A swarm intelligence framework for reconstructing gene networks: searching for biologically plausible architectures.

PubMed

Kentzoglanakis, Kyriakos; Poole, Matthew

2012-01-01

In this paper, we investigate the problem of reverse engineering the topology of gene regulatory networks from temporal gene expression data. We adopt a computational intelligence approach comprising swarm intelligence techniques, namely particle swarm optimization (PSO) and ant colony optimization (ACO). In addition, the recurrent neural network (RNN) formalism is employed for modeling the dynamical behavior of gene regulatory systems. More specifically, ACO is used for searching the discrete space of network architectures and PSO for searching the corresponding continuous space of RNN model parameters. We propose a novel solution construction process in the context of ACO for generating biologically plausible candidate architectures. The objective is to concentrate the search effort into areas of the structure space that contain architectures which are feasible in terms of their topological resemblance to real-world networks. The proposed framework is initially applied to the reconstruction of a small artificial network that has previously been studied in the context of gene network reverse engineering. Subsequently, we consider an artificial data set with added noise for reconstructing a subnetwork of the genetic interaction network of S. cerevisiae (yeast). Finally, the framework is applied to a real-world data set for reverse engineering the SOS response system of the bacterium Escherichia coli. Results demonstrate the relative advantage of utilizing problem-specific knowledge regarding biologically plausible structural properties of gene networks over conducting a problem-agnostic search in the vast space of network architectures.

Research on bulbous bow optimization based on the improved PSO algorithm

NASA Astrophysics Data System (ADS)

Zhang, Sheng-long; Zhang, Bao-ji; Tezdogan, Tahsin; Xu, Le-ping; Lai, Yu-yang

2017-08-01

In order to reduce the total resistance of a hull, an optimization framework for the bulbous bow optimization was presented. The total resistance in calm water was selected as the objective function, and the overset mesh technique was used for mesh generation. RANS method was used to calculate the total resistance of the hull. In order to improve the efficiency and smoothness of the geometric reconstruction, the arbitrary shape deformation (ASD) technique was introduced to change the shape of the bulbous bow. To improve the global search ability of the particle swarm optimization (PSO) algorithm, an improved particle swarm optimization (IPSO) algorithm was proposed to set up the optimization model. After a series of optimization analyses, the optimal hull form was found. It can be concluded that the simulation based design framework built in this paper is a promising method for bulbous bow optimization.

Game theoretic wireless resource allocation for H.264 MGS video transmission over cognitive radio networks

NASA Astrophysics Data System (ADS)

Fragkoulis, Alexandros; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2015-03-01

We propose a method for the fair and efficient allocation of wireless resources over a cognitive radio system network to transmit multiple scalable video streams to multiple users. The method exploits the dynamic architecture of the Scalable Video Coding extension of the H.264 standard, along with the diversity that OFDMA networks provide. We use a game-theoretic Nash Bargaining Solution (NBS) framework to ensure that each user receives the minimum video quality requirements, while maintaining fairness over the cognitive radio system. An optimization problem is formulated, where the objective is the maximization of the Nash product while minimizing the waste of resources. The problem is solved by using a Swarm Intelligence optimizer, namely Particle Swarm Optimization. Due to the high dimensionality of the problem, we also introduce a dimension-reduction technique. Our experimental results demonstrate the fairness imposed by the employed NBS framework.

Fuzzy distributed cooperative tracking for a swarm of unmanned aerial vehicles with heterogeneous goals

NASA Astrophysics Data System (ADS)

Kladis, Georgios P.; Menon, Prathyush P.; Edwards, Christopher

2016-12-01

This article proposes a systematic analysis for a tracking problem which ensures cooperation amongst a swarm of unmanned aerial vehicles (UAVs), modelled as nonlinear systems with linear and angular velocity constraints, in order to achieve different goals. A distributed Takagi-Sugeno (TS) framework design is adopted for the representation of the nonlinear model of the dynamics of the UAVs. The distributed control law which is introduced is composed of both node and network level information. Firstly, feedback gains are synthesised using a parallel distributed compensation (PDC) control law structure, for a collection of isolated UAVs; ignoring communications among the swarm. Then secondly, based on an alternation-like procedure, the resulting feedback gains are used to determine Lyapunov matrices which are utilised at network level to incorporate into the control law, the relative differences in the states of the vehicles, and to induce cooperative behaviour. Eventually stability is guaranteed for the entire swarm. The control synthesis is performed using tools from linear control theory: in particular the design criteria are posed as linear matrix inequalities (LMIs). An example based on a UAV tracking scenario is included to outline the efficacy of the approach.

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.

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

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.

Pre-earthquake multiparameter analysis of the 2016 Amatrice-Norcia (Central Italy) seismic sequence: a case study for the application of the SAFE project concepts

NASA Astrophysics Data System (ADS)

De Santis, A.

2017-12-01

The SAFE (Swarm for Earthquake study) project (funded by European Space Agency in the framework "STSE Swarm+Innovation", 2014-2016) aimed at applying the new approach of geosystemics to the analysis of Swarm satellite (ESA) electromagnetic data for investigating the preparatory phase of earthquakes. We present in this talk the case study of the most recent seismic sequence in Italy. First a M6 earthquake on 24 August 2016 and then a M6.5 earthquake on 30 October 2016 shocked almost in the same region of Central Italy causing about 300 deaths in total (mostly on 24 August), with a revival of other significant seismicity on January 2017. Analysing both geophysical and climatological satellite and ground data preceding the major earthquakes of the sequence we present results that confirm a complex solid earth-atmosphere coupling in the preparation phase of the whole sequence.

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.

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).

Entanglement-Gradient Routing for Quantum Networks.

PubMed

Gyongyosi, Laszlo; Imre, Sandor

2017-10-27

We define the entanglement-gradient routing scheme for quantum repeater networks. The routing framework fuses the fundamentals of swarm intelligence and quantum Shannon theory. Swarm intelligence provides nature-inspired solutions for problem solving. Motivated by models of social insect behavior, the routing is performed using parallel threads to determine the shortest path via the entanglement gradient coefficient, which describes the feasibility of the entangled links and paths of the network. The routing metrics are derived from the characteristics of entanglement transmission and relevant measures of entanglement distribution in quantum networks. The method allows a moderate complexity decentralized routing in quantum repeater networks. The results can be applied in experimental quantum networking, future quantum Internet, and long-distance quantum communications.

Infrared and visible image fusion using discrete cosine transform and swarm intelligence for surveillance applications

NASA Astrophysics Data System (ADS)

Paramanandham, Nirmala; Rajendiran, Kishore

2018-01-01

A novel image fusion technique is presented for integrating infrared and visible images. Integration of images from the same or various sensing modalities can deliver the required information that cannot be delivered by viewing the sensor outputs individually and consecutively. In this paper, a swarm intelligence based image fusion technique using discrete cosine transform (DCT) domain is proposed for surveillance application which integrates the infrared image with the visible image for generating a single informative fused image. Particle swarm optimization (PSO) is used in the fusion process for obtaining the optimized weighting factor. These optimized weighting factors are used for fusing the DCT coefficients of visible and infrared images. Inverse DCT is applied for obtaining the initial fused image. An enhanced fused image is obtained through adaptive histogram equalization for a better visual understanding and target detection. The proposed framework is evaluated using quantitative metrics such as standard deviation, spatial frequency, entropy and mean gradient. The experimental results demonstrate the outperformance of the proposed algorithm over many other state- of- the- art techniques reported in literature.

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.

Construction of Gene Regulatory Networks Using Recurrent Neural Networks and Swarm Intelligence.

PubMed

Khan, Abhinandan; Mandal, Sudip; Pal, Rajat Kumar; Saha, Goutam

2016-01-01

We have proposed a methodology for the reverse engineering of biologically plausible gene regulatory networks from temporal genetic expression data. We have used established information and the fundamental mathematical theory for this purpose. We have employed the Recurrent Neural Network formalism to extract the underlying dynamics present in the time series expression data accurately. We have introduced a new hybrid swarm intelligence framework for the accurate training of the model parameters. The proposed methodology has been first applied to a small artificial network, and the results obtained suggest that it can produce the best results available in the contemporary literature, to the best of our knowledge. Subsequently, we have implemented our proposed framework on experimental (in vivo) datasets. Finally, we have investigated two medium sized genetic networks (in silico) extracted from GeneNetWeaver, to understand how the proposed algorithm scales up with network size. Additionally, we have implemented our proposed algorithm with half the number of time points. The results indicate that a reduction of 50% in the number of time points does not have an effect on the accuracy of the proposed methodology significantly, with a maximum of just over 15% deterioration in the worst case.

Ant-Based Cyber Defense (also known as

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

Glenn Fink, PNNL

2015-09-29

ABCD is a four-level hierarchy with human supervisors at the top, a top-level agent called a Sergeant controlling each enclave, Sentinel agents located at each monitored host, and mobile Sensor agents that swarm through the enclaves to detect cyber malice and misconfigurations. The code comprises four parts: (1) the core agent framework, (2) the user interface and visualization, (3) test-range software to create a network of virtual machines including a simulated Internet and user and host activity emulation scripts, and (4) a test harness to allow the safe running of adversarial code within the framework of monitored virtual machines.

Applying FastSLAM to Articulated Rovers

NASA Astrophysics Data System (ADS)

Hewitt, Robert Alexander

This thesis presents the navigation algorithms designed for use on Kapvik, a 30 kg planetary micro-rover built for the Canadian Space Agency; the simulations used to test the algorithm; and novel techniques for terrain classification using Kapvik's LIDAR (Light Detection And Ranging) sensor. Kapvik implements a six-wheeled, skid-steered, rocker-bogie mobility system. This warrants a more complicated kinematic model for navigation than a typical 4-wheel differential drive system. The design of a 3D navigation algorithm is presented that includes nonlinear Kalman filtering and Simultaneous Localization and Mapping (SLAM). A neural network for terrain classification is used to improve navigation performance. Simulation is used to train the neural network and validate the navigation algorithms. Real world tests of the terrain classification algorithm validate the use of simulation for training and the improvement to SLAM through the reduction of extraneous LIDAR measurements in each scan.

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.

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.

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.

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

Identification of inelastic parameters based on deep drawing forming operations using a global-local hybrid Particle Swarm approach

NASA Astrophysics Data System (ADS)

Vaz, Miguel; Luersen, Marco A.; Muñoz-Rojas, Pablo A.; Trentin, Robson G.

2016-04-01

Application of optimization techniques to the identification of inelastic material parameters has substantially increased in recent years. The complex stress-strain paths and high nonlinearity, typical of this class of problems, require the development of robust and efficient techniques for inverse problems able to account for an irregular topography of the fitness surface. Within this framework, this work investigates the application of the gradient-based Sequential Quadratic Programming method, of the Nelder-Mead downhill simplex algorithm, of Particle Swarm Optimization (PSO), and of a global-local PSO-Nelder-Mead hybrid scheme to the identification of inelastic parameters based on a deep drawing operation. The hybrid technique has shown to be the best strategy by combining the good PSO performance to approach the global minimum basin of attraction with the efficiency demonstrated by the Nelder-Mead algorithm to obtain the minimum itself.

Design of shared unit-dose drug distribution network using multi-level particle swarm optimization.

PubMed

Chen, Linjie; Monteiro, Thibaud; Wang, Tao; Marcon, Eric

2018-03-01

Unit-dose drug distribution systems provide optimal choices in terms of medication security and efficiency for organizing the drug-use process in large hospitals. As small hospitals have to share such automatic systems for economic reasons, the structure of their logistic organization becomes a very sensitive issue. In the research reported here, we develop a generalized multi-level optimization method - multi-level particle swarm optimization (MLPSO) - to design a shared unit-dose drug distribution network. Structurally, the problem studied can be considered as a type of capacitated location-routing problem (CLRP) with new constraints related to specific production planning. This kind of problem implies that a multi-level optimization should be performed in order to minimize logistic operating costs. Our results show that with the proposed algorithm, a more suitable modeling framework, as well as computational time savings and better optimization performance are obtained than that reported in the literature on this subject.

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.

Modeling and simulation of dynamic ant colony's labor division for task allocation of UAV swarm

NASA Astrophysics Data System (ADS)

Wu, Husheng; Li, Hao; Xiao, Renbin; Liu, Jie

2018-02-01

The problem of unmanned aerial vehicle (UAV) task allocation not only has the intrinsic attribute of complexity, such as highly nonlinear, dynamic, highly adversarial and multi-modal, but also has a better practicability in various multi-agent systems, which makes it more and more attractive recently. In this paper, based on the classic fixed response threshold model (FRTM), under the idea of "problem centered + evolutionary solution" and by a bottom-up way, the new dynamic environmental stimulus, response threshold and transition probability are designed, and a dynamic ant colony's labor division (DACLD) model is proposed. DACLD allows a swarm of agents with a relatively low-level of intelligence to perform complex tasks, and has the characteristic of distributed framework, multi-tasks with execution order, multi-state, adaptive response threshold and multi-individual response. With the proposed model, numerical simulations are performed to illustrate the effectiveness of the distributed task allocation scheme in two situations of UAV swarm combat (dynamic task allocation with a certain number of enemy targets and task re-allocation due to unexpected threats). Results show that our model can get both the heterogeneous UAVs' real-time positions and states at the same time, and has high degree of self-organization, flexibility and real-time response to dynamic environments.

Cat swarm optimization based evolutionary framework for multi document summarization

NASA Astrophysics Data System (ADS)

Rautray, Rasmita; Balabantaray, Rakesh Chandra

2017-07-01

Today, World Wide Web has brought us enormous quantity of on-line information. As a result, extracting relevant information from massive data has become a challenging issue. In recent past text summarization is recognized as one of the solution to extract useful information from vast amount documents. Based on number of documents considered for summarization, it is categorized as single document or multi document summarization. Rather than single document, multi document summarization is more challenging for the researchers to find accurate summary from multiple documents. Hence in this study, a novel Cat Swarm Optimization (CSO) based multi document summarizer is proposed to address the problem of multi document summarization. The proposed CSO based model is also compared with two other nature inspired based summarizer such as Harmony Search (HS) based summarizer and Particle Swarm Optimization (PSO) based summarizer. With respect to the benchmark Document Understanding Conference (DUC) datasets, the performance of all algorithms are compared in terms of different evaluation metrics such as ROUGE score, F score, sensitivity, positive predicate value, summary accuracy, inter sentence similarity and readability metric to validate non-redundancy, cohesiveness and readability of the summary respectively. The experimental analysis clearly reveals that the proposed approach outperforms the other summarizers included in the study.

Concept of combinatorial de novo design of drug-like molecules by particle swarm optimization.

PubMed

Hartenfeller, Markus; Proschak, Ewgenij; Schüller, Andreas; Schneider, Gisbert

2008-07-01

We present a fast stochastic optimization algorithm for fragment-based molecular de novo design (COLIBREE, Combinatorial Library Breeding). The search strategy is based on a discrete version of particle swarm optimization. Molecules are represented by a scaffold, which remains constant during optimization, and variable linkers and side chains. Different linkers represent virtual chemical reactions. Side-chain building blocks were obtained from pseudo-retrosynthetic dissection of large compound databases. Here, ligand-based design was performed using chemically advanced template search (CATS) topological pharmacophore similarity to reference ligands as fitness function. A weighting scheme was included for particle swarm optimization-based molecular design, which permits the use of many reference ligands and allows for positive and negative design to be performed simultaneously. In a case study, the approach was applied to the de novo design of potential peroxisome proliferator-activated receptor subtype-selective agonists. The results demonstrate the ability of the technique to cope with large combinatorial chemistry spaces and its applicability to focused library design. The technique was able to perform exploitation of a known scheme and at the same time explorative search for novel ligands within the framework of a given molecular core structure. It thereby represents a practical solution for compound screening in the early hit and lead finding phase of a drug discovery project.

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

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

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.

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.

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 mating competition. PMID:21711542

Cloud-Based Perception and Control of Sensor Nets and Robot Swarms

DTIC Science & Technology

2016-04-01

distributed stream processing framework provides the necessary API and infrastructure to develop and execute such applications in a cluster of computation...streaming DDDAS applications based on challenges they present to the backend Cloud control system. Figure 2 Parallel SLAM Application 3 1) Set of...the art deep learning- based object detectors can recognize among hundreds of object classes and this capability would be very useful for mobile

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.

Lattice Boltzmann simulations of the bead-spring microswimmer with a responsive stroke—from an individual to swarms

NASA Astrophysics Data System (ADS)

Pickl, Kristina; Pande, Jayant; Köstler, Harald; Rüde, Ulrich; Smith, Ana-Sunčana

2017-03-01

Propulsion at low Reynolds numbers is often studied by defining artificial microswimmers which exhibit a particular stroke. The disadvantage of such an approach is that the stroke does not adjust to the environment, in particular the fluid flow, which can diminish the effect of hydrodynamic interactions. To overcome this limitation, we simulate a microswimmer consisting of three beads connected by springs and dampers, using the self-developed waLBerla and pe framework based on the lattice Boltzmann method and the discrete element method. In our approach, the swimming stroke of a swimmer emerges as a balance of the drag, the driving and the elastic internal forces. We validate the simulations by comparing the obtained swimming velocity to the velocity found analytically using a perturbative method where the bead oscillations are taken to be small. Including higher-order terms in the hydrodynamic interactions between the beads improves the agreement to the simulations in parts of the parameter space. Encouraged by the agreement between the theory and the simulations and aided by the massively parallel capabilities of the waLBerla-pe framework, we simulate more than ten thousand such swimmers together, thus presenting the first fully resolved simulations of large swarms with active responsive components.

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

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.

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

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).

Using ANTS to explore small body populations in the solar system.

NASA Astrophysics Data System (ADS)

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

2001-11-01

ANTS (Autonomous Nano-Technology Swarm), a NASA advanced mission concept, is a large (100 to 1000 member) swarm of pico-class (1 kg) totally autonomous spacecraft that prospect the asteroid belt. Little data is available for asteroids because the vast majority are too small to be observed except in close proximity. Light curves are available for thousands of asteroids, confirmed trajectories for tens of thousands, detailed shape models for approximately ten. Asteroids originated in the transitional region between the inner (rocky) and outer (solidified gases) solar system. Many have remained largely unmodified since formation, and thus have more primitive composition than planetary surfaces. Determination of the systematic distribution of physical and compositional properties within the asteroid population is crucial in the understanding of solar system formation. The traditional exploration approach of using few, large spacecraft for sequential exploration, could be improved. Our far more cost-effective approach utilizes distributed intelligence in a swarm of tiny highly maneuverable spacecraft, each with specialized instrument capability (e.g., advanced computing, imaging, spectrometry). NASA is at the forefront of Intelligent Software Agents (ISAs) research, performing experiments in space and on the ground to advance deliberative and collaborative autonomous control techniques. The advanced development under consideration here is in the use of ISAs at a strategic level, to explore remote frontiers of the solar system, potentially involving a large class of objects such as asteroids. Supervised clusters of spacecraft operate simultaneously within a broadly defined framework of goals to select targets (> 1000) from among available candidates while developing scenarios for studying targets. Swarm members use solar sails to fly directly to asteroids > 1 kilometer in diameter, and then perform maneuvers appropriate for the instrument carried, ranging from hovering to orbiting. Selected members return with data and are replaced as needed.

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 media is important for understanding particle sedimentation and contaminant spreading in the subsurface. Acknowledgment: This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Geosciences Research Program under Award Number (DE-FG02-09ER16022).

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.

An algorithmic framework for multiobjective optimization.

PubMed

Ganesan, T; Elamvazuthi, I; Shaari, Ku Zilati Ku; Vasant, P

2013-01-01

Multiobjective (MO) optimization is an emerging field which is increasingly being encountered in many fields globally. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. Nevertheless, many challenges still arise especially when dealing with problems with multiple objectives (especially in cases more than two). In addition, problems with extensive computational overhead emerge when dealing with hybrid algorithms. This paper discusses these issues by proposing an alternative framework that utilizes algorithmic concepts related to the problem structure for generating efficient and effective algorithms. This paper proposes a framework to generate new high-performance algorithms with minimal computational overhead for MO optimization.

An Algorithmic Framework for Multiobjective Optimization

PubMed Central

Ganesan, T.; Elamvazuthi, I.; Shaari, Ku Zilati Ku; Vasant, P.

2013-01-01

Multiobjective (MO) optimization is an emerging field which is increasingly being encountered in many fields globally. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. Nevertheless, many challenges still arise especially when dealing with problems with multiple objectives (especially in cases more than two). In addition, problems with extensive computational overhead emerge when dealing with hybrid algorithms. This paper discusses these issues by proposing an alternative framework that utilizes algorithmic concepts related to the problem structure for generating efficient and effective algorithms. This paper proposes a framework to generate new high-performance algorithms with minimal computational overhead for MO optimization. PMID:24470795

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 events signify pure shears except for the 1997-swarm events the MTs of which indicates a combine sources including both shear and tensile components. The origin of earthquake swarms is still unclear. Nevertheless, we infer that the individual earthquake swarms in West Bohemia-Vogtland are mixture of the mainshock-aftershock sequences which correspond to step by step rupturing of one or a few asperities. The swarms occur on short fault segments with heterogeneous stress and strength, which may be affected by pressurized crustal fluids reducing normal component of the tectonic stress and lower friction. This way critically loaded faults are brought to failure and the swarm activity is driven by the differential local stress.

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.

UAV Swarm Tactics: An Agent-Based Simulation and Markov Process Analysis

DTIC Science & Technology

2013-06-01

CRN Common Random Numbers CSV Comma Separated Values DoE Design of Experiment GLM Generalized Linear Model HVT High Value Target JAR Java ARchive JMF... Java Media Framework JRE Java runtime environment Mason Multi-Agent Simulator Of Networks MOE Measure Of Effectiveness MOP Measures Of Performance...with every set several times, and to write a CSV file with the results. Rather than scripting the agent behavior deterministically, the agents should

Human Robotic Swarm Interaction Using an Artificial Physics Approach

DTIC Science & Technology

2014-12-01

calculates virtual forces that are summed and translated into velocity commands. The virtual forces are modeled after real physical forces such as...results from the physical experiments show that an artificial physics-based framework is an effective way to allow multiple agents to follow a human... modeled after real physical forces such as gravitational and Coulomb, forces but are not restricted to them, for example, the force magnitude may not be

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

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.

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.

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.

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

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.

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.

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.

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 some earthquake swarms show strong interaction with megathrust events where swarms precede the mainshock, swarms show stress interaction with the events, swarms mark the limits of rupture propagation, and swarms occur in areas of long standing seismic gaps. The latter two features also reflect several cases where swarms occur at the subduction of aseismic ridges and trench parallel gravity highs, features often related to megathrust segmentation. Considering that aseismic ridges likely represent material heterogeneity and earthquake swarms typically have low stress drops, we propose that swarms primarily occur in transitional areas of weak coupling that inhibit megathrust seismogenesis and facilitate earthquake swarms. Only 1 swarm in the megathrust area has sufficient geodetic data to investigate slip models, offshore Copiapo, Chile, and while the preferred model suggests aseismic slip, difficulty in modeling an offshore event with onshore data indicates a model without aseismic slip cannot be ruled out. To further examine whether the relationship between swarms and megathrust segmentation is locally derived or more pervasive, we will present results from applying our technique to other major subduction zones.

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.

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

The quadriceps muscle of knee joint modelling Using Hybrid Particle Swarm Optimization-Neural Network (PSO-NN)

NASA Astrophysics Data System (ADS)

Kamaruddin, Saadi Bin Ahmad; Marponga Tolos, Siti; Hee, Pah Chin; Ghani, Nor Azura Md; Ramli, Norazan Mohamed; Nasir, Noorhamizah Binti Mohamed; Ksm Kader, Babul Salam Bin; Saiful Huq, Mohammad

2017-03-01

Neural framework has for quite a while been known for its ability to handle a complex nonlinear system without a logical model and can learn refined nonlinear associations gives. Theoretically, the most surely understood computation to set up the framework is the backpropagation (BP) count which relies on upon the minimization of the mean square error (MSE). However, this algorithm is not totally efficient in the presence of outliers which usually exist in dynamic data. This paper exhibits the modelling of quadriceps muscle model by utilizing counterfeit smart procedures named consolidated backpropagation neural network nonlinear autoregressive (BPNN-NAR) and backpropagation neural network nonlinear autoregressive moving average (BPNN-NARMA) models in view of utilitarian electrical incitement (FES). We adapted particle swarm optimization (PSO) approach to enhance the performance of backpropagation algorithm. In this research, a progression of tests utilizing FES was led. The information that is gotten is utilized to build up the quadriceps muscle model. 934 preparing information, 200 testing and 200 approval information set are utilized as a part of the improvement of muscle model. It was found that both BPNN-NAR and BPNN-NARMA performed well in modelling this type of data. As a conclusion, the neural network time series models performed reasonably efficient for non-linear modelling such as active properties of the quadriceps muscle with one input, namely output namely muscle force.

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 tectonic and volcanic settings. Finally, we demonstrate some swarms underlie areas that are typically quiescent, like Redding and the Sutter Buttes. Our catalog presents a more complete snapshot of the diversity of swarm characteristics in Northern California, and motivates further study of their relationship to tectonic and volcanic processes.

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.

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.

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.

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 portions of the torroid closest to the fracture wall experiences more drag that causes the swarm to bifurcate. In fractures with 2.5 mm apertures, swarms were observed to bifurcate 7-10 times over a distance of 70 mm. The length of the branches in the tree-like structures decreased as the swarm progressed through multiple bifurcations. The bifurcation length is related to the distance swarms can travel along fractures. Acknowledgment: The authors wish to acknowledge support of this work by the Geosciences Research Program, Office of Basic Energy Sciences US Department of Energy (DE-FG02-09ER16022).

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.

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.

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.

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 particulate transport. Acknowledgment: This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Geosciences Research Program under Award Number (DE-FG02-09ER16022) and by National Science Foundation REU program under Award Number (PHY-1460899) at Purdue University.

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 targeted aerosol spraying of the swarms to improve malaria control. PMID:29184918

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.

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 the individual swarms indicate their complexity. All the swarms exhibit both oblique-normal and oblique-thrust faulting but the former prevails. We found a several families of mechanisms, which fit well geometry of respective fault segments being determined by means of the double-difference location. MTs of the most analysed events signify pure shears except for events the second phase of the 1997 swarm the MTs of which indicate significant amount of non-DC components. The existing results do not allow us to explain properly an origin of earthquake swarms. Nevertheless, we infer that the individual earthquake swarms in West Bohemia-Vogtland are mixture of the mainshock-aftershock sequences which correspond to step by step rupturing of one or a few asperities. The swarms occur on short fault segments with heterogeneous stress and strength, which may be affected by crustal fluids. Pressurized fluids may reduce normal component of the tectonic stress and lower friction. Thus, critically loaded and favourably oriented faults are brought to failure and the swarm activity is driven by the differential local stress.

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.

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 slows the swarm, and a cohesive force that prevents swarm expansion and the corresponding decrease in particle density. For apertures >15mm, though the drag force is small, the loss of swarm cohesion dominates. In small apertures (<5mm), the drag from the wall dominates causing a loss in speed even though there is strong confinement. From a force-based particle interaction approach, the initial simulation did not capture the observed experimental behavior, i.e., the distinct peak in swarm velocities was not observed. For the funnel shaped aperture, the swarm was observed to bifurcate immediately upon reaching the intersection between the converging aperture and the uniform aperture portions of the fracture. Furthermore, converging apertures resulted in the deceleration of a swarm. Thus, the rate of transport of particle swarms is strongly affected by fracture aperture. Acknowledgment: The authors wish to acknowledge support of this work by the Geosciences Research Program, Office of Basic Energy Sciences US Department of Energy (DE-FG02-09ER16022).

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 choice. Given these inputs, the tool provides the most efficient maneuver(s) to achieve the objective.Second, SODA provides a variety of visualization tools. We acknowledge that the relationship between a desired relative motion amongst the swarm, and the corresponding orbital parameters for each individual satellite may not be immediately apparent for ground controllers and mission planners. The purpose of SODA's visualization tools is to illustrate this concept clearly with a variety of graphics and animations. After computing the optimal orbital maneuvers to modify the swarm, these results are simulated to demonstrate successful swarm control.Our emphasis in this paper is on the importance of relating the desired motion of the swarm satellites relative to one another with the required orbital element changes. One cannot joystick a drifting swarm satellite back into position; the underlying orbital mechanics dictate the most efficient recovery maneuvers. To illustrate this point, results from several case study simulations are presented. We conclude with our forward work for ongoing SODA development and potential science applications.

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.

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.

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. Converging apertures caused swarms to decelerate rapidly and become trapped in the transition point between the converging and parallel regions for apertures less than 2.5 mm. In uniform aperture fractures, an optimal aperture range (5 mm to 15 mm) exists where swarm velocity was higher and the swarm maintained cohesion over a longer distance. For apertures below this range the swarms were strongly slowed due to drag from the wall, while for larger apertures the swarm velocity approached an asymptote due to the loss of the walls influence. The transport of particle swarms in fractures is strongly controlled by aperture distribution. While drag from the fracture does slow swarms, especially at small apertures, much of the interesting behavior (shape changes in diverging fracture, optimal aperture in parallel fracture) is best explained by fracture induced preferential confinement that controls the evolution of the swarm. When this confinement is suddenly changed, the swarm responds quickly and dramatically to its new environment. This has important implications for the understanding of contaminant dispersal in subsurface fracture networks because the type of aperture variation can exert a strong influence on particle swarm transport. Acknowledgment: The authors wish to acknowledge support of this work by the Geosciences Research Program, Office of Basic Energy Sciences US Department of Energy (DE-FG02-09ER16022).

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.

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

The December 2015 Mount Etna eruption: An analysis of inflation/deflation phases and faulting processes

NASA Astrophysics Data System (ADS)

Aloisi, Marco; Jin, Shuanggen; Pulvirenti, Fabio; Scaltrito, Antonio

2017-06-01

During the first days of December 2015, there were four paroxysmal events at the ;Voragine; crater on Mount Etna, which were among the most violent observed during the last two decades. A few days after the ;Voragine; paroxysms, the Pernicana - Provenzana fault system, located near the crater area, underwent an intense seismic swarm with a maximum ;local; magnitude ML of 3.6. This paper investigates the relationship between the eruptive phenomenon and the faulting process in terms of Coulomb stress changes. The recorded seismicity is compatible with a multicausal stress redistribution inside the volcano edifice, occurring after the four paroxysmal episodes that interrupted the usual trend of inflation observed at Mt. Etna. The recorded seismicity falls within the framework of a complex chain of various and intercorrelated processes that started with the inflation preparing the ;Voragine; magmatic activity. This was followed with the rapid deflation of the volcano edifice during the paroxysmal episodes. We determined that the recorded deflation was not the direct cause of the seismic swarm. In fact, the associated Coulomb stress change, in the area of seismic swarm, was of about -1 [bar]. Instead, the fast deflation caused the rarely observed inversion of dislocation in the eastern flank at the same time as intense hydrothermal activity that, consequently, underwent an alteration. This process probably reduced the friction along the fault system. Then, the new phase of inflation, observed at the end of the magmatic activity, triggered the faulting processes.

Distributed pheromone-based swarming control of unmanned air and ground vehicles for RSTA

NASA Astrophysics Data System (ADS)

Sauter, John A.; Mathews, Robert S.; Yinger, Andrew; Robinson, Joshua S.; Moody, John; Riddle, Stephanie

2008-04-01

The use of unmanned vehicles in Reconnaissance, Surveillance, and Target Acquisition (RSTA) applications has received considerable attention recently. Cooperating land and air vehicles can support multiple sensor modalities providing pervasive and ubiquitous broad area sensor coverage. However coordination of multiple air and land vehicles serving different mission objectives in a dynamic and complex environment is a challenging problem. Swarm intelligence algorithms, inspired by the mechanisms used in natural systems to coordinate the activities of many entities provide a promising alternative to traditional command and control approaches. This paper describes recent advances in a fully distributed digital pheromone algorithm that has demonstrated its effectiveness in managing the complexity of swarming unmanned systems. The results of a recent demonstration at NASA's Wallops Island of multiple Aerosonde Unmanned Air Vehicles (UAVs) and Pioneer Unmanned Ground Vehicles (UGVs) cooperating in a coordinated RSTA application are discussed. The vehicles were autonomously controlled by the onboard digital pheromone responding to the needs of the automatic target recognition algorithms. UAVs and UGVs controlled by the same pheromone algorithm self-organized to perform total area surveillance, automatic target detection, sensor cueing, and automatic target recognition with no central processing or control and minimal operator input. Complete autonomy adds several safety and fault tolerance requirements which were integrated into the basic pheromone framework. The adaptive algorithms demonstrated the ability to handle some unplanned hardware failures during the demonstration without any human intervention. The paper describes lessons learned and the next steps for this promising technology.

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.

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.

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.

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.

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

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

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

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

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.

[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.

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 two different source mechanisms occurred: the oblique-normal on the one segment and the oblique-thrust type on the other one. Furthermore, we disclose that all the ML ≥ 2.7 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 existing results do not allow us to explain properly an origin of earthquake swarms. Nevertheless, some results point to a connection between pressurized fluids in the crust and the earthquake swarm occurrence. Taking this into account, we may infer that earthquake swarms occur on short fault segments with heterogeneous stress and strength, which are affected by crustal fluids. Pressurized fluids reduced normal component of the tectonic stress and lower friction. Thus, critically loaded and favourably oriented faults are brought to failure and the swarm activity is driven by the differential local stress.

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 decreased in speed and came to rest on the interface while maintaining its spherical shape. After the interface between a swarm and the oil thinned sufficiently, the swarm was rapidly released into the water layer. The time that this took depended on the viscosity of the oil layer, which determines the rate of thinning, and on the size and properties of the particles. The swarm geometry and velocity in the water layer depended on the aperture of the fracture, the viscosity of the oil and the hydrophobicity or hydrophyllicity of the particles in the swarm. Hydrophobic beads result in multiple mini swarms after breaking through the interface rather than a single large swarm like that observed for hydrophilic swarms. After many experiments a pile formed at the bottom of the tank near the center of the fracture, indicating that swarms can lead to locally high concentration of colloidal contaminants. Acknowledgment: The authors wish to acknowledge support of this work by the Geosciences Research Program, Office of Basic Energy Sciences US Department of Energy (DE-FG02-09ER16022) and the Summer Undergraduate Research Fellowship program at Purdue University.

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...

The Swarm Archiving Payload Data Facility, an Instance Configuration of the ESA Multi-Mission Facility

NASA Astrophysics Data System (ADS)

Pruin, B.; Martini, A.; Shanmugam, P.; Lopes, C.

2015-04-01

The Swarm mission consists of 3 satellites, each carrying an identical set of instruments. The scientific algorithms for processing are organized in 11 separate processing steps including automated product quality control. In total, the mission data consists of data products of several hundred distinct types from raw to level 2 product types and auxiliary data. The systematic production for Swarm within the ESA Archiving and Payload Data Facility (APDF) is performed up to level 2. The production up to L2 (CAT2-mature algorithm) is performed completely within the APDF. A separate systematic production chain from L1B to L2 (CAT1-evolving algorithm) is performed by an external facility (L2PS) with output files archived within the APDF as well. The APDF also performs re-processing exercises. Re-processing may start directly from the acquired data or from any other intermediate level resulting in the need for a refined product version and baseline management. Storage, dissemination and circulation functionality is configurable in the ESA generic multi-mission elements and does not require any software coding. The control of the production is more involved. While the interface towards the algorithmic entities is standardized due to the introduction of a generic IPF interface by ESA, the orchestration of the individual IPFs into the overall workflows is distinctly mission-specific and not as amenable to standardization. The ESA MMFI production management system provides extension points to integrate additional logical elements for the build-up of complex orchestrated workflows. These extension points have been used to inject the Swarm-specific production logic into the system. A noteworthy fact about the APDF is that the dissemination elements are hosted in a high bandwidth infrastructure procured as a managed service, thus affording users a considerable access bandwidth. This paper gives an overview of the Swarm APDF data flows. It describes the elements of the solution with particular focus on how the available generic multi-mission functionality of the ESA MMFI was utilized and where there was a need to implement missionspecific extensions and plug-ins. The paper concludes with some statistics on the system output during commissioning and early operational phases as well as some general considerations on the utilization of a framework like the ESA MMFI, discussing benefits and pitfalls of the approach.

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.

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.

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.

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.

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.

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.

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.

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.

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

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

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

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.

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.

Dynamic Triggering of Seismic Events and Their Relation to Slow Slip in Interior Alaska

NASA Astrophysics Data System (ADS)

Sims, N. E.; Holtkamp, S. G.

2017-12-01

We conduct a search for dynamically triggered events in the Minto Flats Fault Zone (MFFZ), a left-lateral strike-slip zone expressed as multiple, partially overlapping faults, in central Alaska. We focus on the MFFZ because we have observed slow slip processes (earthquake swarms and Very Low Frequency Earthquakes) and interaction between earthquake swarms and larger main-shock (MS) events in this area before. We utilize the Alaska Earthquake Center catalog to identify potential earthquake swarms and dynamically triggered foreshock and mainshock events along the fault zone. We find 30 swarms occurring in the last two decades, five of which we classify as foreshock (FS) swarms due to their close proximity in both time and space to MS events. Many of the earthquake swarms cluster around 15-20 km depth, which is near the seismic-aseismic transition along this fault zone. Additionally, we observe instances of large teleseismic events such as the M8.6 2012 Sumatra earthquake and M7.4 2012 Guatemala earthquake triggering seismic events within the MFFZ, with the Sumatra earthquake triggering a mainshock event that was preceded by an ongoing earthquake swarm and the Guatemala event triggering earthquake swarms that subsequently transition into a larger mainshock event. In both cases an earthquake swarm transitioned into a mainshock-aftershock event and activity continued for several days after the teleseismic waves had passed, lending some evidence to delayed dynamic triggering of seismic events. We hypothesize that large dynamic transient strain associated with the passage of teleseismic surface waves is triggering slow slip processes near the base of the seismogenic zone. These triggered aseismic transient events result in earthquake swarms, which sometimes lead to the nucleation of larger earthquakes. We utilize network matched filtering to build more robust catalogs of swarm earthquake families in this region to search for additional swarm-like or triggered activity in response to teleseismic surface waves, and to test dynamic triggering hypotheses.

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.

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 detected much earlier by the swarm algorithm than they were by the tremor algorithm.

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 fractured media will improve the ability to perform controlled micro-particulate transport through rock. Acknowledgment: This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Geosciences Research Program under Award Number (DE-FG02-09ER16022).

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 drop or solid sphere, fracture boundaries do not exclusively decelerate swarm motion but instead produce enhanced swarm transport. Acknowledgments: This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Geosciences Research Program under Award Number (DE-FG02-09ER16022).

Guidance and control of swarms of spacecraft

NASA Astrophysics Data System (ADS)

Morgan, Daniel James

There has been considerable interest in formation flying spacecraft due to their potential to perform certain tasks at a cheaper cost than monolithic spacecraft. Formation flying enables the use of smaller, cheaper spacecraft that distribute the risk of the mission. Recently, the ideas of formation flying have been extended to spacecraft swarms made up of hundreds to thousands of 100-gram-class spacecraft known as femtosatellites. The large number of spacecraft and limited capabilities of each individual spacecraft present a significant challenge in guidance, navigation, and control. This dissertation deals with the guidance and control algorithms required to enable the flight of spacecraft swarms. The algorithms developed in this dissertation are focused on achieving two main goals: swarm keeping and swarm reconfiguration. The objectives of swarm keeping are to maintain bounded relative distances between spacecraft, prevent collisions between spacecraft, and minimize the propellant used by each spacecraft. Swarm reconfiguration requires the transfer of the swarm to a specific shape. Like with swarm keeping, minimizing the propellant used and preventing collisions are the main objectives. Additionally, the algorithms required for swarm keeping and swarm reconfiguration should be decentralized with respect to communication and computation so that they can be implemented on femtosats, which have limited hardware capabilities. The algorithms developed in this dissertation are concerned with swarms located in low Earth orbit. In these orbits, Earth oblateness and atmospheric drag have a significant effect on the relative motion of the swarm. The complicated dynamic environment of low Earth orbits further complicates the swarm-keeping and swarm-reconfiguration problems. To better develop and test these algorithms, a nonlinear, relative dynamic model with J2 and drag perturbations is developed. This model is used throughout this dissertation to validate the algorithms using computer simulations. The swarm-keeping problem can be solved by placing the spacecraft on J2-invariant relative orbits, which prevent collisions and minimize the drift of the swarm over hundreds of orbits using a single burn. These orbits are achieved by energy matching the spacecraft to the reference orbit. Additionally, these conditions can be repeatedly applied to minimize the drift of the swarm when atmospheric drag has a large effect (orbits with an altitude under 500 km). The swarm reconfiguration is achieved using two steps: trajectory optimization and assignment. The trajectory optimization problem can be written as a nonlinear, optimal control problem. This optimal control problem is discretized, decoupled, and convexified so that the individual femtosats can efficiently solve the optimization. Sequential convex programming is used to generate the control sequences and trajectories required to safely and efficiently transfer a spacecraft from one position to another. The sequence of trajectories is shown to converge to a Karush-Kuhn-Tucker point of the nonconvex problem. In the case where many of the spacecraft are interchangeable, a variable-swarm, distributed auction algorithm is used to determine the assignment of spacecraft to target positions. This auction algorithm requires only local communication and all of the bidding parameters are stored locally. The assignment generated using this auction algorithm is shown to be near optimal and to converge in a finite number of bids. Additionally, the bidding process is used to modify the number of targets used in the assignment so that the reconfiguration can be achieved even when there is a disconnected communication network or a significant loss of agents. Once the assignment is achieved, the trajectory optimization can be run using the terminal positions determined by the auction algorithm. To implement these algorithms in real time a model predictive control formulation is used. Model predictive 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.

Collective Cellular Decision-Making Gives Developmental Plasticity: A Model of Signaling in Branching Roots

NASA Astrophysics Data System (ADS)

McCleery, W. Tyler; Mohd-Radzman, Nadiatul A.; Grieneisen, Veronica A.

Cells within tissues can be regarded as autonomous entities that respond to their local environment and signaling from neighbors. Cell coordination is particularly important in plants, where root architecture must strategically invest resources for growth to optimize nutrient acquisition. Thus, root cells are constantly adapting to environmental cues and neighbor communication in a non-linear manner. To explain such plasticity, we view the root as a swarm of coupled multi-cellular structures, ''metamers'', rather than as a continuum of identical cells. These metamers are individually programmed to achieve a local objective - developing a lateral root primordia, which aids in local foraging of nutrients. Collectively, such individual attempts may be halted, structuring root architecture as an emergent behavior. Each metamer's decision to branch is coordinated locally and globally through hormone signaling, including processes of controlled diffusion, active polar transport, and dynamic feedback. We present a physical model of the signaling mechanism that coordinates branching decisions in response to the environment. This work was funded by the European Commission 7th Framework Program, Project No. 601062, SWARM-ORGAN.

Double-Group Particle Swarm Optimization and Its Application in Remote Sensing Image Segmentation

PubMed Central

Shen, Liang; Huang, Xiaotao; Fan, Chongyi

2018-01-01

Particle Swarm Optimization (PSO) is a well-known meta-heuristic. It has been widely used in both research and engineering fields. However, the original PSO generally suffers from premature convergence, especially in multimodal problems. In this paper, we propose a double-group PSO (DG-PSO) algorithm to improve the performance. DG-PSO uses a double-group based evolution framework. The individuals are divided into two groups: an advantaged group and a disadvantaged group. The advantaged group works according to the original PSO, while two new strategies are developed for the disadvantaged group. The proposed algorithm is firstly evaluated by comparing it with the other five popular PSO variants and two state-of-the-art meta-heuristics on various benchmark functions. The results demonstrate that DG-PSO shows a remarkable performance in terms of accuracy and stability. Then, we apply DG-PSO to multilevel thresholding for remote sensing image segmentation. The results show that the proposed algorithm outperforms five other popular algorithms in meta-heuristic-based multilevel thresholding, which verifies the effectiveness of the proposed algorithm. PMID:29724013

Double-Group Particle Swarm Optimization and Its Application in Remote Sensing Image Segmentation.

PubMed

Shen, Liang; Huang, Xiaotao; Fan, Chongyi

2018-05-01

Particle Swarm Optimization (PSO) is a well-known meta-heuristic. It has been widely used in both research and engineering fields. However, the original PSO generally suffers from premature convergence, especially in multimodal problems. In this paper, we propose a double-group PSO (DG-PSO) algorithm to improve the performance. DG-PSO uses a double-group based evolution framework. The individuals are divided into two groups: an advantaged group and a disadvantaged group. The advantaged group works according to the original PSO, while two new strategies are developed for the disadvantaged group. The proposed algorithm is firstly evaluated by comparing it with the other five popular PSO variants and two state-of-the-art meta-heuristics on various benchmark functions. The results demonstrate that DG-PSO shows a remarkable performance in terms of accuracy and stability. Then, we apply DG-PSO to multilevel thresholding for remote sensing image segmentation. The results show that the proposed algorithm outperforms five other popular algorithms in meta-heuristic-based multilevel thresholding, which verifies the effectiveness of the proposed algorithm.

Collective dynamics of soft active particles

NASA Astrophysics Data System (ADS)

van Drongelen, Ruben; Pal, Anshuman; Goodrich, Carl P.; Idema, Timon

2015-03-01

We present a model of soft active particles that leads to a rich array of collective behavior found also in dense biological swarms of bacteria and other unicellular organisms. Our model uses only local interactions, such as Vicsek-type nearest-neighbor alignment, short-range repulsion, and a local boundary term. Changing the relative strength of these interactions leads to migrating swarms, rotating swarms, and jammed swarms, as well as swarms that exhibit run-and-tumble motion, alternating between migration and either rotating or jammed states. Interestingly, although a migrating swarm moves slower than an individual particle, the diffusion constant can be up to three orders of magnitude larger, suggesting that collective motion can be highly advantageous, for example, when searching for food.

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.

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.

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.

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

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

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

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.

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.

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.

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 released under gravity into the water. The swarm density is slightly greater than water and falls faster than the terminal velocity of an individual particle in water. The cohesiveness of the swarm was maintained over 50 mm to 95 mm even in the presence of fluid currents. The swarm velocity decreased with decreasing fracture aperture. When the apertures are small, swarms break-up and reform as they pass through a variable aperture fracture. Acknowledgment: The authors wish to acknowledge support of this work by the Geosciences Research Program, Office of Basic Energy Sciences US Department of Energy (DE-FG02-09ER16022) and the Summer Undergraduate Research Fellowship program at Purdue University.

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 (proximal) to regional (distal) subparallel orientations. An implication for Earth is that many regional linear swarms which do not have a radiating pattern may be due to fragmentation of the swarm during later plate tectonic rifting. Completion of the global classification and census of Venus features, comparison to the terrestrial synthesis, and documentation of the mode of emplacement of dikes in these environments (buffered and unbuffered conditions) should lead to additional general insight into mechanisms of formation and evolution and their relation to plumes.

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

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 (1960-2005) and might indicate an increase of magma supply in the region.

On the dynamical behaviour of low-frequency earthquake swarms prior to a dome collapse of Soufrière Hill volcano, Montserrat

NASA Astrophysics Data System (ADS)

Hammer, C.; Neuberg, J. W.

2009-03-01

A series of low-frequency earthquake swarms prior to a dome collapse on Soufrière Hills volcano, Montserrat, are investigated with the emphasis on event rate and amplitude behaviour. In a single swarm, the amplitudes of consecutive events tend to increase with time, while the rate of event occurrence accelerates initially and then decelerates toward the end of the swarm. However, when consecutive swarms are considered, the average event rates seem to follow the material failure law, and the time of the dome collapse can be successfully estimated using the inverse event rate. These patterns in amplitude and event rate are interpreted as fluctuations in magma ascent velocity, which result in both the generation of low-frequency events as well as cyclic ground deformation accompanying the swarm activity.

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.

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

Shallow earthquake swarms in southern Ryukyu area: manifestation of dynamics of fluid and/or magma plumbing system revealed by teleseismic and regional datasets

NASA Astrophysics Data System (ADS)

Špičák, Aleš; Vaněk, Jiří

2017-04-01

Earthquake swarm occurrence beneath volcanic domains is one of the indicators of current magmatic activity in the Earth's crust. Repeated occurrence of teleseismically recorded earthquake swarms has been observed in the lithospheric wedge of the southern Ryukyu area above the subducting slab of the Philippine Sea Plate. The swarms were analyzed using the EHB, ISC and JMA catalogs of hypocenter parameters. The swarm earthquakes are shallow (1-60 km), in the body-wave magnitude range up to 5.8. The swarms are distributed beneath the seafloor, parallel to the Ryukyu Trench along a belt connecting active subaerial volcanoes Io-Torishima north-east and Kueishantao west of the investigated area. Epicentral zones of the swarms often coincide with distinct elevations at the seafloor—seamounts and seamount ranges. The top of the subducting slab reaches a depth of about 100 km beneath the zones of earthquake swarm occurrence, which is an average depth of a slab beneath volcanoes in general. The repeated occurrence of relatively strong, teleseismically recorded earthquake swarms thus probably reflects fluid and/or magma migration in the plumbing system of the volcanic arc and points to brittle character of the lithospheric wedge at respective depths. In addition to the factual results, this study documents the high accuracy of hypocenter parameter determinations published by the International Seismological Centre and the usefulness of the EHB relocation procedure.

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.

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

A complex of meteorite-forming bodies (the Innisfree - Ridgedale family).

NASA Astrophysics Data System (ADS)

Shestaka, I. S.

1994-12-01

For the first time a swarm of meteorite-forming bodies was identified. Yearly this swarm's orbit approaches the Earth's orbit in early February. This swarm contains the Innisfree and Ridgedale fireballs, 9 small meteoric swarms, several asteroids and 12 fireballs photographed by the cameras of the Prairie Network and Canadian Meteorite Observation and Discovery Project. The discovery of this complex, intensive bombardments of the Moon's surface recorded by means of seismographs left on the Moon, the analysis of the time distributions of meteorite falls on the Earth and other established facts confirm the existence of swarms of meteorite-forming bodies which are crossing the Earth's orbit.

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.

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

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.

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.

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.

A cognitive information processing framework for distributed sensor networks

NASA Astrophysics Data System (ADS)

Wang, Feiyi; Qi, Hairong

2004-09-01

In this paper, we present a cognitive agent framework (CAF) based on swarm intelligence and self-organization principles, and demonstrate it through collaborative processing for target classification in sensor networks. The framework involves integrated designs to provide both cognitive behavior at the organization level to conquer complexity and reactive behavior at the individual agent level to retain simplicity. The design tackles various problems in the current information processing systems, including overly complex systems, maintenance difficulties, increasing vulnerability to attack, lack of capability to tolerate faults, and inability to identify and cope with low-frequency patterns. An important and distinguishing point of the presented work from classical AI research is that the acquired intelligence does not pertain to distinct individuals but to groups. It also deviates from multi-agent systems (MAS) due to sheer quantity of extremely simple agents we are able to accommodate, to the degree that some loss of coordination messages and behavior of faulty/compromised agents will not affect the collective decision made by the group.

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.

Verification of NASA Emergent Systems

NASA Technical Reports Server (NTRS)

Rouff, Christopher; Vanderbilt, Amy K. C. S.; Truszkowski, Walt; Rash, James; Hinchey, Mike

2004-01-01

NASA is studying advanced technologies for a future robotic exploration mission to the asteroid belt. This mission, the prospective ANTS (Autonomous Nano Technology Swarm) mission, will comprise of 1,000 autonomous robotic agents designed to cooperate in asteroid exploration. The emergent properties of swarm type missions make them powerful, but at the same time are more difficult to design and assure that the proper behaviors will emerge. We are currently investigating formal methods and techniques for verification and validation of future swarm-based missions. The advantage of using formal methods is their ability to mathematically assure the behavior of a swarm, emergent or otherwise. The ANT mission is being used as an example and case study for swarm-based missions for which to experiment and test current formal methods with intelligent swam. Using the ANTS mission, we have evaluated multiple formal methods to determine their effectiveness in modeling and assuring swarm behavior.

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.

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.

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.

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.

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.

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.

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

Seismicity of Cascade Volcanoes: Characterization and Comparison

NASA Astrophysics Data System (ADS)

Thelen, W. A.

2016-12-01

Here we summarize and compare the seismicity around each of the Very High Threat Volcanoes of the Cascade Range of Washington, Oregon and California as defined by the National Volcanic Early Warning System (NVEWS) threat assessment (Ewert et al., 2005). Understanding the background seismic activity and processes controlling it is critical for assessing changes in seismicity and their implications for volcanic hazards. Comparing seismicity at different volcanic centers can help determine what critical factors or processes affect the observed seismic behavior. Of the ten Very High Threat Volcanoes in the Cascade Range, five volcanoes are consistently seismogenic when considering earthquakes within 10 km of the volcanic center or caldera edge (Mount Rainier, Mount St. Helens, Mount Hood, Newberry Caldera, Lassen Volcanic Center). Other Very High Threat volcanoes (South Sister, Mount Baker, Glacier Peak, Crater Lake and Mount Shasta) have comparatively low rates of seismicity and not enough recorded earthquakes to calculate catalog statistics. Using a swarm definition of 3 or more earthquakes occurring in a day with magnitudes above the largest of the network's magnitude of completenesses (M 0.9), we find that Lassen Volcanic Center is the "swarmiest" in terms of percent of seismicity occurring in swarms, followed by Mount Hood, Mount St. Helens and Rainier. The predominance of swarms at Mount Hood may be overstated, as much of the seismicity is occurring on surrounding crustal faults (Jones and Malone, 2005). Newberry Caldera has a relatively short record of seismicity since the permanent network was installed in 2011, however there have been no swarms detected as defined here. Future work will include developing discriminates for volcanic versus tectonic seismicity to better filter the seismic catalog and more precise binning of depths at some volcanoes so that we may better consider different processes. Ewert J. W., Guffanti, M. and Murray, T. L. (2005). An Assessment of Volcanic Threat and Monitoring Capabilities in the United States: Framework for a National Volcano Early Warning System, USGS Open File Report 2005-1164, 62 pp. Jones, J., & Malone, S. D. (2005). Mount hood earthquake activity: Volcanic or tectonic origins? Bulletin Of The Seismological Society Of America, 95(3), 818-832.

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.

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.

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.

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.

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

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.

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 perturbation (fluid + stress transfer) is insufficient to generate further faulting. Numerical modeling supports this hypothesis - for example, the main features of the 2014 Long Valley swarm can be reproduced by a relatively simple model incorporating both stress transfer and rupture-aided fluid pressure diffusion (Hsieh et al., AGU FM, 2016).

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.

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.

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

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.

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.

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)

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.

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

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

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.

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.

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.

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

Glider communications and controls for the sea sentry mission.

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

Feddema, John Todd; Dohner, Jeffrey Lynn

2005-03-01

This report describes a system level study on the use of a swarm of sea gliders to detect, confirm and kill littoral submarine threats. The report begins with a description of the problem and derives the probability of detecting a constant speed threat without networking. It was concluded that glider motion does little to improve this probability unless the speed of a glider is greater than the speed of the threat. Therefore, before detection, the optimal character for a swarm of gliders is simply to lie in wait for the detection of a threat. The report proceeds by describing themore » effect of noise on the localization of a threat once initial detection is achieved. This noise is estimated as a function of threat location relative to the glider and is temporally reduced through the use of an information or Kalman filtering. In the next section, the swarm probability of confirming and killing a threat is formulated. Results are compared to a collection of stationary sensors. These results show that once a glider has the ability to move faster than the threat, the performance of the swarm is equal to the performance of a stationary swarm of gliders with confirmation and kill ranges equal to detection range. Moreover, at glider speeds greater than the speed of the threat, swarm performance becomes a weak function of speed. At these speeds swarm performance is dominated by detection range. Therefore, to future enhance swarm performance or to reduce the number of gliders required for a given performance, detection range must be increased. Communications latency is also examined. It was found that relatively large communication delays did little to change swarm performance. Thus gliders may come to the surface and use SATCOMS to effectively communicate in this application.« less

Space and time distribution of foci and source-mechanisms of West-Bohemia/Vogtland earthquake swarms - a tool for insight into their triggering mechanisms and driving forces

NASA Astrophysics Data System (ADS)

Horalek, Josef; Fischer, Tomas; Cermakova, Hana

2013-04-01

West Bohemia/Vogtland (border area between Czech Republic and Germany) belongs to the most active intraplate earthquake-swarm regions in Europe. Above, this area is characteristic by high activity of crustal fluids. Swarm earthquakes with magnitudes ML < 4.0 occur frequently in the area of about 3 000 km2, however, the Nový 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. During last fifteen years there were four earthquake swarms in 1997, 2000, 2008 and 20011 (besides a few tens of microswarms) encompassing a fault plane of about 15 x 6 km. The swarms were located close to each other. Moreover, the 2000 (MLmax = 3.3) and 2008 (MLmax = 3.8) swarms were "twins", i.e. their hypocenters fall precisely on the same portion of the NK fault plane; and the 1997 (MLmax = 2.9) and 2011 (MLmax = 3.6) swarms also occurred on the same fault segment. However, the individual swarms differed 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 were pure shears, most of them showing the oblique normal faulting. Although source mechanisms of majority of the 2000- and 2008 events signify the faulting parallel to the main NK fault plane, there is a significant amount of events having different source mechanisms. We also found alteration of the source mechanisms with depths. The 1997 and 2011 swarms took place on two differently oriented fault segments thus two different source mechanisms occurred: the oblique-normal on the one segment and the oblique-thrust type on the other one. Moreover, source mechanisms of the oblique thrust events suggest combined sources (possessing significant non-DC components). This indicates complexity of both NK focal zone (where earthquake swarms have periodically occurred) and rupturing in the individual swarms. Similar pattern of the strain energy release we disclosed for seismicity due to fluid injection into deep boreholes at HDR site Soultz-sous-Forêts (France) in 2003. We analyzed the spatial and temporal distribution of micro-earthquakes and their source mechanisms and found that injected fluids triggered large seismicity (pure-shear events) at two existing natural fault segments, which ran independently of the injection strategy. Taking into account all our results, we can conclude that earthquake swarms occur on short subcritically loaded fault segments which are affected by crustal fluids. Pressurized fluids reduced normal component of the tectonic stress and lower friction, thus decrease the shear strength of the medium (in terms of Coulomb friction criterion). On critically loaded and favourably oriented fault segments the swarm activity is driven by the differential local stress, the shear rupturing occurs.

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.

Using Swarming Agents for Scalable Security in Large Network Environments

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

Crouse, Michael; White, Jacob L.; Fulp, Errin W.

2011-09-23

The difficulty of securing computer infrastructures increases as they grow in size and complexity. Network-based security solutions such as IDS and firewalls cannot scale because of exponentially increasing computational costs inherent in detecting the rapidly growing number of threat signatures. Hostbased solutions like virus scanners and IDS suffer similar issues, and these are compounded when enterprises try to monitor these in a centralized manner. Swarm-based autonomous agent systems like digital ants and artificial immune systems can provide a scalable security solution for large network environments. The digital ants approach offers a biologically inspired design where each ant in the virtualmore » colony can detect atoms of evidence that may help identify a possible threat. By assembling the atomic evidences from different ant types the colony may detect the threat. This decentralized approach can require, on average, fewer computational resources than traditional centralized solutions; however there are limits to its scalability. This paper describes how dividing a large infrastructure into smaller managed enclaves allows the digital ant framework to effectively operate in larger environments. Experimental results will show that using smaller enclaves allows for more consistent distribution of agents and results in faster response times.« less

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).

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.

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

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.

Evolution of Self-Organized Task Specialization in Robot Swarms

PubMed Central

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

2015-01-01

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

Evolution of Self-Organized Task Specialization in Robot Swarms.

PubMed

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

2015-08-01

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

A new strategy for earthquake focal mechanisms using waveform-correlation-derived relative polarities and cluster analysis: Application to the 2014 Long Valley Caldera earthquake swarm

USGS Publications Warehouse

Shelly, David R.; Hardebeck, Jeanne L.; Ellsworth, William L.; Hill, David P.

2016-01-01

In microseismicity analyses, reliable focal mechanisms can typically be obtained for only a small subset of located events. We address this limitation here, presenting a framework for determining robust focal mechanisms for entire populations of very small events. To achieve this, we resolve relative P and S wave polarities between pairs of waveforms by using their signed correlation coefficients—a by-product of previously performed precise earthquake relocation. We then use cluster analysis to group events with similar patterns of polarities across the network. Finally, we apply a standard mechanism inversion to the grouped data, using either catalog or correlation-derived P wave polarity data sets. This approach has great potential for enhancing analyses of spatially concentrated microseismicity such as earthquake swarms, mainshock-aftershock sequences, and industrial reservoir stimulation or injection-induced seismic sequences. To demonstrate its utility, we apply this technique to the 2014 Long Valley Caldera earthquake swarm. In our analysis, 85% of the events (7212 out of 8494 located by Shelly et al. [2016]) fall within five well-constrained mechanism clusters, more than 12 times the number with network-determined mechanisms. Of the earthquakes we characterize, 3023 (42%) have magnitudes smaller than 0.0. We find that mechanism variations are strongly associated with corresponding hypocentral structure, yet mechanism heterogeneity also occurs where it cannot be resolved by hypocentral patterns, often confined to small-magnitude events. Small (5–20°) rotations between mechanism orientations and earthquake location trends persist when we apply 3-D velocity models and might reflect a geometry of en echelon, interlinked shear, and dilational faulting.

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.

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

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.

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.

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.

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

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.

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

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.

Seismological aspects of the 1989-1990 eruptions at redoubt volcano, Alaska: the SSAM perspective

USGS Publications Warehouse

Stephens, C.D.; Chouet, B.A.; Page, R.A.; Lahr, J.C.; Power, J.A.

1994-01-01

SSAM is a simple and inexpensive tool for continuous monitoring of average seismic amplitudes within selected frequency bands in near real-time on a PC-based data acquisition system. During the 1989-1990 eruption sequence at Redoubt Volcano, the potential of SSAM to aid in rapid identification of precursory Long-Period (LP) event swarms was realized, and since this time SSAM has been incorporated in routine monitoring efforts of the Alaska Volcano Observatory. In particular, an eruption that occurred on April 6 was successfully forecast primarily on the basis of recognizing the precursory LP activity on SSAM. Of twenty-two significant eruptions that occurred between December 14 and April 21, eleven had precursory swarms longer than one hour in duration that could be detected on SSAM. For individual swarms, the patterns of relative spectral amplitudes are distinct at each station and remain largely stationary through time, thus indicating that one source may have been preferentially and repeatedly activated throughout the swarm. Typically, a single spectral band dominates the signal at each seismic station: for the vigorous one-day swarm that preceded the first eruption on December 14, signals were sharply peaked in the 1.9-2.7 Hz band at the closest station, located 4 km from the vent, but were dominated by 1.3-1.9 Hz energy at three more distant stations located 7.5-22 km from the vent. The tendency for the signals from different swarms recorded at the same station to be peaked in the same frequency band suggests that all of the sources are characterized by a predominant length scale. Signals from the precursory LP swarms became weaker as the eruption sequence progressed, and swarms that occurred in March and April could only be detected at seismographs on the volcanic edifice. Onset times of precursory LP swarms prior to eruptions ranged from a few hours to about one week, but after the initial vent-clearing phase that ended December 19 these intervals tended to become progressively shorter for successive swarms. These trends in the relative onset times and intensities of successive precursory LP swarms are consistent with an overall depressurization of the magmatic system through time. In general, each of the swarms had an emergent onset, but the intensities did not always increase steadily until the eruptions. Instead, as the time of an eruption approached the intensity usually increased more rapidly before peaking and then declining prior to the eruption; for three of the swarms, two distinct peaks in intensity were apparent. The time intervals between final peaks in swarm intensity and ensuing eruptions ranged from about 2 hours to almost 2 days, but the peaks always occurred closer to the eruptions than to the swarm onsets. Both the onset of LP swarm activity and a decline in intensity prior to an eruption may represent critical points in the process of pressurization that drives the flow of fluids and gas in a sealed magmatic system. A notable exception to this pattern is the eruption of March 9 which lacked a detectable precursory LP swarm, but was followed by an unusually long period of strong LP seismicity that may have been stimulated by a depressurization of the magmatic system resulting from dome failure. On both December 14 and January 2, the spectra of early syn-eruptive signals have peaked signatures much like those of the spectra of precursory LP activity from shortly before the eruptions; these similarities may indicate that the source of precursory seismicity continued to be active during at least the early part of each eruption. In syn-eruptive signals from March and April recorded at stations on the volcanic edifice, the dominant spectral energy progressively shifts with time during the eruption to lower frequencies; at least part of the energy in these signals may have been generated by the debris flows associated with dome failures. ?? 1994.

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 previous earthquakes stress triggering, however, it can be explained by continuing stress loading at the same asperity from fault slow slip. The phenomena of linear migration is more fitting slow slip model than the migration characteristics of fluid diffusion which satisfied diffusion equation. Comparing the phenomena we observed and the seismological mechanism models, we find that the Luanxian earthquake swarm may be associated with fault slow slip. Fault slow slip may play a role in Luanxian earthquake swarm triggering and sustained activity.

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...

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...

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, ...

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...

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

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

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

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.

Preliminary Analysis of Multibeam, Subbottom, and Water Column Data Collected from the Juan de Fuca Plate and Gorda Ridge Earthquake Swarm Sites, March-April 2008.

NASA Astrophysics Data System (ADS)

Merle, S. G.; Dziak, R. P.; Embley, R. W.; Lupton, J. E.; Greene, R. R.; Chadwick, W. W.; Lilley, M.; Bohnenstiehl, D. R.; Braunmiller, J.; Fowler, M.; Resing, J.

2008-12-01

Two oceanographic expeditions were undertaken in the northeast Pacific during April and September of 2008 to collect a variety of scientific data at the sites of intense earthquake swarms that occurred from 30 March to 9 April 2008. The earthquake swarms were detected by the NOAA/PMEL and US Navy SOSUS hydrophone system in the northeast Pacific. The first swarm occurred within the central Juan de Fuca Plate, ~280 km west of the Oregon coast and ~70 km north of the Blanco Transform Fault Zone (BTFZ). Time history of the events indicate this swarm was not a typical mainshock-aftershock sequence, and was the largest SOSUS detected swarm within the intraplate. This intraplate swarm activity was followed by three distinct clusters of earthquakes located along the BTFZ. Two of the clusters, which began on 10 and 12 April, were initiated by MW 5+ earthquakes suggesting these were mainshock-aftershock sequences, and the number of earthquakes on the BTFZ were small relative to the intraplate swarm. On 22 April, another intense earthquake swarm began on the northern Gorda Ridge segment adjacent to the BTFZ. The Gorda swarm produced >1000 SOSUS detected earthquakes over a five-day duration, with activity distributed between the mid-segment high and the ridge-transform intersection. This swarm was of special interest because of previous magmatic activity near its location in 1996. Overall, the March-April earthquake activity showed an interesting spatio-temporal progression, beginning at the intraplate, to the transform, then to a spreading event at the ridge. This pattern once again demonstrates the Juan de Fuca plate is continually moving and converging with North America at the Cascadia Subduction Zone. As the initial swarm was not focused on the ridge crest, it was not interpreted as a significant eruptive event, and we did not advocate a large-scale Ridge2000 response effort. The earthquake activity, however, did have an unusual character and therefore a short (four-day) cruise was organized using the R/V Wecoma in April (support via NOAA Vents Program and NSF). While this cruise was underway, the Gorda Ridge swarm began and therefore another day was added to also sample the Gorda site. A total of 11 CTD casts were completed, covering the significant areas of earthquake activity. Measurements for helium isotopes have been completed on all 11 casts, and for methane and CO2 on one of the Gorda Ridge casts. A second response cruise aboard the R/V Melville will take place in September, funded by the NOAA/Vents, providing 2 days of multibeam survey time. The cruise plan is to collect EM120 multibeam bathymetry and backscatter data, as well as 3.5 kHz subbottom in the area of the initial swarm. The northern Gorda Ridge will also be surveyed, with the goal of comparing this bathymetry with previously collected data to see if there is evidence of depth anomalies and therefore recent seafloor eruptions.

FRAN and RBF-PSO as two components of a hyper framework to recognize protein folds.

PubMed

Abbasi, Elham; Ghatee, Mehdi; Shiri, M E

2013-09-01

In this paper, an intelligent hyper framework is proposed to recognize protein folds from its amino acid sequence which is a fundamental problem in bioinformatics. This framework includes some statistical and intelligent algorithms for proteins classification. The main components of the proposed framework are the Fuzzy Resource-Allocating Network (FRAN) and the Radial Bases Function based on Particle Swarm Optimization (RBF-PSO). FRAN applies a dynamic method to tune up the RBF network parameters. Due to the patterns complexity captured in protein dataset, FRAN classifies the proteins under fuzzy conditions. Also, RBF-PSO applies PSO to tune up the RBF classifier. Experimental results demonstrate that FRAN improves prediction accuracy up to 51% and achieves acceptable multi-class results for protein fold prediction. Although RBF-PSO provides reasonable results for protein fold recognition up to 48%, it is weaker than FRAN in some cases. However the proposed hyper framework provides an opportunity to use a great range of intelligent methods and can learn from previous experiences. Thus it can avoid the weakness of some intelligent methods in terms of memory, computational time and static structure. Furthermore, the performance of this system can be enhanced throughout the system life-cycle. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

Observations of hybrid seismic events at Soufriere Hills Volcano, Montserrat: July 1995 to September 1996

USGS Publications Warehouse

White, R.A.; Miller, A.D.; Lynch, L.; Power, J.

1998-01-01

Swarms of small repetitive events with similar waveforms and magnitudes are often observed during the emplacement of lava domes. Over 300 000 such events were recorded in association with the emplacement of the lava dome at Soufriere Hills Volcano, Montserrat, from August 1995 through August 1996. These events originated <2-3 km deep. They exhibited energy ranging over ??1.5-4.5 Hz and were broader band than typical long-period events. We term the events 'hybrid' between long-period and voclano-tectonic. The events were more impulsive and broader band prior to, compared with during and after, periods of inferred increased magma flux rate. Individual swarms contained up to 10 000 events often exhibiting very similar magnitudes and waveforms throughout the swarm. Swarms lasted hours to weeks, during which inter-event intervals generally increased, then decreased, often several times. Long-duration swarms began about every two months starting in late September 1995. We speculate that the events were produced as the magma column degassed into adjacent cracks.Swarms of small repetitive events with similar waveforms and magnitudes are often observed during the emplacement of lava domes. Over 300,000 such events were recorded in association with the emplacement of the lava dome at Soufriere Hills Volcano, Montserrat, from August 1995 through August 1996. These events originated <2-3 km deep. They exhibited energy ranging over approximately 1.5-4.5 Hz and were broader band than typical long-period events. We term the events `hybrid' between long-period and volcano-tectonic. The events were more impulsive and broader band prior to, compared with during and after, periods of inferred increased magma flux rate. Individual swarms contained up to 10,000 events often exhibiting very similar magnitudes and waveforms throughout the swarm. Swarms lasted hours to weeks, during which inter-event intervals generally increased, then decreased, often several times. Long-duration swarms began about every two months starting in late September 1995. We speculate that the events were produced as the magma column degassed into adjacent cracks.

Hydroacoustical evidence of the expansion of pelagic swarms of Munida gregaria (Decapoda, Munididae) in the Beagle Channel and the Argentine Patagonian Shelf, and its relationship with habitat features

NASA Astrophysics Data System (ADS)

Diez, Mariano J.; Cabreira, Ariel G.; Madirolas, Adrián; Lovrich, Gustavo A.

2016-08-01

Squat lobsters are highly diversified and widespread decapods, of which only three species form pelagic swarms. Here we infer the expansion of Munida gregaria populations in the Beagle Channel and the Argentine Patagonian Shelf by means of acoustic surveys of pelagic swarms. We also describe the habitat characteristics in which these swarms occur. Acoustic data was collected during three multidisciplinary scientific cruises on board of the R/V Puerto Deseado during 2009, 2012 and 2014. Despite differences in the environmental conditions between the two surveyed areas, between 2009 and 2014 pelagic swarms increased their occurrence and abundance both in the Beagle Channel and on the Argentine Patagonian Shelf. Towards the end of the studied period, pelagic swarms of M. gregaria occurred in new locations, supporting the notion of a population expansion. Within the Beagle Channel swarm expansions were more marked than on the Patagonian Shelf. We here postulate that M. gregaria expansions occur in association with productive areas of the Argentine continental shelf, such as frontal zones, favoured by the squat lobster phenotypic plasticity that permit to exploit resources in both the neritic and benthic environments. At a regional scale on the Patagonian Shelf, three main groups of pelagic swarms of M. gregaria were clearly associated to respective frontal zones. The information presented here is necessary to understand fluctuations in both distribution and abundance patterns of a key species on the Argentine continental shelf. These fluctuations could be direct or indirect indicators of changes in the ecosystem.

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.

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 ...

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...

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...

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Control of microfabricated structures powered by flagellated bacteria using phototaxis

NASA Astrophysics Data System (ADS)

Steager, Edward; Kim, Chang-Beom; Patel, Jigarkumar; Bith, Socheth; Naik, Chandan; Reber, Lindsay; Kim, Min Jun

2007-06-01

Flagellated bacteria have been employed as microactuators in low Reynolds number fluidic environments. SU-8 microstructures have been fabricated and released on the surface of swarming Serratia marcescens, and the flagella propel the structures along the swarm surface. Phototactic control of these structures is demonstrated by exposing the localized regions of the swarm to ultraviolet light. The authors additionally discuss the control of microstructures in an open channel powered by bacteria which have been docked through a blotting technique. A tracking algorithm has been developed to analyze swarming patterns of the bacteria as well as the kinematics of the microstructures.

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.

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.

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.

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…

Biologically driven neural platform invoking parallel electrophoretic separation and urinary metabolite screening.

PubMed

Page, Tessa; Nguyen, Huong Thi Huynh; Hilts, Lindsey; Ramos, Lorena; Hanrahan, Grady

2012-06-01

This work reveals a computational framework for parallel electrophoretic separation of complex biological macromolecules and model urinary metabolites. More specifically, the implementation of a particle swarm optimization (PSO) algorithm on a neural network platform for multiparameter optimization of multiplexed 24-capillary electrophoresis technology with UV detection is highlighted. Two experimental systems were examined: (1) separation of purified rabbit metallothioneins and (2) separation of model toluene urinary metabolites and selected organic acids. Results proved superior to the use of neural networks employing standard back propagation when examining training error, fitting response, and predictive abilities. Simulation runs were obtained as a result of metaheuristic examination of the global search space with experimental responses in good agreement with predicted values. Full separation of selected analytes was realized after employing optimal model conditions. This framework provides guidance for the application of metaheuristic computational tools to aid in future studies involving parallel chemical separation and screening. Adaptable pseudo-code is provided to enable users of varied software packages and modeling framework to implement the PSO algorithm for their desired use.

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 Volcan Hudson (last erupted 1991) and Volcan Maca. Given uncertainties in the event locations, the 2007 seismic swarm could also result from a combination of tectonic motions on the Liquiñe-Ofqui fault system and magmatic arc activity. The two earthquakes with magnitudes over 5 and the numerous felt earthquake of the swarm clearly indicate that seismic hazard estimations in this previously quiescent region must be re-estimated.

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 associated with the absorption capacity of the swarm. When parameters of the swarm are set as follows: each Aspergillus Niger spore aggregated particle contains 40 original particles, the radius of original particle is 1.5μm, the density of aggregated particles is around 200/cm3, the measurement area is 4 meters thick, under conditions mentioned above, the infrared transmittance can be less than 10% between the incident wavelengths of 9.5-13μm. In the end, all the results provide the basis for better developing the microorganism aggregated particle swarm as a new kind of infrared functional materials and precisely choosing the effective defiladed infrared band.

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

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.

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.

Pore Pressure Diffusion as a possible mechanism for the Ag. Ioanis 2001 earthquake swarm activity (Gulf of Corinth, Central Greece).

NASA Astrophysics Data System (ADS)

Vallianatos, F.; Michas, G.; Papadakis, G.; Sammonds, P.

2012-04-01

The Gulf of Corinth rift (Central Greece) is one of the most seismotectonically active areas in Europe (Ambraseys and Jackson, 1990; 1997), with an important continental N-S extension of about 13 mm/yr and 6 mm/yr at the west and east part respectively (Clarke et al., 1997a). The seismicity of the area includes 5 main earthquakes of magnitude greater than 5.8 since 1960. In the western part of the rift, where the extension reaches its maximum value, earthquake swarms are often being observed (Bourouis and Cornet, 2009). Such an earthquake crisis has been occurred on 2001 at the southern margin of the west part of the rift. The crisis lasted about 100 days with a major event the Ag. Ioanis earthquake (4.3 Mw) on 8th of April 2001 (Pacchiani and Lyon-Caen, 2010). The possible relation between fluids flow and the observed earthquake swarms at the west part of the Gulf of Corinth rift has been discussed in the works of Bourouis and Cornet (2009) and Pacchiani and Lyon-Caen (2010). In the present work we examine the spatiotemporal properties of the Ag. Ioanis 2001 earthquake swarm, using data from the CRL network (http://crlab.eu/). We connect these properties to a mechanism due to pore pressure diffusion (Shapiro et al., 1997) and we estimate the hydraulic diffusivity and the permeability of the surrounding rocks. A back front of the seismicity (Parotidis et al., 2004) is also been observed, related to the migration of seismicity and the development of a quiescence region near the area of the initial pore pressure perturbation. Moreover, anisotropy of the hydraulic diffusivity has been observed, revealing the heterogeneity of the surrounding rocks and the fracture systems. This anisotropy is consistent in direction with the fault zone responsible for the Ag. Ioanis earthquake (Pacchiani and Lyon-Caen, 2010). Our results indicate that fluids flow and pore pressure perturbations are possible mechanisms for the initiation and the evolution of the Ag. Ioanis 2001 earthquake swarm activity and reveal the possible connection of the complex fracture network to the spatial evolution of seismicity on an active tectonic region as is the Gulf of Corinth rift. Acknowledgments. This work was supported in part by the THALES Program of the Ministry of Education of Greece and the European Union in the framework of the project entitled "Integrated understanding of Seismicity, using innovative Methodologies of Fracture mechanics along with Earthquake and non-extensive statistical physics - Application to the geodynamic system of the Hellenic Arc. SEISMO FEAR HELLARC". GM and GP wish to acknowledge the partial support of the Greek State Scholarships Foundation (IKY).

ANTS: A New Concept for Very Remote Exploration with Intelligent Software Agents

NASA Astrophysics Data System (ADS)

Clark, P. E.; Curtis, S.; Rilee, M.; Truszkowski, W.; Iyengar, J.; Crawford, H.

2001-12-01

ANTS (Autonomous Nano-Technology Swarm), a NASA advanced mission concept, is a large (100 to 1000 member) swarm of pico-class (1 kg) totally autonomous spacecraft that prospect the asteroid belt. As the capacity and complexity of hardware and software, and the sophistication of technical and scientific goals have increased, greater cost constraints have led to fewer resources and thus, the need to operate spacecraft with less frequent contact. At present, autonomous operation of spacecraft systems allows great capability of spacecraft to 'safe' themselves when conditions threaten spacecraft safety. To further develop spacecraft capability, NASA is at the forefront of Intelligent Software Agent (ISA) research, performing experiments in space and on the ground to advance deliberative and collaborative autonomous control techniques. Selected missions in current planning stages require small groups of spacecraft to cooperate at a tactical level to select and schedule measurements to be made by appropriate instruments to characterize rapidly unfolding real-time events on a routine basis. The next level of development, which we are considering here, is in the use of ISAs at a strategic level, to explore the final, remote frontiers of the solar system, potentially involving a large class of objects with only infrequent contact possible. Obvious mission candidates are mainbelt asteroids, a population consisting of more than a million small bodies. Although a large fraction of solar system objects are asteroids, little data is available for them because the vast majority of them are too small to be observed except in close proximity. Asteroids originated in the transitional region between the inner (rocky) and outer (solidified gases) solar system, have remained largely unmodified since formation, and thus have a more primitive composition which includes higher abundances of siderophile (metallic iron-associated) elements and volatiles than other planetary surfaces. As a result, there has been interest in asteroids as sources of exploitable resources. Far more reconnaissance is required before such a program is undertaken. A traditional mission approach (to explore larger asteroids sequentially) is not adequate for determining the systematic distribution of exploitable material in the asteroid population. Our approach involves the use of distributed intelligence in a swarm of tiny spacecraft, each with specialized instrument capability (e.g., advanced computing, imaging, spectrometry, etc.) to evaluate the resource potential of the entire population. Supervised clusters of spacecraft will operate simultaneously within a broadly defined framework of goals to select targets (>1000) from among available candidates and to develop scenarios for studying targets simultaneously. Spacecraft use solar sails to fly directly to asteroids 1 kilometer or greater in diameter. Selected swarm members return to Earth with data, replacements join the swarm as needed. We would like to acknowledge our students R. Watson, V. Cox, and F. Olukomo for their support of this work.

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.

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.

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.

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.

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.

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

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

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.

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.

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.

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.

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.

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

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

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.

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.

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.

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.

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.

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

Resilience and Controllability of Dynamic Collective Behaviors

PubMed Central

Komareji, Mohammad; Bouffanais, Roland

2013-01-01

The network paradigm is used to gain insight into the structural root causes of the resilience of consensus in dynamic collective behaviors, and to analyze the controllability of the swarm dynamics. Here we devise the dynamic signaling network which is the information transfer channel underpinning the swarm dynamics of the directed interagent connectivity based on a topological neighborhood of interactions. The study of the connectedness of the swarm signaling network reveals the profound relationship between group size and number of interacting neighbors, which is found to be in good agreement with field observations on flock of starlings [Ballerini et al. (2008) Proc. Natl. Acad. Sci. USA, 105: 1232]. Using a dynamical model, we generate dynamic collective behaviors enabling us to uncover that the swarm signaling network is a homogeneous clustered small-world network, thus facilitating emergent outcomes if connectedness is maintained. Resilience of the emergent consensus is tested by introducing exogenous environmental noise, which ultimately stresses how deeply intertwined are the swarm dynamics in the physical and network spaces. The availability of the signaling network allows us to analytically establish for the first time the number of driver agents necessary to fully control the swarm dynamics. PMID:24358209

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

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.

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.

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.

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.

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.

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

Molecular Interaction and Cellular Location of RecA and CheW Proteins in Salmonella enterica during SOS Response and Their Implication in Swarming.

PubMed

Irazoki, Oihane; Aranda, Jesús; Zimmermann, Timo; Campoy, Susana; Barbé, Jordi

2016-01-01

In addition to its role in DNA damage repair and recombination, the RecA protein, through its interaction with CheW, is involved in swarming motility, a form of flagella-dependent movement across surfaces. In order to better understand how SOS response modulates swarming, in this work the location of RecA and CheW proteins within the swarming cells has been studied by using super-resolution microscopy. Further, and after in silico docking studies, the specific RecA and CheW regions associated with the RecA-CheW interaction have also been confirmed by site-directed mutagenesis and immunoprecipitation techniques. Our results point out that the CheW distribution changes, from the cell poles to foci distributed in a helical pattern along the cell axis when SOS response is activated or RecA protein is overexpressed. In this situation, the CheW presents the same subcellular location as that of RecA, pointing out that the previously described RecA storage structures may be modulators of swarming motility. Data reported herein not only confirmed that the RecA-CheW pair is essential for swarming motility but it is directly involved in the CheW distribution change associated to SOS response activation. A model explaining not only the mechanism by which DNA damage modulates swarming but also how both the lack and the excess of RecA protein impair this motility is proposed.

Preparation, Imaging, and Quantification of Bacterial Surface Motility Assays

PubMed Central

Morales-Soto, Nydia; Anyan, Morgen E.; Mattingly, Anne E.; Madukoma, Chinedu S.; Harvey, Cameron W.; Alber, Mark; Déziel, Eric; Kearns, Daniel B.; Shrout, Joshua D.

2015-01-01

Bacterial surface motility, such as swarming, is commonly examined in the laboratory using plate assays that necessitate specific concentrations of agar and sometimes inclusion of specific nutrients in the growth medium. The preparation of such explicit media and surface growth conditions serves to provide the favorable conditions that allow not just bacterial growth but coordinated motility of bacteria over these surfaces within thin liquid films. Reproducibility of swarm plate and other surface motility plate assays can be a major challenge. Especially for more “temperate swarmers” that exhibit motility only within agar ranges of 0.4%-0.8% (wt/vol), minor changes in protocol or laboratory environment can greatly influence swarm assay results. “Wettability”, or water content at the liquid-solid-air interface of these plate assays, is often a key variable to be controlled. An additional challenge in assessing swarming is how to quantify observed differences between any two (or more) experiments. Here we detail a versatile two-phase protocol to prepare and image swarm assays. We include guidelines to circumvent the challenges commonly associated with swarm assay media preparation and quantification of data from these assays. We specifically demonstrate our method using bacteria that express fluorescent or bioluminescent genetic reporters like green fluorescent protein (GFP), luciferase (lux operon), or cellular stains to enable time-lapse optical imaging. We further demonstrate the ability of our method to track competing swarming species in the same experiment. PMID:25938934

Multi-Item Multiperiodic Inventory Control Problem with Variable Demand and Discounts: A Particle Swarm Optimization Algorithm

PubMed Central

Mousavi, Seyed Mohsen; Niaki, S. T. A.; Bahreininejad, Ardeshir; Musa, Siti Nurmaya

2014-01-01

A multi-item multiperiod inventory control model is developed for known-deterministic variable demands under limited available budget. Assuming the order quantity is more than the shortage quantity in each period, the shortage in combination of backorder and lost sale is considered. The orders are placed in batch sizes and the decision variables are assumed integer. Moreover, all unit discounts for a number of products and incremental quantity discount for some other items are considered. While the objectives are to minimize both the total inventory cost and the required storage space, the model is formulated into a fuzzy multicriteria decision making (FMCDM) framework and is shown to be a mixed integer nonlinear programming type. In order to solve the model, a multiobjective particle swarm optimization (MOPSO) approach is applied. A set of compromise solution including optimum and near optimum ones via MOPSO has been derived for some numerical illustration, where the results are compared with those obtained using a weighting approach. To assess the efficiency of the proposed MOPSO, the model is solved using multi-objective genetic algorithm (MOGA) as well. A large number of numerical examples are generated at the end, where graphical and statistical approaches show more efficiency of MOPSO compared with MOGA. PMID:25093195

Automatic Parameter Tuning for the Morpheus Vehicle Using Particle Swarm Optimization

NASA Technical Reports Server (NTRS)

Birge, B.

2013-01-01

A high fidelity simulation using a PC based Trick framework has been developed for Johnson Space Center's Morpheus test bed flight vehicle. There is an iterative development loop of refining and testing the hardware, refining the software, comparing the software simulation to hardware performance and adjusting either or both the hardware and the simulation to extract the best performance from the hardware as well as the most realistic representation of the hardware from the software. A Particle Swarm Optimization (PSO) based technique has been developed that increases speed and accuracy of the iterative development cycle. Parameters in software can be automatically tuned to make the simulation match real world subsystem data from test flights. Special considerations for scale, linearity, discontinuities, can be all but ignored with this technique, allowing fast turnaround both for simulation tune up to match hardware changes as well as during the test and validation phase to help identify hardware issues. Software models with insufficient control authority to match hardware test data can be immediately identified and using this technique requires very little to no specialized knowledge of optimization, freeing model developers to concentrate on spacecraft engineering. Integration of the PSO into the Morpheus development cycle will be discussed as well as a case study highlighting the tool's effectiveness.

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

Seismically active column and volcanic plumbing system beneath the island arc of the Izu-Bonin subduction zone

NASA Astrophysics Data System (ADS)

Špičák, Aleš; Vaněk, Jiří; Hanuš, Václav

2009-12-01

A detailed spatio-temporal analysis of teleseismic earthquake occurrence (mb > 4.0) along the convergent margin of the Izu-Bonin-Mariana arc system reveals an anomalously high concentration of events between 27° and 30.5°N, beneath a chain of seamounts between Tori-shima and Nishino-shima volcanoes. This seismicity is dominated by the 1985/1986 earthquake swarm represented in the Engdahl—van der Hilst—Buland database by 146 earthquakes in the body wave magnitude range 4.3-5.8 and focal depth range 1-100 km. The epicentral cluster of the swarm is elongated parallel to the volcanic chain. Available focal mechanisms are consistent with an extensional tectonic regime and reveal nodal planes with azimuths close to that of the epicentral cluster. Earthquakes of the 1985/1986 swarm occurred in seven time phases. Seismic activity migrated in space from one phase to the other. Earthquake foci belonging to individual phases of the swarm aligned in vertically disposed seismically active columns. The epicentral zones of the columns are located in the immediate vicinity of seamounts Suiyo and Mokuyo, recently reported by the Japanese Meteorological Agency as volcanically active. The three observations—episodic character of earthquake occurrence, column-like vertically arranged seismicity pattern, and existence of volcanic seamounts at the seafloor above the earthquake foci—led us to interpret the 1985/1986 swarm as a consequence of subduction-related magmatic and/or fluid activity. A modification of the shallow earthquake swarm magmatic model of D. Hill fits earthquake foci distribution, tectonic stress orientation and fault plane solutions. The 1985/1986 deep-rooted earthquake swarm in the Izu-Bonin region represents an uncommon phenomenon of plate tectonics. The portion of the lithospheric wedge that was affected by the swarm should be composed of fractured rigid, brittle material so that the source of magma and/or fluids which might induce the swarm should be situated at a depth of at least 100 km in the aseismic part of the subduction zone.

Seismically active column and volcanic plumbing system beneath the island arc of the Izu-Bonin subduction zone

NASA Astrophysics Data System (ADS)

Špičák, Aleš; Vaněk, Jiří; Hanuš, Václav

2009-12-01

A detailed spatio-temporal analysis of teleseismic earthquake occurrence (mb > 4.0) along the convergent margin of the Izu-Bonin-Mariana arc system reveals an anomalously high concentration of events between 27° and 30.5°N, beneath a chain of seamounts between Tori-shima and Nishino-shima volcanoes. This seismicity is dominated by the 1985/1986 earthquake swarm represented in the Engdahl-van der Hilst-Buland database by 146 earthquakes in the body wave magnitude range 4.3-5.8 and focal depth range 1-100 km. The epicentral cluster of the swarm is elongated parallel to the volcanic chain. Available focal mechanisms are consistent with an extensional tectonic regime and reveal nodal planes with azimuths close to that of the epicentral cluster. Earthquakes of the 1985/1986 swarm occurred in seven time phases. Seismic activity migrated in space from one phase to the other. Earthquake foci belonging to individual phases of the swarm aligned in vertically disposed seismically active columns. The epicentral zones of the columns are located in the immediate vicinity of seamounts Suiyo and Mokuyo, recently reported by the Japanese Meteorological Agency as volcanically active. The three observations-episodic character of earthquake occurrence, column-like vertically arranged seismicity pattern, and existence of volcanic seamounts at the seafloor above the earthquake foci-led us to interpret the 1985/1986 swarm as a consequence of subduction-related magmatic and/or fluid activity. A modification of the shallow earthquake swarm magmatic model of D. Hill fits earthquake foci distribution, tectonic stress orientation and fault plane solutions. The 1985/1986 deep-rooted earthquake swarm in the Izu-Bonin region represents an uncommon phenomenon of plate tectonics. The portion of the lithospheric wedge that was affected by the swarm should be composed of fractured rigid, brittle material so that the source of magma and/or fluids which might induce the swarm should be situated at a depth of at least 100 km in the aseismic part of the subduction zone.

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

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.

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

An Electromagnetic Pulse (EMP) can severely disrupt the use of electronic devices in its path causing a significant amount of infrastructural damage. EMP can also cause breakdown of the surrounding atmosphere during lightning discharges. This makes modeling EMP phenomenon an important research effort in many military and atmospheric physics applications. EMP events include high-energy Compton electrons or photoelectrons that ionize air and produce low energy conduction electrons. A sufficient number of conduction electrons will damp or alter the EMP through conduction current. Therefore, it is important to understand how conduction electrons interact with air in order to accurately predict the EMP evolution and propagation in the air. It is common for EMP simulation codes to use an equilibrium ohmic model for computing the conduction current. Equilibrium ohmic models assume the conduction electrons are always in equilibrium with the local instantaneous electric field, i.e. for a specific EMP electric field, the conduction electrons instantaneously reach steady state without a transient process. An equilibrium model will work well if the electrons have time to reach their equilibrium distribution with respect to the rise time or duration of the EMP. If the time to reach equilibrium is comparable or longer than the rise time or duration of the EMP then the equilibrium model would not accurately predict the conduction current necessary for the EMP simulation. This is because transport coefficients used in the conduction current calculation will be found based on equilibrium reactions rates which may differ significantly from their non-equilibrium values. We see this deficiency in Los Alamos National Laboratory's EMP code, CHAP-LA (Compton High Altitude Pulse-Los Alamos), when modeling certain EMP scenarios at high altitudes, such as upward EMP, where the ionization rate by secondary electrons is over predicted by the equilibrium model, causing the EMP to short 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 additional physical parameters such as the O2 electron attachment rate, recombination rate, and mutual neutralization rate. This necessitates tracking the positive and negative ion densities in the swarm model. Adding these parameters, especially electron attachment, is important at lower EMP altitudes where atmospheric density is high. We compare swarm model equilibrium temperatures and times using the HLO and BOLSIG+ coefficients for a uniform electric field of 1 StatV/cm for a range of atmospheric heights. This is done in order to test sensitivity to the swarm parameters used in the swarm model. It is shown that the equilibrium temperature and time are sensitive to the modifications in the collision frequency and ionization rate based on the updated electron interaction cross sections. We validate the swarm model by comparing ionization coefficients and equilibrium drift velocities to experimental results over a wide range of reduced electric field values. The final part of the PhD thesis work includes integrating the swarm model into CHAP-LA. We discuss the physics included in the CHAP-LA EMP model and demonstrate EMP damping behavior caused by the ohmic model at high altitudes. We report on numerical techniques for incorporation of the swarm model into CHAP-LA's Maxwell solver. This includes a discussion of integration techniques for Maxwell's equations in CHAP-LA using the swarm model calculated conduction current. We show improvements on EMP parameter calculations when modeling a high altitude, upward EMP scenario. This provides a novel computational capability that will have an important impact on the atmospheric and EMP research community.

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.

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

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.

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.

Physical mechanisms for chemotactic pattern formation by bacteria.

PubMed Central

Brenner, M P; Levitov, L S; Budrene, E O

1998-01-01

This paper formulates a theory for chemotactic pattern formation by the bacteria Escherichia coli in the presence of excreted attractant. In a chemotactically neutral background, through chemoattractant signaling, the bacteria organize into swarm rings and aggregates. The analysis invokes only those physical processes that are both justifiable by known biochemistry and necessary and sufficient for swarm ring migration and aggregate formation. Swarm rings migrate in the absence of an external chemoattractant gradient. The ring motion is caused by the depletion of a substrate that is necessary to produce attractant. Several scaling laws are proposed and are demonstrated to be consistent with experimental data. Aggregate formation corresponds to finite time singularities in which the bacterial density diverges at a point. Instabilities of swarm rings leading to aggregate formation occur via a mechanism similar to aggregate formation itself: when the mass density of the swarm ring exceeds a threshold, the ring collapses cylindrically and then destabilizes into aggregates. This sequence of events is demonstrated both in the theoretical model and in the experiments. PMID:9545032

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.

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

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.

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

Tectonic stress regime in the 2003-2004 and 2012-2015 earthquake swarms in the Ubaye Valley, French Alps

NASA Astrophysics Data System (ADS)

Fojtíková, Lucia; Vavryčuk, Václav

2018-02-01

We study two earthquake swarms that occurred in the Ubaye Valley, French Alps within the past decade: the 2003-2004 earthquake swarm with the strongest shock of magnitude ML = 2.7, and the 2012-2015 earthquake swarm with the strongest shock of magnitude ML = 4.8. The 2003-2004 seismic activity clustered along a 9-km-long rupture zone at depth between 3 and 8 km. The 2012-2015 activity occurred a few kilometres to the northwest from the previous one. We applied the iterative joint inversion for stress and fault orientations developed by Vavryčuk (2014) to focal mechanisms of 74 events of the 2003-2004 swarm and of 13 strongest events of the 2012-2015 swarm. The retrieved stress regime is consistent for both seismic activities. The σ 3 principal axis is nearly horizontal with azimuth of 103°. The σ 1 and σ 2 principal axes are inclined and their stress magnitudes are similar. The active faults are optimally oriented for shear faulting with respect to tectonic stress and differ from major fault systems known from geological mapping in the region. The estimated low value of friction coefficient at the faults 0.2-0.3 supports an idea of seismic activity triggered or strongly affected by presence of fluids.

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.

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.

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

An Approach for Autonomy: A Collaborative Communication Framework for Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Dufrene, Warren Russell, Jr.

2005-01-01

Research done during the last three years has studied the emersion properties of Complex Adaptive Systems (CAS). The deployment of Artificial Intelligence (AI) techniques applied to remote Unmanned Aerial Vehicles has led the author to investigate applications of CAS within the field of Autonomous Multi-Agent Systems. The core objective of current research efforts is focused on the simplicity of Intelligent Agents (IA) and the modeling of these agents within complex systems. This research effort looks at the communication, interaction, and adaptability of multi-agents as applied to complex systems control. The embodiment concept applied to robotics has application possibilities within multi-agent frameworks. A new framework for agent awareness within a virtual 3D world concept is possible where the vehicle is composed of collaborative agents. This approach has many possibilities for applications to complex systems. This paper describes the development of an approach to apply this virtual framework to the NASA Goddard Space Flight Center (GSFC) tetrahedron structure developed under the Autonomous Nano Technology Swarm (ANTS) program and the Super Miniaturized Addressable Reconfigurable Technology (SMART) architecture program. These projects represent an innovative set of novel concepts deploying adaptable, self-organizing structures composed of many tetrahedrons. This technology is pushing current applied Agents Concepts to new levels of requirements and adaptability.

Communities of Social Bees (Apidae: Meliponini) in Trap-Nests: the Spatial Dynamics of Reproduction in an Area of Atlantic Forest.

PubMed

Silva, M D; Ramalho, M; Monteiro, D

2014-08-01

As most stingless bee species depend on preexisting cavities, principally tree hollows, nesting site availability may represent an important restriction in the structuring of their forest communities. The present study examined the spatial dynamics of stingless bee communities in an area of Atlantic Forest by evaluating their swarming to trap-nests. The field work was performed in the Michelin Ecological Reserve (MER) on the southeastern coast of the state of Bahia, Brazil. Seven hundred and twenty trap-nests were distributed within two forest habitats in advanced and initial stages of regeneration. The trap-nests were monitored between September 2009 and March 2011. Twenty-five trap-nests were occupied by five bee species, resulting in a capture ratio of 0.035 swarms/trap (approximately 0.14 swarms/ha), corresponding to 10 swarms/year (0.056 swarms/ha/year). According to previous study at MER, the most abundant species in natural nests were also the most common in trap-nests in the two forest habitats examined, with the exception of Melipona scutellaris Latreille. Swarms of higher numbers of species were captured in initial regeneration stage forests than in advanced regeneration stage areas, and differences in species compositions were significant between both habitats (p = 0.03); these apparent differences were not consistent, however, when considering richness (p = 0.14) and total abundance (p = 0.08). The present study suggests the existence of a minimum cavity size threshold of approximately 1 L for most local species of stingless bees and sustains the hypothesis of a mass effect of Tetragonisca angustula Latreille populations from surrounding disturbed habitats on the MER forest community in terms of propagule (swarm) pressure. Examining swarm densities with trap-nests can be a promising technique for comparative analyses of the carrying capacities of forest habitats for stingless bee colonies, as long as size thresholds of cavities for nesting are taken into consideration.

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.

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 key implications for the questions framed above.

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 Hamouche et al.

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. 2011, and references therein), and we discuss the implications of this architecture for the feeding system of the Tejeda volcano and the associated temporal variations of cone-sheet emplacement. References: Burchardt, S., Tanner, D.C., Troll, V.R., Krumbholz, M., Gustafsson, L.E. (2011) Three-dimensional geometry of concentric intrusive sheet swarms in the Geitafell and the Dyrfjöll volcanoes, eastern Iceland. Geochemistry, Geophysics, Geosystems 12(7): Q0AB09. Burchardt, S., Troll, V.R., Mathieu, L., Emeleus, H.C., Donaldson, C.H. (2013) Ardnamruchan 3D cone-sheet architecture explained by a single elongate magma chamber. Scientific Reports 3:2891. Schirnick, C. (1996) Formation of an intracaldera cone sheet dike swarm (Tejeda Caldera, Gran Canaria) (Dissertation). Christian-Albrechts-Universität, Kiel, Germany. Schirnick, C., van den Bogaard, P., Schmincke, H.-U. (1999) Cone-sheet formation and intrusive growth of an oceanic island - The Miocene Tejeda complex on Gran Canaria (Canary Islands). Geology, 27: 207-210.

Novel probabilistic and distributed algorithms for guidance, control, and nonlinear estimation of large-scale multi-agent systems

NASA Astrophysics Data System (ADS)

Bandyopadhyay, Saptarshi

Multi-agent systems are widely used for constructing a desired formation shape, exploring an area, surveillance, coverage, and other cooperative tasks. This dissertation introduces novel algorithms in the three main areas of shape formation, distributed estimation, and attitude control of large-scale multi-agent systems. In the first part of this dissertation, we address the problem of shape formation for thousands to millions of agents. Here, we present two novel algorithms for guiding a large-scale swarm of robotic systems into a desired formation shape in a distributed and scalable manner. These probabilistic swarm guidance algorithms adopt an Eulerian framework, where the physical space is partitioned into bins and the swarm's density distribution over each bin is controlled using tunable Markov chains. In the first algorithm - Probabilistic Swarm Guidance using Inhomogeneous Markov Chains (PSG-IMC) - each agent determines its bin transition probabilities using a time-inhomogeneous Markov chain that is constructed in real-time using feedback from the current swarm distribution. This PSG-IMC algorithm minimizes the expected cost of the transitions required to achieve and maintain the desired formation shape, even when agents are added to or removed from the swarm. The algorithm scales well with a large number of agents and complex formation shapes, and can also be adapted for area exploration applications. In the second algorithm - Probabilistic Swarm Guidance using Optimal Transport (PSG-OT) - each agent determines its bin transition probabilities by solving an optimal transport problem, which is recast as a linear program. In the presence of perfect feedback of the current swarm distribution, this algorithm minimizes the given cost function, guarantees faster convergence, reduces the number of transitions for achieving the desired formation, and is robust to disturbances or damages to the formation. We demonstrate the effectiveness of these two proposed swarm guidance algorithms using results from numerical simulations and closed-loop hardware experiments on multiple quadrotors. In the second part of this dissertation, we present two novel discrete-time algorithms for distributed estimation, which track a single target using a network of heterogeneous sensing agents. The Distributed Bayesian Filtering (DBF) algorithm, the sensing agents combine their normalized likelihood functions using the logarithmic opinion pool and the discrete-time dynamic average consensus algorithm. Each agent's estimated likelihood function converges to an error ball centered on the joint likelihood function of the centralized multi-sensor Bayesian filtering algorithm. Using a new proof technique, the convergence, stability, and robustness properties of the DBF algorithm are rigorously characterized. The explicit bounds on the time step of the robust DBF algorithm are shown to depend on the time-scale of the target dynamics. Furthermore, the DBF algorithm for linear-Gaussian models can be cast into a modified form of the Kalman information filter. In the Bayesian Consensus Filtering (BCF) algorithm, the agents combine their estimated posterior pdfs multiple times within each time step using the logarithmic opinion pool scheme. Thus, each agent's consensual pdf minimizes the sum of Kullback-Leibler divergences with the local posterior pdfs. The performance and robust properties of these algorithms are validated using numerical simulations. In the third part of this dissertation, we present an attitude control strategy and a new nonlinear tracking controller for a spacecraft carrying a large object, such as an asteroid or a boulder. If the captured object is larger or comparable in size to the spacecraft and has significant modeling uncertainties, conventional nonlinear control laws that use exact feed-forward cancellation are not suitable because they exhibit a large resultant disturbance torque. The proposed nonlinear tracking control law guarantees global exponential convergence of tracking errors with finite-gain Lp stability in the presence of modeling uncertainties and disturbances, and reduces the resultant disturbance torque. Further, this control law permits the use of any attitude representation and its integral control formulation eliminates any constant disturbance. Under small uncertainties, the best strategy for stabilizing the combined system is to track a fuel-optimal reference trajectory using this nonlinear control law, because it consumes the least amount of fuel. In the presence of large uncertainties, the most effective strategy is to track the derivative plus proportional-derivative based reference trajectory, because it reduces the resultant disturbance torque. The effectiveness of the proposed attitude control law is demonstrated by using results of numerical simulation based on an Asteroid Redirect Mission concept. The new algorithms proposed in this dissertation will facilitate the development of versatile autonomous multi-agent systems that are capable of performing a variety of complex tasks in a robust and scalable manner.

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).

The Improvement of Particle Swarm Optimization: a Case Study of Optimal Operation in Goupitan Reservoir

NASA Astrophysics Data System (ADS)

Li, Haichen; Qin, Tao; Wang, Weiping; Lei, Xiaohui; Wu, Wenhui

2018-02-01

Due to the weakness in holding diversity and reaching global optimum, the standard particle swarm optimization has not performed well in reservoir optimal operation. To solve this problem, this paper introduces downhill simplex method to work together with the standard particle swarm optimization. The application of this approach in Goupitan reservoir optimal operation proves that the improved method had better accuracy and higher reliability with small investment.

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

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.

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.

Glacier quakes mimicking volcanic earthquakes: The challenge of monitoring ice-clad volcanoes and some solutions

NASA Astrophysics Data System (ADS)

Allstadt, K.; Carmichael, J. D.; Malone, S. D.; Bodin, P.; Vidale, J. E.; Moran, S. C.

2012-12-01

Swarms of repeating earthquakes at volcanoes are often a sign of volcanic unrest. However, glaciers also can generate repeating seismic signals, so detecting unrest at glacier-covered volcanoes can be a challenge. We have found that multi-day swarms of shallow, low-frequency, repeating earthquakes occur regularly at Mount Rainier, a heavily glaciated stratovolcano in Washington, but that most swarms had escaped recognition until recently. Typically such earthquakes were too small to be routinely detected by the seismic network and were often buried in the noise on visual records, making the few swarms that had been detected seem more unusual and significant at the time they were identified. Our comprehensive search for repeating earthquakes through the past 10 years of continuous seismic data uncovered more than 30 distinct swarms of low-frequency earthquakes at Rainier, each consisting of hundreds to thousands of events. We found that these swarms locate high on the glacier-covered edifice, occur almost exclusively between late fall and early spring, and that their onset coincides with heavy snowfalls. We interpret the correlation with snowfall to indicate a seismically observable glacial response to snow loading. Efforts are underway to confirm this by monitoring glacier motion before and after a major snowfall event using ground based radar interferometry. Clearly, if the earthquakes in these swarms reflect a glacial source, then they are not directly related to volcanic activity. However, from an operational perspective they make volcano monitoring difficult because they closely resemble earthquakes that often precede and accompany volcanic eruptions. Because we now have a better sense of the background level of such swarms and know that their occurrence is seasonal and correlated with snowfall, it will now be easier to recognize if future swarms at Rainier are unusual and possibly related to volcanic activity. To methodically monitor for such unusual activity, we are implementing an automatic detection algorithm to continuously search for repeating earthquakes at Mount Rainier, an algorithm that we eventually intend to apply to other Cascade volcanoes. We propose that a comprehensive routine that characterizes background levels of repeating earthquakes and the degree of correlation with weather and seasonal forcing, combined with real-time monitoring for repeating earthquakes, will provide a means to more rapidly discriminate between glacier seismicity and seismicity related to volcanic activity on monitored glacier-clad volcanoes.

Magma intrusion near Volcan Tancitaro: Evidence from seismic analysis

DOE PAGES

Pinzon, Juan I.; Nunez-Cornu, Francisco J.; Rowe, Charlotte Anne

2016-11-17

Between May and June 2006, an earthquake swarm occurred near Volcan Tancítaro in Mexico, which was recorded by a temporary seismic deployment known as the MARS network. We located ~1000 events from this seismic swarm. Previous earthquake swarms in the area were reported in the years 1997, 1999 and 2000. We relocate and analyze the evolution and properties of the 2006 earthquake swarm, employing a waveform cross-correlation-based phase repicking technique. Hypocenters from 911 events were located and divided into eighteen families having a correlation coefficient at or above 0.75. 90% of the earthquakes provide at least sixteen phase picks. Wemore » used the single-event location code Hypo71 and the P-wave velocity model used by the Jalisco Seismic and Accelerometer Network to improve hypocenters based on the correlation-adjusted phase arrival times. We relocated 121 earthquakes, which show clearly two clusters, between 9–10 km and 3–4 km depth respectively. The average location error estimates are <1 km epicentrally, and <2 km in depth, for the largest event in each cluster. Depths of seismicity migrate upward from 16 to 3.5 km and exhibit a NE-SW trend. The swarm first migrated toward Paricutin Volcano but by mid-June began propagating back toward Volcán Tancítaro. In addition to its persistence, noteworthy aspects of this swarm include a quasi-exponential increase in the rate of activity within the first 15 days; a b-value of 1.47; a jug-shaped hypocenter distribution; a shoaling rate of ~5 km/month within the deeper cluster, and a composite focal mechanism solution indicating largely reverse faulting. As a result, these features of the swarm suggest a magmatic source elevating the crustal strain beneath Volcan Tancítaro.« less

Magma intrusion near Volcan Tancitaro: Evidence from seismic analysis

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

Pinzon, Juan I.; Nunez-Cornu, Francisco J.; Rowe, Charlotte Anne

Between May and June 2006, an earthquake swarm occurred near Volcan Tancítaro in Mexico, which was recorded by a temporary seismic deployment known as the MARS network. We located ~1000 events from this seismic swarm. Previous earthquake swarms in the area were reported in the years 1997, 1999 and 2000. We relocate and analyze the evolution and properties of the 2006 earthquake swarm, employing a waveform cross-correlation-based phase repicking technique. Hypocenters from 911 events were located and divided into eighteen families having a correlation coefficient at or above 0.75. 90% of the earthquakes provide at least sixteen phase picks. Wemore » used the single-event location code Hypo71 and the P-wave velocity model used by the Jalisco Seismic and Accelerometer Network to improve hypocenters based on the correlation-adjusted phase arrival times. We relocated 121 earthquakes, which show clearly two clusters, between 9–10 km and 3–4 km depth respectively. The average location error estimates are <1 km epicentrally, and <2 km in depth, for the largest event in each cluster. Depths of seismicity migrate upward from 16 to 3.5 km and exhibit a NE-SW trend. The swarm first migrated toward Paricutin Volcano but by mid-June began propagating back toward Volcán Tancítaro. In addition to its persistence, noteworthy aspects of this swarm include a quasi-exponential increase in the rate of activity within the first 15 days; a b-value of 1.47; a jug-shaped hypocenter distribution; a shoaling rate of ~5 km/month within the deeper cluster, and a composite focal mechanism solution indicating largely reverse faulting. As a result, these features of the swarm suggest a magmatic source elevating the crustal strain beneath Volcan Tancítaro.« less

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.

Magma intrusion near Volcan Tancítaro: Evidence from seismic analysis

NASA Astrophysics Data System (ADS)

Pinzón, Juan I.; Núñez-Cornú, Francisco J.; Rowe, Charlotte A.

2017-01-01

Between May and June 2006, an earthquake swarm occurred near Volcan Tancítaro in Mexico, which was recorded by a temporary seismic deployment known as the MARS network. We located ∼1000 events from this seismic swarm. Previous earthquake swarms in the area were reported in the years 1997, 1999 and 2000. We relocate and analyze the evolution and properties of the 2006 earthquake swarm, employing a waveform cross-correlation-based phase repicking technique. Hypocenters from 911 events were located and divided into eighteen families having a correlation coefficient at or above 0.75. 90% of the earthquakes provide at least sixteen phase picks. We used the single-event location code Hypo71 and the P-wave velocity model used by the Jalisco Seismic and Accelerometer Network to improve hypocenters based on the correlation-adjusted phase arrival times. We relocated 121 earthquakes, which show clearly two clusters, between 9-10 km and 3-4 km depth respectively. The average location error estimates are <1 km epicentrally, and <2 km in depth, for the largest event in each cluster. Depths of seismicity migrate upward from 16 to 3.5 km and exhibit a NE-SW trend. The swarm first migrated toward Paricutin Volcano but by mid-June began propagating back toward Volcán Tancítaro. In addition to its persistence, noteworthy aspects of this swarm include a quasi-exponential increase in the rate of activity within the first 15 days; a b-value of 1.47; a jug-shaped hypocenter distribution; a shoaling rate of ∼5 km/month within the deeper cluster, and a composite focal mechanism solution indicating largely reverse faulting. These features of the swarm suggest a magmatic source elevating the crustal strain beneath Volcan Tancítaro.

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.

Fluid-faulting evolution in high definition: Connecting fault structure and frequency-magnitude variations during the 2014 Long Valley Caldera, California earthquake swarm

USGS Publications Warehouse

Shelly, David R.; Ellsworth, William L.; Hill, David P.

2016-01-01

An extended earthquake swarm occurred beneath southeastern Long Valley Caldera between May and November 2014, culminating in three magnitude 3.5 earthquakes and 1145 cataloged events on 26 September alone. The swarm produced the most prolific seismicity in the caldera since a major unrest episode in 1997-1998. To gain insight into the physics controlling swarm evolution, we used large-scale cross-correlation between waveforms of cataloged earthquakes and continuous data, producing precise locations for 8494 events, more than 2.5 times the routine catalog. We also estimated magnitudes for 18,634 events (~5.5 times the routine catalog), using a principal component fit to measure waveform amplitudes relative to cataloged events. This expanded and relocated catalog reveals multiple episodes of pronounced hypocenter expansion and migration on a collection of neighboring faults. Given the rapid migration and alignment of hypocenters on narrow faults, we infer that activity was initiated and sustained by an evolving fluid pressure transient with a low-viscosity fluid, likely composed primarily of water and CO2 exsolved from underlying magma. Although both updip and downdip migration were observed within the swarm, downdip activity ceased shortly after activation, while updip activity persisted for weeks at moderate levels. Strongly migrating, single-fault episodes within the larger swarm exhibited a higher proportion of larger earthquakes (lower Gutenberg-Richter b value), which may have been facilitated by fluid pressure confined in two dimensions within the fault zone. In contrast, the later swarm activity occurred on an increasingly diffuse collection of smaller faults, with a much higher b value.

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

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.

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

Phase polyphenism and preventative locust management.

PubMed

Sword, Gregory A; Lecoq, Michel; Simpson, Stephen J

2010-08-01

The ecology of phase polyphenism plays a major role in locust swarm formation. We describe how recent advances in the understanding of phase polyphenism can be combined with existing management approaches as part of a preventative Desert locust management strategy. We start with a brief overview of phase polyphenism with particular emphasis on the role that resource distribution patterns play in the process of locust phase change. We then review current perspective on preventative locust management, and conclude by proposing a framework for quantitatively assessing the risk that phase change will occur in local locust populations. Importantly, the data required to implement this framework can be readily collected with little additional effort or cost just by slightly modifying locust habitat survey protocols that are already in operation. Incorporating gregarization risk assessment into existing preventative management strategies stands to make a considerable contribution toward realizing sustainable goals of reductions in the pesticide, manpower and financial support necessary to combat Desert locust upsurges, outbreaks and ultimately plagues. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

NASA Technical Reports Server (NTRS)

Cheung, Kar-Ming; Lee, Charles H.

2012-01-01

We developed framework and the mathematical formulation for optimizing communication network using mixed integer programming. The design yields a system that is much smaller, in search space size, when compared to the earlier approach. Our constrained network optimization takes into account the dynamics of link performance within the network along with mission and operation requirements. A unique penalty function is introduced to transform the mixed integer programming into the more manageable problem of searching in a continuous space. The constrained optimization problem was proposed to solve in two stages: first using the heuristic Particle Swarming Optimization algorithm to get a good initial starting point, and then feeding the result into the Sequential Quadratic Programming algorithm to achieve the final optimal schedule. We demonstrate the above planning and scheduling methodology with a scenario of 20 spacecraft and 3 ground stations of a Deep Space Network site. Our approach and framework have been simple and flexible so that problems with larger number of constraints and network can be easily adapted and solved.

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.

Geochemistry of a Triassic dyke swarm in the North Patagonian Massif, Argentina. Implications for a postorogenic event of the Permian Gondwanide orogeny

NASA Astrophysics Data System (ADS)

González, Santiago N.; Greco, Gerson A.; González, Pablo D.; Sato, Ana M.; Llambías, Eduardo J.; Varela, Ricardo

2016-10-01

Permo-Triassic magmatism is widespread in the eastern North Patagonian Massif and has been related to the Gondwanide orogeny. Although a magmatic arc setting is widely accepted for the Permian plutonic rocks, the origin and geotectonic setting for the Triassic plutonic and volcanic rocks are still unknown. A NW-SE Triassic dyke swarm composed of andesites and latites with minor rhyolites was previously described in the Sierra Grande - Rincon de Paileman area. The dyke swarm was associated with extensional tectonics which was linked to a postorogenic process. In this paper we present new geochemical data of the rocks that form the swarm. Trachyandesites and rhyolites were separated based on their geochemical characteristics. Both groups may be considered originated from different sources. On the other hand, the content of incompatible elements (LILE and HFSE) indicates a strong relation between the swarm and an active continental margin. The samples also show a transitional signature between continental-arc and postcollisional or anorogenic settings. The new geochemical data on the dyke swarm support the idea of a magmatism that was linked to a postorogenic extensional tectonic regime related to a continental magmatic arc. Such an extension started in the Paleopacific margin of Pangea during the Anisian and might indicate the beginning of the Pangea break-up.

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.

Arginine promotes Proteus mirabilis motility and fitness by contributing to conservation of the proton gradient and proton motive force

PubMed Central

Armbruster, Chelsie E; Hodges, Steven A; Smith, Sara N; Alteri, Christopher J; Mobley, Harry L T

2014-01-01

Swarming contributes to Proteus mirabilis pathogenicity by facilitating access to the catheterized urinary tract. We previously demonstrated that 0.1–20 mmol/L arginine promotes swarming on normally nonpermissive media and that putrescine biosynthesis is required for arginine-induced swarming. We also previously determined that arginine-induced swarming is pH dependent, indicating that the external proton concentration is critical for arginine-dependent effects on swarming. In this study, we utilized survival at pH 5 and motility as surrogates for measuring changes in the proton gradient (ΔpH) and proton motive force (μH+) in response to arginine. We determined that arginine primarily contributes to ΔpH (and therefore μH+) through the action of arginine decarboxylase (speA), independent of the role of this enzyme in putrescine biosynthesis. In addition to being required for motility, speA also contributed to fitness during infection. In conclusion, consumption of intracellular protons via arginine decarboxylase is one mechanism used by P. mirabilis to conserve ΔpH and μH+ for motility. PMID:25100003

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.

[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.

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.

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.

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

Simulating Flying Insects Using Dynamics and Data-Driven Noise Modeling to Generate Diverse Collective Behaviors

PubMed Central

Ren, Jiaping; Wang, Xinjie; Manocha, Dinesh

2016-01-01

We present a biologically plausible dynamics model to simulate swarms of flying insects. Our formulation, which is based on biological conclusions and experimental observations, is designed to simulate large insect swarms of varying densities. We use a force-based model that captures different interactions between the insects and the environment and computes collision-free trajectories for each individual insect. Furthermore, we model the noise as a constructive force at the collective level and present a technique to generate noise-induced insect movements in a large swarm that are similar to those observed in real-world trajectories. We use a data-driven formulation that is based on pre-recorded insect trajectories. We also present a novel evaluation metric and a statistical validation approach that takes into account various characteristics of insect motions. In practice, the combination of Curl noise function with our dynamics model is used to generate realistic swarm simulations and emergent behaviors. We highlight its performance for simulating large flying swarms of midges, fruit fly, locusts and moths and demonstrate many collective behaviors, including aggregation, migration, phase transition, and escape responses. PMID:27187068

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.

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.

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)

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

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.

Fault and joint measurements in Austin Chalk, Superconducting Super Collider Site, Texas

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

Nance, H.S.; Laubach, S.E.; Dutton, A.R.

1994-12-31

Structure maps of 9.4 mi of nearly continuous tunnel excavations and more than 10 mi of other exposures and excavations in Austin Chalk at the Superconducting Super Collider (SSC) site in Ellis County, Texas, record normal-fault and joint populations in the subsurface within the northern segment of the Balcones Fault Zone with unmatched resolution for such a long traverse. Small faults (<10 ft throw) occur in clusters or swarms that have as many as 24 faults. Fault swarms are as much as 2,000 ft wide, and spacing between swarms ranges from 800 to 2,000 ft, averaging about 1,000 ft. Predominantlymore » northeast-trending joints are in swarms spaced 500 to more than 21,000 ft apart.« less

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.

First Quarter Hanford Seismic Report for Fiscal Year 2010

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

Rohay, Alan C.; Sweeney, Mark D.; Hartshorn, Donald C.

2010-03-29

The Hanford Seismic Network and the Eastern Washington Regional Network consist of 44 individual sensor sites and 15 radio relay sites maintained by the Hanford Seismic Assessment Team. The Hanford Seismic Network recorded 81 local earthquakes during the first quarter of FY 2010. Sixty-five of these earthquakes were detected in the vicinity of Wooded Island, located about eight miles north of Richland just west of the Columbia River. The Wooded Island events recorded this quarter is a continuation of the swarm events observed during fiscal year 2009 and reported in previous quarterly and annual reports (Rohay et al; 2009a, 2009b,more » 2009c, and 2009d). Most of the events were considered minor (coda-length magnitude [Mc] less than 1.0) with only 1 event in the 2.0-3.0 range; the maximum magnitude event (2.5 Mc) occurred on December 22 at depth 2.1 km. The average depth of the Wooded Island events during the quarter was 1.4 km with a maximum depth estimated at 3.1 km. This placed the Wooded Island events within the Columbia River Basalt Group (CRBG). The low magnitude of the Wooded Island events has made them undetectable to all but local area residents. The Hanford SMA network was triggered several times by these events and the SMA recordings are discussed in section 6.0. During the last year some Hanford employees working within a few miles of the swarm area and individuals living directly across the Columbia River from the swarm center have reported feeling many of the larger magnitude events. Strong motion accelerometer (SMA) units installed directly above the swarm area at ground surface measured peak ground accelerations approaching 15% g, the largest values recorded at Hanford. This corresponds to strong shaking of the ground, consistent with what people in the local area have reported. However, the duration and magnitude of these swarm events should not result in any structural damage to facilities. The USGS performed a geophysical survey using satellite interferometry that detected approximately 1 inch uplift in surface deformation along an east-west transect within the swarm area. The uplift is thought to be caused by the release of pressure that has built up in sedimentary layers, cracking the brittle basalt layers with the Columbia River Basalt Formation (CRBG) and causing the earthquakes. Similar earthquake swarms have been recorded near this same location in 1970, 1975 and 1988 but not with SMA readings or satellite imagery. Prior to the 1970s, swarming may have occurred, but equipment was not in place to record those events. The Wooded Island swarm, due its location and the limited magnitude of the events, does not appear to pose any significant risk to Hanford waste storage facilities. Since swarms of the past did not intensify in magnitude, seismologists do not expect that these events will persist or increase in intensity. However, Pacific Northwest National Laboratory (PNNL) will continue to monitor the activity. Outside of the Wooded Island swarm, sixteen earthquakes were recorded, all minor events. Seven earthquakes were located at intermediate depths (between 4 and 9 km), most likely in the pre-basalt sediments and nine earthquakes at depths greater than 9 km, within the basement. Geographically, seven earthquakes were located in known swarm areas and nine earthquakes were classified as random events.« less

Imaging the West Bohemia Seismic Zone

NASA Astrophysics Data System (ADS)

Alexandrakis, C.; Calo, M.; Bouchaala, F.; Vavrycuk, V.

2013-12-01

West Bohemia is located at the suture of three mantle lithosphere plates, the Eger Rift, the Cheb basin and is the site of Quaternary volcanism. This complex tectonic setting results in localized, periodic earthquake swarms throughout the region and many CO2 springs and gas exhalation sites. Nový Kostel, the most active swarm area, experiences frequent swarms of several hundreds to thousands of earthquakes over a period of weeks to several months. It is a unique study area, since the swarm region is surrounded by the West Bohemia Seismic Network (WEBNET), providing observations in all directions. Larger swarms, such as those in 1985/1986, 1997, 2000, 2007 and 2008, have been studied in terms of source mechanisms and swarm characteristics (Fischer and Michálek, 2003; Fischer et al., 2010; Vavryčuk, 2011). The seismicity is always located in the same area and depth range (6-15 km), however the active fault planes differ. This indicates changes to the local stress field, and may relate to the complicated tectonic situation and/or migrating fluids. Many studies have examined individual swarms and compared the earthquake episodes, however the mechanisms behind the phenomenon are still not understood. This has motivated many studies, including recent proposals for a reflection seismic profile directly over the swarm area and multidisciplinary monitoring through ICDP. In this study, we image the velocity structure within and around the swarm area using double-difference tomography (Zhang and Thurber, 2003) and Weighted Average Model (WAM) post-processing analysis (Calò et al., 2011). The WAM analysis averages together velocity models calculated with a variety of reasonable starting parameters. The velocities are weighted by the raypath proximity and density at an inversion node. This reduces starting model bias and artifacts, and yields a weighted standard deviation at each grid point. Earthquake locations and WEBNET P and S arrival times for the two most recent large swarms, 2008 and 2011, are used in this study. P-wave, S-wave and P-to-S ratio WAMs (P-to-S ratios are calculated directly from the P and S WAMs) reveal interesting features which correlate with the shallowest earthquakes. These features are interpreted in relation to the role of fluids in Nový Kostel. References: Calò, M., C. Dorbath, F. Cornet, & N. Cuenot, 2011. Geophys. J. Int., doi: 10.1111/j.1365-246X.2011.05108.x. Fischer, T., J. Horálek, J. Michálek & A. Boušková, 2010. J. Seismol., 14: 665-682. Fischer, T. & J. Michálek, 2008. Stud. Geophys. Geod., 52: 493-511. Vavryčuk, V., 2011. Earth Planet. Sci. Lett., 305: 290-296. Zhang, H. & C.H. Thurber, 2003. Bull. Seism. Soc. Am., 93: 1175-1189.

SODA Repuslive Function Shaping

NASA Image and Video Library

2017-06-16

SODA, Swarm Orbital Dynamics Advisor, a tool that provides the orbital maneuvers required to achieve a desired type of relative swarm motion. The SODA algorithm uses a repulsive potential that is a function of the distances between each pair of satellites. Choosing the parameters of the function is a swarm design choice, as different values can yield very different maneuvers and thus impact fuel use and mission life. This is an animation illustrating how the peaks of the repulsive potential function vary when varying certain parameters.

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

Autonomous Navigation, Dynamic Path and Work Flow Planning in Multi-Agent Robotic Swarms Project

NASA Technical Reports Server (NTRS)

Falker, John; Zeitlin, Nancy; Leucht, Kurt; Stolleis, Karl

2015-01-01

Kennedy Space Center has teamed up with the Biological Computation Lab at the University of New Mexico to create a swarm of small, low-cost, autonomous robots, called Swarmies, to be used as a ground-based research platform for in-situ resource utilization missions. The behavior of the robot swarm mimics the central-place foraging strategy of ants to find and collect resources in an unknown environment and return those resources to a central site.

Swarming Mechanisms in the Yellow Fever Mosquito: Aggregation Pheromones are Involved in the Mating Behavior of Aedes aegypti

DTIC Science & Technology

2014-12-01

behavior of Aedes aegypti Emadeldin Y. Fawaz1, Sandra A. Allan2, Ulrich R. Bernier2, Peter J. Obenauer3, and Joseph W. Diclaro II1 1Vector Biology... Aedes aegypti swarming behavior and identified associated chemical cues. Novel evidence is provided that Ae. aegypti females aggregate by means of...the isolated aggregation pheromones in controlling Ae. aegypti. Journal of Vector Ecology 39 (2): 347-354. 2014. Keyword Index: Aedes aegypti, swarm

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.

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.

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.

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 heterogeneity under HL act as an asperity in the epicentral area, whose origin may relate to magma intrusion into upper crust. However, seismic survey is required for detailing this geologic inference.

Gene selection using hybrid binary black hole algorithm and modified binary particle swarm optimization.

PubMed

Pashaei, Elnaz; Pashaei, Elham; Aydin, Nizamettin

2018-04-14

In cancer classification, gene selection is an important data preprocessing technique, but it is a difficult task due to the large search space. Accordingly, the objective of this study is to develop a hybrid meta-heuristic Binary Black Hole Algorithm (BBHA) and Binary Particle Swarm Optimization (BPSO) (4-2) model that emphasizes gene selection. In this model, the BBHA is embedded in the BPSO (4-2) algorithm to make the BPSO (4-2) more effective and to facilitate the exploration and exploitation of the BPSO (4-2) algorithm to further improve the performance. This model has been associated with Random Forest Recursive Feature Elimination (RF-RFE) pre-filtering technique. The classifiers which are evaluated in the proposed framework are Sparse Partial Least Squares Discriminant Analysis (SPLSDA); k-nearest neighbor and Naive Bayes. The performance of the proposed method was evaluated on two benchmark and three clinical microarrays. The experimental results and statistical analysis confirm the better performance of the BPSO (4-2)-BBHA compared with the BBHA, the BPSO (4-2) and several state-of-the-art methods in terms of avoiding local minima, convergence rate, accuracy and number of selected genes. The results also show that the BPSO (4-2)-BBHA model can successfully identify known biologically and statistically significant genes from the clinical datasets. Copyright © 2018 Elsevier Inc. All rights reserved.

New numerical methods for open-loop and feedback solutions to dynamic optimization problems

NASA Astrophysics Data System (ADS)

Ghosh, Pradipto

The topic of the first part of this research is trajectory optimization of dynamical systems via computational swarm intelligence. Particle swarm optimization is a nature-inspired heuristic search method that relies on a group of potential solutions to explore the fitness landscape. Conceptually, each particle in the swarm uses its own memory as well as the knowledge accumulated by the entire swarm to iteratively converge on an optimal or near-optimal solution. It is relatively straightforward to implement and unlike gradient-based solvers, does not require an initial guess or continuity in the problem definition. Although particle swarm optimization has been successfully employed in solving static optimization problems, its application in dynamic optimization, as posed in optimal control theory, is still relatively new. In the first half of this thesis particle swarm optimization is used to generate near-optimal solutions to several nontrivial trajectory optimization problems including thrust programming for minimum fuel, multi-burn spacecraft orbit transfer, and computing minimum-time rest-to-rest trajectories for a robotic manipulator. A distinct feature of the particle swarm optimization implementation in this work is the runtime selection of the optimal solution structure. Optimal trajectories are generated by solving instances of constrained nonlinear mixed-integer programming problems with the swarming technique. For each solved optimal programming problem, the particle swarm optimization result is compared with a nearly exact solution found via a direct method using nonlinear programming. Numerical experiments indicate that swarm search can locate solutions to very great accuracy. The second half of this research develops a new extremal-field approach for synthesizing nearly optimal feedback controllers for optimal control and two-player pursuit-evasion games described by general nonlinear differential equations. A notable revelation from this development is that the resulting control law has an algebraic closed-form structure. The proposed method uses an optimal spatial statistical predictor called universal kriging to construct the surrogate model of a feedback controller, which is capable of quickly predicting an optimal control estimate based on current state (and time) information. With universal kriging, an approximation to the optimal feedback map is computed by conceptualizing a set of state-control samples from pre-computed extremals to be a particular realization of a jointly Gaussian spatial process. Feedback policies are computed for a variety of example dynamic optimization problems in order to evaluate the effectiveness of this methodology. This feedback synthesis approach is found to combine good numerical accuracy with low computational overhead, making it a suitable candidate for real-time applications. Particle swarm and universal kriging are combined for a capstone example, a near optimal, near-admissible, full-state feedback control law is computed and tested for the heat-load-limited atmospheric-turn guidance of an aeroassisted transfer vehicle. The performance of this explicit guidance scheme is found to be very promising; initial errors in atmospheric entry due to simulated thruster misfirings are found to be accurately corrected while closely respecting the algebraic state-inequality constraint.

SwarmSight: Measuring the Temporal Progression of Animal Group Activity Levels from Natural Scene and Laboratory Videos

PubMed Central

Birgiolas, Justas; Jernigan, Christopher M.; Smith, Brian H.; Crook, Sharon M.

2016-01-01

We describe SwarmSight (available at: https://github.com/justasb/SwarmSight), a novel, open-source, Microsoft Windows software tool for quantitative assessment of the temporal progression of animal group activity levels from recorded videos. The tool utilizes a background subtraction machine vision algorithm and provides an activity metric that can be used to quantitatively assess and compare animal group behavior. Here we demonstrate the tool utility by analyzing defensive bee behavior as modulated by alarm pheromones, wild bird feeding onset and interruption, and cockroach nest finding activity. While more sophisticated, commercial software packages are available, SwarmSight provides a low-cost, open-source, and easy-to-use alternative that is suitable for a wide range of users, including minimally trained research technicians and behavioral science undergraduate students in classroom laboratory settings. PMID:27130170

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.

Cooperative Search and Rescue with Artificial Fishes Based on Fish-Swarm Algorithm for Underwater Wireless Sensor Networks

PubMed Central

Zhao, Wei; Tang, Zhenmin; Yang, Yuwang; Wang, Lei; Lan, Shaohua

2014-01-01

This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes' moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited range. A fish-swarm based algorithm is designed requiring local information at each fish node and maximizing the joint detection probabilities of distress signals. Optimization of formation is also considered for the searching control approach and is optimized by fish-swarm algorithm. Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties. PMID:24741341

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.

Cooperative search and rescue with artificial fishes based on fish-swarm algorithm for underwater wireless sensor networks.

PubMed

Zhao, Wei; Tang, Zhenmin; Yang, Yuwang; Wang, Lei; Lan, Shaohua

2014-01-01

This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes' moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited range. A fish-swarm based algorithm is designed requiring local information at each fish node and maximizing the joint detection probabilities of distress signals. Optimization of formation is also considered for the searching control approach and is optimized by fish-swarm algorithm. Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties.

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.

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.

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.

Volcano-Tectonic Activity at Deception Island Volcano Following a Seismic Swarm in the Bransfield Rift (2014-2015)

NASA Astrophysics Data System (ADS)

Almendros, J.; Carmona, E.; Jiménez, V.; Díaz-Moreno, A.; Lorenzo, F.

2018-05-01

In September 2014 there was a sharp increase in the seismic activity of the Bransfield Strait, Antarctica. More than 9,000 earthquakes with magnitudes up to 4.6 located SE of Livingston Island were detected over a period of 8 months. A few months after the series onset, local seismicity at the nearby (˜35 km) Deception Island volcano increased, displaying enhanced long-period seismicity and several outbursts of volcano-tectonic (VT) earthquakes. Before February 2015, VT earthquakes occurred mainly at 5-20 km SW of Deception Island. In mid-February the numbers and sizes of VT earthquakes escalated, and their locations encompassed the whole volcanic edifice, suggesting a situation of generalized unrest. The activity continued in anomalously high levels at least until May 2015. Given the spatial and temporal coincidence, it is unlikely that the Livingston series and the Deception VT swarm were unrelated. We propose that the Livingston series may have produced a triggering effect on Deception Island volcano. Dynamic stresses associated to the seismic swarm may have induced overpressure in the unstable volcanic system, leading to a magmatic intrusion that may in turn have triggered the VT swarm. Alternatively, both the Livingston earthquakes and the VT swarm could be consequences of a magmatic intrusion at Deception Island. The Livingston series would be an example of precursory distal VT swarm, which seems to be a common feature preceding volcanic eruptions and magma intrusions in long-dormant volcanoes.

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.

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.

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.

Arginine promotes Proteus mirabilis motility and fitness by contributing to conservation of the proton gradient and proton motive force.

PubMed

Armbruster, Chelsie E; Hodges, Steven A; Smith, Sara N; Alteri, Christopher J; Mobley, Harry L T

2014-10-01

Swarming contributes to Proteus mirabilis pathogenicity by facilitating access to the catheterized urinary tract. We previously demonstrated that 0.1-20 mmol/L arginine promotes swarming on normally nonpermissive media and that putrescine biosynthesis is required for arginine-induced swarming. We also previously determined that arginine-induced swarming is pH dependent, indicating that the external proton concentration is critical for arginine-dependent effects on swarming. In this study, we utilized survival at pH 5 and motility as surrogates for measuring changes in the proton gradient (ΔpH) and proton motive force (μH(+) ) in response to arginine. We determined that arginine primarily contributes to ΔpH (and therefore μH(+) ) through the action of arginine decarboxylase (speA), independent of the role of this enzyme in putrescine biosynthesis. In addition to being required for motility, speA also contributed to fitness during infection. In conclusion, consumption of intracellular protons via arginine decarboxylase is one mechanism used by P. mirabilis to conserve ΔpH and μH(+) for motility. © 2014 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

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

Low frequency events on Montserrat

NASA Astrophysics Data System (ADS)

Visser, K.; Neuberg, J.

2003-04-01

Earthquake swarms observed on volcanoes consist generally of low frequency events. The low frequency content of these events indicates the presence of interface waves at the boundary of the magma filled conduit and the surrounding country rock. The observed seismic signal at the surface shows therefore a complicated interference pattern of waves originating at various parts of the magma filled conduit, interacting with the free surface and interfaces in the volcanic edifice. This research investigates the applicability of conventional seismic tools on these low frequency events, focusing on hypocenter location analysis using arrival times and particle motion analysis for the Soufrière Hills Volcano on Montserrat. Both single low frequency events and swarms are observed on this volcano. Synthetic low frequency events are used for comparison. Results show that reliable hypocenter locations and particle motions can only be obtained if the low frequency events are single events with an identifiable P wave onset, for example the single events preceding swarms on Montserrat or the first low frequency event of a swarm. Consecutive events of the same swarm are dominated by interface waves which are converted at the top of the conduit into weak secondary P waves and surface waves. Conventional seismic tools fail to correctly analyse these events.

Hysteresis compensation of the Prandtl-Ishlinskii model for piezoelectric actuators using modified particle swarm optimization with chaotic map.

PubMed

Long, Zhili; Wang, Rui; Fang, Jiwen; Dai, Xufei; Li, Zuohua

2017-07-01

Piezoelectric actuators invariably exhibit hysteresis nonlinearities that tend to become significant under the open-loop condition and could cause oscillations and errors in nanometer-positioning tasks. Chaotic map modified particle swarm optimization (MPSO) is proposed and implemented to identify the Prandtl-Ishlinskii model for piezoelectric actuators. Hysteresis compensation is attained through application of an inverse Prandtl-Ishlinskii model, in which the parameters are formulated based on the original model with chaotic map MPSO. To strengthen the diversity and improve the searching ergodicity of the swarm, an initial method of adaptive inertia weight based on a chaotic map is proposed. To compare and prove that the swarm's convergence occurs before stochastic initialization and to attain an optimal particle swarm optimization algorithm, the parameters of a proportional-integral-derivative controller are searched using self-tuning, and the simulated results are used to verify the search effectiveness of chaotic map MPSO. The results show that chaotic map MPSO is superior to its competitors for identifying the Prandtl-Ishlinskii model and that the inverse Prandtl-Ishlinskii model can provide hysteresis compensation under different conditions in a simple and effective manner.

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

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.

Antagonistic activities of some probiotic lactobacilli culture supernatant on Serratia marcescens swarming motility and antibiotic resistance.

PubMed

Vahedi-Shahandashti, Roya; Kasra-Kermanshahi, Rouha; Shokouhfard, Maliheh; Ghadam, Parinaz; Feizabadi, Mohammad Mehdi; Teimourian, Shahram

2017-12-01

Serratia marcescens , a potentially pathogenic bacterium, benefits from its swarming motility and resistance to antibiotic as two important virulence factors. Inappropriate use of antibiotics often results in drug resistance phenomenon in bacterial population. Use of probiotic bacteria has been recommended as partial replacement. In this study, we investigated the effects of some lactobacilli culture supernatant on swarming, motility and antibiotic resistance of S. marcescens . Antimicrobial activity of lactobacilli supernatant and susceptibility testing carried out on S. marcescens isolates. Pretreatment effect of lactobacilli culture supernatant on antibiotic - resistance pattern in S. marcescens was determined by comparison of the MIC of bacteria before and after the treatment. Our results showed that pretreatment with L. acidophilus ATCC 4356 supernatant can affect the resistance of Serratia strains against ceftriaxone, but it had no effect on the resistance to other antibiotics. Furthermore, culture supernatant of lactobacilli with concentrations greater than 2%, had an effect on the swarming ability of S. marcescens ATCC 13880 and inhibited it. Probiotic bacteria and their metabolites have the ability to inhibit virulence factors such as antibiotic resistance and swarming motility and can be used as alternatives to antibiotics.

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.

NanoSat Constellation Mission Design

NASA Technical Reports Server (NTRS)

Concha, Marco; DeFazio, Robert

1998-01-01

The NanoSat constellation concept mission proposes simultaneous operation of multiple swarms of as many as 22 identical 10 kg spacecraft per swarm. The various orbits in a NanoSat swarm vary from 3x12 to 3x42 R(sub e) in geometry. In this report the unique flight dynamics issues of this constellation satellite mission design are addressed. Studies include orbit design, orbit determination, and error analysis. A preliminary survey determined the orbital parameters that would limit the maximum shadow condition while providing adequate ground station access for three ground stations.

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.

3D Tracking of Mating Events in Wild Swarms of the Malaria Mosquito Anopheles gambiae

PubMed Central

Butail, Sachit; Manoukis, Nicholas; Diallo, Moussa; Yaro, Alpha S.; Dao, Adama; Traoré, Sekou F.; Ribeiro, José M.; Lehmann, Tovi; Paley, Derek A.

2013-01-01

We describe an automated tracking system that allows us to reconstruct the 3D kinematics of individual mosquitoes in swarms of Anopheles gambiae. The inputs to the tracking system are video streams recorded from a stereo camera system. The tracker uses a two-pass procedure to automatically localize and track mosquitoes within the swarm. A human-in-the-loop step verifies the estimates and connects broken tracks. The tracker performance is illustrated using footage of mating events filmed in Mali in August 2010. PMID:22254411

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.

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 causes an annual peak-to-peak vertical displacement of about 1 cm at GPS sites in the Cascades and GPS signals that decay with increasing distance from the Cascades. Stress changes due to loading and unloading of snow pack in the Cascades can act in two ways to instantaneously enhance seismicity. For a strike-slip fault roughly parallel to the trend of the load and 10s of km away from it, normal stress decreases slightly leading to slight fault unclamping. The load also leads to simultaneous compression of fluid conduits at greater depth driving fluids rapidly upward into the swarm source region. The small, temporally variable stress changes on the order of a few kPa or less seem to be adequate to modulate seismicity by varying fault normal stresses and controlling fluid injection into a critically stressed fault zone. The swarm region has been quiet since February 2012 suggesting stresses on the fault have been nearly completely released.

Frog Swarms: Earthquake Precursors or False Alarms?

PubMed Central

Grant, Rachel A.; Conlan, Hilary

2013-01-01

Simple Summary Media reports linking unusual animal behaviour with earthquakes can potentially create false alarms and unnecessary anxiety among people that live in earthquake risk zones. Recently large frog swarms in China and elsewhere have been reported as earthquake precursors in the media. By examining international media reports of frog swarms since 1850 in comparison to earthquake data, it was concluded that frog swarms are naturally occurring dispersal behaviour of juveniles and are not associated with earthquakes. However, the media in seismic risk areas may be more likely to report frog swarms, and more likely to disseminate reports on frog swarms after earthquakes have occurred, leading to an apparent link between frog swarms and earthquakes. Abstract In short-term earthquake risk forecasting, the avoidance of false alarms is of utmost importance to preclude the possibility of unnecessary panic among populations in seismic hazard areas. Unusual animal behaviour prior to earthquakes has been reported for millennia but has rarely been scientifically documented. Recently large migrations or unusual behaviour of amphibians have been linked to large earthquakes, and media reports of large frog and toad migrations in areas of high seismic risk such as Greece and China have led to fears of a subsequent large earthquake. However, at certain times of year large migrations are part of the normal behavioural repertoire of amphibians. News reports of “frog swarms” from 1850 to the present day were examined for evidence that this behaviour is a precursor to large earthquakes. It was found that only two of 28 reported frog swarms preceded large earthquakes (Sichuan province, China in 2008 and 2010). All of the reported mass migrations of amphibians occurred in late spring, summer and autumn and appeared to relate to small juvenile anurans (frogs and toads). It was concluded that most reported “frog swarms” are actually normal behaviour, probably caused by 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

Seismogenic structures activated during the pre-eruptive and intrusive swarms of Piton de la Fournaise volcano (La Réunion island) between 2008 and 2011

NASA Astrophysics Data System (ADS)

Battaglia, J.; Brenguier, F.

2011-12-01

Piton de la Fournaise is a frequently active basaltic volcano with more than 30 fissure eruptions since 1998. These eruptions are always preceded by pre-eruptive swarms of volcano-tectonic earthquakes which accompany dike propagation. Occasionally, intrusion swarms occur without leading to any eruption. From October 2008 to May 2011, as part of the research project Undervolc, a temporary network of 15 broadband stations has been installed on the volcano to complement the local monitoring network. We examined in detail the 6 intrusive and 5 pre-eruptive swarms which occurred during the temporary experiment. All the crises lasted for a few hours and only included shallow events clustered below the summit craters, around and above sea level, showing no signs of deeper magma transfers. These characteristics are common to most swarms observed at Piton de la Fournaise arising questions about the origin of the seismicity which seems to be poorly linked with dike propagation. With the aim to identify the main seismogenic structures active during the swarms, we applied precise earthquake detection and classification techniques based on waveform cross-correlation. For each swarm, the onsets of all transients, including small amplitude ones, have been precisely detected at a single station by scanning the continuous data with reference waveforms. The classification of the detected transients indicates the presence of several families of similar earthquakes. The two main families (F01 and F02) include several hundred events. They are systematically activated at the beginning of each pre-eruptive swarm but are inactive during the intrusive ones. They group more than 50 percent of the detected events for the corresponding crises. The other clusters are mostly associated with single swarms. To determine the spatial characteristics of the structures corresponding to the main families, we applied precise relocation techniques. Based on the one-station classification, the events have first been picked at all available stations by cross-correlating waveforms with those of master events whose arrival times have been manually determined. All events have been located using a 3D velocity model to determine accurate hypocentral azimuths and take-off angles. Precise relative locations have been computed for each multiplet using cross-correlation delays calculated for all available stations between all pairs of events. The results indicate the presence at sea level of a major structure grouping families F01 and F02 and describing an East-West elongated pattern with sub-vertical extension. Small scale earthquake migrations, mostly horizontal, occur during the pre-eruptive swarms along that structure. The smaller multiplets define vertically elongated patterns extending around and above the main F01-F02 multiplet. Our results show that different processes are involved in pre-eruptive and intrusive crises and that a structure located around 2.5 km below the summit controls the occurrence of recent eruptions of Piton de la Fournaise volcano.

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 mission for the Flight Control Team at ESOC.

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.

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 trajectory and guidance design for the Mars Science Laboratory mission but may be applied to any optimization problem.

In-situ seismic record of potential sill intrusion at the ultraslow spreading Southwest Indian Ridge

NASA Astrophysics Data System (ADS)

Meier, M.; Schlindwein, V. S. N.

2017-12-01

Ultraslow spreading mid-ocean ridges with full spreading rates up to 15 mm/yr are described as the melt poor endmember of the entire mid-ocean ridge system. The melt supply along ultraslow spreading ridges is uneven resulting in the formation of volcanic centres and amagmatic segments. Amagmatic segments show thicker brittle lithosphere of up to 30 km, whereas magmatic segments have much thinner lithosphere of up to less than 15 km. It is supposed that melt travels along the lithosphere asthenosphere boundary from amagmatic segments to magmatic segments, where it can reach the seafloor and erupt. These spreading events are rare at ultraslow spreading ridges compared to faster spreading ridges and insitu observations hardly exist. During an ocean bottom seismometer (OBS) experiment at the eastern Southwest Indian Ridge two earthquake swarms were accidentally recorded. The swarms occurred in January and April 2013 and both lasted for a few days. The events of the earthquake swarms were relatively located with HypoDD for better spatial resolution. This unique dataset allowed for studying active spreading processes at an ultraslow spreading ridge. The earthquakes occurred in depths, where the magma chamber of the nearby Segment-8 volcano is located. This magma chamber potentially fed a sill intrusion, which was recorded as earthquake swarms. During the first hours of the first earthquake swarm a migration pattern was identified. The hypocentres migrated away from the Segment-8 volcanic centre and slightly downwards. Later events occurred more randomly in the active area. Simultaneously seismic tremor was recorded at the station closest to the swarm locations. The tremor lasted longer for the shorter earthquake swarm in April. During both tremor phases the signal was modulated with a 12 hour period. We speculate that a hydrothermal system was affected by the intrusion and fluid flow modulated by the tides produced the tremor signal.

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

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.

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

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

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.

Dynamics of neutrophil migration in lymph nodes during infection.

PubMed

Chtanova, Tatyana; Schaeffer, Marie; Han, Seong-Ji; van Dooren, Giel G; Nollmann, Marcelo; Herzmark, Paul; Chan, Shiao Wei; Satija, Harshita; Camfield, Kristin; Aaron, Holly; Striepen, Boris; Robey, Ellen A

2008-09-19

Although the signals that control neutrophil migration from the blood to sites of infection have been well characterized, little is known about their migration patterns within lymph nodes or the strategies that neutrophils use to find their local sites of action. To address these questions, we used two-photon scanning-laser microscopy to examine neutrophil migration in intact lymph nodes during infection with an intracellular parasite, Toxoplasma gondii. We found that neutrophils formed both small, transient and large, persistent swarms via a coordinated migration pattern. We provided evidence that cooperative action of neutrophils and parasite egress from host cells could trigger swarm formation. Neutrophil swarm formation coincided in space and time with the removal of macrophages that line the subcapsular sinus of the lymph node. Our data provide insights into the cellular mechanisms underlying neutrophil swarming and suggest new roles for neutrophils in shaping immune responses.

Dynamics of neutrophil migration in lymph nodes during infection

PubMed Central

Chtanova, Tatyana; Schaeffer, Marie; Han, Seong-Ji; van Dooren, Giel G.; Nollmann, Marcelo; Herzmark, Paul; Chan, Shiao Wei; Satija, Harshita; Camfield, Kristin; Aaron, Holly; Striepen, Boris; Robey, Ellen A.

2008-01-01

Summary While the signals that control neutrophil migration from the blood to sites of infection have been well characterized, little is known about their migration patterns within lymph nodes, or the strategies that neutrophils use to find their local sites of action. To address these questions, we used two-photon scanning laser microscopy (TPSLM) to examine neutrophil migration in intact lymph nodes during infection with an intracellular parasite, Toxoplasma gondii. We find that neutrophils form both small, transient or large, persistent swarms via a strikingly coordinated migration pattern. We provide evidence that cooperative action of neutrophils and parasite egress from host cells can trigger swarm formation. Neutrophil swarm formation coincides in space and time with the removal of macrophages that line the subcapsular sinus of the lymph node. Our data provide insights into the cellular mechanisms underlying neutrophil swarming and suggest new roles for neutrophils in shaping immune responses. PMID:18718768

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.

Winter swarming behavior by the exotic cladoceran Daphnia lumholtzi Sars, 1885 in a Kentucky (USA) reservoir

USGS Publications Warehouse

Beaver, John R.; Renicker, Thomas R.; Tausz, Claudia E.; Young, Jade L.; Thomason, Jennifer C.; Wolf, Zachary L.; Russell, Amber L.; Cherry, Mac A.; Scotese, Kyle C.; Koenig, Dawn T.

2018-01-01

We describe swarming behavior in the invasive cladoceran Daphnia lumholtzi Sars, 1885 in a Kentucky, USA, reservoir during winter 2017. The taxon is a highly successful tropical invader and has spread throughout the lower latitude systems in the USA since its discovery in 1991. Other than a few isolated reports, the abundance of D. lumholtzi is often <1 organism L-1. Previous studies indicate that D. lumholtzi is a largely thermophilic species often peaking in abundance in late summer after native daphnids are gone from the water column of lakes and reservoirs. Prior to our study, there have been no published reports of swarming behavior by this species. We document the occurrence of massive swarms (>10,000 organisms L-1) of sexually reproducing females of this exotic cladoceran at water column temperatures <10°C.

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.

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

Slab tears and intermediate-depth seismicity

USGS Publications Warehouse

Meighan, Hallie E.; ten Brink, Uri S.; Pulliam, Jay

2013-01-01

Active tectonic regions where plate boundaries transition from subduction to strike slip can take several forms, such as triple junctions, acute, and obtuse corners. Well-documented slab tears that are associated with high rates of intermediate-depth seismicity are considered here: Gibraltar arc, the southern and northern ends of the Lesser Antilles arc, and the northern end of Tonga trench. Seismicity at each of these locations occurs, at times, in the form of swarms or clusters, and various authors have proposed that each marks an active locus of tear propagation. The swarms and clusters start at the top of the slab below the asthenospheric wedge and extend 30–60 km vertically downward within the slab. We propose that these swarms and clusters are generated by fluid-related embrittlement of mantle rocks. Focal mechanisms of these swarms generally fit the shear motion that is thought to be associated with the tearing process.

Particle Swarm Learning Algorithm Based on Adjustment of Parameter and its Applications Assessment of Agricultural Projects

NASA Astrophysics Data System (ADS)

Yang, Shanlin; Zhu, Weidong; Chen, Li

The particle swarm, which optimizes neural networks, has overcome its disadvantage of slow convergent speed and shortcoming of local optimum. The parameter that the particle swarm optimization relates to is not much. But it has strongly sensitivity to the parameter. In this paper, we applied PSO-BP to evaluate the environmental effect of an agricultural project, and researched application and Particle Swarm learning algorithm based on adjustment of parameter. This paper, we use MATLAB language .The particle number is 5, 30, 50, 90, and the inertia weight is 0.4, 0.6, and 0.8 separately. Calculate 10 times under each same parameter, and analyze the influence under the same parameter. Result is indicated that the number of particles is in 25 ~ 30 and the inertia weight is in 0.6 ~ 0.7, and the result of optimization is satisfied.

Exploring with PAM: Prospecting ANTS Missions for Solar System Surveys

NASA Technical Reports Server (NTRS)

Clark, P. E.; Rilee, M. L.; Curtis, S. A.

2003-01-01

ANTS (Autonomous Nano-Technology Swarm), a large (1000 member) swarm of nano to picoclass (10 to 1 kg) totally autonomous spacecraft, are being developed as a NASA advanced mission concept. ANTS, based on a hierarchical insect social order, use an evolvable, self-similar, hierarchical neural system in which individual spacecraft represent the highest level nodes. ANTS uses swarm intelligence attained through collective, cooperative interactions of the nodes at all levels of the system. At the highest levels this can take the form of cooperative, collective behavior among the individual spacecraft in a very large constellation. The ANTS neural architecture is designed for totally autonomous operation of complex systems including spacecraft constellations. The ANTS (Autonomous Nano Technology Swarm) concept has a number of possible applications. A version of ANTS designed for surveying and determining the resource potential of the asteroid belt, called PAM (Prospecting ANTS Mission), is examined here.

VDLLA: A virtual daddy-long legs optimization

NASA Astrophysics Data System (ADS)

Yaakub, Abdul Razak; Ghathwan, Khalil I.

2016-08-01

Swarm intelligence is a strong optimization algorithm based on a biological behavior of insects or animals. The success of any optimization algorithm is depending on the balance between exploration and exploitation. In this paper, we present a new swarm intelligence algorithm, which is based on daddy long legs spider (VDLLA) as a new optimization algorithm with virtual behavior. In VDLLA, each agent (spider) has nine positions which represent the legs of spider and each position represent one solution. The proposed VDLLA is tested on four standard functions using average fitness, Medium fitness and standard deviation. The results of proposed VDLLA have been compared against Particle Swarm Optimization (PSO), Differential Evolution (DE) and Bat Inspired Algorithm (BA). Additionally, the T-Test has been conducted to show the significant deference between our proposed and other algorithms. VDLLA showed very promising results on benchmark test functions for unconstrained optimization problems and also significantly improved the original swarm algorithms.

Precursory swarms of long-period events at Redoubt Volcano (1989-1990), Alaska: Their origin and use as a forecasting tool

USGS Publications Warehouse

Chouet, B.A.; Page, R.A.; Stephens, C.D.; Lahr, J.C.; Power, J.A.

1994-01-01

During the eruption of Redoubt Volcano from December 1989 through April 1990, the Alaska Volcano Observatory issued advance warnings of several tephra eruptions based on changes in seismic activity related to the occurrence of precursory swarms of long-period (LP) seismic events (dominant period of about 0.5 s). The initial eruption on December 14 occurred after 23 years of quiescence and was heralded by a 23-hour swarm of LP events that ended abruptly with the eruption. After a series of vent-clearing explosions over the next few days, dome growth began on December 21. Another swarm, with LP events similar to those of the first, began on the 26th and ended in a major tephra eruption on January 2. Eruptions continued over the next two weeks and then ceased until February 15, when a large eruption initiated a long phase of repetitive dome-building and dome-destroying episodes that continued into April. Warnings were issued before the major events on December 14 and January 2, but as the eruptive sequence continued after January 2, the energy of the swarms decreased and forecasting became more difficult. A significant but less intense swarm preceded the February 15 eruption, which was not forecast. This eruption destroyed the only seismograph on the volcanic edifice and stymied forecasting until March 4, when the first of three new stations was installed within 3 km of the active vent. From March 4 to the end of the sequence on April 21, there were eight eruptions, six of which were preceded by detectable swarms of LP events. Although weak, these swarms provided the basis for warnings issued before the eruptions on March 23 and April 6. The initial swarm on December 13 had the following features: (1) short duration (23 hours); (2) a rapidly accelerating rate of seismic energy release over the first 18 hours of the swarm, followed by a decline of activity during the 5 hours preceding the eruption; (3) a magnitude range from -0.4 to 1.6; (4) nearly identical LP signatures with a dominant period near 0.5 s; (5) dilatational first motions everywhere; and (6) a stationary source location at a depth of 1.4 km beneath the crater. This occurrence of long-period events suggests a model involving the interaction of magma with groundwater in which magmatic gases, steam and water drive a fixed conduit at a stationary point throughout the swarm. The initiation of that sequence of events is analogous to the failure of a pressure-relief valve connecting a lower, supercharged magma-dominated reservoir to a shallow hydrothermal system. A three-dimensional model of a vibrating fluid-filled crack recently developed by Chouet is found to be compatible with the seismic data and yields the following parameters for the LP source: crack length, 280-380 m; crack width, 140-190 m; crack thickness, 0.05-0.20 m; crack stiffness, 100-200; sound speed of fluid, 0.8-1.3 km/s; compressional-wave speed of rock, 5.1 km/s; density ratio of fluid to rock, ???0.4; and ratio of bulk modulus of fluid to rigidity of rock, 0.03-0.07. The fluid-filled crack is excited intermittently by an impulsive pressure drop that varies in magnitude within the range of 0.4 to 40 bar. Such disturbance appears to be consistent with a triggering mechanism associated with choked flow conditions in the crack. ?? 1994.

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 cutting edge in system correctness, and requires higher levels of assurance than other (traditional) missions that use a single or small number of spacecraft that are deterministic in nature and have near continuous communication access. One of the highest possible levels of assurance comes from the application of formal methods. Formal methods are mathematics-based tools and techniques for specifying and verifying (software and hardware) systems. They are particularly useful for specifying complex parallel systems, such as exemplified by the ANTS mission, where the entire system is difficult for a single person to fully understand, a problem that is multiplied with multiple developers. Once written, a formal specification can be used to prove properties of a system (e.g., the underlying system will go from one state to another or not into a specific state) and check for particular types of errors (e.g., race or livelock conditions). A formal specification can also be used as input to a model checker for further validation. This report gives the results of a survey of formal methods techniques for verification and validation of space missions that use swarm technology. Multiple formal methods were evaluated to determine their effectiveness in modeling and assuring the behavior of swarms of spacecraft using the ANTS mission as an example system. This report is the first result of the project to determine formal approaches that are promising for formally specifying swarm-based systems. From this survey, the most promising approaches were selected and are discussed relative to their possible application to the ANTS mission. Future work will include the application of an integrated approach, based on the selected approaches identified in this report, to the formal specification of the ANTS mission.

Characterization and compensation of thermo-elastic instability of SWARM optical bench on micro Advanced Stellar Compass attitude observations

NASA Astrophysics Data System (ADS)

Herceg, M.; Jørgensen, P. S.; Jørgensen, J. L.

2017-08-01

Launched into orbit on November 22, 2013, the Swarm constellation of three satellites precisely measures magnetic signal of the Earth. To ensure the high accuracy of magnetic observation by vector magnetometer (VFM), its inertial attitude is precisely determined by μASC (micro Advanced Stellar Compass). Each of the three Swarm satellites is equipped with three μASC Camera Head Units (CHU) mounted on a common optical bench (OB), which has a purpose of transference of the attitude from the star trackers to the magnetometer measurements. Although substantial pre-launch analyses were made to maximize thermal and mechanical stability of the OB, significant signal with thermal signature is discovered when comparing relative attitude between the three CHU's (Inter Boresight Angle, IBA). These misalignments between CHU's, and consequently geomagnetic reference frame, are found to be correlated with the period of angle between Swarm orbital plane and the Sun (ca. 267 days), which suggests sensitivity of optical bench system on temperature variation. In this paper, we investigate the propagation of thermal effects into the μASC attitude observations and demonstrate how thermally induced attitude variation can be predicted and corrected in the Swarm data processing. The results after applying thermal corrections show decrease in IBA RMS from 6.41 to 2.58″. The model significantly improves attitude determination which, after correction, meets the requirements of Swarm satellite mission. This study demonstrates the importance of the OB pre-launch analysis to ensure minimum thermal gradient on satellite optical system and therefore maximum attitude accuracy.

Trace Amounts of Furan-2-Carboxylic Acids Determine the Quality of Solid Agar Plates for Bacterial Culture

PubMed Central

Hara, Shintaro; Isoda, Reika; Tahvanainen, Teemu; Hashidoko, Yasuyuki

2012-01-01

Background Many investigators have recognised that a significant proportion of environmental bacteria exist in a viable but non-culturable state on agar plates, and some researchers have also noticed that some of such bacteria clearly recover their growth on matrices other than agar. However, the reason why agar is unsuitable for the growth of some bacteria has not been addressed. Methodology/Principal Findings According to the guide of a bioassay for swarming inhibition, we identified 5-hydroxymethylfuran-2-carboxylic acid (5-HMFA) and furan-2-carboxylic acid (FA) as factors that inhibit bacterial swarming and likely inhibit extracellular polysaccharide production on agar. The furan-2-carboxylic acids 5-HMFA and FA effectively inhibited the swarming and swimming of several environmental bacteria at concentrations of 1.8 and 2.3 µg L−1 (13 and 21 nmol L−1), respectively, which are equivalent to the concentrations of these compounds in 0.3% agar. On Luria-Bertani (LB) plates containing 1.0% agar that had been previously washed with MeOH, a mixture of 5-HMFA and FA in amounts equivalent to their original concentrations in the unwashed agar repressed the swarming of Escherichia coli K12 strain W3110, a representative swarming bacterium. Conclusions/Significance Agar that contains trace amounts of 5-HMFA and FA inhibits the proliferation of some slow-growing or difficult-to-culture bacteria on the plates, but it is useful for single colony isolation due to the ease of identification of swarmable bacteria as the non-swarmed colonies. PMID:22848437

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.

A detection algorithm for scale analysis of post-sunset low-latitude plasma depletions as observed by the Swarm constellation mission

NASA Astrophysics Data System (ADS)

Kervalishvili, Guram; Stolle, Claudia; Xiong, Chao

2016-04-01

ESA's 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. The satellites carry instruments to monitor the F-region electron density with a sampling frequency of 2 Hz. This paper will present a detection algorithm for low-latitude post-sunset plasma bubbles (depletions), which uses local minima and maxima to detect depletions directly from electron density readings from Swarm. Our analyses were performed in the magnetic latitude (MLat) and local time (MLT) coordinate system. The detection procedure also captures the amplitude of depletion, which is called depth in the following. The width of a bubble corresponds to the length the satellite is located inside a depletion. We discuss the global distribution of depth and width of plasma bubbles and its seasonal and local time dependence for all three Swarm satellites from April 2015 through September 2015. As expected, on global average the bubble occurrence rate is highest for combined equinoxes (Mar, Apr, Sep, and Oct) and smallest for June solstice (May, Jun, Jul, and Aug). MLT distribution of the bubble occurrence number shows a sharp increase at about 19 MLT and decreases towards post-midnight hours. Interestingly, there is an inverse relation between depth and width of bubbles as function of MLT. This is true for all seasons and for all Swarm satellites. The bubble depth (width) is decreasing (increasing) from post-sunset to post-midnight for December solstice (Jan, Feb, Nov, and Dec) and combined equinoxes with about the same amplitude values for bubbles depth (width). Therefore we suggest that at post midnight when the depletions are less steep the structures of the depletions is broader than early after sunset. However for June solstice the depletions are less deep and the bubble depth and width do not change significantly throughout the evening. Deepest depletions occur at around +/- 10° magnetic latitude that is at the inner edge of the ionisation anomaly with density maxima at around 15° MLat. Therefore, the level of background electron density does not only determine the depth of a post-sunset depletion.

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.

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.

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.

Possible relationship between the Farmington meteorite and a seismically detected swarm of meteoroids impacting the moon

NASA Technical Reports Server (NTRS)

Oberst, Jurgen

1989-01-01

The Farmington ordinary L5 chondrite with its uniquely short cosmic-ray exposure age of less than 25,000 years may have been a member of a large meteoroid swarm which was detected by the Apollo seismic network when it encountered the moon in June 1975. The association implies that the parent body of the Farmington meteorite was in an earth-crossing orbit at the time the swarm was formed. This supports the idea that at least some meteorites are derived from the observable population of earth-crossing asteroids.

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.

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.

SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware

PubMed Central

Birgiolas, Justas; Jernigan, Christopher M.; Gerkin, Richard C.; Smith, Brian H.; Crook, Sharon M.

2017-01-01

Many scientifically and agriculturally important insects use antennae to detect the presence of volatile chemical compounds and extend their proboscis during feeding. The ability to rapidly obtain high-resolution measurements of natural antenna and proboscis movements and assess how they change in response to chemical, developmental, and genetic manipulations can aid the understanding of insect behavior. By extending our previous work on assessing aggregate insect swarm or animal group movements from natural and laboratory videos using the video analysis software SwarmSight, we developed a novel, free, and open-source software module, SwarmSight Appendage Tracking (SwarmSight.org) for frame-by-frame tracking of insect antenna and proboscis positions from conventional web camera videos using conventional computers. The software processes frames about 120 times faster than humans, performs at better than human accuracy, and, using 30 frames per second (fps) videos, can capture antennal dynamics up to 15 Hz. The software was used to track the antennal response of honey bees to two odors and found significant mean antennal retractions away from the odor source about 1 s after odor presentation. We observed antenna position density heat map cluster formation and cluster and mean angle dependence on odor concentration. PMID:29364251

Honey Bees Inspired Optimization Method: The Bees Algorithm.

PubMed

Yuce, Baris; Packianather, Michael S; Mastrocinque, Ernesto; Pham, Duc Truong; Lambiase, Alfredo

2013-11-06

Optimization algorithms are search methods where the goal is to find an optimal solution to a problem, in order to satisfy one or more objective functions, possibly subject to a set of constraints. Studies of social animals and social insects have resulted in a number of computational models of swarm intelligence. Within these swarms their collective behavior is usually very complex. The collective behavior of a swarm of social organisms emerges from the behaviors of the individuals of that swarm. Researchers have developed computational optimization methods based on biology such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony. The aim of this paper is to describe an optimization algorithm called the Bees Algorithm, inspired from the natural foraging behavior of honey bees, to find the optimal solution. The algorithm performs both an exploitative neighborhood search combined with random explorative search. In this paper, after an explanation of the natural foraging behavior of honey bees, the basic Bees Algorithm and its improved versions are described and are implemented in order to optimize several benchmark functions, and the results are compared with those obtained with different optimization algorithms. The results show that the Bees Algorithm offering some advantage over other optimization methods according to the nature of the problem.

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.

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.

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

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

Comparisons of sets of electron-neutral scattering cross sections and calculated swarm parameters in Kr and Xe

NASA Astrophysics Data System (ADS)

Bordage, M. C.; Hagelaar, G. J. M.; Pitchford, L. C.; Biagi, S. F.; Puech, V.

2011-10-01

Xenon is used in a number of application areas ranging from light sources to x-ray detectors for imaging in medicine, border security and high-energy particle physics. There is a correspondingly large body of data available for electron scattering cross sections and swarm parameters in Xe, whereas data for Kr are more limited. In this communication we show intercomparisons of the cross section sets in Xe and Kr presently available on the LXCat site. Swarm parameters calculated using these cross sections sets are compared with experimental data, also available on the LXCat site. As was found for Ar, diffusion coefficients calculated using these cross section data in a 2-term Boltzmann solver are higher than Monte Carlo results by about 30% over a range of E/N from 1 to 100 Td. We find otherwise good agreement in Xe between 2-term and Monte Carlo results and between measured and calculated values of electron mobility, ionization rates and light emission (dimer) at atmospheric pressure. The available cross section data in Kr yield swarm parameters in agreement with the limited experimental data. The cross section compilations and measured swarm parameters used in this work are available on-line at www.lxcat.laplace. univ-tlse.fr.

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.

Deformation during the 1975-84 Krafla rifting crisis, NE Iceland, measured by optical image correlation

NASA Astrophysics Data System (ADS)

Hollingsworth, J.; Leprince, S.; Avouac, J.; Ayoub, F.

2011-12-01

In this study we combine results from optical image correlation of SPOT, KH-9 spy satellite and aerial photos, EDM data and high resolution topographic data to better constrain the 3D deformation associated with the 1975-84 Krafla rifting crisis, NE Iceland. Inversion of the various geodetic datasets yields new volumes for the amount of material injected into the crust during this rifting crisis. Correlation of aerial photos from 1957 and 1990 for the middle section of the 2 km-wide Krafla fissure swarm, along with DEM differencing of their respective 1957 and 1990 DEM's (extracted using photogrammetric techniques), provides constraints on the full 3D displacement field spanning the entire rifting period. Elastic dislocation modeling of this displacement data is then used to determine the geometry of faulting and diking in the crust. In contrast to leveling data from the northern end of the fissure swarm (Rubin, et al., 1988), we find that dikes do not extend into the upper 1-2 km, where extension is accommodated primarily by faulting in the fissure swarm. Dislocation modeling of a 4 m-wide dike injected between 2 km and 6 km in the crust produces a maximum surface strain which reaches the elastic yield limit for rock (derived from laboratory experiments of deformed granite) at two points spanning a 2 km-wide zone above the dike, and which corresponds with the location of the major rift-bounding faults of the Krafla fissure swarm. If dikes extend nearer to the surface, the predicted fissure zone width would be correspondingly smaller (consistent with the southern-end of the fissure swarm), while deeper diking produces a wider fissure swarm (consistent with the northern-end of the fissure swarm). The apparent northward increase in depth of diking is consistent with the flexural effects of rift-margin topography (Behn, et al., 2006); increased flexure in the south, where the Krafla caldera is located, results in the promotion of shallow diking, where as subdued topography in the north promotes deeper diking. Correlation of aerial photos between 1957 and 1976 (during the early stages of the rifting crisis) indicate 2 m extension, which is localized on faults along the northern end of the fissure swarm. No fault slip occurs in the central section of the fissure swarm during the same period, suggesting extension in the north during the early stages of rifting may result from dike injections sourced from the north (possibly offshore), rather than the Krafla caldera to the south. A similar variation in magmatic source region was also observed during the 2005-2009 Afar rifting crisis in East Africa.

Seismicity patterns of earthquake swarms in the West-Bohemia/Vogtland as a hint to their triggering mechanisms

NASA Astrophysics Data System (ADS)

Fischer, T.; Hainzl, S.; Horalek, J.; Michalek, J.

2009-04-01

The distribution of West-Bohemia/Vogtland seismicity is clustered both in time and space. The time occurrence is manifested in a variety of forms including both swarms with fast and with slow energy release that last from hours to months and also solitary events. The lateral distribution of seismicity is limited to a small number of focal zones, which have been periodically reactivated during the past 18 years of instrumental observations. We don't observe an apparent migration of seismic activity. Instead, the activity has been switching between the focal zones with its largest part residing in the area of Nový Kostel, which dominates with 85% of energy release. Analysis of the activity in the period 1991-2007 has revealed that the interevent times of the seismic activity measured between events in separated focal zones show increased occurrence for time intervals below 8 hours. This fast switching of activity among focal zones with mutual distances above 10 km shows that the seismicity is correlated in a broader area and points to a common triggering force acting in the whole region of West-Bohemia/Vogtland. This force could be stress changes due to earth tides, barometric pressure disturbances, or an abrupt change of the crustal fluid pore pressure. It would trigger the activity in the focal zones which are close to failure. Depending on the local stress and mechanical conditions in each zone, the activity could either cease or an earthquake swarm could be initiated. To disclose the forces governing the already running swarm activity we investigated the space-time relations between consecutive earthquakes of the 2000 swarm. The swarm lasted four months and consisted of more that 8000 M=3.3 strike-slip microearthquakes, which were located along a fault plane at depths 6.5-10.5 km and showed a common rake angle of 30°. We found that the relative positions of consecutive event pairs showed maximum occurrence in the slip-parallel directions. Comparison with the complete Coulomb stress change upon the fault plane due to a typical rupture showed that the observed elongation of the space-time distribution of the relative positions can be explained by a common effect of both static and dynamic stress changes, which act on different distance and timescale. The relatively small magnitudes of the Coulomb stress changes upon the fault plane in the order of 10 kPa, which are supposed to trigger the swarm events, support the idea that high pressurized crustal fluids increase the pore pressure and bring the fault close to its critical state. This is in accordance with the results of our model of the 2000 swarm which took into account both the fluid diffusion and stress triggering. The model consisted of a planar brittle patch placed in a 3-D elastic half-space divided into the number of cells with variable strength. The individual cells rupture when the Coulomb failure criterion including both shear stress and pore pressure is fulfilled. The initial tectonic loading of the patch is presumed subcritical until the pore pressure of diffused fluids brings it into a critical state. Then the earthquake activity is governed by the stress changes due to the co-seismic and post-seismic slip, so that mutual triggering between ruptured cells occurs. It turns out that once the pressurized crustal fluids bring a fault from a subcritical steady-state into a critical state, the self-organization prevails in governing the swarm activity. This is in accordance with the possible effect of a regionally scaled force bringing one or multiple focal zones to the critical state and trigger seismicity. The recent M=3.7 swarm from October 2008 occurred at the identical fault plane as the 2000 swarm and showed a similar areal extent of the ruptured area. The overall migration of activity with first events at the bottom of the activated fault patch and the last events in the northward tail at its top indicates similar triggering scenario. However, the step-wise monotonous event migration in the first swarm period differs significantly from the complex migration patterns of the 2000 swarm, A further analysis is needed to learn if such a pattern could be due to a fluid or magma propagation along the fault plane.

Simultaneous-Fault Diagnosis of Gearboxes Using Probabilistic Committee Machine

PubMed Central

Zhong, Jian-Hua; Wong, Pak Kin; Yang, Zhi-Xin

2016-01-01

This study combines signal de-noising, feature extraction, two pairwise-coupled relevance vector machines (PCRVMs) and particle swarm optimization (PSO) for parameter optimization to form an intelligent diagnostic framework for gearbox fault detection. Firstly, the noises of sensor signals are de-noised by using the wavelet threshold method to lower the noise level. Then, the Hilbert-Huang transform (HHT) and energy pattern calculation are applied to extract the fault features from de-noised signals. After that, an eleven-dimension vector, which consists of the energies of nine intrinsic mode functions (IMFs), maximum value of HHT marginal spectrum and its corresponding frequency component, is obtained to represent the features of each gearbox fault. The two PCRVMs serve as two different fault detection committee members, and they are trained by using vibration and sound signals, respectively. The individual diagnostic result from each committee member is then combined by applying a new probabilistic ensemble method, which can improve the overall diagnostic accuracy and increase the number of detectable faults as compared to individual classifiers acting alone. The effectiveness of the proposed framework is experimentally verified by using test cases. The experimental results show the proposed framework is superior to existing single classifiers in terms of diagnostic accuracies for both single- and simultaneous-faults in the gearbox. PMID:26848665

An intelligent service matching method for mechanical equipment condition monitoring using the fibre Bragg grating sensor network

NASA Astrophysics Data System (ADS)

Zhang, Fan; Zhou, Zude; Liu, Quan; Xu, Wenjun

2017-02-01

Due to the advantages of being able to function under harsh environmental conditions and serving as a distributed condition information source in a networked monitoring system, the fibre Bragg grating (FBG) sensor network has attracted considerable attention for equipment online condition monitoring. To provide an overall conditional view of the mechanical equipment operation, a networked service-oriented condition monitoring framework based on FBG sensing is proposed, together with an intelligent matching method for supporting monitoring service management. In the novel framework, three classes of progressive service matching approaches, including service-chain knowledge database service matching, multi-objective constrained service matching and workflow-driven human-interactive service matching, are developed and integrated with an enhanced particle swarm optimisation (PSO) algorithm as well as a workflow-driven mechanism. Moreover, the manufacturing domain ontology, FBG sensor network structure and monitoring object are considered to facilitate the automatic matching of condition monitoring services to overcome the limitations of traditional service processing methods. The experimental results demonstrate that FBG monitoring services can be selected intelligently, and the developed condition monitoring system can be re-built rapidly as new equipment joins the framework. The effectiveness of the service matching method is also verified by implementing a prototype system together with its performance analysis.

Simultaneous-Fault Diagnosis of Gearboxes Using Probabilistic Committee Machine.

PubMed

Zhong, Jian-Hua; Wong, Pak Kin; Yang, Zhi-Xin

2016-02-02

This study combines signal de-noising, feature extraction, two pairwise-coupled relevance vector machines (PCRVMs) and particle swarm optimization (PSO) for parameter optimization to form an intelligent diagnostic framework for gearbox fault detection. Firstly, the noises of sensor signals are de-noised by using the wavelet threshold method to lower the noise level. Then, the Hilbert-Huang transform (HHT) and energy pattern calculation are applied to extract the fault features from de-noised signals. After that, an eleven-dimension vector, which consists of the energies of nine intrinsic mode functions (IMFs), maximum value of HHT marginal spectrum and its corresponding frequency component, is obtained to represent the features of each gearbox fault. The two PCRVMs serve as two different fault detection committee members, and they are trained by using vibration and sound signals, respectively. The individual diagnostic result from each committee member is then combined by applying a new probabilistic ensemble method, which can improve the overall diagnostic accuracy and increase the number of detectable faults as compared to individual classifiers acting alone. The effectiveness of the proposed framework is experimentally verified by using test cases. The experimental results show the proposed framework is superior to existing single classifiers in terms of diagnostic accuracies for both single- and simultaneous-faults in the gearbox.

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.

Seismic evidence for a slab tear at the Puerto Rico Trench

NASA Astrophysics Data System (ADS)

Meighan, Hallie E.; Pulliam, Jay; ten Brink, Uri; López-Venegas, Alberto M.

2013-06-01

fore-arc region of the northeast Caribbean plate north of Puerto Rico and the Virgin Islands has been the site of numerous seismic swarms since at least 1976. A 6 month deployment of five ocean bottom seismographs recorded two such tightly clustered swarms, along with additional events. Joint analyses of the ocean bottom seismographs and land-based seismic data reveal that the swarms are located at depths of 50-150 km. Focal mechanism solutions, found by jointly fitting P wave first-motion polarities and S/P amplitude ratios, indicate that the broadly distributed events outside the swarm generally have strike- and dip-slip mechanisms at depths of 50-100 km, while events at depths of 100-150 km have oblique mechanisms. A stress inversion reveals two distinct stress regimes: The slab segment east of 65°W longitude is dominated by trench-normal tensile stresses at shallower depths (50-100 km) and by trench-parallel tensile stresses at deeper depths (100-150 km), whereas the slab segment west of 65°W longitude has tensile stresses that are consistently trench normal throughout the depth range at which events were observed (50-100 km). The simple stress pattern in the western segment implies relatively straightforward subduction of an unimpeded slab, while the stress pattern observed in the eastern segment, shallow trench-normal tension and deeper trench-normal compression, is consistent with flexure of the slab due to rollback. These results support the hypothesis that the subducting North American plate is tearing at or near these swarms. The 35 year record of seismic swarms at this location and the recent increase in seismicity suggest that the tear is still propagating.

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.

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.

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.

Seismic evidence for a slab tear at the Puerto Rico Trench

USGS Publications Warehouse

Meighan, Hallie E.; Pulliam, Jay; ten Brink, Uri S.; López-Venegas, Alberto M.

2013-01-01

The fore-arc region of the northeast Caribbean plate north of Puerto Rico and the Virgin Islands has been the site of numerous seismic swarms since at least 1976. A 6 month deployment of five ocean bottom seismographs recorded two such tightly clustered swarms, along with additional events. Joint analyses of the ocean bottom seismographs and land-based seismic data reveal that the swarms are located at depths of 50–150 km. Focal mechanism solutions, found by jointly fitting P wave first-motion polarities and S/P amplitude ratios, indicate that the broadly distributed events outside the swarm generally have strike- and dip-slip mechanisms at depths of 50–100 km, while events at depths of 100–150 km have oblique mechanisms. A stress inversion reveals two distinct stress regimes: The slab segment east of 65°W longitude is dominated by trench-normal tensile stresses at shallower depths (50–100 km) and by trench-parallel tensile stresses at deeper depths (100–150 km), whereas the slab segment west of 65°W longitude has tensile stresses that are consistently trench normal throughout the depth range at which events were observed (50–100 km). The simple stress pattern in the western segment implies relatively straightforward subduction of an unimpeded slab, while the stress pattern observed in the eastern segment, shallow trench-normal tension and deeper trench-normal compression, is consistent with flexure of the slab due to rollback. These results support the hypothesis that the subducting North American plate is tearing at or near these swarms. The 35 year record of seismic swarms at this location and the recent increase in seismicity suggest that the tear is still propagating.

Dike orientations in the late jurassic independence dike swarm and implications for vertical-axis tectonic rotations in eastern California

USGS Publications Warehouse

Hopson, R.F.; Hillhouse, J.W.; Howard, K.A.

2008-01-01

Analysis of the strikes of 3841 dikes in 47 domains in the 500-km-long Late Jurassic Independence dike swarm indicates a distribution that is skewed clockwise from the dominant northwest strike. Independence dike swarm azimuths tend to cluster near 325?? ?? 30??, consistent with initial subparallel intrusion along much of the swarm. Dike azimuths in a quarter of the domains vary widely from the dominant trend. In domains in the essentially unrotated Sierra Nevada block, mean dike azimuths range mostly between 300?? and 320??, with the exception of Mount Goddard (247??). Mean dike azimuths in domains in the Basin and Range Province in the Argus, Inyo, and White Mountains areas range from 291?? to 354?? the mean is 004?? in the El Paso Mountains. In the Mojave Desert, mean dike azimuths range from 318?? to 023??, and in the eastern Transverse Ranges, they range from 316?? to 051??. Restoration for late Cenozoic vertical-axis rotations, suggested by paleodeclinations determined from published studies from nearby Miocene and younger rocks, shifts dike azimuths into better agreement with azimuths measured in the tectonically stable Sierra Nevada. This confirms that vertical-axis tectonic rotations explain some of the dispersion in orientation, especially in the Mojave Desert and eastern Transverse Ranges, and that the dike orientations can be a useful if imperfect guide to tectonic rotations where paleomagnetic data do not exist. Large deviations from the main trend of the swarm may reflect (1) clockwise rotations for which there is no paleomagnetic evidence available, (2) dike intrusions of other ages, (3) crack filling at angles oblique or perpendicular to the main swarm, (4) pre-Miocene rotations, or (5) unrecognized domain boundaries between dike localities and sites with paleomagnetic determinations. ?? 2008 The Geological Society of America.

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

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.

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

Structural framework and Mesozoic Cenozoic evolution of Ponta Grossa Arch, Paraná Basin, southern Brazil

NASA Astrophysics Data System (ADS)

Strugale, Michael; Rostirolla, Sidnei Pires; Mancini, Fernando; Portela Filho, Carlos Vieira; Ferreira, Francisco José Fonseca; de Freitas, Rafael Corrêa

2007-09-01

The integration of structural analyses of outcrops, aerial photographs, satellite images, aeromagnetometric data, and digital terrain models can establish the structural framework and paleostress trends related to the evolution of Ponta Grossa Arch, one of the most important structures of the Paraná Basin in southern Brazil. In the study area, the central-northern region of Paraná State, Brazil, the arch crosses outcropping areas of the Pirambóia, Botucatu, and Serra Geral Formations (São Bento Group, Mesozoic). The Pirambóia and Botucatu Formations are composed of quartz sandstones and subordinated siltstones. The Serra Geral Formation comprises tholeiitic basalt lava flows and associated intrusive rocks. Descriptive and kinematic structural analyses reveal the imprint of two brittle deformation phases: D1, controlled by the activation of an extensional system of regional faults that represent a progressive deformation that generated discontinuous brittle structures and dike swarm emplacement along a NW-SE trend, and D2, which was controlled by a strike-slip (transtensional) deformation system, probably of Late Cretaceous-Tertiary age, responsible for important fault reactivation along dykes and deformation bands in sandstones.

An improved shuffled frog leaping algorithm based evolutionary framework for currency exchange rate prediction

NASA Astrophysics Data System (ADS)

Dash, Rajashree

2017-11-01

Forecasting purchasing power of one currency with respect to another currency is always an interesting topic in the field of financial time series prediction. Despite the existence of several traditional and computational models for currency exchange rate forecasting, there is always a need for developing simpler and more efficient model, which will produce better prediction capability. In this paper, an evolutionary framework is proposed by using an improved shuffled frog leaping (ISFL) algorithm with a computationally efficient functional link artificial neural network (CEFLANN) for prediction of currency exchange rate. The model is validated by observing the monthly prediction measures obtained for three currency exchange data sets such as USD/CAD, USD/CHF, and USD/JPY accumulated within same period of time. The model performance is also compared with two other evolutionary learning techniques such as Shuffled frog leaping algorithm and Particle Swarm optimization algorithm. Practical analysis of results suggest that, the proposed model developed using the ISFL algorithm with CEFLANN network is a promising predictor model for currency exchange rate prediction compared to other models included in the study.

Active contour-based visual tracking by integrating colors, shapes, and motions.

PubMed

Hu, Weiming; Zhou, Xue; Li, Wei; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen

2013-05-01

In this paper, we present a framework for active contour-based visual tracking using level sets. The main components of our framework include contour-based tracking initialization, color-based contour evolution, adaptive shape-based contour evolution for non-periodic motions, dynamic shape-based contour evolution for periodic motions, and the handling of abrupt motions. For the initialization of contour-based tracking, we develop an optical flow-based algorithm for automatically initializing contours at the first frame. For the color-based contour evolution, Markov random field theory is used to measure correlations between values of neighboring pixels for posterior probability estimation. For adaptive shape-based contour evolution, the global shape information and the local color information are combined to hierarchically evolve the contour, and a flexible shape updating model is constructed. For the dynamic shape-based contour evolution, a shape mode transition matrix is learnt to characterize the temporal correlations of object shapes. For the handling of abrupt motions, particle swarm optimization is adopted to capture the global motion which is applied to the contour in the current frame to produce an initial contour in the next frame.

Trust Management Considerations For the Cooperative Infrastructure Defense Framework: Trust Relationships, Evidence, and Decisions

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

Maiden, Wendy M.

Cooperative Infrastructure Defense (CID) is a hierarchical, agent-based, adaptive, cyber-security framework designed to collaboratively protect multiple enclaves or organizations participating in a complex infrastructure. CID employs a swarm of lightweight, mobile agents called Sensors designed to roam hosts throughout a security enclave to find indications of anomalies and report them to host-based Sentinels. The Sensors’ findings become pieces of a larger puzzle, which the Sentinel puts together to determine the problem and respond per policy as given by the enclave-level Sergeant agent. Horizontally across multiple enclaves and vertically within each enclave, authentication and access control technologies are necessary but insufficientmore » authorization mechanisms to ensure that CID agents continue to fulfill their roles in a trustworthy manner. Trust management fills the gap, providing mechanisms to detect malicious agents and offering more robust mechanisms for authorization. This paper identifies the trust relationships throughout the CID hierarchy, the types of trust evidence that could be gathered, and the actions that the CID system could take if an entity is determined to be untrustworthy.« less

Visualization techniques for computer network defense

NASA Astrophysics Data System (ADS)

Beaver, Justin M.; Steed, Chad A.; Patton, Robert M.; Cui, Xiaohui; Schultz, Matthew

2011-06-01

Effective visual analysis of computer network defense (CND) information is challenging due to the volume and complexity of both the raw and analyzed network data. A typical CND is comprised of multiple niche intrusion detection tools, each of which performs network data analysis and produces a unique alerting output. The state-of-the-practice in the situational awareness of CND data is the prevalent use of custom-developed scripts by Information Technology (IT) professionals to retrieve, organize, and understand potential threat events. We propose a new visual analytics framework, called the Oak Ridge Cyber Analytics (ORCA) system, for CND data that allows an operator to interact with all detection tool outputs simultaneously. Aggregated alert events are presented in multiple coordinated views with timeline, cluster, and swarm model analysis displays. These displays are complemented with both supervised and semi-supervised machine learning classifiers. The intent of the visual analytics framework is to improve CND situational awareness, to enable an analyst to quickly navigate and analyze thousands of detected events, and to combine sophisticated data analysis techniques with interactive visualization such that patterns of anomalous activities may be more easily identified and investigated.

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 faulted surfaces. The work described has provided a useful framework for the development of regional ground-motion relations for Western Australia and will enable a better understanding of the mechanisms driving intraplate seismicity.

Motion reconstruction of animal groups: From schooling fish to swarming mosquitoes

NASA Astrophysics Data System (ADS)

Butail, Sachit

The long-term goal of this research is to provide kinematic data for the design and validation of spatial models of collective behavior in animal groups. The specific research objective of this dissertation is to apply methods from nonlinear estimation and computer vision to construct multi-target tracking systems that process multi-view calibrated video to reconstruct the three-dimensional movement of animals in a group. We adapt the tracking systems for the study of two animal species: Danio aequipinnatus, a common species of schooling fish, and Anopheles gambiae, the most important vector of malaria in sub-Saharan Africa. Together these tracking systems span variability in target size on image, density, and movement. For tracking fish, we automatically initialize, predict, and reconstruct shape trajectories of multiple fish through occlusions. For mosquitoes, which appear as faded streaks on in-field footage, we provide methods to extract velocity information from the streaks, adaptively seek missing measurements, and resolve occlusions within a multi-hypothesis framework. In each case the research has yielded an unprecedented volume of trajectory data for subsequent analysis. We present kinematic data of fast-start response in fish schools and first-ever trajectories of wild mosquito swarming and mating events. The broader impact of this work is to advance the understanding of animal groups for the design of bio-inspired robotic systems, where, similar to the animal groups we study, the collective is able to perform tasks far beyond the capabilities of a single inexpensive robot.

Magnetic Field Fluctuations in the High Ionosphere at Polar Latitudes: Impact of the IMF Conditions

NASA Astrophysics Data System (ADS)

De Michelis, P.; Consolini, G.; Tozzi, R.

2016-12-01

The characterization of ionospheric turbulence plays an important role for all those communication systems affected by the ionospheric medium. For instance, independently of geomagnetic latitude, ionospheric turbulence represents a considerable issue for all Global Navigation Satellite Systems (GNSS). Swarm constellation measurements of the Earth's magnetic field allow a precise characterization of ionospheric turbulence. This is possible using a range of indices derived from the analysis of the scaling properties of the geomagnetic field. In particular, by the scaling properties of the 1st order structure function, a scale index can be obtained, with a consequent characterization of the degree of persistence of the fluctuations and of their spectral properties. The knowledge of this index provides a global characterization of the nature and level of ionospheric turbulence on a local scale, which can be displayed along a single satellite orbit or through maps over the region of interest. The present work focuses on the analysis of the scaling properties of the 1st order structure function of magnetic field fluctuations measured by Swarm constellation at polar latitudes in the Northern Hemisphere. They are studied according to different interplanetary magnetic field conditions and Earth's seasons to characterize the possible drivers of magnetic field variability. The obtained results are discussed 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

A candidate secular variation model for IGRF-12 based on Swarm data and inverse geodynamo modelling

NASA Astrophysics Data System (ADS)

Fournier, Alexandre; Aubert, Julien; Thébault, Erwan

2015-05-01

In the context of the 12th release of the international geomagnetic reference field (IGRF), we present the methodology we followed to design a candidate secular variation model for years 2015-2020. An initial geomagnetic field model centered around 2014.3 is first constructed, based on Swarm magnetic measurements, for both the main field and its instantaneous secular variation. This initial model is next fed to an inverse geodynamo modelling framework in order to specify, for epoch 2014.3, the initial condition for the integration of a three-dimensional numerical dynamo model. The initialization phase combines the information contained in the initial model with that coming from the numerical dynamo model, in the form of three-dimensional multivariate statistics built from a numerical dynamo run unconstrained by data. We study the performance of this novel approach over two recent 5-year long intervals, 2005-2010 and 2009-2014. For a forecast horizon of 5 years, shorter than the large-scale secular acceleration time scale (˜10 years), we find that it is safer to neglect the flow acceleration and to assume that the flow determined by the initialization is steady. This steady flow is used to advance the three-dimensional induction equation forward in time, with the benefit of estimating the effects of magnetic diffusion. The result of this deterministic integration between 2015.0 and 2020.0 yields our candidate average secular variation model for that time frame, which is thus centered on 2017.5.

Improving the Adaptability of Simulated Evolutionary Swarm Robots in Dynamically Changing Environments

PubMed Central

Yao, Yao; Marchal, Kathleen; Van de Peer, Yves

2014-01-01

One of the important challenges in the field of evolutionary robotics is the development of systems that can adapt to a changing environment. However, the ability to adapt to unknown and fluctuating environments is not straightforward. Here, we explore the adaptive potential of simulated swarm robots that contain a genomic encoding of a bio-inspired gene regulatory network (GRN). An artificial genome is combined with a flexible agent-based system, representing the activated part of the regulatory network that transduces environmental cues into phenotypic behaviour. Using an artificial life simulation framework that mimics a dynamically changing environment, we show that separating the static from the conditionally active part of the network contributes to a better adaptive behaviour. Furthermore, in contrast with most hitherto developed ANN-based systems that need to re-optimize their complete controller network from scratch each time they are subjected to novel conditions, our system uses its genome to store GRNs whose performance was optimized under a particular environmental condition for a sufficiently long time. When subjected to a new environment, the previous condition-specific GRN might become inactivated, but remains present. This ability to store ‘good behaviour’ and to disconnect it from the novel rewiring that is essential under a new condition allows faster re-adaptation if any of the previously observed environmental conditions is reencountered. As we show here, applying these evolutionary-based principles leads to accelerated and improved adaptive evolution in a non-stable environment. PMID:24599485

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.

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.

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.

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.

Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation.

PubMed

Du, Tingsong; Hu, Yang; Ke, Xianting

2015-01-01

An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA.

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.

Coordination Between the Sexes Constrains the Optimization of Reproductive Timing in Honey Bee Colonies.

PubMed

Lemanski, Natalie J; Fefferman, Nina H

2017-06-01

Honeybees are an excellent model system for examining how trade-offs shape reproductive timing in organisms with seasonal environments. Honeybee colonies reproduce two ways: producing swarms comprising a queen and thousands of workers or producing males (drones). There is an energetic trade-off between producing workers, which contribute to colony growth, and drones, which contribute only to reproduction. The timing of drone production therefore determines both the drones' likelihood of mating and when colonies reach sufficient size to swarm. Using a linear programming model, we ask when a colony should produce drones and swarms to maximize reproductive success. We find the optimal behavior for each colony is to produce all drones prior to swarming, an impossible solution on a population scale because queens and drones would never co-occur. Reproductive timing is therefore not solely determined by energetic trade-offs but by the game theoretic problem of coordinating the production of reproductives among colonies.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Swarm motility inhibitory and antioxidant activities of pomegranate peel processed under three drying conditions.

PubMed

John, K M Maria; Bhagwat, Arvind A; Luthria, Devanand L

2017-11-15

During processing of ready-to-eat fresh fruits, large amounts of peel and seeds are discarded as waste. Pomegranate (Punicagranatum) peels contain high amounts of bioactive compounds which inhibit migration of Salmonella on wet surfaces. The metabolic distribution of bioactives in pomegranate peel, inner membrane, and edible aril portion was investigated under three different drying conditions along with the anti-swarming activity against Citrobacter rodentium. Based on the multivariate analysis, 29 metabolites discriminated the pomegranate peel, inner membrane, and edible aril portion, as well as the three different drying methods. Punicalagins (∼38.6-50.3mg/g) were detected in higher quantities in all fractions as compared to ellagic acid (∼0.1-3.2mg/g) and punicalins (∼0-2.4mg/g). The bioactivity (antioxidant, anti-swarming) and phenolics content was significantly higher in peels than the edible aril portion. Natural anti-swarming agents from food waste may have promising potential for controlling food borne pathogens. Published by Elsevier Ltd.

Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation

PubMed Central

Hu, Yang; Ke, Xianting

2015-01-01

An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA. PMID:26447713

H-NS represses transcription of the flagellin gene lafA of lateral flagella in Vibrio parahaemolyticus.

PubMed

Wang, Yan; Zhang, Yiquan; Yin, Zhe; Wang, Jie; Zhu, Yongzhe; Peng, Haoran; Zhou, Dongsheng; Qi, Zhongtian; Yang, Wenhui

2018-01-01

Swarming motility is ultimately mediated by the proton-powered lateral flagellar (laf) system in Vibrio parahaemolyticus. Expression of laf genes is tightly regulated by a number of environmental conditions and regulatory factors. The nucleoid-associated DNA-binding protein H-NS is a small and abundant protein that is widely distributed in bacteria, and H-NS-like protein-dependent expression of laf genes has been identified in Vibrio cholerae and V. parahaemolyticus. The data presented here show that H-NS acts as a repressor of the swarming motility in V. parahaemolyticus. A single σ 28 -dependent promoter was detected for lafA encoding the flagellin of the lateral flagella, and its activity was directly repressed by H-NS. Thus, H-NS represses swarming motility by directly acting on lafA. Briefly, this work revealed a novel function for H-NS as a repressor of the expression of lafA and swarming motility in V. parahaemolyticus.

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 dimension values are observed. Most significant for intraplate seismicity are relatively low fractal dimension values for temporal distribution. That observation reflects the strong degree of temporal earthquake clustering, which might explain the episodic character of earthquake swarms and support the idea of push-like triggering of earthquake avalanches by intruding magma.

Mafic microgranular enclave swarms in the Chenar granitoid stock, NW of Kerman, Iran: evidence for magma mingling

NASA Astrophysics Data System (ADS)

Arvin, M.; Dargahi, S.; Babaei, A. A.

2004-10-01

Mafic microgranular enclaves (MME) are common in the Early to Middle Miocene Chenar granitoid stock, northwest of Kerman, which is a part of Central Iranian Eocene volcanic belt. They occur individually and in homogeneous or heterogeneous swarms. The MME form a number of two-dimensional structural arrangements, such as dykes, small rafts, vortices, folded lens-shapes and late swarms. The enclaves are elongated, rounded to non-elongated and subrounded in shape and often show some size-sorting parallel to direction of flow. Variation in the elongation of enclaves could reflect variations in the viscosity of the enclave, the time available for enclave deformation and differential strain during flow of the host granitoid magma. The most effective mechanism in the formation of enclave swarms in the Chenar granitoid stock was velocity gradient-related convection currents in the granitoid magma chamber. Gravitational sorting and the break-up of heterogeneous dykes also form MME swarms. The MME (mainly diorite to diorite gabbro) have igneous mineralogy and texture, and are marked by sharp contacts next to their host granitoid rocks. The contact is often marked by a chilled margin with no sign of solid state deformation. Evidence of disequilibrium is manifested in feldspars by oscillatory zoning, resorbed rims, mantling and punctuated growth, together with overgrowth of clinopyroxene/amphibole on quartz crystals, the acicular habit of apatites and the development of Fe-Ti oxides along clinopyroxene cleavages. These observations suggest that the MMEs are derived from a hybrid-magma formed as a result of the intrusion of a mafic magma into the base of a felsic magma chamber. The density contrast between hybrid-magma and the overlying felsic magma was reduced by the release of dissolved fluids and the ascent of exsolved gas bubbles from the mafic magma into the hybrid zone. Further convection in the magma chamber dispersed the hybridized magma as globules in the upper parts of magma chamber where their entrainment and coalescence eventually formed swarms. Magma mingling between felsic and hybrid-magmas led to the formation of MMEs and swarms.

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 local times and at different disturbance levels. Though it is difficult to predict how quasi-definitive data might affect the analysis, we present the results obtained for each Swarm satellite and compare these results with those found for CHAMP.

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 acting on the Swarm satellites is the key for reaching these accuracies. Our results have implications for sea level budget studies, but they may also guide further research in gravity field analysis schemes, including satellites not dedicated to gravity field studies.

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 disposal process do not constitute strong evidence that the seismicity is induced by the fluid disposal, though they do not rule out this possibility.

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 the swarm is currently unknown with hypotheses ranging from magmatic or fluid motion in the crust to tectonic activity along a weakly coupled microplate boundary.

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.

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.

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.

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.

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.

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.

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

SWARMS: Scalable sWarms of Autonomous Robots and Mobile Sensors

DTIC Science & Technology

2013-03-18

Pasqualetti, Antonio Franchi , Francesco Bullo. On optimal cooperative patrolling, 2010 49th IEEE Conference on Decision and Control (CDC). 2010/12/15 00...exhibits “ global stability” Provided a complete convergence proof for the adaptive version of the range only station keeping problem. Graph Theoretic

The dance of male Anopheles gambiae in mating swarms

USDA-ARS?s Scientific Manuscript database

The mating behavior of the malaria vector Anopheles gambiae is of great interest from a fundamental and applied perspective. One of the most important elements of mating in this species is the crepuscular mating aggregation (swarm) composed almost entirely of males, where most coupling and inseminat...

Seismicity And Accretion Process Along The North Mid-Atlantic Ridge From The SIRENA Autonomous Hydrophone Data

NASA Astrophysics Data System (ADS)

Perrot, J.; Goslin, J.; Dziak, R. P.; Haxel, J. H.; Maia, M. A.; Tisseau, C.; Royer, J.

2009-12-01

The seismicity of the North Atlantic Ocean was recorded by the SIRENA array of 6 autonomous underwater hydrophones (AUH) moored within the SOFAR channel on the flanks of the Mid-Atlantic Ridge (MAR). The instruments were deployed north of the Azores Plateau between 40° and 50°N from June 2002 to September 2003. The low attenuation properties of the SOFAR channel for earthquake T-wave propagation result in a detection threshold reduction to a magnitude completeness level (Mc) of ~2.8, to be compared to a Mc~4.7 for MAR events recorded by land-based seismic networks. A spatio-temporal analysis was performed over the 1696 events localized inside the SIRENA array. For hydrophone-derived catalogs, the acoustic magnitude, or Source Level (SL), is used as a measure of earthquake size. The ''source level completeness'', above which the data set is complete, is SLc=208 dB. The SIRENA catalog was searched for swarms using the cluster software of the SEISAN distribution. A minimum SL of 210 dB was chosen to detect a possible mainshock, and all subsequent events within 40 days following the possible mainshock, located within a radius of 15 km from the mainshock were considered as events of the swarm. 15 km correspond to the maximum fault length in a slow-ridge context. 11 swarms with more than 15 events were detected along the MAR between 40°et 50°N during the SIRENA deployment. The maximum number of earthquakes in a swarm is 40 events. The SL vs. time distribution within each swarm allowed a first discrimination between the swarms occurring in a tectonic context and those which can be attributed to volcanic processes, the latter showing a more constant SL vs. time distribution. Moreover, the swarms occurring in a tectonic context show a "mainshock-afterschock" distribution of the cumulative number of events vs. time, fitting a Modified Omori Law. The location of tectonic and volcanic swarms correlates well with regions where a positive and negative Mantle Bouguer Anomalies (MBAs)(Maia et al., 2007) are observed, indicating the presence of thinner/colder and thicker/warmer crust respectively. Our results thus show that hydrophone data can be fruitfully used to help and characterize active ridge processes at various spatial scales. Maia M., J. Goslin, and P. Gente (2007), Evolution of accretion processes along the Mid-Atlantic Ridge north of the Azores since 5.5 Ma: An insight into the interactions between the ridge and the plume, Geochem. Geophys. Geosyst., 8.

Petrology, geochronology and emplacement model of the giant 1.37 Ga arcuate Lake Victoria Dyke Swarm on the margin of a large igneous province in eastern Africa

NASA Astrophysics Data System (ADS)

Mäkitie, Hannu; Data, Gabriel; Isabirye, Edward; Mänttäri, Irmeli; Huhma, Hannu; Klausen, Martin B.; Pakkanen, Lassi; Virransalo, Petri

2014-09-01

A comprehensive description of the petrography, geochemical composition, Sm-Nd data and intrinsic field relationships of a giant arcuate Mesoproterozoic mafic dyke swarm in SW Uganda is presented for the first time. The swarm is ∼100 km wide and mainly hosted in the Palaeoproterozoic Rwenzori Belt between the Mesoproterozoic Karagwe-Ankole Belt and the Archaean Uganda Block. The dykes trend NW-SE across Uganda, but can be correlated across Lake Victoria to another set of arcuate aeromagnetic anomalies that continue southwards into Tanzania, resulting in a remarkably large semi-circular swarm with an outer diameter of ∼500 km. We propose that this unique giant dyke structure be named the Lake Victoria Dyke Swarm (LVDS). The dykes are tholeiites with Mg numbers between 0.69 and 0.44, and with inherited marked negative Nb and P anomalies in spider diagrams. Two dykes provide Sm-Nd mineral ages of 1368 ± 41 Ma and 1374 ± 42 Ma, with initial εNd values of -2.3 and -3.2, and 87Sr/86Sr ratios of ∼0.706-0.709. Geotectonic discrimination diagrams for the swarm exhibit more arc type than within-plate tectonic signatures, but this is in accordance with systematic enrichments in LREE, U and Th in the dolerites, more likely due to the involvement of the continental lithosphere during their petrogenesis. The LVDS is coeval with a regional ∼1375 Ma bimodal magmatic event across nearby Burundi, Rwanda and NW Tanzania, which can collectively be viewed as a large igneous province (LIP). It also indicates that the nearby Karagwe-Ankole Belt sequences - bracketed between 1.78 and 1.37 Ga and assumed by some to have been deposited within intracratonic basins - were capped by flood basalts that have subsequently been removed by erosion. Different geochemical signatures (e.g. LaN/SmN) suggest that most of the arcuate swarm was derived from an enriched SCLM, whereas related intrusions in the centre of this semi-circular segment have more or less enriched asthenospheric mantle source signatures. A model of how the LIP configuration formed, and especially its giant arcuate swarm, requires fortuitous pre-existing structures, an unusually large sub-crustal magma chamber, and/or some very intrinsic rift process. The LIP is apparently related to a global 1.4-1.2 Ga rifting event that led to the break-up of the Columbia/Nuna supercontinent.

Putrescine importer PlaP contributes to swarming motility and urothelial cell invasion in Proteus mirabilis.

PubMed

Kurihara, Shin; Sakai, Yumi; Suzuki, Hideyuki; Muth, Aaron; Phanstiel, Otto; Rather, Philip N

2013-05-31

Previously, we reported that the speA gene, encoding arginine decarboxylase, is required for swarming in the urinary tract pathogen Proteus mirabilis. In addition, this previous study suggested that putrescine may act as a cell-to-cell signaling molecule (Sturgill, G., and Rather, P. N. (2004) Mol. Microbiol. 51, 437-446). In this new study, PlaP, a putative putrescine importer, was characterized in P. mirabilis. In a wild-type background, a plaP null mutation resulted in a modest swarming defect and slightly decreased levels of intracellular putrescine. In a P. mirabilis speA mutant with greatly reduced levels of intracellular putrescine, plaP was required for the putrescine-dependent rescue of swarming motility. When a speA/plaP double mutant was grown in the presence of extracellular putrescine, the intracellular levels of putrescine were greatly reduced compared with the speA mutant alone, indicating that PlaP functioned as the primary putrescine importer. In urothelial cell invasion assays, a speA mutant exhibited a 50% reduction in invasion when compared with wild type, and this defect could be restored by putrescine in a PlaP-dependent manner. The putrescine analog Triamide-44 partially inhibited the uptake of putrescine by PlaP and decreased both putrescine stimulated swarming and urothelial cell invasion in a speA mutant.

Different bees, different needs: how nest-site requirements have shaped the decision-making processes in homeless honeybees (Apis spp.).

PubMed

Beekman, Madeleine; Oldroyd, Benjamin P

2018-05-19

During reproductive swarming, a honeybee swarm needs to decide on a new nest site and then move to the chosen site collectively. Most studies of swarming and nest-site selection are based on one species, Apis mellifera Natural colonies of A. mellifera live in tree cavities. The quality of the cavity is critical to the survival of a swarm. Other honeybee species nest in the open, and have less strict nest-site requirements, such as the open-nesting dwarf honeybee Apis florea Apis florea builds a nest comprised of a single comb suspended from a twig. For a cavity-nesting species, there is only a limited number of potential nest sites that can be located by a swarm, because suitable sites are scarce. By contrast, for an open-nesting species, there is an abundance of equally suitable twigs. While the decision-making process of cavity-nesting bees is geared towards selecting the best site possible, open-nesting species need to coordinate collective movement towards areas with potential nest sites. Here, we argue that the nest-site selection processes of A. florea and A. mellifera have been shaped by each species' specific nest-site requirements. Both species use the same behavioural algorithm, tuned to allow each species to solve their species-specific problem.This article is part of the theme issue 'Collective movement ecology'. © 2018 The Author(s).

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.

EEG/ERP adaptive noise canceller design with controlled search space (CSS) approach in cuckoo and other optimization algorithms.

PubMed

Ahirwal, M K; Kumar, Anil; Singh, G K

2013-01-01

This paper explores the migration of adaptive filtering with swarm intelligence/evolutionary techniques employed in the field of electroencephalogram/event-related potential noise cancellation or extraction. A new approach is proposed in the form of controlled search space to stabilize the randomness of swarm intelligence techniques especially for the EEG signal. Swarm-based algorithms such as Particles Swarm Optimization, Artificial Bee Colony, and Cuckoo Optimization Algorithm with their variants are implemented to design optimized adaptive noise canceler. The proposed controlled search space technique is tested on each of the swarm intelligence techniques and is found to be more accurate and powerful. Adaptive noise canceler with traditional algorithms such as least-mean-square, normalized least-mean-square, and recursive least-mean-square algorithms are also implemented to compare the results. ERP signals such as simulated visual evoked potential, real visual evoked potential, and real sensorimotor evoked potential are used, due to their physiological importance in various EEG studies. Average computational time and shape measures of evolutionary techniques are observed 8.21E-01 sec and 1.73E-01, respectively. Though, traditional algorithms take negligible time consumption, but are unable to offer good shape preservation of ERP, noticed as average computational time and shape measure difference, 1.41E-02 sec and 2.60E+00, respectively.

Surface deformation associated with the March 1996 earthquake swarm at Akutan Island, Alaska, revealed by C-band ERS and L-band JERS radar interferometry

USGS Publications Warehouse

Lu, Z.; Wicks, C.; Kwoun, O.; Power, J.A.; Dzurisin, D.

2005-01-01

In March 1996, an intense earthquake swarm beneath Akutan Island, Alaska, was accompanied by extensive ground cracking but no eruption of Akutan volcano. Radar interferograms produced from L-band JERS-1 and C-band ERS-1/2 images show uplift associated with the swarm by as much as 60 cm on the western part of the island. The JERS-1 interferogram has greater coherence, especially in areas with loose surface material or thick vegetation. It also shows subsidence of similar magnitude on the eastern part of the island and displacements along faults reactivated during the swarm. The axis of uplift and subsidence strikes about N70??W, which is roughly parallel to a zone of fresh cracks on the northwest flank of the volcano, to normal faults that cut the island and to the inferred maximum compressive stress direction. A common feature of models that fit the deformation is the emplacement of a shallow dike along this trend beneath the northwest flank of the volcano. Both before and after the swarm, the northwest flank was uplifted 5-20 mm/year relative to the southwest flank, probably by magma intrusion. The zone of fresh cracks subsided about 20 mm during 1996-1997 and at lesser rates thereafter, possibly because of cooling and degassing of the intrusion. ?? 2005 CASI.

AEKF-SLAM: A New Algorithm for Robotic Underwater Navigation

PubMed Central

Yuan, Xin; Martínez-Ortega, José-Fernán; Fernández, José Antonio Sánchez; Eckert, Martina

2017-01-01

In this work, we focus on key topics related to underwater Simultaneous Localization and Mapping (SLAM) applications. Moreover, a detailed review of major studies in the literature and our proposed solutions for addressing the problem are presented. The main goal of this paper is the enhancement of the accuracy and robustness of the SLAM-based navigation problem for underwater robotics with low computational costs. Therefore, we present a new method called AEKF-SLAM that employs an Augmented Extended Kalman Filter (AEKF)-based SLAM algorithm. The AEKF-based SLAM approach stores the robot poses and map landmarks in a single state vector, while estimating the state parameters via a recursive and iterative estimation-update process. Hereby, the prediction and update state (which exist as well in the conventional EKF) are complemented by a newly proposed augmentation stage. Applied to underwater robot navigation, the AEKF-SLAM has been compared with the classic and popular FastSLAM 2.0 algorithm. Concerning the dense loop mapping and line mapping experiments, it shows much better performances in map management with respect to landmark addition and removal, which avoid the long-term accumulation of errors and clutters in the created map. Additionally, the underwater robot achieves more precise and efficient self-localization and a mapping of the surrounding landmarks with much lower processing times. Altogether, the presented AEKF-SLAM method achieves reliably map revisiting, and consistent map upgrading on loop closure. PMID:28531135

Prediction of protein-protein interaction network using a multi-objective optimization approach.

PubMed

Chowdhury, Archana; Rakshit, Pratyusha; Konar, Amit

2016-06-01

Protein-Protein Interactions (PPIs) are very important as they coordinate almost all cellular processes. This paper attempts to formulate PPI prediction problem in a multi-objective optimization framework. The scoring functions for the trial solution deal with simultaneous maximization of functional similarity, strength of the domain interaction profiles, and the number of common neighbors of the proteins predicted to be interacting. The above optimization problem is solved using the proposed Firefly Algorithm with Nondominated Sorting. Experiments undertaken reveal that the proposed PPI prediction technique outperforms existing methods, including gene ontology-based Relative Specific Similarity, multi-domain-based Domain Cohesion Coupling method, domain-based Random Decision Forest method, Bagging with REP Tree, and evolutionary/swarm algorithm-based approaches, with respect to sensitivity, specificity, and F1 score.

SCM: A method to improve network service layout efficiency with network evolution.

PubMed

Zhao, Qi; Zhang, Chuanhao; Zhao, Zheng

2017-01-01

Network services are an important component of the Internet, which are used to expand network functions for third-party developers. Network function virtualization (NFV) can improve the speed and flexibility of network service deployment. However, with the evolution of the network, network service layout may become inefficient. Regarding this problem, this paper proposes a service chain migration (SCM) method with the framework of "software defined network + network function virtualization" (SDN+NFV), which migrates service chains to adapt to network evolution and improves the efficiency of the network service layout. SCM is modeled as an integer linear programming problem and resolved via particle swarm optimization. An SCM prototype system is designed based on an SDN controller. Experiments demonstrate that SCM could reduce the network traffic cost and energy consumption efficiently.

Seismic swarms and fluid flow offshore Central America

NASA Astrophysics Data System (ADS)

Dzierma, Yvonne; Thorwart, Martin; Hensen, Christian; Rabbel, Wolfgang; Wolf, Florian

2010-05-01

Offshore Nicaragua and Northern Costa Rica, the Cocos Plate subducts beneath the Caribbean Plate, carrying with it a large amount of fluids and volatiles. While some of these are set free at great depth beneath the volcanic arc, causing the extremely high water content observed in Nicaraguan mafic magmas (Carr et al., 2003; Kutterolf et al., 2007), some early dehydration reactions already release fluids from the subducting plate underneath the continental slope. Unlike in accretionary margins, where these fluids migrate up along the decollement towards the deformation front, fluid release at erosional margins seems to occur through fractures in the overriding plate (Ranero et al., 2008). Fluid seeps in this region have be observed at seafloor mounds, appearing as side-scan sonar backscatter anomalies or revealed by the presence of chemosynthetic communities (Sahling et al., 2008). In the framework of the General Research Area SFB 574 "Volatiles and Fluids in Subduction Zones", a network of 20 ocean-bottom-stations was deployed offshore Sta Elena Peninsula, Northern Costa Rica, from December 2005 to June 2006. Several distinct swarms of small earthquakes were observed at the seismic stations, which occurred clustered over a time period of several days and have very similar seismic waveforms. Since a correlation of fluid-release sites with the occurrence of sporadic seismic swarms would indicate that fluid migration and fracturing is the mechanism responsible for triggering the earthquake swarms, the events are re-analysed by double-difference localisation to enhance the resolution of the earthquake locations. The results are then considered to estimate the migration velocity and direction and compare the localisations with the known mound sites. Carr, M., Feigenson, M. D., Patino, L. C., and Walker, J. A., 2003: Volcanism and geochemistry in Central America: Progress and problems, in Eiler, J. (ed.), Inside the subduction factory, pp. 153-179, American Geophysical Union Kutterolf S., Freundt, A., Perez, W. Wehrmann, H., and Schmincke, H. U., 2007: Late Pleistocene to Holocene temporal succession and magnitudes of highly-explosive volcanic eruptions in west-central Nicaragua. J. Volc. Geothermal Res. 163, pp. 55-82 Ranero, C. R., Grevemeyer, I., Sahling, H., Barckhausen, U., Hensen, C., Wallmann, K., Weinrebe, W., Vannucchi, P., von Huene, R., and McIntosh, K., 2008: Hydrogeological system of erosional convergent margins and its influence on tectonics and interplate seismogenesis, Geochem. Geophys. Geosys., Vol 9, Nr 3 Sahling, H., Masson, D. G., Ranero, C. R., Hühnerbach, V., Weinrebe, W., Klauke, I., Bürk, D., Brückmann, W., and Suess, E., 2008: Fluid seepage at the continental margin offshore Costa Rica and southern Nicaragua, Geochem. Geophys. Geosys., Vol 9, Nr 5

Multi-Target Tracking for Swarm vs. Swarm UAV Systems

DTIC Science & Technology

2012-09-01

Uhlmann, “Using covariance intersection for SLAM,” Robotics and Autonomous Systems, vol. 55, pp. 3–20, Jan. 2007. [10] R. B. G. Wolfgang Niehsen... Krause , J. Leskovec, and C. Guestrin, “Data association for topic intensity track- ing,” Proceedings of the 23rd international conference on Machine

Using archived ITS data to measure the operational benefits of a system-wide adaptive ramp metering system.

DOT National Transportation Integrated Search

2008-12-01

A System-Wide Adaptive Ramp Metering (SWARM) system has been implemented in the Portland, Oregon metropolitan area, replacing the previous pre-timed ramp-metering system that had been in operation since 1981. SWARM has been deployed on six major corr...

Characterization and Modeling of Insect Swarms Using tools from Fluid Dynamics

DTIC Science & Technology

2016-09-01

Scientific Reports, (01 2013): 1073 . doi: 10.1038/srep01073 James G. Puckett, Douglas H. Kelley, Nicholas T. Ouellette. Searching for effective...dynamics of laboratory insect swarms,” Sci. Rep. 3, 1073 (2013). [Ouellette et al. 2006] N. T. Ouellette, H. Xu, and E. Bodenschatz, “A quantitative