and 4) missing exo-planets around the star 55 Cnc (and HD 10180). The accuracy of the predicted planet and moon distances amounts to a few percents. All analyzed systems are found to have ≈ 10 resonant zones that can be occupied with planets (or moons) in long-term stable orbits.

  4. Self-Organized Governance Networks for Ecosystem Management: Who Is Accountable?

    Directory of Open Access Journals (Sweden)

    Thomas Hahn

    2011-06-01

    Full Text Available Governance networks play an increasingly important role in ecosystem management. The collaboration within these governance networks can be formalized or informal, top-down or bottom-up, and designed or self-organized. Informal self-organized governance networks may increase legitimacy if a variety of stakeholders are involved, but at the same time, accountability becomes blurred when decisions are taken. Basically, democratic accountability refers to ways in which citizens can control their government and the mechanisms for doing so. Scholars in ecosystem management are generally positive to policy/governance networks and emphasize its potential for enhancing social learning, adaptability, and resilience in social-ecological systems. Political scientists, on the other hand, have emphasized the risk that the public interest may be threatened by governance networks. I describe and analyze the multilevel governance network of Kristianstads Vattenrike Biosphere Reserve (KVBR in Southern Sweden, with the aim of understanding whether and how accountability is secured in the governance network and its relation to representative democracy. The analysis suggests that the governance network of KVBR complements representative democracy. It deals mainly with "low politics"; the learning and policy directions are developed in the governance network, but the decisions are embedded in representative democratic structures. Because several organizations and agencies co-own the process and are committed to the outcomes, there is a shared or extended accountability. A recent large investment in KVBR caused a major crisis at the municipal level, fueled by the financial crisis. The higher levels of the governance network, however, served as a social memory and enhanced resilience of the present biosphere development trajectory. For self-organized networks, legitimacy is the bridge between adaptability and accountability; accountability is secured as long as the

  5. Revisit to the helicity and the generalized self-organization theory

    Energy Technology Data Exchange (ETDEWEB)

    Kondoh, Y.; Takahashi, T. [Dept. of Electronic Engineering, Gunma Univ., Kiryu, Gunma (Japan); Momota, H. [Illinois Univ., Illinois (United States)

    2000-09-01

    It is clarified that the so-caned 'helicity conservation law' is never the conservation equation of the helicity K itself', but is merely 'the time change rate equation of K', which is passively and resultantly determined by the mutually independent volume and surface integral terms. It is shown that since the total helicity K can never be conserved in the real experimental systems, the conjecture of the total helicity invariance is not physically available to real magnetized plasmas in an exact sense. The well-known relaxation theory by Dr. J. B. Taylor is clarified to be neither the variational principle nor the energy principle, but be merely a mathematical calculation, using the variational calculus in order to find the minimum magnetic energy solution from the set of solutions having the same value of K. With the use of auto-correlations for physical quantities, it is presented that a novel basic formulation of an extended generalized self-organization theory, which is not based on neither the variational principle nor the energy principle. It is clarified that conservation equations concerning with all physical quantities for the dynamic system of interest are naturally embedded in the formulation of the generalized self-organization theory. The self-organized states of every physical quantities of interest may be realized during their own phases and the dynamical system may evolve repeatedly those out of phase organizations, depending on boundary conditions and input powers. It is shown that the conservation laws can be used to extend conventional methods of plasma current drives by energy injections with use of various types of energies, such as magnetic energies, electromagnetic wave energies, internal energies of plasmoids by plasma guns, which induce the thermal plasma flow velocity, various particle beam energies, and so on. (author)

  6. Control of the NASA Langley 16-Foot Transonic Tunnel with the Self-Organizing Feature Map

    Science.gov (United States)

    Motter, Mark A.

    1998-01-01

    A predictive, multiple model control strategy is developed based on an ensemble of local linear models of the nonlinear system dynamics for a transonic wind tunnel. The local linear models are estimated directly from the weights of a Self Organizing Feature Map (SOFM). Local linear modeling of nonlinear autonomous systems with the SOFM is extended to a control framework where the modeled system is nonautonomous, driven by an exogenous input. This extension to a control framework is based on the consideration of a finite number of subregions in the control space. Multiple self organizing feature maps collectively model the global response of the wind tunnel to a finite set of representative prototype controls. These prototype controls partition the control space and incorporate experimental knowledge gained from decades of operation. Each SOFM models the combination of the tunnel with one of the representative controls, over the entire range of operation. The SOFM based linear models are used to predict the tunnel response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal. Each SOFM provides a codebook representation of the tunnel dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the minimization of a similarity metric which is the essence of the self organizing feature of the map. Thus, the SOFM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme than selects the best available model for the applied control. Experimental results of controlling the wind tunnel, with the proposed method, during operational runs where strict research requirements on the control of the Mach number were met, are

  7. QUALITATIVE ANALYSIS OF OFFICIAL MILK CONTROL IN VALENCIA COMMUNITY (SPAIN BY SELF ORGANIZING MAPS

    Directory of Open Access Journals (Sweden)

    Carlos Javier Fernandez

    2009-06-01

    Full Text Available Breeding programs in dairy goats are mainly based on milk production and composition. Murciano-Granadina goats are located principally in the central and southern regions of Spain. This study is focused in Valencia Community (Spain and the objective is to study the Murciano-Granadina livestock based on the database from Murciano-Granadina Goat Breeders Association of Valencia (AMURVAL.  The aim of this study is to analyze the relationship among different variables related with milk production; milk yield, fat, protein, lactose, SCC, the number of births, lactation number and season. This analysis is carried out by using the Self Organizing Map. This tool allows mapping high-dimensional input spaces into much lower-dimensional spaces, thus making much more straightforward to understand any representation of data. These representations enable to visually extract qualitative relationships among variables (Visual Data Mining. A total of 3221 Murciano-Granadina dairy goats from AMURVAL were chosen. Self Organizing Maps (SOM were used to analyze data with the system identification toolbox of MATLAB v7. Data were obtained from Official Milk Control during 2006 campaign. SOM considered in this study is formed by 21´14 neurons (294 neurons; the chosen architecture is given by the range of the input variables used. The map shown that more than 70% of the goats has milk yield greater than 300 kg per lactation and goat, indicating good performance of farms. Besides, the SOM obtained indicate a group of neurons that included goats with high SSC (2%. The use of Self Organizing Maps in the descriptive analysis of this kind of data sets has proven to be highly valuable in extracting qualitative conclusions and guiding in improving the performance of farms.

  8. THE STRESS RESISTANCE OF STUDENTS. THE PARADIGM OF SUBJECT PERSONALITY SELF- ORGANIZATION

    Directory of Open Access Journals (Sweden)

    Sergey I. Dyakov

    2016-01-01

    Full Text Available The aim of the investigation is to consider a problem of stress resistance of students in the context of subject self-organization of the personality. Methods. The following methods of research are used: questioning; psychological and diagnostic tests «Tolerance of Uncertainty» (NTN and «Personal Factors of Decisions» (PFD by T. V. Kornilova; original experimental experiences – «Coding», a technique of a self-assessment (scaling and «A locus control». While data processing the methods of mathematical statistics (SPSS 12 package – the correlation analysis of Pearson and the factorial analysis with rotation use a component by «verimax» method are applied. Results and scientific novelty. Types of subjectivity and strategy of stress resistance are allocated. The nature and a role of the emotional and stressful mechanism having information and semantic properties in its basis are disclosed. Communication of irresponsible mechanisms of mentality with the sphere of consciousness in the context of subjectivity of the personality is shown. Mechanisms of emotional and rational self-control of system of mental self-organization of the person are presented. The statistical and qualitative data opening communications between properties of subjectivity and stress resistance of the personality are empirically obtained. Variation of the relations and also types of subjectivity and stress resistance emphasized based on the results of the presented research. Original (author’s methods of studying of subjectivity and factors of stress resistance are presented. Practical significance. The revealed factors of subject self-organization reveal the stress-producing directions of the environment and the relation of the personality to situations of changes and uncertainty: and also indicate subject properties of resistance to stress which need to be developed to increase the level of health of students, to reduce risk of deviance and delinquency of

  9. Entropic chiral symmetry breaking in self-organized two-dimensional colloidal crystals.

    Science.gov (United States)

    Mayoral, Kenny; Mason, Thomas G

    2014-07-07

    Long-range chiral symmetry breaking (CSB) has been recently observed in 2D self-organized rhombic crystals of hard, achiral, 72 degree rhombic microparticles. However, purely entropic selection of a CSB crystal in an idealized system of hard achiral shapes, in which attractions are entirely absent and the shape does not dictate a chiral tiling, has not yet been quantitatively predicted. Overcoming limitations of a purely rotational cage model, we investigate a translational-rotational cage model (TRCM) of dense systems of hard achiral rhombs and quantitatively demonstrate that entropy can spontaneously drive the preferential self-organization of a chiral crystal composed of achiral shapes that also tile into an achiral crystal. At different particle area fractions, ϕA, we calculate the number of accessible translational-rotational microstates, Ω, of a mobile central rhomb in a static cage of neighboring rhombs, which can have different orientation angles, γ, relative to the bisector of the crystalline axes. As we raise ϕA, two maxima emerge in Ω(γ) at non-zero cage orientation angles, ±γmax. These maxima correspond to additional translational microstates that become accessible in the CSB crystalline polymorph through reduced translational tip-tip interference. Thus, entropy, often associated with structural disorder, can drive CSB in condensed phase systems of non-attractive achiral objects that do not tile into chiral structures. The success of the TRCM in explaining the entropic origin of CSB in systems of hard rhombs indicates that the TRCM will have significant utility in predicting the self-organized behavior of dense systems of other hard shapes in 2D.

  10. Substrate dependent self-organization of mesoporous cobalt oxide nanowires with remarkable pseudocapacitance

    KAUST Repository

    Baby, Rakhi Raghavan

    2012-05-09

    A scheme of current collector dependent self-organization of mesoporous cobalt oxide nanowires has been used to create unique supercapacitor electrodes, with each nanowire making direct contact with the current collector. The fabricated electrodes offer the desired properties of macroporosity to allow facile electrolyte flow, thereby reducing device resistance and nanoporosity with large surface area to allow faster reaction kinetics. Co 3O 4 nanowires grown on carbon fiber paper collectors self-organize into a brush-like morphology with the nanowires completely surrounding the carbon microfiber cores. In comparison, Co 3O 4 nanowires grown on planar graphitized carbon paper collectors self-organize into a flower-like morphology. In three electrode configuration, brush-like and flower-like morphologies exhibited specific capacitance values of 1525 and 1199 F/g, respectively, at a constant current density of 1 A/g. In two electrode configuration, the brush-like nanowire morphology resulted in a superior supercapacitor performance with high specific capacitances of 911 F/g at 0.25 A/g and 784 F/g at 40 A/g. In comparison, the flower-like morphology exhibited lower specific capacitance values of 620 F/g at 0.25 A/g and 423 F/g at 40 A/g. The Co 3O 4 nanowires with brush-like morphology exhibited high values of specific power (71 kW/kg) and specific energy (81 Wh/kg). Maximum energy and power densities calculated for Co 3O 4 nanowires with flower-like morphology were 55 Wh/kg and 37 kW/kg respectively. Both electrode designs exhibited excellent cycling stability by retaining ∼91-94% of their maximum capacitance after 5000 cycles of continuous charge-discharge. © 2012 American Chemical Society.

  11. APPLYING PRINCIPAL COMPONENT ANALYSIS, MULTILAYER PERCEPTRON AND SELF-ORGANIZING MAPS FOR OPTICAL CHARACTER RECOGNITION

    Directory of Open Access Journals (Sweden)

    Khuat Thanh Tung

    2016-11-01

    Full Text Available Optical Character Recognition plays an important role in data storage and data mining when the number of documents stored as images is increasing. It is expected to find the ways to convert images of typewritten or printed text into machine-encoded text effectively in order to support for the process of information handling effectively. In this paper, therefore, the techniques which are being used to convert image into editable text in the computer such as principal component analysis, multilayer perceptron network, self-organizing maps, and improved multilayer neural network using principal component analysis are experimented. The obtained results indicated the effectiveness and feasibility of the proposed methods.

  12. Clustering Multiple Sclerosis Subgroups with Multifractal Methods and Self-Organizing Map Algorithm

    Science.gov (United States)

    Karaca, Yeliz; Cattani, Carlo

    Magnetic resonance imaging (MRI) is the most sensitive method to detect chronic nervous system diseases such as multiple sclerosis (MS). In this paper, Brownian motion Hölder regularity functions (polynomial, periodic (sine), exponential) for 2D image, such as multifractal methods were applied to MR brain images, aiming to easily identify distressed regions, in MS patients. With these regions, we have proposed an MS classification based on the multifractal method by using the Self-Organizing Map (SOM) algorithm. Thus, we obtained a cluster analysis by identifying pixels from distressed regions in MR images through multifractal methods and by diagnosing subgroups of MS patients through artificial neural networks.

  13. Self-organization of hot plasmas the canonical profile transport model

    CERN Document Server

    Dnestrovskij, Yu N

    2015-01-01

    In this monograph the author presents the Canonical Profile Transport Model or CPTM as a rather general mathematical framework to simulate plasma discharges.The description of hot plasmas in a magnetic fusion device is a very challenging task and many plasma properties still lack a physical explanation. One important property is plasma self-organization.It is very well known from experiments that the radial profile of the plasma pressure and temperature remains rather unaffected by changes of the deposited power or plasma density. The attractiveness of the CPTM is that it includes the effect o

  14. Invertebrate diversity classification using self-organizing map neural network: with some special topological functions

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2014-06-01

    Full Text Available In present study we used self-organizing map (SOM neural network to conduct the non-supervisory clustering of invertebrate orders in rice field. Four topological functions, i.e., cossintopf, sincostopf, acossintopf, and expsintopf, established on the template in toolbox of Matlab, were used in SOM neural network learning. Results showed that clusters were different when using different topological functions because different topological functions will generate different spatial structure of neurons in neural network. We may chose these functions and results based on comparison with the practical situation.

  15. Plate Tectonics as a Far-From-Equilibrium Self-Organized Dissipative System

    Science.gov (United States)

    Anderson, D. L.

    2001-12-01

    A fluid above the critical Rayleigh number is far from equilibrium and spontaneously organizes itself into patterns involving the collective motion of large numbers of molecules which are resisted by the viscosity of the fluid. No external template is involved in forming the pattern. In 1928 Pearson showed that Bénard's experiments were driven by variations in surface tension at the top of the fluid and the surface motions drove convection in the fluid. In this case, the surface organized itself AND the underlying fluid. Both internal buoyancy driven flow and flow driven by surface forces can be far-from-equilibrium self-organized open systems that receive energy and matter from the environment. In the Earth, the cold thermal boundary layer at the surface drives plate tectonics and introduces temperature, shear and pressure gradients into the mantle that drive mantle convection. The mantle provides energy and material but may not provide the template. Plate tectonics is therefore a candidate for a far-from-equilibrium dissipative self-organizing system. Alternatively, one could view mantle convection as the self-organized system and the plates as simply the surface manifestation. Lithospheric architecture also imposes lateral temperature gradients onto the mantle which can drive and organize flow. Far-from-equilibrium self-organization requires; an open system, interacting parts, nonlinearities or feedbacks, an outside steady source of energy or matter, multiple possible states and a source of dissipation. In uniform fluids viscosity is the source of dissipation. Sources of dissipation in the plate system include bending, breaking, folding, shearing, tearing, collision and basal drag. These can change rapidly, in contrast to plate driving forces, and introduce the sort of fluctuations that can reorganize far-from-equilibrium systems. Global plate reorganizations can alternatively be thought of as convective overturns of the mantle, or thermal weakening of plates

  16. An application of the Self Organizing Map Algorithm to computer aided classification of ASTER multispectral data

    Directory of Open Access Journals (Sweden)

    Ferdinando Giacco

    2008-01-01

    Full Text Available In this paper we employ the Kohonen’s Self Organizing Map (SOM as a strategy for an unsupervised analysis of ASTER multispectral (MS images. In order to obtain an accurate clusterization we introduce as input for the network, in addition to spectral data, some texture measures extracted from IKONOS images, which gives a contribution to the classification of manmade structures. After clustering of SOM outcomes, we associated each cluster with a major land cover and compared them with prior knowledge of the scene analyzed.

  17. Renormalization group and instantons in stochastic nonlinear dynamics, from self-organized criticality to thermonuclear reactors

    Energy Technology Data Exchange (ETDEWEB)

    Volchenkov, D. [Bielefeld Univ., Center of Excellence Cognitive Interaction Technology (CITEC) (Germany)

    2009-03-15

    Stochastic counterparts of nonlinear dynamics are studied by means of nonperturbative functional methods developed in the framework of quantum field theory (QFT). In particular, we discuss fully developed turbulence, including leading corrections on possible compressibility of fluids, transport through porous media, theory of waterspouts and tsunami waves, stochastic magnetohydrodynamics, turbulent transport in crossed fields, self-organized criticality, and dynamics of accelerated wrinkled flame fronts advancing in a wide canal. This report would be of interest to the broad auditorium of physicists and applied mathematicians, with a background in nonperturbative QFT methods or nonlinear dynamical systems, having an interest in both methodological developments and interdisciplinary applications. (author)

  18. Interpreting self-organizing maps through space--time data models

    OpenAIRE

    Sang, Huiyan; Gelfand, Alan E.; Lennard, Chris; Hegerl, Gabriele; Hewitson, Bruce

    2009-01-01

    Self-organizing maps (SOMs) are a technique that has been used with high-dimensional data vectors to develop an archetypal set of states (nodes) that span, in some sense, the high-dimensional space. Noteworthy applications include weather states as described by weather variables over a region and speech patterns as characterized by frequencies in time. The SOM approach is essentially a neural network model that implements a nonlinear projection from a high-dimensional input space to a low-dim...

  19. Information principles of self-organization of natural and artificial ecosystems

    Science.gov (United States)

    Lankin, Yuliy; Pechurkin, Nickolay

    The problems of overcoming the barrier of complexity, identifying common descriptions and understanding of the principles of self-organization of ecosystems are the most complex and actual in modern science. The possibility of survival of all humanity in the global ecological crisis may depend on their decision. However, modern ecology comes from the fact that each ecosystem is unique, the extrapolation of research results from one ecosystem to the other is impossible, and extreme principles for the construction of generalizing the theory have not been yet found. To overcome these difficulties the concept of adaptive systems (CAS) based on the ideas of ecology, biology, synergetics, neurocybernetics (neuroinformatics) and the extreme principles of adaptive self-organization of complex systems allows. In the present study the link among the principles of self-organization which are studied in synergetics, the processes of adaptation in complex systems with many elements and connections which are studied in neuroinformatics and processes of self-organization and adaptation in ecological systems has been found. The community of the approach makes it possible to apply it to different ecosystems (terrestrial and aquatic) and transfer the results obtained to the modeling of other ecosystems, the biosphere and artificial ecosystems. Previously, we have pointed out that at present the substrate (S) and energetic (E) concepts of life are well-developed, but the information (I) concept has not almost developed. At the same time, the most impressive results to be expected from the integration of the three mentioned in the work concepts (S + E + I). Improving the I-concept in the frame of the CAS allows, without loss of generality, to describe i) the formation of attractive landscape and the order parameters, ii) the process of attunement of the complex structure of nested cycles of open systems subjected to continuous pumping of energy outside, iii) the improvement

  20. Multicellular self-organization of P. aeruginosa due to interactions with secreted trails

    CERN Document Server

    Gelimson, Anatolij; Lee, Calvin K; Kranz, W Till; Wong, Gerard C L; Golestanian, Ramin

    2016-01-01

    Guided movement in response to slowly diffusing polymeric trails provides a unique mechanism for self-organization of some microorganisms. To elucidate how this signaling route leads to microcolony formation, we experimentally probe the trajectory and orientation of Pseudomonas aeruginosa that propel themselves on a surface using type IV pili motility appendages, which preferentially attach to deposited exopolysaccharides. We construct a stochastic model by analyzing single-bacterium trajectories, and show that the resulting theoretical prediction for the many-body behavior of the bacteria is in quantitative agreement with our experimental characterization of how cells explore the surface via a power law strategy.

  1. Self-organized criticality, long-time correlations, and the standard transport paradigm

    Energy Technology Data Exchange (ETDEWEB)

    Krommes, J.A.

    2000-02-11

    Some aspects of low-frequency, long-wavelength fluctuations are considered. A stochastic model is used to show that power-law time correlations need not arise from self-organized criticality. A formula for the frequency spectrum of uncorrelated, overlapping avalanches is shown to be a special case of the spectral balance equation of renormalized statistical turbulence theory. It is argued that there need be no contradiction between the presence of long-time correlations and the existence of local transport coefficients.

  2. Nanoscale Si template for the growth of self-organized one-dimensional nanostructures

    Science.gov (United States)

    Masson, Laurence; Sahaf, Houda; Amsalem, Patrick; Dettoni, Florent; Moyen, Eric; Koch, Norbert; Hanbücken, Margrit

    2013-02-01

    Through silicon deposition onto the silver (1 1 0) surface, we have fabricated in a one-step process a highly perfect nanoscale template consisting of a self-assembled Si nanostripe array with a pitch of 2 nm, covering uniformly the entire surface. Scanning tunneling microscopy investigations show that this system can be used, in a very simple way, as a template for the growth of identical highly ordered one-dimensional nanostructures. The adsorption of Co at room temperature and C60 at 190 °C gives rise to the growth of self-organized one-dimensional nanostructures reproducing the one-dimensional pattern of the Si template.

  3. Democracy versus Dictatorship in Self-Organized Models of Financial Markets

    CERN Document Server

    D'Hulst, R

    1999-01-01

    Models to mimic the transmission of information in financial markets are introduced. As an attempt to generate the demand process, we distinguish between dictatorship associations, where groups of agents rely on one of them to make decision, and democratic associations, where each agent takes part in the group decision. In the dictatorship model, agents segregate into two distinct populations, while the democratic model is driven towards a critical state where groups of agents of all sizes exist. Hence, both models display a level of organization, but only the democratic model is self-organized. We show that the dictatorship model generates less volatile markets than the democratic model.

  4. Multicellular Self-Organization of P. aeruginosa due to Interactions with Secreted Trails

    Science.gov (United States)

    Gelimson, Anatolij; Zhao, Kun; Lee, Calvin K.; Kranz, W. Till; Wong, Gerard C. L.; Golestanian, Ramin

    2016-10-01

    Guided movement in response to slowly diffusing polymeric trails provides a unique mechanism for self-organization of some microorganisms. To elucidate how this signaling route leads to microcolony formation, we experimentally probe the trajectory and orientation of Pseudomonas aeruginosa that propel themselves on a surface using type IV pili motility appendages, which preferentially attach to deposited exopolysaccharides. We construct a stochastic model by analyzing single-bacterium trajectories and show that the resulting theoretical prediction for the many-body behavior of the bacteria is in quantitative agreement with our experimental characterization of how cells explore the surface via a power-law strategy.

  5. Computational modeling of luminous bacteria self-organization on the cylindrical container side surface

    Directory of Open Access Journals (Sweden)

    Žilvinas Ledas

    2013-09-01

    Full Text Available This paper deals with the computational modeling of the pattern formation of luminous bacteria. Two bacterial self-organization models are investigated – Keller-Segel diffusion-advection-reaction type equations and the model with additional oxygen equation. These models were applied for the modeling of fluid cultures of lux-gene engineered Escherichia coli in the cylindrical container as seen from the side in 2 dimensions and in quasi-1 dimension along the top three phase contact line. The spatiotemporal patterns were simulated by using the finite difference technique. By applying these models the influence of the cylindrical container depth on the pattern formation was investigated.

  6. Self-organizing maps for measuring similarity of audiovisual speech percepts

    DEFF Research Database (Denmark)

    Bothe, Hans-Heinrich

    . Dependent on the training data, these other units may also be contextually immediate neighboring units. The poster demonstrates the idea with text material spoken by one individual subject using a set of simple audio-visual features. The data material for the training process consists of 44 labeled......The goal of this work is to find a way to measure similarity of audiovisual speech percepts. Phoneme-related self-organizing maps (SOM) with a rectangular basis are trained with data material from a (labeled) video film. For the training, a combination of auditory speech features and corresponding...... audio-visual speech percepts and to measure coarticulatory effects....

  7. Students' use of social software in self-organized learning environment

    DEFF Research Database (Denmark)

    Mathiasen, Helle; Dalsgaard, Christian

    2006-01-01

    The paper will argue that new possibilities of digital media, especially social software, have a potential regarding development of self-organized learning environments and facilitating self-governed activities. Based on a sociological perspective, the paper will clarify the concepts of informal...... and formal learning used in this paper. It is argued that formal and informal conditions of learning can supplement each other within an educational setting. A formal setting of project work forms the basis of informal, selfgoverned activities of students. The paper will argue that social software tools can...

  8. Improving Security for SCADA Sensor Networks with Reputation Systems and Self-Organizing Maps

    Directory of Open Access Journals (Sweden)

    Javier Blesa

    2009-11-01

    Full Text Available The reliable operation of modern infrastructures depends on computerized systems and Supervisory Control and Data Acquisition (SCADA systems, which are also based on the data obtained from sensor networks. The inherent limitations of the sensor devices make them extremely vulnerable to cyberwarfare/cyberterrorism attacks. In this paper, we propose a reputation system enhanced with distributed agents, based on unsupervised learning algorithms (self-organizing maps, in order to achieve fault tolerance and enhanced resistance to previously unknown attacks. This approach has been extensively simulated and compared with previous proposals.

  9. Improving Security for SCADA Sensor Networks with Reputation Systems and Self-Organizing Maps.

    Science.gov (United States)

    Moya, José M; Araujo, Alvaro; Banković, Zorana; de Goyeneche, Juan-Mariano; Vallejo, Juan Carlos; Malagón, Pedro; Villanueva, Daniel; Fraga, David; Romero, Elena; Blesa, Javier

    2009-01-01

    The reliable operation of modern infrastructures depends on computerized systems and Supervisory Control and Data Acquisition (SCADA) systems, which are also based on the data obtained from sensor networks. The inherent limitations of the sensor devices make them extremely vulnerable to cyberwarfare/cyberterrorism attacks. In this paper, we propose a reputation system enhanced with distributed agents, based on unsupervised learning algorithms (self-organizing maps), in order to achieve fault tolerance and enhanced resistance to previously unknown attacks. This approach has been extensively simulated and compared with previous proposals.

  10. Self-Organizing Hidden Markov Model Map (SOHMMM): Biological Sequence Clustering and Cluster Visualization.

    Science.gov (United States)

    Ferles, Christos; Beaufort, William-Scott; Ferle, Vanessa

    2017-01-01

    The present study devises mapping methodologies and projection techniques that visualize and demonstrate biological sequence data clustering results. The Sequence Data Density Display (SDDD) and Sequence Likelihood Projection (SLP) visualizations represent the input symbolical sequences in a lower-dimensional space in such a way that the clusters and relations of data elements are depicted graphically. Both operate in combination/synergy with the Self-Organizing Hidden Markov Model Map (SOHMMM). The resulting unified framework is in position to analyze automatically and directly raw sequence data. This analysis is carried out with little, or even complete absence of, prior information/domain knowledge.

  11. Self-Organization of Quantum Rods Induced by Lipid Membrane Corrugations.

    Science.gov (United States)

    Bizien, Thomas; Ameline, Jean-Claude; Yager, Kevin G; Marchi, Valérie; Artzner, Franck

    2015-11-10

    Self-organization of fluorescent nanoparticles, using biological molecules such as phospholipids to control assembly distances, is a promising method for creating hybrid nanostructures. We report here the formation of hybrid condensed phases made of anisotropic nanoparticles and phospholipids. Such structure formation is driven by electrostatic interaction between the nanoparticles and the phospholipids, and results in the formation of a 2D rectangular liquid crystal, as confirmed by high-resolution Small-Angle X-ray Scattering (SAXS). Moreover, we show that the fluorescent properties of the NPs are not modified by the self-assembly process.

  12. Acid polysaccharide-induced amorphous calcium carbonate (ACC) films: colloidal nanoparticle self-organization process.

    Science.gov (United States)

    Zhong, Chao; Chu, C Chang

    2009-03-03

    Amorphous calcium carbonate (ACC) plays important roles in biomineralization, and its synthesis in vitro has been of keen interest in the field of biomimetic materials. In this report, we describe the synthesis of ACC films using a novel acid polysaccharide, maleic chitosan, as an additive. We prepared the films by directly depositing them onto TEM grids and examined them using polarized optical microscopy (POM), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) combined with selected area electron diffraction (SAED). This enabled us to examine their formation and mesostructure without introducing artifacts. We observed that, in the presence of maleic chitosan, the ACC films are formed through a particle buildup process, with aggregation and coalescence occurring simultaneously. Nanoparticles with a size of less than 10 nm appear to be the basic units responsible for such self-organization. We suggest that the acid polysaccharide plays an important role in forming and stabilizing these nanoparticles, and we propose a colloidal nanoparticle self-organization model to explain the formation of the ACC films.

  13. Manifold Learning with Self-Organizing Mapping for Feature Extraction of Nonlinear Faults in Rotating Machinery

    Directory of Open Access Journals (Sweden)

    Lin Liang

    2015-01-01

    Full Text Available A new method for extracting the low-dimensional feature automatically with self-organization mapping manifold is proposed for the detection of rotating mechanical nonlinear faults (such as rubbing, pedestal looseness. Under the phase space reconstructed by single vibration signal, the self-organization mapping (SOM with expectation maximization iteration algorithm is used to divide the local neighborhoods adaptively without manual intervention. After that, the local tangent space alignment algorithm is adopted to compress the high-dimensional phase space into low-dimensional feature space. The proposed method takes advantages of the manifold learning in low-dimensional feature extraction and adaptive neighborhood construction of SOM and can extract intrinsic fault features of interest in two dimensional projection space. To evaluate the performance of the proposed method, the Lorenz system was simulated and rotation machinery with nonlinear faults was obtained for test purposes. Compared with the holospectrum approaches, the results reveal that the proposed method is superior in identifying faults and effective for rotating machinery condition monitoring.

  14. Self-Organization in Aggregating Robot Swarms: A DW-KNN Topological Approach

    KAUST Repository

    Khaldi, Belkacem

    2018-02-02

    In certain swarm applications, where the inter-agent distance is not the only factor in the collective behaviours of the swarm, additional properties such as density could have a crucial effect. In this paper, we propose applying a Distance-Weighted K-Nearest Neighbouring (DW-KNN) topology to the behaviour of robot swarms performing self-organized aggregation, in combination with a virtual physics approach to keep the robots together. A distance-weighted function based on a Smoothed Particle Hydrodynamic (SPH) interpolation approach, which is used to evaluate the robot density in the swarm, is applied as the key factor for identifying the K-nearest neighbours taken into account when aggregating the robots. The intra virtual physical connectivity among these neighbours is achieved using a virtual viscoelastic-based proximity model. With the ARGoS based-simulator, we model and evaluate the proposed approach, showing various self-organized aggregations performed by a swarm of N foot-bot robots. Also, we compared the aggregation quality of DW-KNN aggregation approach to that of the conventional KNN approach and found better performance.

  15. Self-Organization of Ions at the Interface between Graphene and Ionic Liquid DEME-TFSI.

    Science.gov (United States)

    Hu, Guangliang; Pandey, Gaind P; Liu, Qingfeng; Anaredy, Radhika S; Ma, Chunrui; Liu, Ming; Li, Jun; Shaw, Scott K; Wu, Judy

    2017-10-11

    Electrochemical effects manifest as nonlinear responses to an applied electric field in electrochemical devices, and are linked intimately to the molecular orientation of ions in the electric double layer (EDL). Herein, we probe the origin of the electrochemical effect using a double-gate graphene field effect transistor (GFET) of ionic liquid N,N-diethyl-N-(2-methoxyethyl)-N-methylammonium bis(trifluoromethylsulfonyl)imide (DEME-TFSI) top-gate, paired with a ferroelectric Pb0.92La0.08Zr0.52Ti0.48O3 (PLZT) back-gate of compatible gating efficiency. The orientation of the interfacial molecular ions can be extracted by measuring the GFET Dirac point shift, and their dynamic response to ultraviolet-visible light and a gate electric field was quantified. We have observed that the strong electrochemical effect is due to the TFSI anions self-organizing on a treated GFET surface. Moreover, a reversible order-disorder transition of TFSI anions self-organized on the GFET surface can be triggered by illuminating the interface with ultraviolet-visible light, revealing that it is a useful method to control the surface ion configuration and the overall performance of the device.

  16. Self-organized flexible leadership promotes collective intelligence in human groups.

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    Kurvers, Ralf H J M; Wolf, Max; Naguib, Marc; Krause, Jens

    2015-12-01

    Collective intelligence refers to the ability of groups to outperform individual decision-makers. At present, relatively little is known about the mechanisms promoting collective intelligence in natural systems. We here test a novel mechanism generating collective intelligence: self-organization according to information quality. We tested this mechanism by performing simulated predator detection experiments using human groups. By continuously tracking the personal information of all members prior to collective decisions, we found that individuals adjusted their response time during collective decisions to the accuracy of their personal information. When individuals possessed accurate personal information, they decided quickly during collective decisions providing accurate information to the other group members. By contrast, when individuals had inaccurate personal information, they waited longer, allowing them to use social information before making a decision. Individuals deciding late during collective decisions had an increased probability of changing their decision leading to increased collective accuracy. Our results thus show that groups can self-organize according to the information accuracy of their members, thereby promoting collective intelligence. Interestingly, we find that individuals flexibly acted both as leader and as follower depending on the quality of their personal information at any particular point in time.

  17. Lifelong learning of human actions with deep neural network self-organization.

    Science.gov (United States)

    Parisi, German I; Tani, Jun; Weber, Cornelius; Wermter, Stefan

    2017-12-01

    Lifelong learning is fundamental in autonomous robotics for the acquisition and fine-tuning of knowledge through experience. However, conventional deep neural models for action recognition from videos do not account for lifelong learning but rather learn a batch of training data with a predefined number of action classes and samples. Thus, there is the need to develop learning systems with the ability to incrementally process available perceptual cues and to adapt their responses over time. We propose a self-organizing neural architecture for incrementally learning to classify human actions from video sequences. The architecture comprises growing self-organizing networks equipped with recurrent neurons for processing time-varying patterns. We use a set of hierarchically arranged recurrent networks for the unsupervised learning of action representations with increasingly large spatiotemporal receptive fields. Lifelong learning is achieved in terms of prediction-driven neural dynamics in which the growth and the adaptation of the recurrent networks are driven by their capability to reconstruct temporally ordered input sequences. Experimental results on a classification task using two action benchmark datasets show that our model is competitive with state-of-the-art methods for batch learning also when a significant number of sample labels are missing or corrupted during training sessions. Additional experiments show the ability of our model to adapt to non-stationary input avoiding catastrophic interference. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  18. Complex systems analysis of series of blackouts: cascading failure, critical points, and self-organization

    Energy Technology Data Exchange (ETDEWEB)

    Dobson, Ian [University of Wisconsin, Madison; Carreras, Benjamin A [ORNL; Lynch, Vickie E [ORNL; Newman, David E [University of Alaska

    2007-01-01

    We give an overview of a complex systems approach to large blackouts of electric power transmission systems caused by cascading failure. Instead of looking at the details of particular blackouts, we study the statistics and dynamics of series of blackouts with approximate global models. Blackout data from several countries suggest that the frequency of large blackouts is governed by a power law. The power law makes the risk of large blackouts consequential and is consistent with the power system being a complex system designed and operated near a critical point. Power system overall loading or stress relative to operating limits is a key factor affecting the risk of cascading failure. Power system blackout models and abstract models of cascading failure show critical points with power law behavior as load is increased. To explain why the power system is operated near these critical points and inspired by concepts from self-organized criticality, we suggest that power system operating margins evolve slowly to near a critical point and confirm this idea using a power system model. The slow evolution of the power system is driven by a steady increase in electric loading, economic pressures to maximize the use of the grid, and the engineering responses to blackouts that upgrade the system. Mitigation of blackout risk should account for dynamical effects in complex self-organized critical systems. For example, some methods of suppressing small blackouts could ultimately increase the risk of large blackouts.

  19. Stable learning of functional maps in self-organizing spiking neural networks with continuous synaptic plasticity.

    Science.gov (United States)

    Srinivasa, Narayan; Jiang, Qin

    2013-01-01

    This study describes a spiking model that self-organizes for stable formation and maintenance of orientation and ocular dominance maps in the visual cortex (V1). This self-organization process simulates three development phases: an early experience-independent phase, a late experience-independent phase and a subsequent refinement phase during which experience acts to shape the map properties. The ocular dominance maps that emerge accommodate the two sets of monocular inputs that arise from the lateral geniculate nucleus (LGN) to layer 4 of V1. The orientation selectivity maps that emerge feature well-developed iso-orientation domains and fractures. During the last two phases of development the orientation preferences at some locations appear to rotate continuously through ±180° along circular paths and referred to as pinwheel-like patterns but without any corresponding point discontinuities in the orientation gradient maps. The formation of these functional maps is driven by balanced excitatory and inhibitory currents that are established via synaptic plasticity based on spike timing for both excitatory and inhibitory synapses. The stability and maintenance of the formed maps with continuous synaptic plasticity is enabled by homeostasis caused by inhibitory plasticity. However, a prolonged exposure to repeated stimuli does alter the formed maps over time due to plasticity. The results from this study suggest that continuous synaptic plasticity in both excitatory neurons and interneurons could play a critical role in the formation, stability, and maintenance of functional maps in the cortex.

  20. A self-organizing maps classifier structure for brain computer interfaces

    Directory of Open Access Journals (Sweden)

    Leandro Bueno

    Full Text Available AbstractIntroductionBrain Computer Interfaces provide an alternative communication path to severe paralyzed people and uses electrical signals related to brain activity in order to identify the user’s intention. In this paper a classifier based on a Self-Organizing Map is introduced.MethodsElectroencephalography signal is used on this work as a source for the user’s intention. This signal represents the brain activity and is processed in order to extract the frequency features presented to the classifier, which uses a Self-Organizing Map and a series of probability masks in order to identify the correct class.ResultsThe proposed structure was evaluated using a dataset of Electroencephalography with three mental tasks. The system was able to identify the different states of the users intention with an accuracy of 71.21% for a three-class problem using only 25 neurons for one of the users.ConclusionThe classifier proposed in this paper has an accuracy that is around the value of similar works in the literature, using the same data, but using a small time window for the classification, meaning the system can have a better time response for the user.

  1. Self-Replicators Emerge from a Self-Organizing Prebiotic Computer World.

    Science.gov (United States)

    Greenbaum, B; Pargellis, A N

    2017-01-01

    Amoeba, a computer platform inspired by the Tierra system, is designed to study the generation of self-replicating sequences of machine operations (opcodes) from a prebiotic world initially populated by randomly selected opcodes. Point mutations drive opcode sequences to become more fit as they compete for memory and CPU time. Significant features of the Amoeba system include the lack of artificial encapsulation (there is no write protection) and a computationally universal opcode basis set. Amoeba now includes two additional features: pattern-based addressing and injecting entropy into the system. It was previously thought such changes would make it highly unlikely that an ancestral replicator could emerge from a fortuitous combination of randomly selected opcodes. Instead, Amoeba shows a far richer emergence, exhibiting a self-organization phase followed by the emergence of self-replicators. First, the opcode basis set becomes biased. Second, short opcode building blocks are propagated throughout memory space. Finally, prebiotic building blocks can combine to form self-replicators. Self-organization is quantified by measuring the evolution of opcode frequencies, the size distribution of sequences, and the mutual information of opcode pairs.

  2. Computational modeling of neural plasticity for self-organization of neural networks.

    Science.gov (United States)

    Chrol-Cannon, Joseph; Jin, Yaochu

    2014-11-01

    Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  3. Automated Feature Identification and Classification Using Automated Feature Weighted Self Organizing Map (FWSOM)

    Science.gov (United States)

    Starkey, Andrew; Usman Ahmad, Aliyu; Hamdoun, Hassan

    2017-10-01

    This paper investigates the application of a novel method for classification called Feature Weighted Self Organizing Map (FWSOM) that analyses the topology information of a converged standard Self Organizing Map (SOM) to automatically guide the selection of important inputs during training for improved classification of data with redundant inputs, examined against two traditional approaches namely neural networks and Support Vector Machines (SVM) for the classification of EEG data as presented in previous work. In particular, the novel method looks to identify the features that are important for classification automatically, and in this way the important features can be used to improve the diagnostic ability of any of the above methods. The paper presents the results and shows how the automated identification of the important features successfully identified the important features in the dataset and how this results in an improvement of the classification results for all methods apart from linear discriminatory methods which cannot separate the underlying nonlinear relationship in the data. The FWSOM in addition to achieving higher classification accuracy has given insights into what features are important in the classification of each class (left and right-hand movements), and these are corroborated by already published work in this area.

  4. Network Catastrophe: Self-Organized Patterns Reveal both the Instability and the Structure of Complex Networks

    Science.gov (United States)

    Moon, Hankyu; Lu, Tsai-Ching

    2015-03-01

    Critical events in society or biological systems can be understood as large-scale self-emergent phenomena due to deteriorating stability. We often observe peculiar patterns preceding these events, posing a question of--how to interpret the self-organized patterns to know more about the imminent crisis. We start with a very general description -- of interacting population giving rise to large-scale emergent behaviors that constitute critical events. Then we pose a key question: is there a quantifiable relation between the network of interactions and the emergent patterns? Our investigation leads to a fundamental understanding to: 1. Detect the system's transition based on the principal mode of the pattern dynamics; 2. Identify its evolving structure based on the observed patterns. The main finding of this study is that while the pattern is distorted by the network of interactions, its principal mode is invariant to the distortion even when the network constantly evolves. Our analysis on real-world markets show common self-organized behavior near the critical transitions, such as housing market collapse and stock market crashes, thus detection of critical events before they are in full effect is possible.

  5. Fluid flows created by swimming bacteria drive self-organization in confined suspensions

    Science.gov (United States)

    Lushi, Enkeleida; Wioland, Hugo; Goldstein, Raymond

    Concentrated suspensions of micro-swimmers can display intricate self-organized spatiotemporal patterns on scales larger than those of the individual motile units. The collective dynamics of swimming microorganisms exhibits a complex interplay with the surrounding fluid: the motile cells stir the fluid, which in turn can reorient and advect them. This feedback loop can result in long-range interactions between the cells. We present a computational model that takes into account these cell-fluid interactions and cell-cell forces and that predicts counterintuitive cellular order driven by long-range flows. The predictions are confirmed by new experiments with Bacillus Subtilis bacteria. Simulations and experiments show that if the micro-swimmers are confined inside thin cylindrical chambers the suspension self-organizes into a stable swirling vortex. If the micro-swimmers are confined in thin racetracks, a persistent unidirectional stream can emerge. Both these phenomena emerge as a result of the complex interplay between the swimmers, the specific confining boundaries and the fluid flow.

  6. Self-Organization of Motor-Propelled Cytoskeletal Filaments at Topographically Defined Borders

    Directory of Open Access Journals (Sweden)

    Alf Månsson

    2012-01-01

    Full Text Available Self-organization phenomena are of critical importance in living organisms and of great interest to exploit in nanotechnology. Here we describe in vitro self-organization of molecular motor-propelled actin filaments, manifested as a tendency of the filaments to accumulate in high density close to topographically defined edges on nano- and microstructured surfaces. We hypothesized that this “edge-tracing” effect either (1 results from increased motor density along the guiding edges or (2 is a direct consequence of the asymmetric constraints on stochastic changes in filament sliding direction imposed by the edges. The latter hypothesis is well captured by a model explicitly defining the constraints of motility on structured surfaces in combination with Monte-Carlo simulations [cf. Nitta et al. (2006] of filament sliding. In support of hypothesis 2 we found that the model reproduced the edge tracing effect without the need to assume increased motor density at the edges. We then used model simulations to elucidate mechanistic details. The results are discussed in relation to nanotechnological applications and future experiments to test model predictions.

  7. Self-organized key management with trusted certificate exchange in MANET

    Directory of Open Access Journals (Sweden)

    Saju P John

    2015-03-01

    Full Text Available In MANET, security is more challenging due to problems related to key exchange. It is necessary to secure the exchanges in MANETs for assuring the development of services in the network. The self-organized MANET is visualized as a key communication technology enabler for application such as network centric warfare, disaster relief operations, emergency situations, and intelligent transportation systems. In this paper, we propose a self-organized key management technique coupled with trusted certificate exchange for mobile ad hoc networks. The proposed architecture consists of one coordinator node, servers and normal mobile nodes. The coordinator acts as a mediator for transmitting the message among the servers and mobile nodes. Each node generates its own public/private key pairs using server-signed public keying technique. Then multi-path certificate exchange technique is employed where public key of the nodes is certified by different nodes. Those nodes that issued the certificates are validated using the Eigen Vector Reputation Centrality. By simulation results, we show that the proposed approach improves security.

  8. Emergence of small-world anatomical networks in self-organizing clustered neuronal cultures.

    Directory of Open Access Journals (Sweden)

    Daniel de Santos-Sierra

    Full Text Available In vitro primary cultures of dissociated invertebrate neurons from locust ganglia are used to experimentally investigate the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. At all the different stages of the culture's development, identification of neurons' and neurites' location by means of a dedicated software allows to ultimately extract an adjacency matrix from each image of the culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main network's characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graph's micro- and meso-scale properties emerge. Finally, we identify the main physical processes ruling the culture's morphological transformations, and embed them into a simplified growth model qualitatively reproducing the overall set of experimental observations.

  9. Self-Organized Criticality: Emergent Complex Behavior in PM10 Pollution

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    Shi Kai

    2013-01-01

    Full Text Available We analyze long-term time series of daily average PM10 concentrations in Chengdu city. Detrended fluctuation analysis of the time series shows long range correlation at one-year temporal scale. Spectral analysis of the time series indicates 1/f noise behavior. The probability distribution functions of PM10 concentrations fluctuation have a scale-invariant structure. Why do the complex structures of PM10 concentrations evolution exhibit scale-invariant? We consider that these complex dynamical characteristics can be recognized as the footprint of self-organized criticality (SOC. Based on the theory of self-organized criticality, a simplified sandpile model for PM10 pollution with a nondimensional formalism is put forward. Our model can give a good prediction of scale-invariant in PM10 evolution. A qualitative explanation of the complex dynamics observed in PM10 evolution is suggested. The work supports the proposal that PM10 evolution acts as a SOC process on calm weather. New theory suggests one way to understand the origin of complex dynamical characteristics in PM10 pollution.

  10. Self-organized amniogenesis by human pluripotent stem cells in a biomimetic implantation-like niche

    Science.gov (United States)

    Shao, Yue; Taniguchi, Kenichiro; Gurdziel, Katherine; Townshend, Ryan F.; Xue, Xufeng; Yong, Koh Meng Aw; Sang, Jianming; Spence, Jason R.; Gumucio, Deborah L.; Fu, Jianping

    2017-04-01

    Amniogenesis--the development of amnion--is a critical developmental milestone for early human embryogenesis and successful pregnancy. However, human amniogenesis is poorly understood due to limited accessibility to peri-implantation embryos and a lack of in vitro models. Here we report an efficient biomaterial system to generate human amnion-like tissue in vitro through self-organized development of human pluripotent stem cells (hPSCs) in a bioengineered niche mimicking the in vivo implantation environment. We show that biophysical niche factors act as a switch to toggle hPSC self-renewal versus amniogenesis under self-renewal-permissive biochemical conditions. We identify a unique molecular signature of hPSC-derived amnion-like cells and show that endogenously activated BMP-SMAD signalling is required for the amnion-like tissue development by hPSCs. This study unveils the self-organizing and mechanosensitive nature of human amniogenesis and establishes the first hPSC-based model for investigating peri-implantation human amnion development, thereby helping advance human embryology and reproductive medicine.

  11. Justifications and self-organization as determinants of recycling behavior. The case of used batteries

    Energy Technology Data Exchange (ETDEWEB)

    Hansmann, Ralf; Bernasconi, Petra; Smieszek, Timo; Loukopoulos, Peter; Scholz, Roland W. [Chair of Environmental Sciences: Natural and Social Science Interface, Swiss Federal Institute of Technology, Zurich (ETH Zuerich), Universitaetsstrasse 22, ETH Zentrum CHN J76.3, CH-8092 Zurich (Switzerland)

    2006-06-15

    Much previous research on recycling behavior has drawn heavily on models of personal and perceived social norms, as well as of personal attitudes, to explain recycling behavior. Although such models have received empirical support, the issue concerning discrepancies between norms, personal attitudes and an individual's behavior is yet to be resolved. Using battery recycling in Switzerland as a case in point, the present questionnaire-based research examines via regression analyses the relationship between self-reported recycling behavior and socio-demographic variables, attitudes towards ecologically positive waste disposal, trust in waste disposal authorities, specific knowledge concerning recycling, justifications for not participating in the recycling scheme, self-organization of recycling behavior, and level of battery consumption. It was found that recycling knowledge, self-organization of recycling, and disagreement with justifications for non-recycling were positively related to recycling behavior, while attitudes towards ecological waste disposal and trust in waste disposal authorities were not directly related to respondents' self-reported battery recycling behavior. On the basis of these results, with reference to Sykes and Matza's Neutralization theory [Sykes GM, Matza D. Techniques of neutralization: a theory of delinquency. Am Sociol Rev 1957:22(6):664-70] a contextualized model of recycling behavior is proposed. This model is able to account for inconsistencies between personal attitudes and perceived social norms, and has practical implications for the design of public intervention strategies for enhancing participation in the recycling. (author)

  12. Modeling Multi-Agent Self-Organization through the Lens of Higher Order Attractor Dynamics.

    Science.gov (United States)

    Butner, Jonathan E; Wiltshire, Travis J; Munion, A K

    2017-01-01

    Social interaction occurs across many time scales and varying numbers of agents; from one-on-one to large-scale coordination in organizations, crowds, cities, and colonies. These contexts, are characterized by emergent self-organization that implies higher order coordinated patterns occurring over time that are not due to the actions of any particular agents, but rather due to the collective ordering that occurs from the interactions of the agents. Extant research to understand these social coordination dynamics (SCD) has primarily examined dyadic contexts performing rhythmic tasks. To advance this area of study, we elaborate on attractor dynamics, our ability to depict them visually, and quantitatively model them. Primarily, we combine difference/differential equation modeling with mixture modeling as a way to infer the underlying topological features of the data, which can be described in terms of attractor dynamic patterns. The advantage of this approach is that we are able to quantify the self-organized dynamics that agents exhibit, link these dynamics back to activity from individual agents, and relate it to other variables central to understanding the coordinative functionality of a system's behavior. We present four examples that differ in the number of variables used to depict the attractor dynamics (1, 2, and 6) and range from simulated to non-simulated data sources. We demonstrate that this is a flexible method that advances scientific study of SCD in a variety of multi-agent systems.

  13. Similarity Analysis of EEG Data Based on Self Organizing Map Neural Network

    Directory of Open Access Journals (Sweden)

    Ibrahim Salem Jahan

    2014-01-01

    Full Text Available The Electroencephalography (EEG is the recording of electrical activity along the scalp. This recorded data are very complex. EEG has a big role in several applications such as in the diagnosis of human brain diseases and epilepsy. Also, we can use the EEG signals to control an external device via Brain Computer Interface (BCI by our mind. There are many algorithms to analyse the recorded EEG data, but it still remains one of the big challenges in the world. In this article, we extended our previous proposed method. Our extended method uses Self-organizing Map (SOM as an EEG data classifier. The proposed method we can divide in following steps: capturing EEG raw data from the sensors, applying filters on this data, we will use the frequencies in the range from 0.5~Hz to 60~Hz, smoothing the data with 15-th order of Polynomial Curve Fitting, converting filtered data into text using Turtle Graphic, Lempel-Ziv complexity for measuring similarity between two EEG data trials and Self-Organizing Map Neural Network as a final classifiers. The experiment results show that our model is able to detect up to 96% finger movements correctly.

  14. From self-organization to self-assembly: a new materialism?

    Science.gov (United States)

    Vincent, Bernadette Bensaude

    2016-09-01

    While self-organization has been an integral part of academic discussions about the distinctive features of living organisms, at least since Immanuel Kant's Critique of Judgement, the term 'self-assembly' has only been used for a few decades as it became a hot research topic with the emergence of nanotechnology. Could it be considered as an attempt at reducing vital organization to a sort of assembly line of molecules? Considering the context of research on self-assembly I argue that the shift of attention from self-organization to self-assembly does not really challenge the boundary between chemistry and biology. Self-assembly was first and foremost investigated in an engineering context as a strategy for manufacturing without human intervention and did not raise new perspectives on the emergence of vital organization itself. However self-assembly implies metaphysical assumptions that this paper tries to disentangle. It first describes the emergence of self-assembly as a research field in the context of materials science and nanotechnology. The second section outlines the metaphysical implications and will emphasize a sharp contrast between the ontology underlying two practices of self-assembly developed under the umbrella of synthetic biology. And unexpectedly, we shall see that chemists are less on the reductionist side than most synthetic biologists. Finally, the third section ventures some reflections on the kind of design involved in self-assembly practices.

  15. Phase transitions and self-organized criticality in networks of stochastic spiking neurons

    Science.gov (United States)

    Brochini, Ludmila; de Andrade Costa, Ariadne; Abadi, Miguel; Roque, Antônio C.; Stolfi, Jorge; Kinouchi, Osame

    2016-11-01

    Phase transitions and critical behavior are crucial issues both in theoretical and experimental neuroscience. We report analytic and computational results about phase transitions and self-organized criticality (SOC) in networks with general stochastic neurons. The stochastic neuron has a firing probability given by a smooth monotonic function Φ(V) of the membrane potential V, rather than a sharp firing threshold. We find that such networks can operate in several dynamic regimes (phases) depending on the average synaptic weight and the shape of the firing function Φ. In particular, we encounter both continuous and discontinuous phase transitions to absorbing states. At the continuous transition critical boundary, neuronal avalanches occur whose distributions of size and duration are given by power laws, as observed in biological neural networks. We also propose and test a new mechanism to produce SOC: the use of dynamic neuronal gains - a form of short-term plasticity probably located at the axon initial segment (AIS) - instead of depressing synapses at the dendrites (as previously studied in the literature). The new self-organization mechanism produces a slightly supercritical state, that we called SOSC, in accord to some intuitions of Alan Turing.

  16. Self-organizing multi-resolution grid for motion planning and control.

    Science.gov (United States)

    Fomin, T; Rozgonyi, T; Szepesvári, C; Lörincz, A

    1996-12-01

    A fully self-organizing neural network approach to low-dimensional control problems is described. We consider the problem of learning to control an object and solving the path planning problem at the same time. Control is based on the path planning model that follows the gradient of the stationary solution of a diffusion process working in the state space. Previous works are extended by introducing a self-organizing multigrid-like discretizing structure to represent the external world. Diffusion is simulated within a recurrent neural network built on this multigrid system. The novelty of the approach is that the diffusion on the multigrid is fast. Moreover, the diffusion process on the multigrid fits well the requirements of the path planning: it accelerates the diffusion in large free space regions while still keeps the resolution in small bottleneck-like labyrinths along the path. Control is achieved in the usual way: associative learning identifies the inverse dynamics of the system in a direct fashion. To this end there are introduced interneurons between neighboring discretizing units that detect the strength of the steady-state diffusion and forward control commands to the control neurons via modifiable connections. This architecture forms the Multigrid Position-and-Direction-to-Action (MPDA) map. The architecture integrates reactive path planning and continuous motion control. It is also shown that the scheme leads to population coding for the actual command vector.

  17. Antagonistic Self-Organizing Patterning Systems Control Maintenance and Regeneration of the Anteroposterior Axis in Planarians.

    Science.gov (United States)

    Stückemann, Tom; Cleland, James Patrick; Werner, Steffen; Thi-Kim Vu, Hanh; Bayersdorf, Robert; Liu, Shang-Yun; Friedrich, Benjamin; Jülicher, Frank; Rink, Jochen Christian

    2017-02-06

    Planarian flatworms maintain their body plan in the face of constant internal turnover and can regenerate from arbitrary tissue fragments. Both phenomena require self-maintaining and self-organizing patterning mechanisms, the molecular mechanisms of which remain poorly understood. We show that a morphogenic gradient of canonical Wnt signaling patterns gene expression along the planarian anteroposterior (A/P) axis. Our results demonstrate that gradient formation likely occurs autonomously in the tail and that an autoregulatory module of Wnt-mediated Wnt expression both shapes the gradient at steady state and governs its re-establishment during regeneration. Functional antagonism between the tail Wnt gradient and an unknown head patterning system further determines the spatial proportions of the planarian A/P axis and mediates mutually exclusive molecular fate choices during regeneration. Overall, our results suggest that the planarian A/P axis is patterned by self-organizing patterning systems deployed from either end that are functionally coupled by mutual antagonism. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Self-organized, near-critical behavior during aggregation in Dictyostelium discoideum

    Science.gov (United States)

    de Palo, Giovanna; Yi, Darvin; Gregor, Thomas; Endres, Robert

    During starvation, the social amoeba Dictyostelium discoideum aggregates artfully via pattern formation into a multicellular slug and finally spores. The aggregation process is mediated by the secretion and sensing of cyclic adenosine monophosphate, leading to the synchronized movement of cells. The whole process is a remarkable example of collective behavior, spontaneously emerging from single-cell chemotaxis. Despite this phenomenon being broadly studied, a precise characterization of the transition from single cells to multicellularity has been elusive. Here, using fluorescence imaging data of thousands of cells, we investigate the role of cell shape in aggregation, demonstrating remarkable transitions in cell behavior. To better understand their functional role, we analyze cell-cell correlations and provide evidence for self-organization at the onset of aggregation (as opposed to leader cells), with features of criticality in this finite system. To capture the mechanism of self-organization, we extend a detailed single-cell model of D.discoideum chemotaxis by adding cell-cell communication. We then use these results to extract a minimal set of rules leading to aggregation in the population model. If universal, similar rules may explain other types of collective cell behavior.

  19. A limit-cycle self-organizing map architecture for stable arm control.

    Science.gov (United States)

    Huang, Di-Wei; Gentili, Rodolphe J; Katz, Garrett E; Reggia, James A

    2017-01-01

    Inspired by the oscillatory nature of cerebral cortex activity, we recently proposed and studied self-organizing maps (SOMs) based on limit cycle neural activity in an attempt to improve the information efficiency and robustness of conventional single-node, single-pattern representations. Here we explore for the first time the use of limit cycle SOMs to build a neural architecture that controls a robotic arm by solving inverse kinematics in reach-and-hold tasks. This multi-map architecture integrates open-loop and closed-loop controls that learn to self-organize oscillatory neural representations and to harness non-fixed-point neural activity even for fixed-point arm reaching tasks. We show through computer simulations that our architecture generalizes well, achieves accurate, fast, and smooth arm movements, and is robust in the face of arm perturbations, map damage, and variations of internal timing parameters controlling the flow of activity. A robotic implementation is evaluated successfully without further training, demonstrating for the first time that limit cycle maps can control a physical robot arm. We conclude that architectures based on limit cycle maps can be organized to function effectively as neural controllers. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Multiscale microenvironmental perturbation of pluripotent stem cell fate and self-organization

    Science.gov (United States)

    Tabata, Yoji; Lutolf, Matthias P.

    2017-03-01

    The combination of microfluidics with engineered three-dimensional (3D) matrices can bring new insights into the fate regulation of stem cells and their self-organization into organoids. Although there has been progress in 3D stem cell culturing, most existing in vitro methodologies do not allow for mimicking of the spatiotemporal heterogeneity of stimuli that drive morphogenetic processes in vivo. To address this, we present a perfusion-free microchip concept for the in vitro 3D perturbation of stem cell fate. Stem cells are encapsulated in a hydrogel compartment that is flanked by open reservoirs for the diffusion-driven generation of biomolecule gradients. Juxtaposing additional compartments bearing supportive cells enables investigating the influence of long range cell-cell communication. We explore the utility of the microchips in manipulating early fate choices and self-organizing characteristics of 3D-cultured mouse embryonic stem cells (mESCs) under neural differentiation conditions and exposure to gradients of leukemia inhibitory factor (LIF). mESCs respond to LIF gradients in a spatially dependent manner. At higher LIF concentrations, multicellular colonies maintain pluripotency in contrast, at lower concentrations, mESCs develop into apicobasally polarized epithelial cysts. This versatile system can help to systematically explore the role of multifactorial microenvironments in promoting self-patterning of various stem cell types.

  1. Fairness Is an Emergent Self-Organized Property of the Free Market for Labor

    Directory of Open Access Journals (Sweden)

    Venkat Venkatasubramanian

    2010-06-01

    Full Text Available The excessive compensation packages of CEOs of U.S. corporations in recent years have brought to the foreground the issue of fairness in economics. The conventional wisdom is that the free market for labor, which determines the pay packages, cares only about efficiency and not fairness. We present an alternative theory that shows that an ideal free market environment also promotes fairness, as an emergent property resulting from the self-organizing market dynamics. Even though an individual employee may care only about his or her salary and no one else’s, the collective actions of all the employees, combined with the profit maximizing actions of all the companies, in a free market environment under budgetary constraints, lead towards a more fair allocation of wages, guided by Adam Smith’s invisible hand of self-organization. By exploring deep connections with statistical thermodynamics, we show that entropy is the appropriate measure of fairness in a free market environment which is maximized at equilibrium to yield the lognormal distribution of salaries as the fairest inequality of pay in an organization under ideal conditions.

  2. Correlations induced by depressing synapses in critically self-organized networks with quenched dynamics

    Science.gov (United States)

    Campos, João Guilherme Ferreira; Costa, Ariadne de Andrade; Copelli, Mauro; Kinouchi, Osame

    2017-04-01

    In a recent work, mean-field analysis and computer simulations were employed to analyze critical self-organization in networks of excitable cellular automata where randomly chosen synapses in the network were depressed after each spike (the so-called annealed dynamics). Calculations agree with simulations of the annealed version, showing that the nominal branching ratio σ converges to unity in the thermodynamic limit, as expected of a self-organized critical system. However, the question remains whether the same results apply to the biological case where only the synapses of firing neurons are depressed (the so-called quenched dynamics). We show that simulations of the quenched model yield significant deviations from σ =1 due to spatial correlations. However, the model is shown to be critical, as the largest eigenvalue of the synaptic matrix approaches unity in the thermodynamic limit, that is, λc=1 . We also study the finite size effects near the critical state as a function of the parameters of the synaptic dynamics.

  3. Self-Organized Nanoscale Roughness Engineering for Broadband Light Trapping in Thin FilmSolar Cells

    Directory of Open Access Journals (Sweden)

    Carlo Mennucci

    2017-04-01

    Full Text Available We present a self-organized method based on defocused ion beam sputtering for nanostructuring glass substrates which feature antireflective and light trapping effects. By irradiating the substrate, capped with a thin gold (Au film, a self-organized Au nanowire stencil mask is firstly created. The morphology of the mask is then transferred to the glass surface by further irradiating the substrate, finally producing high aspect ratio, uniaxial ripple-like nanostructures whose morphological parameters can be tailored by varying the ion fluence. The effect of a Ti adhesion layer, interposed between glass and Au with the role of inhibiting nanowire dewetting, has also been investigated in order to achieve an improved morphological tunability of the templates. Morphological and optical characterization have been carried out, revealing remarkable light trapping performance for the largest ion fluences. The photon harvesting capability of the nanostructured glass has been tested for different preparation conditions by fabricating thin film amorphous Si solar cells. The comparison of devices grown on textured and flat substrates reveals a relative increase of the short circuit current up to 25%. However, a detrimental impact on the electrical performance is observed with the rougher morphologies endowed with steep v-shaped grooves. We finally demonstrate that post-growth ion beam restructuring of the glass template represents a viable approach toward improved electrical performance.

  4. FODA: a novel efficient multiple access protocol for highly dynamic self-organizing networks

    Science.gov (United States)

    Li, Hantao; Liu, Kai; Zhang, Jun

    2005-11-01

    Based on the concept of contention reservation for polling transmission and collision prevention strategy for collision resolution, a fair on-demand access (FODA) protocol for supporting node mobility and multihop architecture in highly dynamic self-organizing networks is proposed. In the protocol, a distributed clustering network architecture formed by self-organizing algorithm and a main idea of reserving channel resources to get polling service are adopted, so that the hidden terminal (HT) and exposed terminal (ET) problems existed in traffic transmission due to multihop architecture and wireless transmission can be eliminated completely. In addition, an improved collision prevention scheme based on binary countdown algorithm (BCA), called fair collision prevention (FCP) algorithm, is proposed to greatly eliminate unfair phenomena existed in contention access of newly active ordinary nodes and completely resolve access collisions. Finally, the performance comparison of the FODA protocol with carrier sense multiple access with collision avoidance (CSMA/CA) and polling protocols by OPNET simulation are presented. Simulation results show that the FODA protocol can overcome the disadvantages of CSMA/CA and polling protocols, and achieve higher throughput, lower average message delay and less average message dropping rate.

  5. At Home in the Universe - The Search for the Laws of Self-Organization and Complexity

    Science.gov (United States)

    Kauffman, Stuart

    1995-09-01

    A major scientific revolution has begun, a new paradigm that rivals Darwin's theory in importance. At its heart is the discovery of the order that lies deep within the most complex of systems, from the origin of life, to the workings of giant corporations, to the rise and fall of great civilizations. And more than anyone else, this revolution is the work of one man, Stuart Kauffman, a MacArthur Fellow and visionary pioneer of the new science of complexity. Now, in At Home in the Universe , Kauffman brilliantly weaves together the excitement of intellectual discovery and a fertile mix of insights to give the general reader a fascinating look at this new science--and at the forces for order that lie at the edge of chaos.We all know of instances of spontaneous order in nature--an oil droplet in water forms a sphere, snowflakes have a six-fold symmetry. What we are only now discovering, Kauffman says, is that the range of spontaneous order is enormously greater than we had supposed. Indeed, self-organization is a great undiscovered principle of nature. But how does this spontaneous order arise? Kauffman contends that complexity itself triggers self-organization, or what he calls "order for free," that if enough different molecules pass a certain threshold of complexity, they begin to self-organize into a new entity--a living cell. Kauffman uses the analogy of a thousand buttons on a rug--join two buttons randomly with thread, then another two, and so on. At first, you have isolated pairs; later, small clusters; but suddenly at around the 500th repetition, a remarkable transformation occurs--much like the phase transition when water abruptly turns to ice--and the buttons link up in one giant network. Likewise, life may have originated when the mix of different molecules in the primordial soup passed a certain level of complexity and self-organized into living entities (if so, then life is not a highly improbable chance event, but almost inevitable). Kauffman uses the

  6. Food scenarios 2025

    DEFF Research Database (Denmark)

    Sundbo, Jon

    2016-01-01

    This article presents the results of a future study of the food sector. Two scenarios have been developed using a combination of: 1) a summary of the relevant scientific knowledge, 2) systematic scenario writing, 3) an expert-based Delphi technique, and 4) an expert seminar assessment. The two...... scenarios present possible futures at global, national (Denmark) and regional (Zealand, Denmark) levels. The main scenario is called ‘Food for ordinary days and celebrations’ (a combination of ‘High-technological food production − The functional society’ and ‘High-gastronomic food − The experience society...

  7. The self-organizing fractal theory as a universal discovery method: the phenomenon of life.

    Science.gov (United States)

    Kurakin, Alexei

    2011-03-29

    A universal discovery method potentially applicable to all disciplines studying organizational phenomena has been developed. This method takes advantage of a new form of global symmetry, namely, scale-invariance of self-organizational dynamics of energy/matter at all levels of organizational hierarchy, from elementary particles through cells and organisms to the Universe as a whole. The method is based on an alternative conceptualization of physical reality postulating that the energy/matter comprising the Universe is far from equilibrium, that it exists as a flow, and that it develops via self-organization in accordance with the empirical laws of nonequilibrium thermodynamics. It is postulated that the energy/matter flowing through and comprising the Universe evolves as a multiscale, self-similar structure-process, i.e., as a self-organizing fractal. This means that certain organizational structures and processes are scale-invariant and are reproduced at all levels of the organizational hierarchy. Being a form of symmetry, scale-invariance naturally lends itself to a new discovery method that allows for the deduction of missing information by comparing scale-invariant organizational patterns across different levels of the organizational hierarchy.An application of the new discovery method to life sciences reveals that moving electrons represent a keystone physical force (flux) that powers, animates, informs, and binds all living structures-processes into a planetary-wide, multiscale system of electron flow/circulation, and that all living organisms and their larger-scale organizations emerge to function as electron transport networks that are supported by and, at the same time, support the flow of electrons down the Earth's redox gradient maintained along the core-mantle-crust-ocean-atmosphere axis of the planet. The presented findings lead to a radically new perspective on the nature and origin of life, suggesting that living matter is an organizational state

  8. The self-organizing fractal theory as a universal discovery method: the phenomenon of life

    Directory of Open Access Journals (Sweden)

    Kurakin Alexei

    2011-03-01

    Full Text Available Abstract A universal discovery method potentially applicable to all disciplines studying organizational phenomena has been developed. This method takes advantage of a new form of global symmetry, namely, scale-invariance of self-organizational dynamics of energy/matter at all levels of organizational hierarchy, from elementary particles through cells and organisms to the Universe as a whole. The method is based on an alternative conceptualization of physical reality postulating that the energy/matter comprising the Universe is far from equilibrium, that it exists as a flow, and that it develops via self-organization in accordance with the empirical laws of nonequilibrium thermodynamics. It is postulated that the energy/matter flowing through and comprising the Universe evolves as a multiscale, self-similar structure-process, i.e., as a self-organizing fractal. This means that certain organizational structures and processes are scale-invariant and are reproduced at all levels of the organizational hierarchy. Being a form of symmetry, scale-invariance naturally lends itself to a new discovery method that allows for the deduction of missing information by comparing scale-invariant organizational patterns across different levels of the organizational hierarchy. An application of the new discovery method to life sciences reveals that moving electrons represent a keystone physical force (flux that powers, animates, informs, and binds all living structures-processes into a planetary-wide, multiscale system of electron flow/circulation, and that all living organisms and their larger-scale organizations emerge to function as electron transport networks that are supported by and, at the same time, support the flow of electrons down the Earth's redox gradient maintained along the core-mantle-crust-ocean-atmosphere axis of the planet. The presented findings lead to a radically new perspective on the nature and origin of life, suggesting that living matter

  9. The self-organizing fractal theory as a universal discovery method: the phenomenon of life

    Science.gov (United States)

    2011-01-01

    A universal discovery method potentially applicable to all disciplines studying organizational phenomena has been developed. This method takes advantage of a new form of global symmetry, namely, scale-invariance of self-organizational dynamics of energy/matter at all levels of organizational hierarchy, from elementary particles through cells and organisms to the Universe as a whole. The method is based on an alternative conceptualization of physical reality postulating that the energy/matter comprising the Universe is far from equilibrium, that it exists as a flow, and that it develops via self-organization in accordance with the empirical laws of nonequilibrium thermodynamics. It is postulated that the energy/matter flowing through and comprising the Universe evolves as a multiscale, self-similar structure-process, i.e., as a self-organizing fractal. This means that certain organizational structures and processes are scale-invariant and are reproduced at all levels of the organizational hierarchy. Being a form of symmetry, scale-invariance naturally lends itself to a new discovery method that allows for the deduction of missing information by comparing scale-invariant organizational patterns across different levels of the organizational hierarchy. An application of the new discovery method to life sciences reveals that moving electrons represent a keystone physical force (flux) that powers, animates, informs, and binds all living structures-processes into a planetary-wide, multiscale system of electron flow/circulation, and that all living organisms and their larger-scale organizations emerge to function as electron transport networks that are supported by and, at the same time, support the flow of electrons down the Earth's redox gradient maintained along the core-mantle-crust-ocean-atmosphere axis of the planet. The presented findings lead to a radically new perspective on the nature and origin of life, suggesting that living matter is an organizational state

  10. Surface stress and large-scale self-organization at organic-metal interfaces

    Energy Technology Data Exchange (ETDEWEB)

    Pollinger, Florian

    2009-01-22

    The role of elastic interactions, particularly for the self-organized formation of periodically faceted interfaces, was investigated in this thesis for archetype organic-metal interfaces. The cantilever bending technique was applied to study the change of surface stress upon formation of the interface between 3,4,9,10-perylene-tetracarboxylic-dianhydride (PTCDA) and Ag(111). The main focus of this work was on the investigation of the formation of the long-range ordered, self-organized faceted PTCDA/Ag(10 8 7) interface. Reciprocal space maps of this interface were recorded both by spot profile analysis low energy electron diffraction (SPA-LEED) and low energy electron microscopy (LEEM) in selected area LEED mode. Complementary to the reciprocal data, also microscopic real-space LEEM data were used to characterize the morphology of this interface. Six different facet faces ((111), (532), (743), (954), (13 9 5), and (542)) were observed for the preparation path of molecular adsorption on the substrate kept at 550 K. Facet-sensitive dark-field LEEM localized these facets to grow in homogeneous areas of microscopic extensions. The temperature-dependence of the interface formation was studied in a range between 418 K and 612 K in order to learn more about the kinetics of the process. Additional steeper facets of 27 inclination with respect to the (111) surface were observed in the low temperature regime. Furthermore, using facet-sensitive dark-field LEEM, spatial and size distributions of specific facets were studied for the different temperatures. Moreover, the facet dimensions were statistically analyzed. The total island size of the facets follows an exponential distribution, indicating a random growth mode in absence of any mutual facet interactions. While the length distribution of the facets also follows an exponential distribution, the width distribution is peaked, reflecting the high degree of lateral order. This anisotropy is temperature-dependent and occurs

  11. European practices of providing of efficiency of self-organizations institutions of population in the context of public services

    Directory of Open Access Journals (Sweden)

    T. V. Serohina

    2017-06-01

    Full Text Available The research revealed that European countries devote sufficient attention to ensuring the effectiveness of the institutions of self-organization in the context of their public services. The most common areas where they operate are a system of health, education and assistance during emergencies. The study showed that in the development of public services, there were significant transformations in terms of subject-provider. Historically it was confessional organizations working on a voluntary basis, and linked their activity with the realization of Christian mission. Subsequently, when there had been formation of a «welfare state», the state took over responsibility for the area of public services. In favor of institutions of self-organization has been a change in the system when it became clear that they are best in the provide public services, especially in the social sphere, because they are the demonstrating of social needs. The main mechanisms of cooperation between institutions of self-organization and the public sector are, first, subsidies for statutory activities of the organization. Another mechanism is delegating services or outsourcing and in this case contracts mostly are for one year with possibility of further extension. In addition there is auxiliary element of providing of effectiveness institutions of self-organization, it consists in deprivation of their donors from taxes. Although institutions of self-organization are financed mainly by public authorities, they remain independent, because they have opportunity of funding from other sources. German experience showed that the starting point in the system of public services is the understanding of the necessity of paying taxes as acknowledgment of the rights of all members of society. That is why every taxpayer expects to receive public services at the appropriate level. This unwritten rule contributes to a very high level of provision of public services through an adequate

  12. Nuclear Security Futures Scenarios.

    Energy Technology Data Exchange (ETDEWEB)

    Keller, Elizabeth James Kistin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Warren, Drake Edward [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hayden, Nancy Kay [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Passell, Howard D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Malczynski, Leonard A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Backus, George A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-01-01

    This report provides an overview of the scenarios used in strategic futures workshops conducted at Sandia on September 21 and 29, 2016. The workshops, designed and facilitated by analysts in Center 100, used scenarios to enable thought leaders to think collectively about the changing aspects of global nuclear security and the potential implications for the US Government and Sandia National Laboratories.

  13. Learning Through Scenario Planning

    DEFF Research Database (Denmark)

    Balarezo, Jose

    This project investigates the uses and effects of scenario planning in companies operating in highly uncertain and dynamic environments. Whereas previous research on scenario planning has fallen short of providing sufficient evidence of its mechanisms and effects on individual or organizational...

  14. Evolving power grids with self-organized intermittent strain releases: An analogy with sandpile models and earthquakes

    Science.gov (United States)

    Po, Ho Fai; Yeung, Chi Ho; Zeng, An; Wong, K. Y. Michael

    2017-11-01

    The stability of powergrid is crucial since its disruption affects systems ranging from street lightings to hospital life-support systems. While short-term dynamics of single-event cascading failures have been extensively studied, less is understood on the long-term evolution and self-organization of powergrids. In this paper, we introduce a simple model of evolving powergrid and establish its connection with the sandpile model and earthquakes, i.e., self-organized systems with intermittent strain releases. Various aspects during its self-organization are examined, including blackout magnitudes, their interevent waiting time, the predictability of large blackouts, as well as the spatiotemporal rescaling of blackout data. We examined the self-organized strain releases on simulated networks as well as the IEEE 118-bus system, and we show that both simulated and empirical blackout waiting times can be rescaled in space and time similarly to those observed between earthquakes. Finally, we suggested proactive maintenance strategies to drive the powergrids away from self-organization to suppress large blackouts.

  15. Comparison between genetic algorithm and self organizing map to detect botnet network traffic

    Science.gov (United States)

    Yugandhara Prabhakar, Shinde; Parganiha, Pratishtha; Madhu Viswanatham, V.; Nirmala, M.

    2017-11-01

    In Cyber Security world the botnet attacks are increasing. To detect botnet is a challenging task. Botnet is a group of computers connected in a coordinated fashion to do malicious activities. Many techniques have been developed and used to detect and prevent botnet traffic and the attacks. In this paper, a comparative study is done on Genetic Algorithm (GA) and Self Organizing Map (SOM) to detect the botnet network traffic. Both are soft computing techniques and used in this paper as data analytics system. GA is based on natural evolution process and SOM is an Artificial Neural Network type, uses unsupervised learning techniques. SOM uses neurons and classifies the data according to the neurons. Sample of KDD99 dataset is used as input to GA and SOM.

  16. Biomimetic mineral self-organization from silica-rich spring waters.

    Science.gov (United States)

    García-Ruiz, Juan Manuel; Nakouzi, Elias; Kotopoulou, Electra; Tamborrino, Leonardo; Steinbock, Oliver

    2017-03-01

    Purely inorganic reactions of silica, metal carbonates, and metal hydroxides can produce self-organized complex structures that mimic the texture of biominerals, the morphology of primitive organisms, and that catalyze prebiotic reactions. To date, these fascinating structures have only been synthesized using model solutions. We report that mineral self-assembly can be also obtained from natural alkaline silica-rich water deriving from serpentinization. Specifically, we demonstrate three main types of mineral self-assembly: (i) nanocrystalline biomorphs of barium carbonate and silica, (ii) mesocrystals and crystal aggregates of calcium carbonate with complex biomimetic textures, and (iii) osmosis-driven metal silicate hydrate membranes that form compartmentalized, hollow structures. Our results suggest that silica-induced mineral self-assembly could have been a common phenomenon in alkaline environments of early Earth and Earth-like planets.

  17. An new self-organizing maps strategy for solving the traveling salesman problem

    Energy Technology Data Exchange (ETDEWEB)

    Bai Yanping [Key Lab of Instrument Science and Dynamic Measurement of Ministry of Education, North University of China, No. 3, Xueyuan Road, TaiYuan, ShanXi 030051 (China)]. E-mail: baiyp@nuc.edu.cn; Zhang Wendong [Key Lab of Instrument Science and Dynamic Measurement of Ministry of Education, North University of China, No. 3, Xueyuan Road, TaiYuan, ShanXi 030051 (China)]. E-mail: wdzhang@nuc.edu.cn; Jin Zhen [Department of Applied Mathematics, North University of China, No. 3 Xueyuan Road, TaiYuan, ShanXi 030051 (China)

    2006-05-15

    This paper presents an approach to the well-known traveling salesman problem (TSP) using self-organizing maps (SOM). There are many types of SOM algorithms to solve the TSP found in the literature, whereas the purpose of this paper is to look for the incorporation of an efficient initialization methods and the definition of a parameters adaptation law to achieve better results and a faster convergence. Aspects of parameters adaptation, selecting the number of nodes of neurons, index of winner neurons and effect of the initial ordering of the cities, as well as the initial synaptic weights of the modified SOM algorithm are discussed. The complexity of the modified SOM algorithm is analyzed. The simulated results show an average deviation of 2.32% from the optimal tour length for a set of 12 TSP instances.

  18. Emergent cellular self-organization and mechanosensation initiate follicle pattern in the avian skin.

    Science.gov (United States)

    Shyer, Amy E; Rodrigues, Alan R; Schroeder, Grant G; Kassianidou, Elena; Kumar, Sanjay; Harland, Richard M

    2017-08-25

    The spacing of hair in mammals and feathers in birds is one of the most apparent morphological features of the skin. This pattern arises when uniform fields of progenitor cells diversify their molecular fate while adopting higher-order structure. Using the nascent skin of the developing chicken embryo as a model system, we find that morphological and molecular symmetries are simultaneously broken by an emergent process of cellular self-organization. The key initiators of heterogeneity are dermal progenitors, which spontaneously aggregate through contractility-driven cellular pulling. Concurrently, this dermal cell aggregation triggers the mechanosensitive activation of β-catenin in adjacent epidermal cells, initiating the follicle gene expression program. Taken together, this mechanism provides a means of integrating mechanical and molecular perspectives of organ formation. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

  19. Self-organizing maps of document collections: A new approach to interactive exploration

    Energy Technology Data Exchange (ETDEWEB)

    Lagus, K.; Honkela, T.; Kaski, S.; Kohonen, T. [Helsinki Univ. of Technology (Finland)

    1996-12-31

    Powerful methods for interactive exploration and search from collections of free-form textual documents axe needed to manage the ever-increasing flood of digital information. In this article we present a method, WEBSOM, for automatic organization of full-text document collections using the self-organizing map (SOM) algorithm. The document collection is ordered onto a map in an unsupervised manner utilizing statistical information of short word contexts. The resulting ordered map where similar documents lie near each other thus presents a general view of the document space. With the aid of a suitable (WWW-based) interface, documents in interesting areas of the map can be browsed. The browsing can also be interactively extended to related topics, which appear in nearby areas on the map. Along with the method we present a case study of its use.

  20. Self-organizing actin patterns shape membrane architecture but not cell mechanics

    Science.gov (United States)

    Fritzsche, M.; Li, D.; Colin-York, H.; Chang, V. T.; Moeendarbary, E.; Felce, J. H.; Sezgin, E.; Charras, G.; Betzig, E.; Eggeling, C.

    2017-02-01

    Cell-free studies have demonstrated how collective action of actin-associated proteins can organize actin filaments into dynamic patterns, such as vortices, asters and stars. Using complementary microscopic techniques, we here show evidence of such self-organization of the actin cortex in living HeLa cells. During cell adhesion, an active multistage process naturally leads to pattern transitions from actin vortices over stars into asters. This process is primarily driven by Arp2/3 complex nucleation, but not by myosin motors, which is in contrast to what has been theoretically predicted and observed in vitro. Concomitant measurements of mechanics and plasma membrane fluidity demonstrate that changes in actin patterning alter membrane architecture but occur functionally independent of macroscopic cortex elasticity. Consequently, tuning the activity of the Arp2/3 complex to alter filament assembly may thus be a mechanism allowing cells to adjust their membrane architecture without affecting their macroscopic mechanical properties.

  1. A kinetic stochastic model of blistering and nanofilm islands deposition: self-organization problem

    Energy Technology Data Exchange (ETDEWEB)

    Zmievskaya, G I; Bondareva, A L; Levchenko, V D; Levchenko, T V [M V Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Moscow (Russian Federation)

    2007-08-21

    First-order phase transition at a fluctuation stage into non-linear dissipative plasma-like media is considered. The clustering of new phase germs (or nucleation) is represented by stochastic Wiener processes. Brownian motion of clusters induced by a long-range potential of indirect (through acoustic phonons and Friedel's oscillation of electron density) interaction between one another is taken into account. Kinetic models for blistering materials in a controlled thermonuclear reactor and for melted metal thin film islands deposition during surface CVD modification are both put forward. The non-steady-state distribution of clusters versus their size and position in space is calculated using Ito-Stratonovich stochastic differential equations. Formation of radiation stimulated porosity layers in a lattice as well as liquid island chains on the surface are to be discussed as characteristics of phase transition at fluctuation stages as well as a new kind of self-organization phenomenon.

  2. Surface Approximation using Growing Self-Organizing Nets and Gradient Information

    Directory of Open Access Journals (Sweden)

    Jorge Rivera-Rovelo

    2007-01-01

    Full Text Available In this paper we show how to improve the performance of two self-organizing neural networks used to approximate the shape of a 2D or 3D object by incorporating gradient information in the adaptation stage. The methods are based on the growing versions of the Kohonen's map and the neural gas network. Also, we show that in the adaptation stage the network utilizes efficient transformations, expressed as versors in the conformal geometric algebra framework, which build the shape of the object independent of its position in space (coordinate free. Our algorithms were tested with several images, including medical images (CT and MR images. We include also some examples for the case of 3D surface estimation.

  3. Experimental Demonstration of a Self-organized Architecture for Emerging Grid Computing Applications on OBS Testbed

    Science.gov (United States)

    Liu, Lei; Hong, Xiaobin; Wu, Jian; Lin, Jintong

    As Grid computing continues to gain popularity in the industry and research community, it also attracts more attention from the customer level. The large number of users and high frequency of job requests in the consumer market make it challenging. Clearly, all the current Client/Server(C/S)-based architecture will become unfeasible for supporting large-scale Grid applications due to its poor scalability and poor fault-tolerance. In this paper, based on our previous works [1, 2], a novel self-organized architecture to realize a highly scalable and flexible platform for Grids is proposed. Experimental results show that this architecture is suitable and efficient for consumer-oriented Grids.

  4. River Flow Forecasting: a Hybrid Model of Self Organizing Maps and Least Square Support Vector Machine

    Science.gov (United States)

    Ismail, S.; Samsudin, R.; Shabri, A.

    2010-10-01

    Successful river flow time series forecasting is a major goal and an essential procedure that is necessary in water resources planning and management. This study introduced a new hybrid model based on a combination of two familiar non-linear method of mathematical modeling: Self Organizing Map (SOM) and Least Square Support Vector Machine (LSSVM) model referred as SOM-LSSVM model. The hybrid model uses the SOM algorithm to cluster the training data into several disjointed clusters and the individual LSSVM is used to forecast the river flow. The feasibility of this proposed model is evaluated to actual river flow data from Bernam River located in Selangor, Malaysia. Their results have been compared to those obtained using LSSVM and artificial neural networks (ANN) models. The experiment results show that the SOM-LSSVM model outperforms other models for forecasting river flow. It also indicates that the proposed model can forecast more precisely and provides a promising alternative technique in river flow forecasting.

  5. An Adaptive-PSO-Based Self-Organizing RBF Neural Network.

    Science.gov (United States)

    Han, Hong-Gui; Lu, Wei; Hou, Ying; Qiao, Jun-Fei

    2018-01-01

    In this paper, a self-organizing radial basis function (SORBF) neural network is designed to improve both accuracy and parsimony with the aid of adaptive particle swarm optimization (APSO). In the proposed APSO algorithm, to avoid being trapped into local optimal values, a nonlinear regressive function is developed to adjust the inertia weight. Furthermore, the APSO algorithm can optimize both the network size and the parameters of an RBF neural network simultaneously. As a result, the proposed APSO-SORBF neural network can effectively generate a network model with a compact structure and high accuracy. Moreover, the analysis of convergence is given to guarantee the successful application of the APSO-SORBF neural network. Finally, multiple numerical examples are presented to illustrate the effectiveness of the proposed APSO-SORBF neural network. The results demonstrate that the proposed method is more competitive in solving nonlinear problems than some other existing SORBF neural networks.

  6. Monitoring and Discovery for Self-Organized Network Management in Virtualized and Software Defined Networks

    Directory of Open Access Journals (Sweden)

    Ángel Leonardo Valdivieso Caraguay

    2017-03-01

    Full Text Available This paper presents the Monitoring and Discovery Framework of the Self-Organized Network Management in Virtualized and Software Defined Networks SELFNET project. This design takes into account the scalability and flexibility requirements needed by 5G infrastructures. In this context, the present framework focuses on gathering and storing the information (low-level metrics related to physical and virtual devices, cloud environments, flow metrics, SDN traffic and sensors. Similarly, it provides the monitoring data as a generic information source in order to allow the correlation and aggregation tasks. Our design enables the collection and storing of information provided by all the underlying SELFNET sublayers, including the dynamically onboarded and instantiated SDN/NFV Apps, also known as SELFNET sensors.

  7. Effect of magnetic perturbations on the 3D MHD self-organization of shaped tokamak plasmas

    CERN Document Server

    Bonfiglio, D; Veranda, M; Chacón, L; Escande, D F

    2016-01-01

    The effect of magnetic perturbations (MPs) on the helical self-organization of shaped tokamak plasmas is discussed in the framework of the nonlinear 3D MHD model. Numerical simulations performed in toroidal geometry with the \\textsc{pixie3d} code [L. Chac\\'on, Phys. Plasmas {\\bf 15}, 056103 (2008)] show that $n=1$ MPs significantly affect the spontaneous quasi-periodic sawtoothing activity of such plasmas. In particular, the mitigation of sawtooth oscillations is induced by $m/n=1/1$ and $2/1$ MPs. These numerical findings provide a confirmation of previous circular tokamak simulations, and are in agreement with tokamak experiments in the RFX-mod and DIII-D devices. Sawtooth mitigation via MPs has also been observed in reversed-field pinch simulations and experiments. The effect of MPs on the stochastization of the edge magnetic field is also discussed.

  8. Self-Organization And Self-Management In Control-Flow Error Mitigation

    Directory of Open Access Journals (Sweden)

    Saber Fazel

    2015-08-01

    Full Text Available Abstract This paper presents a software-based technique to mitigate Control-flow Errors CFEs in multithreaded programs. In this paper we concentrate on self-organization and self-management mitigation of control-flow error using additional instructions insertion into specific portions of multithreaded program at design time regarding to control-flow and data-flow dependency graphs. In order to evaluate the proposed technique three multithreaded benchmarks quick sort matrix multiplication and linked list utilized to run on a multi-core processor and a total of 5000 transient faults has been injected into several executable points of each program. The results show that this technique detects and corrects between 91.9 and 93.8 of the injected faults with acceptable performance and memory overheads.

  9. A self-organizing learning account of number-form synaesthesia.

    Science.gov (United States)

    Makioka, Shogo

    2009-09-01

    Some people automatically and involuntarily "see" mental images of numbers in spatial arrays when they think of numbers. This phenomenon, called number forms, shares three key characteristics with the other types of synaesthesia, within-individual consistency, between-individual variety, and mixture of regularity and randomness. A theoretical framework called SOLA (self-organizing learning account of number forms) is proposed, which explains the generation process of number forms and the origin of those three characteristics. The simulations replicated the qualitative properties of the shapes of number forms, the property that numbers are aligned in order of size, that discontinuity usually occurs at the point of carry, and that continuous lines tend to have many bends.

  10. Self-Organizing Peer-To-Peer Middleware for Healthcare Monitoring in Real-Time.

    Science.gov (United States)

    Kim, Hyun Ho; Jo, Hyeong Gon; Kang, Soon Ju

    2017-11-17

    As the number of elderly persons with chronic illnesses increases, a new public infrastructure for their care is becoming increasingly necessary. In particular, technologies that can monitoring bio-signals in real-time have been receiving significant attention. Currently, most healthcare monitoring services are implemented by wireless carrier through centralized servers. These services are vulnerable to data concentration because all data are sent to a remote server. To solve these problems, we propose self-organizing P2P middleware for healthcare monitoring that enables a real-time multi bio-signal streaming without any central server by connecting the caregiver and care recipient. To verify the performance of the proposed middleware, we evaluated the monitoring service matching time based on a monitoring request. We also confirmed that it is possible to provide an effective monitoring service by evaluating the connectivity between Peer-to-Peer and average jitter.

  11. Self-organized noise resistance of oscillatory neural networks with spike timing-dependent plasticity.

    Science.gov (United States)

    Popovych, Oleksandr V; Yanchuk, Serhiy; Tass, Peter A

    2013-10-11

    Intuitively one might expect independent noise to be a powerful tool for desynchronizing a population of synchronized neurons. We here show that, intriguingly, for oscillatory neural populations with adaptive synaptic weights governed by spike timing-dependent plasticity (STDP) the opposite is true. We found that the mean synaptic coupling in such systems increases dynamically in response to the increase of the noise intensity, and there is an optimal noise level, where the amount of synaptic coupling gets maximal in a resonance-like manner as found for the stochastic or coherence resonances, although the mechanism in our case is different. This constitutes a noise-induced self-organization of the synaptic connectivity, which effectively counteracts the desynchronizing impact of independent noise over a wide range of the noise intensity. Given the attempts to counteract neural synchrony underlying tinnitus with noisers and maskers, our results may be of clinical relevance.

  12. Growing self-organizing mini-guts from a single intestinal stem cell: mechanism and applications.

    Science.gov (United States)

    Sato, Toshiro; Clevers, Hans

    2013-06-07

    Recent examples have highlighted how stem cells have the capability to initiate morphogenesis in vitro; that is, to generate complex structures in culture that closely parallel their in vivo counterparts. Lgr5, the receptor for the Wnt-agonistic R-spondins, marks stem cells in multiple adult organs of mice and humans. In R-spondin-based three-dimensional cultures, these Lgr5 stem cells can grow into ever-expanding epithelial organoids that retain their original organ identity. Single Lgr5 stem cells derived from the intestine can be cultured to build epithelial structures that retain hallmarks of the in vivo epithelium. Here, we review the mechanisms that support this notable example of self-organization and discuss applications of this technology for stem cell research, disease modeling (e.g., for colorectal cancer and cystic fibrosis), and regenerative medicine.

  13. Evidence of self-organization in brain electrical activity using wavelet-based informational tools

    Science.gov (United States)

    Rosso, O. A.; Martin, M. T.; Plastino, A.

    2005-03-01

    In the present work, we show that appropriate information-theory tools based on the wavelet transform (relative wavelet energy; normalized total wavelet entropy, H; generalized wavelet complexity, CW), when applied to tonic-clonic epileptic EEG data, provide one with valuable insights into the dynamics of neural activity. Twenty tonic-clonic secondary generalized epileptic records pertaining to eight patients have been analyzed. If the electromyographic activity is excluded the difference between the ictal and pre-ictal mean entropic values (ΔH=-) is negative in 95% of the cases (p-) is positive in 85% of the cases (p=0.0002). Thus during the seizure entropy diminishes while complexity grows. This is construed as evidence supporting the conjecture that an epileptic focus in this kind of seizures triggers a self-organized brain state characterized by both order and maximal complexity.

  14. Monitoring and Discovery for Self-Organized Network Management in Virtualized and Software Defined Networks.

    Science.gov (United States)

    Caraguay, Ángel Leonardo Valdivieso; Villalba, Luis Javier García

    2017-03-31

    This paper presents the Monitoring and Discovery Framework of the Self-Organized Network Management in Virtualized and Software Defined Networks SELFNET project. This design takes into account the scalability and flexibility requirements needed by 5G infrastructures. In this context, the present framework focuses on gathering and storing the information (low-level metrics) related to physical and virtual devices, cloud environments, flow metrics, SDN traffic and sensors. Similarly, it provides the monitoring data as a generic information source in order to allow the correlation and aggregation tasks. Our design enables the collection and storing of information provided by all the underlying SELFNET sublayers, including the dynamically onboarded and instantiated SDN/NFV Apps, also known as SELFNET sensors.

  15. Self-organizing processes in transportation – can we use them to improve traffic control?

    Directory of Open Access Journals (Sweden)

    Zuzana BĚLINOVÁ

    2007-01-01

    Full Text Available The goal of traffic control is to influence the traffic in the way it becomes more effective and safe. At present traffic control is working with the traffic flow considering it a quantity that is possible to regulate and control. The fact that each vehicle represents an independent intelligence is usually not taken into account. In fact each vehicle’s driver decides in dependence on many different factors – from his knowledge and information he possesses to his actual state of mind. When all individual reactions of drivers are combined, self-organizing processes may arise and these self-organizingtendencies may sometimes contribute to the improvement of traffic situation but sometimes they may counterwork and cause more traffic problems.

  16. Feasibility of a feedback control of atomic self-organization in an optical cavity

    Energy Technology Data Exchange (ETDEWEB)

    Ivanov, D. A., E-mail: ivanov-den@yandex.ru; Ivanova, T. Yu. [St. Petersburg State University (Russian Federation)

    2015-08-15

    Many interesting nonlinear effects are based on the strong interaction of motional degrees of freedom of atoms with an optical cavity field. Among them is the spatial self-organization of atoms in a pattern where the atoms group in either odd or even sites of the cavity-induced optical potential. An experimental observation of this effect can be simplified by using, along with the original cavity-induced feedback, an additional electronic feedback based on the detection of light leaking the cavity and the control of the optical potential for the atoms. Following our previous study, we show that this approach is more efficient from the laser power perspective than the original scheme without the electronic feedback.

  17. Analysis of Flue Gas Emission Data from Fluidized Bed Combustion Using Self-Organizing Maps

    Directory of Open Access Journals (Sweden)

    Mika Liukkonen

    2010-01-01

    Full Text Available Efficient combustion of fuels with lower emissions levels has become a demanding task in modern power plants, and new tools are needed to diagnose their energy production. The goals of the study were to find dependencies between process variables and the concentrations of gaseous emission components and to create multivariate nonlinear models describing their formation in the process. First, a generic process model was created by using a self-organizing map, which was clustered with the k-means algorithm to create subsets representing the different states of the process. Characteristically, these process states may include high- and low- load situations and transition states where the load is increased or decreased. Then emission models were constructed for both the entire process and for the process state of high boiler load. The main conclusion is that the methodology used is able to reveal such phenomena that occur within the process states and that could otherwise be difficult to observe.

  18. An Algorithm Based on the Self-Organized Maps for the Classification of Facial Features

    Directory of Open Access Journals (Sweden)

    Gheorghe Gîlcă

    2015-12-01

    Full Text Available This paper deals with an algorithm based on Self Organized Maps networks which classifies facial features. The proposed algorithm can categorize the facial features defined by the input variables: eyebrow, mouth, eyelids into a map of their grouping. The groups map is based on calculating the distance between each input vector and each output neuron layer , the neuron with the minimum distance being declared winner neuron. The network structure consists of two levels: the first level contains three input vectors, each having forty-one values, while the second level contains the SOM competitive network which consists of 100 neurons. The proposed system can classify facial features quickly and easily using the proposed algorithm based on SOMs.

  19. Monitoring and Discovery for Self-Organized Network Management in Virtualized and Software Defined Networks

    Science.gov (United States)

    Valdivieso Caraguay, Ángel Leonardo; García Villalba, Luis Javier

    2017-01-01

    This paper presents the Monitoring and Discovery Framework of the Self-Organized Network Management in Virtualized and Software Defined Networks SELFNET project. This design takes into account the scalability and flexibility requirements needed by 5G infrastructures. In this context, the present framework focuses on gathering and storing the information (low-level metrics) related to physical and virtual devices, cloud environments, flow metrics, SDN traffic and sensors. Similarly, it provides the monitoring data as a generic information source in order to allow the correlation and aggregation tasks. Our design enables the collection and storing of information provided by all the underlying SELFNET sublayers, including the dynamically onboarded and instantiated SDN/NFV Apps, also known as SELFNET sensors. PMID:28362346

  20. Thiophene fused azacoronenes: regioselective synthesis, self organization, charge transport, and its incorporation in conjugated polymers

    Science.gov (United States)

    Liu, Yi; He, Bo

    2015-09-15

    A regioselective synthesis of an azacoronene fused with two peripheral thiophene groups has been realized through a concise synthetic route. The resulting thienoazacoronene (TAC) derivatives show high degree of self-organization in solution, in single crystals, in the bulk, and in spuncast thin films. Spuncast thin film field-effect transistors of the TACs exhibited mobilities up to 0.028 cm.sup.2V.sup.-1 S.sup.-1, which is among the top field effect mobilities for solution processed discotic materials. Organic photovoltaic devices using TAC-containing conjugated polymers as the donor material exhibited a high open-circuit voltage of 0.89 V, which was ascribable to TAC's low-lying highest occupied molecular orbital energy level.

  1. Self-organization of meaning and the reflexive communication of information.

    Science.gov (United States)

    Leydesdorff, Loet; Petersen, Alexander M; Ivanova, Inga

    2017-03-01

    Following a suggestion from Warren Weaver, we extend the Shannon model of communication piecemeal into a complex systems model in which communication is differentiated both vertically and horizontally. This model enables us to bridge the divide between Niklas Luhmann's theory of the self-organization of meaning in communications and empirical research using information theory. First, we distinguish between communication relations and correlations among patterns of relations. The correlations span a vector space in which relations are positioned and can be provided with meaning. Second, positions provide reflexive perspectives. Whereas the different meanings are integrated locally, each instantiation opens global perspectives - 'horizons of meaning' - along eigenvectors of the communication matrix. These next-order codifications of meaning can be expected to generate redundancies when interacting in instantiations. Increases in redundancy indicate new options and can be measured as local reduction of prevailing uncertainty (in bits). The systemic generation of new options can be considered as a hallmark of the knowledge-based economy.

  2. THE MOVEMENT OF SELF-ORGANIZATION AND THEIR CONTRIBUTIONS TO EDUCATION

    Directory of Open Access Journals (Sweden)

    Clara Costa Oliveira

    2013-12-01

    Full Text Available The article begins by contextualizing historically and epistemologically the emergence of the movement of self-organization (MAO, advancing to its characterization as a movement differentiated from other contemporary epistemological currents; accordingly, are enunciated and briefly explained the seven features within the MAO to theories that integrate it. Then briefly I expose the two theories of MAO that were probably more influential in the contemporary scientific world: the theory of autopoiesis and the theory of mimetic desire. Throughout this description, links will be made between them, and between them and other authors/ theories of MAO, particularly with their precursors, as Bateson and Morin. Finally, the article is concluded with the author's personal contribution to the understanding of learning and education, based on the various theories of epistemology and MAO. It also summarizes the thoughts of other MAO 's authors about learning and education.

  3. Bio-Inspired Networking — Self-Organizing Networked Embedded Systems

    Science.gov (United States)

    Dressler, Falko

    The turn to nature has brought us many unforeseen great concepts and solutions. This course seems to hold on for many research domains. In this article, we study the applicability of biological mechanisms and techniques in the domain of communications. In particular, we study the behavior and the challenges in networked embedded systems that are meant to self-organize in large groups of nodes. Application examples include wireless sensor networks and sensor/actuator networks. Based on a review of the needs and requirements in such networks, we study selected bio-inspired networking approaches that claim to outperform other methods in specific domains. We study mechanisms in swarm intelligence, the artificial immune system, and approaches based on investigations on the cellular signaling pathways. As a major conclusion, we derive that bio-inspired networking techniques do have advantages compared to engineering methods. Nevertheless, selection and employment must be done carefully to achieve the desired performance gains.

  4. Schools of fish and flocks of birds: their shape and internal structure by self-organization.

    Science.gov (United States)

    Hemelrijk, Charlotte K; Hildenbrandt, Hanno

    2012-12-06

    Models of self-organization have proved useful in revealing what processes may underlie characteristics of swarms. In this study, we review model-based explanations for aspects of the shape and internal structure of groups of fish and of birds travelling undisturbed (without predator threat). Our models attribute specific collective traits to locomotory properties. Fish slow down to avoid collisions and swim at a constant depth, whereas birds fly at low variability of speed and lose altitude during turning. In both the models of fish and birds, the 'bearing angle' to the nearest neighbour emerges as a side-effect of the 'blind angle' behind individuals and when group size becomes larger, temporary subgroups may increase the complexity of group shape and internal structure. We discuss evidence for model-based predictions and provide a list of new predictions to be tested empirically.

  5. On power system blackout modeling and analysis based on self-organized criticality

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    This paper makes a comprehensive survey on power system blackout modeling and analysis based on SOC (self-organized criticality). Firstly,a generalized SOC theory from the viewpoint of cybernetics is introduced. Then the evolution model of power system and its relative mathematical description,which serves as a concrete example of the proposed generalized SOC,are given. Secondly,five blackout models capturing various critical properties of power systems in different time-scales are listed. Finally,this paper analyzes SOC in power systems,such as,the revelation of criticalities of proposed models in both micro-scale and macro-scale which can be used to assess the security of power system,and cas-cading failures process.

  6. Self-organized criticality of power system faults and its application in adaptation to extreme climate

    Institute of Scientific and Technical Information of China (English)

    SU Sheng; LI YinHong; DUAN XianZhong

    2009-01-01

    This paper analyzes the statistics of faults in a transmission and distribution networks in central China, unveils long-term autocorrelation and power law distribution of power system faults, which indicates that power system fault has self-organized criticality (SOC) feature. The conclusion is consistent with the power systems data in 2008 with ice storm present. Since power systems cover large areas, climate is the key factor to its safety and stability. In-depth analysis shows that the SOC of atmosphere system contributes much to that of power system faults. Extreme climate will be more intense and frequent with global warming, it will have more and more impact upon power systems. The SOC feature of power system faults is utilized to develop approaches to facilitate power systems adaptation to climate varia-tion in an economical and efficient way.

  7. A Contribution to the Study of Ensemble of Self-Organizing Maps

    Directory of Open Access Journals (Sweden)

    Leandro Antonio Pasa

    2015-01-01

    Full Text Available This study presents a factorial experiment to investigate the ensemble of Kohonen Self-Organizing Maps. Clusters Validity Indexes and the Mean Square Quantization Error were used as a criterion for fusing Kohonen Maps, through three different equations and four approaches. Computational simulations were performed with traditional dataset, including those with high dimensionality, not linearly separable classes, Gaussian mixtures, almost touching clusters, and unbalanced classes, from the UCI Machine Learning Repository and from Fundamental Clustering Problems Suite, with variations in map size, number of ensemble components, and the percentage of dataset bagging. The proposed method achieves a better classification than a single Kohonen Map and we applied the Wilcoxon Signed Rank Test to evidence its effectiveness.

  8. Self-organization of hydrodynamically entrained sperm cells into an array of vortices

    Science.gov (United States)

    Riedel, Ingmar; Kruse, Karsten; Howard, Jonathon

    2005-03-01

    The emergence of spatiotemporal patterns is of great interest in many scientific disciplines. Here we report a new dynamically self-organized pattern formed by hydrodynamically entrained sperm cells at planar surfaces. The sperm cells form vortices resembling quantized rotating waves. These vortices form an array with local hexagonal order. Using a novel order parameter, we show that the array is only formed above a critical sperm density. Supported by numerical simulation we suggest a mechanism for the appearance of the array and we estimate the strength of the hydrodynamic coupling between the cells. The vortex array represents a new chiral active gel and may serve as an experimentally accessible model for the metachronal wave of ciliated epithelia and other non-equilibrium phenomena in general. Finally we discuss the biological implications of our work.

  9. Hydrogen atom trapping in a self-organized one-dimensional dimer

    Directory of Open Access Journals (Sweden)

    Tsuyoshi Takami

    2014-09-01

    Full Text Available Metal–organic frameworks (MOFs have attracted widespread attention owing to their unusual structure and properties produced by their nanospaces. However, many MOFs possess the similar three-dimensional frameworks, limiting their structural variety and operating capacity for hydrogen storage under ambient conditions. Here we report the synthesis and structural characterization of a single-crystal one-dimensional dimer whose structure, operating capacity, and physical mechanism contrast with those of existing MOFs. The hydrogen storage capacity of 2.6 wt.% is comparable to the highest capacity achieved by existing MOFs at room temperature. This exceptional storage capacity is realized by self-organization during crystal growth using a weak base.

  10. Persistent correlations in self-organized critical systems away of their critical point

    Energy Technology Data Exchange (ETDEWEB)

    Woodard, Ryan [British Antarctic Survey, Cambridge, UK; Newman, David E [University of Alaska; Sanchez, Raul [ORNL; Carreras, Benjamin A [ORNL

    2007-01-01

    We show that correlated dynamics and long time memory persist in self-organized criticality (SOC) systems even when forced away from the defined critical point that exists at vanishing drive strength. These temporal correlations are found for all levels of external forcing as long as the system is not overdriven. They arise from the same physical mechanism that produces the temporal correlations found at the vanishing drive limit, namely the memory of past events stored in the system profile. The existence of these correlations contradicts the notion that a SOC time series is simply a random superposition of events with sizes distributed as a power law, as has been suggested by previous studies.

  11. Clustering analysis of western North Pacific Tropical Cyclone tracks using the Self Organizing Map

    Science.gov (United States)

    Kim, H.; Seo, K.

    2013-12-01

    A cluster analysis using Self Organizing Map (SOM) is used to characterize tropical cyclone (TC) tracks over the western North Pacific. A False Discovery Rate (FDR) method is used to objectively determine an optimum cluster number. For 620 TC tracks over the WNP from June-October during 1979-2010, the five clusters for TC tracks are selected. These can further be categorized into three major patterns: straight-moving track, recurving track, and quasi-random pattern. Each pattern is characterized by land falling regions: near South and East China, East Asia, and off-shore of Japan. In addition, each pattern shows distinctive properties in its traveling distance, lifetime, intensity (mean minimum sea level pressure), and genesis location. It is revealed that these three patterns are associated with the large-scale dynamics such as variability of the western Pacific subtropical high and the Madden-Julian Oscillation. The impacts of El Nino and NAO will be discussed.

  12. Predictive Multiple Model Switching Control with the Self-Organizing Map

    Science.gov (United States)

    Motter, Mark A.

    2000-01-01

    A predictive, multiple model control strategy is developed by extension of self-organizing map (SOM) local dynamic modeling of nonlinear autonomous systems to a control framework. Multiple SOMs collectively model the global response of a nonautonomous system to a finite set of representative prototype controls. Each SOM provides a codebook representation of the dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the global minimization of a similarity metric. The SOM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme that selects the best available model for the applied control. SOM based linear models are used to predict the response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal.

  13. Self-Organization of Template-Replicating Polymers and the Spontaneous Rise of Genetic Information

    Directory of Open Access Journals (Sweden)

    Jarle Breivik

    2001-11-01

    Full Text Available Abstract: Living systems imply self-reproducing constructs capable of Darwinian evolution. How such dynamics can arise from undirected interactions between simple monomeric objects remains an open question. Here we circumvent difficulties related to the manipulation of chemical interactions, and present a system of ferromagnetic objects that self-organize into template-replicating polymers due to environmental fluctuations in temperature. Initially random sequences of monomers direct the formation of complementary sequences, and structural information is inherited from one structure to another. Selective replication of sequences occurs in dynamic interaction with the environment, and the system demonstrates the fundamental link between thermodynamics, information theory, and life science in an unprecedented manner.

  14. Growing Self-organized Design of Efficient and Robust Complex Networks

    CERN Document Server

    Hayashi, Yukio

    2014-01-01

    A self-organization of efficient and robust networks is important for a future design of communication or transportation systems, however both characteristics are incompatible in many real networks. Recently, it has been found that the robustness of onion-like structure with positive degree-degree correlations is optimal against intentional attacks. We show that, by biologically inspired copying, an onion-like network emerges in the incremental growth with functions of proxy access and reinforced connectivity on a space. The proposed network consists of the backbone of tree-like structure by copyings and the periphery by adding shortcut links between low degree nodes to enhance the connectivity. It has the fine properties of the statistically self-averaging unlike the conventional duplication-divergence model, exponential-like degree distribution without overloaded hubs, strong robustness against both malicious attacks and random failures, and the efficiency with short paths counted by the number of hops as m...

  15. "Hits" emerge through self-organized coordination in collective response of free agents

    Science.gov (United States)

    Chakrabarti, Anindya S.; Sinha, Sitabhra

    2016-10-01

    Individuals in free societies frequently exhibit striking coordination when making independent decisions en masse. Examples include the regular appearance of hit products or memes with substantially higher popularity compared to their otherwise equivalent competitors or extreme polarization in public opinion. Such segregation of events manifests as bimodality in the distribution of collective choices. Here we quantify how apparently independent choices made by individuals result in a significantly polarized but stable distribution of success in the context of the box-office performance of movies and show that it is an emergent feature of a system of noninteracting agents who respond to sequentially arriving signals. The aggregate response exhibits extreme variability amplifying much smaller differences in individual cost of adoption. Due to self-organization of the competitive landscape, most events elicit only a muted response but a few stimulate widespread adoption, emerging as "hits".

  16. Birhythmicity, chaos, and other patterns of temporal self-organization in a multiply regulated biochemical system.

    Science.gov (United States)

    Decroly, O; Goldbeter, A

    1982-11-01

    We analyze on a model biochemical system the effect of a coupling between two instability-generating mechanisms. The system considered is that of two allosteric enzymes coupled in series and activated by their respective products. In addition to simple periodic oscillations, the system can exhibit a variety of new modes of dynamic behavior; coexistence between two stable periodic regimes (birhythmicity), random oscillations (chaos), and coexistence of a stable periodic regime with a stable steady state (hard excitation) or with chaos. The relationship between these patterns of temporal self-organization is analyzed as a function of the control parameters of the model. Chaos and birhythmicity appear to be rare events in comparison with simple periodic behavior. We discuss the relevance of these results with respect to the regularity of most biological rhythms.

  17. Algorithms for changing the structure of geospace self-organizing question-answering sensor networks

    Science.gov (United States)

    Mochalov, Vladimir; Mochalova, Anastasia

    2017-10-01

    Optimization problems of construction, development and changing the structure of geospace self-organizing question-answering sensor networks (GSQASN) are considered. The task specifies the coordinates of various network nodes. It is required with the specified functional, structural, cost and spatial constraints to change the structure of the GSQASN by adding new nodes, moving to new positions or removing some existing nodes. After the formation of the GSQASN structure we solve the task of question-answer agents placement into GSQASN structure in order to be able to answer the given types of questions under the established limitations. The functional scheme of a given category nodes placement into GSQASN structure and approximate bio-inspired algorithms for solving the tasks are proposed. The results of the work can be used in the construction of specific GSQASN and in the GSQASN design support systems.

  18. Algorithms for changing the structure of geospace self-organizing question-answering sensor networks

    Directory of Open Access Journals (Sweden)

    Mochalov Vladimir

    2017-01-01

    Full Text Available Optimization problems of construction, development and changing the structure of geospace self-organizing question-answering sensor networks (GSQASN are considered. The task specifies the coordinates of various network nodes. It is required with the specified functional, structural, cost and spatial constraints to change the structure of the GSQASN by adding new nodes, moving to new positions or removing some existing nodes. After the formation of the GSQASN structure we solve the task of question-answer agents placement into GSQASN structure in order to be able to answer the given types of questions under the established limitations. The functional scheme of a given category nodes placement into GSQASN structure and approximate bio-inspired algorithms for solving the tasks are proposed. The results of the work can be used in the construction of specific GSQASN and in the GSQASN design support systems.

  19. Random-Access Technique for Self-Organization of 5G Millimeter-Wave Cellular Communications

    Directory of Open Access Journals (Sweden)

    Jasper Meynard Arana

    2016-01-01

    Full Text Available The random-access (RA technique is a key procedure in cellular networks and self-organizing networks (SONs, but the overall processing time of this technique in millimeter-wave (mm-wave cellular systems with directional beams is very long because RA preambles (RAPs should be transmitted in all directions of Tx and Rx beams. In this paper, two different types of preambles (RAP-1 and RAP-2 are proposed to reduce the processing time in the RA stage. After analyzing the correlation property, false-alarm probability, and detection probability of the proposed RAPs, we perform simulations to show that the RAP-2 is suitable for RA in mm-wave cellular systems with directional beams because of the smaller processing time and high detection probability in multiuser environments.

  20. Personal sleep pattern visualization using sequence-based kernel self-organizing map on sound data.

    Science.gov (United States)

    Wu, Hongle; Kato, Takafumi; Yamada, Tomomi; Numao, Masayuki; Fukui, Ken-Ichi

    2017-07-01

    We propose a method to discover sleep patterns via clustering of sound events recorded during sleep. The proposed method extends the conventional self-organizing map algorithm by kernelization and sequence-based technologies to obtain a fine-grained map that visualizes the distribution and changes of sleep-related events. We introduced features widely applied in sound processing and popular kernel functions to the proposed method to evaluate and compare performance. The proposed method provides a new aspect of sleep monitoring because the results demonstrate that sound events can be directly correlated to an individual's sleep patterns. In addition, by visualizing the transition of cluster dynamics, sleep-related sound events were found to relate to the various stages of sleep. Therefore, these results empirically warrant future study into the assessment of personal sleep quality using sound data. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Prediction of the Corrosion Current Density in Reinforced Concrete Using a Self-Organizing Feature Map

    Directory of Open Access Journals (Sweden)

    Mehdi Nikoo

    2017-09-01

    Full Text Available A disadvantage of using linear polarization resistance (LPR in the measurement of corrosion current density is the need to partially destroy a concrete cover. In this article, a new technique of predicting the corrosion current density in reinforced concrete using a self-organizing feature map (SOFM is presented. For this purpose, air temperature, and also the parameters determined by the resistivity four-probe method and galvanostatic resistivity measurements, were employed as input variables. The corrosion current density, predicted by the destructive LPR method, was employed as the output variable. The weights of the SOFM were optimized using the genetic algorithm (GA. To evaluate the accuracy of the SOFM, a comparison with the radial basis function (RBF and linear regression (LR was performed. The results indicate that the SOFM–GA model has a higher ability, flexibility, and accuracy than the RBF and LR.

  2. An Anomaly Detection Algorithm of Cloud Platform Based on Self-Organizing Maps

    Directory of Open Access Journals (Sweden)

    Jun Liu

    2016-01-01

    Full Text Available Virtual machines (VM on a Cloud platform can be influenced by a variety of factors which can lead to decreased performance and downtime, affecting the reliability of the Cloud platform. Traditional anomaly detection algorithms and strategies for Cloud platforms have some flaws in their accuracy of detection, detection speed, and adaptability. In this paper, a dynamic and adaptive anomaly detection algorithm based on Self-Organizing Maps (SOM for virtual machines is proposed. A unified modeling method based on SOM to detect the machine performance within the detection region is presented, which avoids the cost of modeling a single virtual machine and enhances the detection speed and reliability of large-scale virtual machines in Cloud platform. The important parameters that affect the modeling speed are optimized in the SOM process to significantly improve the accuracy of the SOM modeling and therefore the anomaly detection accuracy of the virtual machine.

  3. Self-organization in a distributed coordination game through heuristic rules

    Science.gov (United States)

    Agarwal, Shubham; Ghosh, Diptesh; Chakrabarti, Anindya S.

    2016-12-01

    In this paper, we consider a distributed coordination game played by a large number of agents with finite information sets, which characterizes emergence of a single dominant attribute out of a large number of competitors. Formally, N agents play a coordination game repeatedly, which has exactly N pure strategy Nash equilibria, and all of the equilibria are equally preferred by the agents. The problem is to select one equilibrium out of N possible equilibria in the least number of attempts. We propose a number of heuristic rules based on reinforcement learning to solve the coordination problem. We see that the agents self-organize into clusters with varying intensities depending on the heuristic rule applied, although all clusters but one are transitory in most cases. Finally, we characterize a trade-off in terms of the time requirement to achieve a degree of stability in strategies versus the efficiency of such a solution.

  4. The Wireless Environment Monitoring Alarm System Based on Self-organizing Network

    Directory of Open Access Journals (Sweden)

    Zhang Huawei

    2016-01-01

    Full Text Available Under complicated conditions, it is necessary for environmental monitoring to design a wireless monitoring alarm system which can replace the wired system or as a supplement. The system discussed here bases on ARM7 microprocessor named LPC1114 and transceiver module named CC2530. With ZigBee, CSM/GPRS, this system uses multiple sensors to self-organized form a data acquisition and monitoring network system with variety of sensors fusion in the region. The system has some characteristics such as quick, convenient and accurate. Combining with the GSM SMS or GPRS alarm, the system can accurately and reliably monitor temperature, humidity and other environmental factors, and realize remote monitoring in large area and the complicated environment. Thus, this system has high practical value.

  5. Evolutionary Neural Gas (ENG): A Model of Self Organizing Network from Input Categorization

    CERN Document Server

    Licata, Ignazio

    2010-01-01

    Despite their claimed biological plausibility, most self organizing networks have strict topological constraints and consequently they cannot take into account a wide range of external stimuli. Furthermore their evolution is conditioned by deterministic laws which often are not correlated with the structural parameters and the global status of the network, as it should happen in a real biological system. In nature the environmental inputs are noise affected and fuzzy. Which thing sets the problem to investigate the possibility of emergent behaviour in a not strictly constrained net and subjected to different inputs. It is here presented a new model of Evolutionary Neural Gas (ENG) with any topological constraints, trained by probabilistic laws depending on the local distortion errors and the network dimension. The network is considered as a population of nodes that coexist in an ecosystem sharing local and global resources. Those particular features allow the network to quickly adapt to the environment, accor...

  6. Acoustic lung signals analysis based on Mel frequency cepstral coefficients and self-organizing maps

    Directory of Open Access Journals (Sweden)

    Álvaro David Orjuela-Cañón

    2016-09-01

    Full Text Available This study analyzes acoustic lung signals with different abnormalities, using Mel Frequency Cepstral Coefficients (MFCC, Self-Organizing Maps (SOM, and K-means clustering algorithm. SOM models are known as artificial neural networks than can be trained in an unsupervised or supervised manner. Both approaches were used in this work to compare the utility of this tool in lung signals studies. Results showed that with a supervised training, the classification reached rates of 85 % in accuracy. Unsupervised training was used for clustering tasks, and three clusters was the most adequate number for both supervised and unsupervised training. In general, SOM models can be used in lung signals as a strategy to diagnose systems, finding number of clusters in data, and making classifications for computer-aided decision making systems.

  7. Self-organized pseudo-graphene on grain boundaries in topological band insulators

    Science.gov (United States)

    Slager, Robert-Jan; Juričić, Vladimir; Lahtinen, Ville; Zaanen, Jan

    2016-06-01

    Semimetals are characterized by nodal band structures that give rise to exotic electronic properties. The stability of Dirac semimetals, such as graphene in two spatial dimensions, requires the presence of lattice symmetries, while akin to the surface states of topological band insulators, Weyl semimetals in three spatial dimensions are protected by band topology. Here we show that in the bulk of topological band insulators, self-organized topologically protected semimetals can emerge along a grain boundary, a ubiquitous extended lattice defect in any crystalline material. In addition to experimentally accessible electronic transport measurements, these states exhibit a valley anomaly in two dimensions influencing edge spin transport, whereas in three dimensions they appear as graphenelike states that may exhibit an odd-integer quantum Hall effect. The general mechanism underlying these semimetals—the hybridization of spinon modes bound to the grain boundary—suggests that topological semimetals can emerge in any topological material where lattice dislocations bind localized topological modes.

  8. Pre-Columbian agricultural landscapes, ecosystem engineers, and self-organized patchiness in Amazonia.

    Science.gov (United States)

    McKey, Doyle; Rostain, Stéphen; Iriarte, José; Glaser, Bruno; Birk, Jago Jonathan; Holst, Irene; Renard, Delphine

    2010-04-27

    The scale and nature of pre-Columbian human impacts in Amazonia are currently hotly debated. Whereas pre-Columbian people dramatically changed the distribution and abundance of species and habitats in some parts of Amazonia, their impact in other parts is less clear. Pioneer research asked whether their effects reached even further, changing how ecosystems function, but few in-depth studies have examined mechanisms underpinning the resilience of these modifications. Combining archeology, archeobotany, paleoecology, soil science, ecology, and aerial imagery, we show that pre-Columbian farmers of the Guianas coast constructed large raised-field complexes, growing on them crops including maize, manioc, and squash. Farmers created physical and biogeochemical heterogeneity in flat, marshy environments by constructing raised fields. When these fields were later abandoned, the mosaic of well-drained islands in the flooded matrix set in motion self-organizing processes driven by ecosystem engineers (ants, termites, earthworms, and woody plants) that occur preferentially on abandoned raised fields. Today, feedbacks generated by these ecosystem engineers maintain the human-initiated concentration of resources in these structures. Engineer organisms transport materials to abandoned raised fields and modify the structure and composition of their soils, reducing erodibility. The profound alteration of ecosystem functioning in these landscapes coconstructed by humans and nature has important implications for understanding Amazonian history and biodiversity. Furthermore, these landscapes show how sustainability of food-production systems can be enhanced by engineering into them follows that maintain ecosystem services and biodiversity. Like anthropogenic dark earths in forested Amazonia, these self-organizing ecosystems illustrate the ecological complexity of the legacy of pre-Columbian land use.

  9. A theoretical analysis of formation flight as a nonlinear self-organizing phenomenon

    Science.gov (United States)

    Sugimoto, Takeshi

    2003-10-01

    This study analyses the existence, stability and self-organization of formation flight utilized by migrant birds. Air is approximated as an incompressible inviscid flow, while birds are modelled as elliptically loaded lifting-lines. Application of conventional wing theory leads to newly derived, basic equations that describe the problem as a dynamical system of multiple wings interacting with each other through induced flow field. Formation flight is defined as the steady-state solution of the basic equations, in particular the solution that all the birds fly at the same speed. In the case of a prescribed thrust, constant transverse interval between adjacent birds, and a flock of physically identical birds, analytical study of the basic equations reveals the facts that (1) formation flight is self-organized and (2) this formation flight is stable. The new implication is that a configuration of formation emerges as a result of nonlinear dynamical interaction between many birds and that this nonlinear dynamical system does not exhibit chaotic behaviour. Numerical calculation has also been done for cormorant-type birds with the same transverse interval between flock members. The proposed numerical scheme quickly converges to very accurate results owing to the recently derived, closed-form expression of induced velocity distribution around an elliptically loaded lifting-line. Transverse intervals between birds are found to be a more important factor than the number of birds. Configurations of formations are found to be inverted U rather than inverted V. In these formations every bird enjoys the same amount of drag reduction.

  10. Development of objective flow regime identification method using self-organizing neural network

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jae Young; Kim, Nam Seok; Kwak, Nam Yee [Handong Global Univ., Pohang (Korea, Republic of)

    2004-07-01

    Two-phase flow shows various flow patterns according to the amount of the void and its relative velocity to the liquid flow. This variation directly affect the interfacial transfer which is the key factor for the design or analysis of the phase change systems. Especially the safety analysis of the nuclear power plant has been performed based on the numerical code furnished with the proper constitutive relations depending highly upon the flow regimes. Heavy efforts have been focused to identify the flow regime and at this moment we stand on relative very stable engineering background compare to the other research field. However, the issues related to objectiveness and transient flow regime are still open to study. Lee et al. and Ishii developed the method for the objective and instantaneous flow regime identification based on the neural network and new index of probability distribution of the flow regime which allows just one second observation for the flow regime identification. In the present paper, we developed the self-organized neural network for more objective approach to this problem. Kohonen's Self-Organizing Map (SOM) has been used for clustering, visualization, and abstraction. The SOM is trained through unsupervised competitive learning using a 'winner takes it all' policy. Therefore, its unsupervised training character delete the possible interference of the regime developer to the neural network training. After developing the computer code, we evaluate the performance of the code with the vertically upward two-phase flow in the pipes of 25.4 and 50.4 cmm I.D. Also, the sensitivity of the number of the clusters to the flow regime identification was made.

  11. Self-Inhibiting Modules Can Self-Organize as a Brain of a Robot: A Conjecture

    Directory of Open Access Journals (Sweden)

    J. Negrete-Martínez

    2006-01-01

    Full Text Available In this article we describe a new robot control architecture on the basis of self-organization of self-inhibiting modules. The architecture can generate a complex behaviour repertoire. The repertoire can be performance-enhanced or increased by modular poly-functionality and/or by addition of new modules. This architecture is illustrated in a robot consisting of a car carrying an arm with a grasping tool. In the robot, each module drives either a joint motor or a pair of wheel motors. Every module estimates the distance from a sensor placed in the tool to a beacon. If the distance is smaller than a previously measured distance, the module drives its motor in the same direction of its prior movement. If the distance is larger, the next movement will be in the opposite direction; but, if the movement produces no significant change in distance, the module self-inhibits. A self-organization emerges: any module can be the next to take control of the motor activity of the robot once one module self-inhibits. A single module is active at a given time. The modules are implemented as computer procedures and their turn for participation scheduled by an endless program. The overall behaviour of the robot corresponds to a reaching attention behaviour. It is easily switched to a running-away attention behaviour by changing the sign of the same parameter in each module. The addition of a “sensor-gain attenuation reflex” module and of a “light-orientation reflex” module provides an increase of the behavioural attention repertoire and performance enhancement. Since scheduling a module does not necessarily produce its sustained intervention, the architecture of the “brain” is actually providing action induction rather than action selection.

  12. Biophotofuel cell anode containing self-organized titanium dioxide nanotube array

    Energy Technology Data Exchange (ETDEWEB)

    Gan, Yong X., E-mail: yong.gan@utoledo.edu [Mechanical, Industrial and Manufacturing Engineering, College of Engineering, University of Toledo, 2801 W Bancroft Street, Toledo, OH 43606 (United States); Gan, Bo J. [Ottawa Hills High School, 2532 Evergreen Road, Toledo, OH 43606 (United States); Su Lusheng [Mechanical, Industrial and Manufacturing Engineering, College of Engineering, University of Toledo, 2801 W Bancroft Street, Toledo, OH 43606 (United States)

    2011-09-15

    Graphical abstract: Highlights: {center_dot} A photoactive anode containing highly ordered TiO{sub 2} nanotube array was made and the formation mechanism of self-organized TiO{sub 2} nanotube array on Ti was revealed. {center_dot} Effect of electrolyte concentration and voltage on the size distribution of the nanotubes was investigated. {center_dot} Self-organized TiO{sub 2} nanotube array anode possesses good photo-catalytic behavior of biomass decomposition under ultraviolet (UV) radiation. {center_dot} The fuel cell generates electricity and hydrogen via photoelectrochemical decomposition of ethanol, apple vinegar, sugar and tissue paper. - Abstract: We made a biophotofuel cell consisting of a titanium dioxide nanotube array photosensitive anode for biomass decomposition, and a low-hydrogen overpotential metal, Pt, as the cathode for hydrogen production. The titanium dioxide nanotubes (TiO{sub 2} NTs) were prepared via electrochemical oxidation of pure Ti in NaF solutions. Scanning electron microscopy was used to analyze the morphology of the nanotubes. The average diameter, wall thickness and length of the as-prepared TiO{sub 2} NTs were 88 {+-} 16 nm, 10 {+-} 2 nm and 491 {+-} 56 nm, respectively. Such dimensions are affected by the NaF concentration and the applied voltage during processing. Higher NaF concentrations result in the formation of longer and thicker nanotubes. The higher the voltage is, the thicker the nanotubes. The photosensitive anode made from the highly ordered TiO{sub 2} NTs has good photo-catalytic property, as can be seen from the test results of ethanol, apple vinegar, sugar and tissue paper decomposition under ultraviolet (UV) radiation. It is concluded that the biophotofuel cell with the TiO{sub 2} nanotube photoanode and a Pt cathode can generate electricity, hydrogen and clean water depending on the pH value and the oxygen presence in the solutions.

  13. Pre-Columbian agricultural landscapes, ecosystem engineers, and self-organized patchiness in Amazonia

    Science.gov (United States)

    McKey, Doyle; Rostain, Stéphen; Iriarte, José; Glaser, Bruno; Birk, Jago Jonathan; Holst, Irene; Renard, Delphine

    2010-01-01

    The scale and nature of pre-Columbian human impacts in Amazonia are currently hotly debated. Whereas pre-Columbian people dramatically changed the distribution and abundance of species and habitats in some parts of Amazonia, their impact in other parts is less clear. Pioneer research asked whether their effects reached even further, changing how ecosystems function, but few in-depth studies have examined mechanisms underpinning the resilience of these modifications. Combining archeology, archeobotany, paleoecology, soil science, ecology, and aerial imagery, we show that pre-Columbian farmers of the Guianas coast constructed large raised-field complexes, growing on them crops including maize, manioc, and squash. Farmers created physical and biogeochemical heterogeneity in flat, marshy environments by constructing raised fields. When these fields were later abandoned, the mosaic of well-drained islands in the flooded matrix set in motion self-organizing processes driven by ecosystem engineers (ants, termites, earthworms, and woody plants) that occur preferentially on abandoned raised fields. Today, feedbacks generated by these ecosystem engineers maintain the human-initiated concentration of resources in these structures. Engineer organisms transport materials to abandoned raised fields and modify the structure and composition of their soils, reducing erodibility. The profound alteration of ecosystem functioning in these landscapes coconstructed by humans and nature has important implications for understanding Amazonian history and biodiversity. Furthermore, these landscapes show how sustainability of food-production systems can be enhanced by engineering into them fallows that maintain ecosystem services and biodiversity. Like anthropogenic dark earths in forested Amazonia, these self-organizing ecosystems illustrate the ecological complexity of the legacy of pre-Columbian land use. PMID:20385814

  14. Interconnected growing self-organizing maps for auditory and semantic acquisition modeling

    Science.gov (United States)

    Cao, Mengxue; Li, Aijun; Fang, Qiang; Kaufmann, Emily; Kröger, Bernd J.

    2014-01-01

    Based on the incremental nature of knowledge acquisition, in this study we propose a growing self-organizing neural network approach for modeling the acquisition of auditory and semantic categories. We introduce an Interconnected Growing Self-Organizing Maps (I-GSOM) algorithm, which takes associations between auditory information and semantic information into consideration, in this paper. Direct phonetic–semantic association is simulated in order to model the language acquisition in early phases, such as the babbling and imitation stages, in which no phonological representations exist. Based on the I-GSOM algorithm, we conducted experiments using paired acoustic and semantic training data. We use a cyclical reinforcing and reviewing training procedure to model the teaching and learning process between children and their communication partners. A reinforcing-by-link training procedure and a link-forgetting procedure are introduced to model the acquisition of associative relations between auditory and semantic information. Experimental results indicate that (1) I-GSOM has good ability to learn auditory and semantic categories presented within the training data; (2) clear auditory and semantic boundaries can be found in the network representation; (3) cyclical reinforcing and reviewing training leads to a detailed categorization as well as to a detailed clustering, while keeping the clusters that have already been learned and the network structure that has already been developed stable; and (4) reinforcing-by-link training leads to well-perceived auditory–semantic associations. Our I-GSOM model suggests that it is important to associate auditory information with semantic information during language acquisition. Despite its high level of abstraction, our I-GSOM approach can be interpreted as a biologically-inspired neurocomputational model. PMID:24688478

  15. Concepts of Self-Organized Criticality (SOC) for Modeling Hydro-Mechanical Triggering of Shallow Landslides

    Science.gov (United States)

    Lehmann, P.; Or, D.

    2008-12-01

    Sudden landslides often triggered by intense rainfall events present a threat to life and infrastructure in mountainous regions. Empirical relationships between rainfall patterns and landslide occurrence are confounded by topographical, hydrological, land cover and soil factors limiting predictability of onset and frequency of landslides. Even for landslides triggered within a small region due to intense rainfall event, a wide range of released mass per landslide is observed. Landslides frequency often decreases with increasing mass release according to a power-law revealing the criticality nature of the underlying system. A critical behavior without unique scale of landslide magnitude may be readily reproduced based on interactions among hillslope elements. During intense rainfall events a load exerted on certain elements may exceed their mechanical strength resulting in redistribution to neighboring elements. Such load redistribution may result in a cascade of failure events with local mass motions and relaxation which amounts to triggering of a landslide. A critical state (most "dynamically stable") driven by interactions among elements of a system is denoted as self-organized and is attainable under a wide range of external conditions. We capitalize on the concept of self-organized criticality to model landslide triggering by hydrological and mechanical interaction between soil elements of a hillslope. These concepts were formulated in a model SOCHEX that computes surface and subsurface water flows and assigns mechanical properties to bonds, or abstractions of forces connecting hexagonal hillslope cell elements. Water input and flow may alter mechanical loads on the bonds and initiate a cascade of breaking bonds and load redistribution resulting in a landslide. The mechanical properties of bonds and friction at the underlying slip plane depend on water content and pressure spatial distribution patterns as well as on soil properties and plant root distribution

  16. Visualizing the topical structure of the medical sciences: a self-organizing map approach.

    Science.gov (United States)

    Skupin, André; Biberstine, Joseph R; Börner, Katy

    2013-01-01

    We implement a high-resolution visualization of the medical knowledge domain using the self-organizing map (SOM) method, based on a corpus of over two million publications. While self-organizing maps have been used for document visualization for some time, (1) little is known about how to deal with truly large document collections in conjunction with a large number of SOM neurons, (2) post-training geometric and semiotic transformations of the SOM tend to be limited, and (3) no user studies have been conducted with domain experts to validate the utility and readability of the resulting visualizations. Our study makes key contributions to all of these issues. Documents extracted from Medline and Scopus are analyzed on the basis of indexer-assigned MeSH terms. Initial dimensionality is reduced to include only the top 10% most frequent terms and the resulting document vectors are then used to train a large SOM consisting of over 75,000 neurons. The resulting two-dimensional model of the high-dimensional input space is then transformed into a large-format map by using geographic information system (GIS) techniques and cartographic design principles. This map is then annotated and evaluated by ten experts stemming from the biomedical and other domains. Study results demonstrate that it is possible to transform a very large document corpus into a map that is visually engaging and conceptually stimulating to subject experts from both inside and outside of the particular knowledge domain. The challenges of dealing with a truly large corpus come to the fore and require embracing parallelization and use of supercomputing resources to solve otherwise intractable computational tasks. Among the envisaged future efforts are the creation of a highly interactive interface and the elaboration of the notion of this map of medicine acting as a base map, onto which other knowledge artifacts could be overlaid.

  17. Visualizing the topical structure of the medical sciences: a self-organizing map approach.

    Directory of Open Access Journals (Sweden)

    André Skupin

    Full Text Available We implement a high-resolution visualization of the medical knowledge domain using the self-organizing map (SOM method, based on a corpus of over two million publications. While self-organizing maps have been used for document visualization for some time, (1 little is known about how to deal with truly large document collections in conjunction with a large number of SOM neurons, (2 post-training geometric and semiotic transformations of the SOM tend to be limited, and (3 no user studies have been conducted with domain experts to validate the utility and readability of the resulting visualizations. Our study makes key contributions to all of these issues.Documents extracted from Medline and Scopus are analyzed on the basis of indexer-assigned MeSH terms. Initial dimensionality is reduced to include only the top 10% most frequent terms and the resulting document vectors are then used to train a large SOM consisting of over 75,000 neurons. The resulting two-dimensional model of the high-dimensional input space is then transformed into a large-format map by using geographic information system (GIS techniques and cartographic design principles. This map is then annotated and evaluated by ten experts stemming from the biomedical and other domains.Study results demonstrate that it is possible to transform a very large document corpus into a map that is visually engaging and conceptually stimulating to subject experts from both inside and outside of the particular knowledge domain. The challenges of dealing with a truly large corpus come to the fore and require embracing parallelization and use of supercomputing resources to solve otherwise intractable computational tasks. Among the envisaged future efforts are the creation of a highly interactive interface and the elaboration of the notion of this map of medicine acting as a base map, onto which other knowledge artifacts could be overlaid.

  18. Interconnected growing self-organizing maps for auditory and semantic acquisition modeling

    Directory of Open Access Journals (Sweden)

    Mengxue eCao

    2014-03-01

    Full Text Available Based on the incremental nature of knowledge acquisition, in this study we propose a growing self-organizing neural network approach for modeling the acquisition of auditory and semantic categories. We introduce an Interconnected Growing Self-Organizing Maps (I-GSOM algorithm, which takes associations between auditory information and semantic information into consideration, in this paper. Direct phonetic--semantic association is simulated in order to model the language acquisition in early phases, such as the babbling and imitation stages, in which no phonological representations exist. Based on the I-GSOM algorithm, we conducted experiments using paired acoustic and semantic training data. We use a cyclical reinforcing and reviewing training procedure to model the teaching and learning process between children and their communication partners; a reinforcing-by-link training procedure and a link-forgetting procedure are introduced to model the acquisition of associative relations between auditory and semantic information. Experimental results indicate that (1 I-GSOM has good ability to learn auditory and semantic categories presented within the training data; (2 clear auditory and semantic boundaries can be found in the network representation; (3 cyclical reinforcing and reviewing training leads to a detailed categorization as well as to a detailed clustering, while keeping the clusters that have already been learned and the network structure that has already been developed stable; and (4 reinforcing-by-link training leads to well-perceived auditory--semantic associations. Our I-GSOM model suggests that it is important to associate auditory information with semantic information during language acquisition. Despite its high level of abstraction, our I-GSOM approach can be interpreted as a biologically-inspired neurocomputational model.

  19. A Self-Organizing Map-Based Approach to Generating Reduced-Size, Statistically Similar Climate Datasets

    Science.gov (United States)

    Cabell, R.; Delle Monache, L.; Alessandrini, S.; Rodriguez, L.

    2015-12-01

    Climate-based studies require large amounts of data in order to produce accurate and reliable results. Many of these studies have used 30-plus year data sets in order to produce stable and high-quality results, and as a result, many such data sets are available, generally in the form of global reanalyses. While the analysis of these data lead to high-fidelity results, its processing can be very computationally expensive. This computational burden prevents the utilization of these data sets for certain applications, e.g., when rapid response is needed in crisis management and disaster planning scenarios resulting from release of toxic material in the atmosphere. We have developed a methodology to reduce large climate datasets to more manageable sizes while retaining statistically similar results when used to produce ensembles of possible outcomes. We do this by employing a Self-Organizing Map (SOM) algorithm to analyze general patterns of meteorological fields over a regional domain of interest to produce a small set of "typical days" with which to generate the model ensemble. The SOM algorithm takes as input a set of vectors and generates a 2D map of representative vectors deemed most similar to the input set and to each other. Input predictors are selected that are correlated with the model output, which in our case is an Atmospheric Transport and Dispersion (T&D) model that is highly dependent on surface winds and boundary layer depth. To choose a subset of "typical days," each input day is assigned to its closest SOM map node vector and then ranked by distance. Each node vector is treated as a distribution and days are sampled from them by percentile. Using a 30-node SOM, with sampling every 20th percentile, we have been able to reduce 30 years of the Climate Forecast System Reanalysis (CFSR) data for the month of October to 150 "typical days." To estimate the skill of this approach, the "Measure of Effectiveness" (MOE) metric is used to compare area and overlap

  20. Methodical approaches to providing sustainable development of the transport industry management system based on self-organization

    Science.gov (United States)

    Belyantseva, Oksana; Panenkov, Andrey; Safonova, Nataliya

    2017-10-01

    Current conditions of the cognitive economy formation demand to take into account the leading role of information, knowledge and human capital in the development of the transport industry management system. The article substantiates the conceptual approach to the self-organization of a management system on the basis of innovative changes. Human capital is the key aspect of self-organization, so the directions of improving the workforce quality are justified. Basing on the information-innovative genesis of the process of self-organization, the authors justified the necessity of preventing asymmetric information. For this pupose the actions against the resistance to innovations were proposed. The implementation of certain measures contributes to the effective development of the transport management system.

  1. Mars base buildup scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Blacic, J.D.

    1985-01-01

    Two surface base build-up scenarios are presented in order to help visualize the mission and to serve as a basis for trade studies. In the first scenario, direct manned landings on the Martian surface occur early in the missions and scientific investigation is the main driver and rationale. In the second scenario, early development of an infrastructure to exploite the volatile resources of the Martian moons for economic purposes is emphasized. Scientific exploration of the surface is delayed at first, but once begun develops rapidly aided by the presence of a permanently manned orbital station.

  2. Physical processes in thin-film electroluminescent structures based on ZnS:Mn showing self-organized patterns

    CERN Document Server

    Zuccaro, S; Niedernostheide, F J; Kuhn, T; Purwins, H G

    2003-01-01

    Physical processes in thin ZnS:Mn films and their relation to the formation of dynamical patterns in the electroluminescence of AC driven films are investigated. The technique of photo-depolarization-spectroscopy is used to investigate defect states in these films and it is shown that specific features in the spectra correlate with the observed self-organized patterns. Furthermore, the time dependence of the dissipative current is measured at the same samples and compared with current waveforms obtained from numerical simulations of a drift-diffusion model. The results are used to discuss the origin of the self-organized processes in ZnS:Mn-films.

  3. Heterogeneity and Self-Organization of Complex Systems Through an Application to Financial Market with Multiagent Systems

    Science.gov (United States)

    Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

    2017-12-01

    Multiagent systems (MAS) provide a useful tool for exploring the complex dynamics and behavior of financial markets and now MAS approach has been widely implemented and documented in the empirical literature. This paper introduces the implementation of an innovative multi-scale mathematical model for a computational agent-based financial market. The paper develops a method to quantify the degree of self-organization which emerges in the system and shows that the capacity of self-organization is maximized when the agent behaviors are heterogeneous. Numerical results are presented and analyzed, showing how the global market behavior emerges from specific individual behavior interactions.

  4. A self-organized learning strategy for object recognition by an embedded line of attraction

    Science.gov (United States)

    Seow, Ming-Jung; Alex, Ann T.; Asari, Vijayan K.

    2012-04-01

    For humans, a picture is worth a thousand words, but to a machine, it is just a seemingly random array of numbers. Although machines are very fast and efficient, they are vastly inferior to humans for everyday information processing. Algorithms that mimic the way the human brain computes and learns may be the solution. In this paper we present a theoretical model based on the observation that images of similar visual perceptions reside in a complex manifold in an image space. The perceived features are often highly structured and hidden in a complex set of relationships or high-dimensional abstractions. To model the pattern manifold, we present a novel learning algorithm using a recurrent neural network. The brain memorizes information using a dynamical system made of interconnected neurons. Retrieval of information is accomplished in an associative sense. It starts from an arbitrary state that might be an encoded representation of a visual image and converges to another state that is stable. The stable state is what the brain remembers. In designing a recurrent neural network, it is usually of prime importance to guarantee the convergence in the dynamics of the network. We propose to modify this picture: if the brain remembers by converging to the state representing familiar patterns, it should also diverge from such states when presented with an unknown encoded representation of a visual image belonging to a different category. That is, the identification of an instability mode is an indication that a presented pattern is far away from any stored pattern and therefore cannot be associated with current memories. These properties can be used to circumvent the plasticity-stability dilemma by using the fluctuating mode as an indicator to create new states. We capture this behavior using a novel neural architecture and learning algorithm, in which the system performs self-organization utilizing a stability mode and an instability mode for the dynamical system. Based

  5. Power laws and self-organized criticality in theory and nature

    Energy Technology Data Exchange (ETDEWEB)

    Marković, Dimitrije, E-mail: markovic@cbs.mpg.de [Institute for Theoretical Physics, Goethe University Frankfurt (Germany); Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig (Germany); Biomagnetic Center, Hans Berger Clinic for Neurology, University Hospital Jena, Jena (Germany); Gros, Claudius, E-mail: gros@itp.uni-frankfurt.de [Institute for Theoretical Physics, Goethe University Frankfurt (Germany)

    2014-03-01

    Power laws and distributions with heavy tails are common features of many complex systems. Examples are the distribution of earthquake magnitudes, solar flare intensities and the sizes of neuronal avalanches. Previously, researchers surmised that a single general concept may act as an underlying generative mechanism, with the theory of self organized criticality being a weighty contender. The power-law scaling observed in the primary statistical analysis is an important, but by far not the only feature characterizing experimental data. The scaling function, the distribution of energy fluctuations, the distribution of inter-event waiting times, and other higher order spatial and temporal correlations, have seen increased consideration over the last years. Leading to realization that basic models, like the original sandpile model, are often insufficient to adequately describe the complexity of real-world systems with power-law distribution. Consequently, a substantial amount of effort has gone into developing new and extended models and, hitherto, three classes of models have emerged. The first line of models is based on a separation between the time scales of an external drive and an internal dissipation, and includes the original sandpile model and its extensions, like the dissipative earthquake model. Within this approach the steady state is close to criticality in terms of an absorbing phase transition. The second line of models is based on external drives and internal dynamics competing on similar time scales and includes the coherent noise model, which has a non-critical steady state characterized by heavy-tailed distributions. The third line of models proposes a non-critical self-organizing state, being guided by an optimization principle, such as the concept of highly optimized tolerance. We present a comparative overview regarding distinct modeling approaches together with a discussion of their potential relevance as underlying generative models for real

  6. Assessing the accuracy of simulated peak discharges using Self Organizing Maps

    Science.gov (United States)

    Casper, M. C.; Herbst, M.

    2009-04-01

    Distributed watershed models constitute a key component in flood forecasting systems. It is widely recognized that models because of their structural differences have varying capabilities of capturing different aspects of the system behaviour equally well. Of course, this also applies to the reproduction of peak discharges by a simulation model which is of particular interest regarding the flood forecasting problem. In our study we use a Self-Organizing Map (SOM) in combination with index measures which are derived from the flow duration curve in order to examine the conditions under which three different distributed watershed models are capable of reproducing flood events present in the calibration data. These indices are specifically conceptualized to extract information on the peak discharge characteristics of model output time series which are obtained from Monte-Carlo simulations with the distributed watershed models NASIM, LARSIM and WaSIM-ETH. The SOM helps to analyze this data by producing a discretized mapping of their distribution in the index space onto a two dimensional plane such that their pattern and consequently the patterns of model behaviour can be conveyed in a comprehensive manner. It is demonstrated how the SOM provides useful information about details of model behaviour and also helps identifying the model parameters that are relevant for the reproduction of peak discharges and thus for flood prediction problems. It is further shown how the SOM can be used to identify those parameter sets from among the Monte-Carlo data that most closely approximate the peak discharges of a measured time series. The results represent the characteristics of the observed time series with partially superior accuracy than the reference simulation obtained by implementing a simple calibration strategy using the global optimization algorithm SCE-UA. The most prominent advantage of using SOM in the context of model analysis is that it allows to comparatively

  7. Mechanisms of self-organized criticality in social processes of knowledge creation

    Science.gov (United States)

    Tadić, Bosiljka; Dankulov, Marija Mitrović; Melnik, Roderick

    2017-09-01

    In online social dynamics, a robust scale invariance appears as a key feature of collaborative efforts that lead to new social value. The underlying empirical data thus offers a unique opportunity to study the origin of self-organized criticality (SOC) in social systems. In contrast to physical systems in the laboratory, various human attributes of the actors play an essential role in the process along with the contents (cognitive, emotional) of the communicated artifacts. As a prototypical example, we consider the social endeavor of knowledge creation via Questions and Answers (Q&A). Using a large empirical data set from one of such Q&A sites and theoretical modeling, we reveal fundamental characteristics of SOC by investigating the temporal correlations at all scales and the role of cognitive contents to the avalanches of the knowledge-creation process. Our analysis shows that the universal social dynamics with power-law inhomogeneities of the actions and delay times provides the primary mechanism for self-tuning towards the critical state; it leads to the long-range correlations and the event clustering in response to the external driving by the arrival of new users. In addition, the involved cognitive contents (systematically annotated in the data and observed in the model) exert important constraints that identify unique classes of the knowledge-creation avalanches. Specifically, besides determining a fine structure of the developing knowledge networks, they affect the values of scaling exponents and the geometry of large avalanches and shape the multifractal spectrum. Furthermore, we find that the level of the activity of the communities that share the knowledge correlates with the fluctuations of the innovation rate, implying that the increase of innovation may serve as the active principle of self-organization. To identify relevant parameters and unravel the role of the network evolution underlying the process in the social system under consideration, we

  8. Self-organized criticality induced by quenched disorder: Experiments on flux avalanches in NbHx films

    NARCIS (Netherlands)

    Welling, M.S.; Aegerter, C.M.; Wijngaarden, R.J.

    2005-01-01

    We present an experimental study of the influence of quenched disorder on the distribution of flux avalanches in type-II superconductors. In the presence of much quenched disorder, the avalanche sizes are powerlaw distributed and show finite-size scaling, as expected from self-organized criticality

  9. Self-Organizing Neural Network Map for the Purpose of Visualizing the Concept Images of Students on Angles

    Science.gov (United States)

    Kaya, Deniz

    2017-01-01

    The purpose of the study is to perform a less-dimensional thorough visualization process for the purpose of determining the images of the students on the concept of angle. The Ward clustering analysis combined with Self-Organizing Neural Network Map (SOM) has been used for the dimension process. The Conceptual Understanding Tool, which consisted…

  10. Curbing domestic violence: Instantiating C-K theory with formal concept analysis and emergent self-organizing maps

    NARCIS (Netherlands)

    Poelmans, J.; Elzinga, P.; Viaene, S.; Dedene, G.

    2010-01-01

    We propose a human-centred process for knowledge discovery from unstructured text that makes use of formal concept analysis and emergent self-organizing maps. The knowledge discovery process is conceptualized and interpreted as successive iterations through the concept-knowledge (C-K) theory design

  11. The influence of local- and landscape-scale processes on spatial self-organization in estuarine ecosystems

    NARCIS (Netherlands)

    Van de Koppel, J.; Bouma, T.J.; Herman, P.M.J.

    2012-01-01

    Complexity theory proposes that spatial self-organization, the process whereby small-scale, localized interactions among the components of a system generate complex spatial structures at large spatial scales, explains the formation of autogenic spatial patterns in ecosystems. We question this

  12. Unsupervised spatiotemporal analysis of fMRI data using graph-based visualizations of self-organizing maps.

    Science.gov (United States)

    Katwal, Santosh B; Gore, John C; Marois, Rene; Rogers, Baxter P

    2013-09-01

    We present novel graph-based visualizations of self-organizing maps for unsupervised functional magnetic resonance imaging (fMRI) analysis. A self-organizing map is an artificial neural network model that transforms high-dimensional data into a low-dimensional (often a 2-D) map using unsupervised learning. However, a postprocessing scheme is necessary to correctly interpret similarity between neighboring node prototypes (feature vectors) on the output map and delineate clusters and features of interest in the data. In this paper, we used graph-based visualizations to capture fMRI data features based upon 1) the distribution of data across the receptive fields of the prototypes (density-based connectivity); and 2) temporal similarities (correlations) between the prototypes (correlation-based connectivity). We applied this approach to identify task-related brain areas in an fMRI reaction time experiment involving a visuo-manual response task, and we correlated the time-to-peak of the fMRI responses in these areas with reaction time. Visualization of self-organizing maps outperformed independent component analysis and voxelwise univariate linear regression analysis in identifying and classifying relevant brain regions. We conclude that the graph-based visualizations of self-organizing maps help in advanced visualization of cluster boundaries in fMRI data enabling the separation of regions with small differences in the timings of their brain responses.

  13. Self-Organization and the Bypass: Re-Imagining Institutions for More Sustainable Development in Agriculture and Food

    NARCIS (Netherlands)

    Sherwood, Stephen; Bommel, Van Severine; Paredes, Myriam

    2016-01-01

    In exploring the social dynamics of agrofood movements in Ecuador as examples of self-organization (i.e., locally distributed and resolved development), this article departs from a preoccupation with innovation by means of design and the use of scaling as a metaphor for describing research

  14. SCENARIO PLANNING AS LEARNING

    Directory of Open Access Journals (Sweden)

    Antonio Lourenço Junior

    2010-10-01

    Full Text Available Scenario Planning has been increasingly used, from its introduction to the decision process as effective tools to test decisions, and improve performance in a dynamic environment (Chermack, 2005. The purpose of this article is to demonstrate the potential of an experimental Scenario Planning Model to mobilize, encourage and add more content to the organization’s decision making process – mainly with respect to Strategic Plans of two governmental institutions, a pharmaceutical company and a technology education foundation.  This study describes the application stages of a hybrid scenario-planning model – herein referred to as Planning as Learning – via action-research, showing the scenarios resulting from the experiment and describes the main results of an assessment of such practice. In order to do that, two well-established Scenario Planning models (Prospective school and Shell’s model were analyzed. They were used as a reference for the proposition and application of an experimental model in the two study objects. A questionnaire was used to assess the technique impact. It was possible to obtain high levels of reliability. In-depth interviews were also conducted with the participants. At the end, the results confirmed the model efficiency as a basis for decision making in the competitive environment in which the two institutions are inserted, also to encourage the learning process as a group, as observed throughout the work.

  15. BCube Ocean Scenario

    Science.gov (United States)

    Santoro, Mattia; Schofield, Oscar; Pearlman, Jay; Nativi, Stefano

    2015-04-01

    To address complex Earth system issues such as climate change and water resources, geoscientists must work across disciplinary boundaries; this requires them to access data outside of their fields. Scientists are being called upon to find, access, and use diverse and voluminous data types that are described with semantics. Within the framework of the NSF EarthCube programme, the BCube project (A Broker Framework for Next Generation Geoscience) is addressing the need for effective and efficient multi-disciplinary collaboration and interoperability through the advancement of brokering technologies. BCube develops science scenarios as key elements in providing an environment for demonstrating capabilities, benefits, and challenges of the developed e-infrastructure. The initial focus is on hydrology, oceans, polar and weather, with the intent to make the technology applicable and available to all the geosciences. This presentation focuses on the BCube ocean scenario. The purpose of this scenario is to increase the understanding of the ocean dynamics through incorporation of a wide range of in-situ and satellite data into ocean models using net primary productivity as the initial variable. The science scenario aims to identify spatial and temporal domains in ocean models, and key ecological variables. Field data sets and remote observations data sets from distributed and heterogeneous systems are accessed through the broker and will be incorporated into the models. In this work we will present the achievements in the development of the BCube ocean scenario.

  16. Exploiting data topology in visualization and clustering of self-organizing maps.

    Science.gov (United States)

    Taşdemir, Kadim; Merényi, Erzsébet

    2009-04-01

    The self-organizing map (SOM) is a powerful method for visualization, cluster extraction, and data mining. It has been used successfully for data of high dimensionality and complexity where traditional methods may often be insufficient. In order to analyze data structure and capture cluster boundaries from the SOM, one common approach is to represent the SOM's knowledge by visualization methods. Different aspects of the information learned by the SOM are presented by existing methods, but data topology, which is present in the SOM's knowledge, is greatly underutilized. We show in this paper that data topology can be integrated into the visualization of the SOM and thereby provide a more elaborate view of the cluster structure than existing schemes. We achieve this by introducing a weighted Delaunay triangulation (a connectivity matrix) and draping it over the SOM. This new visualization, CONNvis, also shows both forward and backward topology violations along with the severity of forward ones, which indicate the quality of the SOM learning and the data complexity. CONNvis greatly assists in detailed identification of cluster boundaries. We demonstrate the capabilities on synthetic data sets and on a real 8-D remote sensing spectral image.

  17. Semi-automatic mapping of linear-trending bedforms using 'Self-Organizing Maps' algorithm

    Science.gov (United States)

    Foroutan, M.; Zimbelman, J. R.

    2017-09-01

    Increased application of high resolution spatial data such as high resolution satellite or Unmanned Aerial Vehicle (UAV) images from Earth, as well as High Resolution Imaging Science Experiment (HiRISE) images from Mars, makes it necessary to increase automation techniques capable of extracting detailed geomorphologic elements from such large data sets. Model validation by repeated images in environmental management studies such as climate-related changes as well as increasing access to high-resolution satellite images underline the demand for detailed automatic image-processing techniques in remote sensing. This study presents a methodology based on an unsupervised Artificial Neural Network (ANN) algorithm, known as Self Organizing Maps (SOM), to achieve the semi-automatic extraction of linear features with small footprints on satellite images. SOM is based on competitive learning and is efficient for handling huge data sets. We applied the SOM algorithm to high resolution satellite images of Earth and Mars (Quickbird, Worldview and HiRISE) in order to facilitate and speed up image analysis along with the improvement of the accuracy of results. About 98% overall accuracy and 0.001 quantization error in the recognition of small linear-trending bedforms demonstrate a promising framework.

  18. Self-organization processes in polysiloxane block copolymers, initiated by modifying fullerene additives

    Science.gov (United States)

    Voznyakovskii, A. P.; Kudoyarova, V. Kh.; Kudoyarov, M. F.; Patrova, M. Ya.

    2017-08-01

    Thin films of a polyblock polysiloxane copolymer and their composites with a modifying fullerene C60 additive are studied by atomic force microscopy, Rutherford backscattering, and neutron scattering. The data of atomic force microscopy show that with the addition of fullerene to the bulk of the polymer matrix, the initial relief of the film surface is leveled more, the larger the additive. This trend is associated with the processes of self-organization of rigid block sequences, which are initiated by the field effect of the surface of fullerene aggregates and lead to an increase in the number of their domains in the bulk of the polymer matrix. The data of Rutherford backscattering and neutron scattering indicate the formation of additional structures with a radius of 60 nm only in films containing fullerene, and their fraction increases with increasing fullerene concentration. A comparative analysis of the data of these methods has shown that such structures are, namely, the domains of a rigid block and are not formed by individual fullerene aggregates. The interrelation of the structure and mechanical properties of polymer films is considered.

  19. GUASOM: Gaia Utility for Analysis and Knowledge Discovery based on Self Organizing Maps

    Science.gov (United States)

    Fustes, D.; Manteiga, M.; Dafonte, C.; Arcay, B.; Alvarez, M. A.; Garabato, D.

    2014-07-01

    We present a method for knowledge analysis in large astronomical spectrophotometric archives. The method is based on a type of unsupervised learning Artificial Neural Networks named Self-organizing maps (SOMs). SOMs are used to organize the information in clusters of objects, as homogeneously as possible according to their spectral energy distributions, and to project them onto a 2D grid where the data structure can be visualized. Our algorithm has been tested by means of simulated Gaia spectrophotometry (150,000 objects), which is based on SDSS observations and theoretical spectral libraries covering a wide sample of astronomical objects. We demonstrate the usefulness of the method by analyzing over 10,000 objects, mostly fainted objects and unsuccessful observations, that were rejected by the SDSS spectroscopic classification pipeline and thus classified as "UNKNOWN". This dataset was transformed to Gaia BP and RP format by the use of GOG simulator. GUASOM provides a useful toolbox to study the data distribution in extense archives. Even more, the discovered neighbourhood relationships help to unveil the physical nature of objects never observed before. To this effect, we used the SIMBAD catalog to perform crossmatching with the SDSS astrometry, seeking for more identifications.

  20. An efficient self-organizing map designed by genetic algorithms for the traveling salesman problem.

    Science.gov (United States)

    Jin, Hui-Dong; Leung, Kwong-Sak; Wong, Man-Leung; Xu, Z B

    2003-01-01

    As a typical combinatorial optimization problem, the traveling salesman problem (TSP) has attracted extensive research interest. In this paper, we develop a self-organizing map (SOM) with a novel learning rule. It is called the integrated SOM (ISOM) since its learning rule integrates the three learning mechanisms in the SOM literature. Within a single learning step, the excited neuron is first dragged toward the input city, then pushed to the convex hull of the TSP, and finally drawn toward the middle point of its two neighboring neurons. A genetic algorithm is successfully specified to determine the elaborate coordination among the three learning mechanisms as well as the suitable parameter setting. The evolved ISOM (eISOM) is examined on three sets of TSP to demonstrate its power and efficiency. The computation complexity of the eISOM is quadratic, which is comparable to other SOM-like neural networks. Moreover, the eISOM can generate more accurate solutions than several typical approaches for TSP including the SOM developed by Budinich, the expanding SOM, the convex elastic net, and the FLEXMAP algorithm. Though its solution accuracy is not yet comparable to some sophisticated heuristics, the eISOM is one of the most accurate neural networks for the TSP.