Sample records for swarms field experiment

  1. Swarm: ESA's Magnetic Field Mission

    NASA Astrophysics Data System (ADS)

    Plank, G.; Floberghagen, R.; Menard, Y.; Haagmans, R.

    2013-12-01

    Swarm is the fifth Earth Explorer mission in ESA's Living Planet Programme, and is scheduled for launch in fall 2013. The objective of the Swarm mission is to provide the best-ever survey of the geomagnetic field and its temporal evolution using a constellation of three identical satellites. The mission shall deliver data that allow access to new insights into the Earth system by improved scientific understanding of the Earth's interior and near-Earth electromagnetic environment. After launch and triple satellite release at an initial altitude of about 490 km, a pair of the satellites will fly side-by-side with slowly decaying altitude, while the third satellite will be lifted to 530 km to complete the Swarm constellation. High-precision and high-resolution measurements of the strength, direction and variation of the magnetic field, complemented by precise navigation, accelerometer and electric field measurements, will provide the observations required to separate and model various sources of the geomagnetic field and near-Earth current systems. The mission science goals are to provide a unique view into Earth's core dynamics, mantle conductivity, crustal magnetisation, ionospheric and magnetospheric current systems and upper atmosphere dynamics - ranging from understanding the geodynamo to contributing to space weather. The scientific objectives and results from recent scientific studies will be presented. In addition the current status of the project, which is presently in the final stage of the development phase, will be addressed. A consortium of European scientific institutes is developing a distributed processing system to produce geophysical (Level 2) data products for the Swarm user community. The setup of the Swarm ground segment and the contents of the data products will be addressed. In case the Swarm satellites are already in orbit, a summary of the on-going mission operations activities will be given. More information on Swarm can be found at www.esa.int/esaLP/LPswarm.html.

  2. Swarm: ESA's Magnetic Field Mission

    NASA Astrophysics Data System (ADS)

    Plank, G.; Floberghagen, R.; Menard, Y.; Haagmans, R.

    2012-12-01

    Swarm is the fifth Earth Explorer mission in ESA's Living Planet Programme, and is scheduled for launch in fall 2012. The objective of the Swarm mission is to provide the best-ever survey of the geomagnetic field and its temporal evolution using a constellation of three identical satellites. The mission shall deliver data that allow access to new insights into the Earth system by improved scientific understanding of the Earth's interior and near-Earth electromagnetic environment. After launch and triple satellite release at an initial altitude of about 490 km, a pair of the satellites will fly side-by-side with slowly decaying altitude, while the third satellite will be lifted to 530 km to complete the Swarm constellation. High-precision and high-resolution measurements of the strength, direction and variation of the magnetic field, complemented by precise navigation, accelerometer and electric field measurements, will provide the observations required to separate and model various sources of the geomagnetic field and near-Earth current systems. The mission science goals are to provide a unique view into Earth's core dynamics, mantle conductivity, crustal magnetisation, ionospheric and magnetospheric current systems and upper atmosphere dynamics - ranging from understanding the geodynamo to contributing to space weather. The scientific objectives and results from recent scientific studies will be presented. In addition the current status of the project, which is presently in the final stage of the development phase, will be addressed. A consortium of European scientific institutes is developing a distributed processing system to produce geophysical (Level 2) data products for the Swarm user community. The setup of the Swarm ground segment and the contents of the data products will be addressed. In case the Swarm satellites are already in orbit, a summary of the on-going mission operations activities will be given.

  3. The Swarm Initial Field Model for the 2014 Geomagnetic Field

    NASA Technical Reports Server (NTRS)

    Olsen, Nils; Hulot, Gauthier; Lesur, Vincent; Finlay, Christopher C.; Beggan, Ciaran; Chulliat, Arnaud; Sabaka, Terence J.; Floberghagen, Rune; Friis-Christensen, Eigil; Haagmans, Roger

    2015-01-01

    Data from the first year of ESA's Swarm constellation mission are used to derive the Swarm Initial Field Model (SIFM), a new model of the Earth's magnetic field and its time variation. In addition to the conventional magnetic field observations provided by each of the three Swarm satellites, explicit advantage is taken of the constellation aspect by including east-west magnetic intensity gradient information from the lower satellite pair. Along-track differences in magnetic intensity provide further information concerning the north-south gradient. The SIFM static field shows excellent agreement (up to at least degree 60) with recent field models derived from CHAMP data, providing an initial validation of the quality of the Swarm magnetic measurements. Use of gradient data improves the determination of both the static field and its secular variation, with the mean misfit for east-west intensity differences between the lower satellite pair being only 0.12 nT.

  4. The influence of swarm deformation on the velocity behavior of falling swarms of particles

    NASA Astrophysics Data System (ADS)

    Mitchell, C. A.; Pyrak-Nolte, L. J.; Nitsche, L.

    2017-12-01

    Cohesive particle swarms have been shown to exhibit enhanced sedimentation in fractures for an optimal range of fracture apertures. Within this range, swarms travel farther and faster than a disperse (particulate) solution. This study aims to uncover the physics underlying the enhanced sedimentation. Swarm behavior at low Reynolds number in a quiescent unbounded fluid and between smooth rigid planar boundaries is investigated numerically using direct-summation, particle-mesh (PM) and particle-particle particle-mesh (P3M) methods - based upon mutually interacting viscous point forces (Stokeslet fields). Wall effects are treated with a least-squares boundary singularity method. Sub-structural effects beyond pseudo-liquid behavior (i.e., particle-scale interactions) are approximated by the P3M method much more efficiently than with direct summation. The model parameters are selected from particle swarm experiments to enable comparison. From the simulations, if the initial swarm geometry at release is unaffected by the fracture aperture, no enhanced transport occurs. The swarm velocity as a function of apertures increases monotonically until it asymptotes to the swarm velocity in an open tank. However, if the fracture aperture affects the initial swarm geometry, the swarm velocity no longer exhibits a monotonic behavior. When swarms are released between two parallel smooth walls with very small apertures, the swarm is forced to reorganize and quickly deform, which results in dramatically reduced swarm velocities. At large apertures, the swarm evolution is similar to that of a swarm in open tank and quickly flattens into a slow speed torus. In the optimal aperture range, the swarm maintains a cohesive unit behaving similarly to a falling sphere. Swarms falling in apertures less than or greater than the optimal aperture range, experience a level of anisotropy that considerably decreases velocities. Unraveling the physics that drives swarm behavior in fractured porous

  5. Time-variable gravity fields and ocean mass change from 37 months of kinematic Swarm orbits

    NASA Astrophysics Data System (ADS)

    Lück, Christina; Kusche, Jürgen; Rietbroek, Roelof; Löcher, Anno

    2018-03-01

    Measuring the spatiotemporal variation of ocean mass allows for partitioning of volumetric sea level change, sampled by radar altimeters, into mass-driven and steric parts. The latter is related to ocean heat change and the current Earth's energy imbalance. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) mission has provided monthly snapshots of the Earth's time-variable gravity field, from which one can derive ocean mass variability. However, GRACE has reached the end of its lifetime with data degradation and several gaps occurred during the last years, and there will be a prolonged gap until the launch of the follow-on mission GRACE-FO. Therefore, efforts focus on generating a long and consistent ocean mass time series by analyzing kinematic orbits from other low-flying satellites, i.e. extending the GRACE time series. Here we utilize data from the European Space Agency's (ESA) Swarm Earth Explorer satellites to derive and investigate ocean mass variations. For this aim, we use the integral equation approach with short arcs (Mayer-Gürr, 2006) to compute more than 500 time-variable gravity fields with different parameterizations from kinematic orbits. We investigate the potential to bridge the gap between the GRACE and the GRACE-FO mission and to substitute missing monthly solutions with Swarm results of significantly lower resolution. Our monthly Swarm solutions have a root mean square error (RMSE) of 4.0 mm with respect to GRACE, whereas directly estimating constant, trend, annual, and semiannual (CTAS) signal terms leads to an RMSE of only 1.7 mm. Concerning monthly gaps, our CTAS Swarm solution appears better than interpolating existing GRACE data in 13.5 % of all cases, when artificially removing one solution. In the case of an 18-month artificial gap, 80.0 % of all CTAS Swarm solutions were found closer to the observed GRACE data compared to interpolated GRACE data. Furthermore, we show that precise modeling of non-gravitational forces

  6. Gold rush - A swarm dynamics in games

    NASA Astrophysics Data System (ADS)

    Zelinka, Ivan; Bukacek, Michal

    2017-07-01

    This paper is focused on swarm intelligence techniques and its practical use in computer games. The aim is to show how a swarm dynamics can be generated by multiplayer game, then recorded, analyzed and eventually controlled. In this paper we also discuss possibility to use swarm intelligence instead of game players. Based on our previous experiments two games, using swarm algorithms are mentioned briefly here. The first one is strategy game StarCraft: Brood War, and TicTacToe in which SOMA algorithm has also take a role of player against human player. Open research reported here has shown potential benefit of swarm computation in the field of strategy games and players strategy based on swarm behavior record and analysis. We propose new game called Gold Rush as an experimental environment for human or artificial swarm behavior and consequent analysis.

  7. Impact of tracking loop settings of the Swarm GPS receiver on gravity field recovery

    NASA Astrophysics Data System (ADS)

    Dahle, C.; Arnold, D.; Jäggi, A.

    2017-06-01

    The Swarm mission consists of three identical satellites equipped with GPS receivers and orbiting in near-polar low Earth orbits. Thus, they can be used to determine the Earth's gravity field by means of high-low satellite-to-satellite tracking (hl-SST). However, first results by several groups have revealed systematic errors both in precise science orbits and resulting gravity field solutions which are caused by ionospheric disturbances affecting the quality of Swarm GPS observations. Looking at gravity field solutions, the errors lead to systematic artefacts located in two bands north and south of the geomagnetic equator. In order to reduce these artefacts, erroneous GPS observations can be identified and rejected before orbit and gravity field processing, but this may also lead to slight degradations of orbit and low degree gravity field coefficient quality. Since the problems were believed to be receiver-specific, the GPS tracking loop bandwidths onboard Swarm have been widened several times starting in May 2015. The influence of these tracking loop updates on Swarm orbits and, particularly, gravity field solutions is investigated in this work. The main findings are that the first updates increasing the bandwidth from 0.25 Hz to 0.5 Hz help to significantly improve the quality of Swarm gravity fields and that the improvements are even larger than those achieved by GPS data rejection. It is also shown that these improvements are indeed due to an improved quality of GPS observations around the geomagnetic equator, and not due to missing observations in these regions. As the ionospheric activity is rather low in the most recent months, the effect of the tracking loop updates in summer 2016 cannot be properly assessed yet. Nevertheless, the quality of Swarm gravity field solutions has already improved after the first updates which is especially beneficial in view of filling the upcoming gap between the GRACE and GRACE Follow-on missions with hl-SST gravity products.

  8. Symbiosis-Based Alternative Learning Multi-Swarm Particle Swarm Optimization.

    PubMed

    Niu, Ben; Huang, Huali; Tan, Lijing; Duan, Qiqi

    2017-01-01

    Inspired by the ideas from the mutual cooperation of symbiosis in natural ecosystem, this paper proposes a new variant of PSO, named Symbiosis-based Alternative Learning Multi-swarm Particle Swarm Optimization (SALMPSO). A learning probability to select one exemplar out of the center positions, the local best position, and the historical best position including the experience of internal and external multiple swarms, is used to keep the diversity of the population. Two different levels of social interaction within and between multiple swarms are proposed. In the search process, particles not only exchange social experience with others that are from their own sub-swarms, but also are influenced by the experience of particles from other fellow sub-swarms. According to the different exemplars and learning strategy, this model is instantiated as four variants of SALMPSO and a set of 15 test functions are conducted to compare with some variants of PSO including 10, 30 and 50 dimensions, respectively. Experimental results demonstrate that the alternative learning strategy in each SALMPSO version can exhibit better performance in terms of the convergence speed and optimal values on most multimodal functions in our simulation.

  9. A lithospheric magnetic field model derived from the Swarm satellite magnetic field measurements

    NASA Astrophysics Data System (ADS)

    Hulot, G.; Thebault, E.; Vigneron, P.

    2015-12-01

    The Swarm constellation of satellites was launched in November 2013 and has since then delivered high quality scalar and vector magnetic field measurements. A consortium of several research institutions was selected by the European Space Agency (ESA) to provide a number of scientific products which will be made available to the scientific community. Within this framework, specific tools were tailor-made to better extract the magnetic signal emanating from Earth's the lithospheric. These tools rely on the scalar gradient measured by the lower pair of Swarm satellites and rely on a regional modeling scheme that is more sensitive to small spatial scales and weak signals than the standard spherical harmonic modeling. In this presentation, we report on various activities related to data analysis and processing. We assess the efficiency of this dedicated chain for modeling the lithospheric magnetic field using more than one year of measurements, and finally discuss refinements that are continuously implemented in order to further improve the robustness and the spatial resolution of the lithospheric field model.

  10. Probing the Earth's core with magnetic field observations from Swarm

    NASA Astrophysics Data System (ADS)

    Finlay, Christopher; Olsen, Nils; Kotsiaros, Stavros; Gillet, Nicolas; Tøffner-Clausen, Lars

    2016-07-01

    By far the largest part of the Earth's magnetic field is generated by motions taking place within our planet's liquid metal outer core. Variations of this core-generated field thus provide a unique means of probing the dynamics taking place in the deepest reaches of the Earth. In this contribution we present a new high resolution model of the core-generated magnetic field, and its recent time changes, derived from a dataset that includes more two years of observations from the Swarm mission. Resulting inferences regarding the underlying core flow, its dynamics, and the nature of the geodynamo process will be discussed. The CHAOS-6 geomagnetic field model, covering the interval 1999-2016, is derived from magnetic data collected by the three Swarm missions, as well as the earlier CHAMP and Oersted satellites, and monthly means data collected from 160 ground observatories. Advantage is taken of the constellation aspect of the Swarm mission by ingesting both scalar and vector field differences along-track and across track between the lower pair of Swarm satellites. The internal part of the model consists of a spherical harmonic (SH) expansion, time-dependent for degrees 20 and below. The model coefficients are estimated using a regularized, iteratively reweighted, least squares scheme involving Huber weights. At Earth's surface, CHAOS-6 shows evidence for positive acceleration of the field intensity in 2015 over a broad area around longitude 90deg E that is also seen at ground observatories such as Novosibirsk. At the core surface, we are able to map the secular variation (linear trend in the magnetic field) up to SH degree 16. The radial field acceleration at the core surface in 2015 is found be largest at low latitudes under the India-South East Asia region and under the region of northern South America, as well as at high northern latitudes under Alaska and Siberia. Surprisingly, there is also evidence for some acceleration in the central Pacific region, for example

  11. [Application of an Adaptive Inertia Weight Particle Swarm Algorithm in the Magnetic Resonance Bias Field Correction].

    PubMed

    Wang, Chang; Qin, Xin; Liu, Yan; Zhang, Wenchao

    2016-06-01

    An adaptive inertia weight particle swarm algorithm is proposed in this study to solve the local optimal problem with the method of traditional particle swarm optimization in the process of estimating magnetic resonance(MR)image bias field.An indicator measuring the degree of premature convergence was designed for the defect of traditional particle swarm optimization algorithm.The inertia weight was adjusted adaptively based on this indicator to ensure particle swarm to be optimized globally and to avoid it from falling into local optimum.The Legendre polynomial was used to fit bias field,the polynomial parameters were optimized globally,and finally the bias field was estimated and corrected.Compared to those with the improved entropy minimum algorithm,the entropy of corrected image was smaller and the estimated bias field was more accurate in this study.Then the corrected image was segmented and the segmentation accuracy obtained in this research was 10% higher than that with improved entropy minimum algorithm.This algorithm can be applied to the correction of MR image bias field.

  12. Do small swarms have an advantage when house hunting? The effect of swarm size on nest-site selection by Apis mellifera.

    PubMed

    Schaerf, T M; Makinson, J C; Myerscough, M R; Beekman, M

    2013-10-06

    Reproductive swarms of honeybees are faced with the problem of finding a good site to establish a new colony. We examined the potential effects of swarm size on the quality of nest-site choice through a combination of modelling and field experiments. We used an individual-based model to examine the effects of swarm size on decision accuracy under the assumption that the number of bees actively involved in the decision-making process (scouts) is an increasing function of swarm size. We found that the ability of a swarm to choose the best of two nest sites decreases as swarm size increases when there is some time-lag between discovering the sites, consistent with Janson & Beekman (Janson & Beekman 2007 Proceedings of European Conference on Complex Systems, pp. 204-211.). However, when simulated swarms were faced with a realistic problem of choosing between many nest sites discoverable at all times, larger swarms were more accurate in their decisions than smaller swarms owing to their ability to discover nest sites more rapidly. Our experimental fieldwork showed that large swarms invest a larger number of scouts into the decision-making process than smaller swarms. Preliminary analysis of waggle dances from experimental swarms also suggested that large swarms could indeed discover and advertise nest sites at a faster rate than small swarms.

  13. Do small swarms have an advantage when house hunting? The effect of swarm size on nest-site selection by Apis mellifera

    PubMed Central

    Schaerf, T. M.; Makinson, J. C.; Myerscough, M. R.; Beekman, M.

    2013-01-01

    Reproductive swarms of honeybees are faced with the problem of finding a good site to establish a new colony. We examined the potential effects of swarm size on the quality of nest-site choice through a combination of modelling and field experiments. We used an individual-based model to examine the effects of swarm size on decision accuracy under the assumption that the number of bees actively involved in the decision-making process (scouts) is an increasing function of swarm size. We found that the ability of a swarm to choose the best of two nest sites decreases as swarm size increases when there is some time-lag between discovering the sites, consistent with Janson & Beekman (Janson & Beekman 2007 Proceedings of European Conference on Complex Systems, pp. 204–211.). However, when simulated swarms were faced with a realistic problem of choosing between many nest sites discoverable at all times, larger swarms were more accurate in their decisions than smaller swarms owing to their ability to discover nest sites more rapidly. Our experimental fieldwork showed that large swarms invest a larger number of scouts into the decision-making process than smaller swarms. Preliminary analysis of waggle dances from experimental swarms also suggested that large swarms could indeed discover and advertise nest sites at a faster rate than small swarms. PMID:23904590

  14. Daphnia swarms: from single agent dynamics to collective vortex formation

    NASA Astrophysics Data System (ADS)

    Ordemann, Anke; Balazsi, Gabor; Caspari, Elizabeth; Moss, Frank

    2003-05-01

    Swarm theories have become fashionable in theoretical physics over the last decade. They span the range of interactions from individual agents moving in a mean field to coherent collective motions of large agent populations, such as vortex-swarming. But controlled laboratory tests of these theories using real biological agents have been problematic due primarily to poorly known agent-agent interactions (in the case of e.g. bacteria and slime molds) or the large swarm size (e.g. for flocks of birds and schools of fish). Moreover, the entire range of behaviors from single agent interactions to collective vortex motions of the swarm have here-to-fore not been observed with a single animal. We present the results of well defined experiments with the zooplankton Daphnia in light fields showing this range of behaviors. We interpret our results with a theory of the motions of self-propelled agents in a field.

  15. Distributioin, orientation and scales of the field-aligned currents measured by Swarm

    NASA Astrophysics Data System (ADS)

    Yang, J.; Dunlop, M. W.

    2016-12-01

    We have statistically studied the R1, R2 and net field aligned currents using the FAC data of the Swarm satellites. We also have investigated the statistical, dual-spacecraft correlations of field-aligned current signatures between two Swarm spacecraft (A and C). For the first time we have inferred the orientations of the current sheets of FACs directly, using the maximum correlations, obtained from sliding data segments, which show clear trends in magnetic local time (MLT). To compare with this we also check the MVAB method. To explore the scale and variability of the current sheet supposition, we investigate the MLT dependence of the maximum correlations in different time shift or longitude shift bins.

  16. An algorithm for deriving core magnetic field models from the Swarm data set

    NASA Astrophysics Data System (ADS)

    Rother, Martin; Lesur, Vincent; Schachtschneider, Reyko

    2013-11-01

    In view of an optimal exploitation of the Swarm data set, we have prepared and tested software dedicated to the determination of accurate core magnetic field models and of the Euler angles between the magnetic sensors and the satellite reference frame. The dedicated core field model estimation is derived directly from the GFZ Reference Internal Magnetic Model (GRIMM) inversion and modeling family. The data selection techniques and the model parameterizations are similar to what were used for the derivation of the second (Lesur et al., 2010) and third versions of GRIMM, although the usage of observatory data is not planned in the framework of the application to Swarm. The regularization technique applied during the inversion process smoothes the magnetic field model in time. The algorithm to estimate the Euler angles is also derived from the CHAMP studies. The inversion scheme includes Euler angle determination with a quaternion representation for describing the rotations. It has been built to handle possible weak time variations of these angles. The modeling approach and software have been initially validated on a simple, noise-free, synthetic data set and on CHAMP vector magnetic field measurements. We present results of test runs applied to the synthetic Swarm test data set.

  17. Swarm-based medicine.

    PubMed

    Putora, Paul Martin; Oldenburg, Jan

    2013-09-19

    Occasionally, medical decisions have to be taken in the absence of evidence-based guidelines. Other sources can be drawn upon to fill in the gaps, including experience and intuition. Authorities or experts, with their knowledge and experience, may provide further input--known as "eminence-based medicine". Due to the Internet and digital media, interactions among physicians now take place at a higher rate than ever before. With the rising number of interconnected individuals and their communication capabilities, the medical community is obtaining the properties of a swarm. The way individual physicians act depends on other physicians; medical societies act based on their members. Swarm behavior might facilitate the generation and distribution of knowledge as an unconscious process. As such, "swarm-based medicine" may add a further source of information to the classical approaches of evidence- and eminence-based medicine. How to integrate swarm-based medicine into practice is left to the individual physician, but even this decision will be influenced by the swarm.

  18. The Swarm Satellite Constellation Application and Research Facility (SCARF) and Swarm data products

    NASA Astrophysics Data System (ADS)

    Olsen, Nils; Friis-Christensen, Eigil; Floberghagen, Rune; Alken, Patrick; Beggan, Ciaran D.; Chulliat, Arnaud; Doornbos, Eelco; da Encarnação, João Teixeira; Hamilton, Brian; Hulot, Gauthier; van den IJssel, Jose; Kuvshinov, Alexey; Lesur, Vincent; Lühr, Hermann; Macmillan, Susan; Maus, Stefan; Noja, Max; Olsen, Poul Erik H.; Park, Jaeheung; Plank, Gernot; Püthe, Christoph; Rauberg, Jan; Ritter, Patricia; Rother, Martin; Sabaka, Terence J.; Schachtschneider, Reyko; Sirol, Olivier; Stolle, Claudia; Thébault, Erwan; Thomson, Alan W. P.; Tøffner-Clausen, Lars; Velímský, Jakub; Vigneron, Pierre; Visser, Pieter N.

    2013-11-01

    Swarm, a three-satellite constellation to study the dynamics of the Earth's magnetic field and its interactions with the Earth system, is expected to be launched in late 2013. The objective of the Swarm mission is to provide the best ever survey of the geomagnetic field and its temporal evolution, in order to gain new insights into the Earth system by improving our understanding of the Earth's interior and environment. In order to derive advanced models of the geomagnetic field (and other higher-level data products) it is necessary to take explicit advantage of the constellation aspect of Swarm. The Swarm SCARF ( S atellite C onstellation A pplication and R esearch F acility) has been established with the goal of deriving Level-2 products by combination of data from the three satellites, and of the various instruments. The present paper describes the Swarm input data products (Level-1b and auxiliary data) used by SCARF, the various processing chains of SCARF, and the Level-2 output data products determined by SCARF.

  19. Fluid Induced Earthquakes: From KTB Experiments to Natural Seismicity Swarms.

    NASA Astrophysics Data System (ADS)

    Shapiro, S. A.

    2006-12-01

    Experiments with borehole fluid injections are typical for exploration and development of hydrocarbon or geothermal reservoirs (e.g., fluid-injection experiments at Soultz, France and at Fenton-Hill, USA). Microseismicity occurring during such operations has a large potential for understanding physics of the seismogenic process as well as for obtaining detailed information about reservoirs at locations as far as several kilometers from boreholes. The phenomenon of microseismicity triggering by borehole fluid injections is related to the process of the Frenkel-Biot slow wave propagation. In the low-frequency range (hours or days of fluid injection duration) this process reduces to the pore pressure diffusion. Fluid induced seismicity typically shows several diffusion indicating features, which are directly related to the rate of spatial grow, to the geometry of clouds of micro earthquake hypocentres and to their spatial density. Several fluid injection experiments were conducted at the German Continental Deep Drilling Site (KTB) in 1994, 2000 and 2003-2005. Microseismicity occurred at different depth intervals. We analyze this microseismicity in terms of its diffusion-related features. Its relation to the 3-D distribution of the seismic reflectivity has important rock physical and tectonic implications. Starting from such diffusion-typical signatures of man-made earthquakes, we seek analogous patterns for the earthquakes in Vogtland/Bohemia at the German/Czech border region in central Europe. There is strong geophysical evidence that there seismic events are correlated to fluid-related processes in the crust. We test the hypothesis that ascending magmatic fluids trigger earthquakes by the mechanism of pore pressure diffusion. This triggering process is mainly controlled by two physical fields, the hydraulic diffusivity and the seismic criticality (i.e., critical pore pressure value leading to failure; stable locations are characterized by higher critical pressures

  20. Scaling Features of High-Latitude Geomagnetic Field Fluctuations at Swarm Altitude: Impact of IMF Orientation

    NASA Astrophysics Data System (ADS)

    De Michelis, Paola; Consolini, Giuseppe; Tozzi, Roberta; Marcucci, Maria Federica

    2017-10-01

    This paper attempts to explore the statistical scaling features of high-latitude geomagnetic field fluctuations at Swarm altitude. Data for this study are low-resolution (1 Hz) magnetic data recorded by the vector field magnetometer on board Swarm A satellite over 1 year (from 15 April 2014 to 15 April 2015). The first- and second-order structure function scaling exponents and the degree of intermittency of the fluctuations of the intensity of the horizontal component of the magnetic field at high northern latitudes have been evaluated for different interplanetary magnetic field orientations in the GSM Y-Z plane and seasons. In the case of the first-order structure function scaling exponent, a comparison between the average spatial distributions of the obtained values and the statistical convection patterns obtained using a Super Dual Auroral Radar Network dynamic model (CS10 model) has been also considered. The obtained results support the idea that the knowledge of the scaling features of the geomagnetic field fluctuations can help in the characterization of the different ionospheric turbulence regimes of the medium crossed by Swarm A satellite. This study shows that different turbulent regimes of the geomagnetic field fluctuations exist in the regions characterized by a double-cell convection pattern and in those regions near the border of the convective structures.

  1. On the capability of SWARM for estimating time-variable gravity fields and mass variations

    NASA Astrophysics Data System (ADS)

    Reubelt, Tilo; Baur, Oliver; Weigelt, Matthias; Sneeuw, Nico

    2013-04-01

    Recently, the implementation of the GRACE Follow-On mission has been approved. However, this successor of GRACE is planned to become operational in 2017 at the earliest. In order to fill the impending gap of 3-4 years between GRACE and GRACE-FO, the capability of the magnetic field mission SWARM as a gap filler for time-variable gravity field determination has to be investigated. Since the three SWARM satellites, where two of them fly on a pendulum formation, are equipped with high-quality GPS receivers and accelerometers, orbit analysis from high-low Satellite-to-Satellite Tracking (hl-SST) can be applied for geopotential recovery. As data analysis from CHAMP and GRACE has shown, the detection of annual gravity signals and gravity trends from hl-SST is possible for long-wavelength features corresponding to a Gaussian radius of 1000 km, although the accuracy of a low-low SST mission like GRACE cannot be reached. However, since SWARM is a three-satellite constellation and might provide GPS data of higher quality compared to previous missions, improved gravity field recovery can be expected. We present detailed closed-loop simulation studies for a 5 years period based on time-variable gravity caused by mass changes in the hydrosphere, cryosphere and solid Earth. Models for these variations are used to simulate the SWARM satellite orbits. We recover time-variable gravity from orbit analysis adopting the acceleration approach. Finally, we convert time-variable gravity to mass change in order to compare with the a priori model input.

  2. Particle Swarm Optimization

    NASA Technical Reports Server (NTRS)

    Venter, Gerhard; Sobieszczanski-Sobieski Jaroslaw

    2002-01-01

    The purpose of this paper is to show how the search algorithm known as particle swarm optimization performs. Here, particle swarm optimization is applied to structural design problems, but the method has a much wider range of possible applications. The paper's new contributions are improvements to the particle swarm optimization algorithm and conclusions and recommendations as to the utility of the algorithm, Results of numerical experiments for both continuous and discrete applications are presented in the paper. The results indicate that the particle swarm optimization algorithm does locate the constrained minimum design in continuous applications with very good precision, albeit at a much higher computational cost than that of a typical gradient based optimizer. However, the true potential of particle swarm optimization is primarily in applications with discrete and/or discontinuous functions and variables. Additionally, particle swarm optimization has the potential of efficient computation with very large numbers of concurrently operating processors.

  3. Modeling the complex shape evolution of sedimenting particle swarms in fractures

    NASA Astrophysics Data System (ADS)

    Mitchell, C. A.; Nitsche, L.; Pyrak-Nolte, L. J.

    2016-12-01

    The flow of micro- and nano-particles through subsurface systems can occur in several environments, such as hydraulic fracturing or enhanced oil recovery. Computer simulations were performed to advance our understanding of the complexity of subsurface particle swarm transport in fractures. Previous experiments observed that particle swarms in fractures with uniform apertures exhibit enhanced transport speeds and suppressed bifurcations for an optimal range of apertures. Numerical simulations were performed for low Reynolds number, no interfacial tension and uniform viscosity conditions with particulate swarms represented by point-particles that mutually interact through their (regularized) Stokeslet fields. A P3 M technique accelerates the summations for swarms exceeding 105 particles. Fracture wall effects were incorporated using a least-squares variant of the method of fundamental solutions, with grid mapping of the surface force and source elements within the fast-summation scheme. The numerical study was executed on the basis of dimensionless variables and parameters, in the interest of examining the fundamental behavior and relationships of particle swarms in the presence of uniform apertures. Model parameters were representative of particle swarms experiments to enable direct comparison of the results with the experimental observations. The simulations confirmed that the principal phenomena observed in the experiments can be explained within the realm of Stokes flow. The numerical investigation effectively replicated swarm evolution in a uniform fracture and captured the coalescence, torus and tail formation, and ultimate breakup of the particle swarm as it fell under gravity in a quiescent fluid. The rate of swarm evolution depended on the number of particles in a swarm. When an ideal number of particles was used, swarm transport was characterized by an enhanced velocity regime as observed in the laboratory data. Understanding the physics particle swarms in

  4. ESA Swarm Mission - Level 1b Products

    NASA Astrophysics Data System (ADS)

    Tøffner-Clausen, Lars; Floberghagen, Rune; Mecozzi, Riccardo; Menard, Yvon

    2014-05-01

    Swarm, a three-satellite constellation to study the dynamics of the Earth's magnetic field and its interactions with the Earth system, has been launched in November 2013. The objective of the Swarm mission is to provide the best ever survey of the geomagnetic field and its temporal evolution, which will bring new insights into the Earth system by improving our understanding of the Earth's interior and environment. The Level 1b Products of the Swarm mission contain time-series of the quality screened, calibrated, corrected, and fully geo-localized measurements of the magnetic field intensity, the magnetic field vector (provided in both instrument and Earth-fixed frames), the plasma density, temperature, and velocity. Additionally, quality screened and pre-calibrated measurements of the nongravitational accelerations are provided. Geo-localization is performed by 24- channel GPS receivers and by means of unique, three head Advanced Stellar Compasses for high-precision satellite attitude information. The Swarm Level 1b data will be provided in daily products separately for each of the three Swarm spacecrafts. This poster will present detailed lists of the contents of the Swarm Level 1b Products and brief descriptions of the processing algorithms used in the generation of these data.

  5. Spatially extensive uniform stress fields on Venus inferred from radial dike swarm geometries: The Aphrodite Terra example

    NASA Technical Reports Server (NTRS)

    Grosfils, Eric B.; Head, James W.

    1993-01-01

    The high resolution and near global coverage of Magellan radar images is facilitating attempts to systematically investigate the stresses that have deformed the venusian crust. Here we continue earlier efforts to utilize approximately 170 large, radially lineated structures interpreted as dike swarms to assess the orientation of the regional maximum horizontal compressive stress (MHCS) which existed in their vicinities during emplacement. Examination of swarms near the equator reveals a link to broad scale regional structures, such as Aphrodite Terra, across distances in excess of 1000 km, suggesting the existence of first order stress fields which affect areas of more than 10(exp 6) sq km in a uniform fashion. Focusing further upon the Aphrodite Terra region, the MHCS field in the surrounding lowlands inferred from radial swarms is oriented approximately normal to the slope of the highland topography. This stress configuration appears, at a simple level, to be incompatible with that expected during either upwelling or downwelling construction of the highlands. In addition, the relatively undeformed geometry of the radial structures within the highlands implies that these dike swarm features formed more recently than their highly deformed surroundings. We conclude that the differential stresses which existed during emplacement of the dike swarms within and adjacent to the Aphrodite Terra highlands are related to the gravitational relaxation of pre-existing topography.

  6. Bifurcating Particle Swarms in Smooth-Walled Fractures

    NASA Astrophysics Data System (ADS)

    Pyrak-Nolte, L. J.; Sun, H.

    2010-12-01

    Particle swarms can occur naturally or from industrial processes where small liquid drops containing thousands to millions of micron-size to colloidal-size particles are released over time from seepage or leaks into fractured rock. The behavior of these particle swarms as they fall under gravity are affected by particle interactions as well as interactions with the walls of the fractures. In this paper, we present experimental results on the effect of fractures on the cohesiveness of the swarm and the formation of bifurcation structures as they fall under gravity and interact with the fracture walls. A transparent cubic sample (100 mm x 100 mm x 100 mm) containing a synthetic fracture with uniform aperture distributions was optically imaged to quantify the effect of confinement within fractures on particle swarm formation, swarm velocity, and swarm geometry. A fracture with a uniform aperture distribution was fabricated from two polished rectangular prisms of acrylic. A series of experiments were performed to determine how swarm movement and geometry are affected as the walls of the fracture are brought closer together from 50 mm to 1 mm. During the experiments, the fracture was fully saturated with water. We created the swarms using two different particle sizes in dilute suspension (~ 1.0% by mass). The particles were 3 micron diameter fluorescent polymer beads and 25 micron diameter soda-lime glass beads. Experiments were performed using swarms that ranged in size from 5 µl to 60 µl. The swarm behavior was imaged using an optical fluorescent imaging system composed of a CCD camera illuminated by a 100 mW diode-pumped doubled YAG laser. As a swarm falls in an open-tank of water, it forms a torroidal shape that is stable as long as no ambient or background currents exist in the water tank. When a swarm is released into a fracture with an aperture less than 5 mm, the swarm forms the torroidal shape but it is distorted because of the presence of the walls. The

  7. Swarm observations of field-aligned currents associated with pulsating auroral patches

    NASA Astrophysics Data System (ADS)

    Gillies, D. M.; Knudsen, D.; Spanswick, E.; Donovan, E.; Burchill, J.; Patrick, M.

    2015-11-01

    We have performed a superposed epoch study of in situ field-aligned currents located near the edges of regions of pulsating aurora observed simultaneously using ground-based optical data from the Time History of Events and Macroscale Interactions during Substorms (THEMIS) all-sky imager (ASI) network and magnetometers on board the Swarm satellites. A total of nine traversals of Swarm over regions of pulsating aurora identified using THEMIS ASI were studied. We determined that in the cases where a clear boundary can be identified, strong downward currents are seen just poleward and equatorward of the pulsating patches. A downward current in the range of ~1-6 μA/m2 can be seen just poleward of the boundary. A weaker upward current of ~1-3 μA/m2 is observed throughout the interior of the patch. These observations indicate that currents carried by precipitating electrons within patches could close through horizontal currents and be returned at the edges, in agreement with Oguti and Hayashi (1984) and Hosokawa et al. (2010b). In addition to confirming these earlier results and adding to their statistical significance, the contribution of this study is to quantify the upward and downward current magnitudes, in some cases using two satellites traversing the same pulsating regions. Finally, we compare Swarm's two-satellite field-aligned current product to the single-satellite results and determine that the data product can be compromised in regions of pulsating aurora, a phenomenon that occurs over widespread regions and tends to persist for long periods of time. These results underscore the importance of electrical coupling between the ionosphere and magnetosphere in regions of patchy pulsating aurora.

  8. The upper surface of an Escherichia coli swarm is stationary.

    PubMed

    Zhang, Rongjing; Turner, Linda; Berg, Howard C

    2010-01-05

    When grown in a rich medium on agar, many bacteria elongate, produce more flagella, and swim in a thin film of fluid over the agar surface in swirling packs. Cells that spread in this way are said to swarm. The agar is a solid gel, with pores smaller than the bacteria, so the swarm/agar interface is fixed. Here we show, in experiments with Escherichia coli, that the swarm/air interface also is fixed. We deposited MgO smoke particles on the top surface of an E. coli swarm near its advancing edge, where cells move in a single layer, and then followed the motion of the particles by dark-field microscopy and the motion of the underlying cells by phase-contrast microscopy. Remarkably, the smoke particles remained fixed (diffusing only a few micrometers) while the swarming cells streamed past underneath. The diffusion coefficients of the smoke particles were smaller over the virgin agar ahead of the swarm than over the swarm itself. Changes between these two modes of behavior were evident within 10-20 microm of the swarm edge, indicating an increase in depth of the fluid in advance of the swarm. The only plausible way that the swarm/air interface can be fixed is that it is covered by a surfactant monolayer pinned at its edges. When a swarm is exposed to air, such a monolayer can markedly reduce water loss. When cells invade tissue, the ability to move rapidly between closely opposed fixed surfaces is a useful trait.

  9. Time-delayed autosynchronous swarm control.

    PubMed

    Biggs, James D; Bennet, Derek J; Dadzie, S Kokou

    2012-01-01

    In this paper a general Morse potential model of self-propelling particles is considered in the presence of a time-delayed term and a spring potential. It is shown that the emergent swarm behavior is dependent on the delay term and weights of the time-delayed function, which can be set to induce a stationary swarm, a rotating swarm with uniform translation, and a rotating swarm with a stationary center of mass. An analysis of the mean field equations shows that without a spring potential the motion of the center of mass is determined explicitly by a multivalued function. For a nonzero spring potential the swarm converges to a vortex formation about a stationary center of mass, except at discrete bifurcation points where the center of mass will periodically trace an ellipse. The analytical results defining the behavior of the center of mass are shown to correspond with the numerical swarm simulations.

  10. Velocity correlations in laboratory insect swarms

    NASA Astrophysics Data System (ADS)

    Ni, R.; Ouellette, N. T.

    2015-12-01

    In contrast to animal groups such as bird flocks or migratory herds that display net, directed motion, insect swarms do not possess global order. Without such order, it is difficult to define and characterize the transition to collective behavior in swarms; nevertheless, visual observation of swarms strongly suggests that swarming insects do behave collectively. It has recently been suggested that correlation rather than order is the hallmark of emergent collective behavior. Here, we report measurements of spatial velocity correlation functions in laboratory mating swarms of the non-biting midge Chironomus riparius. Although we find some correlation at short distances, our swarms are in general only weakly correlated, in contrast to what has been observed in field studies. Our results hint at the potentially important role of environmental conditions on collective behavior, and suggest that general indicators of the collective nature of swarming are still needed.

  11. June 2006 seismic swarm and dike injection event beneath the Michoacan-Guanajuato volcanic field

    NASA Astrophysics Data System (ADS)

    Cox, T. F.; Gardine, M.; West, M.

    2008-12-01

    A seismic swarm of approximately 700 events, magnitude 2.5-3.5, occurred in June of 2006 approximately 15 km from the summit of the cinder cone Paricutin, in the Michoacan-Guanajuato Volcanic Field in central Mexico. The swarm was detected and located as part of an effort to develop a catalog of regional seismicity using stations fortuitously in place as part of two concurrent IRIS/PASSCAL supported projects- the Mapping of the Rivera Subduction Zone (MARS) project run by the University of Texas at Austin and New Mexico State University, and the Colima Volcano Deep Seismic Experiment (CODEX), run by the University of Alaska Fairbanks. Over a two-week period in June 2006, relocated hypocenters clearly show a shallowing trend with time, indicative of a possible dike injection event. The rate of injection appears to be 346 m/day. Following the injection, there is a period of earthquakes, which all occurred at approximately 5 km in depth, but which migrated southwards. The waveforms of all of these events show similarities within three major groupings: from May 28 to June 1, June 2 to June 9 (which marks the end of the ascent), and from June 9 to July 2.

  12. Imparting magnetic dipole heterogeneity to internalized iron oxide nanoparticles for microorganism swarm control

    NASA Astrophysics Data System (ADS)

    Kim, Paul Seung Soo; Becker, Aaron; Ou, Yan; Julius, Anak Agung; Kim, Min Jun

    2015-03-01

    Tetrahymena pyriformis is a single cell eukaryote that can be modified to respond to magnetic fields, a response called magnetotaxis. Naturally, this microorganism cannot respond to magnetic fields, but after modification using iron oxide nanoparticles, cells are magnetized and exhibit a constant magnetic dipole strength. In experiments, a rotating field is applied to cells using a two-dimensional approximate Helmholtz coil system. Using rotating magnetic fields, we characterize discrete cells' swarm swimming which is affected by several factors. The behavior of the cells under these fields is explained in detail. After the field is removed, relatively straight swimming is observed. We also generate increased heterogeneity within a population of cells to improve controllability of a swarm, which is explored in a cell model. By exploiting this straight swimming behavior, we propose a method to control discrete cells utilizing a single global magnetic input. Successful implementation of this swarm control method would enable teams of microrobots to perform a variety of in vitro microscale tasks impossible for single microrobots, such as pushing objects or simultaneous micromanipulation of discrete entities.

  13. Filamentary field-aligned currents at the polar cap region during northward interplanetary magnetic field derived with the Swarm constellation

    PubMed Central

    Lühr, Hermann; Huang, Tao; Wing, Simon; Kervalishvili, Guram; Rauberg, Jan; Korth, Haje

    2017-01-01

    ESA’s Swarm constellation mission makes it possible for the first time to determine field-aligned currents (FACs) in the ionosphere uniquely. In particular at high latitudes, the dual-satellite approach can reliably detect some FAC structures which are missed by the traditional single-satellite technique. These FAC events occur preferentially poleward of the auroral oval and during times of northward interplanetary magnetic field (IMF) orientation. Most events appear on the nightside. They are not related to the typical FAC structures poleward of the cusp, commonly termed NBZ. Simultaneously observed precipitating particle spectrograms and auroral images from Defense Meteorological Satellite Program (DMSP) satellites are consistent with the detected FACs and indicate that they occur on closed field lines mostly adjacent to the auroral oval. We suggest that the FACs are associated with Sun-aligned filamentary auroral arcs. Here we introduce in an initial study features of the high-latitude FAC structures which have been observed during the early phase of the Swarm mission. A more systematic survey over longer times is required to fully characterize the so far undetected field aligned currents. PMID:29056833

  14. Elastic and inelastic collisions of swarms

    NASA Astrophysics Data System (ADS)

    Armbruster, Dieter; Martin, Stephan; Thatcher, Andrea

    2017-04-01

    Scattering interactions of swarms in potentials that are generated by an attraction-repulsion model are studied. In free space, swarms in this model form a well-defined steady state describing the translation of a stable formation of the particles whose shape depends on the interaction potential. Thus, the collision between a swarm and a boundary or between two swarms can be treated as (quasi)-particle scattering. Such scattering experiments result in internal excitations of the swarm or in bound states, respectively. In addition, varying a parameter linked to the relative importance of damping and potential forces drives transitions between elastic and inelastic scattering of the particles. By tracking the swarm's center of mass, a refraction rule is derived via simulations relating the incoming and outgoing directions of a swarm hitting the wall. Iterating the map derived from the refraction law allows us to predict and understand the dynamics and bifurcations of swarms in square boxes and in channels.

  15. Deriving a Core Magnetic Field Model from Swarm Satellite Data

    NASA Astrophysics Data System (ADS)

    Lesur, V.; Rother, M.; Wardinski, I.

    2014-12-01

    A model of the Earth's core magnetic field has been built using Swarm satellite mission data and observatory quasi-definitive data. The satellite data processing scheme, which was used to derive previous satellite field models (i.e. GRIMM series), has been modified to handle discrepancies between the satellite total intensity data derived from the vector fluxgate magnetometer and the absolute scalar instrument. Further, the Euler angles, i.e. the angles between the vector magnetometer and the satellite reference frame, have been recalculated on a series of 30-day windows to obtain an accurate model of the core field for 2014. Preliminary derivations of core magnetic field and SV models for 2014 present the same characteristics as during the CHAMP era. The acceleration (i.e. the field second time derivative) has shown a rapid evolution over the last few years, and is present in the current model, which confirms previous observations.

  16. Flows around bacterial swarms

    NASA Astrophysics Data System (ADS)

    Dauparas, Justas; Lauga, Eric

    2015-11-01

    Flagellated bacteria on nutrient-rich substrates can differentiate into a swarming state and move in dense swarms across surfaces. A recent experiment (HC Berg, Harvard University) measured the flow in the fluid around the swarm. A systematic chiral flow was observed in the clockwise direction (when viewed from above) ahead of a E.coli swarm with flow speeds of about 10 μm/s, about 3 times greater than the radial velocity at the edge of the swarm. The working hypothesis is that this flow is due to the flagella of cells stalled at the edge of a colony which extend their flagellar filaments outwards, moving fluid over the virgin agar. In this talk we quantitatively test his hypothesis. We first build an analytical model of the flow induced by a single flagellum in a thin film and then use the model, and its extension to multiple flagella, to compare with experimental measurements.

  17. Ethiopian Tertiary dike swarms

    NASA Technical Reports Server (NTRS)

    Mohr, P. A.

    1971-01-01

    Mapping of the Ethiopian rift and Afar margins revealed the existence of Tertiary dike swarms. The structural relations of these swarms and the fed lava pile to monoclinal warping of the margins partly reflect a style of continental margin tectonics found in other parts of the world. In Ethiopia, however, conjugate dike trends appear to be unusually strongly developed. Relation of dikes to subsequent margin faulting is ambiguous, and there are instances where the two phenomena are spatially separate and of differing trends. There is no evidence for lateral migration with time of dike injection toward the rift zone. No separate impingement of Red Sea, Gulf of Aden, and African rift system stress fields on the Ethiopian region can be demonstrated from the Tertiary dike swarms. Rather, a single, regional paleostress field existed, suggestive of a focus beneath the central Ethiopian plateau. This stress field was dominated by tension: there is no cogent evidence for shearing along the rift margins. A gentle compression along the rift floor is indicated. A peculiar sympathy of dike hade directions at given localities is evident.

  18. Geomagnetic Jerks in the Swarm Era

    NASA Astrophysics Data System (ADS)

    Brown, William; Beggan, Ciaran; Macmillan, Susan

    2016-08-01

    The timely provision of geomagnetic observations as part of the European Space Agency (ESA) Swarm mission means up-to-date analysis and modelling of the Earth's magnetic field can be conducted rapidly in a manner not possible before. Observations from each of the three Swarm constellation satellites are available within 4 days and a database of close-to-definitive ground observatory measurements is updated every 3 months. This makes it possible to study very recent variations of the core magnetic field. Here we investigate rapid, unpredictable internal field variations known as geomagnetic jerks. Given that jerks represent (currently) unpredictable changes in the core field and have been identified to have happened in 2014 since Swarm was launched, we ask what impact this might have on the future accuracy of the International Geomagnetic Reference Field (IGRF). We assess the performance of each of the IGRF-12 secular variation model candidates in light of recent jerks, given that four of the nine candidates are novel physics-based predictive models.

  19. Verification of Emergent Behaviors in Swarm-based Systems

    NASA Technical Reports Server (NTRS)

    Rouff, Christopher; Vanderbilt, Amy; Hinchey, Mike; Truszkowski, Walt; Rash, James

    2004-01-01

    The emergent properties of swarms make swarm-based missions powerful, but at the same time more difficult to design and to assure that the proper behaviors will emerge. We are currently investigating formal methods and techniques for verification and validation of swarm-based missions. The Autonomous Nano-Technology Swarm (ANTS) mission is being used as an example and case study for swarm-based missions to experiment and test current formal methods with intelligent swarms. Using the ANTS mission, we have evaluated multiple formal methods to determine their effectiveness in modeling and assuring swarm behavior. This paper introduces how intelligent swarm technology is being proposed for NASA missions, and gives the results of a comparison of several formal methods and approaches for specifying intelligent swarm-based systems and their effectiveness for predicting emergent behavior.

  20. Recent geomagnetic secular variation from Swarm and ground observatories as estimated in the CHAOS-6 geomagnetic field model

    NASA Astrophysics Data System (ADS)

    Finlay, Christopher C.; Olsen, Nils; Kotsiaros, Stavros; Gillet, Nicolas; Tøffner-Clausen, Lars

    2016-07-01

    We use more than 2 years of magnetic data from the Swarm mission, and monthly means from 160 ground observatories as available in March 2016, to update the CHAOS time-dependent geomagnetic field model. The new model, CHAOS-6, provides information on time variations of the core-generated part of the Earth's magnetic field between 1999.0 and 2016.5. We present details of the secular variation (SV) and secular acceleration (SA) from CHAOS-6 at Earth's surface and downward continued to the core surface. At Earth's surface, we find evidence for positive acceleration of the field intensity in 2015 over a broad area around longitude 90°E that is also seen at ground observatories such as Novosibirsk. At the core surface, we are able to map the SV up to at least degree 16. The radial field SA at the core surface in 2015 is found to be largest at low latitudes under the India-South-East Asia region, under the region of northern South America, and at high northern latitudes under Alaska and Siberia. Surprisingly, there is also evidence for significant SA in the central Pacific region, for example near Hawaii where radial field SA is observed on either side of a jerk in 2014. On the other hand, little SV or SA has occurred over the past 17 years in the southern polar region. Inverting for a quasi-geostrophic core flow that accounts for this SV, we obtain a prominent planetary-scale, anti-cyclonic, gyre centred on the Atlantic hemisphere. We also find oscillations of non-axisymmetric, azimuthal, jets at low latitudes, for example close to 40°W, that may be responsible for localized SA oscillations. In addition to scalar data from Ørsted, CHAMP, SAC-C and Swarm, and vector data from Ørsted, CHAMP and Swarm, CHAOS-6 benefits from the inclusion of along-track differences of scalar and vector field data from both CHAMP and the three Swarm satellites, as well as east-west differences between the lower pair of Swarm satellites, Alpha and Charlie. Moreover, ground observatory SV

  1. Parameter estimation for chaotic systems using improved bird swarm algorithm

    NASA Astrophysics Data System (ADS)

    Xu, Chuangbiao; Yang, Renhuan

    2017-12-01

    Parameter estimation of chaotic systems is an important problem in nonlinear science and has aroused increasing interest of many research fields, which can be basically reduced to a multidimensional optimization problem. In this paper, an improved boundary bird swarm algorithm is used to estimate the parameters of chaotic systems. This algorithm can combine the good global convergence and robustness of the bird swarm algorithm and the exploitation capability of improved boundary learning strategy. Experiments are conducted on the Lorenz system and the coupling motor system. Numerical simulation results reveal the effectiveness and with desirable performance of IBBSA for parameter estimation of chaotic systems.

  2. Impact of the IMF conditions on the high latitude geomagnetic field fluctuations at Swarm altitude

    NASA Astrophysics Data System (ADS)

    De Michelis, Paola; Consolini, Giuseppe; Tozzi, Roberta

    2016-04-01

    Several space-plasma media are characterized by turbulent fluctuations covering a wide range of temporal and spatial scales from the MHD domain down to the kinetic region, which substantially affect the overall dynamics of these media. In the framework of ionosphere-magnetosphere coupling, magnetic field and plasma disturbances are driven by different current systems responsible for the coupling. These disturbances manifest in the plasma parameters inhomogeneity and in the magnetic field fluctuations, which are capable of affecting the ionospheric conditions. The present work focuses on the analysis of the statistical features of high latitude magnetic field fluctuations at Swarm altitude. The multi-satellite mission, Swarm, is equipped with several instruments which observe electric and magnetic fields as well as ionospheric parameters of the near-Earth space environment. Using these data we investigate the scaling properties of the magnetic field fluctuations at ionospheric altitude and high latitudes in the Northern and Southern hemispheres according to different interplanetary magnetic field conditions and Earth's seasons. The aim of this work is to characterize the different features of ionospheric turbulence in order to better understand the nature and possible drivers of magnetic field variability and to discuss the results in the framework of Sun-Earth relationship and ionospheric polar convection. This work is supported by the Italian National Program for Antarctic Research (PNRA) Research Project 2013/AC3.08

  3. Swarm formation control utilizing elliptical surfaces and limiting functions.

    PubMed

    Barnes, Laura E; Fields, Mary Anne; Valavanis, Kimon P

    2009-12-01

    In this paper, we present a strategy for organizing swarms of unmanned vehicles into a formation by utilizing artificial potential fields that were generated from normal and sigmoid functions. These functions construct the surface on which swarm members travel, controlling the overall swarm geometry and the individual member spacing. Nonlinear limiting functions are defined to provide tighter swarm control by modifying and adjusting a set of control variables that force the swarm to behave according to set constraints, formation, and member spacing. The artificial potential functions and limiting functions are combined to control swarm formation, orientation, and swarm movement as a whole. Parameters are chosen based on desired formation and user-defined constraints. This approach is computationally efficient and scales well to different swarm sizes, to heterogeneous systems, and to both centralized and decentralized swarm models. Simulation results are presented for a swarm of 10 and 40 robots that follow circle, ellipse, and wedge formations. Experimental results are included to demonstrate the applicability of the approach on a swarm of four custom-built unmanned ground vehicles (UGVs).

  4. Observatory data and the Swarm mission

    NASA Astrophysics Data System (ADS)

    Macmillan, S.; Olsen, N.

    2013-11-01

    The ESA Swarm mission to identify and measure very accurately the different magnetic signals that arise in the Earth's core, mantle, crust, oceans, ionosphere and magnetosphere, which together form the magnetic field around the Earth, has increased interest in magnetic data collected on the surface of the Earth at observatories. The scientific use of Swarm data and Swarm-derived products is greatly enhanced by combination with observatory data and indices. As part of the Swarm Level-2 data activities plans are in place to distribute such ground-based data along with the Swarm data as auxiliary data products. We describe here the preparation of the data set of ground observatory hourly mean values, including procedures to check and select observatory data spanning the modern magnetic survey satellite era. We discuss other possible combined uses of satellite and observatory data, in particular those that may use higher cadence 1-second and 1-minute data from observatories.

  5. Experiences applying Formal Approaches in the Development of Swarm-Based Space Exploration Systems

    NASA Technical Reports Server (NTRS)

    Rouff, Christopher A.; Hinchey, Michael G.; Truszkowski, Walter F.; Rash, James L.

    2006-01-01

    NASA is researching advanced technologies for future exploration missions using intelligent swarms of robotic vehicles. One of these missions is the Autonomous Nan0 Technology Swarm (ANTS) mission that will explore the asteroid belt using 1,000 cooperative autonomous spacecraft. The emergent properties of intelligent swarms make it a potentially powerful concept, but at the same time more difficult to design and ensure that the proper behaviors will emerge. NASA is investigating formal methods and techniques for verification of such missions. The advantage of using formal methods is the ability to mathematically verify the behavior of a swarm, emergent or otherwise. Using the ANTS mission as a case study, we have evaluated multiple formal methods to determine their effectiveness in modeling and ensuring desired swarm behavior. This paper discusses the results of this evaluation and proposes an integrated formal method for ensuring correct behavior of future NASA intelligent swarms.

  6. Stability of Nonlinear Swarms on Flat and Curved Surfaces

    DTIC Science & Technology

    numerical experiments have shown that the system either converges to a rotating circular limit cycle with a fixed center of mass, or the agents clump ...Swarming is a near-universal phenomenon in nature. Many mathematical models of swarms exist , both to model natural processes and to control robotic...agents. We study a swarm of agents with spring-like at-traction and nonlinear self-propulsion. Swarms of this type have been studied numerically, but

  7. Markerless human motion tracking using hierarchical multi-swarm cooperative particle swarm optimization.

    PubMed

    Saini, Sanjay; Zakaria, Nordin; Rambli, Dayang Rohaya Awang; Sulaiman, Suziah

    2015-01-01

    The high-dimensional search space involved in markerless full-body articulated human motion tracking from multiple-views video sequences has led to a number of solutions based on metaheuristics, the most recent form of which is Particle Swarm Optimization (PSO). However, the classical PSO suffers from premature convergence and it is trapped easily into local optima, significantly affecting the tracking accuracy. To overcome these drawbacks, we have developed a method for the problem based on Hierarchical Multi-Swarm Cooperative Particle Swarm Optimization (H-MCPSO). The tracking problem is formulated as a non-linear 34-dimensional function optimization problem where the fitness function quantifies the difference between the observed image and a projection of the model configuration. Both the silhouette and edge likelihoods are used in the fitness function. Experiments using Brown and HumanEva-II dataset demonstrated that H-MCPSO performance is better than two leading alternative approaches-Annealed Particle Filter (APF) and Hierarchical Particle Swarm Optimization (HPSO). Further, the proposed tracking method is capable of automatic initialization and self-recovery from temporary tracking failures. Comprehensive experimental results are presented to support the claims.

  8. Flagellar flows around bacterial swarms

    NASA Astrophysics Data System (ADS)

    Dauparas, Justas; Lauga, Eric

    2016-08-01

    Flagellated bacteria on nutrient-rich substrates can differentiate into a swarming state and move in dense swarms across surfaces. A recent experiment measured the flow in the fluid around an Escherichia coli swarm [Wu, Hosu, and Berg, Proc. Natl. Acad. Sci. USA 108, 4147 (2011)], 10.1073/pnas.1016693108. A systematic chiral flow was observed in the clockwise direction (when viewed from above) ahead of the swarm with flow speeds of about 10 μ m /s , about 3 times greater than the radial velocity at the edge of the swarm. The working hypothesis is that this flow is due to the action of cells stalled at the edge of a colony that extend their flagellar filaments outward, moving fluid over the virgin agar. In this work we quantitatively test this hypothesis. We first build an analytical model of the flow induced by a single flagellum in a thin film and then use the model, and its extension to multiple flagella, to compare with experimental measurements. The results we obtain are in agreement with the flagellar hypothesis. The model provides further quantitative insight into the flagella orientations and their spatial distributions as well as the tangential speed profile. In particular, the model suggests that flagella are on average pointing radially out of the swarm and are not wrapped tangentially.

  9. Swarms, swarming and entanglements of fungal hyphae and of plant roots

    PubMed Central

    Barlow, Peter W.; Fisahn, Joachim

    2013-01-01

    There has been recent interest in the possibility that plant roots can show oriented collective motion, or swarming behavior. We examine the evidence supportive of root swarming and we also present new observations on this topic. Seven criteria are proposed for the definition of a swarm, whose application can help identify putative swarming behavior in plants. Examples where these criteria are fulfilled, at many levels of organization, are presented in relation to plant roots and root systems, as well as to the root-like mycelial cords (rhizomorphs) of fungi. The ideas of both an “active” swarming, directed by a signal which imposes a common vector on swarm element aggregation, and a “passive” swarming, where aggregation results from external constraint, are introduced. Active swarming is a pattern of cooperative behavior peculiar to the sporophyte generation of vascular plants and is the antithesis of the competitive behavior shown by the gametophyte generation of such plants, where passive swarming may be found. Fungal mycelial cords could serve as a model example of swarming in a multi-cellular, non-animal system. PMID:24255743

  10. Electrical conductivity of the Earth's mantle from the first Swarm magnetic field measurements

    NASA Astrophysics Data System (ADS)

    Civet, F.; Thébault, E.; Verhoeven, O.; Langlais, B.; Saturnino, D.

    2015-05-01

    We present a 1-D electrical conductivity profile of the Earth's mantle down to 2000 km derived from L1b Swarm satellite magnetic field measurements from November 2013 to September 2014. We first derive a model for the main magnetic field, correct the data for a lithospheric field model, and additionally select the data to reduce the contributions of the ionospheric field. We then model the primary and induced magnetospheric fields for periods between 2 and 256 days and perform a Bayesian inversion to obtain the probability density function for the electrical conductivity as function of depth. The conductivity increases by 3 orders of magnitude in the 400-900 km depth range. Assuming a pyrolitic mantle composition, this profile is interpreted in terms of temperature variations leading to a temperature gradient in the lower mantle that is close to adiabatic.

  11. The Fate of Colloidal Swarms in Fractures

    NASA Astrophysics Data System (ADS)

    Pyrak-Nolte, L. J.; Olander, M. K.

    2009-12-01

    In the next 10-20 years, nano- and micro-sensor engineering will advance to the stage where sensor swarms could be deployed in the subsurface to probe rock formations and the fluids contained in them. Sensor swarms are groups of nano- or micro- sensors that are maintained as a coherent group to enable either sensor-to-sensor communication and/or coherent transmission of information as a group. The ability to maintain a swarm of sensors depends on the complexity of the flow paths in the rock, on the size and shape of the sensors and on the chemical interaction among the sensors, fluids, and rock surfaces. In this study, we investigate the effect of fracture aperture and fluid currents on the formation, evolution and break-up of colloidal swarms under gravity. Transparent cubic samples (100 mm x 100 mm x 100 mm) containing synthetic fractures with uniform and non-uniform aperture distributions were used to quantify the effect of aperture on swarm formation, swarm velocity, and swarm geometry using optical imaging. A fracture with a uniform aperture distribution was fabricated from two polished rectangular prisms of acrylic. A fracture with a non-uniform aperture distribution was created with a polished rectangular acrylic prism and an acrylic replica of an induced fracture surface from a carbonate rock. A series of experiments were performed to determine how swarm movement and geometry are affected as the walls of the fracture are brought closer together from 50 mm to 1 mm. During the experiments, the fracture was fully saturated with water. We created the swarms using two different particle sizes in dilute suspension (~ 1.0% by mass) . The particles were 3 micron diameter fluorescent polymer beads and 25 micron diameter soda-lime glass beads. The swarm behavior was imaged using an optical fluorescent imaging system composed of a CCD camera illuminated by a 100 mW diode-pumped doubled YAG laser. A swam was created when approximately 0.01 g drop of the suspension was

  12. A corotation electric field model of the Earth derived from Swarm satellite magnetic field measurements

    NASA Astrophysics Data System (ADS)

    Maus, Stefan

    2017-08-01

    Rotation of the Earth in its own geomagnetic field sets up a primary corotation electric field, compensated by a secondary electric field of induced electrical charges. For the geomagnetic field measured by the Swarm constellation of satellites, a derivation of the global corotation electric field inside and outside of the corotation region is provided here, in both inertial and corotating reference frames. The Earth is assumed an electrical conductor, the lower atmosphere an insulator, followed by the corotating ionospheric E region again as a conductor. Outside of the Earth's core, the induced charge is immediately accessible from the spherical harmonic Gauss coefficients of the geomagnetic field. The charge density is positive at high northern and southern latitudes, negative at midlatitudes, and increases strongly toward the Earth's center. Small vertical electric fields of about 0.3 mV/m in the insulating atmospheric gap are caused by the corotation charges located in the ionosphere above and the Earth below. The corotation charges also flow outward into the region of closed magnetic field lines, forcing the plasmasphere to corotate. The electric field of the corotation charges further extends outside of the corotating regions, contributing radial outward electric fields of about 10 mV/m in the northern and southern polar caps. Depending on how the magnetosphere responds to these fields, the Earth may carry a net electric charge.

  13. CM5, a Pre-Swarm Comprehensive Geomagnetic Field Model Derived from Over 12 Yr of CHAMP, Orsted, SAC-C and Observatory Data

    NASA Technical Reports Server (NTRS)

    Sabaka, Terence J.; Olsen, Nils; Tyler, Robert H.; Kuvshinov, Alexey

    2014-01-01

    A comprehensive magnetic field model named CM5 has been derived from CHAMP, Ørsted and SAC-C satellite and observatory hourly-means data from 2000 August to 2013 January using the Swarm Level-2 Comprehensive Inversion (CI) algorithm. Swarm is a recently launched constellation of three satellites to map the Earth's magnetic field. The CI technique includes several interesting features such as the bias mitigation scheme known as Selective Infinite Variance Weighting (SIVW), a new treatment for attitude error in satellite vector measurements, and the inclusion of 3-D conductivity for ionospheric induction. SIVW has allowed for a much improved lithospheric field recovery over CM4 by exploiting CHAMP along-track difference data yielding resolution levels up to spherical harmonic degree 107, and has allowed for the successful extraction of the oceanic M2 tidal magnetic field from quiet, nightside data. The 3-D induction now captures anomalous Solar-quiet features in coastal observatory daily records. CM5 provides a satisfactory, continuous description of the major magnetic fields in the near-Earth region over this time span, and its lithospheric, ionospheric and oceanic M2 tidal constituents may be used as validation tools for future Swarm Level-2 products coming from the CI algorithm and other dedicated product algorithms.

  14. Swarm Utilisation Analysis: LEO satellite observations for the ESA's SSA Space Weather network

    NASA Astrophysics Data System (ADS)

    Kervalishvili, Guram; Stolle, Claudia; Rauberg, Jan; Olsen, Nils; Vennerstrøm, Susanne; Gullikstad Johnsen, Magnar; Hall, Chris

    2017-04-01

    ESA's (European Space Agency) constellation mission Swarm was successfully launched on 22 November 2013. The three satellites achieved their final constellation on 17 April 2014 and since then Swarm-A and Swarm-C orbiting the Earth at about 470 km (flying side-by-side) and Swarm-B at about 520 km altitude. Each of Swarm satellite carries instruments with high precision to measure magnetic and electric fields, neutral and plasma densities, and TEC (Total Electron Content) for which a dual frequency GPS receiver is used. SUA (Swarm Utilisation Analysis) is a project of the ESA's SSA (Space Situational Awareness) SWE (Space Weather) program. Within this framework GFZ (German Research Centre for Geosciences, Potsdam, Germany) and DTU (National Space Institute, Kongens Lyngby, Denmark) have developed two new Swarm products ROT (Rate Of change of TEC) and PEJ (Location and intensity level of Polar Electrojets), respectively. ROT is derived as the first time derivative from the Swarm measurements of TEC at 1 Hz sampling. ROT is highly relevant for users in navigation and communications: strong plasma gradients cause GPS signal degradation or even loss of GPS signal. Also, ROT is a relevant space weather asset irrespective of geomagnetic activity, e.g., high amplitude values of ROT occur during all geomagnetic conditions. PEJ is derived from the Swarm measurements of the magnetic field strength at 1 Hz sampling. PEJ has a high-level importance for power grid companies since the polar electrojet is a major cause for ground-induced currents. ROT and PEJ together with five existing Swarm products TEC, electron density, IBI (Ionospheric Bubble Index), FAC (Field-Aligned Current), and vector magnetic field build the SUA service prototype. This prototype will be integrated into ESA's SSA Space Weather network as a federated service and will be available soon from ESA's SSA SWE Ionospheric Weather and Geomagnetic Conditions Expert Service Centres (ESCs).

  15. Swarm Intelligence in Text Document Clustering

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Cui, Xiaohui; Potok, Thomas E

    2008-01-01

    Social animals or insects in nature often exhibit a form of emergent collective behavior. The research field that attempts to design algorithms or distributed problem-solving devices inspired by the collective behavior of social insect colonies is called Swarm Intelligence. Compared to the traditional algorithms, the swarm algorithms are usually flexible, robust, decentralized and self-organized. These characters make the swarm algorithms suitable for solving complex problems, such as document collection clustering. The major challenge of today's information society is being overwhelmed with information on any topic they are searching for. Fast and high-quality document clustering algorithms play an important role inmore » helping users to effectively navigate, summarize, and organize the overwhelmed information. In this chapter, we introduce three nature inspired swarm intelligence clustering approaches for document clustering analysis. These clustering algorithms use stochastic and heuristic principles discovered from observing bird flocks, fish schools and ant food forage.« less

  16. Transport of Particle Swarms Through Fractures

    NASA Astrophysics Data System (ADS)

    Boomsma, E.; Pyrak-Nolte, L. J.

    2011-12-01

    The transport of engineered micro- and nano-scale particles through fractured rock is often assumed to occur as dispersions or emulsions. Another potential transport mechanism is the release of particle swarms from natural or industrial processes where small liquid drops, containing thousands to millions of colloidal-size particles, are released over time from seepage or leaks. Swarms have higher velocities than any individual colloid because the interactions among the particles maintain the cohesiveness of the swarm as it falls under gravity. Thus particle swarms give rise to the possibility that engineered particles may be transported farther and faster in fractures than predicted by traditional dispersion models. In this study, the effect of fractures on colloidal swarm cohesiveness and evolution was studied as a swarm falls under gravity and interacts with fracture walls. Transparent acrylic was used to fabricate synthetic fracture samples with either (1) a uniform aperture or (2) a converging aperture followed by a uniform aperture (funnel-shaped). The samples consisted of two blocks that measured 100 x 100 x 50 mm. The separation between these blocks determined the aperture (0.5 mm to 50 mm). During experiments, a fracture was fully submerged in water and swarms were released into it. The swarms consisted of dilute suspensions of either 25 micron soda-lime glass beads (2% by mass) or 3 micron polystyrene fluorescent beads (1% by mass) with an initial volume of 5μL. The swarms were illuminated with a green (525 nm) LED array and imaged optically with a CCD camera. In the uniform aperture fracture, the speed of the swarm prior to bifurcation increased with aperture up to a maximum at a fracture width of approximately 10 mm. For apertures greater than ~15 mm, the velocity was essentially constant with fracture width (but less than at 10 mm). This peak suggests that two competing mechanisms affect swarm velocity in fractures. The wall provides both drag, which

  17. CM5, a pre-Swarm comprehensive geomagnetic field model derived from over 12 yr of CHAMP, Ørsted, SAC-C and observatory data

    NASA Astrophysics Data System (ADS)

    Sabaka, Terence J.; Olsen, Nils; Tyler, Robert H.; Kuvshinov, Alexey

    2015-03-01

    A comprehensive magnetic field model named CM5 has been derived from CHAMP, Ørsted and SAC-C satellite and observatory hourly-means data from 2000 August to 2013 January using the Swarm Level-2 Comprehensive Inversion (CI) algorithm. Swarm is a recently launched constellation of three satellites to map the Earth's magnetic field. The CI technique includes several interesting features such as the bias mitigation scheme known as Selective Infinite Variance Weighting (SIVW), a new treatment for attitude error in satellite vector measurements, and the inclusion of 3-D conductivity for ionospheric induction. SIVW has allowed for a much improved lithospheric field recovery over CM4 by exploiting CHAMP along-track difference data yielding resolution levels up to spherical harmonic degree 107, and has allowed for the successful extraction of the oceanic M2 tidal magnetic field from quiet, nightside data. The 3-D induction now captures anomalous Solar-quiet features in coastal observatory daily records. CM5 provides a satisfactory, continuous description of the major magnetic fields in the near-Earth region over this time span, and its lithospheric, ionospheric and oceanic M2 tidal constituents may be used as validation tools for future Swarm Level-2 products coming from the CI algorithm and other dedicated product algorithms.

  18. Sambot II: A self-assembly modular swarm robot

    NASA Astrophysics Data System (ADS)

    Zhang, Yuchao; Wei, Hongxing; Yang, Bo; Jiang, Cancan

    2018-04-01

    The new generation of self-assembly modular swarm robot Sambot II, based on the original generation of self-assembly modular swarm robot Sambot, adopting laser and camera module for information collecting, is introduced in this manuscript. The visual control algorithm of Sambot II is detailed and feasibility of the algorithm is verified by the laser and camera experiments. At the end of this manuscript, autonomous docking experiments of two Sambot II robots are presented. The results of experiments are showed and analyzed to verify the feasibility of whole scheme of Sambot II.

  19. Predator confusion is sufficient to evolve swarming behaviour

    PubMed Central

    Olson, Randal S.; Hintze, Arend; Dyer, Fred C.; Knoester, David B.; Adami, Christoph

    2013-01-01

    Swarming behaviours in animals have been extensively studied owing to their implications for the evolution of cooperation, social cognition and predator–prey dynamics. An important goal of these studies is discerning which evolutionary pressures favour the formation of swarms. One hypothesis is that swarms arise because the presence of multiple moving prey in swarms causes confusion for attacking predators, but it remains unclear how important this selective force is. Using an evolutionary model of a predator–prey system, we show that predator confusion provides a sufficient selection pressure to evolve swarming behaviour in prey. Furthermore, we demonstrate that the evolutionary effect of predator confusion on prey could in turn exert pressure on the structure of the predator's visual field, favouring the frontally oriented, high-resolution visual systems commonly observed in predators that feed on swarming animals. Finally, we provide evidence that when prey evolve swarming in response to predator confusion, there is a change in the shape of the functional response curve describing the predator's consumption rate as prey density increases. Thus, we show that a relatively simple perceptual constraint—predator confusion—could have pervasive evolutionary effects on prey behaviour, predator sensory mechanisms and the ecological interactions between predators and prey. PMID:23740485

  20. Predator confusion is sufficient to evolve swarming behaviour.

    PubMed

    Olson, Randal S; Hintze, Arend; Dyer, Fred C; Knoester, David B; Adami, Christoph

    2013-08-06

    Swarming behaviours in animals have been extensively studied owing to their implications for the evolution of cooperation, social cognition and predator-prey dynamics. An important goal of these studies is discerning which evolutionary pressures favour the formation of swarms. One hypothesis is that swarms arise because the presence of multiple moving prey in swarms causes confusion for attacking predators, but it remains unclear how important this selective force is. Using an evolutionary model of a predator-prey system, we show that predator confusion provides a sufficient selection pressure to evolve swarming behaviour in prey. Furthermore, we demonstrate that the evolutionary effect of predator confusion on prey could in turn exert pressure on the structure of the predator's visual field, favouring the frontally oriented, high-resolution visual systems commonly observed in predators that feed on swarming animals. Finally, we provide evidence that when prey evolve swarming in response to predator confusion, there is a change in the shape of the functional response curve describing the predator's consumption rate as prey density increases. Thus, we show that a relatively simple perceptual constraint--predator confusion--could have pervasive evolutionary effects on prey behaviour, predator sensory mechanisms and the ecological interactions between predators and prey.

  1. Swarm observation of field-aligned current and electric field in multiple arc systems

    NASA Astrophysics Data System (ADS)

    Wu, J.; Knudsen, D. J.; Gillies, M.; Donovan, E.; Burchill, J. K.

    2017-12-01

    It is often thought that auroral arcs are a direct consequence of upward field-aligned currents. In fact, the relation between currents and brightness is more complicated. Multiple auroral arc systems provide and opportunity to study this relation in detail. In this study, we have identified two types of FAC configurations in multiple parallel arc systems using ground-based optical data from the THEMIS all-sky imagers (ASIs), magnetometers and electric field instruments onboard the Swarm satellites during the period from December 2013 to March 2015. In type 1 events, each arc is an intensification within a broad, unipolar current sheet and downward currents only exist outside the upward current sheet. These types of events are termed "unipolar FAC" events. In type 2 events, multiple arc systems represent a collection of multiple up/down current pairs, which are termed as "multipolar FAC" events. Comparisons of these two types of FAC events are presented with 17 "unipolar FAC" events and 12 "multipolar FAC" events. The results show that "unipolar FAC" and "multipolar FAC" events have systematic differences in terms of MLT, arc width and separation, and dependence on substorm onset time. For "unipolar FAC" events, significant electric field enhancements are shown on the edges of the broad upward current sheet. Electric field fluctuations inside the multiple arc system can be large or small. For "multipolar FAC" events, a strong correlation between magnetic and electric field indicate uniform conductance within each upward current sheet. The electrodynamical structures of multiple arc systems presented in this paper represents a step toward understanding arc generation.

  2. An immune-inspired swarm aggregation algorithm for self-healing swarm robotic systems.

    PubMed

    Timmis, J; Ismail, A R; Bjerknes, J D; Winfield, A F T

    2016-08-01

    Swarm robotics is concerned with the decentralised coordination of multiple robots having only limited communication and interaction abilities. Although fault tolerance and robustness to individual robot failures have often been used to justify the use of swarm robotic systems, recent studies have shown that swarm robotic systems are susceptible to certain types of failure. In this paper we propose an approach to self-healing swarm robotic systems and take inspiration from the process of granuloma formation, a process of containment and repair found in the immune system. We use a case study of a swarm performing team work where previous works have demonstrated that partially failed robots have the most detrimental effect on overall swarm behaviour. We have developed an immune inspired approach that permits the recovery from certain failure modes during operation of the swarm, overcoming issues that effect swarm behaviour associated with partially failed robots. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  3. Guidance and control of swarms of spacecraft

    NASA Astrophysics Data System (ADS)

    Morgan, Daniel James

    control uses a finite horizon to apply the most up-to-date control sequence while simultaneously calculating a new assignment and trajectory based on updated state information. Using a finite horizon allows collisions to only be considered between spacecraft that are near each other at the current time. This relaxes the all-to-all communication assumption so that only neighboring agents need to communicate. Experimental validation is done using the formation flying testbed. The swarm-reconfiguration algorithms are tested using multiple quadrotors. Experiments have been performed using sequential convex programming for offline trajectory planning, model predictive control and sequential convex programming for real-time trajectory generation, and the variable-swarm, distributed auction algorithm for optimal assignment. These experiments show that the swarm-reconfiguration algorithms can be implemented in real time using actual hardware. In general, this dissertation presents guidance and control algorithms that maintain and reconfigure swarms of spacecraft while maintaining the shape of the swarm, preventing collisions between the spacecraft, and minimizing the amount of propellant used.

  4. Swarm- Validation of Star Tracker and Accelerometer Data

    NASA Astrophysics Data System (ADS)

    Schack, Peter; Schlicht, Anja; Pail, Roland; Gruber, Thomas

    2016-08-01

    The ESA Swarm mission is designed to advance studies in the field of magnetosphere, thermosphere and gravity field. To be fortunate on this task precise knowledge of the orientation of the Swarm satellites is required together with knowledge about external forces acting on the satellites. The key sensors providing this information are the star trackers and the accelerometers. Based on star tracker studies conducted by the Denmark Technical University (DTU), we found interesting patterns in the interboresight angles on all three satellites, which are partly induced by temperature alterations. Additionally, structures of horizontal stripes seem to be caused by the unique distribution of observed stars on the charge-coupled device of the star trackers. Our accelerometer analyses focus on spikes and pulses in the observations. Those short term events on Swarm might originate from electrical processes introduced by sunlight illuminating the nadir foil. Comparisons to GOCE and GRACE are included.

  5. Benchmark calculations of nonconservative charged-particle swarms in dc electric and magnetic fields crossed at arbitrary angles.

    PubMed

    Dujko, S; White, R D; Petrović, Z Lj; Robson, R E

    2010-04-01

    A multiterm solution of the Boltzmann equation has been developed and used to calculate transport coefficients of charged-particle swarms in gases under the influence of electric and magnetic fields crossed at arbitrary angles when nonconservative collisions are present. The hierarchy resulting from a spherical-harmonic decomposition of the Boltzmann equation in the hydrodynamic regime is solved numerically by representing the speed dependence of the phase-space distribution function in terms of an expansion in Sonine polynomials about a Maxwellian velocity distribution at an internally determined temperature. Results are given for electron swarms in certain collisional models for ionization and attachment over a range of angles between the fields and field strengths. The implicit and explicit effects of ionization and attachment on the electron-transport coefficients are considered using physical arguments. It is found that the difference between the two sets of transport coefficients, bulk and flux, resulting from the explicit effects of nonconservative collisions, can be controlled either by the variation in the magnetic field strengths or by the angles between the fields. In addition, it is shown that the phenomena of ionization cooling and/or attachment cooling/heating previously reported for dc electric fields carry over directly to the crossed electric and magnetic fields. The results of the Boltzmann equation analysis are compared with those obtained by a Monte Carlo simulation technique. The comparison confirms the theoretical basis and numerical integrity of the moment method for solving the Boltzmann equation and gives a set of well-established data that can be used to test future codes and plasma models.

  6. Collective motion patterns of swarms with delay coupling: Theory and experiment.

    PubMed

    Szwaykowska, Klementyna; Schwartz, Ira B; Mier-Y-Teran Romero, Luis; Heckman, Christoffer R; Mox, Dan; Hsieh, M Ani

    2016-03-01

    The formation of coherent patterns in swarms of interacting self-propelled autonomous agents is a subject of great interest in a wide range of application areas, ranging from engineering and physics to biology. In this paper, we model and experimentally realize a mixed-reality large-scale swarm of delay-coupled agents. The coupling term is modeled as a delayed communication relay of position. Our analyses, assuming agents communicating over an Erdös-Renyi network, demonstrate the existence of stable coherent patterns that can be achieved only with delay coupling and that are robust to decreasing network connectivity and heterogeneity in agent dynamics. We also show how the bifurcation structure for emergence of different patterns changes with heterogeneity in agent acceleration capabilities and limited connectivity in the network as a function of coupling strength and delay. Our results are verified through simulation as well as preliminary experimental results of delay-induced pattern formation in a mixed-reality swarm.

  7. Collective motion patterns of swarms with delay coupling: Theory and experiment

    NASA Astrophysics Data System (ADS)

    Szwaykowska, Klementyna; Schwartz, Ira B.; Mier-y-Teran Romero, Luis; Heckman, Christoffer R.; Mox, Dan; Hsieh, M. Ani

    2016-03-01

    The formation of coherent patterns in swarms of interacting self-propelled autonomous agents is a subject of great interest in a wide range of application areas, ranging from engineering and physics to biology. In this paper, we model and experimentally realize a mixed-reality large-scale swarm of delay-coupled agents. The coupling term is modeled as a delayed communication relay of position. Our analyses, assuming agents communicating over an Erdös-Renyi network, demonstrate the existence of stable coherent patterns that can be achieved only with delay coupling and that are robust to decreasing network connectivity and heterogeneity in agent dynamics. We also show how the bifurcation structure for emergence of different patterns changes with heterogeneity in agent acceleration capabilities and limited connectivity in the network as a function of coupling strength and delay. Our results are verified through simulation as well as preliminary experimental results of delay-induced pattern formation in a mixed-reality swarm.

  8. Particle Swarm Transport across the Fracture-Matrix Interface

    NASA Astrophysics Data System (ADS)

    Malenda, M. G.; Pyrak-Nolte, L. J.

    2016-12-01

    A fundamental understanding of particle transport is required for many diverse applications such as effective proppant injection, for deployment of subsurface imaging micro-particles, and for removal of particulate contaminants from subsurface water systems. One method of particulate transport is the use of particle swarms that act as coherent entities. Previous work found that particle swarms travel farther and faster in single fractures than individual particles when compared to dispersions and emulsions. In this study, gravity-driven experiments were performed to characterize swarm transport across the fracture-matrix interface. Synthetic porous media with a horizontal fracture were created from layers of square-packed 3D printed (PMMA) spherical grains (12 mm diameter). The minimum fracture aperture ranged from 0 - 10 mm. Swarms (5 and 25 µL) were composed of 3.2 micron diameter fluorescent polystryene beads (1-2% by mass). Swarms were released into a fractured porous medium that was submerged in water and was illuminated with a green (528 nm) LED array. Descending swarms were imaged with a CCD camera (2 fps). Whether an intact swarm was transported across a fracture depended on the volume of the swarm, the aperture of the fracture, and the alignment of pores on the two fracture walls. Large aperture fractures caused significant deceleration of a swarm because the swarm was free to expand laterally in the fracture. Swarms tended to remain intact when the pores on the two fracture walls were vertically aligned and traveled in the lower porous medium with speeds that were 30%-50% of their original speed in the upper matrix. When the pores on opposing walls were no longer aligned, swarms were observed to bifurcate around the grain into two smaller slower-moving swarms. Understanding the physics of particle swarms in fractured porous media has important implications for enhancing target particulate injection into the subsurface as well as for contaminant

  9. Field-aligned current and auroral Hall current characteristics derived from the Swarm constellation

    NASA Astrophysics Data System (ADS)

    Huang, Tao; Wang, Hui; Hermann, Luehr

    2017-04-01

    On the basis of field-aligned currents (FACs) and Hall currents derived from high-resolution magnetic field data of the Swarm constellation the average characteristics of these two current systems in the auroral regions are comprehensively investigated by statistical methods. This is the first study considering both current types simultaneously and for both hemispheres. The FAC distribution, derived from the Swarm dual-spacecraft approach, reveals the well-known features of Region 1 (R1) and Region 2 (R2) FACs. At high latitudes, Region 0 (R0) FACs appear on the dayside. Their direction depends on the orientation of the interplanetary magnetic field (IMF) By component. Of particular interest is the distribution of auroral Hall currents. The most prominent auroral electrojets are found to be closely controlled by the solar wind input. But there is no dependence on the IMF By orientation. The eastward electrojet is about twice as strong in summer as in winter. Conversely, the westward electrojet shows less dependence on season. Part of the electrojet current is closed over the polar cap. Here the seasonal variation of conductivity mainly controls the current density. There is a clear channeling of return currents over the polar cap. Depending on IMF By orientation most of the current is flowing either on the dawn or dusk side. The direction of Hall currents in the noon sector depends directly on the orientation of the IMF By. This is true for both signs of the IMF Bz component. But largest differences between summer and winter seasons are found for northward IMF Bz. Around the midnight sector the westward substorm electrojet is dominating. As expected, it is highly dependent on magnetic activity, but shows only little response to the IMF By polarity.

  10. Self Organized Sorting in Swarms

    NASA Astrophysics Data System (ADS)

    Copenhagen, Katherine; Quint, David; Gopinathan, Ajay

    2014-03-01

    Swarming behavior extends across multiple length scales in biology ranging from bacteria to whales. Natural swarms are affected by erratic, or dissenting behavior by individuals within the swarm who may display different types of behaviors than the rest of the swarm. This research investigates the introduction of heterogenous behavior amongst individuals within a swarm and their impact on swarm formation and robustness. We model swarms with a finite number of agents utilizing a velocity alignment interaction and a Lennard-Jones potential, which provides both cohesive and repulsive interactions between neighboring agents. Depending on the parameters governing the swarming interactions and the level of heterogeneity in behavior introduced, we found a variety of collective behavior including sharp transitions from swarming to non-swarming regimes and self organized sorting of individuals based on their types of behavior. Our research sheds light on the varied responses of swarms to internal dissent and suggests optimal strategies to tolerate errant individuals.

  11. Analysis of image thresholding segmentation algorithms based on swarm intelligence

    NASA Astrophysics Data System (ADS)

    Zhang, Yi; Lu, Kai; Gao, Yinghui; Yang, Bo

    2013-03-01

    Swarm intelligence-based image thresholding segmentation algorithms are playing an important role in the research field of image segmentation. In this paper, we briefly introduce the theories of four existing image segmentation algorithms based on swarm intelligence including fish swarm algorithm, artificial bee colony, bacteria foraging algorithm and particle swarm optimization. Then some image benchmarks are tested in order to show the differences of the segmentation accuracy, time consumption, convergence and robustness for Salt & Pepper noise and Gaussian noise of these four algorithms. Through these comparisons, this paper gives qualitative analyses for the performance variance of the four algorithms. The conclusions in this paper would give a significant guide for the actual image segmentation.

  12. New evidence of mating swarms of the malaria vector, Anopheles arabiensis in Tanzania

    PubMed Central

    Kaindoa, Emmanuel W.; Ngowo, Halfan S.; Limwagu, Alex; Mkandawile, Gustav; Kihonda, Japhet; Masalu, John Paliga; Bwanary, Hamis; Diabate, Abdoulaye; Okumu, Fredros O.

    2017-01-01

    Background: Malaria mosquitoes form mating swarms around sunset, often at the same locations for months or years. Unfortunately, studies of Anopheles swarms are rare in East Africa, the last recorded field observations in Tanzania having been in 1983. Methods: Mosquito swarms were surveyed by trained volunteers between August-2016 and June-2017 in Ulanga district, Tanzania. Identified Anopheles swarms were sampled using sweep nets, and collected mosquitoes killed by refrigeration then identified by sex and taxa. Sub-samples were further identified by PCR, and spermatheca of females examined for mating status. Mosquito ages were estimated by observing female ovarian tracheoles and rotation of male genitalia. GPS locations, types of swarm markers, start/end times of swarming, heights above ground, mosquito counts/swarm, and copulation events were recorded. Results: A total of 216 Anopheles swarms were identified, characterized and mapped, from which 7,142 Anopheles gambiae s.l and 13 Anopheles funestus were sampled. The An. gambiae s.l were 99.6% males and 0.4% females, while the An. funestus were all males. Of all An. gambiae s.l analyzed by PCR, 86.7% were An. arabiensis, while 13.3% returned non-amplified DNA. Mean height (±SD) of swarms was 2.74±0.64m, and median duration was 20 (IQR; 15-25) minutes. Confirmed swarm markers included rice fields (25.5%), burned grounds (17.2%), banana trees (13%), brick piles (8.8%), garbage heaps (7.9%) and ant-hills (7.4%). Visual estimates of swarm sizes by the volunteers was strongly correlated to actual sizes by sweep nets (R=0.94; P=<0.001). All females examined were nulliparous and 95.6% [N=6787] of males had rotated genitalia, indicating sexual maturity. Conclusions: This is the first report of Anopheles swarms in Tanzania in more than three decades. The study demonstrates that the swarms can be identified and characterized by trained community-based volunteers, and highlights potential new interventions, for example

  13. Swarm intelligence in bioinformatics: methods and implementations for discovering patterns of multiple sequences.

    PubMed

    Cui, Zhihua; Zhang, Yi

    2014-02-01

    As a promising and innovative research field, bioinformatics has attracted increasing attention recently. Beneath the enormous number of open problems in this field, one fundamental issue is about the accurate and efficient computational methodology that can deal with tremendous amounts of data. In this paper, we survey some applications of swarm intelligence to discover patterns of multiple sequences. To provide a deep insight, ant colony optimization, particle swarm optimization, artificial bee colony and artificial fish swarm algorithm are selected, and their applications to multiple sequence alignment and motif detecting problem are discussed.

  14. Precise science orbits for the Swarm satellite constellation

    NASA Astrophysics Data System (ADS)

    van den IJssel, Jose; Encarnação, João; Doornbos, Eelco; Visser, Pieter

    2015-09-01

    The European Space Agency (ESA) Swarm mission was launched on 22 November 2013 to study the dynamics of the Earth's magnetic field and its interaction with the Earth system. The mission consists of three identical satellites, flying in carefully selected near polar orbits. Two satellites fly almost side-by-side at an initial altitude of about 480 km, and will descend due to drag to around 300 km during the mission lifetime. The third satellite was placed in a higher orbit of about 530 km altitude, and therefore descends much more slowly. To geolocate the Swarm observations, each satellite is equipped with an 8-channel, dual-frequency GPS receiver for Precise Orbit Determination (POD). Onboard laser retroreflectors provide the opportunity to validate the orbits computed from the GPS observations using Satellite Laser Ranging (SLR) data. Precise Science Orbits (PSOs) for the Swarm satellites are computed by the Faculty of Aerospace Engineering at Delft University of Technology in the framework of the Swarm Satellite Constellation Application and Research Facility (SCARF). The PSO product consists of both a reduced-dynamic and a kinematic orbit solution. After a short description of the Swarm GPS data characteristics, the adopted POD strategy for both orbit types is explained and first PSO results from more than one year of Swarm GPS data are presented. Independent SLR validation shows that the reduced-dynamic Swarm PSOs have an accuracy of better than 2 cm, while the kinematic orbits have a slightly reduced accuracy of about 4-5 cm. Orbit comparisons indicate that the consistency between the reduced-dynamic and kinematic Swarm PSO for most parts of the Earth is at the 4-5 cm level. Close to the geomagnetic poles and along the geomagnetic equator, however, the kinematic orbits show larger errors, which are probably due to ionospheric scintillations that affect the Swarm GPS receivers over these areas.

  15. Swarms: Optimum aggregations of spacecraft

    NASA Technical Reports Server (NTRS)

    Mayer, H. L.

    1980-01-01

    Swarms are aggregations of spacecraft or elements of a space system which are cooperative in function, but physically isolated or only loosely connected. For some missions the swarm configuration may be optimum compared to a group of completely independent spacecraft or a complex rigidly integrated spacecraft or space platform. General features of swarms are induced by considering an ensemble of 26 swarms, examples ranging from Earth centered swarms for commercial application to swarms for exploring minor planets. A concept for a low altitude swarm as a substitute for a space platform is proposed and a preliminary design studied. The salient design feature is the web of tethers holding the 30 km swarm in a rigid two dimensional array in the orbital plane. A mathematical discussion and tutorial in tether technology and in some aspects of the distribution of services (mass, energy, and information to swarm elements) are included.

  16. A two-step along-track spectral analysis for estimating the magnetic signals of magnetospheric ring current from Swarm data

    NASA Astrophysics Data System (ADS)

    Martinec, Zdeněk; Velímský, Jakub; Haagmans, Roger; Šachl, Libor

    2018-02-01

    This study deals with the analysis of Swarm vector magnetic field measurements in order to estimate the magnetic field of magnetospheric ring current. For a single Swarm satellite, the magnetic measurements are processed by along-track spectral analysis on a track-by-track basis. The main and lithospheric magnetic fields are modelled by the CHAOS-6 field model and subtracted from the along-track Swarm magnetic data. The mid-latitude residual signal is then spectrally analysed and extrapolated to the polar regions. The resulting model of the magnetosphere (model MME) is compared to the existing Swarm Level 2 magnetospheric field model (MMA_SHA_2C). The differences of up to 10 nT are found on the nightsides Swarm data from 2014 April 8 to May 10, which are due to different processing schemes used to construct the two magnetospheric magnetic field models. The forward-simulated magnetospheric magnetic field generated by the external part of model MME then demonstrates the consistency of the separation of the Swarm along-track signal into the external and internal parts by the two-step along-track spectral analysis.

  17. Particle Swarm Transport through Immiscible Fluid Layers in a Fracture

    NASA Astrophysics Data System (ADS)

    Teasdale, N. D.; Boomsma, E.; Pyrak-Nolte, L. J.

    2011-12-01

    Immiscible fluids occur either naturally (e.g. oil & water) or from anthropogenic processes (e.g. liquid CO2 & water) in the subsurface and complicate the transport of natural or engineered micro- or nano-scale particles. In this study, we examined the effect of immiscible fluids on the formation and evolution of particle swarms in a fracture. A particle swarm is a collection of colloidal-size particles in a dilute suspension that exhibits cohesive behavior. Swarms fall under gravity with a velocity that is greater than the settling velocity of a single particle. Thus a particle swarm of colloidal contaminants can potentially travel farther and faster in a fracture than expected for a dispersion or emulsion of colloidal particles. We investigated the formation, evolution, and break-up of colloidal swarms under gravity in a uniform aperture fracture as hydrophobic/hydrophyllic particle swarms move across an oil-water interface. A uniform aperture fracture was fabricated from two transparent acrylic rectangular prisms (100 mm x 50 mm x 100 mm) that are separated by 1, 2.5, 5, 10 or 50 mm. The fracture was placed, vertically, inside a glass tank containing a layer of pure silicone oil (polydimethylsiloxane) on distilled water. Along the length of the fracture, 30 mm was filled with oil and 70 mm with water. Experiments were conducted using silicone oils with viscosities of 5, 10, 100, or 1000 cSt. Particle swarms (5 μl) were comprised of a 1% concentration (by mass) of 25 micron glass beads (hydrophilic) suspended in a water drop, or a 1% concentration (by mass) of 3 micron polystyrene fluorescent beads (hydrophobic) suspended in a water drop. The swarm behavior was imaged using an optical fluorescent imaging system composed of a CCD camera and by green (525 nm) LED arrays for illumination. Swarms were spherical and remained coherent as they fell through the oil because of the immiscibility of oil and water. However, as a swarm approached the oil-water interface, it

  18. Giant radiating dyke swarms on Earth and Venus

    NASA Technical Reports Server (NTRS)

    Ernst, Richard E.; Head, James W.; Parfitt, Elisabeth; Wilson, Lionel; Grosfils, Eric

    1993-01-01

    On Earth, giant radiating dyke swarms are usually preserved as fan-shaped fragments which have been dismembered from their original configuration by subsequent plate tectonic rifting events. Analysis of the largest fragments and consideration of their original configuration has led to the idea that many swarms are plume related, and that dyke swarms radiate away from plume centers. Magellan radar data reveal abundant intact giant radiating swarms on Venus which are similar in scale and pattern to those on Earth. The absence of intense weathering and plate tectonic processes on Venus accounts for the preservation of the primary radiating patterns. It is characteristic of both Earth and Venus that giant radiating dikes are emplaced laterally for distances of at least 2000 km away from plume centers. At distances beyond the influence of the plume on both Earth and Venus, the radiating dyke pattern is often swept into a linear pattern aligned with the regional stress field. There is tremendous potential synergism between the characterization and analysis of terrestrial dyke swarms (where significant erosion has revealed their structure and emplacement directions at depth) and the giant swarms of Venus (where the complete circumferential structure is preserved, and the surface fracture systems above near surface dikes and the nature of the central source regions are revealed). In this study, we report on the characteristics of radial dyke swarms on Earth and Venus and draw some preliminary comparisons from the two perspectives. In summary, on both planets there is evidence for plume-related magmatic centers associated with vertical and lateral injection of magma over considerable distances (up to at least 2000 km). The abundance of very broadly radiating swarms on Venus supports the notion that the swarms on Earth were radiating over broad sectors at the time of intrusion but were dissected by later events. The Venus data show that a swarm can change from radiating

  19. Coherent Pattern Prediction in Swarms of Delay-Coupled Agents

    NASA Astrophysics Data System (ADS)

    Mier-Y-Teran-Romero, Luis; Forgoston, Eric; Scwartz, Ira

    2013-03-01

    We consider a general swarm model of self-propelling particles interacting through a pairwise potential in the presence of a fixed communication time delay. Previous work has shown that swarms with communication time delays and noise may display pattern transitions that depend on the size of the coupling amplitude. We extend these results by completely unfolding the bifurcation structure of the mean field approximation. Our analysis reveals a direct correspondence between the different dynamical behaviors found in different regions of the coupling-time delay plane with the different classes of simulated coherent swarm patterns. We derive the spatio-temporal scales of the swarm structures, and also demonstrate how the complicated interplay of coupling strength, time delay, noise intensity, and choice of initial conditions can affect the swarm. In addition, when adding noise to the system, we find that for sufficiently large values of the coupling strength and/or the time delay, there is a noise intensity threshold that forces a transition of the swarm from a misaligned state into an aligned state. We show that this alignment transition exhibits hysteresis when the noise intensity is taken to be time dependent. Office of Naval Research, NIH (LMR and IBS) and NRL (EF)

  20. Field-aligned currents' scale analysis performed with the Swarm constellation

    NASA Astrophysics Data System (ADS)

    Lühr, Hermann; Park, Jaeheung; Gjerloev, Jesper W.; Rauberg, Jan; Michaelis, Ingo; Merayo, Jose M. G.; Brauer, Peter

    2015-01-01

    We present a statistical study of the temporal- and spatial-scale characteristics of different field-aligned current (FAC) types derived with the Swarm satellite formation. We divide FACs into two classes: small-scale, up to some 10 km, which are carried predominantly by kinetic Alfvén waves, and large-scale FACs with sizes of more than 150 km. For determining temporal variability we consider measurements at the same point, the orbital crossovers near the poles, but at different times. From correlation analysis we obtain a persistent period of small-scale FACs of order 10 s, while large-scale FACs can be regarded stationary for more than 60 s. For the first time we investigate the longitudinal scales. Large-scale FACs are different on dayside and nightside. On the nightside the longitudinal extension is on average 4 times the latitudinal width, while on the dayside, particularly in the cusp region, latitudinal and longitudinal scales are comparable.

  1. Formation control of robotic swarm using bounded artificial forces.

    PubMed

    Qin, Long; Zha, Yabing; Yin, Quanjun; Peng, Yong

    2013-01-01

    Formation control of multirobot systems has drawn significant attention in the recent years. This paper presents a potential field control algorithm, navigating a swarm of robots into a predefined 2D shape while avoiding intermember collisions. The algorithm applies in both stationary and moving targets formation. We define the bounded artificial forces in the form of exponential functions, so that the behavior of the swarm drove by the forces can be adjusted via selecting proper control parameters. The theoretical analysis of the swarm behavior proves the stability and convergence properties of the algorithm. We further make certain modifications upon the forces to improve the robustness of the swarm behavior in the presence of realistic implementation considerations. The considerations include obstacle avoidance, local minima, and deformation of the shape. Finally, detailed simulation results validate the efficiency of the proposed algorithm, and the direction of possible futrue work is discussed in the conclusions.

  2. Transport of Particle Swarms Through Variable Aperture Fractures

    NASA Astrophysics Data System (ADS)

    Boomsma, E.; Pyrak-Nolte, L. J.

    2012-12-01

    Particle transport through fractured rock is a key concern with the increased use of micro- and nano-size particles in consumer products as well as from other activities in the sub- and near surface (e.g. mining, industrial waste, hydraulic fracturing, etc.). While particle transport is often studied as the transport of emulsions or dispersions, particles may also enter the subsurface from leaks or seepage that lead to particle swarms. Swarms are drop-like collections of millions of colloidal-sized particles that exhibit a number of unique characteristics when compared to dispersions and emulsions. Any contaminant or engineered particle that forms a swarm can be transported farther, faster, and more cohesively in fractures than would be expected from a traditional dispersion model. In this study, the effects of several variable aperture fractures on colloidal swarm cohesiveness and evolution were studied as a swarm fell under gravity and interacted with the fracture walls. Transparent acrylic was used to fabricate synthetic fracture samples with (1) a uniform aperture, (2) a converging region followed by a uniform region (funnel shaped), (3) a uniform region followed by a diverging region (inverted funnel), and (4) a cast of a an induced fracture from a carbonate rock. All of the samples consisted of two blocks that measured 100 x 100 x 50 mm. The minimum separation between these blocks determined the nominal aperture (0.5 mm to 20 mm). During experiments a fracture was fully submerged in water and swarms were released into it. The swarms consisted of a dilute suspension of 3 micron polystyrene fluorescent beads (1% by mass) with an initial volume of 5μL. The swarms were illuminated with a green (525 nm) LED array and imaged optically with a CCD camera. The variation in fracture aperture controlled swarm behavior. Diverging apertures caused a sudden loss of confinement that resulted in a rapid change in the swarm's shape as well as a sharp increase in its velocity

  3. Particle Swarm Optimization With Interswarm Interactive Learning Strategy.

    PubMed

    Qin, Quande; Cheng, Shi; Zhang, Qingyu; Li, Li; Shi, Yuhui

    2016-10-01

    The learning strategy in the canonical particle swarm optimization (PSO) algorithm is often blamed for being the primary reason for loss of diversity. Population diversity maintenance is crucial for preventing particles from being stuck into local optima. In this paper, we present an improved PSO algorithm with an interswarm interactive learning strategy (IILPSO) by overcoming the drawbacks of the canonical PSO algorithm's learning strategy. IILPSO is inspired by the phenomenon in human society that the interactive learning behavior takes place among different groups. Particles in IILPSO are divided into two swarms. The interswarm interactive learning (IIL) behavior is triggered when the best particle's fitness value of both the swarms does not improve for a certain number of iterations. According to the best particle's fitness value of each swarm, the softmax method and roulette method are used to determine the roles of the two swarms as the learning swarm and the learned swarm. In addition, the velocity mutation operator and global best vibration strategy are used to improve the algorithm's global search capability. The IIL strategy is applied to PSO with global star and local ring structures, which are termed as IILPSO-G and IILPSO-L algorithm, respectively. Numerical experiments are conducted to compare the proposed algorithms with eight popular PSO variants. From the experimental results, IILPSO demonstrates the good performance in terms of solution accuracy, convergence speed, and reliability. Finally, the variations of the population diversity in the entire search process provide an explanation why IILPSO performs effectively.

  4. Detection of earthquake swarms at subduction zones globally: Insights into tectonic controls on swarm activity

    NASA Astrophysics Data System (ADS)

    Nishikawa, T.; Ide, S.

    2017-07-01

    Earthquake swarms are characterized by an increase in seismicity rate that lacks a distinguished main shock and does not obey Omori's law. At subduction zones, they are thought to be related to slow-slip events (SSEs) on the plate interface. Earthquake swarms in subduction zones can therefore be used as potential indicators of slow-slip events. However, the global distribution of earthquake swarms at subduction zones remains unclear. Here we present a method for detecting such earthquake sequences using the space-time epidemic-type aftershock-sequence model. We applied this method to seismicity (M ≥ 4.5) recorded in the Advanced National Seismic System catalog at subduction zones during the period of 1995-2009. We detected 453 swarms, which is about 6.7 times the number observed in a previous catalog. Foreshocks of some large earthquakes are also detected as earthquake swarms. In some subduction zones, such as at Ibaraki-Oki, Japan, swarm-like foreshocks and ordinary swarms repeatedly occur at the same location. Given that both foreshocks and swarms are related to SSEs on the plate interface, these regions may have experienced recurring SSEs. We then compare the swarm activity and tectonic properties of subduction zones, finding that swarm activity is positively correlated with curvature of the incoming plate before subduction. This result implies that swarm activity is controlled either by hydration of the incoming plate or by heterogeneity on the plate interface due to fracturing related to slab bending.

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

    NASA Astrophysics Data System (ADS)

    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.

  6. Particle Swarms in Fractures: Open Versus Partially Closed Systems

    NASA Astrophysics Data System (ADS)

    Boomsma, E.; Pyrak-Nolte, L. J.

    2014-12-01

    In the field, fractures may be isolated or connected to fluid reservoirs anywhere along the perimeter of a fracture. These boundaries affect fluid circulation, flow paths and communication with external reservoirs. The transport of drop like collections of colloidal-sized particles (particle swarms) in open and partially closed systems was studied. A uniform aperture synthetic fracture was constructed using two blocks (100 x 100 x 50 mm) of transparent acrylic placed parallel to each other. The fracture was fully submerged a tank filled with 100cSt silicone oil. Fracture apertures were varied from 5-80 mm. Partially closed systems were created by sealing the sides of the fracture with plastic film. The four boundary conditions study were: (Case 1) open, (Case 2) closed on the sides, (Case 3) closed on the bottom, and (Case 4) closed on both the sides and bottom of the fracture. A 15 μL dilute suspension of soda-lime glass particles in oil (2% by mass) were released into the fracture. Particle swarms were illuminated using a green (525 nm) LED array and imaged with a CCD camera. The presence of the additional boundaries modified the speed of the particle swarms (see figure). In Case 1, enhanced swarm transport was observed for a range of apertures, traveling faster than either very small or very large apertures. In Case 2, swarm velocities were enhanced over a larger range of fracture apertures than in any of the other cases. Case 3 shifted the enhanced transport regime to lower apertures and also reduced swarm speed when compared to Case 2. Finally, Case 4 eliminated the enhanced transport regime entirely. Communication between the fluid in the fracture and an external fluid reservoir resulted in enhanced swarm transport in Cases 1-3. The non-rigid nature of a swarm enables drag from the fracture walls to modify the swarm geometry. The particles composing a swarm reorganize in response to the fracture, elongating the swarm and maintaining its density. Unlike a

  7. Multiscale modelling and analysis of collective decision making in swarm robotics.

    PubMed

    Vigelius, Matthias; Meyer, Bernd; Pascoe, Geoffrey

    2014-01-01

    We present a unified approach to describing certain types of collective decision making in swarm robotics that bridges from a microscopic individual-based description to aggregate properties. Our approach encompasses robot swarm experiments, microscopic and probabilistic macroscopic-discrete simulations as well as an analytic mathematical model. Following up on previous work, we identify the symmetry parameter, a measure of the progress of the swarm towards a decision, as a fundamental integrated swarm property and formulate its time evolution as a continuous-time Markov process. Contrary to previous work, which justified this approach only empirically and a posteriori, we justify it from first principles and derive hard limits on the parameter regime in which it is applicable.

  8. Multiscale Modelling and Analysis of Collective Decision Making in Swarm Robotics

    PubMed Central

    Vigelius, Matthias; Meyer, Bernd; Pascoe, Geoffrey

    2014-01-01

    We present a unified approach to describing certain types of collective decision making in swarm robotics that bridges from a microscopic individual-based description to aggregate properties. Our approach encompasses robot swarm experiments, microscopic and probabilistic macroscopic-discrete simulations as well as an analytic mathematical model. Following up on previous work, we identify the symmetry parameter, a measure of the progress of the swarm towards a decision, as a fundamental integrated swarm property and formulate its time evolution as a continuous-time Markov process. Contrary to previous work, which justified this approach only empirically and a posteriori, we justify it from first principles and derive hard limits on the parameter regime in which it is applicable. PMID:25369026

  9. Formation Control of Robotic Swarm Using Bounded Artificial Forces

    PubMed Central

    Zha, Yabing; Peng, Yong

    2013-01-01

    Formation control of multirobot systems has drawn significant attention in the recent years. This paper presents a potential field control algorithm, navigating a swarm of robots into a predefined 2D shape while avoiding intermember collisions. The algorithm applies in both stationary and moving targets formation. We define the bounded artificial forces in the form of exponential functions, so that the behavior of the swarm drove by the forces can be adjusted via selecting proper control parameters. The theoretical analysis of the swarm behavior proves the stability and convergence properties of the algorithm. We further make certain modifications upon the forces to improve the robustness of the swarm behavior in the presence of realistic implementation considerations. The considerations include obstacle avoidance, local minima, and deformation of the shape. Finally, detailed simulation results validate the efficiency of the proposed algorithm, and the direction of possible futrue work is discussed in the conclusions. PMID:24453809

  10. Study of Electron Swarm in High Pressure Hydrogen Gas Filled RF Cavities

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Yonehara, K.; Chung, M.; Jansson, A.

    2010-05-01

    A high pressure hydrogen gas filled RF cavity has been proposed for use in the muon collection system for a muon collider. It allows for high electric field gradients in RF cavities located in strong magnetic fields, a condition frequently encountered in a muon cooling channel. In addition, an intense muon beam will generate an electron swarm via the ionization process in the cavity. A large amount of RF power will be consumed into the swarm. We show the results from our studies of the HV RF breakdown in a cavity without a beam and present some results on themore » resulting electron swarm dynamics. This is preliminary to actual beam tests which will take place late in 2010.« less

  11. Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots.

    PubMed

    Duarte, Miguel; Costa, Vasco; Gomes, Jorge; Rodrigues, Tiago; Silva, Fernando; Oliveira, Sancho Moura; Christensen, Anders Lyhne

    2016-01-01

    Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers.

  12. Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots

    PubMed Central

    Duarte, Miguel; Costa, Vasco; Gomes, Jorge; Rodrigues, Tiago; Silva, Fernando; Oliveira, Sancho Moura; Christensen, Anders Lyhne

    2016-01-01

    Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers. PMID:26999614

  13. Precise Orbit Solution for Swarm Using Space-Borne GPS Data and Optimized Pseudo-Stochastic Pulses.

    PubMed

    Zhang, Bingbing; Wang, Zhengtao; Zhou, Lv; Feng, Jiandi; Qiu, Yaodong; Li, Fupeng

    2017-03-20

    Swarm is a European Space Agency (ESA) project that was launched on 22 November 2013, which consists of three Swarm satellites. Swarm precise orbits are essential to the success of the above project. This study investigates how well Swarm zero-differenced (ZD) reduced-dynamic orbit solutions can be determined using space-borne GPS data and optimized pseudo-stochastic pulses under high ionospheric activity. We choose Swarm space-borne GPS data from 1-25 October 2014, and Swarm reduced-dynamic orbits are obtained. Orbit quality is assessed by GPS phase observation residuals and compared with Precise Science Orbits (PSOs) released by ESA. Results show that pseudo-stochastic pulses with a time interval of 6 min and a priori standard deviation (STD) of 10 -2 mm/s in radial (R), along-track (T) and cross-track (N) directions are optimized to Swarm ZD reduced-dynamic precise orbit determination (POD). During high ionospheric activity, the mean Root Mean Square (RMS) of Swarm GPS phase residuals is at 9-11 mm, Swarm orbit solutions are also compared with Swarm PSOs released by ESA and the accuracy of Swarm orbits can reach 2-4 cm in R, T and N directions. Independent Satellite Laser Ranging (SLR) validation indicates that Swarm reduced-dynamic orbits have an accuracy of 2-4 cm. Swarm-B orbit quality is better than those of Swarm-A and Swarm-C. The Swarm orbits can be applied to the geomagnetic, geoelectric and gravity field recovery.

  14. Causal mechanisms of seismo-EM phenomena during the 1965-1967 Matsushiro earthquake swarm.

    PubMed

    Enomoto, Yuji; Yamabe, Tsuneaki; Okumura, Nobuo

    2017-03-21

    The 1965-1967 Matsushiro earthquake swarm in central Japan exhibited two unique characteristics. The first was a hydro-mechanical crust rupture resulting from degassing, volume expansion of CO 2 /water, and a crack opening within the critically stressed crust under a strike-slip stress. The other was, despite the lower total seismic energy, the occurrence of complexed seismo-electromagnetic (seismo-EM) phenomena of the geomagnetic intensity increase, unusual earthquake lights (EQLs) and atmospheric electric field (AEF) variations. Although the basic rupture process of this swarm of earthquakes is reasonably understood in terms of hydro-mechanical crust rupture, the associated seismo-EM processes remain largely unexplained. Here, we describe a series of seismo-EM mechanisms involved in the hydro-mechanical rupture process, as observed by coupling the electric interaction of rock rupture with CO 2 gas and the dielectric-barrier discharge of the modelled fields in laboratory experiments. We found that CO 2 gases passing through the newly created fracture surface of the rock were electrified to generate pressure-impressed current/electric dipoles, which could induce a magnetic field following Biot-Savart's law, decrease the atmospheric electric field and generate dielectric-barrier discharge lightning affected by the coupling effect between the seismic and meteorological activities.

  15. Causal mechanisms of seismo-EM phenomena during the 1965-1967 Matsushiro earthquake swarm

    NASA Astrophysics Data System (ADS)

    Enomoto, Yuji; Yamabe, Tsuneaki; Okumura, Nobuo

    2017-03-01

    The 1965-1967 Matsushiro earthquake swarm in central Japan exhibited two unique characteristics. The first was a hydro-mechanical crust rupture resulting from degassing, volume expansion of CO2/water, and a crack opening within the critically stressed crust under a strike-slip stress. The other was, despite the lower total seismic energy, the occurrence of complexed seismo-electromagnetic (seismo-EM) phenomena of the geomagnetic intensity increase, unusual earthquake lights (EQLs) and atmospheric electric field (AEF) variations. Although the basic rupture process of this swarm of earthquakes is reasonably understood in terms of hydro-mechanical crust rupture, the associated seismo-EM processes remain largely unexplained. Here, we describe a series of seismo-EM mechanisms involved in the hydro-mechanical rupture process, as observed by coupling the electric interaction of rock rupture with CO2 gas and the dielectric-barrier discharge of the modelled fields in laboratory experiments. We found that CO2 gases passing through the newly created fracture surface of the rock were electrified to generate pressure-impressed current/electric dipoles, which could induce a magnetic field following Biot-Savart’s law, decrease the atmospheric electric field and generate dielectric-barrier discharge lightning affected by the coupling effect between the seismic and meteorological activities.

  16. An initial ULF wave index derived from 2 years of Swarm observations

    NASA Astrophysics Data System (ADS)

    Papadimitriou, Constantinos; Balasis, Georgios; Daglis, Ioannis A.; Giannakis, Omiros

    2018-03-01

    The ongoing Swarm satellite mission provides an opportunity for better knowledge of the near-Earth electromagnetic environment. Herein, we use a new methodological approach for the detection and classification of ultra low-frequency (ULF) wave events observed by Swarm based on an existing time-frequency analysis (TFA) tool and utilizing a state-of-the-art high-resolution magnetic field model and Swarm Level 2 products (i.e., field-aligned currents - FACs - and the Ionospheric Bubble Index - IBI). We present maps of the dependence of ULF wave power with magnetic latitude and magnetic local time (MLT) as well as geographic latitude and longitude from the three satellites at their different locations in low-Earth orbit (LEO) for a period spanning 2 years after the constellation's final configuration. We show that the inclusion of the Swarm single-spacecraft FAC product in our analysis eliminates all the wave activity at high altitudes, which is physically unrealistic. Moreover, we derive a Swarm orbit-by-orbit Pc3 wave (20-100 MHz) index for the topside ionosphere and compare its values with the corresponding variations of solar wind variables and geomagnetic activity indices. This is the first attempt, to our knowledge, to derive a ULF wave index from LEO satellite data. The technique can be potentially used to define a new Level 2 product from the mission, the Swarm ULF wave index, which would be suitable for space weather applications.

  17. Analysis of swarm behaviors based on an inversion of the fluctuation theorem.

    PubMed

    Hamann, Heiko; Schmickl, Thomas; Crailsheim, Karl

    2014-01-01

    A grand challenge in the field of artificial life is to find a general theory of emergent self-organizing systems. In swarm systems most of the observed complexity is based on motion of simple entities. Similarly, statistical mechanics focuses on collective properties induced by the motion of many interacting particles. In this article we apply methods from statistical mechanics to swarm systems. We try to explain the emergent behavior of a simulated swarm by applying methods based on the fluctuation theorem. Empirical results indicate that swarms are able to produce negative entropy within an isolated subsystem due to frozen accidents. Individuals of a swarm are able to locally detect fluctuations of the global entropy measure and store them, if they are negative entropy productions. By accumulating these stored fluctuations over time the swarm as a whole is producing negative entropy and the system ends up in an ordered state. We claim that this indicates the existence of an inverted fluctuation theorem for emergent self-organizing dissipative systems. This approach bears the potential of general applicability.

  18. Multiscale Model of Swarming Bacteria

    NASA Astrophysics Data System (ADS)

    Alber, Mark

    2011-03-01

    Many bacteria can rapidly traverse surfaces from which they are extracting nutrient for growth. They generate flat, spreading colonies, called swarms because they resemble swarms of insects. In the beginning of the talk, swarms of the M. xanthus will be described in detail. Individual M. xanthus cells are elongated; they always move in the direction of their long axis; and they are in constant motion, repeatedly touching each other. As a cell glides, the slime capsule of a cell interacts with the bare agar surface, non-oriented slime which arises from the surface contact with the slime capsule, or oriented slime trails. Remarkably, cells regularly reverse their gliding directions. In this talk a detailed cell- and behavior-based computational model of M. xanthus swarming will be used to demonstrate that reversals of gliding direction and cell bending are essential for swarming and that specific reversal frequencies result in optimal swarming rate of the whole population. This suggests that the circuit regulating reversals evolved to its current sensitivity under selection for growth achieved by swarming.

  19. Precise Orbit Solution for Swarm Using Space-Borne GPS Data and Optimized Pseudo-Stochastic Pulses

    PubMed Central

    Zhang, Bingbing; Wang, Zhengtao; Zhou, Lv; Feng, Jiandi; Qiu, Yaodong; Li, Fupeng

    2017-01-01

    Swarm is a European Space Agency (ESA) project that was launched on 22 November 2013, which consists of three Swarm satellites. Swarm precise orbits are essential to the success of the above project. This study investigates how well Swarm zero-differenced (ZD) reduced-dynamic orbit solutions can be determined using space-borne GPS data and optimized pseudo-stochastic pulses under high ionospheric activity. We choose Swarm space-borne GPS data from 1–25 October 2014, and Swarm reduced-dynamic orbits are obtained. Orbit quality is assessed by GPS phase observation residuals and compared with Precise Science Orbits (PSOs) released by ESA. Results show that pseudo-stochastic pulses with a time interval of 6 min and a priori standard deviation (STD) of 10−2 mm/s in radial (R), along-track (T) and cross-track (N) directions are optimized to Swarm ZD reduced-dynamic precise orbit determination (POD). During high ionospheric activity, the mean Root Mean Square (RMS) of Swarm GPS phase residuals is at 9–11 mm, Swarm orbit solutions are also compared with Swarm PSOs released by ESA and the accuracy of Swarm orbits can reach 2–4 cm in R, T and N directions. Independent Satellite Laser Ranging (SLR) validation indicates that Swarm reduced-dynamic orbits have an accuracy of 2–4 cm. Swarm-B orbit quality is better than those of Swarm-A and Swarm-C. The Swarm orbits can be applied to the geomagnetic, geoelectric and gravity field recovery. PMID:28335538

  20. Particle Swarm Optimization with Double Learning Patterns

    PubMed Central

    Shen, Yuanxia; Wei, Linna; Zeng, Chuanhua; Chen, Jian

    2016-01-01

    Particle Swarm Optimization (PSO) is an effective tool in solving optimization problems. However, PSO usually suffers from the premature convergence due to the quick losing of the swarm diversity. In this paper, we first analyze the motion behavior of the swarm based on the probability characteristic of learning parameters. Then a PSO with double learning patterns (PSO-DLP) is developed, which employs the master swarm and the slave swarm with different learning patterns to achieve a trade-off between the convergence speed and the swarm diversity. The particles in the master swarm and the slave swarm are encouraged to explore search for keeping the swarm diversity and to learn from the global best particle for refining a promising solution, respectively. When the evolutionary states of two swarms interact, an interaction mechanism is enabled. This mechanism can help the slave swarm in jumping out of the local optima and improve the convergence precision of the master swarm. The proposed PSO-DLP is evaluated on 20 benchmark functions, including rotated multimodal and complex shifted problems. The simulation results and statistical analysis show that PSO-DLP obtains a promising performance and outperforms eight PSO variants. PMID:26858747

  1. Particle Swarm Optimization with Double Learning Patterns.

    PubMed

    Shen, Yuanxia; Wei, Linna; Zeng, Chuanhua; Chen, Jian

    2016-01-01

    Particle Swarm Optimization (PSO) is an effective tool in solving optimization problems. However, PSO usually suffers from the premature convergence due to the quick losing of the swarm diversity. In this paper, we first analyze the motion behavior of the swarm based on the probability characteristic of learning parameters. Then a PSO with double learning patterns (PSO-DLP) is developed, which employs the master swarm and the slave swarm with different learning patterns to achieve a trade-off between the convergence speed and the swarm diversity. The particles in the master swarm and the slave swarm are encouraged to explore search for keeping the swarm diversity and to learn from the global best particle for refining a promising solution, respectively. When the evolutionary states of two swarms interact, an interaction mechanism is enabled. This mechanism can help the slave swarm in jumping out of the local optima and improve the convergence precision of the master swarm. The proposed PSO-DLP is evaluated on 20 benchmark functions, including rotated multimodal and complex shifted problems. The simulation results and statistical analysis show that PSO-DLP obtains a promising performance and outperforms eight PSO variants.

  2. Mixed reality framework for collective motion patterns of swarms with delay coupling

    NASA Astrophysics Data System (ADS)

    Szwaykowska, Klementyna; Schwartz, Ira

    The formation of coherent patterns in swarms of interacting self-propelled autonomous agents is an important subject for many applications within the field of distributed robotic systems. However, there are significant logistical challenges associated with testing fully distributed systems in real-world settings. In this paper, we provide a rigorous theoretical justification for the use of mixed-reality experiments as a stepping stone to fully physical testing of distributed robotic systems. We also model and experimentally realize a mixed-reality large-scale swarm of delay-coupled agents. Our analyses, assuming agents communicating over an Erdos-Renyi network, demonstrate the existence of stable coherent patterns that can be achieved only with delay coupling and that are robust to decreasing network connectivity and heterogeneity in agent dynamics. We show how the bifurcation structure for emergence of different patterns changes with heterogeneity in agent acceleration capabilities and limited connectivity in the network as a function of coupling strength and delay. Our results are verified through simulation as well as preliminary experimental results of delay-induced pattern formation in a mixed-reality swarm. K. S. was a National Research Council postdoctoral fellow. I.B.S was supported by the U.S. Naval Research Laboratory funding (N0001414WX00023) and office of Naval Research (N0001414WX20610).

  3. Cell-Division Behavior in a Heterogeneous Swarm Environment.

    PubMed

    Erskine, Adam; Herrmann, J Michael

    2015-01-01

    We present a system of virtual particles that interact using simple kinetic rules. It is known that heterogeneous mixtures of particles can produce particularly interesting behaviors. Here we present a two-species three-dimensional swarm in which a behavior emerges that resembles cell division. We show that the dividing behavior exists across a narrow but finite band of parameters and for a wide range of population sizes. When executed in a two-dimensional environment the swarm's characteristics and dynamism manifest differently. In further experiments we show that repeated divisions can occur if the system is extended by a biased equilibrium process to control the split of populations. We propose that this repeated division behavior provides a simple model for cell-division mechanisms and is of interest for the formation of morphological structure and to swarm robotics.

  4. P-adic valued models of swarm behaviour

    NASA Astrophysics Data System (ADS)

    Schumann, Andrew

    2017-07-01

    The swarm behaviour can be fully determined by attractants (food pieces) which change the directions of swarm propagation. If we assume that at each time step the swarm can find out not more than p - 1 attractants, then the swarm behaviour can be coded by p-adic integers. The main task of any swarm is to logistically optimize the road system connecting the reachable attractants. In the meanwhile, the transporting network of the swarm has loops (circles) and permanently changes, e.g. the swarm occupies some attractants and leaves the others. However, this complex dynamics can be effectively coded by p-adic integers. This allows us to represent the swarm behaviour as a calculation on p-adic valued strings.

  5. Multiswarm comprehensive learning particle swarm optimization for solving multiobjective optimization problems.

    PubMed

    Yu, Xiang; Zhang, Xueqing

    2017-01-01

    Comprehensive learning particle swarm optimization (CLPSO) is a powerful state-of-the-art single-objective metaheuristic. Extending from CLPSO, this paper proposes multiswarm CLPSO (MSCLPSO) for multiobjective optimization. MSCLPSO involves multiple swarms, with each swarm associated with a separate original objective. Each particle's personal best position is determined just according to the corresponding single objective. Elitists are stored externally. MSCLPSO differs from existing multiobjective particle swarm optimizers in three aspects. First, each swarm focuses on optimizing the associated objective using CLPSO, without learning from the elitists or any other swarm. Second, mutation is applied to the elitists and the mutation strategy appropriately exploits the personal best positions and elitists. Third, a modified differential evolution (DE) strategy is applied to some extreme and least crowded elitists. The DE strategy updates an elitist based on the differences of the elitists. The personal best positions carry useful information about the Pareto set, and the mutation and DE strategies help MSCLPSO discover the true Pareto front. Experiments conducted on various benchmark problems demonstrate that MSCLPSO can find nondominated solutions distributed reasonably over the true Pareto front in a single run.

  6. LCS-1: a high-resolution global model of the lithospheric magnetic field derived from CHAMP and Swarm satellite observations

    NASA Astrophysics Data System (ADS)

    Olsen, Nils; Ravat, Dhananjay; Finlay, Christopher C.; Kother, Livia K.

    2017-12-01

    We derive a new model, named LCS-1, of Earth's lithospheric field based on four years (2006 September-2010 September) of magnetic observations taken by the CHAMP satellite at altitudes lower than 350 km, as well as almost three years (2014 April-2016 December) of measurements taken by the two lower Swarm satellites Alpha and Charlie. The model is determined entirely from magnetic 'gradient' data (approximated by finite differences): the north-south gradient is approximated by first differences of 15 s along-track data (for CHAMP and each of the two Swarm satellites), while the east-west gradient is approximated by the difference between observations taken by Swarm Alpha and Charlie. In total, we used 6.2 mio data points. The model is parametrized by 35 000 equivalent point sources located on an almost equal-area grid at a depth of 100 km below the surface (WGS84 ellipsoid). The amplitudes of these point sources are determined by minimizing the misfit to the magnetic satellite 'gradient' data together with the global average of |Br| at the ellipsoid surface (i.e. applying an L1 model regularization of Br). In a final step, we transform the point-source representation to a spherical harmonic expansion. The model shows very good agreement with previous satellite-derived lithospheric field models at low degree (degree correlation above 0.8 for degrees n ≤ 133). Comparison with independent near-surface aeromagnetic data from Australia yields good agreement (coherence >0.55) at horizontal wavelengths down to at least 250 km, corresponding to spherical harmonic degree n ≈ 160. The LCS-1 vertical component and field intensity anomaly maps at Earth's surface show similar features to those exhibited by the WDMAM2 and EMM2015 lithospheric field models truncated at degree 185 in regions where they include near-surface data and provide unprecedented detail where they do not. Example regions of improvement include the Bangui anomaly region in central Africa, the west African

  7. Relationship between PC index and magnetospheric field-aligned currents measured by Swarm satellites

    NASA Astrophysics Data System (ADS)

    Troshichev, O.; Sormakov, D.; Behlke, R.

    2018-03-01

    The relationship between the magnetospheric field-aligned currents (FAC) monitored by the Swarm satellites and the magnetic activity PC index (which is a proxy of the solar wind energy incoming into the magnetosphere) is examined. It is shown that current intensities measured in the R1 and R2 FAC layers at the poleward and equtorward boundaries of the auroral oval are well correlated, the R2 currents being evidently secondary in relation to R1 currents and correlation in the dawn and dusk oval sectors being better than in the noon and night sectors. There is evident relationship between the PC index and the intensity of field-aligned currents in the R1 dawn and dusk layers: increase of FAC intensity in the course of substorm development is accompanied by increasing the PC index values. Correlation between PC and FAC intensities in the R2 dawn and dusk layers is also observed, but it is much weaker. No correlation is observed between PC and field-aligned currents in the midnight as well as in the noon sectors ahead of the substorm expansion phase. The results are indicative of the R1 field-aligned currents as a driver of the polar cap magnetic activity (PC index) and currents in the R2 layer.

  8. Enhanced Particle Swarm Optimization Algorithm: Efficient Training of ReaxFF Reactive Force Fields.

    PubMed

    Furman, David; Carmeli, Benny; Zeiri, Yehuda; Kosloff, Ronnie

    2018-06-12

    Particle swarm optimization (PSO) is a powerful metaheuristic population-based global optimization algorithm. However, when it is applied to nonseparable objective functions, its performance on multimodal landscapes is significantly degraded. Here we show that a significant improvement in the search quality and efficiency on multimodal functions can be achieved by enhancing the basic rotation-invariant PSO algorithm with isotropic Gaussian mutation operators. The new algorithm demonstrates superior performance across several nonlinear, multimodal benchmark functions compared with the rotation-invariant PSO algorithm and the well-established simulated annealing and sequential one-parameter parabolic interpolation methods. A search for the optimal set of parameters for the dispersion interaction model in the ReaxFF- lg reactive force field was carried out with respect to accurate DFT-TS calculations. The resulting optimized force field accurately describes the equations of state of several high-energy molecular crystals where such interactions are of crucial importance. The improved algorithm also presents better performance compared to a genetic algorithm optimization method in the optimization of the parameters of a ReaxFF- lg correction model. The computational framework is implemented in a stand-alone C++ code that allows the straightforward development of ReaxFF reactive force fields.

  9. Causal mechanisms of seismo-EM phenomena during the 1965–1967 Matsushiro earthquake swarm

    PubMed Central

    Enomoto, Yuji; Yamabe, Tsuneaki; Okumura, Nobuo

    2017-01-01

    The 1965–1967 Matsushiro earthquake swarm in central Japan exhibited two unique characteristics. The first was a hydro-mechanical crust rupture resulting from degassing, volume expansion of CO2/water, and a crack opening within the critically stressed crust under a strike-slip stress. The other was, despite the lower total seismic energy, the occurrence of complexed seismo-electromagnetic (seismo-EM) phenomena of the geomagnetic intensity increase, unusual earthquake lights (EQLs) and atmospheric electric field (AEF) variations. Although the basic rupture process of this swarm of earthquakes is reasonably understood in terms of hydro-mechanical crust rupture, the associated seismo-EM processes remain largely unexplained. Here, we describe a series of seismo-EM mechanisms involved in the hydro-mechanical rupture process, as observed by coupling the electric interaction of rock rupture with CO2 gas and the dielectric-barrier discharge of the modelled fields in laboratory experiments. We found that CO2 gases passing through the newly created fracture surface of the rock were electrified to generate pressure-impressed current/electric dipoles, which could induce a magnetic field following Biot-Savart’s law, decrease the atmospheric electric field and generate dielectric-barrier discharge lightning affected by the coupling effect between the seismic and meteorological activities. PMID:28322263

  10. Chaotic Model for Lévy Walks in Swarming Bacteria

    NASA Astrophysics Data System (ADS)

    Ariel, Gil; Be'er, Avraham; Reynolds, Andy

    2017-06-01

    We describe a new mechanism for Lévy walks, explaining the recently observed superdiffusion of swarming bacteria. The model hinges on several key physical properties of bacteria, such as an elongated cell shape, self-propulsion, and a collectively generated regular vortexlike flow. In particular, chaos and Lévy walking are a consequence of group dynamics. The model explains how cells can fine-tune the geometric properties of their trajectories. Experiments confirm the spectrum of these patterns in fluorescently labeled swarming Bacillus subtilis.

  11. Bats adjust their pulse emission rates with swarm size in the field.

    PubMed

    Lin, Yuan; Abaid, Nicole; Müller, Rolf

    2016-12-01

    Flying in swarms, e.g., when exiting a cave, could pose a problem to bats that use an active biosonar system because the animals could risk jamming each other's biosonar signals. Studies from current literature have found different results with regard to whether bats reduce or increase emission rate in the presence of jamming ultrasound. In the present work, the number of Eastern bent-wing bats (Miniopterus fuliginosus) that were flying inside a cave during emergence was estimated along with the number of signal pulses recorded. Over the range of average bat numbers present in the recording (0 to 14 bats), the average number of detected pulses per bat increased with the average number of bats. The result was interpreted as an indication that the Eastern bent-wing bats increased their emission rate and/or pulse amplitude with swarm size on average. This finding could be explained by the hypothesis that the bats might not suffer from substantial jamming probabilities under the observed density regimes, so jamming might not have been a limiting factor for their emissions. When jamming did occur, the bats could avoid it through changing the pulse amplitude and other pulse properties such as duration or frequency, which has been suggested by other studies. More importantly, the increased biosonar activities may have addressed a collision-avoidance challenge that was posed by the increased swarm size.

  12. Swarm Verification

    NASA Technical Reports Server (NTRS)

    Holzmann, Gerard J.; Joshi, Rajeev; Groce, Alex

    2008-01-01

    Reportedly, supercomputer designer Seymour Cray once said that he would sooner use two strong oxen to plow a field than a thousand chickens. Although this is undoubtedly wise when it comes to plowing a field, it is not so clear for other types of tasks. Model checking problems are of the proverbial "search the needle in a haystack" type. Such problems can often be parallelized easily. Alas, none of the usual divide and conquer methods can be used to parallelize the working of a model checker. Given that it has become easier than ever to gain access to large numbers of computers to perform even routine tasks it is becoming more and more attractive to find alternate ways to use these resources to speed up model checking tasks. This paper describes one such method, called swarm verification.

  13. SWARMS Early Trials Management for The SWARMs ECSEL-H2020 Project

    NASA Astrophysics Data System (ADS)

    Alcaraz, Daniel; Morales, Tania; Castro, Ayoze; Barrera, Carlos; Hernández, Joaquín; Llinás, Octavio

    2017-04-01

    The work presented on this paper is aimed to explain how the Early Trials of the Project SWARMS were managed in order to complete the first field demonstrations on real environment. SWARMs aims to reduce the operational cost in the use of maritime robots and vehicles, in order to increase the safety of tasks and reduce profesional divers risks. This will be achieved enabling the AUVs/ROVs to work in a cooperative mesh. The challenge is to design and develop an integrated platform (a set of Software/Hardware components), incorporated into the current generation of underwater vehicles in order to improve autonomy, cooperation, robustness, cost-effectiveness, and reliability of the offshore operations. The first demonstration of the project has been performed at PLOCAN (The Oceanic Platform of the Canary Islands) where these technologies were validated on its first stage. The Early Trials have represented the first in situ deployment and test of the novel technologies developed during the initial 14 months of the Project. Going into the sea supposed a huge challenge also in terms of management. The 32 partners of SWARMS had very different requirements (logistics, technical needs, software/computation needs, etc.), and a limited time frame to test and prove their individual developments. In order to fullfill the project objectives, all these tests were divided in 7 missions that were aimed to cover this early demonstration requiements. From PLOCAN, a management protocol was designed in order to cover all the partners needs and make an efficient resource asignment from the begining. These results will be extended to other two demonstrations of the project that forseen to be held in Romania (2017) and Norway (2018).

  14. Swarming UAS II

    DTIC Science & Technology

    2010-05-05

    employed biomimicry to model a swarm of UAS as a colony of ants, where each UAS dynamically updates a global memory map, allowing pheromone-like...matter of design, DSE-R-0808 employed biomimicry to model a swarm of UAS as a colony of ants, where each UAS dynamically updates a global memory map

  15. Thermospheric density and wind retrieval from Swarm observations

    NASA Astrophysics Data System (ADS)

    Visser, Pieter; Doornbos, Eelco; van den IJssel, Jose; Teixeira da Encarnação, João

    2013-11-01

    The three-satellite ESA Swarm mission aims at mapping the Earth's global geomagnetic field at unprecedented spatial and temporal resolution and precision. Swarm also aims at observing thermospheric density and possibly horizontal winds. Precise orbit determination (POD) and Thermospheric Density and Wind (TDW) chains form part of the Swarm Constellation and Application Facility (SCARF), which will provide the so-called Level 2 products. The POD and TDW chains generate the orbit, accelerometer calibration, and thermospheric density and wind Level 2 products. The POD and TDW chains have been tested with data from the CHAMP and GRACE missions, indicating that a 3D orbit precision of about 10 cm can be reached. In addition, POD allows to determine daily accelerometer bias and scale factor values with a precision of around 10-15 nm/s2 and 0.01-0.02, respectively, for the flight direction. With these accelerometer calibration parameter values, derived thermospheric density is consistent at the 9-11% level (standard deviation) with values predicted by models (taking into account that model values are 20-30% higher). The retrieval of crosswinds forms part of the processing chain, but will be challenging. The Swarm observations will be used for further developing and improving density and wind retrieval algorithms.

  16. Revisiting the South Atlantic Anomaly after 3 years of Swarm satellite mission

    NASA Astrophysics Data System (ADS)

    Pavón-Carrasco, F. Javier; Campuzano, Saioa A.; De Santis, Angelo

    2017-04-01

    Covering part of Southern America and the South Atlantic Ocean, the South Atlantic Anomaly (SAA) is nowadays one of the most important and largest features of the geomagnetic field at the Earth's surface. It is characterized by lower intensity values than expected for those geomagnetic latitudes. Thanks to the global geomagnetic models, the spatial and temporal geometry of the Earth's magnetic field can be defined at the core-mantle boundary, showing the origin of the SAA as a reversal polarity patch that is growing with a pronounced rate of -2.54ṡ105 nT per century and with western drift. Since the Swarm satellite mission of the European Space Agency was launched at the end of 2013, the three twin satellites are picking up the most accurate values of the geomagnetic field up to now. In this work, we use the satellite magnetic data from Swarm mission along with the observatory ground data of surrounding areas to evaluate the spatial and temporal evolution of the SAA during the Swarm-life.

  17. Impact of Swarm GPS receiver updates on POD performance

    NASA Astrophysics Data System (ADS)

    van den IJssel, Jose; Forte, Biagio; Montenbruck, Oliver

    2016-05-01

    The Swarm satellites are equipped with state-of-the-art Global Positioning System (GPS) receivers, which are used for the precise geolocation of the magnetic and electric field instruments, as well as for the determination of the Earth's gravity field, the total electron content and low-frequency thermospheric neutral densities. The onboard GPS receivers deliver high-quality data with an almost continuous data rate. However, the receivers show a slightly degraded performance when flying over the geomagnetic poles and the geomagnetic equator, due to ionospheric scintillation. Furthermore, with only eight channels available for dual-frequency tracking, the amount of collected GPS tracking data is relatively low compared with various other missions. Therefore, several modifications have been implemented to the Swarm GPS receivers. To optimise the amount of collected GPS data, the GPS antenna elevation mask has slowly been reduced from 10° to 2°. To improve the robustness against ionospheric scintillation, the bandwidths of the GPS receiver tracking loops have been widened. Because these modifications were first implemented on Swarm-C, their impact can be assessed by a comparison with the close flying Swarm-A satellite. This shows that both modifications have a positive impact on the GPS receiver performance. The reduced elevation mask increases the amount of GPS tracking data by more than 3 %, while the updated tracking loops lead to around 1.3 % more observations and a significant reduction in tracking losses due to severe equatorial scintillation. The additional observations at low elevation angles increase the average noise of the carrier phase observations, but nonetheless slightly improve the resulting reduced-dynamic and kinematic orbit accuracy as shown by independent satellite laser ranging (SLR) validation. The more robust tracking loops significantly reduce the large carrier phase observation errors at the geomagnetic poles and along the geomagnetic

  18. Characteristics of Swarm Seismicity in Northern California

    NASA Astrophysics Data System (ADS)

    Chiorini, S.; Lekic, V.

    2017-12-01

    Seismic swarms are characterized by an anomalously large number of earthquakes compared to the background rate of seismicity that are tightly clustered in space (typically, one to tens of kilometers) and time (typically, days to weeks). However, why and how swarms occur is poorly understood, partly because of the difficulty of identifying the range of swarm behaviors within large seismic catalogs. Previous studies have found that swarms, compared to other earthquake sequences, appear to be more common in extensional (Vidale & Shearer, 2006) and volcanic settings (Hayashi & Morita, 2003). In addition, swarms more commonly exhibit migration patterns, consistent with either fluid diffusion (Chen & Shearer, 2011; Chen et al., 2012) or aseismic creep (Lohman & McGuire, 2007), and are preferentially found in areas of enhanced heat flow (Enescu, 2009; Zaliapin & Ben Zion, 2016). While the swarm seismicity of Southern California has been studied extensively, that of Northern California has not been systematically documented and characterized. We employed two complementary methods of swarm identification: the approach of Vidale and Shearer (2006; henceforth VS2006) based on a priori threshold distances and timings of quakes, and the spatio-temporal distance metric proposed by Zaliapin et al. (2008; henceforth Z2008) in order to build a complete catalog of swarm seismicity in Northern California spanning 1984-2016 (Waldhauser & Schaff, 2008). Once filtered for aftershocks, the catalog allows us to describe the main features of swarm seismicity in Northern California, including spatial distribution, association or lack thereof with known faults and volcanic systems, and seismically quiescent regions. We then apply a robust technique to characterize the morphology of swarms, leading to subsets of swarms that are oriented either vertically or horizontally in space. When mapped, vertical swarms show a significant association with volcanic regions, and horizontal swarms with

  19. A Comprehensive Review of Swarm Optimization Algorithms

    PubMed Central

    2015-01-01

    Many swarm optimization algorithms have been introduced since the early 60’s, Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms have demonstrated their potential to solve many optimization problems. This paper provides an in-depth survey of well-known optimization algorithms. Selected algorithms are briefly explained and compared with each other comprehensively through experiments conducted using thirty well-known benchmark functions. Their advantages and disadvantages are also discussed. A number of statistical tests are then carried out to determine the significant performances. The results indicate the overall advantage of Differential Evolution (DE) and is closely followed by Particle Swarm Optimization (PSO), compared with other considered approaches. PMID:25992655

  20. Research on particle swarm optimization algorithm based on optimal movement probability

    NASA Astrophysics Data System (ADS)

    Ma, Jianhong; Zhang, Han; He, Baofeng

    2017-01-01

    The particle swarm optimization algorithm to improve the control precision, and has great application value training neural network and fuzzy system control fields etc.The traditional particle swarm algorithm is used for the training of feed forward neural networks,the search efficiency is low, and easy to fall into local convergence.An improved particle swarm optimization algorithm is proposed based on error back propagation gradient descent. Particle swarm optimization for Solving Least Squares Problems to meme group, the particles in the fitness ranking, optimization problem of the overall consideration, the error back propagation gradient descent training BP neural network, particle to update the velocity and position according to their individual optimal and global optimization, make the particles more to the social optimal learning and less to its optimal learning, it can avoid the particles fall into local optimum, by using gradient information can accelerate the PSO local search ability, improve the multi beam particle swarm depth zero less trajectory information search efficiency, the realization of improved particle swarm optimization algorithm. Simulation results show that the algorithm in the initial stage of rapid convergence to the global optimal solution can be near to the global optimal solution and keep close to the trend, the algorithm has faster convergence speed and search performance in the same running time, it can improve the convergence speed of the algorithm, especially the later search efficiency.

  1. Adaptive cockroach swarm algorithm

    NASA Astrophysics Data System (ADS)

    Obagbuwa, Ibidun C.; Abidoye, Ademola P.

    2017-07-01

    An adaptive cockroach swarm optimization (ACSO) algorithm is proposed in this paper to strengthen the existing cockroach swarm optimization (CSO) algorithm. The ruthless component of CSO algorithm is modified by the employment of blend crossover predator-prey evolution method which helps algorithm prevent any possible population collapse, maintain population diversity and create adaptive search in each iteration. The performance of the proposed algorithm on 16 global optimization benchmark function problems was evaluated and compared with the existing CSO, cuckoo search, differential evolution, particle swarm optimization and artificial bee colony algorithms.

  2. An Approach to Self-Assembling Swarm Robots Using Multitree Genetic Programming

    PubMed Central

    An, Jinung

    2013-01-01

    In recent days, self-assembling swarm robots have been studied by a number of researchers due to their advantages such as high efficiency, stability, and scalability. However, there are still critical issues in applying them to practical problems in the real world. The main objective of this study is to develop a novel self-assembling swarm robot algorithm that overcomes the limitations of existing approaches. To this end, multitree genetic programming is newly designed to efficiently discover a set of patterns necessary to carry out the mission of the self-assembling swarm robots. The obtained patterns are then incorporated into their corresponding robot modules. The computational experiments prove the effectiveness of the proposed approach. PMID:23861655

  3. An approach to self-assembling swarm robots using multitree genetic programming.

    PubMed

    Lee, Jong-Hyun; Ahn, Chang Wook; An, Jinung

    2013-01-01

    In recent days, self-assembling swarm robots have been studied by a number of researchers due to their advantages such as high efficiency, stability, and scalability. However, there are still critical issues in applying them to practical problems in the real world. The main objective of this study is to develop a novel self-assembling swarm robot algorithm that overcomes the limitations of existing approaches. To this end, multitree genetic programming is newly designed to efficiently discover a set of patterns necessary to carry out the mission of the self-assembling swarm robots. The obtained patterns are then incorporated into their corresponding robot modules. The computational experiments prove the effectiveness of the proposed approach.

  4. Agent-Based Simulation and Analysis of a Defensive UAV Swarm Against an Enemy UAV Swarm

    DTIC Science & Technology

    2011-06-01

    de Investigacion, Programas y Desarrollo de la Armada Armada de Chile CHILE 10. CAPT Jeffrey Kline, USN(ret.) Naval Postgraduate School Monterey, California 91 ...this de - fensive swarm system, an agent-based simulation model is developed, and appropriate designs of experiments and statistical analyses are... de - velopment and implementation of counter UAV technology from readily-available commercial products. The organization leverages the “largest

  5. Absolute Geomagnetic Paleointensity as Recorded by Mafic Dykes of the ~1.98 Ga Bundelkhand Swarm and ~0.75 Ga Malani Igneous Suite from Northern India

    NASA Astrophysics Data System (ADS)

    Piispa, E. J.; Smirnov, A. V.; Pandit, M. K.

    2012-12-01

    Determining the long-term behavior and configuration of the Precambrian geomagnetic field is crucial for understanding the origin and nature of Earth's early geodynamo. However, our knowledge about strength and morphology of the Precambrian geomagnetic field is extremely limited due to paucity of reliable data on the ancient field strength (paleointensity). Information correlating the strength and characteristics of Earth's ancient geomagnetic field can be gained by measuring the paleodirectional and paleointensity properties of Precambrian rocks. We investigated two Proterozoic mafic dyke swarms from the Indian subcontinent: the extensive NW-SE trending 1979±8 Ma (U-Pb) dyke swarm in the Bundelkhand craton and the N-S trending Malani mafic dyke swarm, the latter representing the third and final phase of magmatism in the Malani Igneous Suite. Malani rhyolites have been precisely dated at 771±2 to 751±3 Ma (U - Pb zircon ages). The Malani mafic dykes have been correlated with the ~750 Ma dolerite dykes of Seychelles based on geological and geochemical criteria. The mafic dykes of both studied swarms are vertical to sub-vertical and show little or no evidence of alteration. Detailed paleomagnetic studies, using both thermal and alternating field demagnetization, revealed the presence of stable dual-polarity magnetic component for both dyke swarms. The primary nature of the magnetization is supported by positive baked contact tests. Typically, the characteristic magnetization is single component with narrow unblocking temperature spectra between ~500°C and 550-570°C, with remanence carried by small PSD magnetite or low-Ti titanomagnetite. Absolute paleointensities of these dyke swarms were obtained by two different heating based methods: multiple specimen domain-state corrected (MSP-DSC) and Thellier double heating method with alternating infield-zerofield (IZ) and zerofield-infield (ZI) steps. The multiple sample protocol incorporated checks for alteration

  6. Osmotic Pressure in a Bacterial Swarm

    PubMed Central

    Ping, Liyan; Wu, Yilin; Hosu, Basarab G.; Tang, Jay X.; Berg, Howard C.

    2014-01-01

    Using Escherichia coli as a model organism, we studied how water is recruited by a bacterial swarm. A previous analysis of trajectories of small air bubbles revealed a stream of fluid flowing in a clockwise direction ahead of the swarm. A companion study suggested that water moves out of the agar into the swarm in a narrow region centered ∼30 μm from the leading edge of the swarm and then back into the agar (at a smaller rate) in a region centered ∼120 μm back from the leading edge. Presumably, these flows are driven by changes in osmolarity. Here, we utilized green/red fluorescent liposomes as reporters of osmolarity to verify this hypothesis. The stream of fluid that flows in front of the swarm contains osmolytes. Two distinct regions are observed inside the swarm near its leading edge: an outer high-osmolarity band (∼30 mOsm higher than the agar baseline) and an inner low-osmolarity band (isotonic or slightly hypotonic to the agar baseline). This profile supports the fluid-flow model derived from the drift of air bubbles and provides new (to our knowledge) insights into water maintenance in bacterial swarms. High osmotic pressure at the leading edge of the swarm extracts water from the underlying agar and promotes motility. The osmolyte is of high molecular weight and probably is lipopolysaccharide. PMID:25140422

  7. Autonomous and Autonomic Swarms

    NASA Technical Reports Server (NTRS)

    Hinchey, Michael G.; Rash, James L.; Truszkowski, Walter F.; Rouff, Christopher A.; Sterritt, Roy

    2005-01-01

    A watershed in systems engineering is represented by the advent of swarm-based systems that accomplish missions through cooperative action by a (large) group of autonomous individuals each having simple capabilities and no global knowledge of the group s objective. Such systems, with individuals capable of surviving in hostile environments, pose unprecedented challenges to system developers. Design and testing and verification at much higher levels will be required, together with the corresponding tools, to bring such systems to fruition. Concepts for possible future NASA space exploration missions include autonomous, autonomic swarms. Engineering swarm-based missions begins with understanding autonomy and autonomicity and how to design, test, and verify systems that have those properties and, simultaneously, the capability to accomplish prescribed mission goals. Formal methods-based technologies, both projected and in development, are described in terms of their potential utility to swarm-based system developers.

  8. Swarming: flexible roaming plans.

    PubMed

    Partridge, Jonathan D; Harshey, Rasika M

    2013-03-01

    Movement over an agar surface via swarming motility is subject to formidable challenges not encountered during swimming. Bacteria display a great deal of flexibility in coping with these challenges, which include attracting water to the surface, overcoming frictional forces, and reducing surface tension. Bacteria that swarm on "hard" agar surfaces (robust swarmers) display a hyperflagellated and hyperelongated morphology. Bacteria requiring a "softer" agar surface (temperate swarmers) do not exhibit such a dramatic morphology. For polarly flagellated robust swarmers, there is good evidence that restriction of flagellar rotation somehow signals the induction of a large number of lateral flagella, but this scenario is apparently not relevant to temperate swarmers. Swarming bacteria can be further subdivided by their requirement for multiple stators (Mot proteins) or a stator-associated protein (FliL), secretion of essential polysaccharides, cell density-dependent gene regulation including surfactant synthesis, a functional chemotaxis signaling pathway, appropriate cyclic (c)-di-GMP levels, induction of virulence determinants, and various nutritional requirements such as iron limitation or nitrate availability. Swarming strategies are as diverse as the bacteria that utilize them. The strength of these numerous designs stems from the vantage point they offer for understanding mechanisms for effective colonization of surface niches, acquisition of pathogenic potential, and identification of environmental signals that regulate swarming. The signature swirling and streaming motion within a swarm is an interesting phenomenon in and of itself, an emergent behavior with properties similar to flocking behavior in diverse systems, including birds and fish, providing a convenient new avenue for modeling such behavior.

  9. Swarming: Flexible Roaming Plans

    PubMed Central

    Partridge, Jonathan D.

    2013-01-01

    Movement over an agar surface via swarming motility is subject to formidable challenges not encountered during swimming. Bacteria display a great deal of flexibility in coping with these challenges, which include attracting water to the surface, overcoming frictional forces, and reducing surface tension. Bacteria that swarm on “hard” agar surfaces (robust swarmers) display a hyperflagellated and hyperelongated morphology. Bacteria requiring a “softer” agar surface (temperate swarmers) do not exhibit such a dramatic morphology. For polarly flagellated robust swarmers, there is good evidence that restriction of flagellar rotation somehow signals the induction of a large number of lateral flagella, but this scenario is apparently not relevant to temperate swarmers. Swarming bacteria can be further subdivided by their requirement for multiple stators (Mot proteins) or a stator-associated protein (FliL), secretion of essential polysaccharides, cell density-dependent gene regulation including surfactant synthesis, a functional chemotaxis signaling pathway, appropriate cyclic (c)-di-GMP levels, induction of virulence determinants, and various nutritional requirements such as iron limitation or nitrate availability. Swarming strategies are as diverse as the bacteria that utilize them. The strength of these numerous designs stems from the vantage point they offer for understanding mechanisms for effective colonization of surface niches, acquisition of pathogenic potential, and identification of environmental signals that regulate swarming. The signature swirling and streaming motion within a swarm is an interesting phenomenon in and of itself, an emergent behavior with properties similar to flocking behavior in diverse systems, including birds and fish, providing a convenient new avenue for modeling such behavior. PMID:23264580

  10. Visualization of Biosurfactant Film Flow in a Bacillus subtilis Swarm Colony on an Agar Plate

    PubMed Central

    Kim, Kyunghoon; Kim, Jung Kyung

    2015-01-01

    Collective bacterial dynamics plays a crucial role in colony development. Although many research groups have studied the behavior of fluidic swarm colonies, the detailed mechanics of its motion remains elusive. Here, we developed a visualization method using submicron fluorescent beads for investigating the flow field in a thin layer of fluid that covers a Bacillus subtilis swarm colony growing on an agar plate. The beads were initially embedded in the agar plate and subsequently distributed spontaneously at the upper surface of the expanding colony. We conducted long-term live cell imaging of the B. subtilis colony using the fluorescent tracers, and obtained high-resolution velocity maps of microscale vortices in the swarm colony using particle image velocimetry. A distinct periodic fluctuation in the average speed and vorticity of flow in swarm colony was observed at the inner region of the colony, and correlated with the switch between bacterial swarming and growth phases. At the advancing edge of the colony, both the magnitudes of velocity and vorticity of flow in swarm colony were inversely correlated with the spreading speed of the swarm edge. The advanced imaging tool developed in this study would facilitate further understanding of the effect of micro vortices in swarm colony on the collective dynamics of bacteria. PMID:26343634

  11. Visualization of Biosurfactant Film Flow in a Bacillus subtilis Swarm Colony on an Agar Plate.

    PubMed

    Kim, Kyunghoon; Kim, Jung Kyung

    2015-08-26

    Collective bacterial dynamics plays a crucial role in colony development. Although many research groups have studied the behavior of fluidic swarm colonies, the detailed mechanics of its motion remains elusive. Here, we developed a visualization method using submicron fluorescent beads for investigating the flow field in a thin layer of fluid that covers a Bacillus subtilis swarm colony growing on an agar plate. The beads were initially embedded in the agar plate and subsequently distributed spontaneously at the upper surface of the expanding colony. We conducted long-term live cell imaging of the B. subtilis colony using the fluorescent tracers, and obtained high-resolution velocity maps of microscale vortices in the swarm colony using particle image velocimetry. A distinct periodic fluctuation in the average speed and vorticity of flow in swarm colony was observed at the inner region of the colony, and correlated with the switch between bacterial swarming and growth phases. At the advancing edge of the colony, both the magnitudes of velocity and vorticity of flow in swarm colony were inversely correlated with the spreading speed of the swarm edge. The advanced imaging tool developed in this study would facilitate further understanding of the effect of micro vortices in swarm colony on the collective dynamics of bacteria.

  12. Frog Swarms: Earthquake Precursors or False Alarms?

    PubMed Central

    Grant, Rachel A.; Conlan, Hilary

    2013-01-01

    juvenile animals migrating away from their breeding pond, after a fruitful reproductive season. As amphibian populations undergo large fluctuations in numbers from year to year, this phenomenon will not occur on a yearly basis but will depend on successful reproduction, which is related to numerous climatic and geophysical factors. Hence, most large swarms of amphibians, particularly those involving very small frogs and occurring in late spring or summer, are not unusual and should not be considered earthquake precursors. In addition, it is likely that reports of several mass migration of small toads prior to the Great Sichuan Earthquake in 2008 were not linked to the subsequent M = 7.9 event (some occurred at a great distance from the epicentre), and were probably co-incidence. Statistical analysis of the data indicated frog swarms are unlikely to be connected with earthquakes. Reports of unusual behaviour giving rise to earthquake fears should be interpreted with caution, and consultation with experts in the field of earthquake biology is advised. PMID:26479746

  13. Osmotic pressure in a bacterial swarm.

    PubMed

    Ping, Liyan; Wu, Yilin; Hosu, Basarab G; Tang, Jay X; Berg, Howard C

    2014-08-19

    Using Escherichia coli as a model organism, we studied how water is recruited by a bacterial swarm. A previous analysis of trajectories of small air bubbles revealed a stream of fluid flowing in a clockwise direction ahead of the swarm. A companion study suggested that water moves out of the agar into the swarm in a narrow region centered ∼ 30 μm from the leading edge of the swarm and then back into the agar (at a smaller rate) in a region centered ∼ 120 μm back from the leading edge. Presumably, these flows are driven by changes in osmolarity. Here, we utilized green/red fluorescent liposomes as reporters of osmolarity to verify this hypothesis. The stream of fluid that flows in front of the swarm contains osmolytes. Two distinct regions are observed inside the swarm near its leading edge: an outer high-osmolarity band (∼ 30 mOsm higher than the agar baseline) and an inner low-osmolarity band (isotonic or slightly hypotonic to the agar baseline). This profile supports the fluid-flow model derived from the drift of air bubbles and provides new (to our knowledge) insights into water maintenance in bacterial swarms. High osmotic pressure at the leading edge of the swarm extracts water from the underlying agar and promotes motility. The osmolyte is of high molecular weight and probably is lipopolysaccharide. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  14. SODA In Train Swarm Example

    NASA Image and Video Library

    2017-07-13

    SODA, Swarm Orbital Dynamics Advisor, a tool that provides the orbital maneuvers required to achieve a desired type of relative swarm motion for satellite missions. For the in-train swarm type, the objective is to phase the satellites ahead and behind one another to achieve a string-of-pearls relative position configuration. SODA maneuvers each satellite by performing a two-impulse elliptical transfer orbit from and back to the same orbit, known as a phasing maneuver.

  15. Swarm robotics and complex behaviour of continuum material

    NASA Astrophysics Data System (ADS)

    dell'Erba, Ramiro

    2018-05-01

    In swarm robotics, just as for an animal swarm in nature, one of the aims is to reach and maintain a desired configuration. One of the possibilities for the team, to reach this aim, is to see what its neighbours are doing. This approach generates a rules system governing the movement of the single robot just by reference to neighbour's motion. The same approach is used in position-based dynamics to simulate behaviour of complex continuum materials under deformation. Therefore, in some previous works, we have considered a two-dimensional lattice of particles and calculated its time evolution by using a rules system derived from our experience in swarm robotics. The new position of a particle, like the element of a swarm, is determined by the spatial position of the other particles. No dynamic is considered, but it can be thought as being hidden in the behaviour rules. This method has given good results in some simple situations reproducing the behaviour of deformable bodies under imposed strain. In this paper we try to stress our model to highlight its limits and how they can be improved. Some other, more complex, examples are computed and discussed. Shear test, different lattices, different fracture mechanisms and ASTM shape sample behaviour have been investigated by the software tool we have developed.

  16. Collective navigation of cargo-carrying swarms

    PubMed Central

    Shklarsh, Adi; Finkelshtein, Alin; Ariel, Gil; Kalisman, Oren; Ingham, Colin; Ben-Jacob, Eshel

    2012-01-01

    Much effort has been devoted to the study of swarming and collective navigation of micro-organisms, insects, fish, birds and other organisms, as well as multi-agent simulations and to the study of real robots. It is well known that insect swarms can carry cargo. The studies here are motivated by a less well-known phenomenon: cargo transport by bacteria swarms. We begin with a concise review of how bacteria swarms carry natural, micrometre-scale objects larger than the bacteria (e.g. fungal spores) as well as man-made beads and capsules (for drug delivery). A comparison of the trajectories of virtual beads in simulations (using different putative coupling between the virtual beads and the bacteria) with the observed trajectories of transported fungal spores implies the existence of adaptable coupling. Motivated by these observations, we devised new, multi-agent-based studies of cargo transport by agent swarms. As a first step, we extended previous modelling of collective navigation of simple bacteria-inspired agents in complex terrain, using three putative models of agent–cargo coupling. We found that cargo-carrying swarms can navigate efficiently in a complex landscape. We further investigated how the stability, elasticity and other features of agent–cargo bonds influence the collective motion and the transport of the cargo, and found sharp phase shifts and dual successful strategies for cargo delivery. Further understanding of such mechanisms may provide valuable clues to understand cargo-transport by smart swarms of other organisms as well as by man-made swarming robots. PMID:24312731

  17. Composite Particle Swarm Optimizer With Historical Memory for Function Optimization.

    PubMed

    Li, Jie; Zhang, JunQi; Jiang, ChangJun; Zhou, MengChu

    2015-10-01

    Particle swarm optimization (PSO) algorithm is a population-based stochastic optimization technique. It is characterized by the collaborative search in which each particle is attracted toward the global best position (gbest) in the swarm and its own best position (pbest). However, all of particles' historical promising pbests in PSO are lost except their current pbests. In order to solve this problem, this paper proposes a novel composite PSO algorithm, called historical memory-based PSO (HMPSO), which uses an estimation of distribution algorithm to estimate and preserve the distribution information of particles' historical promising pbests. Each particle has three candidate positions, which are generated from the historical memory, particles' current pbests, and the swarm's gbest. Then the best candidate position is adopted. Experiments on 28 CEC2013 benchmark functions demonstrate the superiority of HMPSO over other algorithms.

  18. Swarm.

    ERIC Educational Resources Information Center

    Petersen, Hugh

    2002-01-01

    Describes an eighth grade art project for which students created bug swarms on scratchboard. Explains that the project also teaches students about design principles, such as balance. Discusses how the students created their drawings. (CMK)

  19. Self-organized sorting limits behavioral variability in swarms

    NASA Astrophysics Data System (ADS)

    Copenhagen, Katherine; Quint, David A.; Gopinathan, Ajay

    2016-08-01

    Swarming is a phenomenon where collective motion arises from simple local interactions between typically identical individuals. Here, we investigate the effects of variability in behavior among the agents in finite swarms with both alignment and cohesive interactions. We show that swarming is abolished above a critical fraction of non-aligners who do not participate in alignment. In certain regimes, however, swarms above the critical threshold can dynamically reorganize and sort out excess non-aligners to maintain the average fraction close to the critical value. This persists even in swarms with a distribution of alignment interactions, suggesting a simple, robust and efficient mechanism that allows heterogeneously mixed populations to naturally regulate their composition and remain in a collective swarming state or even differentiate among behavioral phenotypes. We show that, for evolving swarms, this self-organized sorting behavior can couple to the evolutionary dynamics leading to new evolutionarily stable equilibrium populations set by the physical swarm parameters.

  20. Self-organized sorting limits behavioral variability in swarms

    PubMed Central

    Copenhagen, Katherine; Quint, David A.; Gopinathan, Ajay

    2016-01-01

    Swarming is a phenomenon where collective motion arises from simple local interactions between typically identical individuals. Here, we investigate the effects of variability in behavior among the agents in finite swarms with both alignment and cohesive interactions. We show that swarming is abolished above a critical fraction of non-aligners who do not participate in alignment. In certain regimes, however, swarms above the critical threshold can dynamically reorganize and sort out excess non-aligners to maintain the average fraction close to the critical value. This persists even in swarms with a distribution of alignment interactions, suggesting a simple, robust and efficient mechanism that allows heterogeneously mixed populations to naturally regulate their composition and remain in a collective swarming state or even differentiate among behavioral phenotypes. We show that, for evolving swarms, this self-organized sorting behavior can couple to the evolutionary dynamics leading to new evolutionarily stable equilibrium populations set by the physical swarm parameters. PMID:27550316

  1. Scouts behave as streakers in honeybee swarms

    NASA Astrophysics Data System (ADS)

    Greggers, Uwe; Schöning, Caspar; Degen, Jacqueline; Menzel, Randolf

    2013-08-01

    Harmonic radar tracking was used to record the flights of scout bees during takeoff and initial flight path of two honeybee swarms. One swarm remained intact and performed a full flight to a destination beyond the range of the harmonic radar, while a second swarm disintegrated within the range of the radar and most of the bees returned to the queen. The initial stretch of the full flight is characterized by accelerating speed, whereas the disintegrating swarm flew steadily at low speed. The two scouts in the swarm displaying full flight performed characteristic flight maneuvers. They flew at high speed when traveling in the direction of their destination and slowed down or returned over short stretches at low speed. Scouts in the disintegrating swarm did not exhibit the same kind of characteristic flight performance. Our data support the streaker bee hypothesis proposing that scout bees guide the swarm by traveling at high speed in the direction of the new nest site for short stretches of flight and slowing down when reversing flight direction.

  2. Type IV pili interactions promote intercellular association and moderate swarming of Pseudomonas aeruginosa

    PubMed Central

    Anyan, Morgen E.; Amiri, Aboutaleb; Harvey, Cameron W.; Tierra, Giordano; Morales-Soto, Nydia; Driscoll, Callan M.; Alber, Mark S.; Shrout, Joshua D.

    2014-01-01

    Pseudomonas aeruginosa is a ubiquitous bacterium that survives in many environments, including as an acute and chronic pathogen in humans. Substantial evidence shows that P. aeruginosa behavior is affected by its motility, and appendages known as flagella and type IV pili (TFP) are known to confer such motility. The role these appendages play when not facilitating motility or attachment, however, is unclear. Here we discern a passive intercellular role of TFP during flagellar-mediated swarming of P. aeruginosa that does not require TFP extension or retraction. We studied swarming at the cellular level using a combination of laboratory experiments and computational simulations to explain the resultant patterns of cells imaged from in vitro swarms. Namely, we used a computational model to simulate swarming and to probe for individual cell behavior that cannot currently be otherwise measured. Our simulations showed that TFP of swarming P. aeruginosa should be distributed all over the cell and that TFP−TFP interactions between cells should be a dominant mechanism that promotes cell−cell interaction, limits lone cell movement, and slows swarm expansion. This predicted physical mechanism involving TFP was confirmed in vitro using pairwise mixtures of strains with and without TFP where cells without TFP separate from cells with TFP. While TFP slow swarm expansion, we show in vitro that TFP help alter collective motion to avoid toxic compounds such as the antibiotic carbenicillin. Thus, TFP physically affect P. aeruginosa swarming by actively promoting cell−cell association and directional collective motion within motile groups to aid their survival. PMID:25468980

  3. Independent validation of Swarm Level 2 magnetic field products and `Quick Look' for Level 1b data

    NASA Astrophysics Data System (ADS)

    Beggan, Ciarán D.; Macmillan, Susan; Hamilton, Brian; Thomson, Alan W. P.

    2013-11-01

    Magnetic field models are produced on behalf of the European Space Agency (ESA) by an independent scientific consortium known as the Swarm Satellite Constellation Application and Research Facility (SCARF), through the Level 2 Processor (L2PS). The consortium primarily produces magnetic field models for the core, lithosphere, ionosphere and magnetosphere. Typically, for each magnetic product, two magnetic field models are produced in separate chains using complementary data selection and processing techniques. Hence, the magnetic field models from the complementary processing chains will be similar but not identical. The final step in the overall L2PS therefore involves inspection and validation of the magnetic field models against each other and against data from (semi-) independent sources (e.g. ground observatories). We describe the validation steps for each magnetic field product and the comparison against independent datasets, and we show examples of the output of the validation. In addition, the L2PS also produces a daily set of `Quick Look' output graphics and statistics to monitor the overall quality of Level 1b data issued by ESA. We describe the outputs of the `Quick Look' chain.

  4. Dynamic scaling in natural swarms

    NASA Astrophysics Data System (ADS)

    Cavagna, Andrea; Conti, Daniele; Creato, Chiara; Del Castello, Lorenzo; Giardina, Irene; Grigera, Tomas S.; Melillo, Stefania; Parisi, Leonardo; Viale, Massimiliano

    2017-09-01

    Collective behaviour in biological systems presents theoretical challenges beyond the borders of classical statistical physics. The lack of concepts such as scaling and renormalization is particularly problematic, as it forces us to negotiate details whose relevance is often hard to assess. In an attempt to improve this situation, we present here experimental evidence of the emergence of dynamic scaling laws in natural swarms of midges. We find that spatio-temporal correlation functions in different swarms can be rescaled by using a single characteristic time, which grows with the correlation length with a dynamical critical exponent z ~ 1, a value not found in any other standard statistical model. To check whether out-of-equilibrium effects may be responsible for this anomalous exponent, we run simulations of the simplest model of self-propelled particles and find z ~ 2, suggesting that natural swarms belong to a novel dynamic universality class. This conclusion is strengthened by experimental evidence of the presence of non-dissipative modes in the relaxation, indicating that previously overlooked inertial effects are needed to describe swarm dynamics. The absence of a purely dissipative regime suggests that natural swarms undergo a near-critical censorship of hydrodynamics.

  5. Foreshocks and Swarms of Induced Seismicity in Southern Kansas

    NASA Astrophysics Data System (ADS)

    Rubinstein, J. L.; Skoumal, R.; Dougherty, S. L.; Cochran, E. S.

    2017-12-01

    Protracted foreshock sequences and swarm-like behavior have been observed for a number of induced earthquakes, including Guy-Greenbrier, Raton Basin, Youngstown, and the Fairview sequences. Many other induced earthquake sequences have seen intermittent seismicity before the largest earthquake in the sequence. The prevalence of foreshocks and swarms as part of induced earthquake sequences likely reflects the ongoing increase in and expansion of fluid pressure in a region, such that higher magnitude events will occur once a large region has been sufficiently influenced by fluid injection. Diffusion of fluid pressure has been observed in some induced seismicity sequences whereby seismicity moves away from an injector, making the earlier events foreshocks. Natural seismicity in other parts of the central and eastern United States experience far fewer foreshock sequences. This is additional evidence that injection-caused increase in fluid pressure is the reason that these foreshocks and swarms are occurring. To better understand foreshocks and swarm-like behavior of induced seismicity, we examine the seismicity in southern Kansas from 2014-2017. The seismic network in southern Kansas represents the densest, longest-running (>3.5 years) network with publicly available data in near-real-time in an area of induced seismicity. This has yielded a magnitude of completeness of 2.0, which is lower than in most other areas of induced seismicity. We further enhance this catalog by using template matching. With this expanded catalog, we identify and examine foreshock and swarm behavior for all M3.5 and larger mainshocks in Kansas.

  6. Foraging swarms as Nash equilibria of dynamic games.

    PubMed

    Özgüler, Arif Bülent; Yildiz, Aykut

    2014-06-01

    The question of whether foraging swarms can form as a result of a noncooperative game played by individuals is shown here to have an affirmative answer. A dynamic game played by N agents in 1-D motion is introduced and models, for instance, a foraging ant colony. Each agent controls its velocity to minimize its total work done in a finite time interval. The game is shown to have a unique Nash equilibrium under two different foraging location specifications, and both equilibria display many features of a foraging swarm behavior observed in biological swarms. Explicit expressions are derived for pairwise distances between individuals of the swarm, swarm size, and swarm center location during foraging.

  7. Electrical conductivity of the Earth's mantle after one year of SWARM magnetic field measurements

    NASA Astrophysics Data System (ADS)

    Civet, François; Thebault, Erwan; Verhoeven, Olivier; Langlais, Benoit; Saturnino, Diana

    2015-04-01

    We present a global EM induction study using L1b Swarm satellite magnetic field measurements data down to a depth of 2000 km. Starting from raw measurements, we first derive a model for the main magnetic field, correct the data for a lithospheric field model, and further select the data to reduce the contributions of the ionospheric field. These computations allowed us to keep a full control on the data processes. We correct residual field from outliers and estimate the spherical harmonic coefficients of the transient field for periods between 2 and 256 days. We used full latitude range and all local times to keep a maximum amount of data. We perform a Bayesian inversion and construct a Markov chain during which model parameters are randomly updated at each iteration. We first consider regular layers of equal thickness and extra layers are added where conductivity contrast between successive layers exceed a threshold value. The mean and maximum likelihood of the electrical conductivity profile is then estimated from the probability density function. The obtained profile particularly shows a conductivity jump in the 600-700 km depth range, consistent with the olivine phase transition at 660 km depth. Our study is the first one to show such a conductivity increase in this depth range without any a priori informations on the internal strucutres. Assuming a pyrolitic mantle composition, this profile is interpreted in terms of temperature variations in the depth range where the probability density function is the narrowest. We finally obtained a temperature gradient in the lower mantle close to adiabatic.

  8. Capture of planetesimals into a circumterrestrial swarm

    NASA Technical Reports Server (NTRS)

    Weidenschilling, S. J.

    1984-01-01

    The lunar origin model considered involves processing of protolunar material through a circumterrestrial swarm of particles. Once such a swarm has formed, it can gain mass by capturing infalling planetesimals and ejecta from giant impacts on the Earth, although the angular momentum supply from these sources remains a problem. Examined is the first stage of formation of a geocentric swarm by capture of planetesimals from initialy heliocentric orbits. The only plausible capture mechanism that is not dependent on very low approach velocities is the mutual collision of planetesimals passing within Earth's sphere of influence. This capture scenario was tested directly by many body numerical integration of planetesimal orbits in near Earth space. Results agree that the systematic contribution of angular momentum is insufficient to maintain an orbiting swarm under heavy bombardment. Thus, a circumterrestrial swarm can be formed rather easily, but is hard to sustain because the mean net angular momentum of a many body swarm is small.

  9. Statistical analysis of geomagnetic field intensity differences between ASM and VFM instruments onboard Swarm constellation

    NASA Astrophysics Data System (ADS)

    De Michelis, Paola; Tozzi, Roberta; Consolini, Giuseppe

    2017-02-01

    From the very first measurements made by the magnetometers onboard Swarm satellites launched by European Space Agency (ESA) in late 2013, it emerged a discrepancy between scalar and vector measurements. An accurate analysis of this phenomenon brought to build an empirical model of the disturbance, highly correlated with the Sun incidence angle, and to correct vector data accordingly. The empirical model adopted by ESA results in a significant decrease in the amplitude of the disturbance affecting VFM measurements so greatly improving the vector magnetic data quality. This study is focused on the characterization of the difference between magnetic field intensity measured by the absolute scalar magnetometer (ASM) and that reconstructed using the vector field magnetometer (VFM) installed on Swarm constellation. Applying empirical mode decomposition method, we find the intrinsic mode functions (IMFs) associated with ASM-VFM total intensity differences obtained with data both uncorrected and corrected for the disturbance correlated with the Sun incidence angle. Surprisingly, no differences are found in the nature of the IMFs embedded in the analyzed signals, being these IMFs characterized by the same dominant periodicities before and after correction. The effect of correction manifests in the decrease in the energy associated with some IMFs contributing to corrected data. Some IMFs identified by analyzing the ASM-VFM intensity discrepancy are characterized by the same dominant periodicities of those obtained by analyzing the temperature fluctuations of the VFM electronic unit. Thus, the disturbance correlated with the Sun incidence angle could be still present in the corrected magnetic data. Furthermore, the ASM-VFM total intensity difference and the VFM electronic unit temperature display a maximal shared information with a time delay that depends on local time. Taken together, these findings may help to relate the features of the observed VFM-ASM total intensity

  10. Improving Vector Evaluated Particle Swarm Optimisation by incorporating nondominated solutions.

    PubMed

    Lim, Kian Sheng; Ibrahim, Zuwairie; Buyamin, Salinda; Ahmad, Anita; Naim, Faradila; Ghazali, Kamarul Hawari; Mokhtar, Norrima

    2013-01-01

    The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm.

  11. Particle Swarm Optimization Toolbox

    NASA Technical Reports Server (NTRS)

    Grant, Michael J.

    2010-01-01

    The Particle Swarm Optimization Toolbox is a library of evolutionary optimization tools developed in the MATLAB environment. The algorithms contained in the library include a genetic algorithm (GA), a single-objective particle swarm optimizer (SOPSO), and a multi-objective particle swarm optimizer (MOPSO). Development focused on both the SOPSO and MOPSO. A GA was included mainly for comparison purposes, and the particle swarm optimizers appeared to perform better for a wide variety of optimization problems. All algorithms are capable of performing unconstrained and constrained optimization. The particle swarm optimizers are capable of performing single and multi-objective optimization. The SOPSO and MOPSO algorithms are based on swarming theory and bird-flocking patterns to search the trade space for the optimal solution or optimal trade in competing objectives. The MOPSO generates Pareto fronts for objectives that are in competition. A GA, based on Darwin evolutionary theory, is also included in the library. The GA consists of individuals that form a population in the design space. The population mates to form offspring at new locations in the design space. These offspring contain traits from both of the parents. The algorithm is based on this combination of traits from parents to hopefully provide an improved solution than either of the original parents. As the algorithm progresses, individuals that hold these optimal traits will emerge as the optimal solutions. Due to the generic design of all optimization algorithms, each algorithm interfaces with a user-supplied objective function. This function serves as a "black-box" to the optimizers in which the only purpose of this function is to evaluate solutions provided by the optimizers. Hence, the user-supplied function can be numerical simulations, analytical functions, etc., since the specific detail of this function is of no concern to the optimizer. These algorithms were originally developed to support entry

  12. Spatial distribution and male mating success of Anopheles gambiae swarms

    PubMed Central

    2011-01-01

    Background Anopheles gambiae mates in flight at particular mating sites over specific landmarks known as swarm markers. The swarms are composed of males; females typically approach a swarm, and leave in copula. This mating aggregation looks like a lek, but appears to lack the component of female choice. To investigate the possible mechanisms promoting the evolution of swarming in this mosquito species, we looked at the variation in mating success between swarms and discussed the factors that structure it in light of the three major lekking models, known as the female preference model, the hotspot model, and the hotshot model. Results We found substantial variation in swarm size and in mating success between swarms. A strong correlation between swarm size and mating success was observed, and consistent with the hotspot model of lek formation, the per capita mating success of individual males did not increase with swarm size. For the spatial distribution of swarms, our results revealed that some display sites were more attractive to both males and females and that females were more attracted to large swarms. While the swarm markers we recognize help us in localizing swarms, they did not account for the variation in swarm size or in the swarm mating success, suggesting that mosquitoes probably are attracted to these markers, but also perceive and respond to other aspects of the swarming site. Conclusions Characterizing the mating system of a species helps understand how this species has evolved and how selective pressures operate on male and female traits. The current study looked at male mating success of An. gambiae and discussed possible factors that account for its variation. We found that swarms of An. gambiae conform to the hotspot model of lek formation. But because swarms may lack the female choice component, we propose that the An. gambiae mating system is a lek-like system that incorporates characteristics pertaining to other mating systems such as scramble

  13. Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions

    PubMed Central

    Lim, Kian Sheng; Ibrahim, Zuwairie; Buyamin, Salinda; Ahmad, Anita; Naim, Faradila; Ghazali, Kamarul Hawari; Mokhtar, Norrima

    2013-01-01

    The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm. PMID:23737718

  14. Ionospheric magnetic signals during conjunctions between ground based and Swarm satellite observations

    NASA Astrophysics Data System (ADS)

    Saturnino, Diana; Olsen, Nils; Finlay, Chris

    2017-04-01

    High-precision magnetic measurements collected by satellites such as Swarm or CHAMP,flying at altitudes between 300 and 800km, allow for improved geomagnetic field modelling. An accurate description of the internal (core and crust) field must account for contributions from other sources, such as the ionosphere and magnetosphere. However, the description of the rapidly changing external field contributions, particularly during the quiet times from which the data are selected, constitutes a major challenge of the construction of such models. Our study attempts to obtain improved knowledge on ionospheric field contributions during quiet times conditions, in particular during night local times. We use two different datasets: ground magnetic observatories time series (obtained below the ionospheric E-layer currents), and Swarm satellites measurements acquired above these currents. First, we remove from the data estimates of the core, lithospheric and large-scale magnetospheric magnetic contributions as given by the CHAOS-6 model, to obtain corrected time series. Then, we focus on the differences of the corrected time series: for a pair of ground magnetic observatories, we determine the time series of the difference, and similarly we determine time series differences at satellite altitude, given by the difference between the Swarm Alpha and Charlie satellites taken in the vicinity of the ground observatory locations. The obtained differences time series are analysed regarding their temporal and spatial scales variations, with emphasis on measurements during night local times.

  15. On the Spatio-Temporal Variability of Field-Aligned Currents Observed with the Swarm Satellite Constellation: Implications for the Energetics of Magnetosphere-Ionosphere Coupling

    NASA Astrophysics Data System (ADS)

    Pakhotin, I.; Mann, I. R.; Forsyth, C.; Rae, J.; Burchill, J. K.; Knudsen, D. J.; Murphy, K. R.; Gjerloev, J. W.; Ozeke, L.; Balasis, G.; Daglis, I. A.

    2016-12-01

    With the advent of the Swarm mission with its multi-satellite capacity, it became possible for the first time to make systematic close separation multi-satellite measurements of the magnetic fields associated with field-aligned currents (FACs) at a 50 Hz cadence using fluxgate magnetometers. Initial studies have revealed an even greater level of detail and complexity and spatio-temporal non-stationarity than previously understood. On inter-satellite separation scales of 10 seconds along-track and <120 km cross-track, the peak-to-peak magnitudes of the small scale and poorly correlated inter-spacecraft magnetic field fluctuations can reach tens to hundreds of nanoteslas. These magnitudes are directly comparable to those associated with larger scale magnetic perturbations such as the global scale Region 1 and 2 FAC systems characterised by Iijima and Potemra 40 years ago. We evaluate the impact of these smaller scale magnetic perturbations relative to the larger scale FAC systems statistically as a function of the total number of FAC crossings observed, and as a function of geomagnetic indices, spatial location, and season. Further case studies incorporating Swarm electric field measurements enable estimates of the Poynting flux associated with the small scale and non-stationary magnetic fields. We interpret the small scale structures as Alfvenic, suggesting that Alfven waves play a much larger and more energetically significant role in magnetosphere-ionosphere coupling than previously thought. We further examine what causes such high variability among low-Earth orbit FAC systems to be observed under some conditions but not in others.

  16. Natural or Induced: Identifying Natural and Induced Swarms from Pre-production and Co-production Microseismic Catalogs at the Coso Geothermal Field

    USGS Publications Warehouse

    Schoenball, Martin; Kaven, Joern; Glen, Jonathan M. G.; Davatzes, Nicholas C.

    2015-01-01

    Increased levels of seismicity coinciding with injection of reservoir fluids have prompted interest in methods to distinguish induced from natural seismicity. Discrimination between induced and natural seismicity is especially difficult in areas that have high levels of natural seismicity, such as the geothermal fields at the Salton Sea and Coso, both in California. Both areas show swarm-like sequences that could be related to natural, deep fluid migration as part of the natural hydrothermal system. Therefore, swarms often have spatio-temporal patterns that resemble fluid-induced seismicity, and might possibly share other characteristics. The Coso Geothermal Field and its surroundings is one of the most seismically active areas in California with a large proportion of its activity occurring as seismic swarms. Here we analyze clustered seismicity in and surrounding the currently produced reservoir comparatively for pre-production and co-production periods. We perform a cluster analysis, based on the inter-event distance in a space-time-energy domain to identify notable earthquake sequences. For each event j, the closest previous event i is identified and their relationship categorized. If this nearest neighbor’s distance is below a threshold based on the local minimum of the bimodal distribution of nearest neighbor distances, then the event j is included in the cluster as a child to this parent event i. If it is above the threshold, event j begins a new cluster. This process identifies subsets of events whose nearest neighbor distances and relative timing qualify as a cluster as well as a characterizing the parent-child relationships among events in the cluster. We apply this method to three different catalogs: (1) a two-year microseismic survey of the Coso geothermal area that was acquired before exploration drilling in the area began; (2) the HYS_catalog_2013 that contains 52,000 double-difference relocated events and covers the years 1981 to 2013; and (3) a

  17. Emergent Runaway into an Avoidance Area in a Swarm of Soldier Crabs

    PubMed Central

    Murakami, Hisashi; Tomaru, Takenori; Nishiyama, Yuta; Moriyama, Toru; Niizato, Takayuki; Gunji, Yukio-Pegio

    2014-01-01

    Emergent behavior that arises from a mass effect is one of the most striking aspects of collective animal groups. Investigating such behavior would be important in order to understand how individuals interact with their neighbors. Although there are many experiments that have used collective animals to investigate social learning or conflict between individuals and society such as that between a fish and a school, reports on mass effects are rare. In this study, we show that a swarm of soldier crabs could spontaneously enter a water pool, which are usually avoided, by forming densely populated part of a swarm at the edge of the water pool. Moreover, we show that the observed behavior can be explained by the model of collective behavior based on inherent noise that is individuals’ different velocities in a directed group. Our results suggest that inherent noise, which is widely seen in collective animals, can contribute to formation and/or maintenance of a swarm and that the dense swarm can enter the pool by means of enhanced inherent noise. PMID:24839970

  18. [Swarming phenomenon of an aeromonas spec (author's transl)].

    PubMed

    Müller, H E; Lenz, W

    1975-05-01

    A genuine swarming phenomenon, such as has previously been known to occur in Proteus, Bacillus and Clostridium species only, was observed in an Aeromonas species. Fig. 1 shows the terraced swarming zones of the Aeromonas species on nutrient agar. The swarming rate, expressed as the growth of the swarming zone per time unit, was measured to be 70-120 mum/min on blood agar at 30 degrees C. The swarming could be inhibited by incubation at 37 degrees C (Table 2), by low saline concentrations (Table 3) as well as by addition of 4-nitro-phenylglycerol to the medium (Table 4). A DIENES-phenomenon between the swarming zones of Proteus strains and that of the Aeromonas species could not be observed (Fig. 2). The manner of swarming as seen in phase contrast microscopy was the same kind as that of Proteus. Furthermore, it could be shown by means of light- and electronmicroscopical investigations that the swarming phenomenon is connected with changes in the cell morphology and the form of flagellation (Figs. 4 and 5). Whereas in broth cultures (Fig. 3) as well as in the centre of colonies on solid media (Fig. 5a) the cells appeared as cocoid rods with polar flagellation, they developed elongated forms at the edge of the swarming zone, which - either in addition to or devoid of the polar flagella - were peritrichously populated with thin, flagella-like filaments (Figs. tb, 6, 7 and 8). The discussion deals with the various forms of bacterial surface translocation and investigates into the role of peritrichous flagella or fimbriae in the swarming phenomenon.

  19. Proteus mirabilis interkingdom swarming signals attract blow flies

    PubMed Central

    Ma, Qun; Fonseca, Alicia; Liu, Wenqi; Fields, Andrew T; Pimsler, Meaghan L; Spindola, Aline F; Tarone, Aaron M; Crippen, Tawni L; Tomberlin, Jeffery K; Wood, Thomas K

    2012-01-01

    Flies transport specific bacteria with their larvae that provide a wider range of nutrients for those bacteria. Our hypothesis was that this symbiotic interaction may depend on interkingdom signaling. We obtained Proteus mirabilis from the salivary glands of the blow fly Lucilia sericata; this strain swarmed significantly and produced a strong odor that attracts blow flies. To identify the putative interkingdom signals for the bacterium and flies, we reasoned that as swarming is used by this bacterium to cover the food resource and requires bacterial signaling, the same bacterial signals used for swarming may be used to communicate with blow flies. Using transposon mutagenesis, we identified six novel genes for swarming (ureR, fis, hybG, zapB, fadE and PROSTU_03490), then, confirming our hypothesis, we discovered that fly attractants, lactic acid, phenol, NaOH, KOH and ammonia, restore swarming for cells with the swarming mutations. Hence, compounds produced by the bacterium that attract flies also are utilized for swarming. In addition, bacteria with the swarming mutation rfaL attracted fewer blow flies and reduced the number of eggs laid by the flies. Therefore, we have identified several interkingdom signals between P. mirabilis and blow flies. PMID:22237540

  20. Robot Swarms

    NASA Technical Reports Server (NTRS)

    Morring, Frank, Jr.

    2005-01-01

    Engineers and interns at this NASA field center are building the prototype of a robotic rover that could go where no wheeled rover has gone before-into the dark cold craters at the lunar poles and across the Moon s rugged highlands-like a walking tetrahedron. With NASA pushing to meet President Bush's new exploration objectives, the robots taking shape here today could be on the Moon in a decade. In the longer term, the concept could lead to shape-shifting robot swarms designed to explore distant planetary surfaces in advance of humans. "If you look at all of NASA s projections of the future, anyone s projections of the space program, they re all rigid-body architecture," says Steven Curtis, principal investigator on the effort. "This is not rigid-body. The whole key here is flexibility and reconfigurability with a capital R."

  1. A meta-analysis of human-system interfaces in unmanned aerial vehicle (UAV) swarm management.

    PubMed

    Hocraffer, Amy; Nam, Chang S

    2017-01-01

    A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm's level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. A minimal model of predator–swarm interactions

    PubMed Central

    Chen, Yuxin; Kolokolnikov, Theodore

    2014-01-01

    We propose a minimal model of predator–swarm interactions which captures many of the essential dynamics observed in nature. Different outcomes are observed depending on the predator strength. For a ‘weak’ predator, the swarm is able to escape the predator completely. As the strength is increased, the predator is able to catch up with the swarm as a whole, but the individual prey is able to escape by ‘confusing’ the predator: the prey forms a ring with the predator at the centre. For higher predator strength, complex chasing dynamics are observed which can become chaotic. For even higher strength, the predator is able to successfully capture the prey. Our model is simple enough to be amenable to a full mathematical analysis, which is used to predict the shape of the swarm as well as the resulting predator–prey dynamics as a function of model parameters. We show that, as the predator strength is increased, there is a transition (owing to a Hopf bifurcation) from confusion state to chasing dynamics, and we compute the threshold analytically. Our analysis indicates that the swarming behaviour is not helpful in avoiding the predator, suggesting that there are other reasons why the species may swarm. The complex shape of the swarm in our model during the chasing dynamics is similar to the shape of a flock of sheep avoiding a shepherd. PMID:24598204

  3. A minimal model of predator-swarm interactions.

    PubMed

    Chen, Yuxin; Kolokolnikov, Theodore

    2014-05-06

    We propose a minimal model of predator-swarm interactions which captures many of the essential dynamics observed in nature. Different outcomes are observed depending on the predator strength. For a 'weak' predator, the swarm is able to escape the predator completely. As the strength is increased, the predator is able to catch up with the swarm as a whole, but the individual prey is able to escape by 'confusing' the predator: the prey forms a ring with the predator at the centre. For higher predator strength, complex chasing dynamics are observed which can become chaotic. For even higher strength, the predator is able to successfully capture the prey. Our model is simple enough to be amenable to a full mathematical analysis, which is used to predict the shape of the swarm as well as the resulting predator-prey dynamics as a function of model parameters. We show that, as the predator strength is increased, there is a transition (owing to a Hopf bifurcation) from confusion state to chasing dynamics, and we compute the threshold analytically. Our analysis indicates that the swarming behaviour is not helpful in avoiding the predator, suggesting that there are other reasons why the species may swarm. The complex shape of the swarm in our model during the chasing dynamics is similar to the shape of a flock of sheep avoiding a shepherd.

  4. Long-range Acoustic Interactions in Insect Swarms - An Adaptive Gravity Model

    NASA Astrophysics Data System (ADS)

    Gorbonos, Dan; Ianconescu, Reuven; Puckett, James G.; Ni, Rui; Ouellette, Nicholas T.; Gov, Nir S.

    The collective motion of groups of animals emerges from the net effect of the interactions between individual members of the group. In many cases, such as birds, fish, or ungulates, these interactions are mediated by sensory stimuli that predominantly arise from nearby neighbors. But not all stimuli in animal groups are short range. We consider mating swarms of midges, which are thought to interact primarily via long-range acoustic stimuli. We exploit the similarity in form between the decay of acoustic and gravitational sources to build a model for swarm behavior. By accounting for the adaptive nature of the midges' acoustic sensing, we show that our ``adaptive gravity'' model makes mean-field predictions that agree well with experimental observations of laboratory swarms. Our results highlight the role of sensory mechanisms and interaction range in collective animal behavior. Additionally, the adaptive interactions open a new class of equations of motion, which may appear in other biological contexts.

  5. Long-range Acoustic Interactions in Insect Swarms: An Adaptive Gravity Model

    NASA Astrophysics Data System (ADS)

    Gorbonos, Dan; Ianconescu, Reuven; Puckett, James G.; Ni, Rui; Ouellette, Nicholas T.; Gov, Nir S.

    The collective motion of groups of animals emerges from the net effect of the interactions between individual members of the group. In many cases, such as birds, fish, or ungulates, these interactions are mediated by sensory stimuli that predominantly arise from nearby neighbors. But not all stimuli in animal groups are short range. Here, we consider mating swarms of midges, which interact primarily via long-range acoustic stimuli. We exploit the similarity in form between the decay of acoustic and gravitational sources to build a model for swarm behavior. By accounting for the adaptive nature of the midges' acoustic sensing, we show that our ``adaptive gravity'' model makes mean-field predictions that agree well with experimental observations of laboratory swarms. Our results highlight the role of sensory mechanisms and interaction range in collective animal behavior. The adaptive interactions that we present here open a new class of equations of motion, which may appear in other biological contexts.

  6. Long-range acoustic interactions in insect swarms: an adaptive gravity model

    NASA Astrophysics Data System (ADS)

    Gorbonos, Dan; Ianconescu, Reuven; Puckett, James G.; Ni, Rui; Ouellette, Nicholas T.; Gov, Nir S.

    2016-07-01

    The collective motion of groups of animals emerges from the net effect of the interactions between individual members of the group. In many cases, such as birds, fish, or ungulates, these interactions are mediated by sensory stimuli that predominantly arise from nearby neighbors. But not all stimuli in animal groups are short range. Here, we consider mating swarms of midges, which are thought to interact primarily via long-range acoustic stimuli. We exploit the similarity in form between the decay of acoustic and gravitational sources to build a model for swarm behavior. By accounting for the adaptive nature of the midges’ acoustic sensing, we show that our ‘adaptive gravity’ model makes mean-field predictions that agree well with experimental observations of laboratory swarms. Our results highlight the role of sensory mechanisms and interaction range in collective animal behavior. Additionally, the adaptive interactions that we present here open a new class of equations of motion, which may appear in other biological contexts.

  7. A Survey of Formal Methods for Intelligent Swarms

    NASA Technical Reports Server (NTRS)

    Truszkowski, Walt; Rash, James; Hinchey, Mike; Rouff, Chrustopher A.

    2004-01-01

    Swarms of intelligent autonomous spacecraft, involving complex behaviors and interactions, are being proposed for future space exploration missions. Such missions provide greater flexibility and offer the possibility of gathering more science data than traditional single spacecraft missions. The emergent properties of swarms make these missions powerful, but simultaneously far more difficult to design, and to assure that the proper behaviors will emerge. These missions are also considerably more complex than previous types of missions, and NASA, like other organizations, has little experience in developing or in verifying and validating these types of missions. A significant challenge when verifying and validating swarms of intelligent interacting agents is how to determine that the possible exponential interactions and emergent behaviors are producing the desired results. Assuring correct behavior and interactions of swarms will be critical to mission success. The Autonomous Nano Technology Swarm (ANTS) mission is an example of one of the swarm types of missions NASA is considering. The ANTS mission will use a swarm of picospacecraft that will fly from Earth orbit to the Asteroid Belt. Using an insect colony analogy, ANTS will be composed of specialized workers for asteroid exploration. Exploration would consist of cataloguing the mass, density, morphology, and chemical composition of the asteroids, including any anomalous concentrations of specific minerals. To perform this task, ANTS would carry miniaturized instruments, such as imagers, spectrometers, and detectors. Since ANTS and other similar missions are going to consist of autonomous spacecraft that may be out of contact with the earth for extended periods of time, and have low bandwidths due to weight constraints, it will be difficult to observe improper behavior and to correct any errors after launch. Providing V&V (verification and validation) for this type of mission is new to NASA, and represents the

  8. Scaling and spatial complementarity of tectonic earthquake swarms

    NASA Astrophysics Data System (ADS)

    Passarelli, Luigi; Rivalta, Eleonora; Jónsson, Sigurjón; Hensch, Martin; Metzger, Sabrina; Jakobsdóttir, Steinunn S.; Maccaferri, Francesco; Corbi, Fabio; Dahm, Torsten

    2018-01-01

    Tectonic earthquake swarms (TES) often coincide with aseismic slip and sometimes precede damaging earthquakes. In spite of recent progress in understanding the significance and properties of TES at plate boundaries, their mechanics and scaling are still largely uncertain. Here we evaluate several TES that occurred during the past 20 years on a transform plate boundary in North Iceland. We show that the swarms complement each other spatially with later swarms discouraged from fault segments activated by earlier swarms, which suggests efficient strain release and aseismic slip. The fault area illuminated by earthquakes during swarms may be more representative of the total moment release than the cumulative moment of the swarm earthquakes. We use these findings and other published results from a variety of tectonic settings to discuss general scaling properties for TES. The results indicate that the importance of TES in releasing tectonic strain at plate boundaries may have been underestimated.

  9. SWARM: A 32 GHz Correlator and VLBI Beamformer for the Submillimeter Array

    NASA Astrophysics Data System (ADS)

    Primiani, Rurik A.; Young, Kenneth H.; Young, André; Patel, Nimesh; Wilson, Robert W.; Vertatschitsch, Laura; Chitwood, Billie B.; Srinivasan, Ranjani; MacMahon, David; Weintroub, Jonathan

    2016-03-01

    A 32GHz bandwidth VLBI capable correlator and phased array has been designed and deployeda at the Smithsonian Astrophysical Observatory’s Submillimeter Array (SMA). The SMA Wideband Astronomical ROACH2 Machine (SWARM) integrates two instruments: a correlator with 140kHz spectral resolution across its full 32GHz band, used for connected interferometric observations, and a phased array summer used when the SMA participates as a station in the Event Horizon Telescope (EHT) very long baseline interferometry (VLBI) array. For each SWARM quadrant, Reconfigurable Open Architecture Computing Hardware (ROACH2) units shared under open-source from the Collaboration for Astronomy Signal Processing and Electronics Research (CASPER) are equipped with a pair of ultra-fast analog-to-digital converters (ADCs), a field programmable gate array (FPGA) processor, and eight 10 Gigabit Ethernet (GbE) ports. A VLBI data recorder interface designated the SWARM digital back end, or SDBE, is implemented with a ninth ROACH2 per quadrant, feeding four Mark6 VLBI recorders with an aggregate recording rate of 64 Gbps. This paper describes the design and implementation of SWARM, as well as its deployment at SMA with reference to verification and science data.

  10. A Swarm Optimization Genetic Algorithm Based on Quantum-Behaved Particle Swarm Optimization.

    PubMed

    Sun, Tao; Xu, Ming-Hai

    2017-01-01

    Quantum-behaved particle swarm optimization (QPSO) algorithm is a variant of the traditional particle swarm optimization (PSO). The QPSO that was originally developed for continuous search spaces outperforms the traditional PSO in search ability. This paper analyzes the main factors that impact the search ability of QPSO and converts the particle movement formula to the mutation condition by introducing the rejection region, thus proposing a new binary algorithm, named swarm optimization genetic algorithm (SOGA), because it is more like genetic algorithm (GA) than PSO in form. SOGA has crossover and mutation operator as GA but does not need to set the crossover and mutation probability, so it has fewer parameters to control. The proposed algorithm was tested with several nonlinear high-dimension functions in the binary search space, and the results were compared with those from BPSO, BQPSO, and GA. The experimental results show that SOGA is distinctly superior to the other three algorithms in terms of solution accuracy and convergence.

  11. Determination of equilibrium electron temperature and times using an electron swarm model with BOLSIG+ calculated collision frequencies and rate coefficients

    DOE PAGES

    Pusateri, Elise N.; Morris, Heidi E.; Nelson, Eric M.; ...

    2015-08-04

    Electromagnetic pulse (EMP) events produce low-energy conduction electrons from Compton electron or photoelectron ionizations with air. It is important to understand how conduction electrons interact with air in order to accurately predict EMP evolution and propagation. An electron swarm model can be used to monitor the time evolution of conduction electrons in an environment characterized by electric field and pressure. Here a swarm model is developed that is based on the coupled ordinary differential equations (ODEs) described by Higgins et al. (1973), hereinafter HLO. The ODEs characterize the swarm electric field, electron temperature, electron number density, and drift velocity. Importantmore » swarm parameters, the momentum transfer collision frequency, energy transfer collision frequency, and ionization rate, are calculated and compared to the previously reported fitted functions given in HLO. These swarm parameters are found using BOLSIG+, a two term Boltzmann solver developed by Hagelaar and Pitchford (2005), which utilizes updated cross sections from the LXcat website created by Pancheshnyi et al. (2012). We validate the swarm model by comparing to experimental effective ionization coefficient data in Dutton (1975) and drift velocity data in Ruiz-Vargas et al. (2010). In addition, we report on electron equilibrium temperatures and times for a uniform electric field of 1 StatV/cm for atmospheric heights from 0 to 40 km. We show that the equilibrium temperature and time are sensitive to the modifications in the collision frequencies and ionization rate based on the updated electron interaction cross sections.« less

  12. Swarmie User Manual: A Rover Used for Multi-agent Swarm Research

    NASA Technical Reports Server (NTRS)

    Montague, Gilbert

    2014-01-01

    The ability to create multiple functional yet cost effective robots is crucial for conducting swarming robotics research. The Center Innovation Fund (CIF) swarming robotics project is a collaboration among the KSC Granular Mechanics and Regolith Operations (GMRO) group, the University of New Mexico Biological Computation Lab, and the NASA Ames Intelligent Robotics Group (IRG) that uses rovers, dubbed "Swarmies", as test platforms for genetic search algorithms. This fall, I assisted in the development of the software modules used on the Swarmies and created this guide to provide thorough instructions on how to configure your workspace to operate a Swarmie both in simulation and out in the field.

  13. Generic, scalable and decentralized fault detection for robot swarms.

    PubMed

    Tarapore, Danesh; Christensen, Anders Lyhne; Timmis, Jon

    2017-01-01

    Robot swarms are large-scale multirobot systems with decentralized control which means that each robot acts based only on local perception and on local coordination with neighboring robots. The decentralized approach to control confers number of potential benefits. In particular, inherent scalability and robustness are often highlighted as key distinguishing features of robot swarms compared with systems that rely on traditional approaches to multirobot coordination. It has, however, been shown that swarm robotics systems are not always fault tolerant. To realize the robustness potential of robot swarms, it is thus essential to give systems the capacity to actively detect and accommodate faults. In this paper, we present a generic fault-detection system for robot swarms. We show how robots with limited and imperfect sensing capabilities are able to observe and classify the behavior of one another. In order to achieve this, the underlying classifier is an immune system-inspired algorithm that learns to distinguish between normal behavior and abnormal behavior online. Through a series of experiments, we systematically assess the performance of our approach in a detailed simulation environment. In particular, we analyze our system's capacity to correctly detect robots with faults, false positive rates, performance in a foraging task in which each robot exhibits a composite behavior, and performance under perturbations of the task environment. Results show that our generic fault-detection system is robust, that it is able to detect faults in a timely manner, and that it achieves a low false positive rate. The developed fault-detection system has the potential to enable long-term autonomy for robust multirobot systems, thus increasing the usefulness of robots for a diverse repertoire of upcoming applications in the area of distributed intelligent automation.

  14. Generic, scalable and decentralized fault detection for robot swarms

    PubMed Central

    Christensen, Anders Lyhne; Timmis, Jon

    2017-01-01

    Robot swarms are large-scale multirobot systems with decentralized control which means that each robot acts based only on local perception and on local coordination with neighboring robots. The decentralized approach to control confers number of potential benefits. In particular, inherent scalability and robustness are often highlighted as key distinguishing features of robot swarms compared with systems that rely on traditional approaches to multirobot coordination. It has, however, been shown that swarm robotics systems are not always fault tolerant. To realize the robustness potential of robot swarms, it is thus essential to give systems the capacity to actively detect and accommodate faults. In this paper, we present a generic fault-detection system for robot swarms. We show how robots with limited and imperfect sensing capabilities are able to observe and classify the behavior of one another. In order to achieve this, the underlying classifier is an immune system-inspired algorithm that learns to distinguish between normal behavior and abnormal behavior online. Through a series of experiments, we systematically assess the performance of our approach in a detailed simulation environment. In particular, we analyze our system’s capacity to correctly detect robots with faults, false positive rates, performance in a foraging task in which each robot exhibits a composite behavior, and performance under perturbations of the task environment. Results show that our generic fault-detection system is robust, that it is able to detect faults in a timely manner, and that it achieves a low false positive rate. The developed fault-detection system has the potential to enable long-term autonomy for robust multirobot systems, thus increasing the usefulness of robots for a diverse repertoire of upcoming applications in the area of distributed intelligent automation. PMID:28806756

  15. From hybrid swarms to swarms of hybrids

    USDA-ARS?s Scientific Manuscript database

    The introgression of modern humans (Homo sapiens) with Neanderthals 40,000 YBP after a half-million years of separation, may have led to the best example of a hybrid swarm on earth. Modern trade and transportation in support of the human hybrids has continued to introduce additional species, genotyp...

  16. Particle Swarm Imaging (PSIM) - Innovative Gamma-Ray Assay - 13497

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Parvin, Daniel; Clarke, Sean; Humes, Sarah J.

    2013-07-01

    Particle Swarm Imaging is an innovative technique used to perform quantitative gamma-ray assay. The innovation overcomes some of the difficulties associated with the accurate measurement and declaration of measurement uncertainties of radionuclide inventories within waste items when the distribution of activity is unknown. Implementation requires minimal equipment, with field measurements and results obtained using only a single electrically cooled HRGS gamma-ray detector. Examples of its application in the field are given in this paper. (authors)

  17. Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT

    PubMed Central

    2017-01-01

    Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of “premature convergence,” that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In order to surmount the shortcomings of CSO, Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed in this paper. Firstly, Quantum-behaved Cat Swarm Optimization (QCSO) algorithm improves the accuracy of the CSO algorithm, because it is easy to fall into the local optimum in the later stage. Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed by introducing tent map for jumping out of local optimum in this paper. Secondly, CQCSO has been applied in the simulation of five different test functions, showing higher accuracy and less time consumption than CSO and QCSO. Finally, photovoltaic MPPT model and experimental platform are established and global maximum power point tracking control strategy is achieved by CQCSO algorithm, the effectiveness and efficiency of which have been verified by both simulation and experiment. PMID:29181020

  18. Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT.

    PubMed

    Nie, Xiaohua; Wang, Wei; Nie, Haoyao

    2017-01-01

    Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of "premature convergence," that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In order to surmount the shortcomings of CSO, Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed in this paper. Firstly, Quantum-behaved Cat Swarm Optimization (QCSO) algorithm improves the accuracy of the CSO algorithm, because it is easy to fall into the local optimum in the later stage. Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed by introducing tent map for jumping out of local optimum in this paper. Secondly, CQCSO has been applied in the simulation of five different test functions, showing higher accuracy and less time consumption than CSO and QCSO. Finally, photovoltaic MPPT model and experimental platform are established and global maximum power point tracking control strategy is achieved by CQCSO algorithm, the effectiveness and efficiency of which have been verified by both simulation and experiment.

  19. Medical diagnosis using adaptive perceptive particle swarm optimization and its hardware realization using field programmable gate array.

    PubMed

    Chowdhury, Shubhajit Roy; Chakrabarti, Dipankar; Hiranmay, Saha

    2009-12-01

    The paper proposes to develop a field programmable gate array (FPGA) based low cost, low power and high speed novel diagnostic system that can detect in absence of the physician the approaching critical condition of a patient at an early stage and is thus suitable for diagnosis of patients in the rural areas of developing countries where availability of physicians and availability of power is really scarce. The diagnostic system could be installed in health care centres of rural areas where patients can register themselves for periodic diagnoses and thereby detect potential health hazards at an early stage. Multiple pathophysiological parameters with different weights are involved in diagnosing a particular disease. A novel variation of particle swarm optimization called as adaptive perceptive particle swarm optimization has been proposed to determine the optimal weights of these pathophysiological parameters for a more accurate diagnosis. The FPGA based smart system has been applied for early detection of renal criticality of patients. For renal diagnosis, body mass index, glucose, urea, creatinine, systolic and diastolic blood pressures have been considered as pathophysiological parameters. The detection of approaching critical condition of a patient by the instrument has also been validated with the standard Cockford Gault Equation to verify whether the patient is really approaching a critical condition or not. Using Bayesian analysis on the population of 80 patients under study an accuracy of up to 97.5% in renal diagnosis has been obtained.

  20. A Modular Simulation Framework for Assessing Swarm Search Models

    DTIC Science & Technology

    2014-09-01

    SUBTITLE A MODULAR SIMULATION FRAMEWORK FOR ASSESSING SWARM SEARCH MODELS 5. FUNDING NUMBERS 6. AUTHOR(S) Blake M. Wanier 7. PERFORMING ORGANIZATION...Numerical studies demonstrate the ability to leverage the developed simulation and analysis framework to investigate three canonical swarm search models ...as benchmarks for future exploration of more sophisticated swarm search scenarios. 14. SUBJECT TERMS Swarm Search, Search Theory, Modeling Framework

  1. DNA-assisted swarm control in a biomolecular motor system.

    PubMed

    Keya, Jakia Jannat; Suzuki, Ryuhei; Kabir, Arif Md Rashedul; Inoue, Daisuke; Asanuma, Hiroyuki; Sada, Kazuki; Hess, Henry; Kuzuya, Akinori; Kakugo, Akira

    2018-01-31

    In nature, swarming behavior has evolved repeatedly among motile organisms because it confers a variety of beneficial emergent properties. These include improved information gathering, protection from predators, and resource utilization. Some organisms, e.g., locusts, switch between solitary and swarm behavior in response to external stimuli. Aspects of swarming behavior have been demonstrated for motile supramolecular systems composed of biomolecular motors and cytoskeletal filaments, where cross-linkers induce large scale organization. The capabilities of such supramolecular systems may be further extended if the swarming behavior can be programmed and controlled. Here, we demonstrate that the swarming of DNA-functionalized microtubules (MTs) propelled by surface-adhered kinesin motors can be programmed and reversibly regulated by DNA signals. Emergent swarm behavior, such as translational and circular motion, can be selected by tuning the MT stiffness. Photoresponsive DNA containing azobenzene groups enables switching between solitary and swarm behavior in response to stimulation with visible or ultraviolet light.

  2. Thermal and athermal three-dimensional swarms of self-propelled particles

    NASA Astrophysics Data System (ADS)

    Nguyen, Nguyen H. P.; Jankowski, Eric; Glotzer, Sharon C.

    2012-07-01

    Swarms of self-propelled particles exhibit complex behavior that can arise from simple models, with large changes in swarm behavior resulting from small changes in model parameters. We investigate the steady-state swarms formed by self-propelled Morse particles in three dimensions using molecular dynamics simulations optimized for graphics processing units. We find a variety of swarms of different overall shape assemble spontaneously and that for certain Morse potential parameters at most two competing structures are observed. We report a rich “phase diagram” of athermal swarm structures observed across a broad range of interaction parameters. Unlike the structures formed in equilibrium self-assembly, we find that the probability of forming a self-propelled swarm can be biased by the choice of initial conditions. We investigate how thermal noise influences swarm formation and demonstrate ways it can be exploited to reconfigure one swarm into another. Our findings validate and extend previous observations of self-propelled Morse swarms and highlight open questions for predictive theories of nonequilibrium self-assembly.

  3. Calibration of Swarm accelerometer data by GPS positioning and linear temperature correction

    NASA Astrophysics Data System (ADS)

    Bezděk, Aleš; Sebera, Josef; Klokočník, Jaroslav

    2018-07-01

    Swarm, a mission of the European Space Agency, consists of three satellites orbiting the Earth since November 2013. In addition to the instrumentation aimed at fulfilling the mission's main goal, which is the observation of Earth's magnetic field, each satellite carries a geodetic quality GPS receiver and an accelerometer. Initially put in a 500-km altitude, all Swarm spacecraft slowly decay due to the action of atmospheric drag. Atmospheric particles and radiation forces impinge on the satellite's surface and thus create the main part of the nongravitational force, which together with satellite-induced thrusts can be measured by space accelerometers. Unfortunately, the Swarm accelerometer data are heavily disturbed by the varying onboard temperature. We calibrate the accelerometer data against a calibration standard derived from observed GPS positions, while making use of the models to represent the forces of gravity origin. We show that this procedure can be extended to incorporate the temperature signal. The obtained calibrated accelerations are validated in several different ways; namely by (i) physically modelled nongravitational forces, by (ii) intercomparison of calibrated accelerometer data from two Swarm satellites flying side-by-side, and by (iii) good agreement of our calibrated signals with those released by ESA, obtained via a different approach for reducing temperature effects. Finally, the presented method is applied to the Swarm C accelerometer data set covering almost two years (July 2014-April 2016), which ESA recently released to scientific users.

  4. Swarm Observation of Field-Aligned Currents Associated With Multiple Auroral Arc Systems

    NASA Astrophysics Data System (ADS)

    Wu, J.; Knudsen, D. J.; Gillies, D. M.; Donovan, E. F.; Burchill, J. K.

    2017-10-01

    Auroral arcs occur in regions of upward field-aligned currents (FACs); however, the relation is not one to one, since kinetic energy of the current-carrying electrons is also important in the production of auroral luminosity. Multiple auroral arc systems provide an opportunity to study the relation between FACs and auroral brightness in detail. In this study, we have identified two types of FAC configurations in multiple parallel arc systems using ground-based optical data from the Time History of Events and Macroscale Interactions during Substorms all-sky imagers, magnetometers and electric field instruments on board the Swarm satellites. In "unipolar FAC" events, each arc is an intensification within a broad, unipolar current sheet and downward return currents occur outside of this broad sheet. In "multipolar FAC" events, multiple arc systems represent a collection of multiple up/down current pairs. By collecting 17 events with unipolar FAC and 12 events with multipolar FACs, we find that (1) unipolar FAC events occur most frequently between 20 and 21 magnetic local time and multipolar FAC events tend to occur around local midnight and within 1 h after substorm onset. (2) Arcs in unipolar FAC systems have a typical width of 10-20 km and a spacing of 25-50 km. Arcs in multipolar FAC systems are wider and more separated. (3) Upward currents with more arcs embedded have larger intensities and widths. (4) Electric fields are strong and highly structured on the edges of multiple arc system with unipolar FAC. The fact that arcs with unipolar FAC are much more highly structured than the associated currents suggests that arc multiplicity is indicative not of a structured generator deep in the magnetosphere, but rather of the magnetosphere-ionosphere coupling process.

  5. Chaotic Particle Swarm Optimization with Mutation for Classification

    PubMed Central

    Assarzadeh, Zahra; Naghsh-Nilchi, Ahmad Reza

    2015-01-01

    In this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classify patterns of different classes in the feature space. The introduced mutation operators and chaotic sequences allows us to overcome the problem of early convergence into a local minima associated with particle swarm optimization algorithms. That is, the mutation operator sharpens the convergence and it tunes the best possible solution. Furthermore, to remove the irrelevant data and reduce the dimensionality of medical datasets, a feature selection approach using binary version of the proposed particle swarm optimization is introduced. In order to demonstrate the effectiveness of our proposed classifier, mutation-based classifier particle swarm optimization, it is checked out with three sets of data classifications namely, Wisconsin diagnostic breast cancer, Wisconsin breast cancer and heart-statlog, with different feature vector dimensions. The proposed algorithm is compared with different classifier algorithms including k-nearest neighbor, as a conventional classifier, particle swarm-classifier, genetic algorithm, and Imperialist competitive algorithm-classifier, as more sophisticated ones. The performance of each classifier was evaluated by calculating the accuracy, sensitivity, specificity and Matthews's correlation coefficient. The experimental results show that the mutation-based classifier particle swarm optimization unequivocally performs better than all the compared algorithms. PMID:25709937

  6. Chaotic particle swarm optimization with mutation for classification.

    PubMed

    Assarzadeh, Zahra; Naghsh-Nilchi, Ahmad Reza

    2015-01-01

    In this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classify patterns of different classes in the feature space. The introduced mutation operators and chaotic sequences allows us to overcome the problem of early convergence into a local minima associated with particle swarm optimization algorithms. That is, the mutation operator sharpens the convergence and it tunes the best possible solution. Furthermore, to remove the irrelevant data and reduce the dimensionality of medical datasets, a feature selection approach using binary version of the proposed particle swarm optimization is introduced. In order to demonstrate the effectiveness of our proposed classifier, mutation-based classifier particle swarm optimization, it is checked out with three sets of data classifications namely, Wisconsin diagnostic breast cancer, Wisconsin breast cancer and heart-statlog, with different feature vector dimensions. The proposed algorithm is compared with different classifier algorithms including k-nearest neighbor, as a conventional classifier, particle swarm-classifier, genetic algorithm, and Imperialist competitive algorithm-classifier, as more sophisticated ones. The performance of each classifier was evaluated by calculating the accuracy, sensitivity, specificity and Matthews's correlation coefficient. The experimental results show that the mutation-based classifier particle swarm optimization unequivocally performs better than all the compared algorithms.

  7. Westward tilt of low-latitude plasma blobs as observed by the Swarm constellation

    NASA Astrophysics Data System (ADS)

    Park, Jaeheung; Lühr, Hermann; Michaelis, Ingo; Stolle, Claudia; Rauberg, Jan; Buchert, Stephan; Gill, Reine; Merayo, Jose M. G.; Brauer, Peter

    2015-04-01

    In this study we investigate the three-dimensional structure of low-latitude plasma blobs using multi-instrument and multisatellite observations of the Swarm constellation. During the early commissioning phase the Swarm satellites were flying at the same altitude with zonal separation of about 0.5∘ in geographic longitude. Electron density data from the three satellites constrain the blob morphology projected onto the horizontal plane. Magnetic field deflections around blobs, which originate from field-aligned currents near the irregularity boundaries, constrain the blob structure projected onto the plane perpendicular to the ambient magnetic field. As the two constraints are given for two noncoplanar surfaces, we can get information on the three-dimensional structure of blobs. Combined observation results suggest that blobs are contained within tilted shells of geomagnetic flux tubes, which are similar to the shell structure of equatorial plasma bubbles suggested by previous studies.

  8. Log-linear model based behavior selection method for artificial fish swarm algorithm.

    PubMed

    Huang, Zhehuang; Chen, Yidong

    2015-01-01

    Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm.

  9. Log-Linear Model Based Behavior Selection Method for Artificial Fish Swarm Algorithm

    PubMed Central

    Huang, Zhehuang; Chen, Yidong

    2015-01-01

    Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm. PMID:25691895

  10. Swarm Intelligence Optimization and Its Applications

    NASA Astrophysics Data System (ADS)

    Ding, Caichang; Lu, Lu; Liu, Yuanchao; Peng, Wenxiu

    Swarm Intelligence is a computational and behavioral metaphor for solving distributed problems inspired from biological examples provided by social insects such as ants, termites, bees, and wasps and by swarm, herd, flock, and shoal phenomena in vertebrates such as fish shoals and bird flocks. An example of successful research direction in Swarm Intelligence is ant colony optimization (ACO), which focuses on combinatorial optimization problems. Ant algorithms can be viewed as multi-agent systems (ant colony), where agents (individual ants) solve required tasks through cooperation in the same way that ants create complex social behavior from the combined efforts of individuals.

  11. Electrocardiographic signals and swarm-based support vector machine for hypoglycemia detection.

    PubMed

    Nuryani, Nuryani; Ling, Steve S H; Nguyen, H T

    2012-04-01

    Cardiac arrhythmia relating to hypoglycemia is suggested as a cause of death in diabetic patients. This article introduces electrocardiographic (ECG) parameters for artificially induced hypoglycemia detection. In addition, a hybrid technique of swarm-based support vector machine (SVM) is introduced for hypoglycemia detection using the ECG parameters as inputs. In this technique, a particle swarm optimization (PSO) is proposed to optimize the SVM to detect hypoglycemia. In an experiment using medical data of patients with Type 1 diabetes, the introduced ECG parameters show significant contributions to the performance of the hypoglycemia detection and the proposed detection technique performs well in terms of sensitivity and specificity.

  12. Improving high-altitude emp modeling capabilities by using a non-equilibrium electron swarm model to monitor conduction electron evolution

    NASA Astrophysics Data System (ADS)

    Pusateri, Elise Noel

    abruptly. The objective of the PhD research is to mitigate this effect by integrating a conduction electron model into CHAP-LA which can calculate the conduction current based on a non-equilibrium electron distribution. We propose to use an electron swarm model to monitor the time evolution of conduction electrons in the EMP environment which is characterized by electric field and pressure. Swarm theory uses various collision frequencies and reaction rates to study how the electron distribution and the resultant transport coefficients change with time, ultimately reaching an equilibrium distribution. Validation of the swarm model we develop is a necessary step for completion of the thesis work. After validation, the swarm model is integrated in the air chemistry model CHAP-LA employs for conduction electron simulations. We test high altitude EMP simulations with the swarm model option in the air chemistry model to show improvements in the computational capability of CHAP-LA. A swarm model has been developed that is based on a previous swarm model developed by Higgins, Longmire and O'Dell 1973, hereinafter HLO. The code used for the swarm model calculation solves a system of coupled differential equations for electric field, electron temperature, electron number density, and drift velocity. Important swarm parameters, including the momentum transfer collision frequency, energy transfer collision frequency, and ionization rate, are recalculated and compared to the previously reported empirical results given by HLO. These swarm parameters are found using BOLSIG+, a two term Boltzmann solver developed by Hagelaar and Pitchford 2005. BOLSIG+ utilizes updated electron scattering cross sections that are defined over an expanded energy range found in the atomic and molecular cross section database published by Phelps in the Phelps Database 2014 on the LXcat website created by Pancheshnyi et al. 2012. The swarm model is also updated from the original HLO model by including

  13. The Dynamics of Interacting Swarms

    DTIC Science & Technology

    2018-04-04

    Unlimited 16 Ira Schwartzt (202) 404-8359 Swarms are self-organized dynamical coupled agents which evolve from simple rules of communication. They are ...when delay is introduced to the communicating agents. One of our major findings is that interacting swarms are far less likely to flock cohesively if...they are coupled with delay. In addition, parameter ranges based on coupling strength, incidence angle of collision, and delay change dramatically

  14. Formal Methods for Autonomic and Swarm-based Systems

    NASA Technical Reports Server (NTRS)

    Rouff, Christopher; Vanderbilt, Amy; Hinchey, Mike; Truszkowski, Walt; Rash, James

    2004-01-01

    Swarms of intelligent rovers and spacecraft are being considered for a number of future NASA missions. These missions will provide MSA scientist and explorers greater flexibility and the chance to gather more science than traditional single spacecraft missions. These swarms of spacecraft are intended to operate for large periods of time without contact with the Earth. To do this, they must be highly autonomous, have autonomic properties and utilize sophisticated artificial intelligence. The Autonomous Nano Technology Swarm (ANTS) mission is an example of one of the swarm type of missions NASA is considering. This mission will explore the asteroid belt using an insect colony analogy cataloging the mass, density, morphology, and chemical composition of the asteroids, including any anomalous concentrations of specific minerals. Verifying such a system would be a huge task. This paper discusses ongoing work to develop a formal method for verifying swarm and autonomic systems.

  15. Operating Small Sat Swarms as a Single Entity: Introducing SODA

    NASA Technical Reports Server (NTRS)

    Conn, Tracie; Dono Perez, Andres

    2017-01-01

    Swarm concepts are a growing topic of interest in the small satellite community. Compared to a small satellite constellation, a swarm has the distinction of being multiple spacecraft in close proximity, in approximately the same orbit. Furthermore, we envision swarms to have capabilities for cross-link communication and station-keeping. Of particular interest is a means to maintain operator-specified geometry, alignment, and/or separation.From NASA's decadal survey, it is clear that simultaneous measurements from a 3D volume of space are desired for a variety of Earth scientific studies. As this mission concept is ultimately extended to deep space, some degree of local control for the swarm to self-correct its configuration is required. We claim that the practicality of ground commanding each individual satellite in the swarm is simply not a feasible concept of operations. In other words, the current state-of-practice does not scale to very large swarms (e.g. 100 spacecraft or more) without becoming cost prohibitive. To contain the operations costs and complexity, a new approach is required: the swarm must be operated as a unit, responding to high-level specifications for relative position and velocity.The Mission Design Division at NASA Ames Research Center is looking to the near future for opportunities to develop satellite swarm technology. As part of this effort, we are developing SODA (Swarm Orbital Dynamics Advisor), a tool that provides the orbital maneuvers required to achieve a desired type of relative swarm motion. The purpose of SODA is two-fold. First, it encompasses the algorithms and orbital dynamics model to enable the desired relative motion of the swarm satellites. The process starts with the user specifying the properties of a swarm configuration. This could be as simple as varying in-track spacing of the swarm in one orbit, or as complex as maintaining a specified 3D geometrical orientation. We presume that science objectives will drive this

  16. The role of geomagnetic observatory data during the Swarm mission

    NASA Astrophysics Data System (ADS)

    Ridley, Victoria; Macmillan, Susan; Beggan, Ciaran

    2014-05-01

    The scientific use of Swarm magnetic data and Swarm-derived products is greatly enhanced through combination with observatory data and indices. The strength of observatory data is their long-term accuracy, with great care being taken to ensure temperature control and correction, platform stability and magnetic cleanliness at each site. Observatory data are being distributed with Swarm data as an auxiliary product. We describe the preparation of the data set of ground observatory hourly mean values, including procedures to check and select observatory data spanning the modern magnetic survey satellite era. Existing collaborations, such as INTERMAGNET and the World Data Centres for Geomagnetism, are proving invaluable for this. We also discuss how observatory measurements are being used to ground-truth Swarm data as part of the Calibration/Validation effort. Recent efforts to improve the coverage and timeliness of observatory data have been encouraged and now over 60 INTERMAGNET observatories and several other high-quality observatories are providing close-to-definitive data within 3 months of measurement. During the Calibration/Validation period these data are gathered and homogenised on a regular basis by BGS. We then identify measurements collected during overhead passes of the Swarm satellites. For each pass, we remove an estimate of the main field from both the data collected at altitude and that collected on the ground. Both sets of data are then normalised relative to the data variance during all passes in the Calibration/Validation period. The absolute differences of the two sets of normalised data can be used as a metric of satellite data quality relative to observatory data quality. This can be examined by universal time, local time, disturbance level and geomagnetic latitude, for example. A preliminary study of CHAMP data, using definitive minute mean observatory data, has shown how this approach can provide a baseline for detecting abnormalities at all

  17. Middleware Design for Swarm-Driving Robots Accompanying Humans.

    PubMed

    Kim, Min Su; Kim, Sang Hyuck; Kang, Soon Ju

    2017-02-17

    Research on robots that accompany humans is being continuously studied. The Pet-Bot provides walking-assistance and object-carrying services without any specific controls through interaction between the robot and the human in real time. However, with Pet-Bot, there is a limit to the number of robots a user can use. If this limit is overcome, the Pet-Bot can provide services in more areas. Therefore, in this study, we propose a swarm-driving middleware design adopting the concept of a swarm, which provides effective parallel movement to allow multiple human-accompanying robots to accomplish a common purpose. The functions of middleware divide into three parts: a sequence manager for swarm process, a messaging manager, and a relative-location identification manager. This middleware processes the sequence of swarm-process of robots in the swarm through message exchanging using radio frequency (RF) communication of an IEEE 802.15.4 MAC protocol and manages an infrared (IR) communication module identifying relative location with IR signal strength. The swarm in this study is composed of the master interacting with the user and the slaves having no interaction with the user. This composition is intended to control the overall swarm in synchronization with the user activity, which is difficult to predict. We evaluate the accuracy of the relative-location estimation using IR communication, the response time of the slaves to a change in user activity, and the time to organize a network according to the number of slaves.

  18. Middleware Design for Swarm-Driving Robots Accompanying Humans

    PubMed Central

    Kim, Min Su; Kim, Sang Hyuck; Kang, Soon Ju

    2017-01-01

    Research on robots that accompany humans is being continuously studied. The Pet-Bot provides walking-assistance and object-carrying services without any specific controls through interaction between the robot and the human in real time. However, with Pet-Bot, there is a limit to the number of robots a user can use. If this limit is overcome, the Pet-Bot can provide services in more areas. Therefore, in this study, we propose a swarm-driving middleware design adopting the concept of a swarm, which provides effective parallel movement to allow multiple human-accompanying robots to accomplish a common purpose. The functions of middleware divide into three parts: a sequence manager for swarm process, a messaging manager, and a relative-location identification manager. This middleware processes the sequence of swarm-process of robots in the swarm through message exchanging using radio frequency (RF) communication of an IEEE 802.15.4 MAC protocol and manages an infrared (IR) communication module identifying relative location with IR signal strength. The swarm in this study is composed of the master interacting with the user and the slaves having no interaction with the user. This composition is intended to control the overall swarm in synchronization with the user activity, which is difficult to predict. We evaluate the accuracy of the relative-location estimation using IR communication, the response time of the slaves to a change in user activity, and the time to organize a network according to the number of slaves. PMID:28218650

  19. A persistent homology approach to collective behavior in insect swarms

    NASA Astrophysics Data System (ADS)

    Sinhuber, Michael; Ouellette, Nicholas T.

    Various animals from birds and fish to insects tend to form aggregates, displaying self-organized collective swarming behavior. Due to their frequent occurrence in nature and their implications for engineered, collective systems, these systems have been investigated and modeled thoroughly for decades. Common approaches range from modeling them with coupled differential equations on the individual level up to continuum approaches. We present an alternative, topology-based approach for describing swarming behavior at the macroscale rather than the microscale. We study laboratory swarms of Chironomus riparius, a flying, non-biting midge. To obtain the time-resolved three-dimensional trajectories of individual insects, we use a multi-camera stereoimaging and particle-tracking setup. To investigate the swarming behavior in a topological sense, we employ a persistent homology approach to identify persisting structures and features in the insect swarm that elude a direct, ensemble-averaging approach. We are able to identify features of sub-clusters in the swarm that show behavior distinct from that of the remaining swarm members. The coexistence of sub-swarms with different features resembles some non-biological systems such as active colloids or even thermodynamic systems.

  20. Models of angular momentum input to a circumterrestrial swarm from encounters with heliocentric planetesimals

    NASA Technical Reports Server (NTRS)

    Herbert, F.; Davis, D. R.

    1984-01-01

    Preliminary experiments show that heliocentric planetesimals passing through the Earth environment possess significant angular momentum. However it also appears that these same planetesimals impacting a circularized circumterrestrial planetesimal swarm would likely remove angular momentum (though possibly increasing mean kinetic energy), presumably promoting both swarm infall upon the Earth and escape to heliocentric space. Only a distribution of highly eccentric satellite orbits with mean tangential velocities of a few tens of percent of local circular velocity would be immune against angular momentum loss to passing heliocentric planetesimals.

  1. Effect of Cell Aspect Ratio on Swarming Bacteria

    NASA Astrophysics Data System (ADS)

    Ilkanaiv, Bella; Kearns, Daniel B.; Ariel, Gil; Be'er, Avraham

    2017-04-01

    Swarming bacteria collectively migrate on surfaces using flagella, forming dynamic whirls and jets that consist of millions of individuals. Because some swarming bacteria elongate prior to actual motion, cell aspect ratio may play a significant role in the collective dynamics. Extensive research on self-propelled rodlike particles confirms that elongation promotes alignment, strongly affecting the dynamics. Here, we study experimentally the collective dynamics of variants of swarming Bacillus subtilis that differ in length. We show that the swarming statistics depends on the aspect ratio in a critical, fundamental fashion not predicted by theory. The fastest motion was obtained for the wild-type and variants that are similar in length. However, shorter and longer cells exhibit anomalous, non-Gaussian statistics and nonexponential decay of the autocorrelation function, indicating lower collective motility. These results suggest that the robust mechanisms to maintain aspect ratios may be important for efficient swarming motility. Wild-type cells are optimal in this sense.

  2. Trust Management in Swarm-Based Autonomic Computing Systems

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Maiden, Wendy M.; Haack, Jereme N.; Fink, Glenn A.

    2009-07-07

    Reputation-based trust management techniques can address issues such as insider threat as well as quality of service issues that may be malicious in nature. However, trust management techniques must be adapted to the unique needs of the architectures and problem domains to which they are applied. Certain characteristics of swarms such as their lightweight ephemeral nature and indirect communication make this adaptation especially challenging. In this paper we look at the trust issues and opportunities in mobile agent swarm-based autonomic systems and find that by monitoring the trustworthiness of the autonomic managers rather than the swarming sensors, the trust managementmore » problem becomes much more scalable and still serves to protect the swarms. We also analyze the applicability of trust management research as it has been applied to architectures with similar characteristics. Finally, we specify required characteristics for trust management mechanisms to be used to monitor the trustworthiness of the entities in a swarm-based autonomic computing system.« less

  3. KANTS: a stigmergic ant algorithm for cluster analysis and swarm art.

    PubMed

    Fernandes, Carlos M; Mora, Antonio M; Merelo, Juan J; Rosa, Agostinho C

    2014-06-01

    KANTS is a swarm intelligence clustering algorithm inspired by the behavior of social insects. It uses stigmergy as a strategy for clustering large datasets and, as a result, displays a typical behavior of complex systems: self-organization and global patterns emerging from the local interaction of simple units. This paper introduces a simplified version of KANTS and describes recent experiments with the algorithm in the context of a contemporary artistic and scientific trend called swarm art, a type of generative art in which swarm intelligence systems are used to create artwork or ornamental objects. KANTS is used here for generating color drawings from the input data that represent real-world phenomena, such as electroencephalogram sleep data. However, the main proposal of this paper is an art project based on well-known abstract paintings, from which the chromatic values are extracted and used as input. Colors and shapes are therefore reorganized by KANTS, which generates its own interpretation of the original artworks. The project won the 2012 Evolutionary Art, Design, and Creativity Competition.

  4. From organized internal traffic to collective navigation of bacterial swarms

    NASA Astrophysics Data System (ADS)

    Ariel, Gil; Shklarsh, Adi; Kalisman, Oren; Ingham, Colin; Ben-Jacob, Eshel

    2013-12-01

    Bacterial swarming resulting in collective navigation over surfaces provides a valuable example of cooperative colonization of new territories. The social bacterium Paenibacillus vortex exhibits successful and diverse swarming strategies. When grown on hard agar surfaces with peptone, P. vortex develops complex colonies of vortices (rotating bacterial aggregates). In contrast, during growth on Mueller-Hinton broth gelled into a soft agar surface, a new strategy of multi-level organization is revealed: the colonies are organized into a special network of swarms (or ‘snakes’ of a fraction of millimeter in width) with intricate internal traffic. More specifically, cell movement is organized in two or three lanes of bacteria traveling between the back and the front of the swarm. This special form of cellular logistics suggests new methods in which bacteria can share resources and risk while searching for food or migrating into new territories. While the vortices-based organization on hard agar surfaces has been modeled before, here, we introduce a new multi-agent bacterial swarming model devised to capture the swarms-based organization on soft surfaces. We test two putative generic mechanisms that may underlie the observed swarming logistics: (i) chemo-activated taxis in response to chemical cues and (ii) special align-and-push interactions between the bacteria and the boundary of the layer of lubricant collectively generated by the swarming bacteria. Using realistic parameters, the model captures the observed phenomena with semi-quantitative agreement in terms of the velocity as well as the dynamics of the swarm and its envelope. This agreement implies that the bacteria interactions with the swarm boundary play a crucial role in mediating the interplay between the collective movement of the swarm and the internal traffic dynamics.

  5. Hybrid glowworm swarm optimization for task scheduling in the cloud environment

    NASA Astrophysics Data System (ADS)

    Zhou, Jing; Dong, Shoubin

    2018-06-01

    In recent years many heuristic algorithms have been proposed to solve task scheduling problems in the cloud environment owing to their optimization capability. This article proposes a hybrid glowworm swarm optimization (HGSO) based on glowworm swarm optimization (GSO), which uses a technique of evolutionary computation, a strategy of quantum behaviour based on the principle of neighbourhood, offspring production and random walk, to achieve more efficient scheduling with reasonable scheduling costs. The proposed HGSO reduces the redundant computation and the dependence on the initialization of GSO, accelerates the convergence and more easily escapes from local optima. The conducted experiments and statistical analysis showed that in most cases the proposed HGSO algorithm outperformed previous heuristic algorithms to deal with independent tasks.

  6. The swarming motility of Pseudomonas aeruginosa is blocked by cranberry proanthocyanidins and other tannin-containing materials.

    PubMed

    O'May, Che; Tufenkji, Nathalie

    2011-05-01

    Bacterial motility plays a key role in the colonization of surfaces by bacteria and the subsequent formation of resistant communities of bacteria called biofilms. Derivatives of cranberry fruit, predominantly condensed tannins called proanthocyanidins (PACs) have been reported to interfere with bacterial adhesion, but the effects of PACs and other tannins on bacterial motilities remain largely unknown. In this study, we investigated whether cranberry PAC (CPAC) and the hydrolyzable tannin in pomegranate (PG; punicalagin) affected the levels of motilities exhibited by the bacterium Pseudomonas aeruginosa. This bacterium utilizes flagellum-mediated swimming motility to approach a surface, attaches, and then further spreads via the surface-associated motilities designated swarming and twitching, mediated by multiple flagella and type IV pili, respectively. Under the conditions tested, both CPAC and PG completely blocked swarming motility but did not block swimming or twitching motilities. Other cranberry-containing materials and extracts of green tea (also rich in tannins) were also able to block or impair swarming motility. Moreover, swarming bacteria were repelled by filter paper discs impregnated with many tannin-containing materials. Growth experiments demonstrated that the majority of these compounds did not impair bacterial growth. When CPAC- or PG-containing medium was supplemented with surfactant (rhamnolipid), swarming motility was partially restored, suggesting that the effective tannins are in part acting by a rhamnolipid-related mechanism. Further support for this theory was provided by demonstrating that the agar surrounding tannin-induced nonswarming bacteria was considerably less hydrophilic than the agar area surrounding swarming bacteria. This is the first study to show that natural compounds containing tannins are able to block P. aeruginosa swarming motility and that swarming bacteria are repelled by such compounds.

  7. The Swarming Motility of Pseudomonas aeruginosa Is Blocked by Cranberry Proanthocyanidins and Other Tannin-Containing Materials▿

    PubMed Central

    O'May, Che; Tufenkji, Nathalie

    2011-01-01

    Bacterial motility plays a key role in the colonization of surfaces by bacteria and the subsequent formation of resistant communities of bacteria called biofilms. Derivatives of cranberry fruit, predominantly condensed tannins called proanthocyanidins (PACs) have been reported to interfere with bacterial adhesion, but the effects of PACs and other tannins on bacterial motilities remain largely unknown. In this study, we investigated whether cranberry PAC (CPAC) and the hydrolyzable tannin in pomegranate (PG; punicalagin) affected the levels of motilities exhibited by the bacterium Pseudomonas aeruginosa. This bacterium utilizes flagellum-mediated swimming motility to approach a surface, attaches, and then further spreads via the surface-associated motilities designated swarming and twitching, mediated by multiple flagella and type IV pili, respectively. Under the conditions tested, both CPAC and PG completely blocked swarming motility but did not block swimming or twitching motilities. Other cranberry-containing materials and extracts of green tea (also rich in tannins) were also able to block or impair swarming motility. Moreover, swarming bacteria were repelled by filter paper discs impregnated with many tannin-containing materials. Growth experiments demonstrated that the majority of these compounds did not impair bacterial growth. When CPAC- or PG-containing medium was supplemented with surfactant (rhamnolipid), swarming motility was partially restored, suggesting that the effective tannins are in part acting by a rhamnolipid-related mechanism. Further support for this theory was provided by demonstrating that the agar surrounding tannin-induced nonswarming bacteria was considerably less hydrophilic than the agar area surrounding swarming bacteria. This is the first study to show that natural compounds containing tannins are able to block P. aeruginosa swarming motility and that swarming bacteria are repelled by such compounds. PMID:21378043

  8. Strong Ionospheric Electron Heating Associated With Pulsating Auroras - A Swarm Survey

    NASA Astrophysics Data System (ADS)

    Liang, J.; Yang, B.; Burchill, J. K.; Donovan, E.; Knudsen, D. J.

    2016-12-01

    A pulsating aurora is a repetitive modulation of auroral luminosity with periods typically of the order of 1-30 sec. It is often observed in the equatorward portion of the auroral oval. While it is generally recognized that the ultimate source of the pulsating auroral precipitation comes from energetic electrons of magnetospheric origin, investigating the ionospheric signature of the pulsating aurora may offer clues to the magnetosphere-ionosphere coupling aspect of the pulsating aurora and, under certain circumstance, to the generation mechanism of the pulsating aurora. In this study, we perform an extensive survey on the ionospheric signatures (electron temperature, plasma density and field-aligned current etc.) of pulsating auroras using Swarm satellite data. Via the survey we repeatedly identify a strong electron temperature enhancement associated with the pulsating aurora. On average, the electron temperature at Swarm satellite altitude ( 500 km) increases from 2100 K at subauroral altitudes to a peak of 2900 K upon entering the pulsating aurora patch. This indicates that the pulsating auroras may act as an important heating source of the nightside ionosphere/thermosphere. On the other hand, no well-defined trend of plasma density variation associated with pulsating auroras is identified in the survey. There often exist moderate upward field-aligned currents (up to a few mA/m2) within the pulsating auroral patch when the patch is "on" during the traversal of satellites [Gillies et al., 2015], and the electron temperature enhancement is found to be positively correlated with the magnitude of the field-aligned current. In a few events with high-resolution Swarm electric field instrument (EFI) data, we find that the on-time pulsating auroral patch is associated with structured electric field disturbances with peaks exceeding 10 mV/m. Based upon observations and ionospheric models, we consider and evaluate several possible mechanisms that may account for the

  9. A swarm of autonomous miniature underwater robot drifters for exploring submesoscale ocean dynamics.

    PubMed

    Jaffe, Jules S; Franks, Peter J S; Roberts, Paul L D; Mirza, Diba; Schurgers, Curt; Kastner, Ryan; Boch, Adrien

    2017-01-24

    Measuring the ever-changing 3-dimensional (3D) motions of the ocean requires simultaneous sampling at multiple locations. In particular, sampling the complex, nonlinear dynamics associated with submesoscales (<1-10 km) requires new technologies and approaches. Here we introduce the Mini-Autonomous Underwater Explorer (M-AUE), deployed as a swarm of 16 independent vehicles whose 3D trajectories are measured near-continuously, underwater. As the vehicles drift with the ambient flow or execute preprogrammed vertical behaviours, the simultaneous measurements at multiple, known locations resolve the details of the flow within the swarm. We describe the design, construction, control and underwater navigation of the M-AUE. A field programme in the coastal ocean using a swarm of these robots programmed with a depth-holding behaviour provides a unique test of a physical-biological interaction leading to plankton patch formation in internal waves. The performance of the M-AUE vehicles illustrates their novel capability for measuring submesoscale dynamics.

  10. A swarm of autonomous miniature underwater robot drifters for exploring submesoscale ocean dynamics

    NASA Astrophysics Data System (ADS)

    Jaffe, Jules S.; Franks, Peter J. S.; Roberts, Paul L. D.; Mirza, Diba; Schurgers, Curt; Kastner, Ryan; Boch, Adrien

    2017-01-01

    Measuring the ever-changing 3-dimensional (3D) motions of the ocean requires simultaneous sampling at multiple locations. In particular, sampling the complex, nonlinear dynamics associated with submesoscales (<1-10 km) requires new technologies and approaches. Here we introduce the Mini-Autonomous Underwater Explorer (M-AUE), deployed as a swarm of 16 independent vehicles whose 3D trajectories are measured near-continuously, underwater. As the vehicles drift with the ambient flow or execute preprogrammed vertical behaviours, the simultaneous measurements at multiple, known locations resolve the details of the flow within the swarm. We describe the design, construction, control and underwater navigation of the M-AUE. A field programme in the coastal ocean using a swarm of these robots programmed with a depth-holding behaviour provides a unique test of a physical-biological interaction leading to plankton patch formation in internal waves. The performance of the M-AUE vehicles illustrates their novel capability for measuring submesoscale dynamics.

  11. Identifying and quantifying interactions in a laboratory swarm

    NASA Astrophysics Data System (ADS)

    Puckett, James; Kelley, Douglas; Ouellette, Nicholas

    2013-03-01

    Emergent collective behavior, such as in flocks of birds or swarms of bees, is exhibited throughout the animal kingdom. Many models have been developed to describe swarming and flocking behavior using systems of self-propelled particles obeying simple rules or interacting via various potentials. However, due to experimental difficulties and constraints, little empirical data exists for characterizing the exact form of the biological interactions. We study laboratory swarms of flying Chironomus riparius midges, using stereoimaging and particle tracking techniques to record three-dimensional trajectories for all the individuals in the swarm. We describe methods to identify and quantify interactions by examining these trajectories, and report results on interaction magnitude, frequency, and mutuality.

  12. Genetic Particle Swarm Optimization–Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection

    PubMed Central

    Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

    2016-01-01

    In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm. PMID:27483285

  13. Genetic Particle Swarm Optimization-Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection.

    PubMed

    Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

    2016-07-30

    In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm.

  14. Small-scale field-aligned currents caused by tropical cyclones as observed by the SWARM satellites above the ionosphere

    NASA Astrophysics Data System (ADS)

    Aoyama, T.; Iyemori, T.; Nakanishi, K.

    2014-12-01

    We present case studies of small-scale magnetic fluctuations above typhoons, hurricanes and cyclones as observed by the swarm constellation. It is reported lately that AGWs(atmospheric gravity waves) generated by meteorological phenomena in the troposphere such as typhoons and tornadoes, large earthquakes and volcanic eruptions propagate to the mesosphere and thermosphere. We observe them in various forms(e.g. airglows, ionospheric disturbances and TEC variations). We are proposing the following model. AGWs caused by atmospheric disturbances in the troposphere propagate to the ionospheric E-layer, drive dynamo action and generate field-aligned currents. The satellites observe magnetic fluctuations above the ionosphere. In this presentation, we focus on cases of tropical cyclone(hurricanes in North America, typhoons in North-West Pacific).

  15. Honey Bee Swarms Aboard the USNS Comfort: Recommendations for Sting Prevention, Swarm Removal, and Medical Readiness on Military Ships.

    PubMed

    Dunford, James C; Kronmann, Karl C; Peet, Luke R; Stancil, Jeffrey D

    2016-01-01

    The article provides observations of multiple honey bee (Apis mellifera) swarms aboard the USNS Comfort (TAH-20) during the Continuing Promise 2015 mission. A brief overview of swarming biology is given along with control/removal recommendations to reduce sting exposures. The observations suggest that preventive medicine personnel should provide adequate risk communications about the potential occurrence of bee swarms aboard military ships, and medical department personnel should be prepared for the possibility of treating of multiple sting exposures, especially in the Southern Command Area of Operations where the Africanized genotype of A mellifera is common.

  16. The Maupin, Oregon Earthquake Swarm

    NASA Astrophysics Data System (ADS)

    Braunmiller, J.; Williams, M.; Trehu, A. M.; Nabelek, J.

    2008-12-01

    The area near Maupin, Oregon has experienced over 300 earthquakes since December 2006. The events, located by the Pacific Northwest Seismic Network (PNSN), occurred ~10 km SE of the town in central Oregon and ~50 km E-SE of Mount Hood. The temporal event pattern and lack of a distinct main shock are characteristic of an earthquake swarm with the event-size distribution indicating a low b-value similar to other non-volcanic swarms. Locations show a NW-SE trending, ~4x3 km cluster at apparent depths of 12-24 km. The largest events (Mw=3.8 and 3.9) on March 1, 2007 and July 14, 2008 occurred more than one year apart; 11 other events had a magnitude of 3 or greater. The larger events were felt locally. During the first 14 months EarthScope USArray seismic stations surrounded the swarm, providing a unique high-quality dataset. Waveform similarity at the closest USArray site G06A indicates hypocenters are much tighter than suggested by the PNSN distribution. Moment tensor inversion reveals nearly identical double- couple strike-slip mechanisms on a plane striking ~15° NW for the three largest 2007 events and the July 2008 event. The April 2008 Mw=3.3 event is rotated ~10° clockwise consistent with slight changes of G06A three-component waveforms relative to the other events. Preferred centroid depths are in the 15-20 km range. Historically, seismicity in the Pacific Northwest east of the Cascades is characterized by sporadic bursts of clustered seismicity with occasional M=6 earthquakes. The largest instrumentally recorded earthquake near Maupin (Mw=4.6) occurred 1976. An earlier swarm was observed 1987, but since then only ~2 events/yr occurred until the current swarm. In spite of recurrent seismicity, exposed surface rocks near Maupin are undeformed lava flows of the Columbia River Basalt Group and older John Day volcanics. The geologic map of Oregon shows a NW-trending dip slip fault near the epicenter area, inconsistent with moment tensor solutions. The cause for

  17. Particle swarm optimization with recombination and dynamic linkage discovery.

    PubMed

    Chen, Ying-Ping; Peng, Wen-Chih; Jian, Ming-Chung

    2007-12-01

    In this paper, we try to improve the performance of the particle swarm optimizer by incorporating the linkage concept, which is an essential mechanism in genetic algorithms, and design a new linkage identification technique called dynamic linkage discovery to address the linkage problem in real-parameter optimization problems. Dynamic linkage discovery is a costless and effective linkage recognition technique that adapts the linkage configuration by employing only the selection operator without extra judging criteria irrelevant to the objective function. Moreover, a recombination operator that utilizes the discovered linkage configuration to promote the cooperation of particle swarm optimizer and dynamic linkage discovery is accordingly developed. By integrating the particle swarm optimizer, dynamic linkage discovery, and recombination operator, we propose a new hybridization of optimization methodologies called particle swarm optimization with recombination and dynamic linkage discovery (PSO-RDL). In order to study the capability of PSO-RDL, numerical experiments were conducted on a set of benchmark functions as well as on an important real-world application. The benchmark functions used in this paper were proposed in the 2005 Institute of Electrical and Electronics Engineers Congress on Evolutionary Computation. The experimental results on the benchmark functions indicate that PSO-RDL can provide a level of performance comparable to that given by other advanced optimization techniques. In addition to the benchmark, PSO-RDL was also used to solve the economic dispatch (ED) problem for power systems, which is a real-world problem and highly constrained. The results indicate that PSO-RDL can successfully solve the ED problem for the three-unit power system and obtain the currently known best solution for the 40-unit system.

  18. Collective motion in Proteus mirabilis swarms

    NASA Astrophysics Data System (ADS)

    Haoran, Xu

    Proteus mirabilisis a Gram-negative, rod-shaped bacterium. It is widely distributed in soil and water, and it is well known for exhibiting swarming motility on nutrient agar surfaces. In our study, we focused on the collective motility of P. mirabilis and uncovered a range of interesting phenomena. Here we will present our efforts to understand these phenomena through experiments and simulation. Mailing address: Room 306 Science Centre North Block, The Chinese University of Hong Kong, Shatin, N.T. Hong Kong SAR. Phone: +852-3943-6354. Fax: +852-2603-5204. E-mail:xhrphx@gmail.com.

  19. Position-adaptive explosive detection concepts for swarming micro-UAVs

    NASA Astrophysics Data System (ADS)

    Selmic, Rastko R.; Mitra, Atindra

    2008-04-01

    -adaptive detection (i.e. based on the example in the previous paragraph) consisting of position-adaptive fluid actuators (fans) and position-adaptive sensors. Based on these results, a preliminary analysis of sensor requirements for these fluid actuators and sensors is presented for small-UAVs in a field-enabled explosive detection environment. The computational fluid dynamics (CFD) simulation software Fluent is used to simulate the air flow in the corridor model containing a box with explosive particles. It is found that such flow is turbulent with Reynolds number greater than 106. Simulation methods and results are presented which show particle velocity and concentration distribution throughout the closed box. The results indicate that the CFD-based method can be used for other sensor placement and deployment optimization problems. These techniques and results can be applied towards the development of future system-of-system UAV swarms for defense, homeland defense, and security applications.

  20. A Winner Determination Algorithm for Combinatorial Auctions Based on Hybrid Artificial Fish Swarm Algorithm

    NASA Astrophysics Data System (ADS)

    Zheng, Genrang; Lin, ZhengChun

    The problem of winner determination in combinatorial auctions is a hotspot electronic business, and a NP hard problem. A Hybrid Artificial Fish Swarm Algorithm(HAFSA), which is combined with First Suite Heuristic Algorithm (FSHA) and Artificial Fish Swarm Algorithm (AFSA), is proposed to solve the problem after probing it base on the theories of AFSA. Experiment results show that the HAFSA is a rapidly and efficient algorithm for The problem of winner determining. Compared with Ant colony Optimization Algorithm, it has a good performance with broad and prosperous application.

  1. Limited Bandwidth Recognition of Collective Behaviors in Bio-Inspired Swarms

    DTIC Science & Technology

    2014-05-09

    collective? Some swarm models exhibit multiple emergent behaviors from the same parameters. This provides increased expressivity at the cost of...swarms, namely, how do you know what the swarm is doing if you can’t ob- serve every agent in the collective? Some swarm models exhibit multiple ...flocking [15, 21, 12] or cyclic behavior [8, 7], and in some cases can exhibit multiple group behaviors depending on the model parameters used [6, 3, 17

  2. Field-aligned Currents' Scale Analysis Performed by the Swarm Constellation

    NASA Astrophysics Data System (ADS)

    Luhr, H.; Park, J.; Gjerloev, J. W.; Rauberg, J.; Michaelis, I.; Le, G.; Merayo, J. M. G.; Brauer, P.

    2014-12-01

    We present a statistical study of the temporal and spatial scale characteristics of different field-aligned current (FAC) types. Very suitable for this purpose is the closely spaced Swarm satellite formation, which existed shortly after launch during the commissioning phase. As dataset we use the standard Level 2 product, Single Satellite FAC, which comes at a data rate of 1 Hz, corresponding to an along-track distance of 7.5 km. FACs are known to cover a wide range of scales from 1km to several hundred kilometres, the smaller the scale the larger the amplitude. We like to divide the FACs into two classes. Those of intermediate scale, some tens of kilometres, which are carried predominantly by kinetic Alfvén waves, while the large-scale FACs are assumed to be stationary current structures on the timescales of a satellite crossing. For distinguishing between the two we first look how the temporal variability changes with scale. For that we consider subsequent measurements at the same point, the orbital cross-over near the geographic poles, and interpret the temporal current changes. Here we focus on observations in the southern hemisphere at locations where the geographic pole lies within the auroral region. In a next step the latitudinal and longitudinal scales of the larger-scale FAC structures are investigated. FACs related to Alfvén waves cannot be studied in this way because we have no simultaneous measurements at the same latitude and longitude. The results from this analysis are different for dayside and nightside. Implications for the FAC characteristics resulting from these observations are interpreted in the end.

  3. A Markov Chain Approach to Probabilistic Swarm Guidance

    NASA Technical Reports Server (NTRS)

    Acikmese, Behcet; Bayard, David S.

    2012-01-01

    This paper introduces a probabilistic guidance approach for the coordination of swarms of autonomous agents. The main idea is to drive the swarm to a prescribed density distribution in a prescribed region of the configuration space. In its simplest form, the probabilistic approach is completely decentralized and does not require communication or collabo- ration between agents. Agents make statistically independent probabilistic decisions based solely on their own state, that ultimately guides the swarm to the desired density distribution in the configuration space. In addition to being completely decentralized, the probabilistic guidance approach has a novel autonomous self-repair property: Once the desired swarm density distribution is attained, the agents automatically repair any damage to the distribution without collaborating and without any knowledge about the damage.

  4. A solution quality assessment method for swarm intelligence optimization algorithms.

    PubMed

    Zhang, Zhaojun; Wang, Gai-Ge; Zou, Kuansheng; Zhang, Jianhua

    2014-01-01

    Nowadays, swarm intelligence optimization has become an important optimization tool and wildly used in many fields of application. In contrast to many successful applications, the theoretical foundation is rather weak. Therefore, there are still many problems to be solved. One problem is how to quantify the performance of algorithm in finite time, that is, how to evaluate the solution quality got by algorithm for practical problems. It greatly limits the application in practical problems. A solution quality assessment method for intelligent optimization is proposed in this paper. It is an experimental analysis method based on the analysis of search space and characteristic of algorithm itself. Instead of "value performance," the "ordinal performance" is used as evaluation criteria in this method. The feasible solutions were clustered according to distance to divide solution samples into several parts. Then, solution space and "good enough" set can be decomposed based on the clustering results. Last, using relative knowledge of statistics, the evaluation result can be got. To validate the proposed method, some intelligent algorithms such as ant colony optimization (ACO), particle swarm optimization (PSO), and artificial fish swarm algorithm (AFS) were taken to solve traveling salesman problem. Computational results indicate the feasibility of proposed method.

  5. Does swarming cause honey bees to update their solar ephemerides?

    PubMed

    Towne, William F; Baer, Christopher M; Fabiny, Sarah J; Shinn, Lisa M

    2005-11-01

    Spatial orientation in the social insects offers several examples of specialized learning mechanisms that underlie complex learning tasks. Here we study one of these systems: the processes by which honey bees update, or fail to update, their memories of the sun's daily pattern of movement (the solar ephemeris function) in relation to the landscape. Specifically, we ask whether bees that have initially learned the solar ephemeris function relative to a conspicuous treeline at their natal site can later realign the ephemeris to a differently oriented treeline. We first confirm and clarify an earlier finding that bees transplanted passively (by being carried) do not re-learn the solar ephemeris in relation to the new treeline. When they cannot detect the sun directly, as on overcast days, these transplanted bees use a solar ephemeris function appropriate for their natal site, despite days or weeks of experience at the new site. We then ask whether bees put through a swarming process as they are transplanted are induced to re-learn the solar ephemeris function at the new site, as swarming is a natural process wherein bees transplant themselves. Most of the swarmed bees failed to re-learn, even though they did extensive learning flights (in comparison with those of non-swarmed controls) as they first emerged from the hive at the new site. We hypothesize that the bees' representation of the solar ephemeris function is stored in an encapsulated cognitive module in which the ephemeris is inextricably linked to the reference landscape in which it was learned.

  6. A Challenging Trio in Space 'Routine' Operations of the Swarm Satellite Constellation

    NASA Astrophysics Data System (ADS)

    Diekmann, Frank-Jurgen; Clerigo, Ignacio; Albini, Giuseppe; Maleville, Laurent; Neto, Alessandro; Patterson, David; Nino, Ana Piris; Sieg, Detlef

    2016-08-01

    Swarm is the first ESA Earth Observation Mission with three satellites flying in a semi-controlled constellation. The trio is operated from ESA's satellite control centre ESOC in Darmstadt, Germany. The Swarm Flight Operations Segment consists of the typical elements of a satellite control system at ESOC, but had to be carefully tailored for this innovative mission. The main challenge was the multi-satellite system of Swarm, which necessitated the development of a Mission Control System with a multi-domain functionality, both in hardware and software and covering real-time and backup domains. This was driven by the need for extreme flexibility for constellation operations and parallel activities.The three months of commissioning in 2014 were characterized by a very tight and dynamically changing schedule of activities. All operational issues could be solved during that time, including the challenging orbit acquisition phase to achieve the final constellation.Although the formal spacecraft commissioning phase was concluded in spring 2014, the investigations for some payload instruments continue even today. The Electrical Field Instruments are for instance still being tested in order to characterize and improve science data quality. Various test phases also became necessary for the Accelerometers on the Swarm satellites. In order to improve the performance of the GPS Receivers for better scientific exploitation and to minimize the failures due to loss of synchronization, a number of parameter changes were commanded via on-board patches.Finally, to minimize the impact on operations, a new strategy had to be implemented to handle single/multi bit errors in the on-board mass Memories, defining when to ignore and when to restore the memory via a re-initialisation.The poster presentation summarizes the Swarm specific ground segment elements of the FOS and explains some of the extended payload commissioning operations, turning Swarm into a most demanding and challenging

  7. Stable swarming using adaptive long-range interactions

    NASA Astrophysics Data System (ADS)

    Gorbonos, Dan; Gov, Nir S.

    2017-04-01

    Sensory mechanisms in biology, from cells to humans, have the property of adaptivity, whereby the response produced by the sensor is adapted to the overall amplitude of the signal, reducing the sensitivity in the presence of strong stimulus, while increasing it when it is weak. This property is inherently energy consuming and a manifestation of the nonequilibrium nature of living organisms. We explore here how adaptivity affects the effective forces that organisms feel due to others in the context of a uniform swarm, in both two and three dimensions. The interactions between the individuals are taken to be attractive and long-range and of power-law form. We find that the effects of adaptivity inside the swarm are dramatic, where the effective forces decrease (or remain constant) with increasing swarm density. Linear stability analysis demonstrates how this property prevents collapse (Jeans instability), when the forces are adaptive. Adaptivity therefore endows swarms with a natural mechanism for self-stabilization.

  8. Phenology of Honey Bee Swarm Departure in New Jersey, United States.

    PubMed

    Gilley, D C; Courtright, T J; Thom, C

    2018-03-31

    Departure of swarms from honey bee (Apis mellifera Linnaeus (Hymenoptera: Apidae)) nests is an important reproductive event for wild honey bee colonies and economically costly in managed bee colonies. The seasonal timing of swarm departure varies regionally and annually, creating challenges for honey bee management and emphasizing the potential for swarming behavior to be affected by plant-pollinator phenological mismatch. In this study, we first document variability in the timing of swarm departure across the large and heterogeneous geographical area of New Jersey over 4 years using 689 swarm-cluster observations. Second, hypothesizing that honey bee colonies adaptively tune the timing of swarm departure to match floral food-resource availability, we predicted that growing degree-days could be used to account for regional and annual variability. To test this idea, we used local weather records to determine the growing degree-day on which each swarm cluster was observed and tested for differences among climate regions and years. The state-wide mean swarm cluster date was May 15 (± 0.6 d), with moderate but significant differences among the state's five climate regions and between years. Use of degree-day information suggests that local heat accumulation can account for some climate-region differences in swarm-departure timing. Annual variation existed on a scale of only several days and was not accounted for by growing degree-days, suggesting little adaptive tuning of swarm-departure timing with respect to local heat accumulation.

  9. Swarm Counter-Asymmetric-Threat (CAT) 6-DOF Dynamics Simulation

    DTIC Science & Technology

    2005-07-01

    NAWCWD TP 8593 Swarm Counter-Asymmetric-Threat ( CAT ) 6-DOF Dynamics Simulation by James Bobinchak Weapons and Energetics...mathematical models used in the swarm counter- asymmetric-threat ( CAT ) simulation and the results of extensive Monte Carlo simulations. The swarm CAT ...Asymmetric-Threat ( CAT ) 6-DOF Dynamics Simulation (U) 6. AUTHOR(S) James Bobinchak and Gary Hewer 7. PERFORMING ORGANIZATION NAME(S) AND

  10. Operating Small Sat Swarms as a Single Entity: Introducing SODA

    NASA Technical Reports Server (NTRS)

    Conn, Tracie; Plice, Laura; Dono Perez, Andres; Ho, Michael

    2017-01-01

    NASA's decadal survey determined that simultaneous measurements from a 3D volume of space are advantageous for a variety of studies in space physics and Earth science. Therefore, swarm concepts with multiple spacecraft in close proximity are a growing topic of interest in the small satellite community. Among the capabilities needed for swarm missions is a means to maintain operator-specified geometry, alignment, or separation. Swarm stationkeeping poses a planning challenge due to the limited scalability of ground resources. To address scalable control of orbital dynamics, we introduce SODA - Swarm Orbital Dynamics Advisor - a tool that accepts high-level configuration commands and provides the orbital maneuvers needed to achieve the desired type of swarm relative motion. Rather than conventional path planning, SODA's innovation is the use of artificial potential functions to define boundaries and keepout regions. The software architecture includes high fidelity propagation, accommodates manual or automated inputs, displays motion animations, and returns maneuver commands and analytical results. Currently, two swarm types are enabled: in-train distribution and an ellipsoid volume container. Additional swarm types, simulation applications, and orbital destinations are in planning stages.

  11. Drone Swarms

    DTIC Science & Technology

    2017-05-25

    Adjustment in Aggressive and Nonaggressive Children,” Journal of Abnormal Child Psychology 32, no. 3 (June 2004): 305-20. 128 Naveh, In Pursuit of... Abnormal Child Psychology 32, no. 3 (June 2004): 305-20. Bousquet, Antoine. The Scientific Way of Warfare: Order and Chaos of the Battlefields of...38 Drone Swarm Integration

  12. Streaming Swarm of Nano Space Probes for Modern Analytical Methods Applied to Planetary Science

    NASA Astrophysics Data System (ADS)

    Vizi, P. G.; Horvath, A. F.; Berczi, Sz.

    2017-11-01

    Streaming swarms gives possibilities to collect data from big fields in one time. The whole streaming fleet possible to behave like one big organization and can be realized as a planetary mission solution with stream type analytical methods.

  13. Presence of Russian honey bee genotypes in swarms in Louisiana.

    USDA-ARS?s Scientific Manuscript database

    Swarm traps were placed in an area around USDA, ARS apiaries near Baton Rouge, Louisiana, which had contained ARS Russian and other honey bees for several years. Eighty swarms were sampled and analyzed for their genotype (Russian, hybrid or non-Russian) and mite infestation percentages. Ten swarms...

  14. Empirical Scaling Relations of Source Parameters For The Earthquake Swarm 2000 At Novy Kostel (vogtland/nw-bohemia)

    NASA Astrophysics Data System (ADS)

    Heuer, B.; Plenefisch, T.; Seidl, D.; Klinge, K.

    Investigations on the interdependence of different source parameters are an impor- tant task to get more insight into the mechanics and dynamics of earthquake rup- ture, to model source processes and to make predictions for ground motion at the surface. The interdependencies, providing so-called scaling relations, have often been investigated for large earthquakes. However, they are not commonly determined for micro-earthquakes and swarm-earthquakes, especially for those of the Vogtland/NW- Bohemia region. For the most recent swarm in the Vogtland/NW-Bohemia, which took place between August and December 2000 near Novy Kostel (Czech Republic), we systematically determine the most important source parameters such as energy E0, seismic moment M0, local magnitude ML, fault length L, corner frequency fc and rise time r and build their interdependencies. The swarm of 2000 is well suited for such investigations since it covers a large magnitude interval (1.5 ML 3.7) and there are also observations in the near-field at several stations. In the present paper we mostly concentrate on two near-field stations with hypocentral distances between 11 and 13 km, namely WERN (Wernitzgrün) and SBG (Schönberg). Our data processing includes restitution to true ground displacement and rotation into the ray-based prin- cipal co-ordinate system, which we determine by the covariance matrix of the P- and S-displacement, respectively. Data preparation, determination of the distinct source parameters as well as statistical interpretation of the results will be exemplary pre- sented. The results will be discussed with respect to temporal variations in the swarm activity (the swarm consists of eight distinct sub-episodes) and already existing focal mechanisms.

  15. The January 2006 Volcanic-Tectonic Earthquake Swarm at Mount Martin, Alaska

    USGS Publications Warehouse

    Dixon, James P.; Power, John A.

    2009-01-01

    On January 8, 2006, a swarm of volcanic-tectonic earthquakes began beneath Mount Martin at the southern end of the Katmai volcanic cluster. This was the first recorded swarm at Mount Martin since continuous seismic monitoring began in 1996. The number of located earthquakes increased during the next four days, reaching a peak on January 11. For the next two days, the seismic activity decreased, and on January 14, the number of events increased to twice the previous day's total. Following this increase in activity, seismicity declined, returning to background levels by the end of the month. The Alaska Volcano Observatory located 860 earthquakes near Mount Martin during January 2006. No additional signs of volcanic unrest were noted in association with this earthquake swarm. The earthquakes in the Mount Martin swarm, relocated using the double difference technique, formed an elongated cluster dipping to the southwest. Focal mechanisms beneath Mount Martin show a mix of normal, thrust, and strike-slip solutions, with normal focal mechanisms dominating. For earthquakes more than 1 km from Mount Martin, all focal mechanisms showed normal faulting. The calculated b-value for the Mount Martin swarm is 0.98 and showed no significant change before, during, or after the swarm. The triggering mechanism for the Mount Martin swarm is unknown. The time-history of earthquake occurrence is indicative of a volcanic cause; however, there were no low-frequency events or observations, such as increased steaming associated with the swarm. During the swarm, there was no change in the b-value, and the distribution and type of focal mechanisms were similar to those in the period before the anomalous activity. The short duration of the swarm, the similarity in observed focal mechanisms, and the lack of additional signs of unrest suggest this swarm did not result from a large influx of magma within the shallow crust beneath Mount Martin.

  16. Swarms with canonical active Brownian motion.

    PubMed

    Glück, Alexander; Hüffel, Helmuth; Ilijić, Saša

    2011-05-01

    We present a swarm model of Brownian particles with harmonic interactions, where the individuals undergo canonical active Brownian motion, i.e., each Brownian particle can convert internal energy to mechanical energy of motion. We assume the existence of a single global internal energy of the system. Numerical simulations show amorphous swarming behavior as well as static configurations. Analytic understanding of the system is provided by studying stability properties of equilibria.

  17. Compact cancer biomarkers discovery using a swarm intelligence feature selection algorithm.

    PubMed

    Martinez, Emmanuel; Alvarez, Mario Moises; Trevino, Victor

    2010-08-01

    Biomarker discovery is a typical application from functional genomics. Due to the large number of genes studied simultaneously in microarray data, feature selection is a key step. Swarm intelligence has emerged as a solution for the feature selection problem. However, swarm intelligence settings for feature selection fail to select small features subsets. We have proposed a swarm intelligence feature selection algorithm based on the initialization and update of only a subset of particles in the swarm. In this study, we tested our algorithm in 11 microarray datasets for brain, leukemia, lung, prostate, and others. We show that the proposed swarm intelligence algorithm successfully increase the classification accuracy and decrease the number of selected features compared to other swarm intelligence methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

  18. A new bio-inspired optimisation algorithm: Bird Swarm Algorithm

    NASA Astrophysics Data System (ADS)

    Meng, Xian-Bing; Gao, X. Z.; Lu, Lihua; Liu, Yu; Zhang, Hengzhen

    2016-07-01

    A new bio-inspired algorithm, namely Bird Swarm Algorithm (BSA), is proposed for solving optimisation applications. BSA is based on the swarm intelligence extracted from the social behaviours and social interactions in bird swarms. Birds mainly have three kinds of behaviours: foraging behaviour, vigilance behaviour and flight behaviour. Birds may forage for food and escape from the predators by the social interactions to obtain a high chance of survival. By modelling these social behaviours, social interactions and the related swarm intelligence, four search strategies associated with five simplified rules are formulated in BSA. Simulations and comparisons based on eighteen benchmark problems demonstrate the effectiveness, superiority and stability of BSA. Some proposals for future research about BSA are also discussed.

  19. Seismic swarm associated with the 2008 eruption of Kasatochi Volcano, Alaska: earthquake locations and source parameters

    USGS Publications Warehouse

    Ruppert, Natalia G.; Prejean, Stephanie G.; Hansen, Roger A.

    2011-01-01

    An energetic seismic swarm accompanied an eruption of Kasatochi Volcano in the central Aleutian volcanic arc in August of 2008. In retrospect, the first earthquakes in the swarm were detected about 1 month prior to the eruption onset. Activity in the swarm quickly intensified less than 48 h prior to the first large explosion and subsequently subsided with decline of eruptive activity. The largest earthquake measured as moment magnitude 5.8, and a dozen additional earthquakes were larger than magnitude 4. The swarm exhibited both tectonic and volcanic characteristics. Its shear failure earthquake features were b value = 0.9, most earthquakes with impulsive P and S arrivals and higher-frequency content, and earthquake faulting parameters consistent with regional tectonic stresses. Its volcanic or fluid-influenced seismicity features were volcanic tremor, large CLVD components in moment tensor solutions, and increasing magnitudes with time. Earthquake location tests suggest that the earthquakes occurred in a distributed volume elongated in the NS direction either directly under the volcano or within 5-10 km south of it. Following the MW 5.8 event, earthquakes occurred in a new crustal volume slightly east and north of the previous earthquakes. The central Aleutian Arc is a tectonically active region with seismicity occurring in the crusts of the Pacific and North American plates in addition to interplate events. We postulate that the Kasatochi seismic swarm was a manifestation of the complex interaction of tectonic and magmatic processes in the Earth's crust. Although magmatic intrusion triggered the earthquakes in the swarm, the earthquakes failed in context of the regional stress field.

  20. Virtual spring damper method for nonholonomic robotic swarm self-organization and leader following

    NASA Astrophysics Data System (ADS)

    Wiech, Jakub; Eremeyev, Victor A.; Giorgio, Ivan

    2018-04-01

    In this paper, we demonstrate a method for self-organization and leader following of nonholonomic robotic swarm based on spring damper mesh. By self-organization of swarm robots we mean the emergence of order in a swarm as the result of interactions among the single robots. In other words the self-organization of swarm robots mimics some natural behavior of social animals like ants among others. The dynamics of two-wheel robot is derived, and a relation between virtual forces and robot control inputs is defined in order to establish stable swarm formation. Two cases of swarm control are analyzed. In the first case the swarm cohesion is achieved by virtual spring damper mesh connecting nearest neighboring robots without designated leader. In the second case we introduce a swarm leader interacting with nearest and second neighbors allowing the swarm to follow the leader. The paper ends with numeric simulation for performance evaluation of the proposed control method.

  1. Swarm robotics and minimalism

    NASA Astrophysics Data System (ADS)

    Sharkey, Amanda J. C.

    2007-09-01

    Swarm Robotics (SR) is closely related to Swarm Intelligence, and both were initially inspired by studies of social insects. Their guiding principles are based on their biological inspiration and take the form of an emphasis on decentralized local control and communication. Earlier studies went a step further in emphasizing the use of simple reactive robots that only communicate indirectly through the environment. More recently SR studies have moved beyond these constraints to explore the use of non-reactive robots that communicate directly, and that can learn and represent their environment. There is no clear agreement in the literature about how far such extensions of the original principles could go. Should there be any limitations on the individual abilities of the robots used in SR studies? Should knowledge of the capabilities of social insects lead to constraints on the capabilities of individual robots in SR studies? There is a lack of explicit discussion of such questions, and researchers have adopted a variety of constraints for a variety of reasons. A simple taxonomy of swarm robotics is presented here with the aim of addressing and clarifying these questions. The taxonomy distinguishes subareas of SR based on the emphases and justifications for minimalism and individual simplicity.

  2. Probabilistic Swarm Guidance using Optimal Transport

    DTIC Science & Technology

    2014-10-10

    controlled to collectively exhibit useful emergent behavior [2]–[5]. Similarly, swarms of hundreds to thousands of femtosatellites (100-gram-class...algorithm using inhomo- geneous Markov chains (PSG– IMC ), each agent chooses the tuning parameter (ξjk) based on the Hellinger distance (HD) between the...PGA and PSG– IMC in the next section. B. Simulation Results We now present the setup of this simulation example. The swarm containing m = 5000 agents is

  3. Investigating the Origin of Seismic Swarms

    NASA Astrophysics Data System (ADS)

    Govoni, Aladino; Passarelli, Luigi; Braun, Thomas; Maccaferri, Francesco; Moretti, Milena; Lucente, Francesco Pio; Rivalta, Eleonora; Cesca, Simone; Hainzl, Sebastian; Woith, Heiko; De Gori, Pasquale; Dahm, Torsten; Chiarabba, Claudio; Margheriti, Lucia

    2013-10-01

    According to the U.S. Geological Survey's Earthquake Hazards Program, a seismic swarm is "a localized surge of earthquakes, with no one shock being conspicuously larger than all other shocks of the swarm. They might occur in a variety of geologic environments and are not known to be indicative of any change in the long-term seismic risk of the region in which they occur" (http://vulcan.wr.usgs.gov/Glossary/Seismicity/description_earthquakes.html).

  4. Survey of Methods and Algorithms of Robot Swarm Aggregation

    NASA Astrophysics Data System (ADS)

    E Shlyakhov, N.; Vatamaniuk, I. V.; Ronzhin, A. L.

    2017-01-01

    The paper considers the problem of swarm aggregation of autonomous robots with the use of three methods based on the analogy of the behavior of biological objects. The algorithms substantiating the requirements for hardware realization of sensor, computer and network resources and propulsion devices are presented. Techniques for efficiency estimation of swarm aggregation via space-time characteristics are described. The developed model of the robot swarm reconfiguration into a predetermined three-dimensional shape is presented.

  5. Searching for effective forces in laboratory insect swarms

    NASA Astrophysics Data System (ADS)

    Puckett, James G.; Kelley, Douglas H.; Ouellette, Nicholas T.

    2014-04-01

    Collective animal behaviour is often modeled by systems of agents that interact via effective social forces, including short-range repulsion and long-range attraction. We search for evidence of such effective forces by studying laboratory swarms of the flying midge Chironomus riparius. Using multi-camera stereoimaging and particle-tracking techniques, we record three-dimensional trajectories for all the individuals in the swarm. Acceleration measurements show a clear short-range repulsion, which we confirm by considering the spatial statistics of the midges, but no conclusive long-range interactions. Measurements of the mean free path of the insects also suggest that individuals are on average very weakly coupled, but that they are also tightly bound to the swarm itself. Our results therefore suggest that some attractive interaction maintains cohesion of the swarms, but that this interaction is not as simple as an attraction to nearest neighbours.

  6. The 2017 Maple Creek Seismic Swarm in Yellowstone National Park

    NASA Astrophysics Data System (ADS)

    Pang, G.; Hale, J. M.; Farrell, J.; Burlacu, R.; Koper, K. D.; Smith, R. B.

    2017-12-01

    The University of Utah Seismograph Stations (UUSS) performs near-real-time monitoring of seismicity in the region around Yellowstone National Park in partnership with the United States Geological Survey and the National Park Service. UUSS operates and maintains 29 seismic stations with network code WY (short-period, strong-motion, and broadband) and records data from five other seismic networks—IW, MB, PB, TA, and US—to enhance the location capabilities in the Yellowstone region. A seismic catalog is produced using a conventional STA/LTA detector and single-event location techniques (Hypoinverse). On June 12, 2017, a seismic swarm began in Yellowstone National Park about 5 km east of Hebgen Lake. The swarm is adjacent to the source region of the 1959 MW 7.3 Hebgen Lake earthquake, in an area corresponding to positive Coulumb stress change from that event. As of Aug. 1, 2017, the swarm consists of 1481 earthquakes with 1 earthquake above magnitude 4, 8 earthquakes in the magnitude 3 range, 115 earthquakes in the magnitude 2 range, 469 earthquakes in the magnitude 1 range, 856 earthquakes in the magnitude 0 range, 22 earthquakes with negative magnitudes, and 10 earthquakes with no magnitude. Earthquake depths are mostly between 3 and 10 km and earthquake depth increases toward the northwest. Moment tensors for the 2 largest events (3.6 MW and 4.4. MW) show strike-slip faulting with T axes oriented NE-SW, consistent with the regional stress field. We are currently using waveform cross-correlation methods to measure differential travel times that are being used with the GrowClust program to generate high-accuracy relative relocations. Those locations will be used to identify structures in the seismicity and make inferences about the tectonic and magmatic processes causing the swarm.

  7. Mapping b-value for 2009 Harrat Lunayyir earthquake swarm, western Saudi Arabia and Coulomb stress for its mainshock

    NASA Astrophysics Data System (ADS)

    Abdelfattah, Ali K.; Mogren, Saad; Mukhopadhyay, Manoj

    2017-01-01

    The Harrat Lunayyir (HL) earthquake swarm of 2009 originated in the HL volcanic field and attracted global attention mainly due to three factors: (i) its relatively short life span that ushered a large frequency of the swarm population (30,000 events in < 2 years), (ii) the swarm epicenter zone was contained within a small crustal volume under the HL and (iii) the migratory nature of the swarm following the tectonic trend of a normal fault zone beneath HL. The HL belongs to the Large Igneous Province of Saudi Arabia (LIP-SA) where it correlates to the Great Dikes locally. Our aim in this study is to describe the spatial distribution of the hypocenters, b-value character, and Coulomb stress failure (CSF) in an attempt to analyze the underlying geodynamic process that caused the swarm. We utilize the relocated hypocenters monitored by local networks to examine the b-value characteristics for the swarm. This is best represented in a cross section showing two domains of higher b-value anomalies: two patches occurring at shallow depth and at the deeper crust to the SE from the mainshock originated at the shallower depth northwestward. Consistently positive ΔCFF pattern with a large percentage of aftershocks imply how the mainshock rupture controlled the aftershocks activity. This implies that the failure along the NNW fault trend is due to the prevailing ambient stress field imparted to the swarm. We model this by CSF associated with the mainshock for three time dependent situations: (a) foreshock and aftershock epicenters, (b) foreshock hypocenters, and (c) aftershock hypocenters. In actuality, multiple factors might have controlled the aftershock activity as we speculate that positive Coulomb stress was associated in an area where the higher b-value prevails. The CSF produced by the mainshock illustrates how the stress dissipated along the NNW normal fault zone that interrupts the Great Dykes along the Red Sea coast. These results further suggest that the crustal

  8. Emergent dynamics of laboratory insect swarms

    NASA Astrophysics Data System (ADS)

    Kelley, Douglas H.; Ouellette, Nicholas T.

    2013-01-01

    Collective animal behaviour occurs at nearly every biological size scale, from single-celled organisms to the largest animals on earth. It has long been known that models with simple interaction rules can reproduce qualitative features of this complex behaviour. But determining whether these models accurately capture the biology requires data from real animals, which has historically been difficult to obtain. Here, we report three-dimensional, time-resolved measurements of the positions, velocities, and accelerations of individual insects in laboratory swarms of the midge Chironomus riparius. Even though the swarms do not show an overall polarisation, we find statistical evidence for local clusters of correlated motion. We also show that the swarms display an effective large-scale potential that keeps individuals bound together, and we characterize the shape of this potential. Our results provide quantitative data against which the emergent characteristics of animal aggregation models can be benchmarked.

  9. Discordant introgression in a rapidly expanding hybrid swarm

    USGS Publications Warehouse

    Ward, Jessica L.; Blum, Mike J.; Walters, David M.; Porter, Brady A.; Burkhead, Noel; Freeman, Byron

    2012-01-01

    The erosion of species boundaries can involve rapid evolutionary change. Consequently, many aspects of the process remain poorly understood, including the formation, expansion, and evolution of hybrid swarms. Biological invasions involving hybridization present exceptional opportunities to study the erosion of species boundaries because timelines of interactions and outcomes are frequently well known. Here, we examined clinal variation across codominant and maternally inherited genetic markers as well as phenotypic traits to characterize the expansion and evolution of a hybrid swarm between native Cyprinella venusta and invasive Cyprinella lutrensis minnows. Discordant introgression of phenotype, microsatellite multilocus genotype, and mtDNA haplotype indicates that the observable expansion of the C. venusta x C. lutrensis hybrid swarm is a false invasion front. Both parental and hybrid individuals closely resembling C. lutrensis are numerically dominant in the expansion wake, indicating that the non-native parental phenotype may be selectively favored. These findings show that cryptic introgression can extend beyond the phenotypic boundaries of hybrid swarms and that hybrid swarms likely expand more rapidly than can be documented from phenotypic variation alone. Similarly, dominance of a single parental phenotype following an introduction event may lead to instances of species erosion being mistaken for species displacement without hybridization.

  10. Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization.

    PubMed

    Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

    2017-03-01

    Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

  11. Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization

    PubMed Central

    Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

    2017-01-01

    Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm. PMID:28257060

  12. Seismological mechanism analysis of 2015 Luanxian swarm, Hebei province,China

    NASA Astrophysics Data System (ADS)

    Tan, Yipei; Liao, Xu; Ma, Hongsheng; Zhou, Longquan; Wang, Xingzhou

    2017-04-01

    The seismological mechanism of an earthquake swarm, a kind of seismic burst activity, means the physical and dynamic process in earthquakes triggering in the swarm. Here we focus on the seismological mechanism of 2015 Luanxian swarm in Hebei province, China. The process of digital seismic waveform data processing is divided into four steps. (1) Choose the three components waveform of earthquakes in the catalog as templates, and detect missing earthquakes by scanning the continues waveforms with matched filter technique. (2) Recalibrate P and S-wave phase arrival time using waveform cross-correlation phase detection technique to eliminate the artificial error in phase picking in the observation report made by Hebei seismic network, and then we obtain a more complete catalog and a more precise seismic phase report. (3) Relocate the earthquakes in the swarm using hypoDD based on phase arrival time we recalibrated, and analyze the characteristics of swarm epicenter migration based on the earthquake relocation result. (4) Detect whether there are repeating earthquakes activity using both waveform cross-correlation standard and whether rupture areas can overlapped. We finally detect 106 missing earthquakes in the swarm, 66 of them have the magnitude greater than ML0.0, include 2 greater than ML1.0. Relocation result shows that the epicenters of earthquakes in the swarm have a strip distribution in NE-SW direction, which indicates the seismogenic structure may be a NE-SW trending fault. The spatial-temporal distribution variation of epicenters in the swarm shows a kind of two stages linear migration characteristics, in which the first stage has appeared with a higher migration velocity as 1.2 km per day, and the velocity of the second step is 0.0024 km per day. According to the three basic models to explain the seismological mechanism of earthquake swarms: cascade model, slow slip model and fluid diffusion model, repeating earthquakes activity is difficult to explain by

  13. Main field and secular variation candidate models for the 12th IGRF generation after 10 months of Swarm measurements

    NASA Astrophysics Data System (ADS)

    Saturnino, Diana; Langlais, Benoit; Civet, François; Thébault, Erwan; Mandea, Mioara

    2015-06-01

    We describe the main field and secular variation candidate models for the 12th generation of the International Geomagnetic Reference Field model. These two models are derived from the same parent model, in which the main field is extrapolated to epoch 2015.0 using its associated secular variation. The parent model is exclusively based on measurements acquired by the European Space Agency Swarm mission between its launch on 11/22/2013 and 09/18/2014. It is computed up to spherical harmonic degree and order 25 for the main field, 13 for the secular variation, and 2 for the external field. A selection on local time rather than on true illumination of the spacecraft was chosen in order to keep more measurements. Data selection based on geomagnetic indices was used to minimize the external field contributions. Measurements were screened and outliers were carefully removed. The model uses magnetic field intensity measurements at all latitudes and magnetic field vector measurements equatorward of 50° absolute quasi-dipole magnetic latitude. A second model using only the vertical component of the measured magnetic field and the total intensity was computed. This companion model offers a slightly better fit to the measurements. These two models are compared and discussed.We discuss in particular the quality of the model which does not use the full vector measurements and underline that this approach may be used when only partial directional information is known. The candidate models and their associated companion models are retrospectively compared to the adopted IGRF which allows us to criticize our own choices.

  14. Swarming bacteria migrate by Lévy Walk

    NASA Astrophysics Data System (ADS)

    Ariel, Gil; Rabani, Amit; Benisty, Sivan; Partridge, Jonathan D.; Harshey, Rasika M.; Be'Er, Avraham

    2015-09-01

    Individual swimming bacteria are known to bias their random trajectories in search of food and to optimize survival. The motion of bacteria within a swarm, wherein they migrate as a collective group over a solid surface, is fundamentally different as typical bacterial swarms show large-scale swirling and streaming motions involving millions to billions of cells. Here by tracking trajectories of fluorescently labelled individuals within such dense swarms, we find that the bacteria are performing super-diffusion, consistent with Lévy walks. Lévy walks are characterized by trajectories that have straight stretches for extended lengths whose variance is infinite. The evidence of super-diffusion consistent with Lévy walks in bacteria suggests that this strategy may have evolved considerably earlier than previously thought.

  15. Combining virtual observatory and equivalent source dipole approaches to describe the geomagnetic field with Swarm measurements

    NASA Astrophysics Data System (ADS)

    Saturnino, Diana; Langlais, Benoit; Amit, Hagay; Civet, François; Mandea, Mioara; Beucler, Éric

    2018-03-01

    A detailed description of the main geomagnetic field and of its temporal variations (i.e., the secular variation or SV) is crucial to understanding the geodynamo. Although the SV is known with high accuracy at ground magnetic observatory locations, the globally uneven distribution of the observatories hampers the determination of a detailed global pattern of the SV. Over the past two decades, satellites have provided global surveys of the geomagnetic field which have been used to derive global spherical harmonic (SH) models through some strict data selection schemes to minimise external field contributions. However, discrepancies remain between ground measurements and field predictions by these models; indeed the global models do not reproduce small spatial scales of the field temporal variations. To overcome this problem we propose to directly extract time series of the field and its temporal variation from satellite measurements as it is done at observatory locations. We follow a Virtual Observatory (VO) approach and define a global mesh of VOs at satellite altitude. For each VO and each given time interval we apply an Equivalent Source Dipole (ESD) technique to reduce all measurements to a unique location. Synthetic data are first used to validate the new VO-ESD approach. Then, we apply our scheme to data from the first two years of the Swarm mission. For the first time, a 2.5° resolution global mesh of VO time series is built. The VO-ESD derived time series are locally compared to ground observations as well as to satellite-based model predictions. Our approach is able to describe detailed temporal variations of the field at local scales. The VO-ESD time series are then used to derive global spherical harmonic models. For a simple SH parametrization the model describes well the secular trend of the magnetic field both at satellite altitude and at the surface. As more data will be made available, longer VO-ESD time series can be derived and consequently used to

  16. Automatic Clustering Using Multi-objective Particle Swarm and Simulated Annealing

    PubMed Central

    Abubaker, Ahmad; Baharum, Adam; Alrefaei, Mahmoud

    2015-01-01

    This paper puts forward a new automatic clustering algorithm based on Multi-Objective Particle Swarm Optimization and Simulated Annealing, “MOPSOSA”. The proposed algorithm is capable of automatic clustering which is appropriate for partitioning datasets to a suitable number of clusters. MOPSOSA combines the features of the multi-objective based particle swarm optimization (PSO) and the Multi-Objective Simulated Annealing (MOSA). Three cluster validity indices were optimized simultaneously to establish the suitable number of clusters and the appropriate clustering for a dataset. The first cluster validity index is centred on Euclidean distance, the second on the point symmetry distance, and the last cluster validity index is based on short distance. A number of algorithms have been compared with the MOPSOSA algorithm in resolving clustering problems by determining the actual number of clusters and optimal clustering. Computational experiments were carried out to study fourteen artificial and five real life datasets. PMID:26132309

  17. Driving Processes of Earthquake Swarms: Evidence from High Resolution Seismicity

    NASA Astrophysics Data System (ADS)

    Ellsworth, W. L.; Shelly, D. R.; Hill, D. P.; Hardebeck, J.; Hsieh, P. A.

    2017-12-01

    Earthquake swarms are transient increases in seismicity deviating from a typical mainshock-aftershock pattern. Swarms are most prevalent in volcanic and hydrothermal areas, yet also occur in other environments, such as extensional fault stepovers. Swarms provide a valuable opportunity to investigate source zone physics, including the causes of their swarm-like behavior. To gain insight into this behavior, we have used waveform-based methods to greatly enhance standard seismic catalogs. Depending on the application, we detect and precisely relocate 2-10x as many events as included in the initial catalog. Recently, we have added characterization of focal mechanisms (applied to a 2014 swarm in Long Valley Caldera, California), addressing a common shortcoming in microseismicity analyses (Shelly et al., JGR, 2016). In analysis of multiple swarms (both within and outside volcanic areas), several features stand out, including: (1) dramatic expansion of the active source region with time, (2) tendency for events to occur on the immediate fringe of prior activity, (3) overall upward migration, and (4) complex faulting structure. Some swarms also show an apparent mismatch between seismicity orientations (as defined by patterns in hypocentral locations) and slip orientations (as inferred from focal mechanisms). These features are largely distinct from those observed in mainshock-aftershock sequences. In combination, these swarm behaviors point to an important role for fluid pressure diffusion. Swarms may in fact be generated by a cascade of fluid pressure diffusion and stress transfer: in cases where faults are critically stressed, an increase in fluid pressure will trigger faulting. Faulting will in turn dramatically increase permeability in the faulted area, allowing rapid equilibration of fluid pressure to the fringe of the rupture zone. This process may perpetuate until fluid pressure perturbations drop and/or stresses become further from failure, such that any

  18. Seismic swarm associated with the 2008 eruption of Kasatochi Volcano, Alaska: Earthquake locations and source parameters

    USGS Publications Warehouse

    Ruppert, N.A.; Prejean, S.; Hansen, R.A.

    2011-01-01

    An energetic seismic swarm accompanied an eruption of Kasatochi Volcano in the central Aleutian volcanic arc in August of 2008. In retrospect, the first earthquakes in the swarm were detected about 1 month prior to the eruption onset. Activity in the swarm quickly intensified less than 48 h prior to the first large explosion and subsequently subsided with decline of eruptive activity. The largest earthquake measured as moment magnitude 5.8, and a dozen additional earthquakes were larger than magnitude 4. The swarm exhibited both tectonic and volcanic characteristics. Its shear failure earthquake features were b value = 0.9, most earthquakes with impulsive P and S arrivals and higher-frequency content, and earthquake faulting parameters consistent with regional tectonic stresses. Its volcanic or fluid-influenced seismicity features were volcanic tremor, large CLVD components in moment tensor solutions, and increasing magnitudes with time. Earthquake location tests suggest that the earthquakes occurred in a distributed volume elongated in the NS direction either directly under the volcano or within 5-10 km south of it. Following the MW 5.8 event, earthquakes occurred in a new crustal volume slightly east and north of the previous earthquakes. The central Aleutian Arc is a tectonically active region with seismicity occurring in the crusts of the Pacific and North American plates in addition to interplate events. We postulate that the Kasatochi seismic swarm was a manifestation of the complex interaction of tectonic and magmatic processes in the Earth's crust. Although magmatic intrusion triggered the earthquakes in the swarm, the earthquakes failed in context of the regional stress field. Copyright ?? 2011 by the American Geophysical Union.

  19. Surface-Chemistry-Mediated Control of Individual Magnetic Helical Microswimmers in a Swarm.

    PubMed

    Wang, Xiaopu; Hu, Chengzhi; Schurz, Lukas; De Marco, Carmela; Chen, Xiangzhong; Pané, Salvador; Nelson, Bradley J

    2018-05-31

    Magnetic helical microswimmers, also known as artificial bacterial flagella (ABFs), perform 3D navigation in various liquids under low-strength rotating magnetic fields by converting rotational motion to translational motion. ABFs have been widely studied as carriers for targeted delivery and release of drugs and cells. For in vivo/ in vitro therapeutic applications, control over individual groups of swimmers within a swarm is necessary for several biomedical applications such as drug delivery or small-scale surgery. In this work, we present the selective control of individual swimmers in a swarm of geometrically and magnetically identical ABFs by modifying their surface chemistry. We confirm experimentally and analytically that the forward/rotational velocity ratio of ABFs is independent of their surface coatings when the swimmers are operated below their step-out frequency (the frequency requiring the entire available magnetic torque to maintain synchronous rotation). We also show that ABFs with hydrophobic surfaces exhibit larger step-out frequencies and higher maximum forward velocities compared to their hydrophilic counterparts. Thus, selective control of a group of swimmers within a swarm of ABFs can be achieved by operating the selected ABFs at a frequency that is below their step-out frequencies but higher than the step-out frequencies of unselected ABFs. The feasibility of this method is investigated in water and in biologically relevant solutions. Selective control is also demonstrated inside a Y-shaped microfluidic channel. Our results present a systematic approach for realizing selective control within a swarm of magnetic helical microswimmers.

  20. Swarming behaviors in multi-agent systems with nonlinear dynamics

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Yu, Wenwu, E-mail: wenwuyu@gmail.com; School of Electrical and Computer Engineering, RMIT University, Melbourne VIC 3001; Chen, Guanrong

    2013-12-15

    The dynamic analysis of a continuous-time multi-agent swarm model with nonlinear profiles is investigated in this paper. It is shown that, under mild conditions, all agents in a swarm can reach cohesion within a finite time, where the upper bounds of the cohesion are derived in terms of the parameters of the swarm model. The results are then generalized by considering stochastic noise and switching between nonlinear profiles. Furthermore, swarm models with limited sensing range inducing changing communication topologies and unbounded repulsive interactions between agents are studied by switching system and nonsmooth analysis. Here, the sensing range of each agentmore » is limited and the possibility of collision among nearby agents is high. Finally, simulation results are presented to demonstrate the validity of the theoretical analysis.« less

  1. Alarm systems detect volcanic tremor and earthquake swarms during Redoubt eruption, 2009

    NASA Astrophysics Data System (ADS)

    Thompson, G.; West, M. E.

    2009-12-01

    We ran two alarm algorithms on real-time data from Redoubt volcano during the 2009 crisis. The first algorithm was designed to detect escalations in continuous seismicity (tremor). This is implemented within an application called IceWeb which computes reduced displacement, and produces plots of reduced displacement and spectrograms linked to the Alaska Volcano Observatory internal webpage every 10 minutes. Reduced displacement is a measure of the amplitude of volcanic tremor, and is computed by applying a geometrical spreading correction to a displacement seismogram. When the reduced displacement at multiple stations exceeds pre-defined thresholds and there has been a factor of 3 increase in reduced displacement over the previous hour, a tremor alarm is declared. The second algorithm was to designed to detect earthquake swarms. The mean and median event rates are computed every 5 minutes based on the last hour of data from a real-time event catalog. By comparing these with thresholds, three swarm alarm conditions can be declared: a new swarm, an escalation in a swarm, and the end of a swarm. The end of swarm alarm is important as it may mark a transition from swarm to continuous tremor. Alarms from both systems were dispatched using a generic alarm management system which implements a call-down list, allowing observatory scientists to be called in sequence until someone acknowledged the alarm via a confirmation web page. The results of this simple approach are encouraging. The tremor alarm algorithm detected 26 of the 27 explosive eruptions that occurred from 23 March - 4 April. The swarm alarm algorithm detected all five of the main volcanic earthquake swarm episodes which occurred during the Redoubt crisis on 26-27 February, 21-23 March, 26 March, 2-4 April and 3-7 May. The end-of-swarm alarms on 23 March and 4 April were particularly helpful as they were caused by transitions from swarm to tremor shortly preceding explosive eruptions; transitions which were

  2. Self Organized Multi Agent Swarms (SOMAS) for Network Security Control

    DTIC Science & Technology

    2009-03-01

    Normal hierarchy vs entangled hierarchy 2.5.7 Quantifying Entangledness . While self organization means that the swarm develops a consistent structure of...flexibility due to centralization of control and com- munication. Thus, self organized, entangled hierarchy multi-agent swarms are evolved in this study to...technique. The resulting design exhibits a self organized multi-agent swarm (SOMAS) with entangled hierarchical control and communication through the

  3. Particle Swarm Optimization approach to defect detection in armour ceramics.

    PubMed

    Kesharaju, Manasa; Nagarajah, Romesh

    2017-03-01

    In this research, various extracted features were used in the development of an automated ultrasonic sensor based inspection system that enables defect classification in each ceramic component prior to despatch to the field. Classification is an important task and large number of irrelevant, redundant features commonly introduced to a dataset reduces the classifiers performance. Feature selection aims to reduce the dimensionality of the dataset while improving the performance of a classification system. In the context of a multi-criteria optimization problem (i.e. to minimize classification error rate and reduce number of features) such as one discussed in this research, the literature suggests that evolutionary algorithms offer good results. Besides, it is noted that Particle Swarm Optimization (PSO) has not been explored especially in the field of classification of high frequency ultrasonic signals. Hence, a binary coded Particle Swarm Optimization (BPSO) technique is investigated in the implementation of feature subset selection and to optimize the classification error rate. In the proposed method, the population data is used as input to an Artificial Neural Network (ANN) based classification system to obtain the error rate, as ANN serves as an evaluator of PSO fitness function. Copyright © 2016. Published by Elsevier B.V.

  4. Options for the Further Orbit Evolution of the Swarm Mission

    NASA Astrophysics Data System (ADS)

    Sieg, Detlef; Diekmann, Frank

    2016-08-01

    The three satellites of ESA's magnetic field mission Swarm were launched into a common low Earth circular orbit in November 2013 to measure precisely the magnetic signals from Earth's core, mantle, crust and oceans, as well as the ionosphere and magnetosphere. Since completion of the orbit acquisition phase in April 2014 one satellite (Swarm-B) is flying in a higher orbit with an inclination of 87.8deg and an altitude decaying from 520km. The other two satellites are Swarm-A (trailing) and Swarm-C (leading). They form the lower pair with an initial altitude of 473km, an inclination of 87.4 deg and an ascending node difference of 1.4 deg. The original mission analysis foresaw a decay of the lower pair down to 300km altitude within 4 years after launch. The target altitude of the launcher injection orbit was selected accordingly with some margin due to uncertainties in the solar activity prediction. However the final altitude selection had to be provided more than half a year before launch. Following several launch delays, the major part of the mission falls now beyond the maximum of the current solar cycle. Because of the lower radio flux and geomagnetic activity, the air drag forces are now much lower and the actual decay takes longer.As a first countermeasure the target for the inclination difference between Swarm-B and Swarm-A/C was reduced to 0.4deg shortly before the start of the orbit acquisition manoeuvre sequence early 2014 such that the LTAN drift between the orbit planes of B and A/C has been reduced to 1.5h per year to avoid a too large difference towards the end of the mission.First the paper describes the routine orbit determination approach by ESOC flight dynamics, which is used to determine absolute drag scale factors. Based on the in- flight calibrated values, long-term orbit predictions are calculated every half a year and can be compared against the actual observed decay. This gives good confidence for the prediction of the future altitude

  5. DTU candidate field models for IGRF-12 and the CHAOS-5 geomagnetic field model

    NASA Astrophysics Data System (ADS)

    Finlay, Christopher C.; Olsen, Nils; Tøffner-Clausen, Lars

    2015-07-01

    We present DTU's candidate field models for IGRF-12 and the parent field model from which they were derived, CHAOS-5. Ten months of magnetic field observations from ESA's Swarm mission, together with up-to-date ground observatory monthly means, were used to supplement the data sources previously used to construct CHAOS-4. The internal field part of CHAOS-5, from which our IGRF-12 candidate models were extracted, is time-dependent up to spherical harmonic degree 20 and involves sixth-order splines with a 0.5 year knot spacing. In CHAOS-5, compared with CHAOS-4, we update only the low-degree internal field model (degrees 1 to 24) and the associated external field model. The high-degree internal field (degrees 25 to 90) is taken from the same model CHAOS-4h, based on low-altitude CHAMP data, which was used in CHAOS-4. We find that CHAOS-5 is able to consistently fit magnetic field data from six independent low Earth orbit satellites: Ørsted, CHAMP, SAC-C and the three Swarm satellites (A, B and C). It also adequately describes the secular variation measured at ground observatories. CHAOS-5 thus contributes to an initial validation of the quality of the Swarm magnetic data, in particular demonstrating that Huber weighted rms model residuals to Swarm vector field data are lower than those to Ørsted and CHAMP vector data (when either one or two star cameras were operating). CHAOS-5 shows three pulses of secular acceleration at the core surface over the past decade; the 2006 and 2009 pulses have previously been documented, but the 2013 pulse has only recently been identified. The spatial signature of the 2013 pulse at the core surface, under the Atlantic sector where it is strongest, is well correlated with the 2006 pulse, but anti-correlated with the 2009 pulse.

  6. Optimization of C4.5 algorithm-based particle swarm optimization for breast cancer diagnosis

    NASA Astrophysics Data System (ADS)

    Muslim, M. A.; Rukmana, S. H.; Sugiharti, E.; Prasetiyo, B.; Alimah, S.

    2018-03-01

    Data mining has become a basic methodology for computational applications in the field of medical domains. Data mining can be applied in the health field such as for diagnosis of breast cancer, heart disease, diabetes and others. Breast cancer is most common in women, with more than one million cases and nearly 600,000 deaths occurring worldwide each year. The most effective way to reduce breast cancer deaths was by early diagnosis. This study aims to determine the level of breast cancer diagnosis. This research data uses Wisconsin Breast Cancer dataset (WBC) from UCI machine learning. The method used in this research is the algorithm C4.5 and Particle Swarm Optimization (PSO) as a feature option and to optimize the algorithm. C4.5. Ten-fold cross-validation is used as a validation method and a confusion matrix. The result of this research is C4.5 algorithm. The particle swarm optimization C4.5 algorithm has increased by 0.88%.

  7. Increased Tolerance to Heavy Metals Exhibited by Swarming Bacteria

    NASA Astrophysics Data System (ADS)

    Anyan, M.; Shrout, J. D.

    2014-12-01

    Pseudomonas aeruginosa is a ubiquitous, Gram-negative bacterium that utilizes several different modes of motility to colonize surfaces, including swarming, which is the coordinated movement of cells over surfaces in groups. Swarming facilitates surface colonization and biofilm development for P. aeruginosa, and it is known that swarming behavior is influenced by changes in nutrient composition and surface moisture. To understand the fate and cycling of heavy metals in the environment, it is important to understand the interaction and toxicity of these metals upon bacteria. While previous studies have shown surface-attached bacterial biofilms to be highly resistant to heavy metal toxicity, little is known about the influence of heavy metals upon surface motile bacteria and developing biofilms. Using a combination of laboratory assays we examined differences in bacterial behavior in response to two metals, Cd and Ni. We find that surface swarming bacteria are able to grow on 4x and 2.5x more Cd and Ni, respectively, than planktonic cells (i.e., test tube cultures). P. aeruginosa was able to swarm in the presence ≤0.051mM Ni and ≤0.045mM Cd. To investigate the bioavailability of metals to bacteria growing under our examined conditions, we separated cell and supernatant fractions of P. aeruginosa cultures, and used ICP-MS techniques to measure Cd and Ni sorption. A greater percentage of Cd than Ni was sorbed by both cells and supernatant (which contains rhamnolipid, a surfactant known to sorb some metals and improve swarming). While we show that cell products such as rhamnolipid bind heavy metals (as expected) and should limit metal bioavailability, our results suggest at least one additional mechanism (as yet undetermined) that promotes cell survival during swarming in the presence of these heavy metals.

  8. Sensory coding of nest-site value in honeybee swarms.

    PubMed

    Seeley, Thomas D; Visscher, P Kirk

    2008-12-01

    This study investigates the first stage of the decision-making process of a honeybee swarm as it chooses a nest site: how a scout bee codes the value of a potential nest site in the waggle dances she produces to represent this site. We presented honeybee swarms with a two-alternative choice between a high-value site and a medium-value site and recorded the behavior of individually identifiable scout bees as they reported on these two alternatives. We found that bees performed equally lengthy inspections at the two sites, but that, on the swarm cluster, they performed more dance circuits per bee for the high-value site. We also found that there was much individual-level noise in the coding of site value, but that there were clear population-level differences in total dance circuits produced for the two sites. The first bee to find a site had a high probability of reporting the site with a waggle dance, regardless of its value. This discoverer-should-dance phenomenon may help ensure that a swarm gives attention to all discovered sites. There was rapid decay in the dance response; the number of dance circuits produced by a bee after visiting a site decreased linearly over sequential visits, and eventually each bee ceased visiting her site. This decay, or ;leakage', in the accumulation of bees at a site improves a swarm's decision-making ability by helping a swarm avoid making fast-decision errors.

  9. Effects of physical factors on the swarming motility of text itPseudomonas aeruginosa

    NASA Astrophysics Data System (ADS)

    Si, Tieyan; Ma, Zidong; Tang, Wai Shing; Yang, Alexander; Tang, Jay

    Many species of bacteria can spread over a semi-solid surface via a particular form of collective motion known as surface swarming. Using Pseudomonas aeruginosa as a model organism, we investigate physical factors that either facilitate or restrict the swarming motility. The semi-solid surface is typically formed by 0.5-1% agar containing essential nutrients for the bacterial growth and proliferation. Most bacterial species, including P. aeruginosa, synthesize bio-surfactants to aid in swarming. We found addition of exogenous surfactants such as triton into the agar matrix enhances the swarming. In contrast, increasing agar percentage, infusing osmolites, and adding viscous agents all decrease swarming. We propose that the swarming speed is restricted by the rate of water supply from within the agar gel and by the line tension at the swarm front involving three materials in contact: the air, the bacteria propelled liquid film, and the agar substrate.

  10. A novel artificial fish swarm algorithm for recalibration of fiber optic gyroscope error parameters.

    PubMed

    Gao, Yanbin; Guan, Lianwu; Wang, Tingjun; Sun, Yunlong

    2015-05-05

    The artificial fish swarm algorithm (AFSA) is one of the state-of-the-art swarm intelligent techniques, which is widely utilized for optimization purposes. Fiber optic gyroscope (FOG) error parameters such as scale factors, biases and misalignment errors are relatively unstable, especially with the environmental disturbances and the aging of fiber coils. These uncalibrated error parameters are the main reasons that the precision of FOG-based strapdown inertial navigation system (SINS) degraded. This research is mainly on the application of a novel artificial fish swarm algorithm (NAFSA) on FOG error coefficients recalibration/identification. First, the NAFSA avoided the demerits (e.g., lack of using artificial fishes' pervious experiences, lack of existing balance between exploration and exploitation, and high computational cost) of the standard AFSA during the optimization process. To solve these weak points, functional behaviors and the overall procedures of AFSA have been improved with some parameters eliminated and several supplementary parameters added. Second, a hybrid FOG error coefficients recalibration algorithm has been proposed based on NAFSA and Monte Carlo simulation (MCS) approaches. This combination leads to maximum utilization of the involved approaches for FOG error coefficients recalibration. After that, the NAFSA is verified with simulation and experiments and its priorities are compared with that of the conventional calibration method and optimal AFSA. Results demonstrate high efficiency of the NAFSA on FOG error coefficients recalibration.

  11. Rayleigh wave dispersion curve inversion by using particle swarm optimization and genetic algorithm

    NASA Astrophysics Data System (ADS)

    Buyuk, Ersin; Zor, Ekrem; Karaman, Abdullah

    2017-04-01

    Inversion of surface wave dispersion curves with its highly nonlinear nature has some difficulties using traditional linear inverse methods due to the need and strong dependence to the initial model, possibility of trapping in local minima and evaluation of partial derivatives. There are some modern global optimization methods to overcome of these difficulties in surface wave analysis such as Genetic algorithm (GA) and Particle Swarm Optimization (PSO). GA is based on biologic evolution consisting reproduction, crossover and mutation operations, while PSO algorithm developed after GA is inspired from the social behaviour of birds or fish of swarms. Utility of these methods require plausible convergence rate, acceptable relative error and optimum computation cost that are important for modelling studies. Even though PSO and GA processes are similar in appearence, the cross-over operation in GA is not used in PSO and the mutation operation is a stochastic process for changing the genes within chromosomes in GA. Unlike GA, the particles in PSO algorithm changes their position with logical velocities according to particle's own experience and swarm's experience. In this study, we applied PSO algorithm to estimate S wave velocities and thicknesses of the layered earth model by using Rayleigh wave dispersion curve and also compared these results with GA and we emphasize on the advantage of using PSO algorithm for geophysical modelling studies considering its rapid convergence, low misfit error and computation cost.

  12. Capture of Planetesimals into a Circumterrestrial Swarm

    NASA Technical Reports Server (NTRS)

    Weidenschilling, S. J.

    1985-01-01

    The lunar origin model considered in this report involves processing of protolunar material through a circumterrestrial swarm of particles. Once such a swarm has formed, it can gain mass by capturing infalling planetesimals and ejecta from giant impacts on the Earth, although the angular momentum supply from these sources remains a problem. The first stage of formation of a geocentric swarm by capture of planetesimals from initially heliocentric orbits is examined. The only plausible capture mechanism that is not dependent on very low approach velocities is the mutual collision of planetesimals passing within Earth's sphere of influence. The dissipation of energy in inelastic collisions or accretion events changes the value of the Jacobi parameter, allowing capture into bound geocentric orbits. This capture scenario was tested directly by many body numerical integration of planetesimal orbits in near Earth space.

  13. LinkMind: link optimization in swarming mobile sensor networks.

    PubMed

    Ngo, Trung Dung

    2011-01-01

    A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation.

  14. LinkMind: Link Optimization in Swarming Mobile Sensor Networks

    PubMed Central

    Ngo, Trung Dung

    2011-01-01

    A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation. PMID:22164070

  15. Earthquake swarms on the Mid-Atlantic Ridge - Products of magmatism or extensional tectonics?

    NASA Technical Reports Server (NTRS)

    Bergman, Eric A.; Solomon, Sean C.

    1990-01-01

    The spatial and temporal patterns and other characteristics of earthquakes in 34 earthquake swarms on the Mid-Atlantic Ridge were compared with those of well-studied earthquake swarms which accompany terrestrial volcanic eruptions, to test the assumption that the teleseismically observed earthquake swarms along mid-ocean ridges are indicators of volcanism. Improved resolution of these patterns for the mid-ocean ridge events was achieved by a multiple-event relocation technique. It was found that the teleseismically located earthquake swarms on the mid-ocean ridge system have few features in common with swarms directly associated with active magmatism in terrestrial volcanic rift zones such as Hawaii and Iceland. While the possibility that some of the mid-ocean earthquake swarms might be directly associated with a current episode of eruptive activity on the Mid-Atlantic Ridge cannot be excluded, none of the 34 swarms studied in this work was found to be a conspicuously attractive candidate for such a role.

  16. Langevin dynamics encapsulate the microscopic and emergent macroscopic properties of midge swarms

    PubMed Central

    2018-01-01

    In contrast to bird flocks, fish schools and animal herds, midge swarms maintain cohesion but do not possess global order. High-speed imaging techniques are now revealing that these swarms have surprising properties. Here, I show that simple models found on the Langevin equation are consistent with this wealth of recent observations. The models predict correctly that large accelerations, exceeding 10 g, will be common and they predict correctly the coexistence of core condensed phases surrounded by dilute vapour phases. The models also provide new insights into the influence of environmental conditions on swarm dynamics. They predict that correlations between midges increase the strength of the effective force binding the swarm together. This may explain why such correlations are absent in laboratory swarms but present in natural swarms which contend with the wind and other disturbances. Finally, the models predict that swarms have fluid-like macroscopic mechanical properties and will slosh rather than slide back and forth after being abruptly displaced. This prediction offers a promising avenue for future experimentation that goes beyond current quasi-static testing which has revealed solid-like responses. PMID:29298958

  17. Decision-making in honeybee swarms based on quality and distance information of candidate nest sites.

    PubMed

    Laomettachit, Teeraphan; Termsaithong, Teerasit; Sae-Tang, Anuwat; Duangphakdee, Orawan

    2015-01-07

    In the nest-site selection process of honeybee swarms, an individual bee performs a waggle dance to communicate information about direction, quality, and distance of a discovered site to other bees at the swarm. Initially, different groups of bees dance to represent different potential sites, but eventually the swarm usually reaches an agreement for only one site. Here, we model the nest-site selection process in honeybee swarms of Apis mellifera and show how the swarms make adaptive decisions based on a trade-off between the quality and distance to candidate nest sites. We use bifurcation analysis and stochastic simulations to reveal that the swarm's site distance preference is moderate>near>far when the swarms choose between low quality sites. However, the distance preference becomes near>moderate>far when the swarms choose between high quality sites. Our simulations also indicate that swarms with large population size prefer nearer sites and, in addition, are more adaptive at making decisions based on available information compared to swarms with smaller population size. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Optimization of wireless sensor networks based on chicken swarm optimization algorithm

    NASA Astrophysics Data System (ADS)

    Wang, Qingxi; Zhu, Lihua

    2017-05-01

    In order to reduce the energy consumption of wireless sensor network and improve the survival time of network, the clustering routing protocol of wireless sensor networks based on chicken swarm optimization algorithm was proposed. On the basis of LEACH agreement, it was improved and perfected that the points on the cluster and the selection of cluster head using the chicken group optimization algorithm, and update the location of chicken which fall into the local optimum by Levy flight, enhance population diversity, ensure the global search capability of the algorithm. The new protocol avoided the die of partial node of intensive using by making balanced use of the network nodes, improved the survival time of wireless sensor network. The simulation experiments proved that the protocol is better than LEACH protocol on energy consumption, also is better than that of clustering routing protocol based on particle swarm optimization algorithm.

  19. Water reservoir maintained by cell growth fuels the spreading of a bacterial swarm.

    PubMed

    Wu, Yilin; Berg, Howard C

    2012-03-13

    Flagellated bacteria can swim across moist surfaces within a thin layer of fluid, a means for surface colonization known as swarming. This fluid spreads with the swarm, but how it does so is unclear. We used micron-sized air bubbles to study the motion of this fluid within swarms of Escherichia coli. The bubbles moved diffusively, with drift. Bubbles starting at the swarm edge drifted inward for the first 5 s and then moved outward. Bubbles starting 30 μm from the swarm edge moved inward for the first 20 s, wandered around in place for the next 40 s, and then moved outward. Bubbles starting at 200 or 300 μm from the edge moved outward or wandered around in place, respectively. So the general trend was inward near the outer edge of the swarm and outward farther inside, with flows converging on a region about 100 μm from the swarm edge. We measured cellular metabolic activities with cells expressing a short-lived GFP and cell densities with cells labeled with a membrane fluorescent dye. The fluorescence plots were similar, with peaks about 80 μm from the swarm edge and slopes that mimicked the particle drift rates. These plots suggest that net fluid flow is driven by cell growth. Fluid depth is largest in the multilayered region between approximately 30 and 200 μm from the swarm edge, where fluid agitation is more vigorous. This water reservoir travels with the swarm, fueling its spreading. Intercellular communication is not required; cells need only grow.

  20. Incremental social learning in particle swarms.

    PubMed

    de Oca, Marco A Montes; Stutzle, Thomas; Van den Enden, Ken; Dorigo, Marco

    2011-04-01

    Incremental social learning (ISL) was proposed as a way to improve the scalability of systems composed of multiple learning agents. In this paper, we show that ISL can be very useful to improve the performance of population-based optimization algorithms. Our study focuses on two particle swarm optimization (PSO) algorithms: a) the incremental particle swarm optimizer (IPSO), which is a PSO algorithm with a growing population size in which the initial position of new particles is biased toward the best-so-far solution, and b) the incremental particle swarm optimizer with local search (IPSOLS), in which solutions are further improved through a local search procedure. We first derive analytically the probability density function induced by the proposed initialization rule applied to new particles. Then, we compare the performance of IPSO and IPSOLS on a set of benchmark functions with that of other PSO algorithms (with and without local search) and a random restart local search algorithm. Finally, we measure the benefits of using incremental social learning on PSO algorithms by running IPSO and IPSOLS on problems with different fitness distance correlations.

  1. Rapid movement and instability of an invasive hybrid swarm

    USGS Publications Warehouse

    Glotzbecker, Gregory J.; Walters, David; Blum, Michael J.

    2016-01-01

    Unstable hybrid swarms that arise following the introduction of non-native species can overwhelm native congeners, yet the stability of invasive hybrid swarms has not been well documented over time. Here we examine genetic variation and clinal stability across a recently formed hybrid swarm involving native blacktail shiner (Cyprinella venusta) and non-native red shiner (C. lutrensis) in the Upper Coosa River basin, which is widely considered to be a global hotspot of aquatic biodiversity. Examination of phenotypic, multilocus genotypic, and mitochondrial haplotype variability between 2005 and 2011 revealed that the proportion of hybrids has increased over time, with more than a third of all sampled individuals exhibiting admixture in the final year of sampling. Comparisons of clines over time indicated that the hybrid swarm has been rapidly progressing upstream, but at a declining and slower pace than rates estimated from historical collection records. Clinal comparisons also showed that the hybrid swarm has been expanding and contracting over time. Additionally, we documented the presence of red shiner and hybrids farther downstream than prior studies have detected, which suggests that congeners in the Coosa River basin, including all remaining populations of the threatened blue shiner (Cyprinella caerulea), are at greater risk than previously thought.

  2. On the capability of Swarm for surface mass variation monitoring: Quantitative assessment based on orbit information from CHAMP, GRACE and GOCE

    NASA Astrophysics Data System (ADS)

    Baur, Oliver; Weigelt, Matthias; Zehentner, Norbert; Mayer-Gürr, Torsten; Jäggi, Adrian

    2014-05-01

    In the last decade, temporal variations of the gravity field from GRACE observations have become one of the most ubiquitous and valuable sources of information for geophysical and environmental studies. In the context of global climate change, mass balance of the Arctic and Antarctic ice sheets gained particular attention. Because GRACE has outlived its predicted lifetime by several years already, it is very likely that a gap between GRACE and its successor GRACE follow-on (supposed to be launched in 2017, at the earliest) occurs. The Swarm mission - launched on November 22, 2013 - is the most promising candidate to bridge this potential gap, i.e., to directly acquire large-scale mass variation information on the Earth's surface in case of a gap between the present GRACE and the upcoming GRACE follow-on projects. Although the magnetometry mission Swarm has not been designed for gravity field purposes, its three satellites have the characteristics for such an endeavor: (i) low, near-circular and near-polar orbits, (ii) precise positioning with high-quality GNSS receivers, (iii) on-board accelerometers to measure the influence of non-gravitational forces. Hence, from an orbit analysis point of view the Swarm satellites are comparable to the CHAMP, GRACE and GOCE spacecraft. Indeed and as data analysis from CHAMP has been shown, the detection of annual signals and trends from orbit analysis is possible for long-wavelength features of the gravity field, although the accuracy associated with the inter-satellite GRACE measurements cannot be reached. We assess the capability of the (non-dedicated) mission Swarm for mass variation detection in a real-case environment (opposed to simulation studies). For this purpose, we "approximate" the Swarm scenario by the GRACE+CHAMP and GRACE+GOCE constellations. In a first step, kinematic orbits of the individual satellites are derived from GNSS observations. From these orbits, we compute monthly combined GRACE+CHAMP and GRACE

  3. Theory of periodic swarming of bacteria: Application to Proteus mirabilis

    NASA Astrophysics Data System (ADS)

    Czirók, A.; Matsushita, M.; Vicsek, T.

    2001-03-01

    The periodic swarming of bacteria is one of the simplest examples for pattern formation produced by the self-organized collective behavior of a large number of organisms. In the spectacular colonies of Proteus mirabilis (the most common species exhibiting this type of growth), a series of concentric rings are developed as the bacteria multiply and swarm following a scenario that periodically repeats itself. We have developed a theoretical description for this process in order to obtain a deeper insight into some of the typical processes governing the phenomena in systems of many interacting living units. Our approach is based on simple assumptions directly related to the latest experimental observations on colony formation under various conditions. The corresponding one-dimensional model consists of two coupled differential equations investigated here both by numerical integrations and by analyzing the various expressions obtained from these equations using a few natural assumptions about the parameters of the model. We determine the phase diagram corresponding to systems exhibiting periodic swarming, and discuss in detail how the various stages of the colony development can be interpreted in our framework. We point out that all of our theoretical results are in excellent agreement with the complete set of available observations. Thus the present study represents one of the few examples where self-organized biological pattern formation is understood within a relatively simple theoretical approach, leading to results and predictions fully compatible with experiments.

  4. Role of tumbling in bacterial swarming

    NASA Astrophysics Data System (ADS)

    Sidortsov, Marina; Morgenstern, Yakov; Be'er, Avraham

    2017-08-01

    Typical wild-type bacteria swimming in sparse suspensions exhibit a movement pattern called "run and tumble," characterized by straight trajectories (runs) interspersed by shorter, random reorientation (tumbles). This is achieved by rotating their flagella counterclockwise, or clockwise, respectively. The chemotaxis signaling network operates in controlling the frequency of tumbles, enabling navigation toward or away from desired regions in the medium. In contrast, while in dense populations, flagellated bacteria exhibit collective motion and form large dynamic clusters, whirls, and jets, with intricate dynamics that is fundamentally different than trajectories of sparsely swimming cells. Although collectively swarming cells do change direction at the level of the individual cell, often exhibiting reversals, it has been suggested that chemotaxis does not play a role in multicellular colony expansion, but the change in direction stems from clockwise flagellar rotation. In this paper, the effects of cell rotor switching (i.e., the ability to tumble) and chemotaxis on the collective statistics of swarming bacteria are studied experimentally in wild-type Bacillus subtilis and two mutants—one that does not tumble and one that tumbles independently of the chemotaxis system. We show that while several of the parameters examined are similar between the strains, other collective and individual characteristics are significantly different. The results demonstrate that tumbling and/or flagellar directional rotor switching has an important role on the dynamics of swarming, and imply that swarming models of self-propelled rods that do not take tumbling and/or rotor switching into account may be oversimplified.

  5. Utilizing field-aligned current profiles derived from Swarm to estimate the peak emission height of 630 nm auroral arcs: a comparison of methods and discussion of associated error estimates in the ASI data.

    NASA Astrophysics Data System (ADS)

    Gillies, D. M.; Knudsen, D. J.; Donovan, E.; Jackel, B. J.; Gillies, R.; Spanswick, E.

    2017-12-01

    We compare field-aligned currents (FACs) measured by the Swarm constellation of satellites with the location of red-line (630 nm) auroral arcs observed by all-sky imagers (ASIs) to derive a characteristic emission height for the optical emissions. In our 10 events we find that an altitude of 200 km applied to the ASI maps gives optimal agreement between the two observations. We also compare the new FAC method against the traditional triangulation method using pairs of all-sky imagers (ASIs), and against electron density profiles obtained from the Resolute Bay Incoherent Scatter Radar-Canadian radar (RISR-C), both of which are consistent with a characteristic emission height of 200 km. We also present the spatial error associated with georeferencing REdline Geospace Observatory (REGO) and THEMIS all-sky imagers (ASIs) and how it applies to altitude projections of the mapped image. Utilizing this error we validate the estimated altitude of redline aurora using two methods: triangulation between ASIs and field-aligned current profiles derived from magnetometers on-board the Swarm satellites.

  6. An Earthquake Swarm Search Implemented at Major Convergent Margins to Test for Associated Aseismic Slip

    NASA Astrophysics Data System (ADS)

    Holtkamp, S. G.; Pritchard, M. E.; Lohman, R. B.; Brudzinski, M. R.

    2009-12-01

    Recent geodetic analysis indicates earthquake swarms may be associated with slow slip such that earthquakes may only represent a fraction of the moment release. To investigate this potential relationship, we have developed a manual search approach to identify earthquake swarms from a seismicity catalog. Our technique is designed to be insensitive to spatial and temporal scales and the total number of events, as seismicity rates vary in different fault zones. Our first application of this technique on globally recorded earthquakes in South America detects 35 possible swarms of varying spatial scale, with 18 in the megathrust region and 8 along the volcanic arc. Three swarms in the vicinity of the arc appear to be triggered by the Mw=8.5 2001 Peru earthquake, and are examined for possible triggering mechanisms. Coulomb stress modeling suggests that static stress changes due to the earthquake are insufficient to trigger activity, so a dynamic or secondary triggering mechanism is more likely. Volcanic swarms are often associated with ground deformation, either associated with fluid movement (e.g. dike intrusion or chamber inflation or deflation) or fault movement, although these processes are sometimes difficult to differentiate. The only swarm along the arc with sufficient geodetic data that we can process and model is near Ticsani Volcano in Peru. In this case, a swarm of events southeast of the volcano precedes a more typical earthquake sequence beneath the volcano, and evidence for deformation is found in the location of the swarm, but there is no evidence for aseismic slip. Rather, we favor a model where the swarm is associated with deflation of a magma body to the southeast that triggered the earthquake sequence by promoting movement on a fault beneath Ticsani. Since swarms on the subduction interface may indicate aseismic moment release, with a direct impact on hazard, we examine potential relations between swarms and megathrust ruptures. We find evidence that

  7. Software Engineering and Swarm-Based Systems

    NASA Technical Reports Server (NTRS)

    Hinchey, Michael G.; Sterritt, Roy; Pena, Joaquin; Rouff, Christopher A.

    2006-01-01

    We discuss two software engineering aspects in the development of complex swarm-based systems. NASA researchers have been investigating various possible concept missions that would greatly advance future space exploration capabilities. The concept mission that we have focused on exploits the principles of autonomic computing as well as being based on the use of intelligent swarms, whereby a (potentially large) number of similar spacecraft collaborate to achieve mission goals. The intent is that such systems not only can be sent to explore remote and harsh environments but also are endowed with greater degrees of protection and longevity to achieve mission goals.

  8. Ground and CHAMP observations of field-aligned current circuits generated by lower atmospheric disturbances and expectations to the SWARM to clarify their three dimensional structure

    NASA Astrophysics Data System (ADS)

    Iyemori, Toshihiko; Nakanishi, Kunihito; Aoyama, Tadashi; Lühr, Hermann

    2014-05-01

    Acoustic gravity waves propagated to the ionosphere cause dynamo currents in the ionosphere. They divert along geomagnetic field lines of force to another hemisphere accompanying electric field and then flow in the ionosphere of another hemisphere by the electric field forming closed current circuits. The oscillating current circuits with the period of acoustic waves generate magnetic variations on the ground, and they are observed as long period geomagnetic pulsations. This effect has been detected during big earthquakes, strong typhoons, tornados etc. On a low-altitude satellite orbit, the spatial distribution (i.e., structure) of the current circuits along the satellite orbit should be detected as temporal magnetic oscillations, and the effect is confirmed by a CHAMP data analysis. On the spatial structure, in particular, in the longitudinal direction, it has been difficult to examine by a single satellite or from ground magnetic observations. The SWARM satellites will provide an unique opportunity to clarify the three dimensional structure of the field-aligned current circuits.

  9. Water reservoir maintained by cell growth fuels the spreading of a bacterial swarm

    PubMed Central

    Wu, Yilin; Berg, Howard C.

    2012-01-01

    Flagellated bacteria can swim across moist surfaces within a thin layer of fluid, a means for surface colonization known as swarming. This fluid spreads with the swarm, but how it does so is unclear. We used micron-sized air bubbles to study the motion of this fluid within swarms of Escherichia coli. The bubbles moved diffusively, with drift. Bubbles starting at the swarm edge drifted inward for the first 5 s and then moved outward. Bubbles starting 30 μm from the swarm edge moved inward for the first 20 s, wandered around in place for the next 40 s, and then moved outward. Bubbles starting at 200 or 300 μm from the edge moved outward or wandered around in place, respectively. So the general trend was inward near the outer edge of the swarm and outward farther inside, with flows converging on a region about 100 μm from the swarm edge. We measured cellular metabolic activities with cells expressing a short-lived GFP and cell densities with cells labeled with a membrane fluorescent dye. The fluorescence plots were similar, with peaks about 80 μm from the swarm edge and slopes that mimicked the particle drift rates. These plots suggest that net fluid flow is driven by cell growth. Fluid depth is largest in the multilayered region between approximately 30 and 200 μm from the swarm edge, where fluid agitation is more vigorous. This water reservoir travels with the swarm, fueling its spreading. Intercellular communication is not required; cells need only grow. PMID:22371567

  10. Myxococcus xanthus Swarms Are Driven by Growth and Regulated by a Pacemaker ▿

    PubMed Central

    Kaiser, Dale; Warrick, Hans

    2011-01-01

    The principal social activity of Myxococcus xanthus is to organize a dynamic multicellular structure, known as a swarm. Although its cell density is high, the swarm can grow and expand rapidly. Within the swarm, the individual rod-shaped cells are constantly moving, transiently interacting with one another, and independently reversing their gliding direction. Periodic reversal is, in fact, essential for creating a swarm, and the reversal frequency controls the rate of swarm expansion. Chemotaxis toward nutrient has been thought to drive swarming, but here the nature of swarm growth and the impact of genetic deletions of members of the Frz family of proteins suggest otherwise. We find that three cytoplasmic Frz proteins, FrzCD, FrzF, and FrzE, constitute a cyclic pathway that sets the reversal frequency. Within each cell these three proteins appear to be connected in a negative-feedback loop that produces oscillations whose frequencies are finely tuned by methylation and by phosphorylation. This oscillator, in turn, drives MglAB, a small G-protein switch, to oscillate between its GTP- and GDP-bound states that ultimately determine when the cell moves forward or backward. The periodic reversal of interacting rod-shaped cells promotes their alignment. Swarm organization ensures that each cell can move without blocking the movement of others. PMID:21856842

  11. The Effect of Larval Diet on Adult Survival, Swarming Activity and Copulation Success in Male Aedes aegypti (Diptera: Culicidae)

    PubMed Central

    Lang, Bethan J; Idugboe, Stefano; McManus, Kirelle; Drury, Florence; Qureshi, Alima

    2018-01-01

    Abstract Control of Aedes aegypti (L.) (Diptera: Culicidae) populations is vital for reducing the transmission of several pervasive human diseases. The success of new vector control technologies will be influenced by the fitness of laboratory-reared transgenic males. However, there has been relatively little published data on how rearing practices influence male fitness in Aedes mosquitoes. In the laboratory, the effect of larval food availability on adult male fitness was tested, using a range of different fitness measures. Larval food availability was demonstrated to be positively correlated with adult body size. Larger males survived longer and exhibited greater swarming activity. As a consequence, larger males may have more mating opportunities in the wild. However, we also found that within a swarm larger males did not have an increased likelihood of copulating with a female. The outcome of the mating competition experiments depended on the methodology used to mark the males. These results show that fitness assessment can vary depending on the measure analyzed, and the methodology used to determine it. Continued investigation into these fitness measures and methodologies, and critically, their utility for predicting male performance in the field, will increase the efficiency of vector control programs. PMID:29029298

  12. Supervised self-organization of homogeneous swarms using ergodic projections of Markov chains.

    PubMed

    Chattopadhyay, Ishanu; Ray, Asok

    2009-12-01

    This paper formulates a self-organization algorithm to address the problem of global behavior supervision in engineered swarms of arbitrarily large population sizes. The swarms considered in this paper are assumed to be homogeneous collections of independent identical finite-state agents, each of which is modeled by an irreducible finite Markov chain. The proposed algorithm computes the necessary perturbations in the local agents' behavior, which guarantees convergence to the desired observed state of the swarm. The ergodicity property of the swarm, which is induced as a result of the irreducibility of the agent models, implies that while the local behavior of the agents converges to the desired behavior only in the time average, the overall swarm behavior converges to the specification and stays there at all times. A simulation example illustrates the underlying concept.

  13. Phase Coexistence in Insect Swarms

    NASA Astrophysics Data System (ADS)

    Sinhuber, Michael; Ouellette, Nicholas T.

    2017-10-01

    Animal aggregations are visually striking, and as such are popular examples of collective behavior in the natural world. Quantitatively demonstrating the collective nature of such groups, however, remains surprisingly difficult. Inspired by thermodynamics, we applied topological data analysis to laboratory insect swarms and found evidence for emergent, material-like states. We show that the swarms consist of a core "condensed" phase surrounded by a dilute "vapor" phase. These two phases coexist in equilibrium, and maintain their distinct macroscopic properties even though individual insects pass freely between them. We further define a pressure and chemical potential to describe these phases, extending theories of active matter to aggregations of macroscopic animals and laying the groundwork for a thermodynamic description of collective animal groups.

  14. Improved discrete swarm intelligence algorithms for endmember extraction from hyperspectral remote sensing images

    NASA Astrophysics Data System (ADS)

    Su, Yuanchao; Sun, Xu; Gao, Lianru; Li, Jun; Zhang, Bing

    2016-10-01

    Endmember extraction is a key step in hyperspectral unmixing. A new endmember extraction framework is proposed for hyperspectral endmember extraction. The proposed approach is based on the swarm intelligence (SI) algorithm, where discretization is used to solve the SI algorithm because pixels in a hyperspectral image are naturally defined within a discrete space. Moreover, a "distance" factor is introduced into the objective function to limit the endmember numbers which is generally limited in real scenarios, while traditional SI algorithms likely produce superabundant spectral signatures, which generally belong to the same classes. Three endmember extraction methods are proposed based on the artificial bee colony, ant colony optimization, and particle swarm optimization algorithms. Experiments with both simulated and real hyperspectral images indicate that the proposed framework can improve the accuracy of endmember extraction.

  15. ANTS: Exploring the Solar System with an Autonomous Nanotechnology Swarm

    NASA Technical Reports Server (NTRS)

    Clark, P. E.; Curtis, S.; Rilee, M.; Truszkowski, W.; Marr, G.

    2002-01-01

    ANTS (Autonomous Nano-Technology Swarm), a NASA advanced mission concept, calls for a large (1000 member) swarm of pico-class (1 kg) totally autonomous spacecraft to prospect the asteroid belt. Additional information is contained in the original extended abstract.

  16. Emergence of Swarming Behavior: Foraging Agents Evolve Collective Motion Based on Signaling.

    PubMed

    Witkowski, Olaf; Ikegami, Takashi

    2016-01-01

    Swarming behavior is common in biology, from cell colonies to insect swarms and bird flocks. However, the conditions leading to the emergence of such behavior are still subject to research. Since Reynolds' boids, many artificial models have reproduced swarming behavior, focusing on details ranging from obstacle avoidance to the introduction of fixed leaders. This paper presents a model of evolved artificial agents, able to develop swarming using only their ability to listen to each other's signals. The model simulates a population of agents looking for a vital resource they cannot directly detect, in a 3D environment. Instead of a centralized algorithm, each agent is controlled by an artificial neural network, whose weights are encoded in a genotype and adapted by an original asynchronous genetic algorithm. The results demonstrate that agents progressively evolve the ability to use the information exchanged between each other via signaling to establish temporary leader-follower relations. These relations allow agents to form swarming patterns, emerging as a transient behavior that improves the agents' ability to forage for the resource. Once they have acquired the ability to swarm, the individuals are able to outperform the non-swarmers at finding the resource. The population hence reaches a neutral evolutionary space which leads to a genetic drift of the genotypes. This reductionist approach to signal-based swarming not only contributes to shed light on the minimal conditions for the evolution of a swarming behavior, but also more generally it exemplifies the effect communication can have on optimal search patterns in collective groups of individuals.

  17. The Aysen (Southern Chile) 2007 Seismic Swarm: Volcanic or Tectonic Origin?

    NASA Astrophysics Data System (ADS)

    Comte, D.; Gallego, A.; Russo, R.; Mocanu, V.; Murdie, R.; Vandecar, J.

    2007-05-01

    The Aysen seismic swarm began January 23, 2007, with a magnitude 5.2 (USGS) earthquake and, after an apparent decrease in activity, continued with a magnitude 5.6 event on February 26. The swarm is characterized by numerous felt earthquakes of small to moderate magnitude, located at crustal depths beneath the Aysen Canal, a prominent fiord of the Chilean littoral. The region is characterized by the subduction of an active oceanic spreading ridge: the Chile Ridge, the divergent Nazca-Antarctic plate boundary, is currently subducting beneath continental South America along the Chile Trench at approximately 46.5°S, forming a plate triple junction in the vicinity of the Taitao Peninsula, somewhat south and west of the swarm. Also, the Liquine-Ofqui dextral strike- slip fault traverses the Aysen Canal in the vicinity of the swarm. This fault has been interpreted as a 1000 km long dextral intra-arc strike-slip fault zone, consisting of two major strands which extend north from the Chile Margin triple junction. The Liquiñe-Ofqui system is marked by several pull-apart basins along its trace through the area. Seismic activity along the Liquiñe-Ofqui fault zone has been poorly studied to date, largely because teleseismic events clearly related to the fault have been few, and southern hemisphere seismic stations are lacking. However, we deployed a dense temporary broad-band seismic network both onland and on the islands in the Aysen region, which allowed us to capture the initial phases of the swarm on some 20 stations, and to determine the background seismicity patterns in this area for the two years preceding the swarm. The swarm could be caused by several processes: the spatial and depth distribution of the events suggests that they are well correlated with reactivation of the southern end of the Liquiñe-Ofqui fault, as defined by geologic studies and onshore gravity data collected in southern Chile. The swarm may be related to formation of new volcanic center between

  18. The infrared spectral transmittance of Aspergillus niger spore aggregated particle swarm

    NASA Astrophysics Data System (ADS)

    Zhao, Xinying; Hu, Yihua; Gu, Youlin; Li, Le

    2015-10-01

    Microorganism aggregated particle swarm, which is quite an important composition of complex media environment, can be developed as a new kind of infrared functional materials. Current researches mainly focus on the optical properties of single microorganism particle. As for the swarm, especially the microorganism aggregated particle swarm, a more accurate simulation model should be proposed to calculate its extinction effect. At the same time, certain parameters deserve to be discussed, which helps to better develop the microorganism aggregated particle swarm as a new kind of infrared functional materials. In this paper, take Aspergillus Niger spore as an example. On the one hand, a new calculation model is established. Firstly, the cluster-cluster aggregation (CCA) model is used to simulate the structure of Aspergillus Niger spore aggregated particle. Secondly, the single scattering extinction parameters for Aspergillus Niger spore aggregated particle are calculated by using the discrete dipole approximation (DDA) method. Thirdly, the transmittance of Aspergillus Niger spore aggregated particle swarm is simulated by using Monte Carlo method. On the other hand, based on the model proposed above, what influences can wavelength causes has been studied, including the spectral distribution of scattering intensity of Aspergillus Niger spore aggregated particle and the infrared spectral transmittance of the aggregated particle swarm within the range of 8-14μm incident infrared wavelengths. Numerical results indicate that the scattering intensity of Aspergillus Niger spore aggregated particle reduces with the increase of incident wavelengths at each scattering angle. Scattering energy mainly concentrates on the scattering angle between 0-40°, forward scattering has an obvious effect. In addition, the infrared transmittance of Aspergillus Niger spore aggregated particle swarm goes up with the increase of incident wavelengths. However, some turning points of the trend are

  19. Identifying intervals of temporally invariant field-aligned currents from Swarm: Assessing the validity of single-spacecraft methods

    NASA Astrophysics Data System (ADS)

    Forsyth, C.; Rae, I. J.; Mann, I. R.; Pakhotin, I. P.

    2017-03-01

    Field-aligned currents (FACs) are a fundamental component of coupled solar wind-magnetosphere-ionosphere. By assuming that FACs can be approximated by stationary infinite current sheets that do not change on the spacecraft crossing time, single-spacecraft magnetic field measurements can be used to estimate the currents flowing in space. By combining data from multiple spacecraft on similar orbits, these stationarity assumptions can be tested. In this technical report, we present a new technique that combines cross correlation and linear fitting of multiple spacecraft measurements to determine the reliability of the FAC estimates. We show that this technique can identify those intervals in which the currents estimated from single-spacecraft techniques are both well correlated and have similar amplitudes, thus meeting the spatial and temporal stationarity requirements. Using data from European Space Agency's Swarm mission from 2014 to 2015, we show that larger-scale currents (>450 km) are well correlated and have a one-to-one fit up to 50% of the time, whereas small-scale (<50 km) currents show similar amplitudes only 1% of the time despite there being a good correlation 18% of the time. It is thus imperative to examine both the correlation and amplitude of the calculated FACs in order to assess both the validity of the underlying assumptions and hence ultimately the reliability of such single-spacecraft FAC estimates.

  20. Inhibition of Swarming motility of Pseudomonas aeruginosa by Methanol extracts of Alpinia officinarum Hance. and Cinnamomum tamala T. Nees and Eberm.

    PubMed

    Lakshmanan, Divya; Nanda, Jishudas; Jeevaratnam, K

    2018-06-01

    Bacterial drug resistance is a challenge in clinical settings, especially in countries like India. Hence, discovery of novel alternative therapeutics has become a necessity in the fight against drug resistance. Compounds that inhibit bacterial virulence properties form new therapeutic alternatives. Pseudomonas aeruginosa is an opportunistic, nosocomial pathogen that infects immune-compromised patients. Swarming motility is an important virulence property of Pseudomonas which aids it in reaching host cells under nutrient limiting conditions. Here, we report the screening of five plant extracts against swarming motility of P. aeruginosa and show that methanol extracts of Alpinia officinarum and Cinnamomum tamala inhibit swarming motility at 5 μg mL -1 without inhibiting its growth. These extracts did not inhibit swimming and twitching motilities indicating a mode of action specific to swarming pathway. Preliminary experiments indicated that rhamnolipid production was not affected. This study reveals the potential of the two plants in anti-virulence drug discovery.

  1. Self-focusing therapeutic gene delivery with intelligent gene vector swarms: intra-swarm signalling through receptor transgene expression in targeted cells.

    PubMed

    Tolmachov, Oleg E

    2015-01-01

    Gene delivery in vivo that is tightly focused on the intended target cells is essential to maximize the benefits of gene therapy and to reduce unwanted side-effects. Cell surface markers are immediately available for probing by therapeutic gene vectors and are often used to direct gene transfer with these vectors to specific target cell populations. However, it is not unusual for the choice of available extra-cellular markers to be too scarce to provide a reliable definition of the desired therapeutically relevant set of target cells. Therefore, interrogation of intra-cellular determinants of cell-specificity, such as tissue-specific transcription factors, can be vital in order to provide detailed cell-guiding information to gene vector particles. An important improvement in cell-specific gene delivery can be achieved through auto-buildup in vector homing efficiency using intelligent 'self-focusing' of swarms of vector particles on target cells. Vector self-focusing was previously suggested to rely on the release of diffusible chemo-attractants after a successful target-specific hit by 'scout' vector particles. I hypothesize that intelligent self-focusing behaviour of swarms of cell-targeted therapeutic gene vectors can be accomplished without the employment of difficult-to-use diffusible chemo-attractants, instead relying on the intra-swarm signalling through cells expressing a non-diffusible extra-cellular receptor for the gene vectors. In the proposed model, cell-guiding information is gathered by the 'scout' gene vector particles, which: (1) attach to a variety of cells via a weakly binding (low affinity) receptor; (2) successfully facilitate gene transfer into these cells; (3) query intra-cellular determinants of cell-specificity with their transgene expression control elements and (4) direct the cell-specific biosynthesis of a vector-encoded strongly binding (high affinity) cell-surface receptor. Free members of the vector swarm loaded with therapeutic cargo

  2. Moving without a purpose: an experimental study of swarm guidance in the Western honey bee, Apis mellifera.

    PubMed

    Makinson, James C; Beekman, Madeleine

    2014-06-01

    During reproductive swarming, honey bee scouts perform two very important functions. Firstly, they find new nesting locations and return to the swarm cluster to communicate their discoveries. Secondly, once the swarm is ready to depart, informed scout bees act as guides, leading the swarm to its final destination. We have previously hypothesised that the two processes, selecting a new nest site and swarm guidance, are tightly linked in honey bees. When swarms can be laissez faire about where they nest, reaching directional consensus prior to lift off seems unnecessary. If, in contrast, it is essential that the swarm reaches a precise location, either directional consensus must be near unanimous prior to swarm departure or only a select subgroup of the scouts guide the swarm. Here, we tested experimentally whether directional consensus is necessary for the successful guidance of swarms of the Western honey bee Apis mellifera by forcing swarms into the air prior to the completion of the decision-making process. Our results show that swarms were unable to guide themselves prior to the swarm reaching the pre-flight buzzing phase of the decision-making process, even when directional consensus was high. We therefore suggest that not all scouts involved in the decision-making process attempt to guide the swarm. © 2014. Published by The Company of Biologists Ltd.

  3. Investigating the auroral electrojets using Swarm

    NASA Astrophysics Data System (ADS)

    Smith, Ashley; Macmillan, Susan; Beggan, Ciaran; Whaler, Kathy

    2016-04-01

    The auroral electrojets are large horizontal currents that flow within the ionosphere in ovals around the polar regions. They are an important aspect of space weather and their position and intensity vary with solar wind conditions and geomagnetic activity. The electrojet positions are also governed by the Earth's main magnetic field. During more active periods, the auroral electrojets typically move equatorward and become more intense. This causes a range of effects on Earth and in space, including geomagnetically induced currents in power transmission networks, disturbance to radio communications and increased drag on satellites due to expansion of the atmosphere. They are also indicative of where the aurora are visible. Monitoring of the auroral electrojets in the pre-satellite era was limited to the network of ground-based magnetic observatories, from which the traditional AE activity indices are produced. These suffer in particular from the stations' poor distribution in position and so this motivates the use of satellite-based measurements. With polar low-Earth orbit satellites carrying magnetometers, all latitudes can be sampled with excellent resolution. This poster presents an investigation using Swarm's magnetometer data to detect the electrojets as the spacecraft move above them. We compare and contrast two approaches, one which uses vector data and the other which uses scalar data (Hamilton and Macmillan 2013, Vennerstrom and Moretto, 2013). Using ideas from both approaches we determine the oval positions and intensities from Swarm and earlier satellites. The variation in latitude and intensity with solar wind conditions, geomagnetic activity and secular variation of the main field is investigated. We aim to elucidate the relative importance of these factors. Hamilton, B. and Macmillan, S., 2013. Investigation of decadal scale changes in the auroral oval positions using Magsat and CHAMP data. Poster at IAGA 12th Scientific Assembly, 2013. http

  4. Modeling, Analysis, and Control of Swarming Agents in a Probabilistic Framework

    DTIC Science & Technology

    2012-11-01

    configurations, which can ultimately lead the swarm towards configurations close to the global minimum of the total potential of interactions. The drawback ...165–171, 1992. [6] H. Ye, H. Wang, and H. Wang, “Stabilization of a PVTOL aircraft and an inertia wheel pendulum using saturation technique,” IEEE...estimate its parameters. The drawback of this approach is that the assumed form of the field can be unrealistic. In the approach that we are presenting here

  5. Finding Minimal Addition Chains with a Particle Swarm Optimization Algorithm

    NASA Astrophysics Data System (ADS)

    León-Javier, Alejandro; Cruz-Cortés, Nareli; Moreno-Armendáriz, Marco A.; Orantes-Jiménez, Sandra

    The addition chains with minimal length are the basic block to the optimal computation of finite field exponentiations. It has very important applications in the areas of error-correcting codes and cryptography. However, obtaining the shortest addition chains for a given exponent is a NP-hard problem. In this work we propose the adaptation of a Particle Swarm Optimization algorithm to deal with this problem. Our proposal is tested on several exponents whose addition chains are considered hard to find. We obtained very promising results.

  6. Propulsion Trade Studies for Spacecraft Swarm Mission Design

    NASA Technical Reports Server (NTRS)

    Dono, Andres; Plice, Laura; Mueting, Joel; Conn, Tracie; Ho, Michael

    2018-01-01

    Spacecraft swarms constitute a challenge from an orbital mechanics standpoint. Traditional mission design involves the application of methodical processes where predefined maneuvers for an individual spacecraft are planned in advance. This approach does not scale to spacecraft swarms consisting of many satellites orbiting in close proximity; non-deterministic maneuvers cannot be preplanned due to the large number of units and the uncertainties associated with their differential deployment and orbital motion. For autonomous small sat swarms in LEO, we investigate two approaches for controlling the relative motion of a swarm. The first method involves modified miniature phasing maneuvers, where maneuvers are prescribed that cancel the differential delta V of each CubeSat's deployment vector. The second method relies on artificial potential functions (APFs) to contain the spacecraft within a volumetric boundary and avoid collisions. Performance results and required delta V budgets are summarized, indicating that each method has advantages and drawbacks for particular applications. The mini phasing maneuvers are more predictable and sustainable. The APF approach provides a more responsive and distributed performance, but at considerable propellant cost. After considering current state of the art CubeSat propulsion systems, we conclude that the first approach is feasible, but the modified APF method of requires too much control authority to be enabled by current propulsion systems.

  7. Toward more complete magnetic gradiometry with the Swarm mission

    NASA Astrophysics Data System (ADS)

    Kotsiaros, Stavros

    2016-07-01

    An analytical and numerical analysis of the spectral properties of the gradient tensor, initially performed by Rummel and van Gelderen (Geophys J Int 111(1):159-169, 1992) for the gravity potential, shows that when the tensor elements are grouped into sets of semi-tangential and pure-tangential parts, they produce almost identical signal content as the normal element. Moreover, simple eigenvalue relations can be derived between these sets and the spherical harmonic expansion of the potential. This theoretical development generally applies to any potential field. First, the analysis of Rummel and van Gelderen (1992) is adapted to the magnetic field case and then the elements of the magnetic gradient tensor are estimated by 2 years of Swarm data and grouped into \\varvec{Γ }^{(1)} = {[\\varvec{nabla } {{B}}]_{rθ },[\\varvec{nabla } {{B}}]_{r\\varphi }} resp. \\varvec{Γ }^{(2)} = {[\\varvec{nabla } {{B}}]_{θ θ }-[\\varvec{nabla } {{B}}]_{\\varphi \\varphi }, 2[\\varvec{nabla } {{B}}]_{θ \\varphi }}. It is shown that the estimated combinations \\varvec{Γ }^{(1)} and \\varvec{Γ }^{(2)} produce similar signal content as the theoretical radial gradient \\varvec{Γ }^{(0)} = {[\\varvec{nabla } {{B}}]_{rr}}. These results demonstrate the ability of multi-satellite missions such as Swarm, which cannot directly measure the radial gradient, to retrieve similar signal content by means of the horizontal gradients. Finally, lithospheric field models are derived using the gradient combinations \\varvec{Γ }^{(1)} and \\varvec{Γ }^{(2)} and compared with models derived from traditional vector and gradient data. The model resulting from \\varvec{Γ }^{(1)} leads to a very similar, and in particular cases improved, model compared to models retrieved by using approximately three times more data, i.e., a full set of vector, North-South and East-West gradients. This demonstrates the high information content of

  8. Comparison result of inversion of gravity data of a fault by particle swarm optimization and Levenberg-Marquardt methods.

    PubMed

    Toushmalani, Reza

    2013-01-01

    The purpose of this study was to compare the performance of two methods for gravity inversion of a fault. First method [Particle swarm optimization (PSO)] is a heuristic global optimization method and also an optimization algorithm, which is based on swarm intelligence. It comes from the research on the bird and fish flock movement behavior. Second method [The Levenberg-Marquardt algorithm (LM)] is an approximation to the Newton method used also for training ANNs. In this paper first we discussed the gravity field of a fault, then describes the algorithms of PSO and LM And presents application of Levenberg-Marquardt algorithm, and a particle swarm algorithm in solving inverse problem of a fault. Most importantly the parameters for the algorithms are given for the individual tests. Inverse solution reveals that fault model parameters are agree quite well with the known results. A more agreement has been found between the predicted model anomaly and the observed gravity anomaly in PSO method rather than LM method.

  9. Loss of FliL alters Proteus mirabilis surface sensing and temperature-dependent swarming.

    PubMed

    Lee, Yi-Ying; Belas, Robert

    2015-01-01

    Proteus mirabilis is a dimorphic motile bacterium well known for its flagellum-dependent swarming motility over surfaces. In liquid, P. mirabilis cells are 1.5- to 2.0-μm swimmer cells with 4 to 6 flagella. When P. mirabilis encounters a solid surface, where flagellar rotation is limited, swimmer cells differentiate into elongated (10- to 80-μm), highly flagellated swarmer cells. In order for P. mirabilis to swarm, it first needs to detect a surface. The ubiquitous but functionally enigmatic flagellar basal body protein FliL is involved in P. mirabilis surface sensing. Previous studies have suggested that FliL is essential for swarming through its involvement in viscosity-dependent monitoring of flagellar rotation. In this study, we constructed and characterized ΔfliL mutants of P. mirabilis and Escherichia coli. Unexpectedly and unlike other fliL mutants, both P. mirabilis and E. coli ΔfliL cells swarm (Swr(+)). Further analysis revealed that P. mirabilis ΔfliL cells also exhibit an alteration in their ability to sense a surface: e.g., ΔfliL P. mirabilis cells swarm precociously over surfaces with low viscosity that normally impede wild-type swarming. Precocious swarming is due to an increase in the number of elongated swarmer cells in the population. Loss of fliL also results in an inhibition of swarming at <30°C. E. coli ΔfliL cells also exhibit temperature-sensitive swarming. These results suggest an involvement of FliL in the energetics and function of the flagellar motor. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  10. Properties of a Formal Method to Model Emergence in Swarm-Based Systems

    NASA Technical Reports Server (NTRS)

    Rouff, Christopher; Vanderbilt, Amy; Truszkowski, Walt; Rash, James; Hinchey, Mike

    2004-01-01

    Future space missions will require cooperation between multiple satellites and/or rovers. Developers are proposing intelligent autonomous swarms for these missions, but swarm-based systems are difficult or impossible to test with current techniques. This viewgraph presentation examines the use of formal methods in testing swarm-based systems. The potential usefulness of formal methods in modeling the ANTS asteroid encounter mission is also examined.

  11. Physics-based approach to chemical source localization using mobile robotic swarms

    NASA Astrophysics Data System (ADS)

    Zarzhitsky, Dimitri

    2008-07-01

    Recently, distributed computation has assumed a dominant role in the fields of artificial intelligence and robotics. To improve system performance, engineers are combining multiple cooperating robots into cohesive collectives called swarms. This thesis illustrates the application of basic principles of physicomimetics, or physics-based design, to swarm robotic systems. Such principles include decentralized control, short-range sensing and low power consumption. We show how the application of these principles to robotic swarms results in highly scalable, robust, and adaptive multi-robot systems. The emergence of these valuable properties can be predicted with the help of well-developed theoretical methods. In this research effort, we have designed and constructed a distributed physicomimetics system for locating sources of airborne chemical plumes. This task, called chemical plume tracing (CPT), is receiving a great deal of attention due to persistent homeland security threats. For this thesis, we have created a novel CPT algorithm called fluxotaxis that is based on theoretical principles of fluid dynamics. Analytically, we show that fluxotaxis combines the essence, as well as the strengths, of the two most popular biologically-inspired CPT methods-- chemotaxis and anemotaxis. The chemotaxis strategy consists of navigating in the direction of the chemical density gradient within the plume, while the anemotaxis approach is based on an upwind traversal of the chemical cloud. Rigorous and extensive experimental evaluations have been performed in simulated chemical plume environments. Using a suite of performance metrics that capture the salient aspects of swarm-specific behavior, we have been able to evaluate and compare the three CPT algorithms. We demonstrate the improved performance of our fluxotaxis approach over both chemotaxis and anemotaxis in these realistic simulation environments, which include obstacles. To test our understanding of CPT on actual hardware

  12. 2014 Mainshock-Aftershock Activity Versus Earthquake Swarms in West Bohemia, Czech Republic

    NASA Astrophysics Data System (ADS)

    Jakoubková, Hana; Horálek, Josef; Fischer, Tomáš

    2018-01-01

    A singular sequence of three episodes of ML3.5, 4.4 and 3.6 mainshock-aftershock occurred in the West Bohemia/Vogtland earthquake-swarm region during 2014. We analysed this activity using the WEBNET data and compared it with the swarms of 1997, 2000, 2008 and 2011 from the perspective of cumulative seismic moment, statistical characteristics, space-time distribution of events, and prevailing focal mechanisms. For this purpose, we improved the scaling relation between seismic moment M0 and local magnitude ML by WEBNET. The total seismic moment released during 2014 episodes (M_{0tot}≈ 1.58× 10^{15} Nm) corresponded to a single ML4.6+ event and was comparable to M_{0tot} of the swarms of 2000, 2008 and 2011. We inferred that the ML4.8 earthquake is the maximum expected event in Nový Kostel (NK), the main focal zone. Despite the different character of the 2014 sequence and the earthquake swarms, the magnitude-frequency distributions (MFDs) show the b-values ≈ 1 and probability density functions (PDFs) of the interevent times indicate the similar event rate of the individual swarms and 2014 activity. Only the a-value (event-productivity) in the MFD of the 2014 sequence is significantly lower than those of the swarms. A notable finding is a significant acceleration of the seismic moment release in each subsequent activity starting from the 2000 swarm to the 2014 sequence, which may indicate an alteration from the swarm-like to the mainshocks-aftershock character of the seismicity. The three mainshocks are located on a newly activated fault segment/asperity (D in out notation) of the NK zone situated in the transition area among fault segments A, B, C, which hosted the 2000, 2008 and 2011 swarms. The segment D appears to be predisposed to an oblique-thrust faulting while strike-slip faulting is typical of segments A, B and C. In conclusion, we propose a basic segment scheme of the NK zone which should be improved gradually.

  13. Seasonal Modulation of Earthquake Swarm Activity Near Maupin, Oregon

    NASA Astrophysics Data System (ADS)

    Braunmiller, J.; Nabelek, J.; Trehu, A. M.

    2012-12-01

    Between December 2006 and November 2011, the Pacific Northwest Seismic Network (PNSN) reported 464 earthquakes in a swarm about 60 km east-southeast of Mt. Hood near the town of Maupin, Oregon. Relocation of forty-five MD≥2.5 earthquakes and regional moment tensor analysis of nine 3.3≤Mw≤3.9 earthquakes reveals a north-northwest trending, less than 1 km2 sized active fault patch on a 70° west dipping fault. At about 17 km depth, the swarm occurred at or close to the bottom of the seismogenic crust. The swarm's cumulative seismic moment release, equivalent to an Mw=4.4 earthquake, is not dominated by a single shock; it is rather mainly due to 20 MD≥3.0 events, which occurred throughout the swarm. The swarm started at the southern end and, during the first 18 months of activity, migrated to the northwest at a rate of about 1-2 m/d until reaching its northern terminus. A 10° fault bend, inferred from locations and fault plane solutions, acted as geometrical barrier that temporarily halted event migration in mid-2007 before continuing north in early 2008. The slow event migration points to a pore pressure diffusion process suggesting the swarm onset was triggered by fluid inflow into the fault zone. At 17 km depth, triggering by meteoritic water seems unlikely for a normal crustal permeability. The double couple source mechanisms preclude a magmatic intrusion at the depth of the earthquakes. However, fluids (or gases) associated with a deeper, though undocumented, magma injection beneath the Cascade Mountains, could trigger seismicity in a pre-stressed region when they have migrated upward and reached the seismogenic crust. Superimposed on overall swarm evolution, we found a statistically significant annual seismicity variation, which is likely surface driven. The annual seismicity peak during spring (March-May) coincides with the maximum snow load on the near-by Cascades. The load corresponds to a surface pressure variation of about 6 kPa, which likely

  14. Male motion coordination in swarming Anopheles gambiae and Anopheles coluzzii

    USDA-ARS?s Scientific Manuscript database

    The Anopheles gambiae species complex comprises the primary vectors of malaria in much of sub-Saharan Africa; most of the mating in these species occurs in swarms composed almost entirely of males. Intermittent, parallel flight patterns in such swarms have been observed, but a detailed description o...

  15. Mechanism of the 1996-97 non-eruptive volcano-tectonic earthquake swarm at Iliamna Volcano, Alaska

    USGS Publications Warehouse

    Roman, D.C.; Power, J.A.

    2011-01-01

    A significant number of volcano-tectonic(VT) earthquake swarms, some of which are accompanied by ground deformation and/or volcanic gas emissions, do not culminate in an eruption.These swarms are often thought to represent stalled intrusions of magma into the mid- or shallow-level crust.Real-time assessment of the likelihood that a VTswarm will culminate in an eruption is one of the key challenges of volcano monitoring, and retrospective analysis of non-eruptive swarms provides an important framework for future assessments. Here we explore models for a non-eruptive VT earthquake swarm located beneath Iliamna Volcano, Alaska, in May 1996-June 1997 through calculation and inversion of fault-plane solutions for swarm and background periods, and through Coulomb stress modeling of faulting types and hypocenter locations observed during the swarm. Through a comparison of models of deep and shallow intrusions to swarm observations,we aim to test the hypothesis that the 1996-97 swarm represented a shallow intrusion, or "failed" eruption.Observations of the 1996-97 swarm are found to be consistent with several scenarios including both shallow and deep intrusion, most likely involving a relatively small volume of intruded magma and/or a low degree of magma pressurization corresponding to a relatively low likelihood of eruption. ?? 2011 Springer-Verlag.

  16. Optimization of shared autonomy vehicle control architectures for swarm operations.

    PubMed

    Sengstacken, Aaron J; DeLaurentis, Daniel A; Akbarzadeh-T, Mohammad R

    2010-08-01

    The need for greater capacity in automotive transportation (in the midst of constrained resources) and the convergence of key technologies from multiple domains may eventually produce the emergence of a "swarm" concept of operations. The swarm, which is a collection of vehicles traveling at high speeds and in close proximity, will require technology and management techniques to ensure safe, efficient, and reliable vehicle interactions. We propose a shared autonomy control approach, in which the strengths of both human drivers and machines are employed in concert for this management. Building from a fuzzy logic control implementation, optimal architectures for shared autonomy addressing differing classes of drivers (represented by the driver's response time) are developed through a genetic-algorithm-based search for preferred fuzzy rules. Additionally, a form of "phase transition" from a safe to an unsafe swarm architecture as the amount of sensor capability is varied uncovers key insights on the required technology to enable successful shared autonomy for swarm operations.

  17. Swarm v2: highly-scalable and high-resolution amplicon clustering

    PubMed Central

    Quince, Christopher; de Vargas, Colomban; Dunthorn, Micah

    2015-01-01

    Previously we presented Swarm v1, a novel and open source amplicon clustering program that produced fine-scale molecular operational taxonomic units (OTUs), free of arbitrary global clustering thresholds and input-order dependency. Swarm v1 worked with an initial phase that used iterative single-linkage with a local clustering threshold (d), followed by a phase that used the internal abundance structures of clusters to break chained OTUs. Here we present Swarm v2, which has two important novel features: (1) a new algorithm for d = 1 that allows the computation time of the program to scale linearly with increasing amounts of data; and (2) the new fastidious option that reduces under-grouping by grafting low abundant OTUs (e.g., singletons and doubletons) onto larger ones. Swarm v2 also directly integrates the clustering and breaking phases, dereplicates sequencing reads with d = 0, outputs OTU representatives in fasta format, and plots individual OTUs as two-dimensional networks. PMID:26713226

  18. Swarm v2: highly-scalable and high-resolution amplicon clustering.

    PubMed

    Mahé, Frédéric; Rognes, Torbjørn; Quince, Christopher; de Vargas, Colomban; Dunthorn, Micah

    2015-01-01

    Previously we presented Swarm v1, a novel and open source amplicon clustering program that produced fine-scale molecular operational taxonomic units (OTUs), free of arbitrary global clustering thresholds and input-order dependency. Swarm v1 worked with an initial phase that used iterative single-linkage with a local clustering threshold (d), followed by a phase that used the internal abundance structures of clusters to break chained OTUs. Here we present Swarm v2, which has two important novel features: (1) a new algorithm for d = 1 that allows the computation time of the program to scale linearly with increasing amounts of data; and (2) the new fastidious option that reduces under-grouping by grafting low abundant OTUs (e.g., singletons and doubletons) onto larger ones. Swarm v2 also directly integrates the clustering and breaking phases, dereplicates sequencing reads with d = 0, outputs OTU representatives in fasta format, and plots individual OTUs as two-dimensional networks.

  19. Magma Reservoirs Feeding Giant Radiating Dike Swarms: Insights from Venus

    NASA Technical Reports Server (NTRS)

    Grosfils, E. B.; Ernst, R. E.

    2003-01-01

    Evidence of lateral dike propagation from shallow magma reservoirs is quite common on the terrestrial planets, and examination of the giant radiating dike swarm population on Venus continues to provide new insight into the way these complex magmatic systems form and evolve. For example, it is becoming clear that many swarms are an amalgamation of multiple discrete phases of dike intrusion. This is not surprising in and of itself, as on Earth there is clear evidence that formation of both magma reservoirs and individual giant radiating dikes often involves periodic magma injection. Similarly, giant radiating swarms on Earth can contain temporally discrete subswarms defined on the basis of geometry, crosscutting relationships, and geochemical or paleomagnetic signatures. The Venus data are important, however, because erosion, sedimentation, plate tectonic disruption, etc. on Earth have destroyed most giant radiating dike swarm's source regions, and thus we remain uncertain about the geometry and temporal evolution of the magma sources from which the dikes are fed. Are the reservoirs which feed the dikes large or small, and what are the implications for how the dikes themselves form? Does each subswarm originate from a single, periodically reactivated reservoir, or do subswarms emerge from multiple discrete geographic foci? If the latter, are these discrete foci located at the margins of a single large magma body, or do multiple smaller reservoirs define the character of the magmatic center as a whole? Similarly, does the locus of magmatic activity change with time, or are all the foci active simultaneously? Careful study of giant radiating dike swarms on Venus is yielding the data necessary to address these questions and constrain future modeling efforts. Here, using giant radiating dike swarms from the Nemesis Tessera (V14) and Carson (V43) quadrangles as examples, we illustrate some of the dike swarm focal region diversity observed on Venus and briefly explore some

  20. Diminished tektite ablation in the wake of a swarm

    NASA Technical Reports Server (NTRS)

    Sepri, P.; Chen, K. K.; Okeefe, J. A.

    1981-01-01

    Observations of ablation markings on tektite surfaces reveal that a large variation in aerodynamic heating must have occurred among the members of a swarm during atmospheric entry. In a few cases, the existence of jagged features indicates that these tektite surfaces may have barely reached the melting temperature. Such an observation seems to be incompatible with the necessarily large heating rates suffered by other tektites which exhibit the ring wave melt flow. A reconciliation is proposed in the form of a wake shielding model which is a natural consequence of swarm entry. Calculations indicate that the observed ablation variations are actually possible for swarm entry at greater than escape velocity. This aerodynamic conclusion provides support for the arguments favoring extraterrestrial origin of tektites.

  1. DualTrust: A Trust Management Model for Swarm-Based Autonomic Computing Systems

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Maiden, Wendy M.

    Trust management techniques must be adapted to the unique needs of the application architectures and problem domains to which they are applied. For autonomic computing systems that utilize mobile agents and ant colony algorithms for their sensor layer, certain characteristics of the mobile agent ant swarm -- their lightweight, ephemeral nature and indirect communication -- make this adaptation especially challenging. This thesis looks at the trust issues and opportunities in swarm-based autonomic computing systems and finds that by monitoring the trustworthiness of the autonomic managers rather than the swarming sensors, the trust management problem becomes much more scalable and stillmore » serves to protect the swarm. After analyzing the applicability of trust management research as it has been applied to architectures with similar characteristics, this thesis specifies the required characteristics for trust management mechanisms used to monitor the trustworthiness of entities in a swarm-based autonomic computing system and describes a trust model that meets these requirements.« less

  2. Swarm intelligence-based approach for optimal design of CMOS differential amplifier and comparator circuit using a hybrid salp swarm algorithm

    NASA Astrophysics Data System (ADS)

    Asaithambi, Sasikumar; Rajappa, Muthaiah

    2018-05-01

    In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.

  3. Swarm intelligence-based approach for optimal design of CMOS differential amplifier and comparator circuit using a hybrid salp swarm algorithm.

    PubMed

    Asaithambi, Sasikumar; Rajappa, Muthaiah

    2018-05-01

    In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.

  4. A Novel Method for Tracking Individuals of Fruit Fly Swarms Flying in a Laboratory Flight Arena.

    PubMed

    Cheng, Xi En; Qian, Zhi-Ming; Wang, Shuo Hong; Jiang, Nan; Guo, Aike; Chen, Yan Qiu

    2015-01-01

    The growing interest in studying social behaviours of swarming fruit flies, Drosophila melanogaster, has heightened the need for developing tools that provide quantitative motion data. To achieve such a goal, multi-camera three-dimensional tracking technology is the key experimental gateway. We have developed a novel tracking system for tracking hundreds of fruit flies flying in a confined cubic flight arena. In addition to the proposed tracking algorithm, this work offers additional contributions in three aspects: body detection, orientation estimation, and data validation. To demonstrate the opportunities that the proposed system offers for generating high-throughput quantitative motion data, we conducted experiments on five experimental configurations. We also performed quantitative analysis on the kinematics and the spatial structure and the motion patterns of fruit fly swarms. We found that there exists an asymptotic distance between fruit flies in swarms as the population density increases. Further, we discovered the evidence for repulsive response when the distance between fruit flies approached the asymptotic distance. Overall, the proposed tracking system presents a powerful method for studying flight behaviours of fruit flies in a three-dimensional environment.

  5. Whistler-like Signals Detected Simultaneously by Swarm Satellites

    NASA Astrophysics Data System (ADS)

    Hulot, G.; Coisson, P.; Deram, P.; Leger, J. M.; Jager, T.; Brocco, L.

    2016-12-01

    The three Swarm satellites embark an absolute scalar magnetometer (ASM) that generates nominally 1 Hz filtered data of the intensity of the magnetic field. Its internal frequency of operation however allows to record data at higher sampling rate, generating so-called "burst-mode" data at 250 Hz. During the commissioning phase of the Swarm mission, between December 2013 and February 2014 several burst-mode sessions have been recorded. At the beginning the satellites were still on a pearls-on-string orbital configuration and later each satellite was successively moved to its final orbit. During the last two burst sessions satellites B and C were still following each other, while satellite A was already orbiting at a lower altitude, on the opposite side of the Earth. We present an analysis of the burst data recorded on 22 and 23 February 2014, when several short signals were detected, usually lasting less than 1 second, presenting a descending tone in the frequency band accessible using burst data (1-125 Hz), similar to the whistlers signals in VLF band. These signals were detected nearly simultaneously by satellites B and C, at about 300 km distance, corresponding to a horizontal speed of about 1500 km/s. We present an analysis of these events and of their coincidence with lighting activity on the ground in the area of visibility of these satellites, as provided by the WWLN.

  6. Climatology of the Auroral Electrojets Derived From the Along-Track Gradient of Magnetic Field Intensity Measured by POGO, Magsat, CHAMP, and Swarm

    NASA Astrophysics Data System (ADS)

    Smith, A. R. A.; Beggan, C. D.; Macmillan, S.; Whaler, K. A.

    2017-10-01

    The auroral electrojets (AEJs) are complex and dynamic horizontal ionospheric electric currents which form ovals around Earth's poles, being controlled by the morphology of the main magnetic field and the energy input from the solar wind interaction with the magnetosphere. The strength and location of the AEJ varies with solar wind conditions and the solar cycle but should also be controlled on decadal timescales by main field secular variation. To determine the AEJ climatology, we use data from four polar Low Earth Orbit magnetic satellite missions: POGO, Magsat, CHAMP, and Swarm. A simple estimation of the AEJ strength and latitude is made from each pass of the satellites, from peaks in the along-track gradient of the magnetic field intensity after subtracting a core and crustal magnetic field model. This measure of the AEJ activity is used to study the response in different sectors of magnetic local time (MLT) during different seasons and directions of the interplanetary magnetic field (IMF). We find a season-dependent hemispherical asymmetry in the AEJ response to IMF By, with a tendency toward stronger (weaker) AEJ currents in the north than the south during By>0 (By<0) around local winter. This effect disappears during local summer when we find a tendency toward stronger currents in the south than the north. The solar cycle modulation of the AEJ and the long-term shifting of its position and strength due to the core field variation are presented as challenges to internal field modeling.

  7. The Delta Low-Inclination Satellite Concept, an Opportunity to Enhance the Science Return of the Swarm Mission

    NASA Astrophysics Data System (ADS)

    Hulot, G.; Leger, J. M.; Olsen, N.; Stolle, C.; Chulliat, A.; Kuvshinov, A. V.; Vigneron, P.; Lesur, V.; Shimizu, H.; Sreenivasan, B.

    2015-12-01

    ESA's Swarm mission aims at studying all sources of Earth's magnetic field. It consists of two satellites (Alpha and Charlie), which fly side-by-side on near polar orbits at an altitude of slightly less than 500 km, and of a third satellite (Bravo) on a similar but slightly more polar and higher orbit, which progressively drifts with respect to that of Alpha and Charlie. This orbital configuration has proven extremely valuable, as evidenced by the many results already obtained from the first two years of the mission. These results, however, also reveal that geomagnetic field modeling and investigation efforts are now hampered by the still limited local time coverage provided by this constellation. This affects our ability to accurately characterize time changes in the ionospheric and magnetospheric field contributions, and to model the electrical conductivity of the Earth's mantle. It also indirectly limits our ability to model the core and lithospheric field. More generally, many of the "residual signals" detected in the very accurate magnetic data of the Swarm mission can still not fully be exploited. Further increasing the scientific return of the Swarm mission by squeezing more out of these data, however, would be possible if a fourth "Delta" satellite were to be launched soon enough to join the constellation at a similar altitude but much lower inclination orbit (such as 60°). Such a satellite would provide less geographical coverage but a much faster mapping of all local times over these latitudes. In this presentation we will present the rational for such a Delta mission and discuss the benefit it would bring, as well as plans currently under consideration to build a small satellite that could meet the corresponding requirements.

  8. Properties of a Formal Method for Prediction of Emergent Behaviors in Swarm-based Systems

    NASA Technical Reports Server (NTRS)

    Rouff, Christopher; Vanderbilt, Amy; Hinchey, Mike; Truszkowski, Walt; Rash, James

    2004-01-01

    Autonomous intelligent swarms of satellites are being proposed for NASA missions that have complex behaviors and interactions. The emergent properties of swarms make these missions powerful, but at the same time more difficult to design and assure that proper behaviors will emerge. This paper gives the results of research into formal methods techniques for verification and validation of NASA swarm-based missions. Multiple formal methods were evaluated to determine their effectiveness in modeling and assuring the behavior of swarms of spacecraft. The NASA ANTS mission was used as an example of swarm intelligence for which to apply the formal methods. This paper will give the evaluation of these formal methods and give partial specifications of the ANTS mission using four selected methods. We then give an evaluation of the methods and the needed properties of a formal method for effective specification and prediction of emergent behavior in swarm-based systems.

  9. A discrete particle model reproducing collective dynamics of a bee swarm.

    PubMed

    Bernardi, Sara; Colombi, Annachiara; Scianna, Marco

    2018-02-01

    In this article, we present a microscopic discrete mathematical model describing collective dynamics of a bee swarm. More specifically, each bee is set to move according to individual strategies and social interactions, the former involving the desire to reach a target destination, the latter accounting for repulsive/attractive stimuli and for alignment processes. The insects tend in fact to remain sufficiently close to the rest of the population, while avoiding collisions, and they are able to track and synchronize their movement to the flight of a given set of neighbors within their visual field. The resulting collective behavior of the bee cloud therefore emerges from non-local short/long-range interactions. Differently from similar approaches present in the literature, we here test different alignment mechanisms (i.e., based either on an Euclidean or on a topological neighborhood metric), which have an impact also on the other social components characterizing insect behavior. A series of numerical realizations then shows the phenomenology of the swarm (in terms of pattern configuration, collective productive movement, and flight synchronization) in different regions of the space of free model parameters (i.e., strength of attractive/repulsive forces, extension of the interaction regions). In this respect, constraints in the possible variations of such coefficients are here given both by reasonable empirical observations and by analytical results on some stability characteristics of the defined pairwise interaction kernels, which have to assure a realistic crystalline configuration of the swarm. An analysis of the effect of unconscious random fluctuations of bee dynamics is also provided. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. An External Archive-Guided Multiobjective Particle Swarm Optimization Algorithm.

    PubMed

    Zhu, Qingling; Lin, Qiuzhen; Chen, Weineng; Wong, Ka-Chun; Coello Coello, Carlos A; Li, Jianqiang; Chen, Jianyong; Zhang, Jun

    2017-09-01

    The selection of swarm leaders (i.e., the personal best and global best), is important in the design of a multiobjective particle swarm optimization (MOPSO) algorithm. Such leaders are expected to effectively guide the swarm to approach the true Pareto optimal front. In this paper, we present a novel external archive-guided MOPSO algorithm (AgMOPSO), where the leaders for velocity update are all selected from the external archive. In our algorithm, multiobjective optimization problems (MOPs) are transformed into a set of subproblems using a decomposition approach, and then each particle is assigned accordingly to optimize each subproblem. A novel archive-guided velocity update method is designed to guide the swarm for exploration, and the external archive is also evolved using an immune-based evolutionary strategy. These proposed approaches speed up the convergence of AgMOPSO. The experimental results fully demonstrate the superiority of our proposed AgMOPSO in solving most of the test problems adopted, in terms of two commonly used performance measures. Moreover, the effectiveness of our proposed archive-guided velocity update method and immune-based evolutionary strategy is also experimentally validated on more than 30 test MOPs.

  11. Comparison between Mean Forces and Swarms-of-Trajectories String Methods.

    PubMed

    Maragliano, Luca; Roux, Benoît; Vanden-Eijnden, Eric

    2014-02-11

    The original formulation of the string method in collective variable space is compared with a recent variant called string method with swarms-of-trajectories. The assumptions made in the original method are revisited and the significance of the minimum free energy path (MFEP) is discussed in the context of reactive events. These assumptions are compared to those made in the string method with swarms-of-trajectories, and shown to be equivalent in a certain regime: in particular an expression for the path identified by the swarms-of-trajectories method is given and shown to be closely related to the MFEP. Finally, the algorithmic aspects of both methods are compared.

  12. A fluid-driven earthquake swarm on the margin of the Yellowstone caldera

    USGS Publications Warehouse

    Shelly, David R.; Hill, David P.; Massin, Frederick; Farrell, Jamie; Smith, Robert B.; Taira, Taka'aki

    2013-01-01

    Over the past several decades, the Yellowstone caldera has experienced frequent earthquake swarms and repeated cycles of uplift and subsidence, reflecting dynamic volcanic and tectonic processes. Here, we examine the detailed spatial-temporal evolution of the 2010 Madison Plateau swarm, which occurred near the northwest boundary of the Yellowstone caldera. To fully explore the evolution of the swarm, we integrated procedures for seismic waveform-based earthquake detection with precise double-difference relative relocation. Using cross-correlation of continuous seismic data and waveform templates constructed from cataloged events, we detected and precisely located 8710 earthquakes during the three-week swarm, nearly four times the number of events included in the standard catalog. This high-resolution analysis reveals distinct migration of earthquake activity over the course of the swarm. The swarm initiated abruptly on January 17, 2010 at about 10 km depth and expanded dramatically outward (both shallower and deeper) over time, primarily along a NNW-striking, ~55º ENE-dipping structure. To explain these characteristics, we hypothesize that the swarm was triggered by the rupture of a zone of confined high-pressure aqueous fluids into a pre-existing crustal fault system, prompting release of accumulated stress. The high-pressure fluid injection may have been accommodated by hybrid shear and dilatational failure, as is commonly observed in exhumed hydrothermally affected fault zones. This process has likely occurred repeatedly in Yellowstone as aqueous fluids exsolved from magma migrate into the brittle crust, and it may be a key element in the observed cycles of caldera uplift and subsidence.

  13. VO-ESD: a virtual observatory approach to describe the geomagnetic field temporal variations with application to Swarm data

    NASA Astrophysics Data System (ADS)

    Saturnino, Diana; Langlais, Benoit; Amit, Hagay; Mandea, Mioara; Civet, François; Beucler, Éric

    2017-04-01

    A complete description of the main geomagnetic field temporal variation is crucial to understand dynamics in the core. This variation, termed secular variation (SV), is known with high accuracy at ground magnetic observatory locations. However the description of its spatial variability is hampered by the globally uneven distribution of the observatories. For the past two decades a global coverage of the field changes has been allowed by satellites. Their surveys of the geomagnetic field have been used to derive and improve global spherical harmonic (SH) models through some strict data selection schemes to minimise external field contributions. But discrepancies remain between ground measurements and field predictions by these models. Indeed, the global models do not reproduce small spatial scales of the field temporal variations. To overcome this problem we propose a modified Virtual Observatory (VO) approach by defining a globally homogeneous mesh of VOs at satellite altitude. With this approach we directly extract time series of the field and its temporal variation from satellite measurements as it is done at observatory locations. As satellite measurements are acquired at different altitudes a correction for the altitude is needed. Therefore, we apply an Equivalent Source Dipole (ESD) technique for each VO and each given time interval to reduce all measurements to a unique location, leading to time series similar to those available at ground magnetic observatories. Synthetic data is first used to validate the new VO-ESD approach. Then, we apply our scheme to measurements from the Swarm mission. For the first time, a 2.5 degrees resolution global mesh of VO times series is built. The VO-ESD derived time series are locally compared to ground observations as well as to satellite-based model predictions. The approach is able to describe detailed temporal variations of the field at local scales. The VO-ESD time series are also used to derive global SH models. Without

  14. An Improved Quantum-Behaved Particle Swarm Optimization Algorithm with Elitist Breeding for Unconstrained Optimization.

    PubMed

    Yang, Zhen-Lun; Wu, Angus; Min, Hua-Qing

    2015-01-01

    An improved quantum-behaved particle swarm optimization with elitist breeding (EB-QPSO) for unconstrained optimization is presented and empirically studied in this paper. In EB-QPSO, the novel elitist breeding strategy acts on the elitists of the swarm to escape from the likely local optima and guide the swarm to perform more efficient search. During the iterative optimization process of EB-QPSO, when criteria met, the personal best of each particle and the global best of the swarm are used to generate new diverse individuals through the transposon operators. The new generated individuals with better fitness are selected to be the new personal best particles and global best particle to guide the swarm for further solution exploration. A comprehensive simulation study is conducted on a set of twelve benchmark functions. Compared with five state-of-the-art quantum-behaved particle swarm optimization algorithms, the proposed EB-QPSO performs more competitively in all of the benchmark functions in terms of better global search capability and faster convergence rate.

  15. A Novel Particle Swarm Optimization Algorithm for Global Optimization

    PubMed Central

    Wang, Chun-Feng; Liu, Kui

    2016-01-01

    Particle Swarm Optimization (PSO) is a recently developed optimization method, which has attracted interest of researchers in various areas due to its simplicity and effectiveness, and many variants have been proposed. In this paper, a novel Particle Swarm Optimization algorithm is presented, in which the information of the best neighbor of each particle and the best particle of the entire population in the current iteration is considered. Meanwhile, to avoid premature, an abandoned mechanism is used. Furthermore, for improving the global convergence speed of our algorithm, a chaotic search is adopted in the best solution of the current iteration. To verify the performance of our algorithm, standard test functions have been employed. The experimental results show that the algorithm is much more robust and efficient than some existing Particle Swarm Optimization algorithms. PMID:26955387

  16. The Effect of Larval Diet on Adult Survival, Swarming Activity and Copulation Success in Male Aedes aegypti (Diptera: Culicidae).

    PubMed

    Lang, Bethan J; Idugboe, Stefano; McManus, Kirelle; Drury, Florence; Qureshi, Alima; Cator, Lauren J

    2018-01-10

    Control of Aedes aegypti (L.) (Diptera: Culicidae) populations is vital for reducing the transmission of several pervasive human diseases. The success of new vector control technologies will be influenced by the fitness of laboratory-reared transgenic males. However, there has been relatively little published data on how rearing practices influence male fitness in Aedes mosquitoes. In the laboratory, the effect of larval food availability on adult male fitness was tested, using a range of different fitness measures. Larval food availability was demonstrated to be positively correlated with adult body size. Larger males survived longer and exhibited greater swarming activity. As a consequence, larger males may have more mating opportunities in the wild. However, we also found that within a swarm larger males did not have an increased likelihood of copulating with a female. The outcome of the mating competition experiments depended on the methodology used to mark the males. These results show that fitness assessment can vary depending on the measure analyzed, and the methodology used to determine it. Continued investigation into these fitness measures and methodologies, and critically, their utility for predicting male performance in the field, will increase the efficiency of vector control programs. © The Author(s) 2017. Published by Oxford University Press on behalf of Entomological Society of America.

  17. Cultural-based particle swarm for dynamic optimisation problems

    NASA Astrophysics Data System (ADS)

    Daneshyari, Moayed; Yen, Gary G.

    2012-07-01

    Many practical optimisation problems are with the existence of uncertainties, among which a significant number belong to the dynamic optimisation problem (DOP) category in which the fitness function changes through time. In this study, we propose the cultural-based particle swarm optimisation (PSO) to solve DOP problems. A cultural framework is adopted incorporating the required information from the PSO into five sections of the belief space, namely situational, temporal, domain, normative and spatial knowledge. The stored information will be adopted to detect the changes in the environment and assists response to the change through a diversity-based repulsion among particles and migration among swarms in the population space, and also helps in selecting the leading particles in three different levels, personal, swarm and global levels. Comparison of the proposed heuristics over several difficult dynamic benchmark problems demonstrates the better or equal performance with respect to most of other selected state-of-the-art dynamic PSO heuristics.

  18. Oscillators that sync and swarm.

    PubMed

    O'Keeffe, Kevin P; Hong, Hyunsuk; Strogatz, Steven H

    2017-11-15

    Synchronization occurs in many natural and technological systems, from cardiac pacemaker cells to coupled lasers. In the synchronized state, the individual cells or lasers coordinate the timing of their oscillations, but they do not move through space. A complementary form of self-organization occurs among swarming insects, flocking birds, or schooling fish; now the individuals move through space, but without conspicuously altering their internal states. Here we explore systems in which both synchronization and swarming occur together. Specifically, we consider oscillators whose phase dynamics and spatial dynamics are coupled. We call them swarmalators, to highlight their dual character. A case study of a generalized Kuramoto model predicts five collective states as possible long-term modes of organization. These states may be observable in groups of sperm, Japanese tree frogs, colloidal suspensions of magnetic particles, and other biological and physical systems in which self-assembly and synchronization interact.

  19. Swarm Deployable Boom Assembly (DBA) Development of a Deployable Magnetometer Boom for the Swarm Spacecraft

    NASA Astrophysics Data System (ADS)

    McMahon, Paul; Jung, Hans-Juergen; Edwards, Jeff

    2013-09-01

    The Swarm programme consists of 3 magnetically clean satellites flying in close formation designed to measure the Earth's magnetic field using 2 Magnetometers mounted on a 4.3m long deployable boom.Deployment is initiated by releasing 3 HDRMs, once released the boom oscillates back and forth on a pair of pivots, similar to a restaurant kitchen door hinge, for around 120 seconds before coming to rest on 3 kinematic mounts which are used to provide an accurate reference location in the deployed position. Motion of the boom is damped through a combination of friction, spring hysteresis and flexing of the 120+ cables crossing the hinge. Considerable development work and accurate numerical modelling of the hinge motion was required to predict performance across a wide temperature range and ensure that during the 1st overshoot the boom did not damage itself, the harness or the spacecraft.Due to the magnetic cleanliness requirements of the spacecraft no magnetic materials could be used in the design of the hardware.

  20. Simple stochastic order-book model of swarm behavior in continuous double auction

    NASA Astrophysics Data System (ADS)

    Ichiki, Shingo; Nishinari, Katsuhiro

    2015-02-01

    In this study, we present a simple stochastic order-book model for investors' swarm behaviors seen in the continuous double auction mechanism, which is employed by major global exchanges. Our study shows a characteristic called 'fat tail' seen in the data obtained from our model that incorporates the investors' swarm behaviors. Our model captures two swarm behaviors: one is investors' behavior to follow a trend in the historical price movement, and another is investors' behavior to send orders that contradict a trend in the historical price movement. In order to capture the features of influence by the swarm behaviors, from price data derived from our simulations using these models, we analyzed the price movement range, that is, how much the price is moved when it is continuously moved in a single direction. Depending on the type of swarm behavior, we saw a difference in the cumulative frequency distribution of this price movement range. In particular, for the model of investors who followed a trend in the historical price movement, we saw the power law in the tail of the cumulative frequency distribution of this price movement range. In addition, we analyzed the shape of the tail of the cumulative frequency distribution. The result demonstrated that one of the reasons the trend following of price occurs is that orders temporarily swarm on the order book in accordance with past price trends.

  1. Towards a Logical Distinction Between Swarms and Aftershock Sequences

    NASA Astrophysics Data System (ADS)

    Gardine, M.; Burris, L.; McNutt, S.

    2007-12-01

    The distinction between swarms and aftershock sequences has, up to this point, been fairly arbitrary and non- uniform. Typically 0.5 to 1 order of magnitude difference between the mainshock and largest aftershock has been a traditional choice, but there are many exceptions. Seismologists have generally assumed that the mainshock carries most of the energy, but this is only true if it is sufficiently large compared to the size and numbers of aftershocks. Here we present a systematic division based on energy of the aftershock sequence compared to the energy of the largest event of the sequence. It is possible to calculate the amount of aftershock energy assumed to be in the sequence using the b-value of the frequency-magnitude relation with a fixed choice of magnitude separation (M-mainshock minus M-largest aftershock). Assuming that the energy of an aftershock sequence is less than the energy of the mainshock, the b-value at which the aftershock energy exceeds that of the mainshock energy determines the boundary between aftershock sequences and swarms. The amount of energy for various choices of b-value is also calculated using different values of magnitude separation. When the minimum b-value at which the sequence energy exceeds that of the largest event/mainshock is plotted against the magnitude separation, a linear trend emerges. Values plotting above this line represent swarms and values plotting below it represent aftershock sequences. This scheme has the advantage that it represents a physical quantity - energy - rather than only statistical features of earthquake distributions. As such it may be useful to help distinguish swarms from mainshock/aftershock sequences and to better determine the underlying causes of earthquake swarms.

  2. Targeting male mosquito swarms to control malaria vector density

    PubMed Central

    Sawadogo, Simon Peguedwinde; Niang, Abdoulaye; Bilgo, Etienne; Millogo, Azize; Maïga, Hamidou; Dabire, Roch K.; Tripet, Frederic; Diabaté, Abdoulaye

    2017-01-01

    Malaria control programs are being jeopardized by the spread of insecticide resistance in mosquito vector populations. It has been estimated that the spread of resistance could lead to an additional 120000 deaths per year, and interfere with the prospects for sustained control or the feasibility of achieving malaria elimination. Another complication for the development of resistance management strategies is that, in addition to insecticide resistance, mosquito behavior evolves in a manner that diminishes the impact of LLINs and IRS. Mosquitoes may circumvent LLIN and IRS control through preferential feeding and resting outside human houses and/or being active earlier in the evening before people go to sleep. Recent developments in our understanding of mosquito swarming suggest that new tools targeting mosquito swarms can be designed to cut down the high reproductive rate of malaria vectors. Targeting swarms of major malaria vectors may provide an effective control method to counteract behavioral resistance developed by mosquitoes. Here, we evaluated the impact of systematic spraying of swarms of Anopheles gambiae s.l. using a mixed carbamate and pyrethroid aerosol. The impact of this intervention on vector density, female insemination rates and the age structure of males was measured. We showed that the resulting mass killing of swarming males and some mate-seeking females resulted in a dramatic 80% decrease in population size compared to a control population. A significant decrease in female insemination rate and a significant shift in the age structure of the male population towards younger males incapable of mating were observed. This paradigm-shift study therefore demonstrates that targeting primarily males rather than females, can have a drastic impact on mosquito population. PMID:28278212

  3. Improved Performance of Loop-Mediated Isothermal Amplification Assays via Swarm Priming.

    PubMed

    Martineau, Rhett L; Murray, Sarah A; Ci, Shufang; Gao, Weimin; Chao, Shih-Hui; Meldrum, Deirdre R

    2017-01-03

    This work describes an enhancement to the loop-mediated isothermal amplification (LAMP) reaction which results in improved performance. Enhancement is achieved by adding a new set of primers to conventional LAMP reactions. These primers are termed "swarm primers" based on their relatively high concentration and their ability to create new amplicons despite the theoretical lack of single-stranded annealing sites. The primers target a region upstream of the FIP/BIP primer recognition sequences on opposite strands, substantially overlapping F1/B1 sites. Thus, despite the addition of a new primer set to an already complex assay, no significant increase in assay complexity is incurred. Swarm priming is presented for three DNA templates: Lambda phage, Synechocystis sp. PCC 6803 rbcL gene, and human HFE. The results of adding swarm primers to conventional LAMP reactions include increased amplification speed, increased indicator contrast, and increased reaction products. For at least one template, minor improvements in assay repeatability are also shown. In addition, swarm priming is shown to be effective at increasing the reaction speed for RNA amplification via RT-LAMP. Collectively, these results suggest that the addition of swarm primers will likely benefit most if not all existing LAMP assays based on state-of-the-art, six-primer reactions.

  4. Reversals and collisions optimize protein exchange in bacterial swarms

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Amiri, Aboutaleb; Harvey, Cameron; Buchmann, Amy

    Swarming groups of bacteria coordinate their behavior by self-organizing as a population to move over surfaces in search of nutrients and optimal niches for colonization. Many open questions remain about the cues used by swarming bacteria to achieve this self-organization. While chemical cue signaling known as quorum sensing is well-described, swarming bacteria often act and coordinate on time scales that could not be achieved via these extracellular quorum sensing cues. Here, cell-cell contact-dependent protein exchange is explored as amechanism of intercellular signaling for the bacterium Myxococcus xanthus. A detailed biologically calibrated computational model is used to study how M. xanthusmore » optimizes the connection rate between cells and maximizes the spread of an extracellular protein within the population. The maximum rate of protein spreading is observed for cells that reverse direction optimally for swarming. Cells that reverse too slowly or too fast fail to spread extracellular protein efficiently. In particular, a specific range of cell reversal frequencies was observed to maximize the cell-cell connection rate and minimize the time of protein spreading. Furthermore, our findings suggest that predesigned motion reversal can be employed to enhance the collective behavior of biological synthetic active systems.« less

  5. Fluid-Faulting Interactions Examined Though Massive Waveform-Based Analyses of Earthquake Swarms in Volcanic and Tectonic Settings: Mammoth Mountain, Long Valley, Lassen, and Fillmore, California Swarms, 2014-2015

    NASA Astrophysics Data System (ADS)

    Shelly, D. R.; Ellsworth, W. L.; Prejean, S. G.; Hill, D. P.; Hardebeck, J.; Hsieh, P. A.

    2015-12-01

    Earthquake swarms, sequences of sustained seismicity, convey active subsurface processes that sometimes precede larger tectonic or volcanic episodes. Their extended activity and spatiotemporal migration can often be attributed to fluid pressure transients as migrating crustal fluids (typically water and CO2) interact with subsurface structures. Although the swarms analyzed here are interpreted to be natural in origin, the mechanisms of seismic activation likely mirror those observed for earthquakes induced by industrial fluid injection. Here, we use massive-scale waveform correlation to detect and precisely locate 3-10 times as many earthquakes as included in routine catalogs for recent (2014-2015) swarms beneath Mammoth Mountain, Long Valley Caldera, Lassen Volcanic Center, and Fillmore areas of California, USA. These enhanced catalogs, with location precision as good as a few meters, reveal signatures of fluid-faulting interactions, such as systematic migration, fault-valve behavior, and fracture mesh structures, not resolved in routine catalogs. We extend this analysis to characterize source mechanism similarity even for very small newly detected events using relative P and S polarity estimates. This information complements precise locations to define fault complexities that would otherwise be invisible. In particular, although swarms often consist of groups of highly similar events, some swarms contain a population of outliers with different slip and/or fault orientations. These events highlight the complexity of fluid-faulting interactions. Despite their different settings, the four swarms analyzed here share many similarities, including pronounced hypocenter migration suggestive of a fluid pressure trigger. This includes the July 2015 Fillmore swarm, which, unlike the others, occurred outside of an obvious volcanic zone. Nevertheless, it exhibited systematic westward and downdip migration on a ~1x1.5 km low-angle, NW-dipping reverse fault at midcrustal depth.

  6. The global distribution of giant radiating dike swarms on Venus: Implications for the global stress state

    NASA Astrophysics Data System (ADS)

    Grosfils, E. B.; Head, J. W.

    1994-04-01

    Magellan radar data of Venus reveal 163 large radial lineament systems composed of graben, fissure, and fracture elements. On the basis of their structure, plan view geometry, and volcanic associations, at least 72% are interpreted to have formed primarily through subsurface dike swarm emplacement, the remainder through uplift or a combination of these two mechanisms. The population of swarms is used to determine regional and global stress orientation. The stress configuration recorded from 330-210 deg E (Aphrodite Terra) is best explained by isostatic compensation of existing long wavelength topography or coupling between mantle flow and the lithosphere. The rest are correlated with concentrations of rifting and volcanism in the Beta-Atla-Themis region. The global stress field on Venus is different than that of Earth, where plate boundary forces dominate.

  7. The global distribution of giant radiating dike swarms on Venus: Implications for the global stress state

    NASA Technical Reports Server (NTRS)

    Grosfils, Eric B.; Head, James W.

    1994-01-01

    Magellan radar data of Venus reveal 163 large radial lineament systems composed of graben, fissure, and fracture elements. On the basis of their structure, plan view geometry, and volcanic associations, at least 72% are interpreted to have formed primarily through subsurface dike swarm emplacement, the remainder through uplift or a combination of these two mechanisms. The population of swarms is used to determine regional and global stress orientation. The stress configuration recorded from 330-210 deg E (Aphrodite Terra) is best explained by isostatic compensation of existing long wavelength topography or coupling between mantle flow and the lithosphere. The rest are correlated with concentrations of rifting and volcanism in the Beta-Atla-Themis region. The global stress field on Venus is different than that of Earth, where plate boundary forces dominate.

  8. C/NOFS, SWARM, and LISN Observations of Equatorial Plasma Bubbles

    NASA Astrophysics Data System (ADS)

    Valladares, C. E.; Coisson, P.; Buchert, S. C.; Huang, C.; Sheehan, R.

    2017-12-01

    We have used Langmuir Probe densities measured during the early commissioning phase of the SWARM mission and simultaneous number densities recorded with the PLP instrument on board the C/NOFS satellite to investigate the geometric characteristics of equatorial plasma bubbles (EPB). The SWARM satellites orbit in a polar orbit and the C/NOFS satellite has a near equatorial trajectory making it possible to precisely measure the north-south and the east-west width of plasma depletions. This unique satellite database is complemented with TEC values collected with hundreds of GPS receivers that belong to LISN and other networks that operate in South and Central America. The GPS receivers provide multiple and almost concurrent observations of the TEC depletions that are required to calculate the velocity of plasma bubbles as a function of time, latitude, and longitude. The bubble velocity field commonly decreases through the night from 150 to 0 m/s and from low to higher latitudes at a rate equal to 5 m/s/degree. This bubble velocity field is used to trace backward and forward in time the satellite and GPS observations and reconstruct plasma depletions in 3 dimensions. The 3-D geometry indicates that in December 2013, the EPBs most of the time correspond to a series of embedded shells that drift eastward with velocities that vary between 125 and 20 m/s. The 3-D reconstructed EPBs can be used to perform close comparisons with results of numerical simulations and 2-D observations conducted with coherent radars or imagers.

  9. Long-term evolution of a planetesimal swarm in the vicinity of a protoplanet

    NASA Technical Reports Server (NTRS)

    Kary, David M.; Lissauer, Jack J.

    1991-01-01

    Many models of planet formation involve scenarios in which one or a few large protoplanets interact with a swarm of much smaller planetesimals. In such scenarios, three-body perturbations by the protoplanet as well as mutual collisions and gravitational interactions between the swarm bodies are important in determining the velocity distribution of the swarm. We are developing a model to examine the effects of these processes on the evolution of a planetesimal swarm. The model consists of a combination of numerical integrations of the gravitational influence of one (or a few) massive protoplanets on swarm bodies together with a statistical treatment of the interactions between the planetesimals. Integrating the planetesimal orbits allows us to take into account effects that are difficult to model analytically or statistically, such as three-body collision cross-sections and resonant perturbations by the protoplanet, while using a statistical treatment for the particle-particle interactions allows us to use a large enough sample to obtain meaningful results.

  10. Stationary swarming motion of active Brownian particles in parabolic external potential

    NASA Astrophysics Data System (ADS)

    Zhu, Wei Qiu; Deng, Mao Lin

    2005-08-01

    We investigate the stationary swarming motion of active Brownian particles in parabolic external potential and coupled to its mass center. Using Monte Carlo simulation we first show that the mass center approaches to rest after a sufficient long period of time. Thus, all the particles of a swarm have identical stationary motion relative to the mass center. Then the stationary probability density obtained by using the stochastic averaging method for quasi integrable Hamiltonian systems in our previous paper for the motion in 4-dimensional phase space of single active Brownian particle with Rayleigh friction model in parabolic potential is used to describe the relative stationary motion of each particle of the swarm and to obtain more probability densities including that for the total energy of the swarm. The analytical results are confirmed by comparing with those from simulation and also shown to be consistent with the existing deterministic exact steady-state solution.

  11. Swarming of the Formosan Subteranean Termite (Isoptera: Rhinotermitidae) in Southern Mississippi

    USDA-ARS?s Scientific Manuscript database

    Swarms of Formosan subterranean termites (FST) in Southern Mississippi were monitored from mid-April through late June, 2007-2009. Distribution of swarming colonies was recorded at 69 traps within Poplarville (Pearl River County) and an additional 45-65 traps, spaced at 1-5 mile (1.6-8 km) intervals...

  12. A Novel Method for Tracking Individuals of Fruit Fly Swarms Flying in a Laboratory Flight Arena

    PubMed Central

    Cheng, Xi En; Qian, Zhi-Ming; Wang, Shuo Hong; Jiang, Nan; Guo, Aike; Chen, Yan Qiu

    2015-01-01

    The growing interest in studying social behaviours of swarming fruit flies, Drosophila melanogaster, has heightened the need for developing tools that provide quantitative motion data. To achieve such a goal, multi-camera three-dimensional tracking technology is the key experimental gateway. We have developed a novel tracking system for tracking hundreds of fruit flies flying in a confined cubic flight arena. In addition to the proposed tracking algorithm, this work offers additional contributions in three aspects: body detection, orientation estimation, and data validation. To demonstrate the opportunities that the proposed system offers for generating high-throughput quantitative motion data, we conducted experiments on five experimental configurations. We also performed quantitative analysis on the kinematics and the spatial structure and the motion patterns of fruit fly swarms. We found that there exists an asymptotic distance between fruit flies in swarms as the population density increases. Further, we discovered the evidence for repulsive response when the distance between fruit flies approached the asymptotic distance. Overall, the proposed tracking system presents a powerful method for studying flight behaviours of fruit flies in a three-dimensional environment. PMID:26083385

  13. Rigid Body Modes Influence On Microvibration Analysis-Application To Swarm

    NASA Astrophysics Data System (ADS)

    Laduree, G.; Fransen, S.; Baldesi, G.; Pflieger, I.

    2012-07-01

    Microvibrations are defined as low level mechanical disturbances affecting payload performance, generated by mobile parts or mechanism operating on-board the spacecraft, like momentum or reaction wheels, pointing mechanism, cryo-coolers or thrusters. The disturbances caused by these sources are transmitted through the spacecraft structure and excite modes of that structure or elements of the payload impacting its performance (e.g. Line of sight rotations inducing some image quality degradation). The dynamic interaction between these three elements (noise source, spacecraft structure and sensitive receiver) makes the microvibration prediction a delicate problem. Microvibration sources are generally of concern in the frequency range from a few Hz to 1000 Hz. However, in some specific cases, high stability at lower frequencies might be requested. This is the case of the SWARM mission, whose objectives are to provide the best ever survey of the geomagnetic field and its temporal evolution as well as supplementary information for studying the interaction of the magnetic field with other physical quantities describing the Earth system (e.g. ocean circulation). Among its instruments, SWARM is embarking a very sensitive 6-axis accelerometer in the low frequency range (10-8 m/s2 or rad/s2 between 10-4 and 0.1 Hz) located at its Centre of Gravity and an Absolute Scalar Magnetometer located at the tip of a boom far from the spacecraft body. The ASM performs its measurements by rotating an alternative magnetic field around its main axis thanks to a piezo-electric motor. This repeated disturbance might generate some pollution of the accelerometer science data. The objective of this work is to focus on the interaction of the rigid body mode calculation method with the elastic contribution of the normal modes excited by the noise source frequency content. It has indeed been reported in the past that NASTRAN Lanczos rigid body modes may lead to inaccurate rigid-body accelerations

  14. SWARMs Ontology: A Common Information Model for the Cooperation of Underwater Robots

    PubMed Central

    Li, Xin; Bilbao, Sonia; Martín-Wanton, Tamara; Bastos, Joaquim; Rodriguez, Jonathan

    2017-01-01

    In order to facilitate cooperation between underwater robots, it is a must for robots to exchange information with unambiguous meaning. However, heterogeneity, existing in information pertaining to different robots, is a major obstruction. Therefore, this paper presents a networked ontology, named the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs) ontology, to address information heterogeneity and enable robots to have the same understanding of exchanged information. The SWARMs ontology uses a core ontology to interrelate a set of domain-specific ontologies, including the mission and planning, the robotic vehicle, the communication and networking, and the environment recognition and sensing ontology. In addition, the SWARMs ontology utilizes ontology constructs defined in the PR-OWL ontology to annotate context uncertainty based on the Multi-Entity Bayesian Network (MEBN) theory. Thus, the SWARMs ontology can provide both a formal specification for information that is necessarily exchanged between robots and a command and control entity, and also support for uncertainty reasoning. A scenario on chemical pollution monitoring is described and used to showcase how the SWARMs ontology can be instantiated, be extended, represent context uncertainty, and support uncertainty reasoning. PMID:28287468

  15. SWARMs Ontology: A Common Information Model for the Cooperation of Underwater Robots.

    PubMed

    Li, Xin; Bilbao, Sonia; Martín-Wanton, Tamara; Bastos, Joaquim; Rodriguez, Jonathan

    2017-03-11

    In order to facilitate cooperation between underwater robots, it is a must for robots to exchange information with unambiguous meaning. However, heterogeneity, existing in information pertaining to different robots, is a major obstruction. Therefore, this paper presents a networked ontology, named the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs) ontology, to address information heterogeneity and enable robots to have the same understanding of exchanged information. The SWARMs ontology uses a core ontology to interrelate a set of domain-specific ontologies, including the mission and planning, the robotic vehicle, the communication and networking, and the environment recognition and sensing ontology. In addition, the SWARMs ontology utilizes ontology constructs defined in the PR-OWL ontology to annotate context uncertainty based on the Multi-Entity Bayesian Network (MEBN) theory. Thus, the SWARMs ontology can provide both a formal specification for information that is necessarily exchanged between robots and a command and control entity, and also support for uncertainty reasoning. A scenario on chemical pollution monitoring is described and used to showcase how the SWARMs ontology can be instantiated, be extended, represent context uncertainty, and support uncertainty reasoning.

  16. A Machine Learning and Optimization Toolkit for the Swarm

    DTIC Science & Technology

    2014-11-17

    Machine   Learning  and  Op0miza0on   Toolkit  for  the  Swarm   Ilge  Akkaya,  Shuhei  Emoto...3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE A Machine Learning and Optimization Toolkit for the Swarm 5a. CONTRACT NUMBER... machine   learning   methodologies  by  providing  the  right  interfaces  between   machine   learning  tools  and

  17. Optimal configuration of power grid sources based on optimal particle swarm algorithm

    NASA Astrophysics Data System (ADS)

    Wen, Yuanhua

    2018-04-01

    In order to optimize the distribution problem of power grid sources, an optimized particle swarm optimization algorithm is proposed. First, the concept of multi-objective optimization and the Pareto solution set are enumerated. Then, the performance of the classical genetic algorithm, the classical particle swarm optimization algorithm and the improved particle swarm optimization algorithm are analyzed. The three algorithms are simulated respectively. Compared with the test results of each algorithm, the superiority of the algorithm in convergence and optimization performance is proved, which lays the foundation for subsequent micro-grid power optimization configuration solution.

  18. Solving Fractional Programming Problems based on Swarm Intelligence

    NASA Astrophysics Data System (ADS)

    Raouf, Osama Abdel; Hezam, Ibrahim M.

    2014-04-01

    This paper presents a new approach to solve Fractional Programming Problems (FPPs) based on two different Swarm Intelligence (SI) algorithms. The two algorithms are: Particle Swarm Optimization, and Firefly Algorithm. The two algorithms are tested using several FPP benchmark examples and two selected industrial applications. The test aims to prove the capability of the SI algorithms to solve any type of FPPs. The solution results employing the SI algorithms are compared with a number of exact and metaheuristic solution methods used for handling FPPs. Swarm Intelligence can be denoted as an effective technique for solving linear or nonlinear, non-differentiable fractional objective functions. Problems with an optimal solution at a finite point and an unbounded constraint set, can be solved using the proposed approach. Numerical examples are given to show the feasibility, effectiveness, and robustness of the proposed algorithm. The results obtained using the two SI algorithms revealed the superiority of the proposed technique among others in computational time. A better accuracy was remarkably observed in the solution results of the industrial application problems.

  19. Tectonic setting of the Wooded Island earthquake swarm, eastern Washington

    USGS Publications Warehouse

    Blakely, Richard J.; Sherrod, Brian L.; Weaver, Craig S.; Rohay, Alan C.; Wells, Ray E.

    2012-01-01

    Magnetic anomalies provide insights into the tectonic implications of a swarm of ~1500 shallow (~1 km deep) earthquakes that occurred in 2009 on the Hanford site,Washington. Epicenters were concentrated in a 2 km2 area nearWooded Island in the Columbia River. The largest earthquake (M 3.0) had first motions consistent with slip on a northwest-striking reverse fault. The swarm was accompanied by 35 mm of vertical surface deformation, seen in satellite interferometry (InSAR), interpreted to be caused by ~50 mm of slip on a northwest-striking reverse fault and associated bedding-plane fault in the underlying Columbia River Basalt Group (CRBG). A magnetic anomaly over exposed CRBG at Yakima Ridge 40 km northwest of Wooded Island extends southeastward beyond the ridge to the Columbia River, suggesting that the Yakima Ridge anticline and its associated thrust fault extend southeastward in the subsurface. In map view, the concealed anticline passes through the earthquake swarm and lies parallel to reverse faults determined from first motions and InSAR data. A forward model of the magnetic anomaly near Wooded Island is consistent with uplift of concealed CRBG, with the top surface <200 m below the surface. The earthquake swarm and the thrust and bedding-plane faults modeled from interferometry all fall within the northeastern limb of the faulted anticline. Although fluids may be responsible for triggering the Wooded Island earthquake swarm, the seismic and aseismic deformation are consistent with regional-scale tectonic compression across the concealed Yakima Ridge anticline.

  20. Mapping Ad Hoc Communications Network of a Large Number Fixed-Wing UAV Swarm

    DTIC Science & Technology

    2017-03-01

    partitioned sub-swarms. The work covered in this thesis is to build a model of the NPS swarm’s communication network in ns-3 simulation software and use...partitioned sub- swarms. The work covered in this thesis is to build a model of the NPS swarm’s communication network in ns-3 simulation software and...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS MAPPING AD HOC COMMUNICATIONS NETWORK OF A LARGE NUMBER FIXED-WING UAV SWARM by Alexis

  1. A shifted hyperbolic augmented Lagrangian-based artificial fish two-swarm algorithm with guaranteed convergence for constrained global optimization

    NASA Astrophysics Data System (ADS)

    Rocha, Ana Maria A. C.; Costa, M. Fernanda P.; Fernandes, Edite M. G. P.

    2016-12-01

    This article presents a shifted hyperbolic penalty function and proposes an augmented Lagrangian-based algorithm for non-convex constrained global optimization problems. Convergence to an ?-global minimizer is proved. At each iteration k, the algorithm requires the ?-global minimization of a bound constrained optimization subproblem, where ?. The subproblems are solved by a stochastic population-based metaheuristic that relies on the artificial fish swarm paradigm and a two-swarm strategy. To enhance the speed of convergence, the algorithm invokes the Nelder-Mead local search with a dynamically defined probability. Numerical experiments with benchmark functions and engineering design problems are presented. The results show that the proposed shifted hyperbolic augmented Lagrangian compares favorably with other deterministic and stochastic penalty-based methods.

  2. Increase in earthquake swarm activity in the southern Red Sea, Afar and Gulf of Aden

    NASA Astrophysics Data System (ADS)

    Ruch, Joël; Keir, Derek; Ogubazghi, Ghebrebrhan; di Giacomo, Domenico; Ladron Viltres, Renier; Jónsson, Sigurjón

    2017-04-01

    Rifting events periodically occur at divergent plate boundaries, consisting of magmatic intrusions, seismic swarms, surface faulting and in some cases volcanic eruptions. While earthquake swarms also occur at other types of plate boundaries, the swarms that have been observed in inland rift zones (e.g., in Afar and Iceland) and in a few offshore cases show an unambiguous relation with magmatic intrusions. These swarms typically last for a few days to a few weeks, lack a clear mainshock-aftershock decay pattern. Here we present a new study on earthquake swarms in the southern Red Sea, Afar and Gulf of Aden. We provide the first earthquake swarm catalogue for the region, which we compiled by integrating reexamined global and local earthquake catalogues with historical observations from 1960 to 2016. We find that in several cases in all the three areas, swarms have been re-occurring at the same locations every few decades (e.g., in the Bada area in Eritrea and Port Sudan region in the southern Red Sea in 1967 and 1993, and in the western Gulf of Aden in 1979, 1997 and 2010-2012). This suggests the existence of active spreading centers that are more active than previously thought. The swarms show different families of earthquake magnitudes, with clusters of Mw4 and Mw5 events (southern Red Sea and Aden) and occasional larger than Mw6 events, primarily in the southern Afar region (the Serdo and Dobi areas). Of the three areas, Gulf of Aden shows the highest swarm activity, followed by the Afar area and the southern Red Sea. Despite seeing the least amount of activity and lower magnitudes, the southern Red Sea has experienced multiple earthquake swarms and three volcanic eruptions (two of which resulted in new volcanic islands) during the past 10 years. We show that the three areas have been subject to an almost simultaneous increase of earthquake swarm activity during the last 10 years. This period (2005-2014) was much more active compared to the preceding decades (1960

  3. Multiple-Swarm Ensembles: Improving the Predictive Power and Robustness of Predictive Models and Its Use in Computational Biology.

    PubMed

    Alves, Pedro; Liu, Shuang; Wang, Daifeng; Gerstein, Mark

    2018-01-01

    Machine learning is an integral part of computational biology, and has already shown its use in various applications, such as prognostic tests. In the last few years in the non-biological machine learning community, ensembling techniques have shown their power in data mining competitions such as the Netflix challenge; however, such methods have not found wide use in computational biology. In this work, we endeavor to show how ensembling techniques can be applied to practical problems, including problems in the field of bioinformatics, and how they often outperform other machine learning techniques in both predictive power and robustness. Furthermore, we develop a methodology of ensembling, Multi-Swarm Ensemble (MSWE) by using multiple particle swarm optimizations and demonstrate its ability to further enhance the performance of ensembles.

  4. Multiple R&D projects scheduling optimization with improved particle swarm algorithm.

    PubMed

    Liu, Mengqi; Shan, Miyuan; Wu, Juan

    2014-01-01

    For most enterprises, in order to win the initiative in the fierce competition of market, a key step is to improve their R&D ability to meet the various demands of customers more timely and less costly. This paper discusses the features of multiple R&D environments in large make-to-order enterprises under constrained human resource and budget, and puts forward a multi-project scheduling model during a certain period. Furthermore, we make some improvements to existed particle swarm algorithm and apply the one developed here to the resource-constrained multi-project scheduling model for a simulation experiment. Simultaneously, the feasibility of model and the validity of algorithm are proved in the experiment.

  5. Seismotectonic significance of the 2008–2010 Walloon Brabant seismic swarm in the Brabant Massif, Belgium

    USGS Publications Warehouse

    Van Noten, Koen; Lecocq, Thomas; Shah, Anjana K.; Camelbeeck, Thierry

    2015-01-01

    Between 12 July 2008 and 18 January 2010 a seismic swarm occurred close to the town of Court-Saint-Etienne, 20 km SE of Brussels (Belgium). The Belgian network and a temporary seismic network covering the epicentral area established a seismic catalogue in which magnitude varies between ML -0.7 and ML 3.2. Based on waveform cross-correlation of co-located earthquakes, the spatial distribution of the hypocentre locations was improved considerably and shows a dense cluster displaying a 200 m-wide, 1.5-km long, NW-SE oriented fault structure at a depth range between 5 and 7 km, located in the Cambrian basement rocks of the Lower Palaeozoic Anglo-Brabant Massif. Waveform comparison of the largest events of the 2008–2010 swarm with an ML 4.0 event that occurred during swarm activity between 1953 and 1957 in the same region shows similar P- and S-wave arrivals at the Belgian Uccle seismic station. The geometry depicted by the hypocentral distribution is consistent with a nearly vertical, left-lateral strike-slip fault taking place in a current local WNW–ESE oriented local maximum horizontal stress field. To determine a relevant tectonic structure, a systematic matched filtering approach of aeromagnetic data, which can approximately locate isolated anomalies associated with hypocentral depths, has been applied. Matched filtering shows that the 2008–2010 seismic swarm occurred along a limited-sized fault which is situated in slaty, low-magnetic rocks of the Mousty Formation. The fault is bordered at both ends with obliquely oriented magnetic gradients. Whereas the NW end of the fault is structurally controlled, its SE end is controlled by a magnetic gradient representing an early-orogenic detachment fault separating the low-magnetic slaty Mousty Formation from the high-magnetic Tubize Formation. The seismic swarm is therefore interpreted as a sinistral reactivation of an inherited NW–SE oriented isolated fault in a weakened crust within the Cambrian core of

  6. Earthquake statistics, spatiotemporal distribution of foci and source mechanisms - a key to understanding of the West Bohemia/Vogtland earthquake swarms

    NASA Astrophysics Data System (ADS)

    Horálek, Josef; Čermáková, Hana; Fischer, Tomáš

    2016-04-01

    Earthquake swarms are sequences of numerous events closely clustered in space and time and do not have a single dominant mainshock. A few of the largest events in a swarm reach similar magnitudes and usually occur throughout the course of the earthquake sequence. These attributes differentiate earthquake swarms from ordinary mainshock-aftershock sequences. Earthquake swarms occur worldwide, in diverse geological units. The swarms typically accompany volcanic activity at margins of the tectonic plate but also occur in intracontinental areas where strain from tectonic-plate movement is small. The origin of earthquake swarms is still unclear. The swarms typically occur at the plate margins but also in intracontinental areas. West Bohemia-Vogtland represents one of the most active intraplate earthquake-swarm areas in Europe. It is characterised by a frequent reoccurrence of ML < 4.0 swarms and by high activity of crustal fluids. West Bohemia-Vogtland is one of the most active intraplate earthquake-swarm areas in Europe which also exhibits high activity of crustal fluids. The Nový Kostel focal zone (NK) dominates the recent seismicity, there were swarms in 1997, 2000, 2008 and 20011, and a striking non-swarm activity (mainshock-aftershock sequences) up to magnitude ML= 4.5 in May to August 2014. The swarms and the 2014 mainshock-aftershock sequences are located close to each other at depths between 6 and 13 km. The frequency-magnitude distributions of all the swarms show bimodal-like character: the most events obey the b-value = 1.0 distribution, but a group of the largest events depart significantly from it. All the ML > 2.8 swarm events are located in a few dense clusters which implies step by step rupturing of one or a few asperities during the individual swarms. The source mechanism patters (moment-tensor description, MT) of the individual swarms indicate several families of the mechanisms, which fit well geometry of respective fault segments. MTs of the most

  7. First structural approach to the SE Sardinia mafic dyke swarm

    NASA Astrophysics Data System (ADS)

    Martínez-Poza, Ana Isabel; Druguet, Elena

    2015-04-01

    We present a tectonic study of a NNW-SSE trending mafic dyke swarm intruded into granitoids of the late Variscan Sàrrabus pluton in SE Sardinia (Italy). Porphyritic to lamprophyric dykes show a predominant calc-alkaline affinity and they were emplaced during the Lower Permian at about 290-270 Ma (Vaccaro et al., 1991). The circular scanlines method of Mauldon (2001) was applied to aerial photographs along the coastal exposures to measure fracture frequency tendencies. This, together with field measurements, allowed us to determine the dyke pattern and the joint network present in the granitoid rocks and in the dykes. The subvertical dykes have a ~N135o ~N165o mean trend, with a secondary set at ~N10o which mainly corresponds to a previous intrusive pulse. The joint network has a wider range of orientations, with multiple joint sets present both in the host rocks and in the dykes. A clear distinction cannot be established in terms of orientation between fractures pre-dating and post-dating dykes. Using dyke orientations from field data, we applied the Bussell (1989) method to deduce the mean dilation direction of the dykes (246/02), and then, we performed a paleostress analysis (Jolly and Sanderson 1997) to get the principal stress axes compatibles with dyke emplacement (σ1: 135/77; σ2: 335/13; σ3: 244/05). σ3 is sub-parallel to the obtained sub-horizontal mean dyke opening direction, both being normal to the mean trend of the dyke swarm. During the dyke intrusion, the magmatic pressure (Pm) was lower than σ2. These results allowed us to construct the Mohr circle and to get the driving pressure ratio (R'=0.132) and the stress ratio (φ=0.327). It is inferred that dykes intruded into extensional fractures at relatively low fluid pressure conditions in comparison with the relatively higher regional differential stresses. Dyke emplacement was likely taking place under an ENE-WSW extensional regime (without considering the effect of post-intrusion crustal block

  8. Cranberry derivatives enhance biofilm formation and transiently impair swarming motility of the uropathogen Proteus mirabilis HI4320.

    PubMed

    O'May, Che; Amzallag, Olivier; Bechir, Karim; Tufenkji, Nathalie

    2016-06-01

    Proteus mirabilis is a major cause of catheter-associated urinary tract infection (CAUTI), emphasizing that novel strategies for targeting this bacterium are needed. Potential targets are P. mirabilis surface-associated swarming motility and the propensity of these bacteria to form biofilms that may lead to catheter blockage. We previously showed that the addition of cranberry powder (CP) to lysogeny broth (LB) medium resulted in impaired P. mirabilis swarming motility over short time periods (up to 16 h). Herein, we significantly expanded on those findings by exploring (i) the effects of cranberry derivatives on biofilm formation of P. mirabilis, (ii) whether swarming inhibition occurred transiently or over longer periods more relevant to real infections (∼3 days), (iii) whether swarming was also blocked by commercially available cranberry juices, (iv) whether CP or cranberry juices exhibited effects under natural urine conditions, and (v) the effects of cranberry on medium pH, which is an indirect indicator of urease activity. At short time scales (24 h), CP and commercially available pure cranberry juice impaired swarming motility and repelled actively swarming bacteria in LB medium. Over longer time periods more representative of infections (∼3 days), the capacity of the cranberry material to impair swarming diminished and bacteria would start to migrate across the surface, albeit by exhibiting a different motility phenotype to the regular "bull's-eye" swarming phenotype of P. mirabilis. This bacterium did not swarm on urine agar or LB agar supplemented with urea, suggesting that any potential application of anti-swarming compounds may be better suited to settings external to the urine environment. Anti-swarming effects were confounded by the ability of cranberry products to enhance biofilm formation in both LB and urine conditions. These findings provide key insights into the long-term strategy of targeting P. mirabilis CAUTIs.

  9. A comparative analysis of swarm intelligence techniques for feature selection in cancer classification.

    PubMed

    Gunavathi, Chellamuthu; Premalatha, Kandasamy

    2014-01-01

    Feature selection in cancer classification is a central area of research in the field of bioinformatics and used to select the informative genes from thousands of genes of the microarray. The genes are ranked based on T-statistics, signal-to-noise ratio (SNR), and F-test values. The swarm intelligence (SI) technique finds the informative genes from the top-m ranked genes. These selected genes are used for classification. In this paper the shuffled frog leaping with Lévy flight (SFLLF) is proposed for feature selection. In SFLLF, the Lévy flight is included to avoid premature convergence of shuffled frog leaping (SFL) algorithm. The SI techniques such as particle swarm optimization (PSO), cuckoo search (CS), SFL, and SFLLF are used for feature selection which identifies informative genes for classification. The k-nearest neighbour (k-NN) technique is used to classify the samples. The proposed work is applied on 10 different benchmark datasets and examined with SI techniques. The experimental results show that the results obtained from k-NN classifier through SFLLF feature selection method outperform PSO, CS, and SFL.

  10. An Energy-Aware Runtime Management of Multi-Core Sensory Swarms.

    PubMed

    Kim, Sungchan; Yang, Hoeseok

    2017-08-24

    In sensory swarms, minimizing energy consumption under performance constraint is one of the key objectives. One possible approach to this problem is to monitor application workload that is subject to change at runtime, and to adjust system configuration adaptively to satisfy the performance goal. As today's sensory swarms are usually implemented using multi-core processors with adjustable clock frequency, we propose to monitor the CPU workload periodically and adjust the task-to-core allocation or clock frequency in an energy-efficient way in response to the workload variations. In doing so, we present an online heuristic that determines the most energy-efficient adjustment that satisfies the performance requirement. The proposed method is based on a simple yet effective energy model that is built upon performance prediction using IPC (instructions per cycle) measured online and power equation derived empirically. The use of IPC accounts for memory intensities of a given workload, enabling the accurate prediction of execution time. Hence, the model allows us to rapidly and accurately estimate the effect of the two control knobs, clock frequency adjustment and core allocation. The experiments show that the proposed technique delivers considerable energy saving of up to 45%compared to the state-of-the-art multi-core energy management technique.

  11. An Energy-Aware Runtime Management of Multi-Core Sensory Swarms

    PubMed Central

    Kim, Sungchan

    2017-01-01

    In sensory swarms, minimizing energy consumption under performance constraint is one of the key objectives. One possible approach to this problem is to monitor application workload that is subject to change at runtime, and to adjust system configuration adaptively to satisfy the performance goal. As today’s sensory swarms are usually implemented using multi-core processors with adjustable clock frequency, we propose to monitor the CPU workload periodically and adjust the task-to-core allocation or clock frequency in an energy-efficient way in response to the workload variations. In doing so, we present an online heuristic that determines the most energy-efficient adjustment that satisfies the performance requirement. The proposed method is based on a simple yet effective energy model that is built upon performance prediction using IPC (instructions per cycle) measured online and power equation derived empirically. The use of IPC accounts for memory intensities of a given workload, enabling the accurate prediction of execution time. Hence, the model allows us to rapidly and accurately estimate the effect of the two control knobs, clock frequency adjustment and core allocation. The experiments show that the proposed technique delivers considerable energy saving of up to 45%compared to the state-of-the-art multi-core energy management technique. PMID:28837094

  12. Swarm Optimization-Based Magnetometer Calibration for Personal Handheld Devices

    PubMed Central

    Ali, Abdelrahman; Siddharth, Siddharth; Syed, Zainab; El-Sheimy, Naser

    2012-01-01

    Inertial Navigation Systems (INS) consist of accelerometers, gyroscopes and a processor that generates position and orientation solutions by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the user heading based on Earth's magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are usually corrupted by several errors, including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO)-based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometers. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. Furthermore, the proposed algorithm can help in the development of Pedestrian Navigation Devices (PNDs) when combined with inertial sensors and GPS/Wi-Fi for indoor navigation and Location Based Services (LBS) applications.

  13. Swarming Unmanned Aircraft Systems

    DTIC Science & Technology

    2008-09-01

    systems may become a viable part of strategy and tactics in the future. Specific to Unmanned Aircraft Sys- tems ( UAS ). they see a strong and central...system itself. They do not want to limit direct access to only Military Occupational Specialty (MOS) trained UAS operators. Rather, they feel that...Collaborating (SASC) characteristics within swarms of UAS that support operations. Technical Approach The approach taken to model this system begins with an

  14. Reconstructing the flight kinematics of swarming and mating behavior in wild mosquitoes

    USDA-ARS?s Scientific Manuscript database

    We describe a tracking system for reconstructing three-dimensional tracks of individual mosquitoes in wild swarms and present the results of validating the system by filming swarms and mating events of the malaria mosquito Anopheles gambiae in Mali. The tracking system is designed to address noisy, ...

  15. A swarm-trained k-nearest prototypes adaptive classifier with automatic feature selection for interval data.

    PubMed

    Silva Filho, Telmo M; Souza, Renata M C R; Prudêncio, Ricardo B C

    2016-08-01

    Some complex data types are capable of modeling data variability and imprecision. These data types are studied in the symbolic data analysis field. One such data type is interval data, which represents ranges of values and is more versatile than classic point data for many domains. This paper proposes a new prototype-based classifier for interval data, trained by a swarm optimization method. Our work has two main contributions: a swarm method which is capable of performing both automatic selection of features and pruning of unused prototypes and a generalized weighted squared Euclidean distance for interval data. By discarding unnecessary features and prototypes, the proposed algorithm deals with typical limitations of prototype-based methods, such as the problem of prototype initialization. The proposed distance is useful for learning classes in interval datasets with different shapes, sizes and structures. When compared to other prototype-based methods, the proposed method achieves lower error rates in both synthetic and real interval datasets. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Interaction of Electromagnetic Fields with Chondrocytes in Gel Culture

    DTIC Science & Technology

    1990-02-01

    biosynthesis due to applied electromagnetic fields. The results suggest that both normal chondrocytes and swarm rat chondrosarcoma cells in agarose Culture...and Swarm rat chondrosarcoma cells in agarose iii culture can, under proper culture conditions, continue to synthesize ma- trix macromolecules at a...cartilagc, and in rat chondrosarcoma cells (a continuous cell line). The overt gene expression of chondrocytes results in the synthesis and deposition of a

  17. Evolving and Controlling Perimeter, Rendezvous, and Foraging Behaviors in a Computation-Free Robot Swarm

    DTIC Science & Technology

    2016-04-01

    cheap, disposable swarms of robots that can accomplish these tasks quickly and with- out much human supervision. While there has been a lot of work...have shown that swarms of robots so dumb that they have no computational power–they can’t even add or subtract, and have no memory can still collec...behaviors can be achieved using swarms of computation-free robots . Our work starts with the simple robot model proposed in [6] and adds a form of

  18. Deploying swarm intelligence in medical imaging identifying metastasis, micro-calcifications and brain image segmentation.

    PubMed

    al-Rifaie, Mohammad Majid; Aber, Ahmed; Hemanth, Duraiswamy Jude

    2015-12-01

    This study proposes an umbrella deployment of swarm intelligence algorithm, such as stochastic diffusion search for medical imaging applications. After summarising the results of some previous works which shows how the algorithm assists in the identification of metastasis in bone scans and microcalcifications on mammographs, for the first time, the use of the algorithm in assessing the CT images of the aorta is demonstrated along with its performance in detecting the nasogastric tube in chest X-ray. The swarm intelligence algorithm presented in this study is adapted to address these particular tasks and its functionality is investigated by running the swarms on sample CT images and X-rays whose status have been determined by senior radiologists. In addition, a hybrid swarm intelligence-learning vector quantisation (LVQ) approach is proposed in the context of magnetic resonance (MR) brain image segmentation. The particle swarm optimisation is used to train the LVQ which eliminates the iteration-dependent nature of LVQ. The proposed methodology is used to detect the tumour regions in the abnormal MR brain images.

  19. The interhemispheric and F region dynamo currents revisited with the Swarm constellation

    NASA Astrophysics Data System (ADS)

    Lühr, Hermann; Kervalishvili, Guram; Michaelis, Ingo; Rauberg, Jan; Ritter, Patricia; Park, Jaeheung; Merayo, Jose M. G.; Brauer, Peter

    2015-05-01

    Based on magnetic field data sampled by the Swarm satellite constellation it is possible for the first time to determine uniquely F region currents at low latitudes. Initial results are presented from the first 200 days of formation flight (17 April to 5 November 2014). Detailed results have been obtained for interhemispheric field-aligned currents connecting the solar quiet day magnetic variation (Sq) current systems in the two hemispheres. We obtain prominent currents from the Southern (winter) Hemisphere to the Northern around noon. Weaker currents in opposite direction are observed during morning and evening hours. Furthermore, we could confirm the existence of vertical currents above the dip equator, downward around noon and upward around sunset. For both current systems we present and discuss longitudinal variations.

  20. Using Seismic Interferometry to Investigate Seismic Swarms

    NASA Astrophysics Data System (ADS)

    Matzel, E.; Morency, C.; Templeton, D. C.

    2017-12-01

    Seismicity provides a direct means of measuring the physical characteristics of active tectonic features such as fault zones. Hundreds of small earthquakes often occur along a fault during a seismic swarm. This seismicity helps define the tectonically active region. When processed using novel geophysical techniques, we can isolate the energy sensitive to the fault, itself. Here we focus on two methods of seismic interferometry, ambient noise correlation (ANC) and the virtual seismometer method (VSM). ANC is based on the observation that the Earth's background noise includes coherent energy, which can be recovered by observing over long time periods and allowing the incoherent energy to cancel out. The cross correlation of ambient noise between a pair of stations results in a waveform that is identical to the seismogram that would result if an impulsive source located at one of the stations was recorded at the other, the Green function (GF). The calculation of the GF is often stable after a few weeks of continuous data correlation, any perturbations to the GF after that point are directly related to changes in the subsurface and can be used for 4D monitoring.VSM is a style of seismic interferometry that provides fast, precise, high frequency estimates of the Green's function (GF) between earthquakes. VSM illuminates the subsurface precisely where the pressures are changing and has the potential to image the evolution of seismicity over time, including changes in the style of faulting. With hundreds of earthquakes, we can calculate thousands of waveforms. At the same time, VSM collapses the computational domain, often by 2-3 orders of magnitude. This allows us to do high frequency 3D modeling in the fault region. Using data from a swarm of earthquakes near the Salton Sea, we demonstrate the power of these techniques, illustrating our ability to scale from the far field, where sources are well separated, to the near field where their locations fall within each other

  1. A localized swarm of low-resource CubeSat-class spacecraft for auroral ionospheric science

    NASA Astrophysics Data System (ADS)

    Clayton, R.; Lynch, K. A.; Gayetsky, L.; Guinther, J.; Slagle, A.; Currey, S.

    2012-12-01

    In interesting and dynamic auroral ionospheric plasmas, single-point in situ measurements are insufficient. Changes in measurements recorded from a single probe can be ascribed to either changes in position or to changes over time, and gradient scales can only be inferred. A localized array of sensors deployed as a low-resource swarm from a main deployer, can address these issues. We consider two aspects of designing such a swarm: (a) maintaining the localization in a low-cost manner, and (b) creating an extremely low-resource spacecraft by taking advantage of commercially available technologies. For a few-week low-altitude mission, STK (SatelliteToolKit) studies show that with proper deployment, an array of CubeSat-class spacecraft near 350 km altitude can regroup once per orbit to within a few 10s of km. Kepler's laws and Hill's equations allow us to put constraints on the capability of the deployer needed, in order to deploy the array with a minimal component of the ejection velocity along the orbital track. In order to keep the cost of each spacecraft low, we are exploring commercially available technologies such as Arduino controllers and video-game sensors. The Arduino on each payload will take in information from the sensors on the payload, and will send the information to a DNT-900MHz local area communications system. We show an example experiment measuring river flows on the Connecticut river, and discuss the design of our payload swarm.

  2. Anaerobic Respiration Using a Complete Oxidative TCA Cycle Drives Multicellular Swarming in Proteus mirabilis

    PubMed Central

    Alteri, Christopher J.; Himpsl, Stephanie D.; Engstrom, Michael D.; Mobley, Harry L. T.

    2012-01-01

    ABSTRACT Proteus mirabilis rapidly migrates across surfaces using a periodic developmental process of differentiation alternating between short swimmer cells and elongated hyperflagellated swarmer cells. To undergo this vigorous flagellum-mediated motility, bacteria must generate a substantial proton gradient across their cytoplasmic membranes by using available energy pathways. We sought to identify the link between energy pathways and swarming differentiation by examining the behavior of defined central metabolism mutants. Mutations in the tricarboxylic acid (TCA) cycle (fumC and sdhB mutants) caused altered patterns of swarming periodicity, suggesting an aerobic pathway. Surprisingly, the wild-type strain swarmed on agar containing sodium azide, which poisons aerobic respiration; the fumC TCA cycle mutant, however, was unable to swarm on azide. To identify other contributing energy pathways, we screened transposon mutants for loss of swarming on sodium azide and found insertions in the following genes that involved fumarate metabolism or respiration: hybB, encoding hydrogenase; fumC, encoding fumarase; argH, encoding argininosuccinate lyase (generates fumarate); and a quinone hydroxylase gene. These findings validated the screen and suggested involvement of anaerobic electron transport chain components. Abnormal swarming periodicity of fumC and sdhB mutants was associated with the excretion of reduced acidic fermentation end products. Bacteria lacking SdhB were rescued to wild-type pH and periodicity by providing fumarate, independent of carbon source but dependent on oxygen, while fumC mutants were rescued by glycerol, independent of fumarate only under anaerobic conditions. These findings link multicellular swarming patterns with fumarate metabolism and membrane electron transport using a previously unappreciated configuration of both aerobic and anaerobic respiratory chain components. PMID:23111869

  3. Interaction of Electromagnetic Fields with Biosynthetic Processes in Connective Tissue Cells

    DTIC Science & Technology

    1989-12-01

    Normal Chondrocytes.............................................10 Swarm Rat Chondrosarcoma Cells..................................15 Conclusions...articular cartilage, and in rat chondrosarcoma cells (a continuous cell line). Another long-term goal is to study the possible role of fields in...Investigators have recently found that bovine [12, 13, 14], rabbit [15], and human [161 chondrocytes as well as Swarm rat chondrosarcoma cells [171 isolated a

  4. Machining fixture layout optimization using particle swarm optimization algorithm

    NASA Astrophysics Data System (ADS)

    Dou, Jianping; Wang, Xingsong; Wang, Lei

    2011-05-01

    Optimization of fixture layout (locator and clamp locations) is critical to reduce geometric error of the workpiece during machining process. In this paper, the application of particle swarm optimization (PSO) algorithm is presented to minimize the workpiece deformation in the machining region. A PSO based approach is developed to optimize fixture layout through integrating ANSYS parametric design language (APDL) of finite element analysis to compute the objective function for a given fixture layout. Particle library approach is used to decrease the total computation time. The computational experiment of 2D case shows that the numbers of function evaluations are decreased about 96%. Case study illustrates the effectiveness and efficiency of the PSO based optimization approach.

  5. A Comparison of Swarm Cross-Track Ion-Drifts and SuperDARN Line-of-Sight Velocities

    NASA Astrophysics Data System (ADS)

    Koustov, A. V.; Lavoie, D. B.; Kouznetsov, A.; Burchill, J. K.; Knudsen, D. J.

    2017-12-01

    Cross-track ion drifts measured by the Swarm-A satellite are compared with line-of-sight SuperDARN HF velocities in approximately the same directions. More than 200 Swarm-A passes over four polar cap SuperDARN radars in the northern and southern hemispheres are considered. Overall, the radar velocities are found to be smaller than the Swarm-derived velocities with the slope of the best linear fit line on the order of 0.5. Such relationship is in effect only for points with good quality of measurements by both instruments. In a number of cases, disagreements not only in the magnitude but also in the direction of the velocity are found. Potential reasons for disagreements are discussed. The comparison implies that Swarm cross-track velocity data are often compatible with those from SuperDARN radars and thus can be used for research. However, a careful examination of each piece of Swarm data is still highly desirable.

  6. Earthquake swarm in the non-volcanic area north of Harrat Lunayyir, western Saudi Arabia: observations and imaging

    NASA Astrophysics Data System (ADS)

    Youssof, M.; Mai, P. M.; Parisi, L.; Tang, Z.; Zahran, H. M.; El-Hadidy, S. Y.; Al-Raddadi, W.; Sami, M.; El-Hadidy, M. S. Y.

    2017-12-01

    We report on an unusual earthquake swarm in a non-volcanic area of western Saudi Arabia. Since March 2017, hundreds of earthquakes were recorded, reaching magnitude Ml 3.7, which occurred within a very narrowly defined rock volume. The seismicity is shallow, mostly between 4 to 8 km depths, with some events reaching as deep as 16 km. One set of events aligns into a well-defined horizontal tube of 2 km height, 1 km width, and 4-5 km E-W extent. Other event clusters exist, but are less well-defined. The focal mechanism solutions of the largest earthquakes indicate normal faulting, which agree with the regional stress field. The earthquake swarm occurs 75 km NW of Harrat Lunayyir. However, the area of interest doesn't seem to be associated with the well-known volcanic area of Harrat Lunayyir, which experienced a magmatic dike intrusion in 2009 with intense seismic activity (including a surface rupturing Mw 5.7 earthquake). Furthermore, the study area is characterized by a complex shear system, which host gold mineralization. Therefore, the exact origin of the swarm sequence is enigmatic as it's the first of its kind in this region. By using continuous seismological data recorded by the Saudi Geological Survey (SGS) that operates three permanent seismic stations and a temporary network of 11 broadband sensors, we analyze the seismic patterns in space and time. For the verified detected events, we assemble the body wave arrival times that are inverted for the velocity structures along with events hypocenters to investigate possible causes of this swarm sequence, that is, whether the activity is of tectonic- or hydro-thermal origin.

  7. A new inertia weight control strategy for particle swarm optimization

    NASA Astrophysics Data System (ADS)

    Zhu, Xianming; Wang, Hongbo

    2018-04-01

    Particle Swarm Optimization is a member of swarm intelligence algorithms, which is inspired by the behavior of bird flocks. The inertia weight, one of the most important parameters of PSO, is crucial for PSO, for it balances the performance of exploration and exploitation of the algorithm. This paper proposes a new inertia weight control strategy and PSO with this new strategy is tested by four benchmark functions. The results shows that the new strategy provides the PSO with better performance.

  8. Initiation of Swarming Motility by Proteus mirabilis Occurs in Response to Specific Cues Present in Urine and Requires Excess l-Glutamine

    PubMed Central

    Armbruster, Chelsie E.; Hodges, Steven A.

    2013-01-01

    Proteus mirabilis, a leading cause of catheter-associated urinary tract infection (CaUTI), differentiates into swarm cells that migrate across catheter surfaces and medium solidified with 1.5% agar. While many genes and nutrient requirements involved in the swarming process have been identified, few studies have addressed the signals that promote initiation of swarming following initial contact with a surface. In this study, we show that P. mirabilis CaUTI isolates initiate swarming in response to specific nutrients and environmental cues. Thirty-three compounds, including amino acids, polyamines, fatty acids, and tricarboxylic acid (TCA) cycle intermediates, were tested for the ability to promote swarming when added to normally nonpermissive media. l-Arginine, l-glutamine, dl-histidine, malate, and dl-ornithine promoted swarming on several types of media without enhancing swimming motility or growth rate. Testing of isogenic mutants revealed that swarming in response to the cues required putrescine biosynthesis and pathways involved in amino acid metabolism. Furthermore, excess glutamine was found to be a strict requirement for swarming on normal swarm agar in addition to being a swarming cue under normally nonpermissive conditions. We thus conclude that initiation of swarming occurs in response to specific cues and that manipulating concentrations of key nutrient cues can signal whether or not a particular environment is permissive for swarming. PMID:23316040

  9. Smart Swarms of Bacteria-Inspired Agents with Performance Adaptable Interactions

    PubMed Central

    Shklarsh, Adi; Ariel, Gil; Schneidman, Elad; Ben-Jacob, Eshel

    2011-01-01

    Collective navigation and swarming have been studied in animal groups, such as fish schools, bird flocks, bacteria, and slime molds. Computer modeling has shown that collective behavior of simple agents can result from simple interactions between the agents, which include short range repulsion, intermediate range alignment, and long range attraction. Here we study collective navigation of bacteria-inspired smart agents in complex terrains, with adaptive interactions that depend on performance. More specifically, each agent adjusts its interactions with the other agents according to its local environment – by decreasing the peers' influence while navigating in a beneficial direction, and increasing it otherwise. We show that inclusion of such performance dependent adaptable interactions significantly improves the collective swarming performance, leading to highly efficient navigation, especially in complex terrains. Notably, to afford such adaptable interactions, each modeled agent requires only simple computational capabilities with short-term memory, which can easily be implemented in simple swarming robots. PMID:21980274

  10. Smart swarms of bacteria-inspired agents with performance adaptable interactions.

    PubMed

    Shklarsh, Adi; Ariel, Gil; Schneidman, Elad; Ben-Jacob, Eshel

    2011-09-01

    Collective navigation and swarming have been studied in animal groups, such as fish schools, bird flocks, bacteria, and slime molds. Computer modeling has shown that collective behavior of simple agents can result from simple interactions between the agents, which include short range repulsion, intermediate range alignment, and long range attraction. Here we study collective navigation of bacteria-inspired smart agents in complex terrains, with adaptive interactions that depend on performance. More specifically, each agent adjusts its interactions with the other agents according to its local environment--by decreasing the peers' influence while navigating in a beneficial direction, and increasing it otherwise. We show that inclusion of such performance dependent adaptable interactions significantly improves the collective swarming performance, leading to highly efficient navigation, especially in complex terrains. Notably, to afford such adaptable interactions, each modeled agent requires only simple computational capabilities with short-term memory, which can easily be implemented in simple swarming robots.

  11. Swarming in viscous fluids: three-dimensional patterns in swimmer- and force-induced flows

    NASA Astrophysics Data System (ADS)

    Chuang, Yao-Li; D'Orsogna, Maria R.; Chou, Tom

    Mathematical models of self-propelled interacting particles have reproduced various fascinating ``swarming'' patterns observed in natural and artificial systems. The formulation of such models usually ignores the influence of the surrounding medium in which the particles swarm. Here we develop from first principles a three-dimensional theory of swarming particles in a viscous fluid environment and investigate how the hydrodynamic coupling among the particles may affect their collective behavior. Specifically, we examine the hydrodynamic coupling among self-propelled particles interacting through ``social'' or ``mechanical'' forces. We discover that new patterns arise as a consequence of different interactions and self-propulsion mechanisms. Examples include flocks with prolate or oblate shapes, intermittent mills, recirculating peloton-like structures, and jet-like fluid flows that kinetically destabilize mill-like structures. Our results reveal possible mechanisms for three-dimensional swarms to kinetically control their collective behaviors in fluids. Supported by NSF DMS 1021818 & 1021850, ARO W1911NF-14-1-0472, ARO MURI W1911NF-11-10332.

  12. PSOVina: The hybrid particle swarm optimization algorithm for protein-ligand docking.

    PubMed

    Ng, Marcus C K; Fong, Simon; Siu, Shirley W I

    2015-06-01

    Protein-ligand docking is an essential step in modern drug discovery process. The challenge here is to accurately predict and efficiently optimize the position and orientation of ligands in the binding pocket of a target protein. In this paper, we present a new method called PSOVina which combined the particle swarm optimization (PSO) algorithm with the efficient Broyden-Fletcher-Goldfarb-Shannon (BFGS) local search method adopted in AutoDock Vina to tackle the conformational search problem in docking. Using a diverse data set of 201 protein-ligand complexes from the PDBbind database and a full set of ligands and decoys for four representative targets from the directory of useful decoys (DUD) virtual screening data set, we assessed the docking performance of PSOVina in comparison to the original Vina program. Our results showed that PSOVina achieves a remarkable execution time reduction of 51-60% without compromising the prediction accuracies in the docking and virtual screening experiments. This improvement in time efficiency makes PSOVina a better choice of a docking tool in large-scale protein-ligand docking applications. Our work lays the foundation for the future development of swarm-based algorithms in molecular docking programs. PSOVina is freely available to non-commercial users at http://cbbio.cis.umac.mo .

  13. Diagnosing the Role of Alfvén Waves in Magnetosphere-Ionosphere Coupling: Swarm Observations of Large Amplitude Nonstationary Magnetic Perturbations During an Interval of Northward IMF

    NASA Astrophysics Data System (ADS)

    Pakhotin, I. P.; Mann, I. R.; Lysak, R. L.; Knudsen, D. J.; Gjerloev, J. W.; Rae, I. J.; Forsyth, C.; Murphy, K. R.; Miles, D. M.; Ozeke, L. G.; Balasis, G.

    2018-01-01

    High-resolution multispacecraft Swarm data are used to examine magnetosphere-ionosphere coupling during a period of northward interplanetary magnetic field (IMF) on 31 May 2014. The observations reveal a prevalence of unexpectedly large amplitude (>100 nT) and time-varying magnetic perturbations during the polar passes, with especially large amplitude magnetic perturbations being associated with large-scale downward field-aligned currents. Differences between the magnetic field measurements sampled at 50 Hz from Swarm A and C, approximately 10 s apart along track, and the correspondence between the observed electric and magnetic fields at 16 samples per second, provide significant evidence for an important role for Alfvén waves in magnetosphere-ionosphere coupling even during northward IMF conditions. Spectral comparison between the wave E- and B-fields reveals a frequency-dependent phase difference and amplitude ratio consistent with interference between incident and reflected Alfvén waves. At low frequencies, the E/B ratio is in phase with an amplitude determined by the Pedersen conductance. At higher frequencies, the amplitude and phase change as a function of frequency in good agreement with an ionospheric Alfvén resonator model including Pedersen conductance effects. Indeed, within this Alfvén wave incidence, reflection, and interference paradigm, even quasi-static field-aligned currents might be reasonably interpreted as very low frequency (ω → 0) Alfvén waves. Overall, our results not only indicate the importance of Alfvén waves for magnetosphere-ionosphere coupling but also demonstrate a method for using Swarm data for the innovative experimental diagnosis of Pedersen conductance from low-Earth orbit satellite measurements.

  14. Firefly as a novel swarm intelligence variable selection method in spectroscopy.

    PubMed

    Goodarzi, Mohammad; dos Santos Coelho, Leandro

    2014-12-10

    A critical step in multivariate calibration is wavelength selection, which is used to build models with better prediction performance when applied to spectral data. Up to now, many feature selection techniques have been developed. Among all different types of feature selection techniques, those based on swarm intelligence optimization methodologies are more interesting since they are usually simulated based on animal and insect life behavior to, e.g., find the shortest path between a food source and their nests. This decision is made by a crowd, leading to a more robust model with less falling in local minima during the optimization cycle. This paper represents a novel feature selection approach to the selection of spectroscopic data, leading to more robust calibration models. The performance of the firefly algorithm, a swarm intelligence paradigm, was evaluated and compared with genetic algorithm and particle swarm optimization. All three techniques were coupled with partial least squares (PLS) and applied to three spectroscopic data sets. They demonstrate improved prediction results in comparison to when only a PLS model was built using all wavelengths. Results show that firefly algorithm as a novel swarm paradigm leads to a lower number of selected wavelengths while the prediction performance of built PLS stays the same. Copyright © 2014. Published by Elsevier B.V.

  15. Reconstructing the flight kinematics of swarming and mating in wild mosquitoes

    PubMed Central

    Butail, Sachit; Manoukis, Nicholas; Diallo, Moussa; Ribeiro, José M.; Lehmann, Tovi; Paley, Derek A.

    2012-01-01

    We describe a novel tracking system for reconstructing three-dimensional tracks of individual mosquitoes in wild swarms and present the results of validating the system by filming swarms and mating events of the malaria mosquito Anopheles gambiae in Mali. The tracking system is designed to address noisy, low frame-rate (25 frames per second) video streams from a stereo camera system. Because flying A. gambiae move at 1–4 m s−1, they appear as faded streaks in the images or sometimes do not appear at all. We provide an adaptive algorithm to search for missing streaks and a likelihood function that uses streak endpoints to extract velocity information. A modified multi-hypothesis tracker probabilistically addresses occlusions and a particle filter estimates the trajectories. The output of the tracking algorithm is a set of track segments with an average length of 0.6–1 s. The segments are verified and combined under human supervision to create individual tracks up to the duration of the video (90 s). We evaluate tracking performance using an established metric for multi-target tracking and validate the accuracy using independent stereo measurements of a single swarm. Three-dimensional reconstructions of A. gambiae swarming and mating events are presented. PMID:22628212

  16. Han's model parameters for microalgae grown under intermittent illumination: Determined using particle swarm optimization.

    PubMed

    Pozzobon, Victor; Perre, Patrick

    2018-01-21

    This work provides a model and the associated set of parameters allowing for microalgae population growth computation under intermittent lightning. Han's model is coupled with a simple microalgae growth model to yield a relationship between illumination and population growth. The model parameters were obtained by fitting a dataset available in literature using Particle Swarm Optimization method. In their work, authors grew microalgae in excess of nutrients under flashing conditions. Light/dark cycles used for these experimentations are quite close to those found in photobioreactor, i.e. ranging from several seconds to one minute. In this work, in addition to producing the set of parameters, Particle Swarm Optimization robustness was assessed. To do so, two different swarm initialization techniques were used, i.e. uniform and random distribution throughout the search-space. Both yielded the same results. In addition, swarm distribution analysis reveals that the swarm converges to a unique minimum. Thus, the produced set of parameters can be trustfully used to link light intensity to population growth rate. Furthermore, the set is capable to describe photodamages effects on population growth. Hence, accounting for light overexposure effect on algal growth. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Performance Review of Harmony Search, Differential Evolution and Particle Swarm Optimization

    NASA Astrophysics Data System (ADS)

    Mohan Pandey, Hari

    2017-08-01

    Metaheuristic algorithms are effective in the design of an intelligent system. These algorithms are widely applied to solve complex optimization problems, including image processing, big data analytics, language processing, pattern recognition and others. This paper presents a performance comparison of three meta-heuristic algorithms, namely Harmony Search, Differential Evolution, and Particle Swarm Optimization. These algorithms are originated altogether from different fields of meta-heuristics yet share a common objective. The standard benchmark functions are used for the simulation. Statistical tests are conducted to derive a conclusion on the performance. The key motivation to conduct this research is to categorize the computational capabilities, which might be useful to the researchers.

  18. Swarm Tactics and the Doctrinal Void: Lessons from the Chechen Wars

    DTIC Science & Technology

    2008-06-01

    classify as a vapor swarm, the Finnish guerrillas “Using their quick-firing Suomi submachine guns, the skiers appeared out of nowhere, poured a...our knowledge that we hope to answer, provide a departure point for further existing work, and set the foundation for analysis and validation of the...scholarly literature on the Soviet Afghan War, three works stand out as contributing to our body of knowledge on swarming. Tactics of the Crescent

  19. Confidential and Authenticated Communications in a Large Fixed-Wing UAV Swarm

    DTIC Science & Technology

    2016-12-01

    either a UAV or a ground station. Asymmetric cryptography is not an option for swarm communications. It is a potential option for initially keying or...each UAV grows ten bytes for each UAV in the swarm, and a 30% overhead is added on for worst case cryptography . The resulting throughput is...analysis in Section IV, we can predict the burden that cryptography places on the ODroid computer. Given that the average unencrypted message size was

  20. Particle swarm optimization algorithm based low cost magnetometer calibration

    NASA Astrophysics Data System (ADS)

    Ali, A. S.; Siddharth, S., Syed, Z., El-Sheimy, N.

    2011-12-01

    Inertial Navigation Systems (INS) consist of accelerometers, gyroscopes and a microprocessor provide inertial digital data from which position and orientation is obtained by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the absolute user heading based on Earth's magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are corrupted by several errors including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO) based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometer. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. The estimated bias and scale factor errors from the proposed algorithm improve the heading accuracy and the results are also statistically significant. Also, it can help in the development of the Pedestrian Navigation Devices (PNDs) when combined with the INS and GPS/Wi-Fi especially in the indoor environments

  1. Collective motion of predictive swarms

    PubMed Central

    Vural, Dervis Can

    2017-01-01

    Theoretical models of populations and swarms typically start with the assumption that the motion of agents is governed by the local stimuli. However, an intelligent agent, with some understanding of the laws that govern its habitat, can anticipate the future, and make predictions to gather resources more efficiently. Here we study a specific model of this kind, where agents aim to maximize their consumption of a diffusing resource, by attempting to predict the future of a resource field and the actions of other agents. Once the agents make a prediction, they are attracted to move towards regions that have, and will have, denser resources. We find that the further the agents attempt to see into the future, the more their attempts at prediction fail, and the less resources they consume. We also study the case where predictive agents compete against non-predictive agents and find the predictors perform better than the non-predictors only when their relative numbers are very small. We conclude that predictivity pays off either when the predictors do not see too far into the future or the number of predictors is small. PMID:29065136

  2. Collective motion of predictive swarms.

    PubMed

    Rupprecht, Nathaniel; Vural, Dervis Can

    2017-01-01

    Theoretical models of populations and swarms typically start with the assumption that the motion of agents is governed by the local stimuli. However, an intelligent agent, with some understanding of the laws that govern its habitat, can anticipate the future, and make predictions to gather resources more efficiently. Here we study a specific model of this kind, where agents aim to maximize their consumption of a diffusing resource, by attempting to predict the future of a resource field and the actions of other agents. Once the agents make a prediction, they are attracted to move towards regions that have, and will have, denser resources. We find that the further the agents attempt to see into the future, the more their attempts at prediction fail, and the less resources they consume. We also study the case where predictive agents compete against non-predictive agents and find the predictors perform better than the non-predictors only when their relative numbers are very small. We conclude that predictivity pays off either when the predictors do not see too far into the future or the number of predictors is small.

  3. Intrinsic Fluctuations and Driven Response of Insect Swarms

    NASA Astrophysics Data System (ADS)

    Ni, Rui; Puckett, James G.; Dufresne, Eric R.; Ouellette, Nicholas T.

    2015-09-01

    Animals of all sizes form groups, as acting together can convey advantages over acting alone; thus, collective animal behavior has been identified as a promising template for designing engineered systems. However, models and observations have focused predominantly on characterizing the overall group morphology, and often focus on highly ordered groups such as bird flocks. We instead study a disorganized aggregation (an insect mating swarm), and compare its natural fluctuations with the group-level response to an external stimulus. We quantify the swarm's frequency-dependent linear response and its spectrum of intrinsic fluctuations, and show that the ratio of these two quantities has a simple scaling with frequency. Our results provide a new way of comparing models of collective behavior with experimental data.

  4. Swarm intelligence in humans: A perspective of emergent evolution

    NASA Astrophysics Data System (ADS)

    Tao, Yong

    2018-07-01

    The origin of intelligence has fascinated scientists for a long time. Over the past 100 years, many scholars have observed the connection between entropy and intelligence. In the present study, we investigated a potential origin of the swarm intelligence in humans. The present study shows that a competitive economy consisting of a large number of self-interested agents can be mapped to a Boltzmann-like system, where entropy and energy play roles of swarm intelligence and income, respectively. However, different from the physical entropy in the Boltzmann system, the entropy (or swarm intelligence) in the economic system is a self-referential variable, which may be a key characteristic for distinguishing between biological and physical systems. Furthermore, we employ the household income data from 66 countries and Hong Kong SAR to test the validity of the Boltzmann-like distribution. Remarkably, the empirical data are perfectly consistent with the theoretical results. This finding implies that the competitive behaviors among a colony of self-interested agents will spontaneously prompt the colony to evolve to a state of higher technological level, although each agent has no willingness to evolve.

  5. Designing Artificial Neural Networks Using Particle Swarm Optimization Algorithms

    PubMed Central

    Vázquez, Roberto A.

    2015-01-01

    Artificial Neural Network (ANN) design is a complex task because its performance depends on the architecture, the selected transfer function, and the learning algorithm used to train the set of synaptic weights. In this paper we present a methodology that automatically designs an ANN using particle swarm optimization algorithms such as Basic Particle Swarm Optimization (PSO), Second Generation of Particle Swarm Optimization (SGPSO), and a New Model of PSO called NMPSO. The aim of these algorithms is to evolve, at the same time, the three principal components of an ANN: the set of synaptic weights, the connections or architecture, and the transfer functions for each neuron. Eight different fitness functions were proposed to evaluate the fitness of each solution and find the best design. These functions are based on the mean square error (MSE) and the classification error (CER) and implement a strategy to avoid overtraining and to reduce the number of connections in the ANN. In addition, the ANN designed with the proposed methodology is compared with those designed manually using the well-known Back-Propagation and Levenberg-Marquardt Learning Algorithms. Finally, the accuracy of the method is tested with different nonlinear pattern classification problems. PMID:26221132

  6. Identifying Interacting Genetic Variations by Fish-Swarm Logic Regression

    PubMed Central

    Yang, Aiyuan; Yan, Chunxia; Zhu, Feng; Zhao, Zhongmeng; Cao, Zhi

    2013-01-01

    Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR) is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR), which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds. PMID:23984382

  7. How Honey Bee Colonies Survive in the Wild: Testing the Importance of Small Nests and Frequent Swarming

    PubMed Central

    Loftus, J. Carter; Smith, Michael L.; Seeley, Thomas D.

    2016-01-01

    The ectoparasitic mite, Varroa destructor, and the viruses that it transmits, kill the colonies of European honey bees (Apis mellifera) kept by beekeepers unless the bees are treated with miticides. Nevertheless, there exist populations of wild colonies of European honey bees that are persisting without being treated with miticides. We hypothesized that the persistence of these wild colonies is due in part to their habits of nesting in small cavities and swarming frequently. We tested this hypothesis by establishing two groups of colonies living either in small hives (42 L) without swarm-control treatments or in large hives (up to 168 L) with swarm-control treatments. We followed the colonies for two years and compared the two groups with respect to swarming frequency, Varroa infesttion rate, disease incidence, and colony survival. Colonies in small hives swarmed more often, had lower Varroa infestation rates, had less disease, and had higher survival compared to colonies in large hives. These results indicate that the smaller nest cavities and more frequent swarming of wild colonies contribute to their persistence without mite treatments. PMID:26968000

  8. Swarm intelligence metaheuristics for enhanced data analysis and optimization.

    PubMed

    Hanrahan, Grady

    2011-09-21

    The swarm intelligence (SI) computing paradigm has proven itself as a comprehensive means of solving complicated analytical chemistry problems by emulating biologically-inspired processes. As global optimum search metaheuristics, associated algorithms have been widely used in training neural networks, function optimization, prediction and classification, and in a variety of process-based analytical applications. The goal of this review is to provide readers with critical insight into the utility of swarm intelligence tools as methods for solving complex chemical problems. Consideration will be given to algorithm development, ease of implementation and model performance, detailing subsequent influences on a number of application areas in the analytical, bioanalytical and detection sciences.

  9. Fractal analysis of earthquake swarms of Vogtland/NW-Bohemia intraplate seismicity

    NASA Astrophysics Data System (ADS)

    Mittag, Reinhard J.

    2003-03-01

    The special type of intraplate microseismicity with swarm-like occurrence of earthquakes within the Vogtland/NW-Bohemian Region is analysed to reveal the nature and the origin of the seismogenic regime. The long-term data set of continuous seismic monitoring since 1962, including more than 26000 events within a range of about 5 units of local magnitude, provides an unique database for statistical investigations. Most earthquakes occur in narrow hypocentral volumes (clusters) within the lower part of the upper crust, but also single event occurrence outside of spatial clusters is observed. Temporal distribution of events is concentrated in clusters (swarms), which last some days until few month in dependence of intensity. Since 1962 three strong swarms occurred (1962, 1985/86, 2000), including two seismic cycles. Spatial clusters are distributed along a fault system of regional extension (Leipzig-Regensburger Störung), which is supposed to act as the joint tectonic fracture zone for the whole seismogenic region. Seismicity is analysed by fractal analysis, suggesting a unifractal behaviour of seismicity and uniform character of seismotectonic regime for the whole region. A tendency of decreasing fractal dimension values is observed for temporal distribution of earthquakes, indicating an increasing degree of temporal clustering from swarm to swarm. Following the idea of earthquake triggering by magma intrusions and related fluid and gas release into the tectonically pre-stressed parts of the crust, a steady increased intensity of intrusion and/or fluid and gas release might account for that observation. Additionally, seismic parameters for Vogtland/NW-Bohemia intraplate seismicity are compared with an adequate data set of mining-induced seismicity in a nearby mine of Lubin/Poland and with synthetic data sets to evaluate parameter estimation. Due to different seismogenic regime of tectonic and induced seismicity, significant differences between b-values and temporal

  10. Investigation of an earthquake swarm near Trinidad, Colorado, August-October 2001

    USGS Publications Warehouse

    Meremonte, Mark E.; Lahr, John C.; Frankel, Arthur D.; Dewey, James W.; Crone, Anthony J.; Overturf, Dee E.; Carver, David L.; Bice., W. Thomas

    2002-01-01

    A swarm of 12 widely felt earthquakes occurred between August 28 and September 21, 2001, in the area west of the town of Trinidad, Colorado. The earthquakes ranged in magnitude between 2.8 and 4.6, and the largest event occurred on September 5, eight days after the initial M 3.4 event. The nearest permanent seismograph station to the swarm is about 290 km away, resulting in large uncertainties in the location and depth of these events. To better locate and characterize the earthquakes in this swarm, we deployed a total of 12 portable seismographs in the area of the swarm starting on September 6. Here we report on data from this portable network that was recorded between September 7 and October 15. During this time period, we have high-quality data from 39 earthquakes. The hypocenters of these earthquakes cluster to define a 6 km long northeast-trending fault plane that dips steeply (70-80?) to the southeast. The upper bound of well-constrained hypocenters is near 3 km depth and lower bound is near 6 km depth. Preliminary fault mechanisms suggest normal faulting with movement down to the southeast. Significant historical earthquakes have occurred in the Trinidad region in 1966 and 1973. Reexamination of felt reports from these earthquakes suggest that the 1973 events may have occurred in the same area, and possibly on the same fault, as the 2001 swarm. In recent years, a large volume of excess water that is produced in conjunction with coal-bed methane gas production has been returned to the subsurface in fluid disposal wells in the area of the earthquake swarm. Because of the proximity of these disposal wells to the earthquakes, local residents and officials are concerned that the fluid disposal might have triggered the earthquakes. We have evaluated the characteristics of the seismicity using criteria proposed by Davis and Frohlich (1993) as diagnostic of seismicity induced by fluid injection. We conclude that the characteristics of the seismicity and the fluid

  11. Tree-ring 14C links seismic swarm to CO2 spike at Yellowstone, USA

    USGS Publications Warehouse

    Evans, William C.; Bergfeld, D.; McGeehin, J.P.; King, J.C.; Heasler, H.

    2010-01-01

    Mechanisms to explain swarms of shallow seismicity and inflation-deflation cycles at Yellowstone caldera (western United States) commonly invoke episodic escape of magma-derived brines or gases from the ductile zone, but no correlative changes in the surface efflux of magmatic constituents have ever been documented. Our analysis of individual growth rings in a tree core from the Mud Volcano thermal area within the caldera links a sharp ~25% drop in 14C to a local seismic swarm in 1978. The implied fivefold increase in CO2 emissions clearly associates swarm seismicity with upflow of magma-derived fluid and shows that pulses of magmatic CO2 can rapidly traverse the 5-kmthick brittle zone, even through Yellowstone's enormous hydrothermal reservoir. The 1978 event predates annual deformation surveys, but recognized connections between subsequent seismic swarms and changes in deformation suggest that CO2 might drive both processes. ?? 2010 Geological Society of America.

  12. Earthquake Swarm Along the San Andreas Fault near Palmdale, Southern California, 1976 to 1977.

    PubMed

    McNally, K C; Kanamori, H; Pechmann, J C; Fuis, G

    1978-09-01

    Between November 1976 and November 1977 a swarm of small earthquakes (local magnitude swarm was the first observed along this section of the San Andreas since cataloging of instrumental data began in 1932. The activity followed partial subsidence of the 35-centimeter vertical crustal uplift known as the Palmdale bulge along this "locked" section of the San Andreas, which last broke in the great (surface-wave magnitude = 8(1/4)+) 1857 Fort Tejon earthquake. The swarm events exhibit characteristics previously observed for some foreshock sequences, such as tight clustering of hypocenters and time-dependent rotations of stress axes inferred from focal mechanisms. However, because of our present lack of understanding of the processes that precede earthquake faulting, the implications of the swarm for future large earthquakes on the San Andreas fault are unknown.

  13. Earthquake swarm along the San Andreas fault near Palmdale, Southern California, 1976 to 1977

    USGS Publications Warehouse

    Mcnally, K.C.; Kanamori, H.; Pechmann, J.C.; Fuis, G.

    1978-01-01

    Between November 1976 and November 1977 a swarm of small earthquakes (local magnitude ??? 3) occurred on or near the San Andreas fault near Palmdale, California. This swarm was the first observed along this section of the San Andreas since cataloging of instrumental data began in 1932. The activity followed partial subsidence of the 35-centimeter vertical crustal uplift known as the Palmdale bulge along this "locked" section of the San Andreas, which last broke in the great (surface-wave magnitude = 81/4+) 1857 Fort Tejon earthquake. The swarm events exhibit characteristics previously observed for some foreshock sequences, such as tight clustering of hypocenters and time-dependent rotations of stress axes inferred from focal mechanisms. However, because of our present lack of understanding of the processes that precede earthquake faulting, the implications of the swarm for future large earthquakes on the San Andreas fault are unknown. Copyright ?? 1978 AAAS.

  14. Volcanic outcrops of southeast Ethiopia and the Ogaden Dyke Swarm

    NASA Astrophysics Data System (ADS)

    Mège, Daniel; Purcell, Peter; Jourdan, Fred; Pochat, Stéphane

    2013-04-01

    A new map of Tertiary volcanics occurrences in the Ogaden region of southeast Ethiopia and adjacent areas of Somalia has been prepared. Outcrop areas, mapped using satellite images and helicopter-­-supported field work in 2008, are more widespread than previously recognized, while magnetic and drill data reveal the vast subsurface extent of the magmatism. Several spectacular 'meandering' outcrops, over 100 km long, are undoubtedly exhumed canyon-­-filling flows and magnetic data show that many other apparently isolated outcrops are actually part of similar flows, the bulk of which are now subsurface. Age dating and well intersections show several volcanic episodes, with the major outpouring occurring across a broad peneplain in the Oligocene. Geological and aeromagnetic mapping, and 40Ar/39Ar age dating, reveal a dyke swarm extending SSE from the southern Afar margin more than 600 km across the Somali Plate, and coeval with dyke injection in the Red Sea rift at ~25 Ma. The Ogaden Dyke Swarm, which occurs in an area historically considered remote from the impact of the Afro-­-Arabian rifting and volcanism, appears associated with the Marda Fault and marks a zone of crustal dilation along the Red Sea trend across the Horn of Africa. Contemporaneous rifts, also trending WNW/ESE and over 120 km long, occur in NE Somalia, confirming the predominantly NE/SW-­-directed crustal stress regime in the Ogaden and adjacent region at this time.

  15. Geodynamic Setting of Proterozoic Dyke Swarms of the Leo-Man Craton, West Africa, Based on New U-Pb Dating and Geochemistry

    NASA Astrophysics Data System (ADS)

    Baratoux, L.; Jessell, M.; Söderlund, U.; Ernst, R. E.; Benoit, M.; Naba, S.; Cournede, C.; Perrouty, S.; Metelka, V.; Yatte, D.; Diallo, D. P.; Ndiaye, P. M.; Dioh, E.; Baratoux, D.

    2016-12-01

    Over 20 sets of dolerite dykes crosscutting Paleoproterozoic basement in West Africa were distinguished via the interpretation of regional and high-resolution airborne magnetic data available over the West African Craton. Some of the dykes reach over 300 km in length and are considered parts of much larger systems of mafic dyke swarms which form the plumbing system of Large Igneous Provinces (LIPs). Five different dyke swarms in Burkina Faso, Niger, Ghana and Senegal were investigated. In terms of petrography and composition, the mafic dykes correspond to tholeiitic basalts and are typically composed of plagioclase + clinopyroxene ± orthopyroxene ± olivine. They display a doleritic texture of variable grain size. Eleven ID-TIMS U-Pb ages obtained on baddeleyite define five generations of Proterozoic age. The N10 Libiri dyke swarm, found in western Niger, yielded an age of ca. 1790 Ma. The N40 Bassari swarm in Senegal was dated at ca. 1764 Ma, and is potentially linked to the 1790 Ma Libiri swarm, 1400 km away. The 300 by 400 km Korsimoro N100 dyke swarm transects central Burkina Faso and was dated at ca. 1575 Ma. Five ca. 1520 Ma ages were obtained for dykes of the Essakane swarm, three in Burkina Faso, one from Ghana (N130 orientation) and one from Senegal (E-W orientation), and document a large extent (600 km wide and 1500 km long) and short duration of dyke emplacement. The Manso N350 dyke swarm in southern Ghana, which is about 400 km long and about 200 km wide, yields a preliminary age of ca 870 Ma. A mantle plume origin is suggested for these swarms, especially the 1790-1765 Ma Libiri-Bassari swarm and the 1520 Ma Essakane swarms (which have lithosphere-contaminated E-MORB chemistry), whose scale is similar to largest giant radiating swarms (e.g. CAMP and Mackenzie). The 870 Ma Manso swarm has composition closer to OIB, consistent with a plume/hotspot origin. The 1575 Ma Korsimoro swarm has composition between EMORB and NMORB, which suggests a rift setting.

  16. Nonlinear dynamics optimization with particle swarm and genetic algorithms for SPEAR3 emittance upgrade

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Huang, Xiaobiao; Safranek, James

    2014-09-01

    Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.

  17. Effect of swarming on biodiversity in non-symmetric rock-paper-scissor game.

    PubMed

    Bose, R

    2010-05-01

    Cyclic dominance of species is a potential mechanism for maintaining biodiversity. The author investigates the generalised scenario when the cyclic dominance of three or more interacting species is described by a non-symmetric matrix game that has multiple Nash equilibria. Modified Lotka-Volterra equations are proposed to incorporate the effects of swarming, and the condition for biodiversity is derived. The species are modelled using replicator equations, where each member of the species is assigned a fitness value. The authors show, for the first time, that the 'swarming effect' has an important role to play in the maintenance of biodiversity. The authors have also discovered the existence of a critical value of the swarming parameter for a given mobility, above which there is a high probability of existence of biodiversity.

  18. Artificial pheromone for path selection by a foraging swarm of robots.

    PubMed

    Campo, Alexandre; Gutiérrez, Alvaro; Nouyan, Shervin; Pinciroli, Carlo; Longchamp, Valentin; Garnier, Simon; Dorigo, Marco

    2010-11-01

    Foraging robots involved in a search and retrieval task may create paths to navigate faster in their environment. In this context, a swarm of robots that has found several resources and created different paths may benefit strongly from path selection. Path selection enhances the foraging behavior by allowing the swarm to focus on the most profitable resource with the possibility for unused robots to stop participating in the path maintenance and to switch to another task. In order to achieve path selection, we implement virtual ants that lay artificial pheromone inside a network of robots. Virtual ants are local messages transmitted by robots; they travel along chains of robots and deposit artificial pheromone on the robots that are literally forming the chain and indicating the path. The concentration of artificial pheromone on the robots allows them to decide whether they are part of a selected path. We parameterize the mechanism with a mathematical model and provide an experimental validation using a swarm of 20 real robots. We show that our mechanism favors the selection of the closest resource is able to select a new path if a selected resource becomes unavailable and selects a newly detected and better resource when possible. As robots use very simple messages and behaviors, the system would be particularly well suited for swarms of microrobots with minimal abilities.

  19. Family Oriented Field Experience in Geography.

    ERIC Educational Resources Information Center

    Williams, Karen A.

    A family-oriented geography field course about the southwestern United States was conducted in 1978 by a community college in Michigan (Delta College). Course activities took place in Colorado. The major purpose of the field experience was to offer learning experiences to family groups rather than to individual students. For purposes of the field…

  20. Improving Vector Evaluated Particle Swarm Optimisation Using Multiple Nondominated Leaders

    PubMed Central

    Lim, Kian Sheng; Buyamin, Salinda; Ahmad, Anita; Shapiai, Mohd Ibrahim; Naim, Faradila; Mubin, Marizan; Kim, Dong Hwa

    2014-01-01

    The vector evaluated particle swarm optimisation (VEPSO) algorithm was previously improved by incorporating nondominated solutions for solving multiobjective optimisation problems. However, the obtained solutions did not converge close to the Pareto front and also did not distribute evenly over the Pareto front. Therefore, in this study, the concept of multiple nondominated leaders is incorporated to further improve the VEPSO algorithm. Hence, multiple nondominated solutions that are best at a respective objective function are used to guide particles in finding optimal solutions. The improved VEPSO is measured by the number of nondominated solutions found, generational distance, spread, and hypervolume. The results from the conducted experiments show that the proposed VEPSO significantly improved the existing VEPSO algorithms. PMID:24883386

  1. [Optimization of the parameters of microcirculatory structural adaptation model based on improved quantum-behaved particle swarm optimization algorithm].

    PubMed

    Pan, Qing; Yao, Jialiang; Wang, Ruofan; Cao, Ping; Ning, Gangmin; Fang, Luping

    2017-08-01

    The vessels in the microcirculation keep adjusting their structure to meet the functional requirements of the different tissues. A previously developed theoretical model can reproduce the process of vascular structural adaptation to help the study of the microcirculatory physiology. However, until now, such model lacks the appropriate methods for its parameter settings with subsequent limitation of further applications. This study proposed an improved quantum-behaved particle swarm optimization (QPSO) algorithm for setting the parameter values in this model. The optimization was performed on a real mesenteric microvascular network of rat. The results showed that the improved QPSO was superior to the standard particle swarm optimization, the standard QPSO and the previously reported Downhill algorithm. We conclude that the improved QPSO leads to a better agreement between mathematical simulation and animal experiment, rendering the model more reliable in future physiological studies.

  2. 3D modelling of the Tejeda Caldera cone-sheet swarm, Gran Canaria, Canary Islands, Spain

    NASA Astrophysics Data System (ADS)

    Samrock, Lisa K.; Jensen, Max J.; Burchardt, Steffi; Troll, Valentin R.; Mattsson, Tobias; Geiger, Harri

    2015-04-01

    Cone-sheet swarms provide vital information on the interior of volcanic systems and their plumbing systems (e.g. Burchardt et al. 2013). This information is important for the interpretation of processes and dynamics of modern and ancient volcanic systems, and is therefore vital for assessing volcanic hazards and to reduce risks to modern society. To more realistically model cone-sheet emplacement an approximation of their 3D shape needs to be known. Most cone-sheet swarms are not sufficiently exposed laterally and/or vertically, however, which makes it difficult to determine the geometry of a cone-sheet swarm at depth, especially since different shapes (e.g. convex, straight or concave continuations) would produce a similar trace at the surface (cf. Burchardt et al. 2011, and references therein). The Miocene Tejeda Caldera on Gran Canaria, Canary Islands, Spain, hosts a cone-sheet swarm that was emplaced into volcaniclastic caldera infill at about 12.3-7.3 Ma (Schirnick et al. 1999). The dyke swarm displays over 1000 m of vertical exposure and more than 15 km of horizontal exposure, making it a superb locality to study the evolution of cone-sheet swarms in detail and to determine its actual geometry in 3D space. We have used structural data of Schirnick (1996) to model the geometry of the Tejeda cone-sheet in 3D, using the software Move® by Midland Valley Ltd. Based on previous 2D projections, Schirnick et al. (1999) suggested that the cone-sheet swarm is formed by a stack of parallel intrusive sheets which have a truncated dome geometry and form a concentric structure around a central axis, assuming straight sheet-intrusions. Our 3D model gives insight into the symmetries of the sheets and the overall geometry of the cone-sheet swarm below the surface. This visualization now allows to grasp the complexity of the Tejeda cone-sheet swarm at depth, particularly in relation to different possible cone-sheet geometries suggested in the literature (cf. Burchardt et al

  3. Particle Swarm Optimization for Programming Deep Brain Stimulation Arrays

    PubMed Central

    Peña, Edgar; Zhang, Simeng; Deyo, Steve; Xiao, YiZi; Johnson, Matthew D.

    2017-01-01

    Objective Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Approach Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. Main Results The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (≤9.2%) and ROA (≤1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n=3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations

  4. Climatology of GPS signal loss observed by Swarm satellites

    NASA Astrophysics Data System (ADS)

    Xiong, Chao; Stolle, Claudia; Park, Jaeheung

    2018-04-01

    By using 3-year global positioning system (GPS) measurements from December 2013 to November 2016, we provide in this study a detailed survey on the climatology of the GPS signal loss of Swarm onboard receivers. Our results show that the GPS signal losses prefer to occur at both low latitudes between ±5 and ±20° magnetic latitude (MLAT) and high latitudes above 60° MLAT in both hemispheres. These events at all latitudes are observed mainly during equinoxes and December solstice months, while totally absent during June solstice months. At low latitudes the GPS signal losses are caused by the equatorial plasma irregularities shortly after sunset, and at high latitude they are also highly related to the large density gradients associated with ionospheric irregularities. Additionally, the high-latitude events are more often observed in the Southern Hemisphere, occurring mainly at the cusp region and along nightside auroral latitudes. The signal losses mainly happen for those GPS rays with elevation angles less than 20°, and more commonly occur when the line of sight between GPS and Swarm satellites is aligned with the shell structure of plasma irregularities. Our results also confirm that the capability of the Swarm receiver has been improved after the bandwidth of the phase-locked loop (PLL) widened, but the updates cannot radically avoid the interruption in tracking GPS satellites caused by the ionospheric plasma irregularities. Additionally, after the PLL bandwidth increased larger than 0.5 Hz, some unexpected signal losses are observed even at middle latitudes, which are not related to the ionospheric plasma irregularities. Our results suggest that rather than 1.0 Hz, a PLL bandwidth of 0.5 Hz is a more suitable value for the Swarm receiver.

  5. Seismicity-based estimation of the driving fluid pressure in the case of swarm activity in Western Bohemia

    NASA Astrophysics Data System (ADS)

    Hainzl, S.; Fischer, T.; Dahm, T.

    2012-10-01

    Two recent major swarms in Western Bohemia occurred in the years 2000 and 2008 within almost the same portion of a fault close to Novy Kostel. Previous analysis of the year 2000 earthquake swarm revealed that fluid intrusion seemed to initiate the activity whereas stress redistribution by the individual swarm earthquakes played a major role in the further swarm evolution. Here we analyse the new swarm, which occurred in the year 2008, with regard to its correlation to the previous swarm as well its spatiotemporal migration patterns. We find that (i) the main part of the year 2008 activity ruptured fault patches adjacent to the main activity of the swarm 2000, but that also (ii) a significant overlap exists where earthquakes occurred in patches in which stress had been already released by precursory events; (iii) the activity shows a clear migration which can be described by a 1-D (in up-dip direction) diffusion process; (iv) the migration pattern can be equally well explained by a hydrofracture growth, which additionally explains the faster migration in up-dip compared to the down-dip direction as well as the maximum up-dip extension of the activity. We use these observations to estimate the underlying fluid pressure change in two different ways: First, we calculate the stress changes induced by precursory events at the location of each swarm earthquake assuming that observed stress deficits had to be compensated by pore pressure increases; and secondly, we estimate the fluid overpressure by fitting a hydrofracture model to the asymmetric seismicity patterns. Both independent methods indicate that the fluid pressure increase was initially up to 30 MPa.

  6. InSAR observations of aseismic slip associated with an earthquake swarm in the Columbia River flood basalts

    USGS Publications Warehouse

    Wicks, Charles; Thelen, W.; Weaver, C.; Gomberg, J.; Rohay, A.; Bodin, P.

    2011-01-01

    In 2009 a swarm of small shallow earthquakes occurred within the basalt flows of the Columbia River Basalt Group (CRBG). The swarm occurred within a dense seismic network in the U.S. Department of Energys Hanford Site. Data from the seismic network along with interferometric synthetic aperture radar (InSAR) data from the European Space Agencys (ESA) ENVISAT satellite provide insight into the nature of the swarm. By modeling the InSAR deformation data we constructed a model that consists of a shallow thrust fault and a near horizontal fault. We suggest that the near horizontal lying fault is a bedding-plane fault located between basalt flows. The geodetic moment of the modeled fault system is about eight times the cumulative seismic moment of the swarm. Precise location estimates of the swarm earthquakes indicate that the area of highest slip on the thrust fault, ???70mm of slip less than ???0.5km depth, was not located within the swarm cluster. Most of the slip on the faults appears to have progressed aseismically and we suggest that interbed sediments play a central role in the slip process. Copyright 2011 by the American Geophysical Union.

  7. Kinematics of the 2015 San Ramon, California earthquake swarm: Implications for fault zone structure and driving mechanisms

    NASA Astrophysics Data System (ADS)

    Xue, Lian; Bürgmann, Roland; Shelly, David R.; Johnson, Christopher W.; Taira, Taka'aki

    2018-05-01

    Earthquake swarms represent a sudden increase in seismicity that may indicate a heterogeneous fault-zone, the involvement of crustal fluids and/or slow fault slip. Swarms sometimes precede major earthquake ruptures. An earthquake swarm occurred in October 2015 near San Ramon, California in an extensional right step-over region between the northern Calaveras Fault and the Concord-Mt. Diablo fault zone, which has hosted ten major swarms since 1970. The 2015 San Ramon swarm is examined here from 11 October through 18 November using template matching analysis. The relocated seismicity catalog contains ∼4000 events with magnitudes between - 0.2 swarm illuminated three sub-parallel, southwest striking and northwest dipping fault segments of km-scale dimension and thickness of up to 200 m. The segments contain coexisting populations of different focal-mechanisms, suggesting a complex fault zone structure with several sets of en échelon fault orientations. The migration of events along the three planar structures indicates a complex fluid and faulting interaction processes. We searched for correlations between seismic activity and tidal stresses and found some suggestive features, but nothing that we can be confident is statistically significant.

  8. Nontoxic colloidal particles impede antibiotic resistance of swarming bacteria by disrupting collective motion and speed

    NASA Astrophysics Data System (ADS)

    Lu, Shengtao; Liu, Fang; Xing, Bengang; Yeow, Edwin K. L.

    2015-12-01

    A monolayer of swarming B. subtilis on semisolid agar is shown to display enhanced resistance against antibacterial drugs due to their collective behavior and motility. The dynamics of swarming motion, visualized in real time using time-lapse microscopy, prevents the bacteria from prolonged exposure to lethal drug concentrations. The elevated drug resistance is significantly reduced when the collective motion of bacteria is judiciously disrupted using nontoxic polystyrene colloidal particles immobilized on the agar surface. The colloidal particles block and hinder the motion of the cells, and force large swarming rafts to break up into smaller packs in order to maneuver across narrow spaces between densely packed particles. In this manner, cohesive rafts rapidly lose their collectivity, speed, and group dynamics, and the cells become vulnerable to the drugs. The antibiotic resistance capability of swarming B. subtilis is experimentally observed to be negatively correlated with the number density of colloidal particles on the engineered surface. This relationship is further tested using an improved self-propelled particle model that takes into account interparticle alignment and hard-core repulsion. This work has pertinent implications on the design of optimal methods to treat drug resistant bacteria commonly found in swarming colonies.

  9. Swarm Intelligence for Optimizing Hybridized Smoothing Filter in Image Edge Enhancement

    NASA Astrophysics Data System (ADS)

    Rao, B. Tirumala; Dehuri, S.; Dileep, M.; Vindhya, A.

    In this modern era, image transmission and processing plays a major role. It would be impossible to retrieve information from satellite and medical images without the help of image processing techniques. Edge enhancement is an image processing step that enhances the edge contrast of an image or video in an attempt to improve its acutance. Edges are the representations of the discontinuities of image intensity functions. For processing these discontinuities in an image, a good edge enhancement technique is essential. The proposed work uses a new idea for edge enhancement using hybridized smoothening filters and we introduce a promising technique of obtaining best hybrid filter using swarm algorithms (Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO)) to search for an optimal sequence of filters from among a set of rather simple, representative image processing filters. This paper deals with the analysis of the swarm intelligence techniques through the combination of hybrid filters generated by these algorithms for image edge enhancement.

  10. Gravity inversion of a fault by Particle swarm optimization (PSO).

    PubMed

    Toushmalani, Reza

    2013-01-01

    Particle swarm optimization is a heuristic global optimization method and also an optimization algorithm, which is based on swarm intelligence. It comes from the research on the bird and fish flock movement behavior. In this paper we introduce and use this method in gravity inverse problem. We discuss the solution for the inverse problem of determining the shape of a fault whose gravity anomaly is known. Application of the proposed algorithm to this problem has proven its capability to deal with difficult optimization problems. The technique proved to work efficiently when tested to a number of models.

  11. Developments in the kinetic theories of ion and electron swarms in the 1960s and 70s

    NASA Astrophysics Data System (ADS)

    Skullerud, H. R.

    2017-04-01

    The two decades between 1960 to 1980 saw quite a fantastic development in diverse areas in physics, and so also in the quantitative theoretical treatment and deeper understanding of the behaviour of isolated electrons and ions in gases—that is ‘charged particle swarm physics’. The evolution in swarm theory was strongly correlated with the contemporary advances in computer technology and the emergence of new and accurate experimental methods for finding charged particle transport parameters, as drift velocities, diffusion coefficients and reaction rates, and also with developments in neighbouring fields as plasma physics and the physics of electronic and molecular collisions. In 1960, low energy electron behaviour could already be calculated with reasonable accuracy in the so-called two-term approximation, while ion behaviour could only be treated at weak electric fields. By 1980, reasonably complete theories had been developed for perhaps most cases in interest—which is reflected in a number of reviews, books and journal articles published in the early 1980s. We will present a journey through the developments in this period and the basic theories behind the Boltzmann equation and Maxwell’s transfer equations. We will also indicate how the interaction between different studies of the same basic processes have led to the elimination of shortcomings and a better understanding.

  12. Cost Minimization for Joint Energy Management and Production Scheduling Using Particle Swarm Optimization

    NASA Astrophysics Data System (ADS)

    Shah, Rahul H.

    production planning framework are discussed. A modified Particle Swarm Optimization solution technique is adopted to solve the proposed scheduling problem. The algorithm is described in detail and compared to Genetic Algorithm. Case studies are presented to illustrate the benefits of using the proposed model and the effectiveness of the Particle Swarm Optimization approach. Numerical Experiments are implemented and analyzed to test the effectiveness of the proposed model. The proposed scheduling strategy can achieve savings of around 19 to 27 % in cost per part when compared to the baseline scheduling scenarios. By optimizing key production system parameters from the cost per part model, the baseline scenarios can obtain around 20 to 35 % in savings for the cost per part. These savings further increase by 42 to 55 % when system parameter optimization is integrated with the proposed scheduling problem. Using this method, the most influential parameters on the cost per part are the rated power from production, the production rate, and the initial machine reliabilities. The modified Particle Swarm Optimization algorithm adopted allows greater diversity and exploration compared to Genetic Algorithm for the proposed joint model which results in it being more computationally efficient in determining the optimal scheduling. While Genetic Algorithm could achieve a solution quality of 2,279.63 at an expense of 2,300 seconds in computational effort. In comparison, the proposed Particle Swarm Optimization algorithm achieved a solution quality of 2,167.26 in less than half the computation effort which is required by Genetic Algorithm.

  13. Spatially-dependent alkyl quinolone signaling responses to antibiotics in Pseudomonas aeruginosa swarms.

    PubMed

    Morales-Soto, Nydia; Dunham, Sage J B; Baig, Nameera F; Ellis, Joseph F; Madukoma, Chinedu S; Bohn, Paul W; Sweedler, Jonathan V; Shrout, Joshua D

    2018-03-27

    There is a general lack of understanding about how communities of bacteria respond to exogenous toxins such as antibiotics. Most of our understanding of community-level stress responses comes from the study of stationary biofilm communities. Although several community behaviors and production of specific biomolecules affecting biofilm development and associated behavior have been described for Pseudomonas aeruginosa and other bacteria, we have little appreciation for the production and dispersal of secreted metabolites within the 2D and 3D spaces they occupy as they colonize, spread, and grow on surfaces. Here we specifically studied the phenotypic responses and spatial variability of alkyl quinolones, including the Pseudomonas quinolone signal (PQS) and members of the alkyl hydroxyquinoline (AQNO) subclass, in P. aeruginosa plate-assay swarming communities. We found that PQS production was not a universal signaling response to antibiotics as tobramycin elicited an alkyl quinolone response while carbenicillin did not. We also found that PQS and AQNO profiles in response to tobramycin were markedly distinct and influenced these swarms on different spatial scales. The distribution of alkyl quinolones varied by several orders of magnitude within the same swarm. At some tobramycin exposures, P. aeruginosa swarms produced alkyl quinolones in the range of 150 µM PQS and 400 µM AQNO that accumulated as aggregates. Our collective findings show that the distribution of alkyl quinolones can vary by several orders of magnitude within the same swarming community.  More notably, our results suggest that multiple intercellular signals acting on different spatial scales can be triggered by one common cue. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.

  14. SWARM : a scientific workflow for supporting Bayesian approaches to improve metabolic models.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Shi, X.; Stevens, R.; Mathematics and Computer Science

    2008-01-01

    With the exponential growth of complete genome sequences, the analysis of these sequences is becoming a powerful approach to build genome-scale metabolic models. These models can be used to study individual molecular components and their relationships, and eventually study cells as systems. However, constructing genome-scale metabolic models manually is time-consuming and labor-intensive. This property of manual model-building process causes the fact that much fewer genome-scale metabolic models are available comparing to hundreds of genome sequences available. To tackle this problem, we design SWARM, a scientific workflow that can be utilized to improve genome-scale metabolic models in high-throughput fashion. SWARM dealsmore » with a range of issues including the integration of data across distributed resources, data format conversions, data update, and data provenance. Putting altogether, SWARM streamlines the whole modeling process that includes extracting data from various resources, deriving training datasets to train a set of predictors and applying Bayesian techniques to assemble the predictors, inferring on the ensemble of predictors to insert missing data, and eventually improving draft metabolic networks automatically. By the enhancement of metabolic model construction, SWARM enables scientists to generate many genome-scale metabolic models within a short period of time and with less effort.« less

  15. Swarm intelligence inspired shills and the evolution of cooperation.

    PubMed

    Duan, Haibin; Sun, Changhao

    2014-06-09

    Many hostile scenarios exist in real-life situations, where cooperation is disfavored and the collective behavior needs intervention for system efficiency improvement. Towards this end, the framework of soft control provides a powerful tool by introducing controllable agents called shills, who are allowed to follow well-designed updating rules for varying missions. Inspired by swarm intelligence emerging from flocks of birds, we explore here the dependence of the evolution of cooperation on soft control by an evolutionary iterated prisoner's dilemma (IPD) game staged on square lattices, where the shills adopt a particle swarm optimization (PSO) mechanism for strategy updating. We demonstrate that not only can cooperation be promoted by shills effectively seeking for potentially better strategies and spreading them to others, but also the frequency of cooperation could be arbitrarily controlled by choosing appropriate parameter settings. Moreover, we show that adding more shills does not contribute to further cooperation promotion, while assigning higher weights to the collective knowledge for strategy updating proves a efficient way to induce cooperative behavior. Our research provides insights into cooperation evolution in the presence of PSO-inspired shills and we hope it will be inspirational for future studies focusing on swarm intelligence based soft control.

  16. Genetic particle swarm parallel algorithm analysis of optimization arrangement on mistuned blades

    NASA Astrophysics Data System (ADS)

    Zhao, Tianyu; Yuan, Huiqun; Yang, Wenjun; Sun, Huagang

    2017-12-01

    This article introduces a method of mistuned parameter identification which consists of static frequency testing of blades, dichotomy and finite element analysis. A lumped parameter model of an engine bladed-disc system is then set up. A bladed arrangement optimization method, namely the genetic particle swarm optimization algorithm, is presented. It consists of a discrete particle swarm optimization and a genetic algorithm. From this, the local and global search ability is introduced. CUDA-based co-evolution particle swarm optimization, using a graphics processing unit, is presented and its performance is analysed. The results show that using optimization results can reduce the amplitude and localization of the forced vibration response of a bladed-disc system, while optimization based on the CUDA framework can improve the computing speed. This method could provide support for engineering applications in terms of effectiveness and efficiency.

  17. A joint swarm intelligence algorithm for multi-user detection in MIMO-OFDM system

    NASA Astrophysics Data System (ADS)

    Hu, Fengye; Du, Dakun; Zhang, Peng; Wang, Zhijun

    2014-11-01

    In the multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) system, traditional multi-user detection (MUD) algorithms that usually used to suppress multiple access interference are difficult to balance system detection performance and the complexity of the algorithm. To solve this problem, this paper proposes a joint swarm intelligence algorithm called Ant Colony and Particle Swarm Optimisation (AC-PSO) by integrating particle swarm optimisation (PSO) and ant colony optimisation (ACO) algorithms. According to simulation results, it has been shown that, with low computational complexity, the MUD for the MIMO-OFDM system based on AC-PSO algorithm gains comparable MUD performance with maximum likelihood algorithm. Thus, the proposed AC-PSO algorithm provides a satisfactory trade-off between computational complexity and detection performance.

  18. Fault Weakening due to Erosion by Fluids: A Possible Origin of Intraplate Earthquake Swarms

    NASA Astrophysics Data System (ADS)

    Vavrycuk, V.; Hrubcova, P.

    2016-12-01

    The occurrence and specific properties of earthquake swarms in geothermal areas are usually attributed to a highly fractured rock and/or heterogeneous stress within the rock mass being triggered by magmatic or hydrothermal fluid intrusion. The increase of fluid pressure destabilizes fractures and causes their opening and subsequent shear-tensile rupture. The spreading and evolution of the seismic activity is controlled by fluid flow due to diffusion in a permeable rock and/or by the redistribution of Coulomb stress. The `fluid-injection model', however, is not valid universally. We provide evidence that this model is inconsistent with observations of earthquake swarms in West Bohemia, Czech Republic. Full seismic moment tensors of micro-earthquakes in the 1997 and 2008 swarms in West Bohemia indicate that fracturing at the starting phase of the swarm was not associated with fault openings caused by pressurized fluids but rather with fault compactions. This can physically be explained by a `fluid-erosion model', when the essential role in the swarm triggering is attributed to chemical and hydrothermal fluid-rock interactions in the focal zone. Since the rock is exposed to circulating hydrothermal, CO2-saturated fluids, the walls of fractures are weakened by dissolving and altering various minerals. If fault strength lowers to a critical value, the seismicity is triggered. The fractures are compacted during failure, the fault strength recovers and a new cycle begins.

  19. Steady-state configuration and tension calculations of marine cables under complex currents via separated particle swarm optimization

    NASA Astrophysics Data System (ADS)

    Xu, Xue-song

    2014-12-01

    Under complex currents, the motion governing equations of marine cables are complex and nonlinear, and the calculations of cable configuration and tension become difficult compared with those under the uniform or simple currents. To obtain the numerical results, the usual Newton-Raphson iteration is often adopted, but its stability depends on the initial guessed solution to the governing equations. To improve the stability of numerical calculation, this paper proposed separated the particle swarm optimization, in which the variables are separated into several groups, and the dimension of search space is reduced to facilitate the particle swarm optimization. Via the separated particle swarm optimization, these governing nonlinear equations can be solved successfully with any initial solution, and the process of numerical calculation is very stable. For the calculations of cable configuration and tension of marine cables under complex currents, the proposed separated swarm particle optimization is more effective than the other particle swarm optimizations.

  20. Monitoring the West Bohemian earthquake swarm in 2008/2009 by a temporary small-aperture seismic array

    NASA Astrophysics Data System (ADS)

    Hiemer, Stefan; Roessler, Dirk; Scherbaum, Frank

    2012-04-01

    The most recent intense earthquake swarm in West Bohemia lasted from 6 October 2008 to January 2009. Starting 12 days after the onset, the University of Potsdam monitored the swarm by a temporary small-aperture seismic array at 10 km epicentral distance. The purpose of the installation was a complete monitoring of the swarm including micro-earthquakes ( M L < 0). We identify earthquakes using a conventional short-term average/long-term average trigger combined with sliding-window frequency-wavenumber and polarisation analyses. The resulting earthquake catalogue consists of 14,530 earthquakes between 19 October 2008 and 18 March 2009 with magnitudes in the range of - 1.2 ≤ M L ≤ 2.7. The small-aperture seismic array substantially lowers the detection threshold to about M c = - 0.4, when compared to the regional networks operating in West Bohemia ( M c > 0.0). In the course of this work, the main temporal features (frequency-magnitude distribution, propagation of back azimuth and horizontal slowness, occurrence rate of aftershock sequences and interevent-time distribution) of the recent 2008/2009 earthquake swarm are presented and discussed. Temporal changes of the coefficient of variation (based on interevent times) suggest that the swarm earthquake activity of the 2008/2009 swarm terminates by 12 January 2009. During the main phase in our studied swarm period after 19 October, the b value of the Gutenberg-Richter relation decreases from 1.2 to 0.8. This trend is also reflected in the power-law behavior of the seismic moment release. The corresponding total seismic moment release of 1.02×1017 Nm is equivalent to M L,max = 5.4.

  1. Living on the edge: Emergence of spontaneous gac mutations in Pseudomonas protegens during swarming motility

    USDA-ARS?s Scientific Manuscript database

    Swarming motility is a flagella-driven multicellular behavior that allows bacteria to colonize new niches and escape competition. Here, we investigated the spatial distribution and evolution of ‘social cheaters’ in swarming colonies of Pseudomonas protegens Pf-5. Lipopeptide surfactants in the orfam...

  2. Low Stress Drop Swarm Events in the Yilgarn Craton, Western Australia

    NASA Astrophysics Data System (ADS)

    Allen, T. I.; Cummins, P. R.; Leonard, M.; Collins, C. D.

    2004-12-01

    Since September 2001, the small rural community of Burakin, southwest Western Australia, has been at the focus of seismic activity in Australia. In the six month period following commencement of seismicity, some 18,000 events had occurred, the largest of which having a moment magnitude of M 4.6. At the onset of activity, Geoscience Australia made a concerted effort to deploy a temporary seismic network in the region. The primary objective of this network was to collect high-quality strong-motion data for use in attenuation studies. Levels of seismicity near Burakin have decreased significantly since the 2001-02 swarm, however the region continues to experience a few small earthquakes per month. Earthquake source and path parameters are evaluated for a subset of 67 earthquakes. The dataset comprises some 375 seismograph and accelerograph records for events of magnitude M 2.3-4.6, including strong-motion data for seven earthquakes of M 4.0 and greater recorded at hypocentral distances less than 10 km. Source parameters are evaluated from far-field displacement spectra. Average corner frequencies are typically quite low, chiefly ranging between 2-3 Hz for events M 3.0 and above. Given the small variability in corner frequency, stress drop is observed to increase with magnitude, from very low values of 0.04 MPa to 18 MPa for the largest events in the catalogue. The stress drops for lower magnitude events (M < 4.0) are typically lower than those obtained for southeastern Australian earthquakes of similar seismic moment. Since corner frequency is not observed to vary significantly with seismic moment, it is thought that the spectral content of shallow, small swarm events and consequently, the stress drop, is characteristically different to that of isolated intraplate earthquakes. We suggest that the larger events may be faulting previously unfractured rock or healed fault asperities, while the smaller events are adjustment events or aftershocks and occur on recently

  3. Is the seismicity swarm at long-dormant Jailolo volcano (Indonesia) a signature of a magmatic unrest?

    NASA Astrophysics Data System (ADS)

    Passarelli, Luigi; Cesca, Simone; Heryandoko, Nova; Lopez Comino, Jose Angel; Strollo, Angelo; Rivalta, Eleonora; Rohadi, Supryianto; Dahm, Torsten; Milkereit, Claus

    2017-04-01

    Magmatic unrest is challenging to detect when monitoring is sparse and there is little knowledge about the volcano. This is especially true for long-dormant volcanoes. Geophysical observables like seismicity, deformation, temperature and gas emission are reliable indicators of ongoing volcanic unrest caused by magma movements. Jailolo volcano is a Holocene volcano belonging to the Halmahera volcanic arc in the Northern Moluccas Islands, Indonesia. Global databases of volcanic eruptions have no records of its eruptive activity and no geological investigation has been carried out to better assess the past eruptive activity at Jailolo. It probably sits on the northern rim of an older caldera which now forms the Jailolo bay. Hydrothermal activity is intense with several hot-springs and steaming ground spots around the Jailolo volcano. In November 2015 an energetic seismic swarm started and lasted until late February 2016 with four earthquakes with M>5 recorded by global seismic networks. At the time of the swarm no close geophysical monitoring network was available around Jailolo volcano except for a broadband station at 30km distant. We installed last summer a local dense multi-parametric monitoring network with 36 seismic stations, 6 GPS and 2 gas monitoring stations around Jailolo volcano. We revised the focal mechanisms of the larger events and used single station location methods in order to exploit the little information available at the time of the swarm activity. We also combined the old sparse data with our local dense network. Migration of hypocenters and inversion of the local stress field derived by focal mechanisms analysis indicate that the Nov-Feb seismicity swarm may be related to a magmatic intrusion at shallow depth. Data from our dense network confirms ongoing micro-seismic activity underneath Jailolo volcano but there are no indications of new magma intrusion. Our findings indicate that magmatic unrest occurred at Jailolo volcano and call for a

  4. Reconstruction of F-Region Electric Current Densities from more than 2 Years of Swarm Satellite Magnetic data

    NASA Astrophysics Data System (ADS)

    Tozzi, R.; Pezzopane, M.; De Michelis, P.; Pignalberi, A.; Siciliano, F.

    2016-12-01

    The constellation geometry adopted by ESA for Swarm satellites has opened the way to new investigations based on magnetic data. An example is the curl-B technique that allows reconstructing F-region electric current density in terms of its radial, meridional, and zonal components based on data from two satellites of Swarm constellation (Swarm A and B) which fly at different altitudes. Here, we apply this technique to more than 2 years of Swarm magnetic vector data and investigate the average large scale behaviour of F-region current densities as a function of local time, season and different interplanetary conditions (different strength and direction of the three IMF components and/or geomagnetic activity levels).

  5. Observations and modeling of the ionospheric gravity and diamagnetic current systems from CHAMP and Swarm measurements

    NASA Astrophysics Data System (ADS)

    Alken, P.

    2016-01-01

    The CHAMP and Swarm satellites, which provide high-quality magnetic field measurements in low-altitude polar orbits, are ideally suited for investigating ionospheric current systems. In this study, we focus on the F region low-latitude gravity and diamagnetic currents which are prominent in the equatorial ionization anomaly (EIA) region in the North and South Hemisphere. During its 10 year mission, CHAMP has sampled nearly the entire altitude range of the EIA, offering the opportunity to study these currents from above, inside, and below their source region. The Swarm constellation offers the unique opportunity to study near-simultaneous measurements of the current systems at different longitudinal separations. In this study, we present new observations of these current systems, investigate their seasonal and local time dependence, investigate the use of in situ electron density measurements as a proxy for the magnetic perturbations, and compute the longitudinal self correlation of these currents. We find that these currents are strongest during spring and fall, produce nighttime magnetic fields at satellite altitude of up to 5-7 nT during solar maximum, 2-3 nT during solar minimum, and are highly correlated with in situ electron density measurements. We also find these currents are self-correlated above 70% up to 15° longitude in both hemispheres during the evening.

  6. Adaptive particle swarm optimization for optimal orbital elements of binary stars

    NASA Astrophysics Data System (ADS)

    Attia, Abdel-Fattah

    2016-12-01

    The paper presents an adaptive particle swarm optimization (APSO) as an alternative method to determine the optimal orbital elements of the star η Bootis of MK type G0 IV. The proposed algorithm transforms the problem of finding periodic orbits into the problem of detecting global minimizers as a function, to get a best fit of Keplerian and Phase curves. The experimental results demonstrate that the proposed approach of APSO generally more accurate than the standard particle swarm optimization (PSO) and other published optimization algorithms, in terms of solution accuracy, convergence speed and algorithm reliability.

  7. A Parallel Particle Swarm Optimization Algorithm Accelerated by Asynchronous Evaluations

    NASA Technical Reports Server (NTRS)

    Venter, Gerhard; Sobieszczanski-Sobieski, Jaroslaw

    2005-01-01

    A parallel Particle Swarm Optimization (PSO) algorithm is presented. Particle swarm optimization is a fairly recent addition to the family of non-gradient based, probabilistic search algorithms that is based on a simplified social model and is closely tied to swarming theory. Although PSO algorithms present several attractive properties to the designer, they are plagued by high computational cost as measured by elapsed time. One approach to reduce the elapsed time is to make use of coarse-grained parallelization to evaluate the design points. Previous parallel PSO algorithms were mostly implemented in a synchronous manner, where all design points within a design iteration are evaluated before the next iteration is started. This approach leads to poor parallel speedup in cases where a heterogeneous parallel environment is used and/or where the analysis time depends on the design point being analyzed. This paper introduces an asynchronous parallel PSO algorithm that greatly improves the parallel e ciency. The asynchronous algorithm is benchmarked on a cluster assembled of Apple Macintosh G5 desktop computers, using the multi-disciplinary optimization of a typical transport aircraft wing as an example.

  8. Application of Particle Swarm Optimization Algorithm in the Heating System Planning Problem

    PubMed Central

    Ma, Rong-Jiang; Yu, Nan-Yang; Hu, Jun-Yi

    2013-01-01

    Based on the life cycle cost (LCC) approach, this paper presents an integral mathematical model and particle swarm optimization (PSO) algorithm for the heating system planning (HSP) problem. The proposed mathematical model minimizes the cost of heating system as the objective for a given life cycle time. For the particularity of HSP problem, the general particle swarm optimization algorithm was improved. An actual case study was calculated to check its feasibility in practical use. The results show that the improved particle swarm optimization (IPSO) algorithm can more preferably solve the HSP problem than PSO algorithm. Moreover, the results also present the potential to provide useful information when making decisions in the practical planning process. Therefore, it is believed that if this approach is applied correctly and in combination with other elements, it can become a powerful and effective optimization tool for HSP problem. PMID:23935429

  9. DualTrust: A Distributed Trust Model for Swarm-Based Autonomic Computing Systems

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Maiden, Wendy M.; Dionysiou, Ioanna; Frincke, Deborah A.

    2011-02-01

    For autonomic computing systems that utilize mobile agents and ant colony algorithms for their sensor layer, trust management is important for the acceptance of the mobile agent sensors and to protect the system from malicious behavior by insiders and entities that have penetrated network defenses. This paper examines the trust relationships, evidence, and decisions in a representative system and finds that by monitoring the trustworthiness of the autonomic managers rather than the swarming sensors, the trust management problem becomes much more scalable and still serves to protect the swarm. We then propose the DualTrust conceptual trust model. By addressing themore » autonomic manager’s bi-directional primary relationships in the ACS architecture, DualTrust is able to monitor the trustworthiness of the autonomic managers, protect the sensor swarm in a scalable manner, and provide global trust awareness for the orchestrating autonomic manager.« less

  10. Adaptive Control Parameters for Dispersal of Multi-Agent Mobile Ad Hoc Network (MANET) Swarms

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kurt Derr; Milos Manic

    A mobile ad hoc network is a collection of independent nodes that communicate wirelessly with one another. This paper investigates nodes that are swarm robots with communications and sensing capabilities. Each robot in the swarm may operate in a distributed and decentralized manner to achieve some goal. This paper presents a novel approach to dynamically adapting control parameters to achieve mesh configuration stability. The presented approach to robot interaction is based on spring force laws (attraction and repulsion laws) to create near-optimal mesh like configurations. In prior work, we presented the extended virtual spring mesh (EVSM) algorithm for the dispersionmore » of robot swarms. This paper extends the EVSM framework by providing the first known study on the effects of adaptive versus static control parameters on robot swarm stability. The EVSM algorithm provides the following novelties: 1) improved performance with adaptive control parameters and 2) accelerated convergence with high formation effectiveness. Simulation results show that 120 robots reach convergence using adaptive control parameters more than twice as fast as with static control parameters in a multiple obstacle environment.« less

  11. Tectonic and Magmatic Implications of the Off-Nicobar Earthquake Swarm, Andaman Sea

    NASA Astrophysics Data System (ADS)

    Kattoju, K. R.; Ray, D.; Mudholkar, A.; Gollu, M. P.; Mathew, R.; Paropkari, A. L.; Kalathil, B.; Ramachandran, R.

    2008-12-01

    The off Nicobar earthquake swarm, considered as the most energetic earthquake swarm ever observed globally occurred during January 2005 in the Andaman Sea. The swarm was broadly associated with the aftershock effects of the great Mw 9.3 Sumatra - Andaman earthquake of 26 December 2004 that ruptured 1600 kilometres long stretch of the megathrust zone, the longest of any recorded earthquake. The swarm is located within the rupture area that roughly coincides with the after shock distribution and consisted of more than 150 events of magnitude 5 and above, the intense burst of events occurred in a span of 48 hours during 27-28 January 2005. The fault plane solutions indicate both strike-slip and normal fault events. Usually volcanic eruptions precede or accompany the earthquake swarms. The initial reports suggested absence of any volcanic activity associated with the unusual energy release east of Nicobar Islands in the Andaman Sea. A multidisciplinary voyage conducted to the region revealed a cratered seamount located at the center of the most intense burst of events. Unconsolidated aggregates recovered from the flank of the seamount by the TV-guided grab consist of globules with 66 to 97% manganese oxide, indicative of hydrothermal manganese precipitation as a consequence of recent pulses of hydrothermal activity. Evidences from seismicity, morphology, video footage of the seafloor, geochemical analysis of the seabed samples, and the preliminary findings from a sediment core in the vicinity suggest that the cratered seamount has a history of episodic volcanism. The findings are the first documented report of recent submarine volcanism in the Andaman Sea. We infer that the volcano is in a dormant state at present and is connected to the sub-aerial volcanoes of Sumatra and the Barren-Narcondam Island volcanoes of the Andaman Sea.

  12. Swarms of repeating long-period earthquakes at Shishaldin Volcano, Alaska, 2001-2004

    USGS Publications Warehouse

    Petersen, Tanja

    2007-01-01

    During 2001–2004, a series of four periods of elevated long-period seismic activity, each lasting about 1–2 months, occurred at Shishaldin Volcano, Aleutian Islands, Alaska. The time periods are termed swarms of repeating events, reflecting an abundance of earthquakes with highly similar waveforms that indicate stable, non-destructive sources. These swarms are characterized by increased earthquake amplitudes, although the seismicity rate of one event every 0.5–5 min has remained more or less constant since Shishaldin last erupted in 1999. A method based on waveform cross-correlation is used to identify highly repetitive events, suggestive of spatially distinct source locations. The waveform analysis shows that several different families of similar events co-exist during a given swarm day, but generally only one large family dominates. A network of hydrothermal fractures may explain the events that do not belong to a dominant repeating event group, i.e. multiple sources at different locations exist next to a dominant source. The dominant waveforms exhibit systematic changes throughout each swarm, but some of these waveforms do reappear over the course of 4 years indicating repeatedly activated source locations. The choked flow model provides a plausible trigger mechanism for the repeating events observed at Shishaldin, explaining the gradual changes in waveforms over time by changes in pressure gradient across a constriction within the uppermost part of the conduit. The sustained generation of Shishaldin's long-period events may be attributed to complex dynamics of a multi-fractured hydrothermal system: the pressure gradient within the main conduit may be regulated by temporarily sealing and reopening of parallel flow pathways, by the amount of debris within the main conduit and/or by changing gas influx into the hydrothermal system. The observations suggest that Shishaldin's swarms of repeating events represent time periods during which a dominant source

  13. Particle swarm optimization - Genetic algorithm (PSOGA) on linear transportation problem

    NASA Astrophysics Data System (ADS)

    Rahmalia, Dinita

    2017-08-01

    Linear Transportation Problem (LTP) is the case of constrained optimization where we want to minimize cost subject to the balance of the number of supply and the number of demand. The exact method such as northwest corner, vogel, russel, minimal cost have been applied at approaching optimal solution. In this paper, we use heurisitic like Particle Swarm Optimization (PSO) for solving linear transportation problem at any size of decision variable. In addition, we combine mutation operator of Genetic Algorithm (GA) at PSO to improve optimal solution. This method is called Particle Swarm Optimization - Genetic Algorithm (PSOGA). The simulations show that PSOGA can improve optimal solution resulted by PSO.

  14. Amphibious Quadcopter Swarm for the Exploration of Titan

    NASA Astrophysics Data System (ADS)

    Rajguru, A.; Faler, A. C.; Franz, B.

    2014-06-01

    This is a proposal for a low mass and cost effective mission architecture consisting of an amphibious quadcopter swarm flight vehicle system for the exploration of Titan's liquid methane lake, Ligeia Mare. The paper focuses on the EDL and operations.

  15. Metabolic flux estimation using particle swarm optimization with penalty function.

    PubMed

    Long, Hai-Xia; Xu, Wen-Bo; Sun, Jun

    2009-01-01

    Metabolic flux estimation through 13C trace experiment is crucial for quantifying the intracellular metabolic fluxes. In fact, it corresponds to a constrained optimization problem that minimizes a weighted distance between measured and simulated results. In this paper, we propose particle swarm optimization (PSO) with penalty function to solve 13C-based metabolic flux estimation problem. The stoichiometric constraints are transformed to an unconstrained one, by penalizing the constraints and building a single objective function, which in turn is minimized using PSO algorithm for flux quantification. The proposed algorithm is applied to estimate the central metabolic fluxes of Corynebacterium glutamicum. From simulation results, it is shown that the proposed algorithm has superior performance and fast convergence ability when compared to other existing algorithms.

  16. Source area of the 1858 earthquake swarm in the central Ryukyu Islands revealed by the observations of Father Louis Furet

    NASA Astrophysics Data System (ADS)

    Oda, Takuma; Nakamura, Mamoru

    2017-09-01

    We estimated the location and magnitude of earthquakes constituting the 1858 earthquake swarm in the central Ryukyu Islands using the felt earthquakes recorded by Father Louis Furet who lived in Naha, Okinawa Island, in the middle of the nineteenth century. First, we estimated the JMA seismic intensity of the earthquakes by interpreting the words used to describe the shaking. Next, using the seismic intensity and shaking duration of the felt earthquakes, we estimated the epicentral distance and magnitude range of three earthquakes in the swarm. The results showed that the epicentral distances of the earthquakes were 20-250 km and that magnitudes ranged between 4.5 and 6.5, with a strong correlation between epicentral distance and magnitude. Since the rumblings accompanying some earthquakes in the swarm were heard from a northward direction, the swarm probably occurred to the north of Naha. The most likely source area for the 1858 swarm is the central Okinawa Trough, where a similar swarm event occurred in 1980. If the 1858 swarm occurred in the central Okinawa Trough, the estimated maximum magnitude would have reached 6-7. In contrast, if the 1858 swarm occurred in the vicinity of Amami Island, which is the second most likely candidate area, it would have produced a cluster of magnitude 7-8 earthquakes.[Figure not available: see fulltext.

  17. Bacillus subtilis Swarmer Cells Lead the Swarm, Multiply, and Generate a Trail of Quiescent Descendants.

    PubMed

    Hamouche, Lina; Laalami, Soumaya; Daerr, Adrian; Song, Solène; Holland, I Barry; Séror, Simone J; Hamze, Kassem; Putzer, Harald

    2017-02-07

    Bacteria adopt social behavior to expand into new territory, led by specialized swarmers, before forming a biofilm. Such mass migration of Bacillus subtilis on a synthetic medium produces hyperbranching dendrites that transiently (equivalent to 4 to 5 generations of growth) maintain a cellular monolayer over long distances, greatly facilitating single-cell gene expression analysis. Paradoxically, while cells in the dendrites (nonswarmers) might be expected to grow exponentially, the rate of swarm expansion is constant, suggesting that some cells are not multiplying. Little attention has been paid to which cells in a swarm are actually multiplying and contributing to the overall biomass. Here, we show in situ that DNA replication, protein translation and peptidoglycan synthesis are primarily restricted to the swarmer cells at dendrite tips. Thus, these specialized cells not only lead the population forward but are apparently the source of all cells in the stems of early dendrites. We developed a simple mathematical model that supports this conclusion. Swarming motility enables rapid coordinated surface translocation of a microbial community, preceding the formation of a biofilm. This movement occurs in thin films and involves specialized swarmer cells localized to a narrow zone at the extreme swarm edge. In the B. subtilis system, using a synthetic medium, the swarm front remains as a cellular monolayer for up to 1.5 cm. Swarmers display high-velocity whirls and vortexing and are often assumed to drive community expansion at the expense of cell growth. Surprisingly, little attention has been paid to which cells in a swarm are actually growing and contributing to the overall biomass. Here, we show that swarmers not only lead the population forward but continue to multiply as a source of all cells in the community. We present a model that explains how exponential growth of only a few cells is compatible with the linear expansion rate of the swarm. Copyright © 2017

  18. NASA's Swarm Missions: The Challenge of Building Autonomous Software

    NASA Technical Reports Server (NTRS)

    Truszkowski, Walt; Hinchey, Mike; Rash, James; Rouff, Christopher

    2004-01-01

    The days of watching a massive manned cylinder thrust spectacularly off a platform into space might rapidly become ancient history when the National Aeronautics and Space Administration (NASA) introduces its new millenium mission class. Motivated by the need to gather more data than is possible with a single spacecraft, scientists have developed a new class of missions based on the efficiency and cooperative nature of a hive culture. The missions, aptly dubbed nanoswarm will be little more than mechanized colonies cooperating in their exploration of the solar system. Each swarm mission can have hundreds or even thousands of cooperating intelligent spacecraft that work in teams. The spacecraft must operate independently for long periods both in teams and individually, as well as have autonomic properties - self-healing, -configuring, -optimizing, and -protecting- to survive the harsh space environment. One swarm mission under concept development for 2020 to 2030 is the Autonomous Nano Technology Swarm (ANTS), in which a thousand picospacecraft, each weighing less than three pounds, will work cooperatively to explore the asteroid belt. Some spacecraft will form teams to catalog asteroid properties, such as mass, density, morphology, and chemical composition, using their respective miniature scientific instruments. Others will communicate with the data gatherers and send updates to mission elements on Earth. For software and systems development, this is uncharted territory that calls for revolutionary techniques.

  19. Space and time distribution of foci and source mechanisms of West-Bohemia/Vogtland earthquake swarms - a tool for understanding of their origin

    NASA Astrophysics Data System (ADS)

    Horálek, Josef; Čermáková, Hana; Fischer, Tomáš

    2014-05-01

    The origin of earthquake swarms remains still an enigma. The swarms typically accompany volcanic activity at the plate margins but also occur in intracontinental areas. West Bohemia-Vogtland (border area between Czech Republic and Germany) represents one of the most active intraplate earthquake-swarm regions in Europe. Above, this area is characteristic by high activity of crustal fluids. Swarm earthquakes occur persistently in the area of about 3 000 km2. However, the Novö Kostel focal zone (NK), which shows a few tens of thousands events within the last twenty years, dominates the recent seismicity of the whole region. There were swarms in 1997, 2000, 2008 and 20011 followed by reactivation in 2013, and a few tens of microswarms which forming a focal belt of about 15 x 6 km. We analyse geometry of the NK focal zone applying the double-difference method to seismicity in the period 1997 - 2013. The swarms are located close to each other in at depths from 6 to 13 km. The 2000 (MLmax = 3.3) and 2008 (MLmax = 3.8) swarms are 'twins' i.e. their hypocenters fall precisely on the same portion of the NK fault; similarly the 1997 (MLmax = 2.9), 2011 (MLmax = 3.6) and 2013 (MLmax = 2.4) swarms also occurred on the same fault segment. However, the individual swarms differ considerably in their evolution, mainly in the rate of the seismic-moment release and foci migration. Source mechanisms (in the full moment-tensor description) and their time and space variations also show different patterns. All the 2000- and 2008-swarm events are pure shears, signifying both oblique-normal and oblique-thrust faulting but the former prevails. We found a several families of source mechanisms, which fit well geometry of respective fault segments being determined on the basis of the event location: The 2000 and 2008 swarms activated the same portion of the NK fault, hence the source mechanisms are similar. The 1997 and 2011 swarms took place on two differently oriented fault segments, thus

  20. Using Animal Instincts to Design Efficient Biomedical Studies via Particle Swarm Optimization.

    PubMed

    Qiu, Jiaheng; Chen, Ray-Bing; Wang, Weichung; Wong, Weng Kee

    2014-10-01

    Particle swarm optimization (PSO) is an increasingly popular metaheuristic algorithm for solving complex optimization problems. Its popularity is due to its repeated successes in finding an optimum or a near optimal solution for problems in many applied disciplines. The algorithm makes no assumption of the function to be optimized and for biomedical experiments like those presented here, PSO typically finds the optimal solutions in a few seconds of CPU time on a garden-variety laptop. We apply PSO to find various types of optimal designs for several problems in the biological sciences and compare PSO performance relative to the differential evolution algorithm, another popular metaheuristic algorithm in the engineering literature.

  1. Particle swarm optimization using multi-information characteristics of all personal-best information.

    PubMed

    Huang, Song; Tian, Na; Wang, Yan; Ji, Zhicheng

    2016-01-01

    Convergence stagnation is the chief difficulty to solve hard optimization problems for most particle swarm optimization variants. To address this issue, a novel particle swarm optimization using multi-information characteristics of all personal-best information is developed in our research. In the modified algorithm, two positions are defined by personal-best positions and an improved cognition term with three positions of all personal-best information is used in velocity update equation to enhance the search capability. This strategy could make particles fly to a better direction by discovering useful information from all the personal-best positions. The validity of the proposed algorithm is assessed on twenty benchmark problems including unimodal, multimodal, rotated and shifted functions, and the results are compared with that obtained by some published variants of particle swarm optimization in the literature. Computational results demonstrate that the proposed algorithm finds several global optimum and high-quality solutions in most case with a fast convergence speed.

  2. Fluid-faulting interactions: Fracture-mesh and fault-valve behavior in the February 2014 Mammoth Mountain, California, earthquake swarm

    USGS Publications Warehouse

    Shelly, David R.; Taira, Taka’aki; Prejean, Stephanie; Hill, David P.; Dreger, Douglas S.

    2015-01-01

    Faulting and fluid transport in the subsurface are highly coupled processes, which may manifest seismically as earthquake swarms. A swarm in February 2014 beneath densely monitored Mammoth Mountain, California, provides an opportunity to witness these interactions in high resolution. Toward this goal, we employ massive waveform-correlation-based event detection and relative relocation, which quadruples the swarm catalog to more than 6000 earthquakes and produces high-precision locations even for very small events. The swarm's main seismic zone forms a distributed fracture mesh, with individual faults activated in short earthquake bursts. The largest event of the sequence, M 3.1, apparently acted as a fault valve and was followed by a distinct wave of earthquakes propagating ~1 km westward from the updip edge of rupture, 1–2 h later. Late in the swarm, multiple small, shallower subsidiary faults activated with pronounced hypocenter migration, suggesting that a broader fluid pressure pulse propagated through the subsurface.

  3. Particle swarm optimization for programming deep brain stimulation arrays

    NASA Astrophysics Data System (ADS)

    Peña, Edgar; Zhang, Simeng; Deyo, Steve; Xiao, YiZi; Johnson, Matthew D.

    2017-02-01

    Objective. Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Approach. Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. Main results. The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (⩽9.2%) and ROA (⩽1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n  =  3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon

  4. Microwave-based medical diagnosis using particle swarm optimization algorithm

    NASA Astrophysics Data System (ADS)

    Modiri, Arezoo

    This dissertation proposes and investigates a novel architecture intended for microwave-based medical diagnosis (MBMD). Furthermore, this investigation proposes novel modifications of particle swarm optimization algorithm for achieving enhanced convergence performance. MBMD has been investigated through a variety of innovative techniques in the literature since the 1990's and has shown significant promise in early detection of some specific health threats. In comparison to the X-ray- and gamma-ray-based diagnostic tools, MBMD does not expose patients to ionizing radiation; and due to the maturity of microwave technology, it lends itself to miniaturization of the supporting systems. This modality has been shown to be effective in detecting breast malignancy, and hence, this study focuses on the same modality. A novel radiator device and detection technique is proposed and investigated in this dissertation. As expected, hardware design and implementation are of paramount importance in such a study, and a good deal of research, analysis, and evaluation has been done in this regard which will be reported in ensuing chapters of this dissertation. It is noteworthy that an important element of any detection system is the algorithm used for extracting signatures. Herein, the strong intrinsic potential of the swarm-intelligence-based algorithms in solving complicated electromagnetic problems is brought to bear. This task is accomplished through addressing both mathematical and electromagnetic problems. These problems are called benchmark problems throughout this dissertation, since they have known answers. After evaluating the performance of the algorithm for the chosen benchmark problems, the algorithm is applied to MBMD tumor detection problem. The chosen benchmark problems have already been tackled by solution techniques other than particle swarm optimization (PSO) algorithm, the results of which can be found in the literature. However, due to the relatively high level

  5. Interhemispheric Poynting Flux Associated with Postsunset Equatorial Plasma Depletions as Observed by Swarm

    NASA Astrophysics Data System (ADS)

    Rodriguez-Zuluaga, J.; Stolle, C.; Park, J.

    2017-12-01

    By using simultaneous measurements of electric and magnetic fields gathered by the Swarm constellation, the direction of both Poynting flux and field-aligned currents (FACs) associated with topside equatorial plasma depletions (EPDs) is derived. Contrary to expectations, FACs are found to flow at the walls of EPDs from one magnetic hemisphere to the other rather than flowing away from and towards the dip equator, as has been suggested so far. In turn, an interhemispheric Poynting flux is observed to flow into the E region of the hemisphere with larger ionospheric conductivity when eastward polarisation electric field is present across the depletion. However, also westward electric field is often observed but without a change in the FACs orientation, that would preserve the direction of the Poynting flux. The interhemispheric flows show seasonal, longitudinal and local time dependence. Empirical models are used to substantiate the conclusions of this study. After these new findings, the question about the location of a generator and load in terms of electromagnetic energy flow remains open.

  6. SWARMing for a Solution: Integrating Service Learning and Peer Education into the Health Education Curriculum

    ERIC Educational Resources Information Center

    Butler, Karen L.; Jeter, Angela; Andrades, Rovaughna

    2002-01-01

    Johnson C. Smith University, one of the nation's oldest historically Black colleges and universities, has a peer education program known as Students with a Realistic Mission (SWARM). SWARM's primary focus is on HIV/AIDS, other sexually transmitted disease prevention, alcohol education, and other drug awareness. During the spring 2000 semester, we…

  7. Application of particle swarm optimization in path planning of mobile robot

    NASA Astrophysics Data System (ADS)

    Wang, Yong; Cai, Feng; Wang, Ying

    2017-08-01

    In order to realize the optimal path planning of mobile robot in unknown environment, a particle swarm optimization algorithm based on path length as fitness function is proposed. The location of the global optimal particle is determined by the minimum fitness value, and the robot moves along the points of the optimal particles to the target position. The process of moving to the target point is done with MATLAB R2014a. Compared with the standard particle swarm optimization algorithm, the simulation results show that this method can effectively avoid all obstacles and get the optimal path.

  8. Short-term forecasting of aftershock sequences, microseismicity and swarms inside the Corinth Gulf continental rift

    NASA Astrophysics Data System (ADS)

    Segou, Margarita

    2014-05-01

    Corinth Gulf (Central Greece) is the fastest continental rift in the world with extension rates 11-15 mm/yr with diverse seismic deformation including earthquakes with M greater than 6.0, several periods of increased microseismic activity, usually lasting few months and possibly related with fluid diffusion, and swarm episodes lasting few days. In this study I perform a retrospective forecast experiment between 1995-2012, focusing on the comparison between physics-based and statistical models for short term time classes. Even though Corinth gulf has been studied extensively in the past there is still today a debate whether earthquake activity is related with the existence of either a shallow dipping structure or steeply dipping normal faults. In the light of the above statement, two CRS realization are based on resolving Coulomb stress changes on specified receiver faults, expressing the aforementioned structural models, whereas the third CRS model uses optimally-oriented for failure planes. The CRS implementation accounts for stress changes following all major ruptures with M greater than 4.5 within the testing phase. I also estimate fault constitutive parameters from modeling the response to major earthquakes at the vicinity of the gulf (Aσ=0.2, stressing rate app. 0.02 bar/yr). The generic ETAS parameters are taken as the maximum likelihood estimates derived from the stochastic declustering of the modern seismicity catalog (1995-2012) with minimum triggering magnitude M2.5. I test whether the generic ETAS can efficiently describe the aftershock spatio-temporal clustering but also the evolution of swarm episodes and microseismicity. For the reason above, I implement likelihood tests to evaluate the forecasts for their spatial consistency and for the total amount of predicted versus observed events with M greater than 3.0 in 10-day time windows during three distinct evaluation phases; the first evaluation phase focuses on the Aigio 1995 aftershock sequence (15

  9. UAV Swarm Operational Risk Assessment System

    DTIC Science & Technology

    2015-09-01

    a SIPRNET connection. For practicality in development of this prototype, the interface was created using the MATLAB GUI language . By design, the use ...and Budget, Paperwork Reduction Project (0704-0188) Washington DC 20503. 1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE September 2015 3...discrete-event simulation of UAV swarm attacks using ExtendSim, statistical analysis of the simulation data using Minitab, and a graphical user interface

  10. Optimization of multi-objective micro-grid based on improved particle swarm optimization algorithm

    NASA Astrophysics Data System (ADS)

    Zhang, Jian; Gan, Yang

    2018-04-01

    The paper presents a multi-objective optimal configuration model for independent micro-grid with the aim of economy and environmental protection. The Pareto solution set can be obtained by solving the multi-objective optimization configuration model of micro-grid with the improved particle swarm algorithm. The feasibility of the improved particle swarm optimization algorithm for multi-objective model is verified, which provides an important reference for multi-objective optimization of independent micro-grid.

  11. Tidal Turbine Array Optimization Based on the Discrete Particle Swarm Algorithm

    NASA Astrophysics Data System (ADS)

    Wu, Guo-wei; Wu, He; Wang, Xiao-yong; Zhou, Qing-wei; Liu, Xiao-man

    2018-06-01

    In consideration of the resource wasted by unreasonable layout scheme of tidal current turbines, which would influence the ratio of cost and power output, particle swarm optimization algorithm is introduced and improved in the paper. In order to solve the problem of optimal array of tidal turbines, the discrete particle swarm optimization (DPSO) algorithm has been performed by re-defining the updating strategies of particles' velocity and position. This paper analyzes the optimization problem of micrositing of tidal current turbines by adjusting each turbine's position, where the maximum value of total electric power is obtained at the maximum speed in the flood tide and ebb tide. Firstly, the best installed turbine number is generated by maximizing the output energy in the given tidal farm by the Farm/Flux and empirical method. Secondly, considering the wake effect, the reasonable distance between turbines, and the tidal velocities influencing factors in the tidal farm, Jensen wake model and elliptic distribution model are selected for the turbines' total generating capacity calculation at the maximum speed in the flood tide and ebb tide. Finally, the total generating capacity, regarded as objective function, is calculated in the final simulation, thus the DPSO could guide the individuals to the feasible area and optimal position. The results have been concluded that the optimization algorithm, which increased 6.19% more recourse output than experience method, can be thought as a good tool for engineering design of tidal energy demonstration.

  12. The Integration of Multimedia and Field Experience.

    ERIC Educational Resources Information Center

    Dawson, George

    A professor of science education at Florida State University shares his experiences with the growth of the field of environmental education and the problems inherent in trying to teach formal environmental education outdoors. Although field experience is best, it must be limited in most situations since logistics get in the way. Technology can…

  13. Youth on YouTube as Smart Swarms

    ERIC Educational Resources Information Center

    Duncum, Paul

    2014-01-01

    Viewing YouTube culture as a creative, collaborative process similar to animal swarms can help art educators understand and embrace youth's digital practices. School-age youth are among the most prolific contributors to YouTube, not just as viewers, but also as producers. Even preschoolers now produce videos (McClure, 2010). So pervasive,…

  14. An Improved Co-evolutionary Particle Swarm Optimization for Wireless Sensor Networks with Dynamic Deployment

    PubMed Central

    Wang, Xue; Wang, Sheng; Ma, Jun-Jie

    2007-01-01

    The effectiveness of wireless sensor networks (WSNs) depends on the coverage and target detection probability provided by dynamic deployment, which is usually supported by the virtual force (VF) algorithm. However, in the VF algorithm, the virtual force exerted by stationary sensor nodes will hinder the movement of mobile sensor nodes. Particle swarm optimization (PSO) is introduced as another dynamic deployment algorithm, but in this case the computation time required is the big bottleneck. This paper proposes a dynamic deployment algorithm which is named “virtual force directed co-evolutionary particle swarm optimization” (VFCPSO), since this algorithm combines the co-evolutionary particle swarm optimization (CPSO) with the VF algorithm, whereby the CPSO uses multiple swarms to optimize different components of the solution vectors for dynamic deployment cooperatively and the velocity of each particle is updated according to not only the historical local and global optimal solutions, but also the virtual forces of sensor nodes. Simulation results demonstrate that the proposed VFCPSO is competent for dynamic deployment in WSNs and has better performance with respect to computation time and effectiveness than the VF, PSO and VFPSO algorithms.

  15. Migrating swarms of brittle-failure earthquakes in the lower crust beneath Mammoth Mountain, California

    USGS Publications Warehouse

    Shelly, D.R.; Hill, D.P.

    2011-01-01

    Brittle-failure earthquakes in the lower crust, where high pressures and temperatures would typically promote ductile deformation, are relatively rare but occasionally observed beneath active volcanic centers. Where they occur, these earthquakes provide a rare opportunity to observe volcanic processes in the lower crust, such as fluid injection and migration, which may induce brittle faulting under these conditions. Here, we examine recent short-duration earthquake swarms deep beneath the southwestern margin of Long Valley Caldera, near Mammoth Mountain. We focus in particular on a swarm that occurred September 29-30, 2009. To maximally illuminate the spatial-temporal progression, we supplement catalog events by detecting additional small events with similar waveforms in the continuous data, achieving up to a 10-fold increase in the number of locatable events. We then relocate all events, using cross-correlation and a double-difference algorithm. We find that the 2009 swarm exhibits systematically decelerating upward migration, with hypocenters shallowing from 21 to 19 km depth over approximately 12 hours. This relatively high migration rate, combined with a modest maximum magnitude of 1.4 in this swarm, suggests the trigger might be ascending CO2 released from underlying magma.

  16. Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

    PubMed Central

    Abdulameer, Mohammed Hasan; Othman, Zulaiha Ali

    2014-01-01

    Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO) technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM). In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented. PMID:24790584

  17. The effect of antibiotics on swimming and swarming motility of multidrug-resistant Salmonella enterica serovar Typhimurium

    USDA-ARS?s Scientific Manuscript database

    Motile bacteria can employ one or more different strategies to move, including swimming, swarming, twitching, gliding, sliding, and darting. Swimming is considered the movement of individual bacteria through a liquid or semi-solid medium, while swarming is the concerted movement of a group of bacte...

  18. Kinetic and fluid descriptions of charged particle swarms in gases and nonpolar fluids: Theory and applications

    NASA Astrophysics Data System (ADS)

    Dujko, Sasa

    2016-09-01

    In this work we review the progress achieved over the last few decades in the fundamental kinetic theory of charged particle swarms with the focus on numerical techniques for the solution of Boltzmann's equation for electrons, as well as on the development of fluid models. We present a time-dependent multi term solution of Boltzmann's equation valid for electrons and positrons in varying configurations of electric and magnetic fields. The capacity of a theory and associated computer code will be illustrated by considering the heating mechanisms for electrons in radio-frequency electric and magnetic fields in a collision-dominated regime under conditions when electron transport is greatly affected by non-conservative collisions. The kinetic theory for solving the Boltzmann equation will be followed by a fluid equation description of charged particle swarms in both the hydrodynamic and non-hydrodynamic regimes, highlighting (i) the utility of momentum transfer theory for evaluating collisional terms in the balance equations and (ii) closure assumptions and approximations. The applications of this theory are split into three sections. First, we will present our 1.5D model of Resistive Plate Chambers (RPCs) which are used for timing and triggering purposes in many high energy physics experiments. The model is employed to study the avalanche to streamer transition in RPCs under the influence of space charge effects and photoionization. Second, we will discuss our high-order fluid model for streamer discharges. Particular emphases will be placed on the correct implementation of transport data in streamer models as well as on the evaluation of the mean-energy-dependent collision rates for electrons required as an input in the high-order fluid model. In the last segment of this work, we will present our model to study the avalanche to streamer transition in non-polar fluids. Using a Monte Carlo simulation technique we have calculated transport coefficients for electrons in

  19. Multi-Objective Mission Route Planning Using Particle Swarm Optimization

    DTIC Science & Technology

    2002-03-01

    solutions to complex problems using particles that interact with each other. Both Particle Swarm Optimization (PSO) and the Ant System (AS) have been...EXPERIMENTAL DESING PROCESS..............................................................55 5.1. Introduction...46 18. Phenotype level particle interaction

  20. The 2015 Fillmore earthquake swarm and possible crustal deformation mechanisms near the bottom of the eastern Ventura Basin, California

    USGS Publications Warehouse

    Hauksson, Egill; Andrews, Jennifer; Plesch, Andreas; Shaw, John H.; Shelly, David R.

    2016-01-01

    The 2015 Fillmore swarm occurred about 6 km west of the city of Fillmore in Ventura, California, and was located beneath the eastern part of the actively subsiding Ventura basin at depths from 11.8 to 13.8 km, similar to two previous swarms in the area. Template‐matching event detection showed that it started on 5 July 2015 at 2:21 UTC with an M∼1.0 earthquake. The swarm exhibited unusual episodic spatial and temporal migrations and unusual diversity in the nodal planes of the focal mechanisms as compared to the simple hypocenter‐defined plane. It was also noteworthy because it consisted of >1400 events of M≥0.0, with M 2.8 being the largest event. We suggest that fluids released by metamorphic dehydration processes, migration of fluids along a detachment zone, and cascading asperity failures caused this prolific earthquake swarm, but other mechanisms (such as simple mainshock–aftershock stress triggering or a regional aseismic creep event) are less likely. Dilatant strengthening may be a mechanism that causes the temporal decay of the swarm as pore‐pressure drop increased the effective normal stress, and counteracted the instability driving the swarm.

  1. Particle swarm optimization of ascent trajectories of multistage launch vehicles

    NASA Astrophysics Data System (ADS)

    Pontani, Mauro

    2014-02-01

    Multistage launch vehicles are commonly employed to place spacecraft and satellites in their operational orbits. If the rocket characteristics are specified, the optimization of its ascending trajectory consists of determining the optimal control law that leads to maximizing the final mass at orbit injection. The numerical solution of a similar problem is not trivial and has been pursued with different methods, for decades. This paper is concerned with an original approach based on the joint use of swarming theory and the necessary conditions for optimality. The particle swarm optimization technique represents a heuristic population-based optimization method inspired by the natural motion of bird flocks. Each individual (or particle) that composes the swarm corresponds to a solution of the problem and is associated with a position and a velocity vector. The formula for velocity updating is the core of the method and is composed of three terms with stochastic weights. As a result, the population migrates toward different regions of the search space taking advantage of the mechanism of information sharing that affects the overall swarm dynamics. At the end of the process the best particle is selected and corresponds to the optimal solution to the problem of interest. In this work the three-dimensional trajectory of the multistage rocket is assumed to be composed of four arcs: (i) first stage propulsion, (ii) second stage propulsion, (iii) coast arc (after release of the second stage), and (iv) third stage propulsion. The Euler-Lagrange equations and the Pontryagin minimum principle, in conjunction with the Weierstrass-Erdmann corner conditions, are employed to express the thrust angles as functions of the adjoint variables conjugate to the dynamics equations. The use of these analytical conditions coming from the calculus of variations leads to obtaining the overall rocket dynamics as a function of seven parameters only, namely the unknown values of the initial state

  2. Earthquake statistics, spatiotemporal distribution of foci and source mechanisms as a key to understanding of causes leading to the West Bohemia/Vogtland earthquake swarms

    NASA Astrophysics Data System (ADS)

    Horalek, Josef; Jakoubkova, Hana

    2017-04-01

    The origin of earthquake swarms is still unclear. The swarms typically occur at the plate margins but also in intracontinental areas. West Bohemia-Vogtland represents one of the most active intraplate earthquake-swarm areas in Europe. It is characterised by a frequent reoccurrence of ML < 4.0 swarms and by high activity of crustal fluids. The Nový Kostel focal zone (NK) dominates the recent seismicity of the whole region. There were swarms in 1997, 2000, 2008 and 20011 followed by reactivation in 2013 which forming a focal belt of about 15 x 6 km, focal depths vary from 6 to 15 km. An exceptional non-swarm activity (mainshock-aftershock sequences) up to magnitudes ML = 4.5, stroke the region in May to August 2014, the events were also located in the NK swarm-focal belt. We analysed geometry of the NK focal zone applying the double-difference method to seismicity in the period 1997 - 2014. The swarms are located close to each other at depths between 6 and 13 km, the 2014 maishock-aftershock sequences among them. The 2000 and 2008 swarms were located on the same portion of the NK fault, similarly the swarms of 1997, 2011 and 2013 also occurred on the same fault segment. Other fault segment hosted three mainshock-aftershock sequences of 2014. The individual swarms differ considerably in their evolution, mainly in the rate of the seismic-moment release and foci migration. The frequency-magnitude distributions of all the swarms show bimodal-like character: the most events obey the b-value = 1.0 distribution, however, a group of the largest events ( ML > 2.8) depart significantly from it. Furthermore, we disclose that all the ML > 2.8 swarm events, which occurred in the given time span, are located in a few dense clusters. It implies that the most of seismic energy in the individual swarms has been released in step by step rupturing of one or a few asperities. The source mechanisms have been retrieved in the full moment-tensor description (MT). The mechanism patters of

  3. Adaptive routing in wireless communication networks using swarm intelligence

    NASA Technical Reports Server (NTRS)

    Arabshahi, P.; Gray, A.; Kassabalidis, I.; Das, A.; Narayanan, S.; Sharkawi, M. El; Marks, R. J.

    2001-01-01

    In this paper we focus on the network routing problem, and survey swarm intelligent approaches for its efficient solution, after a brief overview of power-aware routing schemes, which are important in the network examples outlined above.

  4. 2-Heptyl-4-Quinolone, a Precursor of the Pseudomonas Quinolone Signal Molecule, Modulates Swarming Motility in Pseudomonas aeruginosa▿

    PubMed Central

    Ha, Dae-Gon; Merritt, Judith H.; Hampton, Thomas H.; Hodgkinson, James T.; Janecek, Matej; Spring, David R.; Welch, Martin; O'Toole, George A.

    2011-01-01

    Pseudomonas aeruginosa is an opportunistic pathogen capable of group behaviors, including biofilm formation and swarming motility. These group behaviors are regulated by both the intracellular signaling molecule c-di-GMP and acylhomoserine lactone quorum-sensing systems. Here, we show that the Pseudomonas quinolone signal (PQS) system also contributes to the regulation of swarming motility. Specifically, our data indicate that 2-heptyl-4-quinolone (HHQ), a precursor of PQS, likely induces the production of the phenazine-1-carboxylic acid (PCA), which in turn acts via an as-yet-unknown downstream mechanism to repress swarming motility. We show that this HHQ- and PCA-dependent swarming repression is apparently independent of changes in global levels of c-di-GMP, suggesting complex regulation of this group behavior. PMID:21965567

  5. Full glowworm swarm optimization algorithm for whole-set orders scheduling in single machine.

    PubMed

    Yu, Zhang; Yang, Xiaomei

    2013-01-01

    By analyzing the characteristics of whole-set orders problem and combining the theory of glowworm swarm optimization, a new glowworm swarm optimization algorithm for scheduling is proposed. A new hybrid-encoding schema combining with two-dimensional encoding and random-key encoding is given. In order to enhance the capability of optimal searching and speed up the convergence rate, the dynamical changed step strategy is integrated into this algorithm. Furthermore, experimental results prove its feasibility and efficiency.

  6. Competitive Swarm Optimizer Based Gateway Deployment Algorithm in Cyber-Physical Systems

    PubMed Central

    Huang, Shuqiang; Tao, Ming

    2017-01-01

    Wireless sensor network topology optimization is a highly important issue, and topology control through node selection can improve the efficiency of data forwarding, while saving energy and prolonging lifetime of the network. To address the problem of connecting a wireless sensor network to the Internet in cyber-physical systems, here we propose a geometric gateway deployment based on a competitive swarm optimizer algorithm. The particle swarm optimization (PSO) algorithm has a continuous search feature in the solution space, which makes it suitable for finding the geometric center of gateway deployment; however, its search mechanism is limited to the individual optimum (pbest) and the population optimum (gbest); thus, it easily falls into local optima. In order to improve the particle search mechanism and enhance the search efficiency of the algorithm, we introduce a new competitive swarm optimizer (CSO) algorithm. The CSO search algorithm is based on an inter-particle competition mechanism and can effectively avoid trapping of the population falling into a local optimum. With the improvement of an adaptive opposition-based search and its ability to dynamically parameter adjustments, this algorithm can maintain the diversity of the entire swarm to solve geometric K-center gateway deployment problems. The simulation results show that this CSO algorithm has a good global explorative ability as well as convergence speed and can improve the network quality of service (QoS) level of cyber-physical systems by obtaining a minimum network coverage radius. We also find that the CSO algorithm is more stable, robust and effective in solving the problem of geometric gateway deployment as compared to the PSO or Kmedoids algorithms. PMID:28117735

  7. Competitive Swarm Optimizer Based Gateway Deployment Algorithm in Cyber-Physical Systems.

    PubMed

    Huang, Shuqiang; Tao, Ming

    2017-01-22

    Wireless sensor network topology optimization is a highly important issue, and topology control through node selection can improve the efficiency of data forwarding, while saving energy and prolonging lifetime of the network. To address the problem of connecting a wireless sensor network to the Internet in cyber-physical systems, here we propose a geometric gateway deployment based on a competitive swarm optimizer algorithm. The particle swarm optimization (PSO) algorithm has a continuous search feature in the solution space, which makes it suitable for finding the geometric center of gateway deployment; however, its search mechanism is limited to the individual optimum (pbest) and the population optimum (gbest); thus, it easily falls into local optima. In order to improve the particle search mechanism and enhance the search efficiency of the algorithm, we introduce a new competitive swarm optimizer (CSO) algorithm. The CSO search algorithm is based on an inter-particle competition mechanism and can effectively avoid trapping of the population falling into a local optimum. With the improvement of an adaptive opposition-based search and its ability to dynamically parameter adjustments, this algorithm can maintain the diversity of the entire swarm to solve geometric K -center gateway deployment problems. The simulation results show that this CSO algorithm has a good global explorative ability as well as convergence speed and can improve the network quality of service (QoS) level of cyber-physical systems by obtaining a minimum network coverage radius. We also find that the CSO algorithm is more stable, robust and effective in solving the problem of geometric gateway deployment as compared to the PSO or Kmedoids algorithms.

  8. A Secular Variation Model for Igrf-12 Based on Swarm Data and Inverse Geodynamo Modelling

    NASA Astrophysics Data System (ADS)

    Fournier, A.; Aubert, J.; Erwan, T.

    2014-12-01

    We are proposing a secular variation candidate model for the 12th generation of the international geomagnetic reference field, spanning the years 2015-2020. The novelty of our approach stands in the initialization of a 5-yr long integration of a numerical model of Earth's dynamo by means of inverse geodynamo modelling, as introduced by Aubert (GJI, 2014). This inverse technique combines the information coming from the observations (in the form of an instantaneous estimate of the Gauss coefficients for the magnetic field and its secular variation) with that coming from the multivariate statistics of a free run of a numerical model of the geodynamo. The Gauss coefficients and their error covariance properties are determined from Swarm data along the lines detailed by Thébault et al. (EPS, 2010). The numerical model of the geodynamo is the so-called Coupled Earth Dynamo model (Aubert et al., Nature, 2013), whose variability possesses a strong level of similarity with that of the geomagnetic field. We illustrate and assess the potential of this methodology by applying it to recent time intervals, with an initialization based on CHAMP data, and conclude by presenting our SV candidate, whose initialization is based on the 1st year of Swarm data This work is supported by the French "Agence Nationale de la Recherche" under the grant ANR-11-BS56-011 (http://avsgeomag.ipgp.fr) and by the CNES. References: Aubert, J., Geophys. J. Int. 197, 1321-1334, 2014, doi: 10.1093/gji/ggu064 Aubert, J., Finlay, C., Fournier, F. Nature 502, 219-223, 2013, doi: 10.1038/nature12574 Thébault E. , A. Chulliat, S. Maus, G. Hulot, B. Langais, A. Chambodut and M. Menvielle, Earth Planets Space, Vol. 62 (No. 10), pp. 753-763, 2010.

  9. Detection of Subtle Hydromechanical Medium Changes Caused By a Small-Magnitude Earthquake Swarm in NE Brazil

    NASA Astrophysics Data System (ADS)

    D'Hour, V.; Schimmel, M.; Do Nascimento, A. F.; Ferreira, J. M.; Lima Neto, H. C.

    2016-04-01

    Ambient noise correlation analyses are largely used in seismology to map heterogeneities and to monitor the temporal evolution of seismic velocity changes associated mostly with stress field variations and/or fluid movements. Here we analyse a small earthquake swarm related to a main mR 3.7 intraplate earthquake in North-East of Brazil to study the corresponding post-seismic effects on the medium. So far, post-seismic effects have been observed mainly for large magnitude events. In our study, we show that we were able to detect localized structural changes even for a small earthquake swarm in an intraplate setting. Different correlation strategies are presented and their performances are also shown. We compare the classical auto-correlation with and without pre-processing, including 1-bit normalization and spectral whitening, and the phase auto-correlation. The worst results were obtained for the pre-processed data due to the loss of waveform details. The best results were achieved with the phase cross-correlation which is amplitude unbiased and sensitive to small amplitude changes as long as there exist waveform coherence superior to other unrelated signals and noise. The analysis of 6 months of data using phase auto-correlation and cross-correlation resulted in the observation of a progressive medium change after the major recorded event. The progressive medium change is likely related to the swarm activity through opening new path ways for pore fluid diffusion. We further observed for the auto-correlations a lag time frequency-dependent change which likely indicates that the medium change is localized in depth. As expected, the main change is observed along the fault.

  10. Swarming and the Future of Warfare

    DTIC Science & Technology

    2005-01-01

    the horse archers swarmed around the square and began delivering arrows and spears from standoff range. As Plutarch described it, "The Parthians thus...cutting it off, surrounded and annihilated it. The harassment of the main body continued until nightfall, when the darkness prevented 2 Plutarch ...Plaster, John L. SOG: The Secret Wars of America’s Commandos in Vietnam. New York, NY: Penguin Group, 1997. Plutarch . Selected Lives from the Lives of Noble

  11. Application of hybrid artificial fish swarm algorithm based on similar fragments in VRP

    NASA Astrophysics Data System (ADS)

    Che, Jinnuo; Zhou, Kang; Zhang, Xueyu; Tong, Xin; Hou, Lingyun; Jia, Shiyu; Zhen, Yiting

    2018-03-01

    Focused on the issue that the decrease of convergence speed and the precision of calculation at the end of the process in Artificial Fish Swarm Algorithm(AFSA) and instability of results, a hybrid AFSA based on similar fragments is proposed. Traditional AFSA enjoys a lot of obvious advantages in solving complex optimization problems like Vehicle Routing Problem(VRP). AFSA have a few limitations such as low convergence speed, low precision and instability of results. In this paper, two improvements are introduced. On the one hand, change the definition of the distance for artificial fish, as well as increase vision field of artificial fish, and the problem of speed and precision can be improved when solving VRP. On the other hand, mix artificial bee colony algorithm(ABC) into AFSA - initialize the population of artificial fish by the ABC, and it solves the problem of instability of results in some extend. The experiment results demonstrate that the optimal solution of the hybrid AFSA is easier to approach the optimal solution of the standard database than the other two algorithms. In conclusion, the hybrid algorithm can effectively solve the problem that instability of results and decrease of convergence speed and the precision of calculation at the end of the process.

  12. Industry Cluster's Adaptive Co-competition Behavior Modeling Inspired by Swarm Intelligence

    NASA Astrophysics Data System (ADS)

    Xiang, Wei; Ye, Feifan

    Adaptation helps the individual enterprise to adjust its behavior to uncertainties in environment and hence determines a healthy growth of both the individuals and the whole industry cluster as well. This paper is focused on the study on co-competition adaptation behavior of industry cluster, which is inspired by swarm intelligence mechanisms. By referencing to ant cooperative transportation and ant foraging behavior and their related swarm intelligence approaches, the cooperative adaptation and competitive adaptation behavior are studied and relevant models are proposed. Those adaptive co-competition behaviors model can be integrated to the multi-agent system of industry cluster to make the industry cluster model more realistic.

  13. Combining CHAMP and Swarm Satellite Data to Invert the Lithospheric Magnetic Field in the Tibetan Plateau.

    PubMed

    Qiu, Yaodong; Wang, Zhengtao; Jiang, Weiping; Zhang, Bingbing; Li, Fupeng; Guo, Fei

    2017-01-26

    CHAMP and Swarm satellite magnetic data are combined to establish the lithospheric magnetic field over the Tibetan Plateau at satellite altitude by using zonal revised spherical cap harmonic analysis (R-SCHA). These data are integrated with geological structures data to analyze the relationship between magnetic anomaly signals and large-scale geological tectonic over the Tibetan Plateau and to explore the active tectonic region based on the angle of the magnetic anomaly. Results show that the model fitting error is small for a layer 250-500 km high, and the RMSE of the horizontal and radial geomagnetic components is better than 0.3 nT. The proposed model can accurately describe medium- to long-scale lithospheric magnetic anomalies. Analysis indicates that a negative magnetic anomaly in the Tibetan Plateau significantly differs with a positive magnetic anomaly in the surrounding area, and the boundary of the positive and negative regions is generally consistent with the geological tectonic boundary in the plateau region. Significant differences exist between the basement structures of the hinterland of the plateau and the surrounding area. The magnetic anomaly in the Central and Western Tibetan Plateau shows an east-west trend, which is identical to the direction of the geological structures. The magnetic anomaly in the eastern part is arc-shaped and extends along the northeast direction. Its direction is significantly different from the trend of the geological structures. The strongest negative anomaly is located in the Himalaya block, with a central strength of up to -9 nT at a height of 300 km. The presence of a strong negative anomaly implies that the Curie isotherm in this area is relatively shallow and deep geological tectonic activity may exist.

  14. Combining CHAMP and Swarm Satellite Data to Invert the Lithospheric Magnetic Field in the Tibetan Plateau

    PubMed Central

    Qiu, Yaodong; Wang, Zhengtao; Jiang, Weiping; Zhang, Bingbing; Li, Fupeng; Guo, Fei

    2017-01-01

    CHAMP and Swarm satellite magnetic data are combined to establish the lithospheric magnetic field over the Tibetan Plateau at satellite altitude by using zonal revised spherical cap harmonic analysis (R-SCHA). These data are integrated with geological structures data to analyze the relationship between magnetic anomaly signals and large-scale geological tectonic over the Tibetan Plateau and to explore the active tectonic region based on the angle of the magnetic anomaly. Results show that the model fitting error is small for a layer 250–500 km high, and the RMSE of the horizontal and radial geomagnetic components is better than 0.3 nT. The proposed model can accurately describe medium- to long-scale lithospheric magnetic anomalies. Analysis indicates that a negative magnetic anomaly in the Tibetan Plateau significantly differs with a positive magnetic anomaly in the surrounding area, and the boundary of the positive and negative regions is generally consistent with the geological tectonic boundary in the plateau region. Significant differences exist between the basement structures of the hinterland of the plateau and the surrounding area. The magnetic anomaly in the Central and Western Tibetan Plateau shows an east–west trend, which is identical to the direction of the geological structures. The magnetic anomaly in the eastern part is arc-shaped and extends along the northeast direction. Its direction is significantly different from the trend of the geological structures. The strongest negative anomaly is located in the Himalaya block, with a central strength of up to −9 nT at a height of 300 km. The presence of a strong negative anomaly implies that the Curie isotherm in this area is relatively shallow and deep geological tectonic activity may exist. PMID:28134755

  15. The Absolute Vector Magnetometers on Board Swarm, Lessons Learned From Two Years in Space.

    NASA Astrophysics Data System (ADS)

    Hulot, G.; Leger, J. M.; Vigneron, P.; Brocco, L.; Olsen, N.; Jager, T.; Bertrand, F.; Fratter, I.; Sirol, O.; Lalanne, X.

    2015-12-01

    ESA's Swarm satellites carry 4He absolute magnetometers (ASM), designed by CEA-Léti and developed in partnership with CNES. These instruments are the first-ever space-born magnetometers to use a common sensor to simultaneously deliver 1Hz independent absolute scalar and vector readings of the magnetic field. They have provided the very high accuracy scalar field data nominally required by the mission (for both science and calibration purposes, since each satellite also carries a low noise high frequency fluxgate magnetometer designed by DTU), but also very useful experimental absolute vector data. In this presentation, we will report on the status of the instruments, as well as on the various tests and investigations carried out using these experimental data since launch in November 2013. In particular, we will illustrate the advantages of flying ASM instruments on space-born magnetic missions for nominal data quality checks, geomagnetic field modeling and science objectives.

  16. The 2010-2011 Microearthquake Swarm in Krýsuvík, SW Iceland: Was it Triggered by Crustal Magma Injection?

    NASA Astrophysics Data System (ADS)

    Liu, J.; Michael, F.; Hager, B. H.

    2013-12-01

    Iceland, the on-land continuation of the Mid-Atlantic Ridge, is the result of the interaction between the Mid-Atlantic Ridge and the North-Atlantic mantle plume. The superposition and relative motion of the spreading plate boundary over the mantle plume are manifested by the volcanism and seismicity in Iceland. The Krýsuvík geothermal field is one of the most active geothermal fields in southwest Iceland. In 2010, Massachusetts Institute of Technology, Reykjanes University, Uppsala University, and the Iceland Geosurvey (ISOR) deployed 38 temporary seismic stations on the Reykjanes Peninsula. Using data from 18 of the temporary seismic stations and from 5 stations of the South Iceland Lowland network around Krýsuvík, we captured an earthquake swarm that occurred between November, 2010 and February, 2011. We applied double difference tomography to relocate the events and determine the velocity structure in the region. Activity is clustered around the center of the Krýsuvík volcano system. Our seismic tomography result indicates a low velocity zone at a depth of about 6 km, right under the earthquake swarm. We consider that this low velocity zone contains some crustal magma that may be the thermal source for the geothermal field. At the same time, our relocated events delineate faults above and around this magma chamber. The system is within the stress field of a combination of left-lateral shear and extension; the majority of the strike-slip faults are right-lateral and most dip-slip faults are normal faults. Published geodetic measurements for the time period between 2009 and 2012 show a few centimeters uplift and extension in the area of the seismic swarm. We modeled the observed deformation using the Coulomb 3.3 software (U.S. Geological Survey). Our result indicates that a Mogi source of about 20×10^6 m^3 at a depth of about 6 km, consistent with the location and size of the tomography result, can explain the main deformation. The normal and the right

  17. Bacterial Swarms Recruit Cargo Bacteria To Pave the Way in Toxic Environments

    PubMed Central

    Finkelshtein, Alin; Roth, Dalit

    2015-01-01

    ABSTRACT Swarming bacteria are challenged by the need to invade hostile environments. Swarms of the flagellated bacterium Paenibacillus vortex can collectively transport other microorganisms. Here we show that P. vortex can invade toxic environments by carrying antibiotic-degrading bacteria; this transport is mediated by a specialized, phenotypic subpopulation utilizing a process not dependent on cargo motility. Swarms of beta-lactam antibiotic (BLA)-sensitive P. vortex used beta-lactamase-producing, resistant, cargo bacteria to detoxify BLAs in their path. In the presence of BLAs, both transporter and cargo bacteria gained from this temporary cooperation; there was a positive correlation between BLA resistance and dispersal. P. vortex transported only the most beneficial antibiotic-resistant cargo (including environmental and clinical isolates) in a sustained way. P. vortex displayed a bet-hedging strategy that promoted the colonization of nontoxic niches by P. vortex alone; when detoxifying cargo bacteria were not needed, they were lost. This work has relevance for the dispersal of antibiotic-resistant microorganisms and for strategies for asymmetric cooperation with agricultural and medical implications. PMID:25968641

  18. Swarming mechanisms in the yellow fever mosquito: aggregation pheromones involved in the mating behavior of Aedes aegypti

    USDA-ARS?s Scientific Manuscript database

    Mosquitoes of various species mate in swarms comprised of tens to thousands flying males. Yet little information is known about mosquito swarming mechanism. Discovering chemical cues involved in mosquito biology leads to better adaptation of disease control interventions. In this study, we aimed ...

  19. Damage during the 6-24 February 2017 Ayvacık (Çanakkale) earthquake swarm

    NASA Astrophysics Data System (ADS)

    Livaoğlu, Ramazan; Ömer Timurağaoğlu, Mehmet; Serhatoğlu, Cavit; Sami Döven, Mahmud

    2018-03-01

    On 6 February 2017 an earthquake swarm began at the western end of Turkey. This was the first recorded swarm in the Çanakkale region since continuous seismic monitoring began in 1970. The number of earthquakes located increased during the following 10 days. This paper describes the output of a survey carried out in the earthquake-prone towns in the area of Ayvacık, Çanakkale, Turkey, in February 2017 after the earthquakes. Observations of traditional buildings were made on site at the rural area of Ayvacık. A description of the main structural features and their effects on the most frequently viewed damage modes were made according to in-plane, out-of-plane behavior of the wall regarding construction practice, connection type, etc. It was found that there were no convenient connections like cavity ties or sufficient mortar strength resulting in decreased and/or lack of lateral load bearing capacity of the wall. Furthermore, distribution maps of damaged/undamaged buildings according to villages, damage ratios, structures and damage levels are generated. Distribution maps showed that damage ratio of structures is higher in villages close to epicenter and decrease away from epicenter except Gülpınar, where past experiences and development level affect the construction quality.

  20. Topical treatment of herpes simplex virus infection with enzymatically created siRNA swarm.

    PubMed

    Paavilainen, Henrik; Lehtinen, Jenni; Romanovskaya, Alesia; Nygårdas, Michaela; Bamford, Dennis H; Poranen, Minna M; Hukkanen, Veijo

    2017-01-01

    Herpes simplex virus (HSV) is a common human pathogen. Despite current antivirals, it causes a significant medical burden. Drug resistant strains exist and they are especially prevalent in immunocompromised patients and in HSV eye infections. New treatment modalities are needed. BALB/c mice were corneally infected with HSV and subsequently treated with a swarm of enzymatically created, Dicer-substrate small interfering RNA (siRNA) molecules that targeted the HSV gene UL29. Two infection models were used, one in which the infection was predominantly peripheral and another in which it spread to the central nervous system. Mouse survival, as well as viral spread, load, latency and peripheral shedding, was studied. The anti-HSV-UL29 siRNA swarm alleviated HSV infection symptoms, inhibited viral shedding and replication and had a favourable effect on mouse survival. Treatment with anti-HSV-UL29 siRNA swarm reduced symptoms and viral spread in HSV infection of mice and also inhibited local viral replication in mouse corneas.