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Sample records for maps swarm perception

  1. IR-based Communication and Perception in Microrobotic Swarms

    CERN Document Server

    Kornienko, S

    2011-01-01

    In this work we consider development of IR-based communication and perception mechanisms for real microrobotic systems. It is demonstrated that a specific combination of hardware and software elements provides capabilities for navigation, objects recognition, directional and unidirectional communication. We discuss open issues and their resolution based on the experiments in the swarm of microrobots "Jasmine".

  2. Continuous Swarm Surveillance via Distributed Priority Maps

    Science.gov (United States)

    Howden, David

    With recent and ongoing improvements to unmanned aerial vehicle (UAV) endurance and availability, they are in a unique position to provide long term surveillance in risky environments. This paper presents a swarm intelligence algorithm for executing an exhaustive and persistent search of a non-trivial area of interest using a decentralized UAV swarm without long range communication. The algorithm allows for an environment containing arbitrary arrangements of no-fly zones, non-uniform levels of priority and dynamic priority changes in response to target acquisition or external commands. Performance is quantitatively analysed via comparative simulation with another leading algorithm of its class.

  3. Martian Swarm Exploration and Mapping Using Laser Slam

    Science.gov (United States)

    Nowak, S.; Krüger, T.; Matthaei, J.; Bestmann, U.

    2013-08-01

    In order to explore planet Mars in detail and search for extra-terrestrial life the observation from orbit is not sufficient. To realize complex exploration tasks the use of automatic operating robots with a robust fault-tolerant method of navigation, independent of any infrastructure is a possibility. This work includes a concept of rotary-wing Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) for Martian exploration in a swarm. Besides the scenario of Martian surrounding, with a small number of distinctive landmarks, the challenge consists of a Simultaneous Localization and Mapping (SLAM) concept using laser data of all swarm members.

  4. Swarm.

    Science.gov (United States)

    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)

  5. A scanning drift tube apparatus for spatio-temporal mapping of electron swarms

    CERN Document Server

    Korolov, I; Bastykova, N Kh; Donko, Z

    2016-01-01

    A "scanning" drift tube apparatus, capable of mapping of the spatio-temporal evolution of electron swarms, developing between two plane electrodes under the effect of a homogeneous electric field, is presented. The electron swarms are initiated by photoelectron pulses and the temporal distributions of the electron flux are recorded while the electrode gap length (at a fixed electric field strength) is varied. Operation of the system is tested and verified with argon gas, the measured data are used for the evaluation of the electron bulk drift velocity. The experimental results for the space-time maps of the electron swarms - presented here for the first time - also allow clear observation of deviations from hydrodynamic transport. The swarm maps are also reproduced by particle simulations.

  6. Levels and properties of map perception

    Directory of Open Access Journals (Sweden)

    Żyszkowska Wiesława

    2017-03-01

    Full Text Available Map perception consists of numerous processes of information processing, taking place almost simultaneously at different levels and stages which makes it conditioned by many factors. In the article, a review of processes related to the perception of a map as well as levels and properties of perception which impact its course and the nature of information obtained from a map is presented. The most important process constituting the basis of a map perception is a visual search (eye movement. However, as stated based on the studies, the process is individual depending on the purpose of map perception and it may be guided by its image (visual search guidance or by the knowledge of users (cognitive search guidance. Perception can take place according to various schemes – “local-to-global” or “global-to-local”, or in accordance with the guided search theory. Perception is divided into three processes: perceiving, distinguishing and identifying, which constitute the basis to interpret and understand a map. They are related to various degrees of intellectual involvement of the user and to various levels of questions concerning the relations between signs and their content. Identification involves referring a sign to its explanation in the legend. Interpretation means transformation of the initial information collected from the map into derivative information in which two basic types of understanding take place: deductive and inductive. Identification of geographical space objects on the map and the interpretation of its content constitute the basis to introduce information into memory structures. In the brain a resource of information is generated called geographic knowledge or spatial representation (mental map which may have a double nature – verbal or pictorial. An important feature of mental maps is organization of spatial information into hierarchical structures, e.g. grouping towns into regions as well as deformation of spatial

  7. Swarm based mean-variance mapping optimization (MVMOS) for solving economic dispatch

    Science.gov (United States)

    Khoa, T. H.; Vasant, P. M.; Singh, M. S. Balbir; Dieu, V. N.

    2014-10-01

    The economic dispatch (ED) is an essential optimization task in the power generation system. It is defined as the process of allocating the real power output of generation units to meet required load demand so as their total operating cost is minimized while satisfying all physical and operational constraints. This paper introduces a novel optimization which named as Swarm based Mean-variance mapping optimization (MVMOS). The technique is the extension of the original single particle mean-variance mapping optimization (MVMO). Its features make it potentially attractive algorithm for solving optimization problems. The proposed method is implemented for three test power systems, including 3, 13 and 20 thermal generation units with quadratic cost function and the obtained results are compared with many other methods available in the literature. Test results have indicated that the proposed method can efficiently implement for solving economic dispatch.

  8. 3-D electromagnetic induction studies using the Swarm constellation: Mapping conductivity anomalies in the Earth's mantle

    DEFF Research Database (Denmark)

    Kuvshinov, A.; Sabaka, T.; Olsen, Nils

    2006-01-01

    satellite data that contain contributions from the core and lithosphere, from the rnagnetosphere and ionosphere (and their Earth-induced counterparts), as well as payload noise has been investigated. The model Studies have shown that C-responses obtained oil a regular grid might be used to map regional deep......An approach is presented to detect deep-seated regional conductivity anomalies by analysis of magnetic observations taken by low-Earth-orbiting satellites. The approach deals with recovery of C-responses on a regular grid and starts with a determination of time series of external and internal....... For validation of the approach, 3 years of realistic synthetic data at Simulated orbits of the forthcoming Swarm constellation of 3 satellites have been used. To obtain the synthetic data for a given 3-D conductivity Earth's model a time-domain scheme has been applied which relies oil a Fourier transformation...

  9. Using H/V Spectral Ratio Analysis to Map Sediment Thickness and to Explain Macroseismic Intensity Variation of a Low-Magnitude Seismic Swarm in Central Belgium

    Science.gov (United States)

    Van Noten, K.; Lecocq, T.; Camelbeeck, T.

    2013-12-01

    Between 2008 and 2010, the Royal Observatory of Belgium received numerous ';Did You Feel It'-reports related to a 2-year lasting earthquake swarm at Court-Saint-Etienne, a small town in a hilly area 20 km SE of Brussels, Belgium. These small-magnitude events (-0.7 ≤ ML ≤ 3.2, n = c. 300 events) were recorded both by the permanent seismometer network in Belgium and by a locally installed temporary seismic network deployed in the epicentral area. Relocation of the hypocenters revealed that the seismic swarm can be related to the reactivation of a NW-SE strike-slip fault at 3 to 6 km depth in the basement rocks of the Lower Palaeozoic London-Brabant Massif. This sequence caused a lot of emotion in the region because more than 60 events were felt by the local population. Given the small magnitudes of the seismic swarm, most events were more often heard than felt by the respondents, which is indicative of a local high-frequency earthquake source. At places where the bedrock is at the surface or where it is covered by thin alluvial sediments ( 30 m). In those river valleys that have a considerable alluvial sedimentary cover, macroseismic intensities are again lower. To explain this variation in macroseismic intensity we present a macroseismic analysis of all DYFI-reports related to the 2008-2010 seismic swarm and a pervasive H/V spectral ratio (HVSR) analysis of ambient noise measurements to model the thickness of sediments covering the London-Brabant Massif. The HVSR method is a very powerful tool to map the basement morphology, particularly in regions of unknown subsurface structure. By calculating the soil's fundamental frequency above boreholes, we calibrated the power-law relationship between the fundamental frequency, shear wave velocity and the thickness of sediments. This relationship is useful for places where the sediment thickness is unknown and where the fundamental frequency can be calculated by H/V spectral ratio analysis of ambient noise. In a

  10. Mapping the topography and cone morphology of the Dalinor volcanic swarm in Inner Mongolia with remote sensing and DEM data

    Science.gov (United States)

    Gong, Liwen; Li, Ni; Fan, Qicheng; Zhao, Yongwei; Zhang, Liuyi; Zhang, Chuanjie

    2016-09-01

    The Dalinor volcanic swarm, located south of Xilinhot, Inner Mongolia of China, was a result of multistage eruptions that occurred since the Neogene period. This swarm is mainly composed of volcanic cones and lava tablelands. The objective of this study is to map the topography and morphology of this volcanic swarm. It is based on a variety of data collected from various sources, such as the digital elevation model (DEM), Landsat images, and a 1:50,000 topographic map, in addition to various software platforms, including ArcGIS, Envi4.8, Global Mapper, and Google Earth for data processing and interpretation. The results show that the overall topography of the volcanic swarm is a platform with a central swell having great undulation, sizable gradient variations, a rough surface, and small terrain relief. According to the undulating characteristics of the line profile, the volcanic swarm can be divided into four stairs with heights of 1,280 m, 1,360 m, 1,440 m, and 1,500 m. The analysis of the swath profile characterizes the two clusters of volcanoes with different height ranges and evolution. The lava tablelands and volcanic cones are distributed in nearly EW-trending belts, where tableland coverage was delineated with superposed layers of gradients and degrees of relief. According to the morphology, the volcanic cones were classified into four types: conical, composite, dome, and shield. The formation causes and classification basis for each type of volcanic cone were analyzed and their parameters were extracted. The H/D ratios of all types of volcanic cones were then statistically determined and projected to create a map of volcanic density distribution. Based on the relationship between distribution and time sequence of the formation of different volcanic cones, it can be inferred that the volcanic eruptions migrated from the margins to the center of the lava plateau. The central area was formed through superposition of multi-stage eruptive materials. In addition

  11. Tracking and mapping of spatiotemporal quantities using unicellular swarm intelligence visualisation of invisible hazardous substances using unicellular swarm intelligence

    CERN Document Server

    Oyekan, John Oluwagbemiga

    2016-01-01

    The book discusses new algorithms capable of searching for, tracking, mapping and providing a visualization of invisible substances. It reports on the realization of a bacterium-inspired robotic controller that can be used by an agent to search for any environmental spatial function such as temperature or pollution. Using the parameters of a mathematical model, the book shows that it is possible to control the exploration, exploitation and sensitivity of the agent. This feature sets the work apart from the usual method of applying the bacterium behavior to robotic agents. The book also discusses how a computationally tractable multi-agent robotic controller was developed and used to track as well as provide a visual map of a spatio-temporal distribution of a substance. On the one hand, this book provides biologists and ecologists with a basis to perform simulations related to how individual organisms respond to spatio-temporal factors in their environment as well as predict and analyze the behavior of organis...

  12. Swarm - The European Space Agency's Constellation Mission: Mapping Earth's Magnetic and Electric Fields

    Science.gov (United States)

    Floberghagen, Rune

    2016-07-01

    Launched on 22 November 2013, the three-satellite Swarm constellation is about halfway into its four-year nominal mission. Embarking identical, high accuracy and high spatial as well as temporal resolution instrumentation on all satellites, the mission has ambitious goals reaching from the deep Earth interior (the liquid outer core) all the way out to the solar-terrestrial interaction in the magnetosphere. One may safely state that the mission addresses a diverse range of science issues, and therefore acts as a true discoverer in many fields. Measurements of the magnetic field (magnitude and vector components), the electric field (through ion drift velocity, ion density, ion temperature, electron density, electron temperature and spacecraft potential), the gas density and horizontal winds as well as precise positioning are supported by a range of derived products for the magnetic field, geophysics, aeronomy and space physics communities. Indeed, Swarm is at the forefront of cross-cutting science issues that involve significant parts of the space and earth physics community. In recent data exploitation and science projects we have also seen a high number of coupling studies emerging. This contribution details the status and achievements of the mission in the field of magnetic field, electric field and geospace research. It furthermore discusses the the Agency's further plans, beyond the currently foreseen nominal end of mission in spring 2018. The role of Swarm for space weather research will also be discussed.

  13. Modeling dynamic swarms

    KAUST Repository

    Ghanem, Bernard

    2013-01-01

    This paper proposes the problem of modeling video sequences of dynamic swarms (DSs). We define a DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local spatiotemporal interdependency and stationarity, i.e., the motions are similar in any small spatiotemporal neighborhood. Examples of DS abound in nature, e.g., herds of animals and flocks of birds. To capture the local spatiotemporal properties of the DS, we present a probabilistic model that learns both the spatial layout of swarm elements (based on low-level image segmentation) and their joint dynamics that are modeled as linear transformations. To this end, a spatiotemporal neighborhood is associated with each swarm element, in which local stationarity is enforced both spatially and temporally. We assume that the prior on the swarm dynamics is distributed according to an MRF in both space and time. Embedding this model in a MAP framework, we iterate between learning the spatial layout of the swarm and its dynamics. We learn the swarm transformations using ICM, which iterates between estimating these transformations and updating their distribution in the spatiotemporal neighborhoods. We demonstrate the validity of our method by conducting experiments on real and synthetic video sequences. Real sequences of birds, geese, robot swarms, and pedestrians evaluate the applicability of our model to real world data. © 2012 Elsevier Inc. All rights reserved.

  14. Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce.

    Science.gov (United States)

    Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan

    2016-01-01

    A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network's initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data.

  15. Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce.

    Directory of Open Access Journals (Sweden)

    Jianfang Cao

    Full Text Available A back-propagation (BP neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network's initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data.

  16. Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce

    Science.gov (United States)

    Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan

    2016-01-01

    A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network’s initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data. PMID:27304987

  17. A method to derive maps of ionospheric conductances, currents, and convection from the Swarm multisatellite mission

    DEFF Research Database (Denmark)

    Amm, O.; Vanhamäki, H.; Kauristie, K.

    2015-01-01

    , currents, and electric field in the area between the trajectories of the two lower spacecraft, and even to some extent outside of it. This technique is based on Spherical Elementary Current Systems. We present test cases of modeled situations from which we calculate virtual Swarm data and show...... that the technique is able to reconstruct the model electric field, horizontal currents, and conductances with a very good accuracy. Larger errors arise for the reconstruction of the 2-D field-aligned currents (FAC), especially in the area outside of the spacecraft orbits. However, even in this case the general...... pattern of FAC is recovered, and the magnitudes are valid in an integrated sense. Finally, using an MHD model run, we show how our technique allows estimation of the ionosphere-magnetosphere coupling parameter K, if conjugate observations of the magnetospheric magnetic and electric field are available...

  18. Double-bottom chaotic map particle swarm optimization based on chi-square test to determine gene-gene interactions.

    Science.gov (United States)

    Yang, Cheng-Hong; Lin, Yu-Da; Chuang, Li-Yeh; Chang, Hsueh-Wei

    2014-01-01

    Gene-gene interaction studies focus on the investigation of the association between the single nucleotide polymorphisms (SNPs) of genes for disease susceptibility. Statistical methods are widely used to search for a good model of gene-gene interaction for disease analysis, and the previously determined models have successfully explained the effects between SNPs and diseases. However, the huge numbers of potential combinations of SNP genotypes limit the use of statistical methods for analysing high-order interaction, and finding an available high-order model of gene-gene interaction remains a challenge. In this study, an improved particle swarm optimization with double-bottom chaotic maps (DBM-PSO) was applied to assist statistical methods in the analysis of associated variations to disease susceptibility. A big data set was simulated using the published genotype frequencies of 26 SNPs amongst eight genes for breast cancer. Results showed that the proposed DBM-PSO successfully determined two- to six-order models of gene-gene interaction for the risk association with breast cancer (odds ratio > 1.0; P value <0.05). Analysis results supported that the proposed DBM-PSO can identify good models and provide higher chi-square values than conventional PSO. This study indicates that DBM-PSO is a robust and precise algorithm for determination of gene-gene interaction models for breast cancer.

  19. Double-Bottom Chaotic Map Particle Swarm Optimization Based on Chi-Square Test to Determine Gene-Gene Interactions

    Directory of Open Access Journals (Sweden)

    Cheng-Hong Yang

    2014-01-01

    Full Text Available Gene-gene interaction studies focus on the investigation of the association between the single nucleotide polymorphisms (SNPs of genes for disease susceptibility. Statistical methods are widely used to search for a good model of gene-gene interaction for disease analysis, and the previously determined models have successfully explained the effects between SNPs and diseases. However, the huge numbers of potential combinations of SNP genotypes limit the use of statistical methods for analysing high-order interaction, and finding an available high-order model of gene-gene interaction remains a challenge. In this study, an improved particle swarm optimization with double-bottom chaotic maps (DBM-PSO was applied to assist statistical methods in the analysis of associated variations to disease susceptibility. A big data set was simulated using the published genotype frequencies of 26 SNPs amongst eight genes for breast cancer. Results showed that the proposed DBM-PSO successfully determined two- to six-order models of gene-gene interaction for the risk association with breast cancer (odds ratio > 1.0; P value <0.05. Analysis results supported that the proposed DBM-PSO can identify good models and provide higher chi-square values than conventional PSO. This study indicates that DBM-PSO is a robust and precise algorithm for determination of gene-gene interaction models for breast cancer.

  20. Microclimate perception analysis through cognitive mapping

    NARCIS (Netherlands)

    Lenzholzer, S.

    2008-01-01

    Outdoor thermal comfort is not only determined by microclimate, but also by perceptual factors. As environmental psychology has brought forward, people develop cognitive ¿schemata¿ about the physical settings they are exposed to. It can be assumed that this mechanism influences thermal perception as

  1. Enhanced visual perception through tone mapping

    Science.gov (United States)

    Harrison, Andre; Mullins, Linda L.; Raglin, Adrienne; Etienne-Cummings, Ralph

    2016-05-01

    Tone mapping operators compress high dynamic range images to improve the picture quality on a digital display when the dynamic range of the display is lower than that of the image. However, tone mapping operators have been largely designed and evaluated based on the aesthetic quality of the resulting displayed image or how perceptually similar the compressed image appears relative to the original scene. They also often require per image tuning of parameters depending on the content of the image. In military operations, however, the amount of information that can be perceived is more important than the aesthetic quality of the image and any parameter adjustment needs to be as automated as possible regardless of the content of the image. We have conducted two studies to evaluate the perceivable detail of a set of tone mapping algorithms, and we apply our findings to develop and test an automated tone mapping algorithm that demonstrates a consistent improvement in the amount of perceived detail. An automated, and thereby predictable, tone mapping method enables a consistent presentation of perceivable features, can reduce the bandwidth required to transmit the imagery, and can improve the accessibility of the data by reducing the needed expertise of the analyst(s) viewing the imagery.

  2. Elastic and inelastic collisions of swarms

    Science.gov (United States)

    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.

  3. Using a Combined Platform of Swarm Intelligence Algorithms and GIS to Provide Land Suitability Maps for Locating Cardiac Rehabilitation Defibrillators

    Directory of Open Access Journals (Sweden)

    Neda KAFFASH-CHARANDABI

    2015-10-01

    Full Text Available Background: Cardiac arrest is a condition in which the heart is completely stopped and is not pumping any blood. Although most cardiac arrest cases are reported from homes or hospitals, about 20% occur in public areas. Therefore, these areas need to be investigated in terms of cardiac arrest incidence so that places of high incidence can be identi-fied and cardiac rehabilitation defibrillators installed there.Methods: In order to investigate a study area in Petersburg, Pennsylvania State, and to determine appropriate places for installing defibrillators with 5-year period data, swarm intelligence algorithms were used. Moreover, the location of the defibrillators was determined based on the following five evaluation criteria: land use, altitude of the area, econom-ic conditions, distance from hospitals and approximate areas of reported cases of cardiac arrest for public places that were created in geospatial information system (GIS.Results: The A-P HADEL algorithm results were more precise about 27.36%. The validation results indicated a wider coverage of real values and the verification results confirmed the faster and more exact optimization of the cost func-tion in the PSO method.Conclusion: The study findings emphasize the necessity of applying optimal optimization methods along with GIS and precise selection of criteria in the selection of optimal locations for installing medical facilities because the selected algorithm and criteria dramatically affect the final responses. Meanwhile, providing land suitability maps for installing facilities across hot and risky spots has the potential to save many lives.

  4. Vowel Acoustics in Dysarthria: Mapping to Perception

    Science.gov (United States)

    Lansford, Kaitlin L.; Liss, Julie M.

    2014-01-01

    Purpose The aim of the present report was to explore whether vowel metrics, demonstrated to distinguish dysarthric and healthy speech in a companion article (Lansford & Liss, 2014), are able to predict human perceptual performance. Method Vowel metrics derived from vowels embedded in phrases produced by 45 speakers with dysarthria were compared with orthographic transcriptions of these phrases collected from 120 healthy listeners. First, correlation and stepwise multiple regressions were conducted to identify acoustic metrics that had predictive value for perceptual measures. Next, discriminant function analysis misclassifications were compared with listeners’ misperceptions to examine more directly the perceptual consequences of degraded vowel acoustics. Results Several moderate correlative relationships were found between acoustic metrics and perceptual measures, with predictive models accounting for 18%–75% of the variance in measures of intelligibility and vowel accuracy. Results of the second analysis showed that listeners better identified acoustically distinctive vowel tokens. In addition, the level of agreement between misclassified-to-misperceived vowel tokens supports some specificity of degraded acoustic profiles on the resulting percept. Conclusion Results provide evidence that degraded vowel acoustics have some effect on human perceptual performance, even in the presence of extravowel variables that naturally exert influence in phrase perception. PMID:24687468

  5. Perception of the contents of animated maps

    Directory of Open Access Journals (Sweden)

    Łucjan Kamila

    2016-12-01

    Full Text Available Intense development of computer technology has taken place in the last several decades made it possible to cartographically present variability of phenomena in a dynamic way. As a result of using animation techniques in cartography there appeared new methods of presentation of changes, referred to as direct. Considering the character of the relation between display time and real time, two basic types of animated maps have been distinguished: temporal and non-temporal. Other criteria of classifying animation are the presence and level of interactivity and the technical criteria of production.

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

    Science.gov (United States)

    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 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

  7. Mapping spatial patterns of people's risk perception of landslides

    Science.gov (United States)

    Kofler, Christian; Pedoth, Lydia; Elzbieta Stawinoga, Agnieszka; Schneiderbauer, Stefan

    2016-04-01

    The resilience of communities against natural hazards is largely influenced by how the individuals perceive risk. A good understanding of people's risk perception, awareness and hazard knowledge is crucial for developing and improving risk management and communication strategies between authorities and the affected population. A lot of research has been done in investigating the social aspects of risks to natural hazards by means of interviews or questionnaires. However, there is still a lack of research in the investigation of the influence of the spatial distance to a hazard event on peoples risk perception. While the spatial dimension of a natural hazard event is always assessed in works with a natural science approach, it is often neglected in works on social aspects of natural hazards. In the present study, we aimed to overcome these gaps by combining methods from different disciplines and assessing and mapping the spatial pattern of risk perception through multivariate statistical approaches based on empirical data from questionnaires. We will present results from a case study carried out in Badia, located in the Province of South Tyrol- Italy, where in December 2012 a landslide destroyed four residential buildings and led to the evacuation of 36 people. By means of questionnaires distributed to all adults living in the case study area we assessed people's risk perception and asked respondents to allocate their place of residence on a map of the case study area subdivided in 7 zones. Based on the data of the questionnaire results we developed a risk perception factor in order to express various assessed aspects linked to risk perception with one metric. We analyzed and mapped this factor according to the different zones reflecting the spatial distance to the event. Furthermore, a cluster analysis identified various risk behavior profiles within the population. We also investigated the spatial patterns of these risk profiles. We revealed that the residential

  8. A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China.

    Science.gov (United States)

    Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

    2016-05-11

    In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%-19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides.

  9. Swarm Intelligence

    OpenAIRE

    Thampi, Sabu M.

    2009-01-01

    Biologically inspired computing is an area of computer science which uses the advantageous properties of biological systems. It is the amalgamation of computational intelligence and collective intelligence. Biologically inspired mechanisms have already proved successful in achieving major advances in a wide range of problems in computing and communication systems. The consortium of bio-inspired computing are artificial neural networks, evolutionary algorithms, swarm intelligence, artificial i...

  10. Differences in Stakeholder Perceptions about Training Evaluation: A Concept Mapping/Pattern Matching Investigation.

    Science.gov (United States)

    Michalski, Greg V.; Cousins, J. Bradley

    2000-01-01

    Used concept mapping and pattern matching in exploratory research to investigate differences in stakeholder perceptions of training results and evaluation. Group perceptions and the individual perceptions of 39 managers, product developers, and training professionals show that all stakeholder groups agreed reasonably well about the importance of…

  11. Landslide Susceptibility Mapping Based on Particle Swarm Optimization of Multiple Kernel Relevance Vector Machines: Case of a Low Hill Area in Sichuan Province, China

    Directory of Open Access Journals (Sweden)

    Yongliang Lin

    2016-10-01

    Full Text Available In this paper, we propose a multiple kernel relevance vector machine (RVM method based on the adaptive cloud particle swarm optimization (PSO algorithm to map landslide susceptibility in the low hill area of Sichuan Province, China. In the multi-kernel structure, the kernel selection problem can be solved by adjusting the kernel weight, which determines the single kernel contribution of the final kernel mapping. The weights and parameters of the multi-kernel function were optimized using the PSO algorithm. In addition, the convergence speed of the PSO algorithm was increased using cloud theory. To ensure the stability of the prediction model, the result of a five-fold cross-validation method was used as the fitness of the PSO algorithm. To verify the results, receiver operating characteristic curves (ROC and landslide dot density (LDD were used. The results show that the model that used a heterogeneous kernel (a combination of two different kernel functions had a larger area under the ROC curve (0.7616 and a lower prediction error ratio (0.28% than did the other types of kernel models employed in this study. In addition, both the sum of two high susceptibility zone LDDs (6.71/100 km2 and the sum of two low susceptibility zone LDDs (0.82/100 km2 demonstrated that the landslide susceptibility map based on the heterogeneous kernel model was closest to the historical landslide distribution. In conclusion, the results obtained in this study can provide very useful information for disaster prevention and land-use planning in the study area.

  12. A particle swarm optimized kernel-based clustering method for crop mapping from multi-temporal polarimetric L-band SAR observations

    Science.gov (United States)

    Tamiminia, Haifa; Homayouni, Saeid; McNairn, Heather; Safari, Abdoreza

    2017-06-01

    Polarimetric Synthetic Aperture Radar (PolSAR) data, thanks to their specific characteristics such as high resolution, weather and daylight independence, have become a valuable source of information for environment monitoring and management. The discrimination capability of observations acquired by these sensors can be used for land cover classification and mapping. The aim of this paper is to propose an optimized kernel-based C-means clustering algorithm for agriculture crop mapping from multi-temporal PolSAR data. Firstly, several polarimetric features are extracted from preprocessed data. These features are linear polarization intensities, and several statistical and physical based decompositions such as Cloude-Pottier, Freeman-Durden and Yamaguchi techniques. Then, the kernelized version of hard and fuzzy C-means clustering algorithms are applied to these polarimetric features in order to identify crop types. The kernel function, unlike the conventional partitioning clustering algorithms, simplifies the non-spherical and non-linearly patterns of data structure, to be clustered easily. In addition, in order to enhance the results, Particle Swarm Optimization (PSO) algorithm is used to tune the kernel parameters, cluster centers and to optimize features selection. The efficiency of this method was evaluated by using multi-temporal UAVSAR L-band images acquired over an agricultural area near Winnipeg, Manitoba, Canada, during June and July in 2012. The results demonstrate more accurate crop maps using the proposed method when compared to the classical approaches, (e.g. 12% improvement in general). In addition, when the optimization technique is used, greater improvement is observed in crop classification, e.g. 5% in overall. Furthermore, a strong relationship between Freeman-Durden volume scattering component, which is related to canopy structure, and phenological growth stages is observed.

  13. Swarm Verification

    Science.gov (United States)

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

    2008-01-01

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

  14. Perception Mapping of Travelers: Case of Six Indian Domestic Airlines

    Directory of Open Access Journals (Sweden)

    Shobhit Agarwal

    2010-01-01

    Full Text Available Problem statement: A comparison of customer satisfaction based on service quality as perceived by air travelers was done among six domestic airlines. Literature review suggested that flying experience has three stages: Pre-flight, in-flight and post-flight and a set of six variables can be used to measure satisfaction. These variables are: Ease of bookings through the website/call center; Hassle free check in/efficient ticketing staff/regular announcements during flight delays at airport; on time performance of flights; in flight experience; baggage handling and value for money. Approach: A questionnaire was designed with above set of variables and responses of 150 fliers of six domestic airlines viz., GoAir, Kingfisher, Jet Airways, Indigo, SpiceJet and Air India (Domestic was recorded on a five point Likert scale. About 150 respondents were interviewed from different places in NCR: Delhi, Gurgaon, Noida, Greater Noida and Faridabad. A convenient sampling method was followed. Perceptions of only those travelers were captured who had actually undergone the experience of travelling by an airline. The range for the number of respondents was between 103 (for GoAir and 133 (for Jet Air. Results: Using one way ANOVA, it was checked whether travelers perceive any significant difference between six airlines for each of the above six identified variables. With Tukey-Kramer test the airlines which are significantly different from the rest were identified. Perceptual maps with combination of up to two variables (attributes were drawn to infer about the positioning of six different airlines. Conclusion: This study will help marketers of domestic airlines and designers of flight service offerings to enhance the satisfaction level of air travelers.

  15. Subjectivity in Design Education: The Perception of the City through Personal Maps

    Science.gov (United States)

    Yilmaz, Ebru

    2016-01-01

    Our mental maps related to the cities are limited by our personal perception and fragmented in the process. There are many inner and outer effects that shape our mental maps, and as a result the fragmented whole refers to the total city image in our minds. To represent this image, an experimental study has been conducted with a group of students.…

  16. Approximate Robotic Mapping from sonar data by modeling Perceptions with Antonyms

    CERN Document Server

    Guadarrama, Sergio

    2010-01-01

    This work, inspired by the idea of "Computing with Words and Perceptions" proposed by Zadeh in 2001, focuses on how to transform measurements into perceptions for the problem of map building by Autonomous Mobile Robots. We propose to model the perceptions obtained from sonar-sensors as two grid maps: one for obstacles and another for empty spaces. The rules used to build and integrate these maps are expressed by linguistic descriptions and modeled by fuzzy rules. The main difference of this approach from other studies reported in the literature is that the method presented here is based on the hypothesis that the concepts "occupied" and "empty" are antonyms rather than complementary (as it happens in probabilistic approaches), or independent (as it happens in the previous fuzzy models). Controlled experimentation with a real robot in three representative indoor environments has been performed and the results presented. We offer a qualitative and quantitative comparison of the estimated maps obtained by the pr...

  17. From hybrid swarms to swarms of hybrids

    Science.gov (United States)

    Stohlgren, Thomas J.; Szalanski, Allen L; Gaskin, John F.; Young, Nicholas E.; West, Amanda; Jarnevich, Catherine S.; Tripodi, Amber

    2015-01-01

    Science has shown that the introgression or hybridization of modern humans (Homo sapiens) with Neanderthals up to 40,000 YBP may have led to the swarm of modern humans on earth. However, there is little doubt that modern trade and transportation in support of the humans has continued to introduce additional species, genotypes, and hybrids to every country on the globe. We assessed the utility of species distributions modeling of genotypes to assess the risk of current and future invaders. We evaluated 93 locations of the genus Tamarix for which genetic data were available. Maxent models of habitat suitability showed that the hybrid, T. ramosissima x T. chinensis, was slightly greater than the parent taxa (AUCs > 0.83). General linear models of Africanized honey bees, a hybrid cross of Tanzanian Apis mellifera scutellata and a variety of European honey bee including A. m. ligustica, showed that the Africanized bees (AUC = 0.81) may be displacing European honey bees (AUC > 0.76) over large areas of the southwestern U.S. More important, Maxent modeling of sub-populations (A1 and A26 mitotypes based on mDNA) could be accurately modeled (AUC > 0.9), and they responded differently to environmental drivers. This suggests that rapid evolutionary change may be underway in the Africanized bees, allowing the bees to spread into new areas and extending their total range. Protecting native species and ecosystems may benefit from risk maps of harmful invasive species, hybrids, and genotypes.

  18. Attribute Perception Mapping Services Domestic Airlines Using Correspondence Analysis

    Directory of Open Access Journals (Sweden)

    Reni Heviandri Riandarini

    2015-04-01

    Full Text Available Positioning analysis provides a better understanding of the position based on the perception of passenger flights to service these attributes attached to each airline. This study aims to perform positioning of the domestic airline services based attributes, which characterize the air-line based on the perception of consumers. Correspondence Analysis (CA is used to determine the positioning of the six commercial airlines in Indonesia. The results of correspondence analysis showed that the airline Garuda, Lion Air, Citilink and Air Asia already has its own characteristics inherent in the minds of consumers, while the two other airlines, namely Batik Air and Sriwijaya Air has not had a special identifier.

  19. Attribute Perception Mapping Services Domestic Airlines Using Correspondence Analysis

    Directory of Open Access Journals (Sweden)

    Reni Heviandri Riandarini

    2015-04-01

    Full Text Available Positioning analysis provides a better understanding of the position based on the perception of passenger flights to service these attributes attached to each airline. This study aims to perform positioning of thedomestic airline services based attributes, which characterize the air line based on the perception of consumers. Correspondence Analysis (CA is used to determine the positioning of the six commercial airlines in Indonesia. The results of correspondence analysis showed that the airline Garuda, Lion Air, Citilink and Air Asia already has its own characteristics inherent in the minds of consumers, while the two other airlines, namely Batik Air and Sriwijaya Air has not had a special identifier.

  20. Perceptions of Quantitative Methods in Higher Education: Mapping Student Profiles

    Science.gov (United States)

    Ramos, Madalena; Carvalho, Helena

    2011-01-01

    A number of studies have concluded that when students have greater confidence about their math skills and are aware of its usefulness, they have a more positive perception of the subject. This article aims to examine whether this pseudo linear trend in the relationship between affective and instrumental dimensions is also true of the university…

  1. Spatiotemporal brain mapping during preparation, perception, and action.

    Science.gov (United States)

    Di Russo, Francesco; Lucci, Giuliana; Sulpizio, Valentina; Berchicci, Marika; Spinelli, Donatella; Pitzalis, Sabrina; Galati, Gaspare

    2016-02-01

    Deciding whether to act or not to act is a fundamental cognitive function. To avoid incorrect responses, both reactive and proactive modes of control have been postulated. Little is known, however, regarding the brain implementation of proactive mechanisms, which are deployed prior to an actual need to inhibit a response. Via a combination of electrophysiological and neuroimaging measures (recorded in 21 and 16 participants, respectively), we describe the brain localization and timing of neural activity that underlies the anticipatory proactive mechanism. From these results, we conclude that proactive control originates in the inferior Frontal gyrus, is established well before stimulus perception, and is released concomitantly with stimulus appearance. Stimulus perception triggers early activity in the anterior insula and intraparietal cortex contralateral to the responding hand; these areas likely mediate the transition from perception to action. The neural activities leading to the decision to act or not to act are described in the framework of a three-stage model that includes perception, action, and anticipatory functions taking place well before stimulus onset.

  2. Particle Swarm Optimization

    Science.gov (United States)

    Venter, Gerhard; Sobieszczanski-Sobieski Jaroslaw

    2002-01-01

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

  3. PERCEPTION OF THE WORLD: MENTAL MAPS AND SOCIOENVIRONMENTAL PROBLEMS

    Directory of Open Access Journals (Sweden)

    Antonio José Morales Hernández

    Full Text Available INTRODUCTION: People build their world image in relation to stories they hear from family and friends, news that they observe in the mass media... School environment influence is relevant as well, especially from subjects such as Geography, which not only presents facts and data in the world but also a representation of the planet on a map.In this article we provide empirical evidence on the mental construction of the world map by Teacher Training students of Valencia. By this, we want to show the need to work this content on cartographic skills to prevent deformation of the explanation of the planet Earth and its problems.

  4. How Culture Constructs Our Sense of Neighborhood: Mental Maps and Children's Perceptions of Place

    Science.gov (United States)

    Gillespie, Carol Ann

    2010-01-01

    This research examines the effects of culture on a child's perceptions of his or her neighborhood by comparing the neighborhood sketch maps of a group of Amish and non-Amish children from the same rural Pennsylvania neighborhood. The results of this study lend credence to the belief that early and intensive acculturation helps define our sense of…

  5. Swarm Level 2 Comprehensive Inversion, 2016 Production

    DEFF Research Database (Denmark)

    Tøffner-Clausen, Lars; Sabaka, Terence; Olsen, Nils;

    In the framework of the ESA Earth Observation Magnetic Mapping Mission Swarm, the Expert Support Laboratories (ESL) provides high quality Level 2 Products describing a.o. the magnetic fields of the Earth. This poster provides details of the Level 2 Products from the Comprehensive Inversion chain ...

  6. Enhancing comprehensive inversions using the Swarm constellation

    DEFF Research Database (Denmark)

    Sabaka, T.J.; Olsen, Nils

    2006-01-01

    This paper reports on the findings of a simulation study designed to test various satellite configurations suggested for the upcoming Swarm magnetic mapping mission. The test is to see whether the mission objectives of recovering small-scale core secular variation (SV) and lithospheric magnetic s...

  7. The Swarm Magnetometry Package

    DEFF Research Database (Denmark)

    Merayo, José M.G.; Jørgensen, John Leif; Friis-Christensen, Eigil

    2008-01-01

    The Swarm mission under the ESA's Living Planet Programme is planned for launch in 2010 and consists of a constellation of three satellites at LEO. The prime objective of Swarm is to measure the geomagnetic field with unprecedented accuracy in space and time. The magnetometry package consists...

  8. Flows around bacterial swarms

    Science.gov (United States)

    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.

  9. Dolphin swarm algorithm

    Institute of Scientific and Technical Information of China (English)

    Tian-qi WU; Min YAO; Jian-hua YANG

    2016-01-01

    By adopting the distributed problem-solving strategy, swarm intelligence algorithms have been successfully applied to many optimization problems that are difficult to deal with using traditional methods. At present, there are many well-implemented algorithms, such as particle swarm optimization, genetic algorithm, artificial bee colony algorithm, and ant colony optimization. These algorithms have already shown favorable performances. However, with the objects becoming increasingly complex, it is becoming gradually more difficult for these algorithms to meet human’s demand in terms of accuracy and time. Designing a new algorithm to seek better solutions for optimization problems is becoming increasingly essential. Dolphins have many noteworthy biological characteristics and living habits such as echolocation, information exchanges, cooperation, and division of labor. Combining these biological characteristics and living habits with swarm intelligence and bringing them into optimization prob-lems, we propose a brand new algorithm named the ‘dolphin swarm algorithm’ in this paper. We also provide the definitions of the algorithm and specific descriptions of the four pivotal phases in the algorithm, which are the search phase, call phase, reception phase, and predation phase. Ten benchmark functions with different properties are tested using the dolphin swarm algorithm, particle swarm optimization, genetic algorithm, and artificial bee colony algorithm. The convergence rates and benchmark func-tion results of these four algorithms are compared to testify the effect of the dolphin swarm algorithm. The results show that in most cases, the dolphin swarm algorithm performs better. The dolphin swarm algorithm possesses some great features, such as first-slow-then-fast convergence, periodic convergence, local-optimum-free, and no specific demand on benchmark functions. Moreover, the dolphin swarm algorithm is particularly appropriate to optimization problems, with more

  10. Occupancy Grid Mapping Based on DSmT for Dynamic Environment Perception

    Directory of Open Access Journals (Sweden)

    Junjing Zhou

    2013-06-01

    Full Text Available Occupancy grid mapping is an important approach for intelligent vehicle environment perception. In this paper, an occupancy grid mapping approach in Dezert-Smarandache theory (DSmT framework for the purpose of dynamic environment perception is proposed. To avoid the transformation of the local map from polar to Catersian coordinate, a different inverse sensor model in Cartesian coordinate for laser scanner was proposed. Two different combination rules in DSmT framework, Dempster’s rule of combination and PCR2, are implemented independently for global map update and mobile object detection. The performance of the two combination rules were compared by ways of simulation and experiment. According to the comparisons we find that both of the combination rules are capable of detecting mobile objects. And the former effectively filtered out the noise and make the detection robust, but the latter didn’t, suggesting that the former is more suitable for occupancy grid mapping. Static and mobile objects are extracted from the occupancy grid map using digital image processing technology.

  11. From hybrid swarms to swarms of hybrids

    Science.gov (United States)

    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...

  12. MAGNAS - Magnetic Nanoprobe SWARM

    DEFF Research Database (Denmark)

    Lubberstedt, H.; Koebel, D.; Hansen, Flemming;

    2005-01-01

    This paper presents the Magnetic Nano-Probe Swarm mission utilising a constellation of several swarms of nano-satellites in order to acquire simultaneous measurements of the geomagnetic field resolving the local field gradients. The space segment comprises of up to 4 S/C swarms each consisting...... of up to 6 nano-satellites (Nano-Probes) and 1 mother spacecraft (MSC) to be launched with a single launcher in polar low Earth orbits. The Nano-Probes. equipped with magnetometer payloads operate in the vicinity of the MSCs. The MSCs will eject the NPs after acquisition of the initial orbits. provide...

  13. Adaptive cockroach swarm algorithm

    Science.gov (United States)

    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.

  14. Mapping Muscles Activation to Force Perception during Unloading.

    Directory of Open Access Journals (Sweden)

    Simone Toma

    Full Text Available It has been largely proved that while judging a force humans mainly rely on the motor commands produced to interact with that force (i.e., sense of effort. Despite of a large bulk of previous investigations interested in understanding the contributions of the descending and ascending signals in force perception, very few attempts have been made to link a measure of neural output (i.e., EMG to the psychophysical performance. Indeed, the amount of correlation between EMG activity and perceptual decisions can be interpreted as an estimate of the contribution of central signals involved in the sensation of force. In this study we investigated this correlation by measuring the muscular activity of eight arm muscles while participants performed a quasi-isometric force detection task. Here we showed a method to quantitatively describe muscular activity ("muscle-metric function" that was directly comparable to the description of the participants' psychophysical decisions about the stimulus force. We observed that under our experimental conditions, muscle-metric absolute thresholds and the shape of the muscle-metric curves were closely related to those provided by the psychophysics. In fact a global measure of the muscles considered was able to predict approximately 60% of the perceptual decisions total variance. Moreover the inter-subjects differences in psychophysical sensitivity showed high correlation with both participants' muscles sensitivity and participants' joint torques. Overall, our findings gave insights into both the role played by the corticospinal motor commands while performing a force detection task and the influence of the gravitational muscular torque on the estimation of vertical forces.

  15. Using concept maps to explore preservice teachers' perceptions of science content knowledge, teaching practices, and reflective processes

    Science.gov (United States)

    Somers, Judy L.

    This qualitative study examined seven preservice teachers' perceptions of their science content knowledge, teaching practices, and reflective processes through the use of the metacognitive strategy of concept maps. Included in the paper is a review of literature in the areas of preservice teachers' perceptions of teaching, concept development, concept mapping, science content understanding, and reflective process as a part of metacognition. The key questions addressed include the use of concept maps to indicate organization and understanding of science content, mapping strategies to indicate perceptions of teaching practice, and the influence of concept maps on reflective process. There is also a comparison of preservice teachers' perceptions of concept map usage with the purposes and practices of maps as described by experienced teachers. Data were collected primarily through interviews, observations, a pre and post concept mapping activity, and an analysis of those concept maps using a rubric developed for this study. Findings showed that concept map usage clarified students' understanding of the organization and relationships within content area and that the process of creating the concept maps increased participants' understanding of the selected content. The participants felt that the visual element of concept mapping was an important factor in improving content understanding. These participants saw benefit in using concept maps as planning tools and as instructional tools. They did not recognize the use of concept maps as assessment tools. When the participants were able to find personal relevance in and through their concept maps they were better able to be reflective about the process. The experienced teachers discussed student understanding and skill development as the primary purpose of concept map usage, while they were able to use concept maps to accomplish multiple purposes in practice.

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

    DEFF Research Database (Denmark)

    Bothe, Hans-Heinrich

    The goal of this work is to find a way to measure similarity of audiovisual speech percepts. Phoneme-related self-organizing maps (SOM) with a rectangular basis are trained with data material from a (labeled) video film. For the training, a combination of auditory speech features and corresponding...... sentences in German with a balanced phoneme repertoire. As a result it can be stated that (i) the SOM can be trained to map auditory and visual features in a topology-preserving way and (ii) they show strain due to the influence of other audio-visual units. The SOM can be used to measure similarity amongst...... audio-visual speech percepts and to measure coarticulatory effects....

  17. Longitude perception and bicoordinate magnetic maps in sea turtles.

    Science.gov (United States)

    Putman, Nathan F; Endres, Courtney S; Lohmann, Catherine M F; Lohmann, Kenneth J

    2011-03-22

    Long-distance animal migrants often navigate in ways that imply an awareness of both latitude and longitude. Although several species are known to use magnetic cues as a surrogate for latitude, it is not known how any animal perceives longitude. Magnetic parameters appear to be unpromising as longitudinal markers because they typically vary more in a north-south rather than an east-west direction. Here we report, however, that hatchling loggerhead sea turtles (Caretta caretta) from Florida, USA, when exposed to magnetic fields that exist at two locations with the same latitude but on opposite sides of the Atlantic Ocean, responded by swimming in different directions that would, in each case, help them advance along their circular migratory route. The results demonstrate for the first time that longitude can be encoded into the magnetic positioning system of a migratory animal. Because turtles also assess north-south position magnetically, the findings imply that loggerheads have a navigational system that exploits the Earth's magnetic field as a kind of bicoordinate magnetic map from which both longitudinal and latitudinal information can be extracted. Copyright © 2011 Elsevier Ltd. All rights reserved.

  18. Mapping the sensory perception of apple using descriptive sensory evaluation in a genome wide association study

    OpenAIRE

    Amyotte, Beatrice; Bowen, Amy J.; Banks, Travis; Rajcan, Istvan; Somers, Daryl J.

    2017-01-01

    Breeding apples is a long-term endeavour and it is imperative that new cultivars are selected to have outstanding consumer appeal. This study has taken the approach of merging sensory science with genome wide association analyses in order to map the human perception of apple flavour and texture onto the apple genome. The goal was to identify genomic associations that could be used in breeding apples for improved fruit quality. A collection of 85 apple cultivars was examined over two years thr...

  19. Mapping the Speech Code: Cortical Responses Linking the Perception and Production of Vowels.

    Science.gov (United States)

    Schuerman, William L; Meyer, Antje S; McQueen, James M

    2017-01-01

    The acoustic realization of speech is constrained by the physical mechanisms by which it is produced. Yet for speech perception, the degree to which listeners utilize experience derived from speech production has long been debated. In the present study, we examined how sensorimotor adaptation during production may affect perception, and how this relationship may be reflected in early vs. late electrophysiological responses. Participants first performed a baseline speech production task, followed by a vowel categorization task during which EEG responses were recorded. In a subsequent speech production task, half the participants received shifted auditory feedback, leading most to alter their articulations. This was followed by a second, post-training vowel categorization task. We compared changes in vowel production to both behavioral and electrophysiological changes in vowel perception. No differences in phonetic categorization were observed between groups receiving altered or unaltered feedback. However, exploratory analyses revealed correlations between vocal motor behavior and phonetic categorization. EEG analyses revealed correlations between vocal motor behavior and cortical responses in both early and late time windows. These results suggest that participants' recent production behavior influenced subsequent vowel perception. We suggest that the change in perception can be best characterized as a mapping of acoustics onto articulation.

  20. Students' perception of a modified form of PBL using concept mapping.

    Science.gov (United States)

    Addae, Jonas Innies; Wilson, Jacqueline I; Carrington, Christine

    2012-01-01

    Problem-based learning (PBL) and concept mapping have been shown to promote active and meaningful learning. To design a method of PBL that includes concept mapping and examine students' perceptions of this form of PBL. We designed a 5-phase method of PBL which produced three clearly identifiable mapping phases that reflected the learning activities during the tutorial: (1) the initial understanding of the clinical problem, (2) students' prior knowledge of the problem, (3) the final understanding of the problem following self-directed study. The process of developing the second and third phases of the map involved the students answering questions that they generated on two occasions to give the entire process a 5-phase approach. Each student was exposed to both methods of PBL: a conventional 7-step method (Maastricht type) and the modified PBL (5-phase) method. We used a questionnaire to evaluate the students' perceptions of the two methods in four learning domains. The students' ratings for the 5-phase method were significantly higher than for the 7-step method (paired t-test) on all items on the questionnaire. The students perceived the 5-phase method as promoting their passion for learning, and developing their cognitive, metacognitive and interpersonal skills.

  1. The perception of quality mapping product and service quality to consumer perceptions

    CERN Document Server

    Kenyon, George N

    2015-01-01

    Exploring the concept of quality management from a new point of view, this book presents a holistic model of how consumers judge the quality of products. It links consumer perceptions of quality to the design and delivery of the final product, and presents models and methods for improving the quality of these products and services. It offers readers an improved understanding of how and why the design process must consider how the consumer will perceive a product or service. In order to facilitate the presentation and understanding of these concepts, illustrations and case examples are also provided throughout the book.   This book provides an invaluable resource for managers, designers, manufacturers, professional practitioners and academics interested in quality management. It also offers a useful supplementary text for marketing and quality management courses.

  2. A tone mapping operator based on neural and psychophysical models of visual perception

    Science.gov (United States)

    Cyriac, Praveen; Bertalmio, Marcelo; Kane, David; Vazquez-Corral, Javier

    2015-03-01

    High dynamic range imaging techniques involve capturing and storing real world radiance values that span many orders of magnitude. However, common display devices can usually reproduce intensity ranges only up to two to three orders of magnitude. Therefore, in order to display a high dynamic range image on a low dynamic range screen, the dynamic range of the image needs to be compressed without losing details or introducing artefacts, and this process is called tone mapping. A good tone mapping operator must be able to produce a low dynamic range image that matches as much as possible the perception of the real world scene. We propose a two stage tone mapping approach, in which the first stage is a global method for range compression based on a gamma curve that equalizes the lightness histogram the best, and the second stage performs local contrast enhancement and color induction using neural activity models for the visual cortex.

  3. 引入Logistic混沌映射的连续蟑螂算法应用于函数优化问题%Continuous Cockroach Swarm Optimization with Logistic Chaotic Map for Solving Function Optimization Problems

    Institute of Scientific and Technical Information of China (English)

    程乐; 杨晔; 钱兆楼; 韩锐; 潘永安

    2011-01-01

    For solving function optimization problems ,a new continuous cockroach swarm optimization(CCSO)is put forward in this paper. Some biological characteristics of cockroach has been simulated ,such as gregarious colony, non-fixing nest , disorderly craw-ling path and so on. The argorithm have truck throwing food in solution space. The cockroaches could crawl to these food and search for optimal solutions. Logistic chaotic map is used in nest distribution and throwing food. The experimental results show that CCSO is surpior to API and PPBO in Solving Precision,convergent rates and optimization rate.%通过模拟蟑螂的觅食行为,提出用于解决函数优化问题的连续蟑螂算法(continuous cockroach swarm optimization,CC-SO).算法模拟了蟑螂的群居、巢穴不固定、爬行轨迹杂乱无章等生物特性.通过食物车在解空间内抛洒食物,吸引蟑螂向食物爬行完成搜索.在巢穴分配和食物抛洒环节引入了Logistic混沌映射,增强了巢穴和食物在解空间内分布的随机性和遍历性.仿真实验显示,与API和PPBO算法相比,CCSO算法在求解精度、收敛速度、寻优率等方面均提高显著.

  4. Determinants and mapping of collective perceptions of technological risk: the case of the second nuclear power plant in Taiwan.

    Science.gov (United States)

    Hung, Hung-Chih; Wang, Tzu-Wen

    2011-04-01

    Nuclear power is a highly controversial and salient example of environmental risk. The siting or operating of a nuclear power plant often faces widespread public opposition. Although studies of public perceptions of nuclear power date back to 1970s, little research attempts to explain the spatial heterogeneity of risk attitude toward nuclear power among individuals or communities. This article intends to improve the knowledge about the major factors contributing to nuclear power plant risk perceptions by mapping the geographical patterns of local risk perception and examining the determinants in forming the nature and distribution of the perceived risk among potentially affected population. The analysis was conducted by a case study of the Second Nuclear Power Plant (SNPP) in Taiwan by using a novel methodology that incorporates a comprehensive risk perception (CRP) model into an ethnographic approach called risk perception mapping (RPM). First, we examined the determinants of local nuclear power risk perceptions through the CRP model and multivariate regression analysis. Second, the results were integrated with the RPM approach to map and explain the spatial pattern of risk perceptions. The findings demonstrate that the respondents regard the nuclear power plant as an extremely high-risk facility, causing them to oppose the SNPP and reject the compensation payment to accept its continuing operation. Results also indicate that perceptions of nuclear power risk were mainly influenced by social trust, psychological and socioeconomic attributes, proximity, and the perceived effects of the SNPP on the quality of everyday life.

  5. Swarm-based medicine.

    Science.gov (United States)

    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.

  6. Mapping perception to action in piano practice: a longitudinal DC-EEG study

    Directory of Open Access Journals (Sweden)

    Bangert Marc

    2003-10-01

    Full Text Available Abstract Background Performing music requires fast auditory and motor processing. Regarding professional musicians, recent brain imaging studies have demonstrated that auditory stimulation produces a co-activation of motor areas, whereas silent tapping of musical phrases evokes a co-activation in auditory regions. Whether this is obtained via a specific cerebral relay station is unclear. Furthermore, the time course of plasticity has not yet been addressed. Results Changes in cortical activation patterns (DC-EEG potentials induced by short (20 minute and long term (5 week piano learning were investigated during auditory and motoric tasks. Two beginner groups were trained. The 'map' group was allowed to learn the standard piano key-to-pitch map. For the 'no-map' group, random assignment of keys to tones prevented such a map. Auditory-sensorimotor EEG co-activity occurred within only 20 minutes. The effect was enhanced after 5-week training, contributing elements of both perception and action to the mental representation of the instrument. The 'map' group demonstrated significant additional activity of right anterior regions. Conclusion We conclude that musical training triggers instant plasticity in the cortex, and that right-hemispheric anterior areas provide an audio-motor interface for the mental representation of the keyboard.

  7. Turbulence of swarming sperm

    Science.gov (United States)

    Creppy, Adama; Praud, Olivier; Druart, Xavier; Kohnke, Philippa L.; Plouraboué, Franck

    2015-09-01

    Collective motion of self-sustained swarming flows has recently provided examples of small-scale turbulence arising where viscous effects are dominant. We report the first observation of universal enstrophy cascade in concentrated swarming sperm consistent with a body of evidence built from various independent measurements. We found a well-defined k-3 power-law decay of a velocity field power spectrum and relative dispersion of small beads consistent with theoretical predictions in 2D turbulence. Concentrated living sperm displays long-range, correlated whirlpool structures of a size that provides an integral scale of turbulence. We propose a consistent explanation for this quasi-2D turbulence based on self-structured laminated flow forced by steric interactions and alignment, a state of active matter that we call "swarming liquid crystal." We develop scaling arguments consistent with this interpretation.

  8. Swarming: flexible roaming plans.

    Science.gov (United States)

    Partridge, Jonathan D; Harshey, Rasika M

    2013-03-01

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

  9. Particle Swarm Optimization Toolbox

    Science.gov (United States)

    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

  10. Corruption Cases Mapping Based on Indonesia’s Corruption Perception Index

    Science.gov (United States)

    Noerlina; Wulandhari, L. A.; Sasmoko; Muqsith, A. M.; Alamsyah, M.

    2017-01-01

    Government plays an important role in nation economic growth. Nevertheless, there are still many occurrences of government officers abusing their offices to do an act of corruption. In this order, the central government should pay attention to every area in the nation to avoid corruption case. Meanwhile, the news media always constantly preach about corruption case, this makes the news media relevant for being one of the sources of measurement of corruption perception index (CPI). It is required to map the corruption case in Indonesia so the central government can pay attention to every region in Indonesia. To develop the mapping system, researchers use Naïve Bayes Classifier to classify which news articles talk about corruption and which news articles are not, before implementing a Naïve Bayes Classifier there are some text processing such as tokenizing, stopping, and stemming.

  11. A Novel Distributed Quantum-Behaved Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Yangyang Li

    2017-01-01

    Full Text Available Quantum-behaved particle swarm optimization (QPSO is an improved version of particle swarm optimization (PSO and has shown superior performance on many optimization problems. But for now, it may not always satisfy the situations. Nowadays, problems become larger and more complex, and most serial optimization algorithms cannot deal with the problem or need plenty of computing cost. Fortunately, as an effective model in dealing with problems with big data which need huge computation, MapReduce has been widely used in many areas. In this paper, we implement QPSO on MapReduce model and propose MapReduce quantum-behaved particle swarm optimization (MRQPSO which achieves parallel and distributed QPSO. Comparisons are made between MRQPSO and QPSO on some test problems and nonlinear equation systems. The results show that MRQPSO could complete computing task with less time. Meanwhile, from the view of optimization performance, MRQPSO outperforms QPSO in many cases.

  12. The use and perceptions of concept mapping as a learning tool by dietetic internship students and preceptors.

    Science.gov (United States)

    Molaison, Elaine Fontenot; Taylor, Kimberly A; Erickson, Dawn; Connell, Carol Lawson

    2009-01-01

    Critical thinking and problem solving skills are currently emphasis areas in the education of allied health professionals. Use of concept maps to teach these skills have been utilized primarily in nursing and medical education, but little has been published about their use in dietetics education. Therefore the purpose of this study was to evaluate the potential efficacy of concept mapping as a learning tool for nutrition assessment among dietetic interns and its acceptability by internship preceptors. Nineteen dietetic interns and 31 preceptors participated in a quasi-experimental pre-/post-design in which the concept mapping strategy was taught as a replacement for the traditional nutrition care plan. The pre-concept map mean score was significantly lower than the post-concept mean score (28.35 vs. 117.96; p=0.001) based on the Student t-test, thus indicating improved critical thinking skills as evidenced through concept mapping. Overall students' perceptions of concept mapping as a teaching-learning method were more positive than the preceptors' perceptions. In conclusion, internship preceptors and dietetic interns perceived concept mapping as effective in assisting interns to engage in critical thinking, to problem solve, and understand relationships among medical nutrition therapy concepts. However, preceptors had more negative attitudes toward concept mapping than the dietetic interns related to time and effort to complete and evaluate the concept map.

  13. Glowworm swarm optimization theory, algorithms, and applications

    CERN Document Server

    Kaipa, Krishnanand N

    2017-01-01

    This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate students in the area of swarm intelligence and computational intellige...

  14. Momentum particle swarm optimizer

    Institute of Scientific and Technical Information of China (English)

    Liu Yu; Qin Zheng; Wang Xianghua; He Xingshi

    2005-01-01

    The previous particle swarm optimizers lack direct mechanism to prevent particles beyond predefined search space, which results in invalid solutions in some special cases. A momentum factor is introduced into the original particle swarm optimizer to resolve this problem. Furthermore, in order to accelerate convergence, a new strategy about updating velocities is given. The resulting approach is mromentum-PSO which guarantees that particles are never beyond predefined search space without checking boundary in every iteration. In addition, linearly decreasing wight PSO (LDW-PSO) equipped with a boundary checking strategy is also discussed, which is denoted as LDWBC-PSO. LDW-PSO, LDWBC-PSO and momentum-PSO are compared in optimization on five test functions. The experimental results show that in some special cases LDW-PSO finds invalid solutions and LDWBC-PSO has poor performance, while momentum-PSO not only exhibits good performance but also reduces computational cost for updating velocities.

  15. Perception-action map learning in controlled multiscroll systems applied to robot navigation.

    Science.gov (United States)

    Arena, Paolo; De Fiore, Sebastiano; Fortuna, Luigi; Patané, Luca

    2008-12-01

    In this paper a new technique for action-oriented perception in robots is presented. The paper starts from exploiting the successful implementation of the basic idea that perceptual states can be embedded into chaotic attractors whose dynamical evolution can be associated with sensorial stimuli. In this way, it can be possible to encode, into the chaotic dynamics, environment-dependent patterns. These have to be suitably linked to an action, executed by the robot, to fulfill an assigned mission. This task is addressed here: the action-oriented perception loop is closed by introducing a simple unsupervised learning stage, implemented via a bio-inspired structure based on the motor map paradigm. In this way, perceptual meanings, useful for solving a given task, can be autonomously learned, based on the environment-dependent patterns embedded into the controlled chaotic dynamics. The presented framework has been tested on a simulated robot and the performance have been successfully compared with other traditional navigation control paradigms. Moreover an implementation of the proposed architecture on a Field Programmable Gate Array is briefly outlined and preliminary experimental results on a roving robot are also reported.

  16. Perception-action map learning in controlled multiscroll systems applied to robot navigation

    Science.gov (United States)

    Arena, Paolo; De Fiore, Sebastiano; Fortuna, Luigi; Patané, Luca

    2008-12-01

    In this paper a new technique for action-oriented perception in robots is presented. The paper starts from exploiting the successful implementation of the basic idea that perceptual states can be embedded into chaotic attractors whose dynamical evolution can be associated with sensorial stimuli. In this way, it can be possible to encode, into the chaotic dynamics, environment-dependent patterns. These have to be suitably linked to an action, executed by the robot, to fulfill an assigned mission. This task is addressed here: the action-oriented perception loop is closed by introducing a simple unsupervised learning stage, implemented via a bio-inspired structure based on the motor map paradigm. In this way, perceptual meanings, useful for solving a given task, can be autonomously learned, based on the environment-dependent patterns embedded into the controlled chaotic dynamics. The presented framework has been tested on a simulated robot and the performance have been successfully compared with other traditional navigation control paradigms. Moreover an implementation of the proposed architecture on a Field Programmable Gate Array is briefly outlined and preliminary experimental results on a roving robot are also reported.

  17. Perceptions of Pre-Service Social Sciences Teachers Regarding the Concept of "Geography" by Mind Mapping Technique

    Science.gov (United States)

    Ozturk Demirbas, Cagri

    2013-01-01

    The objective of this study is to present the perceptions of preservice social sciences teachers regarding the concept of geography. In the study, the study group consists of 46 preservice social sciences teachers, who receive education at Ahi Evran University. The data were collected in December, 2010. Mind maps were used as data collection tools…

  18. Perceptions of Pre-Service Social Sciences Teachers Regarding the Concept of "Geography" by Mind Mapping Technique

    Science.gov (United States)

    Ozturk Demirbas, Cagri

    2013-01-01

    The objective of this study is to present the perceptions of preservice social sciences teachers regarding the concept of geography. In the study, the study group consists of 46 preservice social sciences teachers, who receive education at Ahi Evran University. The data were collected in December, 2010. Mind maps were used as data collection tools…

  19. Features of Bacillus cereus swarm cells.

    Science.gov (United States)

    Senesi, Sonia; Salvetti, Sara; Celandroni, Francesco; Ghelardi, Emilia

    2010-11-01

    When propagated on solid surfaces, Bacillus cereus can produce differentiated swarm cells under a wide range of growth conditions. This behavioural versatility is ecologically relevant, since it allows this bacterium to adapt swarming to environmental changes. Swarming by B. cereus is medically important: swarm cells are more virulent and particularly prone to invade host tissues. Characterisation of swarming-deficient mutants highlights that flagellar genes as well as genes governing different metabolic pathways are involved in swarm-cell differentiation. In this review, the environmental and genetic requirements for swarming and the role played by swarm cells in the virulence this pathogen exerts will be outlined.

  20. Earthquake swarms in South America

    Science.gov (United States)

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

    2011-10-01

    We searched for earthquake swarms in South America between 1973 and 2009 using the global Preliminary Determination of Epicenters (PDE) catalogue. Seismicity rates vary greatly over the South American continent, so we employ a manual search approach that aims to be insensitive to spatial and temporal scales or to the number of earthquakes in a potential swarm. We identify 29 possible swarms involving 5-180 earthquakes each (with total swarm moment magnitudes between 4.7 and 6.9) within a range of tectonic and volcanic locations. Some of the earthquake swarms on the subduction megathrust occur as foreshocks and delineate the limits of main shock rupture propagation for large earthquakes, including the 2010 Mw 8.8 Maule, Chile and 2007 Mw 8.1 Pisco, Peru earthquakes. Also, subduction megathrust swarms commonly occur at the location of subduction of aseismic ridges, including areas of long-standing seismic gaps in Peru and Ecuador. The magnitude-frequency relationship of swarms we observe appears to agree with previously determined magnitude-frequency scaling for swarms in Japan. We examine geodetic data covering five of the swarms to search for an aseismic component. Only two of these swarms (at Copiapó, Chile, in 2006 and near Ticsani Volcano, Peru, in 2005) have suitable satellite-based Interferometric Synthetic Aperture Radar (InSAR) observations. We invert the InSAR geodetic signal and find that the ground deformation associated with these swarms does not require a significant component of aseismic fault slip or magmatic intrusion. Three swarms in the vicinity of the volcanic arc in southern Peru appear to be triggered by the Mw= 8.5 2001 Peru earthquake, but predicted static Coulomb stress changes due to the main shock were very small at the swarm locations, suggesting that dynamic triggering processes may have had a role in their occurrence. Although we identified few swarms in volcanic regions, we suggest that particularly large volcanic swarms (those that

  1. Mapping the sensory perception of apple using descriptive sensory evaluation in a genome wide association study.

    Science.gov (United States)

    Amyotte, Beatrice; Bowen, Amy J; Banks, Travis; Rajcan, Istvan; Somers, Daryl J

    2017-01-01

    Breeding apples is a long-term endeavour and it is imperative that new cultivars are selected to have outstanding consumer appeal. This study has taken the approach of merging sensory science with genome wide association analyses in order to map the human perception of apple flavour and texture onto the apple genome. The goal was to identify genomic associations that could be used in breeding apples for improved fruit quality. A collection of 85 apple cultivars was examined over two years through descriptive sensory evaluation by a trained sensory panel. The trained sensory panel scored randomized sliced samples of each apple cultivar for seventeen taste, flavour and texture attributes using controlled sensory evaluation practices. In addition, the apple collection was subjected to genotyping by sequencing for marker discovery. A genome wide association analysis suggested significant genomic associations for several sensory traits including juiciness, crispness, mealiness and fresh green apple flavour. The findings include previously unreported genomic regions that could be used in apple breeding and suggest that similar sensory association mapping methods could be applied in other plants.

  2. Swarm Science objectives and challenges

    DEFF Research Database (Denmark)

    Friis-Christensen, Eigil; Lühr, Hermann; Hulot, Gauthier

    Swarm is the fifth Earth Explorer mission in ESA’s Living Planet Programme to be launched in 2009. The objective of the Swarm mission is to provide the best ever survey of the geomagnetic field and its temporal evolution. The innovative constellation concept and a unique set of dedicated instrume...

  3. Components of Swarm Intelligence

    Energy Technology Data Exchange (ETDEWEB)

    David Bruemmer; Donald Dudenhoeffer; Matthew Anderson; Mark McKay

    2004-03-01

    This paper discusses the successes and failures over the past three years as efforts at the Idaho National Engineering and Environmental Laboratory (INEEL) have developed and evaluated robot behaviors that promote the emergence of swarm intelligence. Using a team of 12 small robots with the ability to respond to light and sound, the INEEL has investigated the fundamental advantages of swarm behavior as well as the limitations of this approach. The paper discusses the ways in which biology has inspired this work and the ways in which adherence to the biological model has proven to be both a benefit and hindrance to developing a fieldable system. The paper outlines how a hierarchical command and control structure can be imposed in order to permit human control at a level of group abstraction and discusses experimental results that show how group performance scales as different numbers of robots are utilized. Lastly, the paper outlines the applications for which the resulting capabilities have been applied and demonstrated.

  4. The Influence of Tactile Cognitive Maps on Auditory Space Perception in Sighted Persons.

    Science.gov (United States)

    Tonelli, Alessia; Gori, Monica; Brayda, Luca

    2016-01-01

    We have recently shown that vision is important to improve spatial auditory cognition. In this study, we investigate whether touch is as effective as vision to create a cognitive map of a soundscape. In particular, we tested whether the creation of a mental representation of a room, obtained through tactile exploration of a 3D model, can influence the perception of a complex auditory task in sighted people. We tested two groups of blindfolded sighted people - one experimental and one control group - in an auditory space bisection task. In the first group, the bisection task was performed three times: specifically, the participants explored with their hands the 3D tactile model of the room and were led along the perimeter of the room between the first and the second execution of the space bisection. Then, they were allowed to remove the blindfold for a few minutes and look at the room between the second and third execution of the space bisection. Instead, the control group repeated for two consecutive times the space bisection task without performing any environmental exploration in between. Considering the first execution as a baseline, we found an improvement in the precision after the tactile exploration of the 3D model. Interestingly, no additional gain was obtained when room observation followed the tactile exploration, suggesting that no additional gain was obtained by vision cues after spatial tactile cues were internalized. No improvement was found between the first and the second execution of the space bisection without environmental exploration in the control group, suggesting that the improvement was not due to task learning. Our results show that tactile information modulates the precision of an ongoing space auditory task as well as visual information. This suggests that cognitive maps elicited by touch may participate in cross-modal calibration and supra-modal representations of space that increase implicit knowledge about sound propagation.

  5. The influence of tactile cognitive maps on auditory space perception in sighted persons.

    Directory of Open Access Journals (Sweden)

    Alessia Tonelli

    2016-11-01

    Full Text Available We have recently shown that vision is important to improve spatial auditory cognition. In this study we investigate whether touch is as effective as vision to create a cognitive map of a soundscape. In particular we tested whether the creation of a mental representation of a room, obtained through tactile exploration of a 3D model, can influence the perception of a complex auditory task in sighted people. We tested two groups of blindfolded sighted people – one experimental and one control group – in an auditory space bisection task. In the first group the bisection task was performed three times: specifically, the participants explored with their hands the 3D tactile model of the room and were led along the perimeter of the room between the first and the second execution of the space bisection. Then, they were allowed to remove the blindfold for a few minutes and look at the room between the second and third execution of the space bisection. Instead, the control group repeated for two consecutive times the space bisection task without performing any environmental exploration in between. Considering the first execution as a baseline, we found an improvement in the precision after the tactile exploration of the 3D model. Interestingly, no additional gain was obtained when room observation followed the tactile exploration, suggesting that no additional gain was obtained by vision cues after spatial tactile cues were internalized. No improvement was found between the first and the second execution of the space bisection without environmental exploration in the control group, suggesting that the improvement was not due to task learning. Our results show that tactile information modulates the precision of an ongoing space auditory task as well as visual information. This suggests that cognitive maps elicited by touch may participate in cross-modal calibration and supra-modal representations of space that increase implicit knowledge about sound

  6. Tectonic setting of the Wooded Island earthquake swarm, eastern Washington

    Science.gov (United States)

    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 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.

  7. Multi-Target Tracking for Swarm vs. Swarm UAV Systems

    Science.gov (United States)

    2012-09-01

    models. UAV, Unmanned systems, Swarm vs. Swarm systems, Agent-based simulations, Common Operational Picture, K-means clustering, L-method, Polynomial ...An example graph for polynomial fit. It should be noted that the graph consists of log(x) and y parameters of the data in Section 3.3.1.1. . . . 33...near-optimal solution with low overhead and low communication. In order to re- duce the power consumption, the notion of sleep and wake periods for

  8. CityAir app: Mapping air-quality perception using people as sensors

    Science.gov (United States)

    Castell, Nuria; Fredriksen, Mirjam; Cole-Hunter, Thomas; Robinson, Johanna; Keune, Hans; Nieuwenhuijsen, Mark; Bartonova, Alena

    2016-04-01

    Outdoor air pollution is a major environmental health problem affecting all people in developed and developing countries alike. Ambient (outdoor) air pollution in both cities and rural areas was estimated to cause 3.7 million premature deaths worldwide in 2012. In modern society, people are expending an increasing amount of time in polluted urban environments, thus increasing their exposure and associated health responses. Some cities provide information about air pollution levels to their citizens using air quality monitoring networks. However, due to their high cost and maintenance, the density of the monitoring networks is very low and not capable to capture the high temporal and spatial variability of air pollution. Thus, the citizen lacks a specific answer to the question of "how the air quality is in our surroundings". In the framework of the EU-funded CITI-SENSE project the innovative concept of People as Sensors is being applied to the field of outdoor air pollution. This is being done in eight European cities, including Barcelona, Belgrade, Edinburgh, Haifa, Ljubljana, Oslo, Ostrava and Vienna. People as Sensors defines a measurement model, in which measurements are not only taken by hardware sensors, but in which also humans can contribute with their individual "measurements" such as their subjective perception of air quality and other personal observations. In order to collect the personal observations a mobile app, CityAir, has been developed. CityAir allows citizens to rate the air quality in their surroundings with colour at their current location: green if air quality is very good, yellow if air quality is good, orange if air quality is poor and red if air quality is very poor. The users have also the possibility of indicating the source of pollution (i.e. traffic, industry, wood burning) and writing a comment. The information is on-line and accessible for other app users, thus contributing to create an air-quality map based on citizens' perception

  9. Quantum Behaved Particle Swarm Optimization Algorithm Based on Artificial Fish Swarm

    OpenAIRE

    Dong Yumin; Zhao Li

    2014-01-01

    Quantum behaved particle swarm algorithm is a new intelligent optimization algorithm; the algorithm has less parameters and is easily implemented. In view of the existing quantum behaved particle swarm optimization algorithm for the premature convergence problem, put forward a quantum particle swarm optimization algorithm based on artificial fish swarm. The new algorithm based on quantum behaved particle swarm algorithm, introducing the swarm and following activities, meanwhile using the a...

  10. Swarm Science objectives and challenges

    DEFF Research Database (Denmark)

    Friis-Christensen, Eigil; Lühr, Hermann; Hulot, Gauthier

    Swarm is the fifth Earth Explorer mission in ESA’s Living Planet Programme to be launched in 2009. The objective of the Swarm mission is to provide the best ever survey of the geomagnetic field and its temporal evolution. The innovative constellation concept and a unique set of dedicated instrume......Swarm is the fifth Earth Explorer mission in ESA’s Living Planet Programme to be launched in 2009. The objective of the Swarm mission is to provide the best ever survey of the geomagnetic field and its temporal evolution. The innovative constellation concept and a unique set of dedicated...... instruments will provide the necessary observations that are required to separate and model the various sources of the geomagnetic field. This will provide new insights into the Earth system by improving our understanding of the Earth’s interior and Sun-Earth connection processes....

  11. An Extended Particle Swarm Optimizer

    Institute of Scientific and Technical Information of China (English)

    XU Jun-jie; XIN Zhan-hong

    2005-01-01

    An Extended Particle Swarm Optimizer (EPSO) is proposed in this paper. In this new algorithm, not only the local but also the global best position will impact the particle's velocity updating process. EPSO is an integration of Local Best paradigm (LBEST) and Global Best paradigm (GBEST) and it significantly enhances the performance of the conventional particle swarm optimizers. The experiment results have proved that EPSO deserves to be investigated.

  12. Flagellar flows around bacterial swarms

    Science.gov (United States)

    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.

  13. Self-organized motion in anisotropic swarms

    Institute of Scientific and Technical Information of China (English)

    Tianguang CHU; Long WANG; Tongwen CHEN

    2003-01-01

    This paper considers an anisotropic swarm model with a class of attraction and repulsion functions. It is shown that the members of the swarm will aggregate and eventually form a cohesive cluster of finite size around the swarm center. Moreover,It is also proved that under certain conditions, the swarm system can be completely stable, i. e., every solution converges to the equilibrium points of the system. The model and results of this paper extend a recent work on isotropic swarms to more general cases and provide further insight into the effect of the interaction pattern on self-organized motion in a swarm system.

  14. Collective Behaviour without Collective Order in Wild Swarms of Midges

    Science.gov (United States)

    Attanasi, Alessandro; Cavagna, Andrea; Del Castello, Lorenzo; Giardina, Irene; Melillo, Stefania; Parisi, Leonardo; Pohl, Oliver; Rossaro, Bruno; Shen, Edward; Silvestri, Edmondo; Viale, Massimiliano

    2014-01-01

    Collective behaviour is a widespread phenomenon in biology, cutting through a huge span of scales, from cell colonies up to bird flocks and fish schools. The most prominent trait of collective behaviour is the emergence of global order: individuals synchronize their states, giving the stunning impression that the group behaves as one. In many biological systems, though, it is unclear whether global order is present. A paradigmatic case is that of insect swarms, whose erratic movements seem to suggest that group formation is a mere epiphenomenon of the independent interaction of each individual with an external landmark. In these cases, whether or not the group behaves truly collectively is debated. Here, we experimentally study swarms of midges in the field and measure how much the change of direction of one midge affects that of other individuals. We discover that, despite the lack of collective order, swarms display very strong correlations, totally incompatible with models of non-interacting particles. We find that correlation increases sharply with the swarm's density, indicating that the interaction between midges is based on a metric perception mechanism. By means of numerical simulations we demonstrate that such growing correlation is typical of a system close to an ordering transition. Our findings suggest that correlation, rather than order, is the true hallmark of collective behaviour in biological systems. PMID:25057853

  15. Collective behaviour without collective order in wild swarms of midges.

    Directory of Open Access Journals (Sweden)

    Alessandro Attanasi

    2014-07-01

    Full Text Available Collective behaviour is a widespread phenomenon in biology, cutting through a huge span of scales, from cell colonies up to bird flocks and fish schools. The most prominent trait of collective behaviour is the emergence of global order: individuals synchronize their states, giving the stunning impression that the group behaves as one. In many biological systems, though, it is unclear whether global order is present. A paradigmatic case is that of insect swarms, whose erratic movements seem to suggest that group formation is a mere epiphenomenon of the independent interaction of each individual with an external landmark. In these cases, whether or not the group behaves truly collectively is debated. Here, we experimentally study swarms of midges in the field and measure how much the change of direction of one midge affects that of other individuals. We discover that, despite the lack of collective order, swarms display very strong correlations, totally incompatible with models of non-interacting particles. We find that correlation increases sharply with the swarm's density, indicating that the interaction between midges is based on a metric perception mechanism. By means of numerical simulations we demonstrate that such growing correlation is typical of a system close to an ordering transition. Our findings suggest that correlation, rather than order, is the true hallmark of collective behaviour in biological systems.

  16. Flagellar flows around bacterial swarms

    CERN Document Server

    Dauparas, Justas

    2016-01-01

    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, 2011 Proc. Natl. Acad. Sci. USA 108 4147). A systematic chiral flow was observed in the clockwise direction (when viewed from above) ahead of the swarm with flow speeds of about $10~\\mu$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 outwards, moving fluid over the virgin agar. In this work 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. The results we obtain are in agreement with the flagellar hypothesis. The model provides...

  17. Using participatory risk mapping (PRM) to identify and understand people's perceptions of crop loss to animals in Uganda.

    Science.gov (United States)

    Webber, Amanda D; Hill, Catherine M

    2014-01-01

    Considering how people perceive risks to their livelihoods from local wildlife is central to (i) understanding the impact of crop damage by animals on local people and (ii) recognising how this influences their interactions with, and attitudes towards, wildlife. Participatory risk mapping (PRM) is a simple, analytical tool that can be used to identify and classify risk within communities. Here we use it to explore local people's perceptions of crop damage by wildlife and the animal species involved. Interviews (n = 93, n = 76) and seven focus groups were conducted in four villages around Budongo Forest Reserve, Uganda during 2004 and 2005. Farms (N = 129) were simultaneously monitored for crop loss. Farmers identified damage by wildlife as the most significant risk to their crops; risk maps highlighted its anomalous status compared to other anticipated challenges to agricultural production. PRM was further used to explore farmers' perceptions of animal species causing crop damage and the results of this analysis compared with measured crop losses. Baboons (Papio anubis) were considered the most problematic species locally but measurements of loss indicate this perceived severity was disproportionately high. In contrast goats (Capra hircus) were considered only a moderate risk, yet risk of damage by this species was significant. Surprisingly, for wild pigs (Potamochoerus sp), perceptions of severity were not as high as damage incurred might have predicted, although perceived incidence was greater than recorded frequency of damage events. PRM can assist researchers and practitioners to identify and explore perceptions of the risk of crop damage by wildlife. As this study highlights, simply quantifying crop loss does not determine issues that are important to local people nor the complex relationships between perceived risk factors. Furthermore, as PRM is easily transferable it may contribute to the identification and development of standardised approaches

  18. Particle Swarm Optimization with Double Learning Patterns.

    Science.gov (United States)

    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.

  19. Multispacecraft current estimates at swarm

    DEFF Research Database (Denmark)

    Dunlop, M. W.; Yang, Y.-Y.; Yang, J.-Y.

    2015-01-01

    During the first several months of the three-spacecraft Swarm mission all three spacecraft camerepeatedly into close alignment, providing an ideal opportunity for validating the proposed dual-spacecraftmethod for estimating current density from the Swarm magnetic field data. Two of the Swarm...... orbit the use oftime-shifted positions allow stable estimates of current density to be made and can verify temporal effects aswell as validating the interpretation of the current components as arising predominantly from field-alignedcurrents. In the case of four-spacecraft configurations we can resolve...... the full vector current and therefore cancheck the perpendicular as well as parallel current density components directly, together with the qualityfactor for the estimates directly (for the first time in situ at low Earth orbit)....

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

    Science.gov (United States)

    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

  1. Binary Cockroach Swarm Optimization for Combinatorial Optimization Problem

    Directory of Open Access Journals (Sweden)

    Ibidun Christiana Obagbuwa

    2016-09-01

    Full Text Available The Cockroach Swarm Optimization (CSO algorithm is inspired by cockroach social behavior. It is a simple and efficient meta-heuristic algorithm and has been applied to solve global optimization problems successfully. The original CSO algorithm and its variants operate mainly in continuous search space and cannot solve binary-coded optimization problems directly. Many optimization problems have their decision variables in binary. Binary Cockroach Swarm Optimization (BCSO is proposed in this paper to tackle such problems and was evaluated on the popular Traveling Salesman Problem (TSP, which is considered to be an NP-hard Combinatorial Optimization Problem (COP. A transfer function was employed to map a continuous search space CSO to binary search space. The performance of the proposed algorithm was tested firstly on benchmark functions through simulation studies and compared with the performance of existing binary particle swarm optimization and continuous space versions of CSO. The proposed BCSO was adapted to TSP and applied to a set of benchmark instances of symmetric TSP from the TSP library. The results of the proposed Binary Cockroach Swarm Optimization (BCSO algorithm on TSP were compared to other meta-heuristic algorithms.

  2. Swarming UAVs mission design strategy

    Science.gov (United States)

    Lin, Kuo-Chi

    2007-04-01

    This paper uses a behavioral hierarchy approach to reduce the mission solution space and make the mission design easier. A UAV behavioral hierarchy is suggested, which is derived from three levels of behaviors: basic, individual and group. The individual UAV behavior is a combination of basic, lower level swarming behaviors with priorities. Mission design can be simplified by picking the right combination of individual swarming behaviors, which will emerge the needed group behaviors. Genetic Algorithm is used in both lower-level basic behavior design and mission design.

  3. Exploring teacher's perceptions of concept mapping as a teaching strategy in science: An action research approach

    Science.gov (United States)

    Marks Krpan, Catherine Anne

    In order to promote science literacy in the classroom, students need opportunities in which they can personalize their understanding of the concepts they are learning. Current literature supports the use of concept maps in enabling students to make personal connections in their learning of science. Because they involve creating explicit connections between concepts, concept maps can assist students in developing metacognitive strategies and assist educators in identifying misconceptions in students' thinking. The literature also notes that concept maps can improve student achievement and recall. Much of the current literature focuses primarily on concept mapping at the secondary and university levels, with limited focus on the elementary panel. The research rarely considers teachers' thoughts and ideas about the concept mapping process. In order to effectively explore concept mapping from the perspective of elementary teachers, I felt that an action research approach would be appropriate. Action research enabled educators to debate issues about concept mapping and test out ideas in their classrooms. It also afforded the participants opportunities to explore their own thinking, reflect on their personal journeys as educators and play an active role in their professional development. In an effort to explore concept mapping from the perspective of elementary educators, an action research group of 5 educators and myself was established and met regularly from September 1999 until June 2000. All of the educators taught in the Toronto area. These teachers were interested in exploring how concept mapping could be used as a learning tool in their science classrooms. In summary, this study explores the journey of five educators and myself as we engaged in collaborative action research. This study sets out to: (1) Explore how educators believe concept mapping can facilitate teaching and student learning in the science classroom. (2) Explore how educators implement concept

  4. Gold rush - A swarm dynamics in games

    Science.gov (United States)

    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.

  5. Placement of the Services with the help of Perception Maps presented by the GSM Operators Facilitating in Turkey

    Directory of Open Access Journals (Sweden)

    Aykut Ekiyor

    2014-03-01

    Full Text Available Product placement comes into prominence as a wide and de tailed topic reaching the basis to the differentiation in the market. The product placement facilities are to form a specific product perception on the target consumer’s minds. In giving these services, a good marketing communication with the consumers has an important role. In the frame of product placement, the perception maps are used as a visual vehicle. In this study: the aim was to put forth the positioning of the service given by the cell phone operators facilitating in Turkey by the help of percepti on maps with the data gained by the consumers. Also, another aim was to visually show the different and similar variables of the cell phone operators in the minds of the consumers. In the scope of a literature review a questionnaire has been prepared to id entify the similarities and differences between the cell phone operators. The questionnaire has been applied to 521 consumers. As each consumer evaluated the three operators 1563 data has been gained. The evaluation of the data gained after the study was done by discriminant analysis

  6. Epidemic Synchronization in Robotic Swarms

    DEFF Research Database (Denmark)

    Schiøler, Henrik; Nielsen, Jens Frederik Dalsgaard; Ngo, Trung Dung

    2009-01-01

    Clock synchronization in swarms of networked mobile robots is studied in a probabilistic, epidemic framework. In this setting communication and synchonization is considered to be a randomized process, taking place at unplanned instants of geographical rendezvous between robots. In combination wit...

  7. Beyond swarm intelligence: The Ultraswarm

    OpenAIRE

    Holland, Owen; Woods, John; De Nardi, Renzo; Clarck, Adrian

    2005-01-01

    This paper explores the idea that it may be possible to combine two ideas – UAV flocking, and wireless cluster computing – in a single system, the UltraSwarm. The possible advantages of such a system are considered, and solutions to some of the technical problems are identified. Initial work on constructing such a system based around miniature electric helicopters is described.

  8. Map Your Hazards! - an Interdisciplinary, Place-Based Educational Approach to Assessing Natural Hazards, Social Vulnerability, Risk and Risk Perception.

    Science.gov (United States)

    Brand, B. D.; McMullin-Messier, P. A.; Schlegel, M. E.

    2014-12-01

    'Map your Hazards' is an educational module developed within the NSF Interdisciplinary Teaching about Earth for a Sustainable Future program (InTeGrate). The module engages students in place-based explorations of natural hazards, social vulnerability, and the perception of natural hazards and risk. Students integrate geoscience and social science methodologies to (1) identify and assess hazards, vulnerability and risk within their communities; (2) distribute, collect and evaluate survey data (designed by authors) on the knowledge, risk perception and preparedness within their social networks; and (3) deliver a PPT presentation to local stakeholders detailing their findings and recommendations for development of a prepared, resilient community. 'Map your Hazards' underwent four rigorous assessments by a team of geoscience educators and external review before being piloted in our classrooms. The module was piloted in a 300-level 'Volcanoes and Society' course at Boise State University, a 300-level 'Environmental Sociology' course at Central Washington University, and a 100-level 'Natural Disasters and Environmental Geology' course at the College of Western Idaho. In all courses students reported a fascination with learning about the hazards around them and identifying the high risk areas in their communities. They were also surprised at the low level of knowledge, inaccurate risk perception and lack of preparedness of their social networks. This successful approach to engaging students in an interdisciplinary, place-based learning environment also has the broad implications of raising awareness of natural hazards (survey participants are provided links to local hazard and preparedness information). The data and preparedness suggestions can be shared with local emergency managers, who are encouraged to attend the student's final presentations. All module materials are published at serc.carleton.edu/integrate/ and are appropriate to a wide range of classrooms.

  9. Using Concept Maps to Elicit and Study Student Teachers' Perceptions about Inclusive Education: A Tanzanian Experience

    Science.gov (United States)

    Wormnaes, Siri; Mkumbo, Kitila; Skaar, Bjørn; Refseth, Yngve

    2015-01-01

    In this study, concept map activities were used to trigger group discussions about inclusive education, with a focus on learners with disabilities. The participants were 226 Tanzanian student teachers. This article reports and discusses how the maps were analysed and what they indicate about the students' thinking about certain aspects of…

  10. Using Concept Maps to Elicit and Study Student Teachers' Perceptions about Inclusive Education: A Tanzanian Experience

    Science.gov (United States)

    Wormnaes, Siri; Mkumbo, Kitila; Skaar, Bjørn; Refseth, Yngve

    2015-01-01

    In this study, concept map activities were used to trigger group discussions about inclusive education, with a focus on learners with disabilities. The participants were 226 Tanzanian student teachers. This article reports and discusses how the maps were analysed and what they indicate about the students' thinking about certain aspects of…

  11. Brands as Intentional Agents Framework: How Perceived Intentions and Ability Can Map Brand Perception.

    Science.gov (United States)

    Kervyn, Nicolas; Fiske, Susan T; Malone, Chris

    2012-04-01

    Building on the Stereotype Content Model, this paper introduces and tests the Brands as Intentional Agents Framework. A growing body of research suggests that consumers have relationships with brands that resemble relations between people. We propose that consumers perceive brands in the same way they perceive people. This approach allows us to explore how social perception theories and processes can predict brand purchase interest and loyalty. Brands as Intentional Agents Framework is based on a well-established social perception approach: the Stereotype Content Model. Two studies support the Brands as Intentional Agents Framework prediction that consumers assess a brand's perceived intentions and ability and that these perceptions elicit distinct emotions and drive differential brand behaviors. The research shows that human social interaction relationships translate to consumer-brand interactions in ways that are useful to inform brand positioning and brand communications.

  12. The collaborative image of the city: mapping the inequality of urban perception.

    Directory of Open Access Journals (Sweden)

    Philip Salesses

    Full Text Available A traveler visiting Rio, Manila or Caracas does not need a report to learn that these cities are unequal; she can see it directly from the taxicab window. This is because in most cities inequality is conspicuous, but also, because cities express different forms of inequality that are evident to casual observers. Cities are highly heterogeneous and often unequal with respect to the income of their residents, but also with respect to the cleanliness of their neighborhoods, the beauty of their architecture, and the liveliness of their streets, among many other evaluative dimensions. Until now, however, our ability to understand the effect of a city's built environment on social and economic outcomes has been limited by the lack of quantitative data on urban perception. Here, we build on the intuition that inequality is partly conspicuous to create quantitative measure of a city's contrasts. Using thousands of geo-tagged images, we measure the perception of safety, class and uniqueness; in the cities of Boston and New York in the United States, and Linz and Salzburg in Austria, finding that the range of perceptions elicited by the images of New York and Boston is larger than the range of perceptions elicited by images from Linz and Salzburg. We interpret this as evidence that the cityscapes of Boston and New York are more contrasting, or unequal, than those of Linz and Salzburg. Finally, we validate our measures by exploring the connection between them and homicides, finding a significant correlation between the perceptions of safety and class and the number of homicides in a NYC zip code, after controlling for the effects of income, population, area and age. Our results show that online images can be used to create reproducible quantitative measures of urban perception and characterize the inequality of different cities.

  13. The collaborative image of the city: mapping the inequality of urban perception.

    Science.gov (United States)

    Salesses, Philip; Schechtner, Katja; Hidalgo, César A

    2013-01-01

    A traveler visiting Rio, Manila or Caracas does not need a report to learn that these cities are unequal; she can see it directly from the taxicab window. This is because in most cities inequality is conspicuous, but also, because cities express different forms of inequality that are evident to casual observers. Cities are highly heterogeneous and often unequal with respect to the income of their residents, but also with respect to the cleanliness of their neighborhoods, the beauty of their architecture, and the liveliness of their streets, among many other evaluative dimensions. Until now, however, our ability to understand the effect of a city's built environment on social and economic outcomes has been limited by the lack of quantitative data on urban perception. Here, we build on the intuition that inequality is partly conspicuous to create quantitative measure of a city's contrasts. Using thousands of geo-tagged images, we measure the perception of safety, class and uniqueness; in the cities of Boston and New York in the United States, and Linz and Salzburg in Austria, finding that the range of perceptions elicited by the images of New York and Boston is larger than the range of perceptions elicited by images from Linz and Salzburg. We interpret this as evidence that the cityscapes of Boston and New York are more contrasting, or unequal, than those of Linz and Salzburg. Finally, we validate our measures by exploring the connection between them and homicides, finding a significant correlation between the perceptions of safety and class and the number of homicides in a NYC zip code, after controlling for the effects of income, population, area and age. Our results show that online images can be used to create reproducible quantitative measures of urban perception and characterize the inequality of different cities.

  14. Tectonic Setting of the Wooded Island Earthquake Swarm, Eastern Washington

    Energy Technology Data Exchange (ETDEWEB)

    Blakely, R. J.; Sherrod, B. L.; Weaver, C. S.; Rohay, A. C.; Wells, R. E.

    2012-08-01

    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 near Wooded 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. Finally, 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.

  15. Mapping the speech code: Cortical responses linking the perception and production of vowels

    NARCIS (Netherlands)

    Schuerman, W.L.; Meyer, A.S.; McQueen, J.M.

    2017-01-01

    The acoustic realization of speech is constrained by the physical mechanisms by which it is produced. Yet for speech perception, the degree to which listeners utilize experience derived from speech production has long been debated. In the present study, we examined how sensorimotor adaptation during

  16. Social dataset analysis and mapping tools for Risk Perception: resilience, people preparation and communication tools

    Science.gov (United States)

    Peters-Guarin, Graciela; Garcia, Carolina; Frigerio, Simone

    2010-05-01

    Perception has been identified as resource and part of the resilience of a community to disasters. Risk perception, if present, may determine the potential damage a household or community experience. Different levels of risk perception and preparedness can influence directly people's susceptibility and the way they might react in case of an emergency caused by natural hazards. In spite of the profuse literature about risk perception, works to spatially portray this feature are really scarce. The spatial relationship to danger or hazard is being recognised as an important factor of the risk equation; it can be used as a powerful tool either for better knowledge or for operational reasons (e.g. management of preventive information). Risk perception and people's awareness when displayed in a spatial format can be useful for several actors in the risk management arena. Local authorities and civil protection can better address educational activities to increase the preparation of particularly vulnerable groups of clusters of households within a community. It can also be useful for the emergency personal in order to optimally direct the actions in case of an emergency. In the framework of the Marie Curie Research Project, a Community Based Early Warning System (CBEWS) it's been developed in the Mountain Community Valtellina of Tirano, northern Italy. This community has been continuously exposed to different mass movements and floods, in particular, a large event in 1987 which affected a large portion of the valley and left 58 dead. The actual emergency plan for the study area is composed by a real time, highly detailed, decision support system. This emergency plan contains detailed instructions for the rapid deployment of civil protection and other emergency personal in case of emergency, for risk scenarios previously defined. Especially in case of a large event, where timely reaction is crucial for reducing casualties, it is important for those in charge of emergency

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

    Science.gov (United States)

    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.

  18. Attribute Perception Mapping Services Domestic Airlines Using Correspondence Analysis (59-67

    Directory of Open Access Journals (Sweden)

    Reni Heviandri Riandarini

    2016-06-01

    Full Text Available Positioning analysis provides a better understanding of the position based on the perception of passenger flights to service these attributes attached to each airline. This study aims to perform positioning of the domestic airline services based attributes, which characterize the airline based on the perception of consumers. Correspondence Analysis (CA is used to determine the positioning of the six commercial airlines in Indonesia. The results of correspondence analysis showed that the airline Garuda, Lion Air, Citilink and Air Asia already has its own characteristics inherent in the minds of consumers, while the two other airlines, namely Batik Air and Sriwijaya Air has not had a special identifier.Keywords: Positioning, Correspondence Analysis, Full Service Airline (FSA, Low Fare Airline (LFA

  19. Time-delayed autosynchronous swarm control.

    Science.gov (United States)

    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.

  20. Swarming behavior of multi-agent systems

    Institute of Scientific and Technical Information of China (English)

    Hong SHI; Long WANG; Tianguang CHU

    2004-01-01

    We consider an anisotropic swarm model with an attraction/repulsion function and study its aggregation properties.It is shown that the swarm members will aggregate and eventually form a cohesive cluster of finite size around the swarm center in a finite time.Moreover,we extend our results to more general attraction/repulsion functions.Numerical simulations demonstrate that all agents will eventually enter into and remain in a bounded region around the swarm center which may exhibit complex spiral motion due to asymmetry of the coupling structure.The model in this paper is more general than isotropic swarms and our results provide further insight into the effect of the interaction pattern on individual motion in a swarm system.

  1. Collective motion in non-reciprocal swarms

    Institute of Scientific and Technical Information of China (English)

    Bo LIU; Tianguang CHU; Long WANG

    2009-01-01

    This paper studies a non-reciprocal swarm model that consists of a group of mobile autonomous agents with an attraction-repulsion function governing the interaction of the agents. The function is chosen to have infinitely large values of repulsion for vanishing distance between two agents so as to avoid occurrence of collision. It is shown analytically that under the detailed balance condition in coupling weights, all the agents will aggregate and eventually form a cohesive cluster of finite size around the weighted center of the swarm in a finite time. Moreover, the swarm system is completely stable, namely, the motion of all agents converge to the set of equilibrium points. For the general case of non-reciprocal swarms without the detailed balance condition, numerical simulations show that more complex self-organized oscillations can emerge in the swarms. The effect of noise on collective dynamics of the swarm is also examined with a white Gaussian noise model.

  2. On the tensile strength of insect swarms

    Science.gov (United States)

    Ni, Rui; Ouellette, Nicholas T.

    2016-08-01

    Collective animal groups are often described by the macroscopic patterns they form. Such global patterns, however, convey limited information about the nature of the aggregation as a whole. Here, we take a different approach, drawing on ideas from materials testing to probe the macroscopic mechanical properties of mating swarms of the non-biting midge Chironomus riparius. By manipulating ground-based visual features that tend to position the swarms in space, we apply an effective tensile load to the swarms, and show that we can quasi-statically pull single swarms apart into multiple daughter swarms. Our results suggest that swarms surprisingly have macroscopic mechanical properties similar to solids, including a finite Young’s modulus and yield strength, and that they do not flow like viscous fluids.

  3. Development of Micro UAV Swarms

    Science.gov (United States)

    Bürkle, Axel; Leuchter, Sandro

    Some complex application scenarios for micro UAVs (Unmanned Aerial Vehicles) call for the formation of swarms of multiple drones. In this paper a platform for the creation of such swarms is presented. It consists of modified commercial quadrocopters and a self-made ground control station software architecture. Autonomy of individual drones is generated through a micro controller equipped video camera. Currently it is possible to fly basic maneuvers autonomously, such as take-off, fly to position, and landing. In the future the camera's image processing capabilities will be used to generate additional control information. Different co-operation strategies for teams of UAVs are currently evaluated with an agent based simulation tool. Finally complex application scenarios for multiple micro UAVs are presented.

  4. Overpressurized fluids drive microseismic swarm activity around Mt. Ontake volcano, Japan

    Science.gov (United States)

    Terakawa, Toshiko

    2017-06-01

    Microseismic swarm activity has taken place since 1976 around Mt. Ontake, the second highest stratovolcano in Japan. This activity is thought to be linked to high pore-fluid pressure in the vicinity of the volcano. We analyzed well-constrained focal mechanism solutions of microseismicity to re-estimate the 3-D pore-fluid pressure field driving vigorous swarm activity around Mt. Ontake. Pore-fluid pressures were measured by mapping earthquake focal mechanisms on the 3-D Mohr diagram for the regional stress field with high resolutions of 2-5 km. The assumption of the reference stress pattern can cause modeling errors in measurements of pore-fluid pressure. To remove the effect, we statistically evaluated the estimation errors of the regional stress field and included these errors in the analysis. We detected an overpressurized fluid reservoir with a peak of about 10-30 MPa in the east flank of Mt. Ontake, where microseismic swarm activity has been vigorous for the last two decades. The level of pore-fluid pressure was maintained for at least 5 years after 2009. This finding indicates that there are some interactions between the intensive swarm activity and overpressurized fluids: the swarm activity has been driven by overpressurized fluids, whereas pore-fluid pressures have been suppressed by the swarm activity.[Figure not available: see fulltext.

  5. A comparison of policy and direct practice stakeholder perceptions of factors affecting evidence-based practice implementation using concept mapping

    Directory of Open Access Journals (Sweden)

    Green Amy E

    2011-09-01

    Full Text Available Abstract Background The goal of this study was to assess potential differences between administrators/policymakers and those involved in direct practice regarding factors believed to be barriers or facilitating factors to evidence-based practice (EBP implementation in a large public mental health service system in the United States. Methods Participants included mental health system county officials, agency directors, program managers, clinical staff, administrative staff, and consumers. As part of concept mapping procedures, brainstorming groups were conducted with each target group to identify specific factors believed to be barriers or facilitating factors to EBP implementation in a large public mental health system. Statements were sorted by similarity and rated by each participant in regard to their perceived importance and changeability. Multidimensional scaling, cluster analysis, descriptive statistics and t-tests were used to analyze the data. Results A total of 105 statements were distilled into 14 clusters using concept-mapping procedures. Perceptions of importance of factors affecting EBP implementation varied between the two groups, with those involved in direct practice assigning significantly higher ratings to the importance of Clinical Perceptions and the impact of EBP implementation on clinical practice. Consistent with previous studies, financial concerns (costs, funding were rated among the most important and least likely to change by both groups. Conclusions EBP implementation is a complex process, and different stakeholders may hold different opinions regarding the relative importance of the impact of EBP implementation. Implementation efforts must include input from stakeholders at multiple levels to bring divergent and convergent perspectives to light.

  6. Towards CHAOS-5 - How can Swarm contribute?

    DEFF Research Database (Denmark)

    Finlay, Chris; Olsen, Nils; Tøffner-Clausen, Lars

    2014-01-01

    The launch of ESA's satellite trio Swarm in November 2013 opens an exciting new chapter in the observation and monitoring of Earth's magnetic field from space. We report preliminary results from an extension of the CHAOS series of geomagnetic field models to include both scalar and vector field...... observations from the three Swarm satellites, along with the most recent quasi-definitive ground observatory data. The fit of this new update CHAOS field model to the Swarm observations will be presented in detail providing useful insight the initial Swarm data. Enhancements of the CHAOS modelling scheme...

  7. Swarm controlled emergence for ant clustering

    DEFF Research Database (Denmark)

    Scheidler, Alexander; Merkle, Daniel; Middendorf, Martin

    2013-01-01

    Purpose: Swarm controlled emergence is proposed as an approach to control emergent effects in (artificial) swarms. The method involves the introduction of specific control agents into the swarm systems. Control agents behave similar to the normal agents and do not directly influence the behavior...... implications: The particular finding, that certain behaviours of control agents can lead to stronger clustering, can help to design improved clustering algorithms by using heterogeneous swarms of agents. Originality/value: In general, the control of (unwanted) emergent effects in artificial systems...

  8. Interacting Brownian Swarms: Some Analytical Results

    Directory of Open Access Journals (Sweden)

    Guillaume Sartoretti

    2016-01-01

    Full Text Available We consider the dynamics of swarms of scalar Brownian agents subject to local imitation mechanisms implemented using mutual rank-based interactions. For appropriate values of the underlying control parameters, the swarm propagates tightly and the distances separating successive agents are iid exponential random variables. Implicitly, the implementation of rank-based mutual interactions, requires that agents have infinite interaction ranges. Using the probabilistic size of the swarm’s support, we analytically estimate the critical interaction range below that flocked swarms cannot survive. In the second part of the paper, we consider the interactions between two flocked swarms of Brownian agents with finite interaction ranges. Both swarms travel with different barycentric velocities, and agents from both swarms indifferently interact with each other. For appropriate initial configurations, both swarms eventually collide (i.e., all agents interact. Depending on the values of the control parameters, one of the following patterns emerges after collision: (i Both swarms remain essentially flocked, or (ii the swarms become ultimately quasi-free and recover their nominal barycentric speeds. We derive a set of analytical flocking conditions based on the generalized rank-based Brownian motion. An extensive set of numerical simulations corroborates our analytical findings.

  9. Fishing for Data: Using Particle Swarm Optimization to Search Data

    Science.gov (United States)

    Caputo, Daniel P.; Dolan, R.

    2010-01-01

    As the size of data and model sets continue to increase, more efficient ways are needed to sift through the available information. We present a computational method which will efficiently search large parameter spaces to either map the space or find individual data/models of interest. Particle swarm optimization (PSO) is a subclass of artificial life computer algorithms. The PSO algorithm attempts to leverage "swarm intelligence” against finding optimal solutions to a problem. This system is often based on a biological model of a swarm (e.g. schooling fish). These biological models are broken down into a few simple rules which govern the behavior of the system. "Agents” (e.g. fish) are introduced and the agents, following the rules, search out solutions much like a fish would seek out food. We have made extensive modifications to the standard PSO model which increase its efficiency as-well-as adding the capacity to map a parameter space and find multiple solutions. Our modified PSO is ideally suited to search and map large sets of data/models which are degenerate or to search through data/models which are too numerous to analyze by hand. One example of this would include radiative transfer models, which are inherently degenerate. Applying the PSO algorithm will allow the degeneracy space to be mapped and thus better determine limits on dust shell parameters. Another example is searching through legacy data from a survey for hints of Polycyclic Aromatic Hydrocarbon emission. What might have once taken years of searching (and many frustrated graduate students) can now be relegated to the task of a computer which will work day and night for only the cost of electricity. We hope this algorithm will allow fellow astronomers to more efficiently search data and models, thereby freeing them to focus on the physics of the Universe.

  10. Mapping the Racial Inequality in Place: Using Youth Perceptions to Identify Unequal Exposure to Neighborhood Environmental Hazards

    Directory of Open Access Journals (Sweden)

    Samantha Teixeira

    2016-08-01

    Full Text Available Black youth are more likely than white youth to grow up in poor, segregated neighborhoods. This racial inequality in the neighborhood environments of black youth increases their contact with hazardous neighborhood environmental features including violence and toxic exposures that contribute to racial inequality in youth health and well-being. While the concept of neighborhood effects has been studied at length by social scientists, this work has not been as frequently situated within an environmental justice (EJ paradigm. The present study used youth perceptions gained from in-depth interviews with youth from one Pittsburgh, Pennsylvania neighborhood to identify neighborhood environmental health hazards. We then mapped these youth-identified features to examine how they are spatially and racially distributed across the city. Our results suggest that the intersection of race and poverty, neighborhood disorder, housing abandonment, and crime were salient issues for youth. The maps show support for the youths’ assertions that the environments of black and white individuals across the city of Pittsburgh differ in noteworthy ways. This multi-lens, mixed-method analysis was designed to challenge some of the assumptions we make about addressing environmental inequality using youths’ own opinions on the issue to drive our inquiry.

  11. Conceptualizing Stakeholders' Perceptions of Ecosystem Services: A Participatory Systems Mapping Approach

    Science.gov (United States)

    Lopes, Rita; Videira, Nuno

    2015-12-01

    A participatory system dynamics modelling approach is advanced to support conceptualization of feedback processes underlying ecosystem services and to foster a shared understanding of leverage intervention points. The process includes systems mapping workshop and follow-up tasks aiming at the collaborative construction of causal loop diagrams. A case study developed in a natural area in Portugal illustrates how a stakeholder group was actively engaged in the development of a conceptual model depicting policies for sustaining the climate regulation ecosystem service.

  12. Identifying Interacting Genetic Variations by Fish-Swarm Logic Regression

    Science.gov (United States)

    Yang, Aiyuan; Yan, Chunxia; Zhu, Feng; Zhao, Zhongmeng; Cao, Zhi

    2013-01-01

    Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR) is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR), which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds. PMID:23984382

  13. Global volcanic earthquake swarm database and preliminary analysis of volcanic earthquake swarm duration

    Directory of Open Access Journals (Sweden)

    S. R. McNutt

    1996-06-01

    Full Text Available Global data from 1979 to 1989 pertaining to volcanic earthquake swarms have been compiled into a custom-designed relational database. The database is composed of three sections: 1 a section containing general information on volcanoes, 2 a section containing earthquake swarm data (such as dates of swarm occurrence and durations, and 3 a section containing eruption information. The most abundant and reliable parameter, duration of volcanic earthquake swarms, was chosen for preliminary analysis. The distribution of all swarm durations was found to have a geometric mean of 5.5 days. Precursory swarms were then separated from those not associated with eruptions. The geometric mean precursory swarm duration was 8 days whereas the geometric mean duration of swarms not associated with eruptive activity was 3.5 days. Two groups of precursory swarms are apparent when duration is compared with the eruption repose time. Swarms with durations shorter than 4 months showed no clear relationship with the eruption repose time. However, the second group, lasting longer than 4 months, showed a significant positive correlation with the log10 of the eruption repose period. The two groups suggest that different suites of physical processes are involved in the generation of volcanic earthquake swarms.

  14. Swarm: Recent Progress in Analysis of the Sun Induced Magnetic Disturbance

    DEFF Research Database (Denmark)

    Tøffner-Clausen, Lars; Lesur, Vincent; Brauer, Peter

    The ESA Earth Observation Magnetic Mission Swarm carries high precision vector and scalar magnetometers. Careful analyses have revealed s smaller, Sun driven magnetic disturbance of the vector magnetometer. This disturbance have been imperically mapped and corrected since mid 2015. This work...

  15. Swarm: Recent Progress in Analysis of the Sun Induced Magnetic Disturbance

    DEFF Research Database (Denmark)

    Tøffner-Clausen, Lars; Lesur, Vincent; Brauer, Peter

    The ESA Earth Observation Magnetic Mission Swarm carries high precision vector and scalar magnetometers. Careful analyses have revealed s smaller, Sun driven magnetic disturbance of the vector magnetometer. This disturbance have been imperically mapped and corrected since mid 2015. This work...

  16. Osmotic pressure in a bacterial swarm.

    Science.gov (United States)

    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.

  17. Swarm Products and Space Weather Applications

    DEFF Research Database (Denmark)

    Stolle, Claudia; Olsen, Nils; Martini, Daniel

    The Swarm satellite constellation mission provides high precision magnetic field data and models and other observations that enable us to explore near Earth space for example in terms of in situ electron density and electric fields. On board GPS observables can be used for sounding ionospheric an...... in aeronomy and space weather. We will emphasize results from the Swarm mission....

  18. Swarm intelligence for scheduling: a review

    OpenAIRE

    Madureira, Ana Maria; Sousa, Nelson; Pereira, Ivo

    2011-01-01

    Swarm Intelligence generally refers to a problem-solving ability that emerges from the interaction of simple information-processing units. The concept of Swarm suggests multiplicity, distribution, stochasticity, randomness, and messiness. The concept of Intelligence suggests that problem-solving approach is successful considering learning, creativity, cognition capabilities. This paper introduces some of the theoretical foundations, the biological motivation and fundamental aspect...

  19. Conceptualizing Stakeholders’ Perceptions of Ecosystem Services: A Participatory Systems Mapping Approach

    Directory of Open Access Journals (Sweden)

    Lopes Rita

    2015-12-01

    Full Text Available A participatory system dynamics modelling approach is advanced to support conceptualization of feedback processes underlying ecosystem services and to foster a shared understanding of leverage intervention points. The process includes systems mapping workshop and follow-up tasks aiming at the collaborative construction of causal loop diagrams. A case study developed in a natural area in Portugal illustrates how a stakeholder group was actively engaged in the development of a conceptual model depicting policies for sustaining the climate regulation ecosystem service.

  20. Particle Swarm Transport in Fracture Networks

    Science.gov (United States)

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

    2012-12-01

    Colloidal particles of many types occur in fractures in the subsurface as a result of both natural and industrial processes (e.g., environmental influences, synthetic nano- & micro-particles from consumer products, chemical and mechanical erosion of geologic material, proppants used in gas and oil extraction, etc.). The degree of localization and speed of transport of such particles depends on the transport mechanisms, the chemical and physical properties of the particles and the surrounding rock, and the flow path geometry through the fracture. In this study, we investigated the transport of particle swarms through artificial fracture networks. A synthetic fracture network was created using an Objet Eden 350V 3D printer to build a network of fractures. Each fracture in the network had a rectangular cross-sectional area with a constant depth of 7 mm but with widths that ranged from 2 mm to 11 mm. The overall dimensions of the network were 132 mm by 166 mm. The fracture network had 7 ports that were used either as the inlet or outlet for fluid flow through the sample or for introducing a particle swarm. Water flow rates through the fracture were controlled with a syringe pump, and ranged from zero flow to 6 ml/min. Swarms were composed of a dilute suspension (2% by mass) of 3 μm fluorescent polystyrene beads in water. Swarms with volumes of 5, 10, 20, 30 and 60 μl were used and delivered into the network using a second syringe pump. The swarm behavior was imaged using an optical fluorescent imaging system illuminated by green (525 nm) LED arrays and captured by a CCD camera. For fracture networks with quiescent fluids, particle swarms fell under gravity and remained localized within the network. Large swarms (30-60 μl) were observed to bifurcate at shallower depths resulting in a broader dispersal of the particles than for smaller swarm volumes. For all swarm volumes studied, particle swarms tended to bifurcate at the intersection between fractures. These

  1. Design and control of swarm dynamics

    CERN Document Server

    Bouffanais, Roland

    2016-01-01

    The book is about the key elements required for designing, building and controlling effective artificial swarms comprised of multiple moving physical agents. Therefore this book presents the fundamentals of each of those key elements in the particular frame of dynamic swarming, specifically exposing the profound connections between these elements and establish some general design principles for swarming behaviors. This scientific endeavor requires an inter-disciplinary approach: biomimetic inspiration from ethology and ecology, study of social information flow, analysis of temporal and adaptive signaling network of interaction, considerations of control of networked real-time systems, and lastly, elements of complex adaptive dynamical systems. This book offers a completely new perspective on the scientific understanding of dynamic collective behaviors thanks to its multi-disciplinary approach and its focus on artificial swarm of physical agents. Two of the key problems in understanding the emergence of swarm ...

  2. Swarm Data Processing and First Scientific Results

    DEFF Research Database (Denmark)

    Olsen, Nils

    2014-01-01

    , accelerometer, plasma and electric field measurements. These observations will be distributed by ESA as Level-1b data, which are the calibrated and formatted time series of e.g. the magnetic field measurements taken by each of the three Swarm satellites. The talks presents a first scientific validation of Swarm......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. Each of the three Swarm satellites provides high-precision and high-resolution measurements of the strength, direction and variation of the magnetic field, complemented by precise navigation...

  3. Optical Networking in a Swarm of Microrobots

    Science.gov (United States)

    Corradi, Paolo; Schmickl, Thomas; Scholz, Oliver; Menciassi, Arianna; Dario, Paolo

    Swarm Microrobotics aims to apply Swarm Intelligence algorithms and strategies to a large number of fabricated miniaturized autonomous or semi-autonomous agents, allowing collective, decentralized and self-organizing behaviors of the robots. The ability to establish basic information networking is fundamental in such swarm systems, where inter-robot communication is the base of emergent behaviors. Optical communication represents so far probably the only feasible and suitable solution for the constraints and requirements imposed by the development of a microrobotic swarm. This paper introduces a miniaturized optical communication module for millimeter-sized autonomous robots and presents a computer-simulated demonstration of its basic working principle to exploit bio-inspired swarm strategies.

  4. Insular species swarm goes underground

    DEFF Research Database (Denmark)

    P. S. Reboleira, Ana Sofia; Enghoff, Henrik

    2014-01-01

    Two new species of the genus Cylindroiulus Verhoeff, 1894, C. julesvernei and C. oromii, are described from the subterranean ecosystem of Madeira Island, Portugal. Species are illustrated with photographs and diagrammatic drawings. The new species belong to the Cylindroiulus madeirae......-group, an insular species swarm distributed in the archipelagos of Madeira and the Canary Islands. We discuss the differences between the new species and their relatives and present information on the subterranean environment of Madeira. An updated overview of the subterranean biodiversity of millipedes...

  5. Naturalistic fMRI Mapping Reveals Superior Temporal Sulcus as the Hub for the Distributed Brain Network for Social Perception

    Science.gov (United States)

    Lahnakoski, Juha M.; Glerean, Enrico; Salmi, Juha; Jääskeläinen, Iiro P.; Sams, Mikko; Hari, Riitta; Nummenmaa, Lauri

    2012-01-01

    Despite the abundant data on brain networks processing static social signals, such as pictures of faces, the neural systems supporting social perception in naturalistic conditions are still poorly understood. Here we delineated brain networks subserving social perception under naturalistic conditions in 19 healthy humans who watched, during 3-T functional magnetic resonance imaging (fMRI), a set of 137 short (approximately 16 s each, total 27 min) audiovisual movie clips depicting pre-selected social signals. Two independent raters estimated how well each clip represented eight social features (faces, human bodies, biological motion, goal-oriented actions, emotion, social interaction, pain, and speech) and six filler features (places, objects, rigid motion, people not in social interaction, non-goal-oriented action, and non-human sounds) lacking social content. These ratings were used as predictors in the fMRI analysis. The posterior superior temporal sulcus (STS) responded to all social features but not to any non-social features, and the anterior STS responded to all social features except bodies and biological motion. We also found four partially segregated, extended networks for processing of specific social signals: (1) a fronto-temporal network responding to multiple social categories, (2) a fronto-parietal network preferentially activated to bodies, motion, and pain, (3) a temporo-amygdalar network responding to faces, social interaction, and speech, and (4) a fronto-insular network responding to pain, emotions, social interactions, and speech. Our results highlight the role of the pSTS in processing multiple aspects of social information, as well as the feasibility and efficiency of fMRI mapping under conditions that resemble the complexity of real life. PMID:22905026

  6. Naturalistic FMRI mapping reveals superior temporal sulcus as the hub for the distributed brain network for social perception.

    Science.gov (United States)

    Lahnakoski, Juha M; Glerean, Enrico; Salmi, Juha; Jääskeläinen, Iiro P; Sams, Mikko; Hari, Riitta; Nummenmaa, Lauri

    2012-01-01

    Despite the abundant data on brain networks processing static social signals, such as pictures of faces, the neural systems supporting social perception in naturalistic conditions are still poorly understood. Here we delineated brain networks subserving social perception under naturalistic conditions in 19 healthy humans who watched, during 3-T functional magnetic resonance imaging (fMRI), a set of 137 short (approximately 16 s each, total 27 min) audiovisual movie clips depicting pre-selected social signals. Two independent raters estimated how well each clip represented eight social features (faces, human bodies, biological motion, goal-oriented actions, emotion, social interaction, pain, and speech) and six filler features (places, objects, rigid motion, people not in social interaction, non-goal-oriented action, and non-human sounds) lacking social content. These ratings were used as predictors in the fMRI analysis. The posterior superior temporal sulcus (STS) responded to all social features but not to any non-social features, and the anterior STS responded to all social features except bodies and biological motion. We also found four partially segregated, extended networks for processing of specific social signals: (1) a fronto-temporal network responding to multiple social categories, (2) a fronto-parietal network preferentially activated to bodies, motion, and pain, (3) a temporo-amygdalar network responding to faces, social interaction, and speech, and (4) a fronto-insular network responding to pain, emotions, social interactions, and speech. Our results highlight the role of the pSTS in processing multiple aspects of social information, as well as the feasibility and efficiency of fMRI mapping under conditions that resemble the complexity of real life.

  7. Naturalistic fMRI mapping reveals superior temporal sulcus as the hub for the distributed brain network for social perception

    Directory of Open Access Journals (Sweden)

    Juha Marko Lahnakoski

    2012-08-01

    Full Text Available Despite the abundant data on brain networks processing static social signals, such as pictures of faces, the neural systems supporting social perception in naturalistic conditions are still poorly understood. Here we delineated brain networks subserving social perception under naturalistic conditions in 19 healthy humans who watched, during 3-tesla functional magnetic imaging (fMRI, a set of 137 short (~16 s each, total 27 min audiovisual movie clips depicting pre-selected social signals. Two independent raters estimated how well each clip represented eight social features (faces, human bodies, biological motion, goal-oriented actions, emotion, social interaction, pain, and speech and six filler features (places, objects, rigid motion, people not in social interaction, non-goal-oriented action and non-human sounds lacking social content. These ratings were used as predictors in the fMRI analysis. The posterior superior temporal sulcus (STS responded to all social features but not to any non-social features, and the anterior STS responded to all social features except bodies and biological motion. We also found four partially segregated, extended networks for processing of specific social signals: 1 a fronto-temporal network responding to multiple social categories, 2 a fronto-parietal network preferentially activated to bodies, motion and pain, 3 a temporo-amygdalar network responding to faces, social interaction and speech, and 4 a fronto-insular network responding to pain, emotions, social interactions, and speech. Our results highlight the role of the posterior STS in processing multiple aspects of social information, as well as the feasibility and efficiency of fMRI mapping under conditions that resemble the complexity of real life.

  8. [The Second Health Care Market: Market Mapping Based upon Consumer Perception].

    Science.gov (United States)

    Teichert, T; Mühlbach, C

    2016-04-14

    Introduction: The aim of the study was to present a picture of consumers' views on the specific market of health and health products, the second German health market. Market analysis of the product categories was carried out. Methods: A large-scale representative survey (N=1 033) determined with an innovative adaptation of the repertory grid method the consumer's perspective on the specific market. Basic questions concerning attitudes to health as well as healthy behaviors completed the telephone survey. Results: In the saturated markets, market for health is growing, especially in the context of aging societies, and this is not limited to primary medical products. In this study, product categories such as "dental care", "fruit and vegetables" or "nuts" were classified as healthy products. Conclusion: The relevance of health also in the macroeconomic context has been long underestimated. Health has still a high priority for consumers. A disclosure of individual perceptions in the health context provides a significantly more relevant product design. The identification of healthy product dimensions from the consumer's perspective sheds light on the actually desired product properties and the available potential to meet these desires.

  9. InSAR measurement of surface deformation at the Hanford Reservation associated with the 2009 Wooded Island earthquake swarm (Invited)

    Science.gov (United States)

    Wicks, C. W.; Gomberg, J. S.; Weaver, C. S.

    2009-12-01

    Earthquake swarms are frequent in much of eastern Washington. Earthquakes in these swarms typically are in the range of magnitude 1 to 3 and are often shallow with depths of a few kilometers. The most recent swarm of small earthquakes occurred from January 2009 through July 2009 and was located near Wooded Island 15 km north of Richland, Washington on the southeastern corner of the Hanford Reservation. The swarm location is along the eastern edge of the Yakima Fold and Thrust Belt, where swarm activity appears to be common. The Wooded Island swarm location is about 10 km northeast of the northwest-striking Rattlesnake Mountain fault and about 10 km south of the Gable Mountain fault that strikes west-northwest. Both of these mapped faults are associated with major thrusts that deform the Columbia River basalts, but the relation between these faults and the current swarm location is unknown. Although there have been at least two other swarms near Wooded Island in the last 30 years, the current swarm is of particular interest because we are able to map the surface deformation associated with the swarm with multi-temporal InSAR images from the European Space Agency’s ENVISAT satellite. We find two clear “pods” of deformation in interferograms generated from the satellite data, coincident with the distribution of the swarm hypocenters. We measure about 35 mm of peak surface deformation in the satellite line-of-sight direction. The deformation became resolvable in interferograms after the end of February 2009, when seismicity rates were highest. Preliminary modeling of the deformation is consistent with two small (about two km long) reverse faults each striking west-northwest with nearly 50 mm of slip. The geodetically estimated slip exceeds the seismic slip significantly, suggesting that the swarm was driven by aseismic creep. One of the modeled faults is well constrained to be shallow, about 200 m deep, and both faults occur within the underlying ~3 km thick

  10. Cooperative Control of Swarms of Unmanned Aerial Vehicles

    NARCIS (Netherlands)

    De Vries, E.; Subbarao, K.

    2011-01-01

    Potential function based swarm control is a technique using artificial potential functions to generate steering commands resulting in swarming behavior. This means that the vehicles in the swarm autonomously take care of flying in formation, resulting in steering the swarm, instead of all the indivi

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

    DEFF Research Database (Denmark)

    Bothe, Hans-Heinrich

    . Dependent on the training data, these other units may also be contextually immediate neighboring units. The poster demonstrates the idea with text material spoken by one individual subject using a set of simple audio-visual features. The data material for the training process consists of 44 labeled...... visual lip features is used. Phoneme-related receptive fields result on the SOM basis; they are speaker dependent and show individual locations and strain. Overlapping main slopes indicate a high similarity of respective units; distortion or extra peaks originate from the influence of other units...... sentences in German with a balanced phoneme repertoire. As a result it can be stated that (i) the SOM can be trained to map auditory and visual features in a topology-preserving way and (ii) they show strain due to the influence of other audio-visual units. The SOM can be used to measure similarity amongst...

  12. Seismic Swarms at Paricutin Volcano Area. Magmatic Intrusion or Tectonic Seismicity?

    Science.gov (United States)

    Pinzon, J. I.; Nunez-Cornu, F. J.; Escudero, C. R.; Rowe, C. A.

    2014-12-01

    We relocate a seismic swarm with more than 700 earthquakes that took place between May and June 2006 in the Paricutin volcano area, Mexico inside of the Michoacan monogenetic volcanic field. This seismic swarm was recorded by the project "Mapping the Riviera Subduction Zone" (MARS), a temporary seismic network that was installed in the states of Jalisco, Colima and Michoacán between January 2006 and June 2007. Previously seismic swarms in the area were reported in the years of 1997, 1999 and 2000. For one that took place in the year of 1997 the Servicio Sismologico Nacional deployed a local network in the area, they conclude that the source of the seismicity was tectonic with depths between 18 and 12 km. The episodes of 1999 and 2000 were reported as similar to the 1997 swarm. A previous analysis of the 2006 swarm concludes that the depth of seismicity migrates from 9 to 5 km and was originated by a magmatic intrusion. We did a relocation of this swarm reading all the events and using Hypo71 and the P-wave velocity model used by the Jalisco Seismic and Acelerometric Network; a waveform analysis using cross-correlation method was also carried out. We obtained 15 earthquakes families with a correlation factor equal or greater than 0.79 and composed focal mechanism for each family. These families present a migration in depth beginning at 16 km and ended at 9 km. Our results agrees with a magmatic intrusion, but not so shallow as the previous study of the 2006 swarm.

  13. COPD care delivery pathways in five European Union countries: mapping and health care professionals’ perceptions

    Science.gov (United States)

    Kayyali, Reem; Odeh, Bassel; Frerichs, Inéz; Davies, Nikki; Perantoni, Eleni; D’arcy, Shona; Vaes, Anouk W; Chang, John; Spruit, Martijn A; Deering, Brenda; Philip, Nada; Siva, Roshan; Kaimakamis, Evangelos; Chouvarda, Ioanna; Pierscionek, Barbara; Weiler, Norbert; Wouters, Emiel FM; Raptopoulos, Andreas; Nabhani-Gebara, Shereen

    2016-01-01

    Background COPD is among the leading causes of chronic morbidity and mortality in the European Union with an estimated annual economic burden of €25.1 billion. Various care pathways for COPD exist across Europe leading to different responses to similar problems. Determining these differences and the similarities may improve health and the functioning of health services. Objective The aim of this study was to compare COPD patients’ care pathway in five European Union countries including England, Ireland, the Netherlands, Greece, and Germany and to explore health care professionals’ (HCPs) perceptions about the current pathways. Methods HCPs were interviewed in two stages using a qualitative, semistructured email interview and a face-to-face semistructured interview. Results Lack of communication among different health care providers managing COPD and comorbidities was a common feature of the studied care pathways. General practitioners/family doctors are responsible for liaising between different teams/services, except in Greece where this is done through pulmonologists. Ireland and the UK are the only countries with services for patients at home to shorten unnecessary hospital stay. HCPs emphasized lack of communication, limited resources, and poor patient engagement as issues in the current pathways. Furthermore, no specified role exists for pharmacists and informal carers. Conclusion Service and professional integration between care settings using a unified system targeting COPD and comorbidities is a priority. Better communication between health care providers, establishing a clear role for informal carers, and enhancing patients’ engagement could optimize current care pathways resulting in a better integrated system. PMID:27881915

  14. Increasing support for contraception as HIV prevention: stakeholder mapping to identify influential individuals and their perceptions.

    Directory of Open Access Journals (Sweden)

    Tricia Petruney

    Full Text Available BACKGROUND: Voluntary contraceptive use by HIV-positive women currently prevents more HIV-positive births, at a lower cost, than anti-retroviral drug (ARV regimens. Despite this evidence, most prevention of mother-to-child transmission (PMTCT programs focus solely on providing ARV prophylaxis to pregnant women and rarely include the prevention of unintended pregnancies among HIV-positive women. METHODOLOGY/PRINCIPAL FINDINGS: To strengthen support for family planning as HIV prevention, we systematically identified key individuals in the field of international HIV/AIDS-those who could potentially influence the issue-and sought to determine their perceptions of barriers to and facilitators for implementing this PMTCT strategy. We used a criteria-based approach to determine which HIV/AIDS stakeholders have the most significant impact on HIV/AIDS research, programs, funding and policy and stratified purposive sampling to conduct interviews with a subset of these individuals. The interview findings pointed to obstacles to strengthening linkages between family planning and HIV/AIDS, including the need for: resources to integrate family planning and HIV services, infrastructure or capacity to provide integrated services at the facility level, national leadership and coordination, and targeted advocacy to key decision-makers. CONCLUSIONS/SIGNIFICANCE: The individuals we identified as having regional or international influence in the field of HIV/AIDS have the ability to leverage an increasingly conducive funding environment and a growing evidence base to address the policy, programmatic and operational challenges to integrating family planning with HIV/AIDS. Fostering greater support for implementing contraception for HIV prevention will require the dedication, collaboration and coordination of many such actors. Our findings can inform a targeted advocacy campaign.

  15. The precursory earthquake swarm in Greece

    Directory of Open Access Journals (Sweden)

    D. Rhoades

    2000-06-01

    Full Text Available The Hellenic subduction region displays the same precursory swarm phenomenon as has been found in comparable regions of New Zealand and Japan. In the earthquake catalogue of the Aristotle University of Thessaloniki, 10 past sequences of precursory swarms and related major mainshock events have been identified. These correlate, in respect of location, magnitude and time, with the 9 sequences previously identified in New Zealand, and 9 in Japan, bringing the total of sequences to 28, and the totals of related events (allowing for clustering to 56 precursory swarms and 42 mainshock events. The results add strength to the hypothesis that swarms are long-range predictors of mainshock events. A close similarity between the swarm and aftershock magnitudes in a given sequence is also confirmed in Greece, supporting the proposal that swarms are an integral part of the seismogenic process in subduction regions. Further, the modelling of swarms as part of an overall increase in seismicity, the onset of which marks the onset of seismogenesis, is well illustrated from past sequences in Greece. Formal tests are being carried out in Greece, in parallel with New Zealand and Japan, to ascertain the performance of the hypothesis as a basis for long-range synoptic forecasting.

  16. A Concept Mapping Study of Physicians’ Perceptions of Factors Influencing Management and Control of Hypertension in Sub-Saharan Africa

    Directory of Open Access Journals (Sweden)

    Juliet Iwelunmor

    2015-01-01

    Full Text Available Hypertension, once a rare problem in Sub-Saharan Africa (SSA, is predicted to be a major cause of death by 2020 with mortality rates as high as 75%. However, comprehensive knowledge of provider-level factors that influence optimal management is limited. The objective of the current study was to discover physicians’ perceptions of factors influencing optimal management and control of hypertension in SSA. Twelve physicians attending the Cardiovascular Research Training (CaRT Institute at the University of Ghana, College of Health Sciences, were invited to complete a concept mapping process that included brainstorming the factors influencing optimal management and control of hypertension in patients, sorting and organizing the factors into similar domains, and rating the importance and feasibility of efforts to address these factors. The highest ranked important and feasible factors include helping patients accept their condition and availability of adequate equipment to enable the provision of needed care. The findings suggest that patient self-efficacy and support, physician-related factors, policy factors, and economic factors are important aspects that must be addressed to achieve optimal hypertension management. Given the work demands identified by physicians, future research should investigate cost-effective strategies of shifting physician responsibilities to well-trained no-physician clinicians in order to improve hypertension management.

  17. Changes in Earth's core-generated magnetic field, as observed by Swarm

    DEFF Research Database (Denmark)

    Finlay, Chris; Olsen, Nils; Gillet, Nicolas

    By far the largest part of the Earth's magnetic field is generated by motions taking place within our planet's liquid metal outer core. Variations of this core-generated field thus provide us with a unique means of probing the dynamics taking place in the deepest reaches of the Earth....... In this contribution, we will present the core-generated magnetic field, and its recent time changes, as seen by ESA's Earth explorer mission Swarm. We will present a new time-dependent geomagnetic field model, called CHAOS-6, derived from satellite data collected by the Swarm constellation, as well as data from...... of the source region, the core-mantle boundary, we present maps of the detailed structure of the geodynamo, and how this is presently evolving. Both the trend (secular variation) and accelerations in the field changes since the launch of the Swarm mission will be presented. Assuming that field changes...

  18. COPD care delivery pathways in five European Union countries: mapping and health care professionals’ perceptions

    Directory of Open Access Journals (Sweden)

    Kayyali R

    2016-11-01

    Full Text Available Reem Kayyali,1 Bassel Odeh,1 Inéz Frerichs,2 Nikki Davies,3 Eleni Perantoni,4 Shona D’arcy,5 Anouk W Vaes,6 John Chang,3 Martijn A Spruit,6 Brenda Deering,7 Nada Philip,1 Roshan Siva,3 Evangelos Kaimakamis,8 Ioanna Chouvarda,8 Barbara Pierscionek,1 Norbert Weiler,2 Emiel FM Wouters,6 Andreas Raptopoulos,9 Shereen Nabhani-Gebara1 1Faculty of Science, Engineering and Computing, Kingston University, Kingston-Upon-Thames, UK; 2Department of Anaesthesiology and Intensive Care Medicine, University Medical Centre Schleswig-Holstein, Kiel, Germany; 3Chest Clinic and Research and Development, Croydon University Hospital, Croydon, UK; 4Pulmonary Clinic, AHEPA University Hospital, Thessaloniki, Greece; 5Department of Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland; 6Research and Education, CIRO – Centre of Expertise for Chronic Organ Failure, Horn, the Netherlands; 7COPD Outreach, Beaumont Hospital, Dublin, Ireland; 8Medical School, Aristotle University, Thessaloniki, 9Research and Development, Exodus Information Technology SA, Athens, Greece Background: COPD is among the leading causes of chronic morbidity and mortality in the European Union with an estimated annual economic burden of €25.1 billion. Various care pathways for COPD exist across Europe leading to different responses to similar problems. Determining these differences and the similarities may improve health and the functioning of health services.Objective: The aim of this study was to compare COPD patients’ care pathway in five European Union countries including England, Ireland, the Netherlands, Greece, and Germany and to explore health care professionals’ (HCPs perceptions about the current pathways.Methods: HCPs were interviewed in two stages using a qualitative, semistructured email interview and a face-to-face semistructured interview.Results: Lack of communication among different health care providers managing COPD and comorbidities was a common feature of the

  19. Mapping the Developmental Trajectory and Correlates of Enhanced Pitch Perception on Speech Processing in Adults with ASD

    Science.gov (United States)

    Mayer, Jennifer L.; Hannent, Ian; Heaton, Pamela F.

    2016-01-01

    Whilst enhanced perception has been widely reported in individuals with Autism Spectrum Disorders (ASDs), relatively little is known about the developmental trajectory and impact of atypical auditory processing on speech perception in intellectually high-functioning adults with ASD. This paper presents data on perception of complex tones and…

  20. Immunity clone algorithm with particle swarm evolution

    Institute of Scientific and Technical Information of China (English)

    LIU Li-jue; CAI Zi-xing; CHEN Hong

    2006-01-01

    Combining the clonal selection mechanism of the immune system with the evolution equations of particle swarm optimization, an advanced algorithm was introduced for functions optimization. The advantages of this algorithm lies in two aspects.Via immunity operation, the diversity of the antibodies was maintained, and the speed of convergent was improved by using particle swarm evolution equations. Simulation programme and three functions were used to check the effect of the algorithm. The advanced algorithm were compared with clonal selection algorithm and particle swarm algorithm. The results show that this advanced algorithm can converge to the global optimum at a great rate in a given range, the performance of optimization is improved effectively.

  1. A field guide to bacterial swarming motility.

    Science.gov (United States)

    Kearns, Daniel B

    2010-09-01

    How bacteria regulate, assemble and rotate flagella to swim in liquid media is reasonably well understood. Much less is known about how some bacteria use flagella to move over the tops of solid surfaces in a form of movement called swarming. The focus of bacteriology is changing from planktonic to surface environments, and so interest in swarming motility is on the rise. Here, I review the requirements that define swarming motility in diverse bacterial model systems, including an increase in the number of flagella per cell, the secretion of a surfactant to reduce surface tension and allow spreading, and movement in multicellular groups rather than as individuals.

  2. Vertical pipe inspection using swarm of independent robots

    Energy Technology Data Exchange (ETDEWEB)

    Pellizzari, D.; Ramirez-Serrano, A. [Calgary Univ., AB (Canada). Dept. of Mechanical and Manufacturing Engineering; Pettinaro, G.C. [Scuola Univ. Professionale della Svizzera Italiana, Canton Ticino (Switzerland). Inst. Dalle Molle di Studi sull' Intelligenza Artificiale

    2004-07-01

    This study investigated the use of multiple small robots for pipeline inspection operations. A team of autonomous s-bots were used. The s-bots were comprised of a traction system; a turret; a gripper for tight grasps; and an extensible gripper for keeping loose physical contacts with other peers. The robots were designed to collaborate with each other by connecting firmly or loosely together in different structures called swarm-bots. Communication between the s-bots was conducted by means of stigmergy and local perception. The robots are equipped with an omni-directional CCD camera; microphones; IR proximity sensors; accelerometers; and inclinometers. The s-bots were designed to be used for scouting purposes, but can be reconfigured and synchronized for a variety of different tasks. The robots comprising a swarm can climb the inner vertical walls of pipes by exerting a force towards the pipe walls and by jointly moving forward at the same time. The robots are able to monitor their peers as well as the integrity of the pipe surface by using the cameras attached to their heads and the light emitter diodes and diverse light sensors located on the grippers. When one robot detects an unusual condition, it can alert the other robots by lighting up. A reactive controller that uses artificial neural networks (ANNs) and a knowledge-based system (KBS) to control how the s-bots move in a connected formation inside vertical pipes has also been proposed. It was concluded that the swarm-bots will be able to effectively inspect diverse pipe configurations. 20 refs., 6 figs.

  3. Scalar transport by planktonic swarms

    Science.gov (United States)

    Martinez-Ortiz, Monica; Dabiri, John O.

    2012-11-01

    Nutrient and energy transport in the ocean is primarily governed by the action of physical phenomena. In previous studies it has been suggested that aquatic fauna may significantly contribute to this process through the action of the induced drift mechanism. In this investigation, the role of planktonic swarms as ecosystem engineers is assessed through the analysis of scalar transport within a stratified water column. The vertical migration of Artemia salina is controlled via luminescent signals on the top and bottom of the column. The scalar transport of fluorescent dye is visualized and quantified through planar laser induced fluorescence (PLIF). Preliminary results show that the vertical movement of these organisms enhances scalar transport relative to control cases in which only buoyancy forces and diffusion are present. Funded by the BSF program (2011553).

  4. A Swarm of Ancient Stars

    Science.gov (United States)

    1999-01-01

    This stellar swarm is M80 (NGC 6093), one of the densest of the 147 known globular star clusters in the Milky Way galaxy. Located about 28,000 light-years from Earth, M80 contains hundreds of thousands of stars, all held together by their mutual gravitational attraction. Globular clusters are particularly useful for studying stellar evolution, since all of the stars in the cluster have the same age (about 15 billion years), but cover a range of stellar masses. Every star visible in this image is either more highly evolved than, or in a few rare cases more massive than, our own Sun. Especially obvious are the bright red giants, which are stars similar to the Sun in mass that are nearing the ends of their lives.

  5. Swarm-Based Spatial Sorting

    CERN Document Server

    Amos, Martyn

    2008-01-01

    Purpose: To present an algorithm for spatially sorting objects into an annular structure. Design/Methodology/Approach: A swarm-based model that requires only stochastic agent behaviour coupled with a pheromone-inspired "attraction-repulsion" mechanism. Findings: The algorithm consistently generates high-quality annular structures, and is particularly powerful in situations where the initial configuration of objects is similar to those observed in nature. Research limitations/implications: Experimental evidence supports previous theoretical arguments about the nature and mechanism of spatial sorting by insects. Practical implications: The algorithm may find applications in distributed robotics. Originality/value: The model offers a powerful minimal algorithmic framework, and also sheds further light on the nature of attraction-repulsion algorithms and underlying natural processes.

  6. Mapping hospice patients' perception and verbal communication of end-of-life needs: an exploratory mixed methods inquiry

    Directory of Open Access Journals (Sweden)

    Arnold Bruce L

    2011-01-01

    Full Text Available Abstract Background Comprehensive "Total Pain" assessments of patients' end-of-life needs are critical for providing improved patient-clinician communication, assessing needs, and offering high quality palliative care. However, patients' needs-based research methodologies and findings remain highly diverse with their lack of consensus preventing optimum needs assessments and care planning. Mixed-methods is an underused yet robust "patient-based" approach for reported lived experiences to map both the incidence and prevalence of what patients perceive as important end of life needs. Methods Findings often include methodological artifacts and their own selection bias. Moving beyond diverse findings therefore requires revisiting methodological choices. A mixed methods research cross-sectional design is therefore used to reduce limitations inherent in both qualitative and quantitative methodologies. Audio-taped phenomenological "thinking aloud" interviews of a purposive sample of 30 hospice patients are used to identify their vocabulary for communicating perceptions of end-of-life needs. Grounded theory procedures assisted by QSR-NVivo software is then used for discovering domains of needs embedded in the interview narratives. Summary findings are translated into quantified format for presentation and analytical purposes. Results Findings from this mixed-methods feasibility study indicate patients' narratives represent 7 core domains of end-of-life needs. These are (1 time, (2 social, (3 physiological, (4 death and dying, (5 safety, (6 spirituality, (7 change & adaptation. The prevalence, rather than just the occurrence, of patients' reported needs provides further insight into their relative importance. Conclusion Patients' perceptions of end-of-life needs are multidimensional, often ambiguous and uncertain. Mixed methodology appears to hold considerable promise for unpacking both the occurrence and prevalence of cognitive structures represented by

  7. Swarm Intelligence in Text Document Clustering

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Xiaohui [ORNL; Potok, Thomas E [ORNL

    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 in 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.

  8. Intelligent Mobile Olfaction of Swarm Robots

    National Research Council Canada - National Science Library

    Siti Nurmaini; Bambang Tutuko; Aulia Rahman Thoharsin

    2013-01-01

      This work presents intelligent mobile olfaction design and experimental results of intelligent swarm robots to detection a gas/odour source in an indoor environment by using multi agent based on hybrid algorithm...

  9. Locating multiple optima using particle swarm optimization

    CSIR Research Space (South Africa)

    Brits, R

    2007-01-01

    Full Text Available Many scientific and engineering applications require optimization methods to find more than one solution to multimodal optimization problems. This paper presents a new particle swarm optimization (PSO) technique to locate and refine multiple...

  10. A REVIEW OF SWARMING UNMANNED AERIAL VEHICLES

    Directory of Open Access Journals (Sweden)

    CORNEA Mihai

    2016-11-01

    Full Text Available This paper in if fact an overview of state of the art in mobile multi-robot systems as an initial part of our research in implementing a system based on swarm robotics concepts to be used in natural disaster search and rescue missions. The system is to be composed of a group of drones that can detect survivor mobile cell signals and exhibit some other features as well. This paper surveys the swarm robotics research landscape to provide a theoretical background to the implementation and help determine the techniques available to create the system. The Particle swarm optimization (PSO and Glowworm swarm optimization (GSO algorithms are briefly described and there is also insight into Bird flocking behavior and the model behind it

  11. Gene expression in Pseudomonas aeruginosa swarming motility

    Directory of Open Access Journals (Sweden)

    Déziel Eric

    2010-10-01

    Full Text Available Abstract Background The bacterium Pseudomonas aeruginosa is capable of three types of motilities: swimming, twitching and swarming. The latter is characterized by a fast and coordinated group movement over a semi-solid surface resulting from intercellular interactions and morphological differentiation. A striking feature of swarming motility is the complex fractal-like patterns displayed by migrating bacteria while they move away from their inoculation point. This type of group behaviour is still poorly understood and its characterization provides important information on bacterial structured communities such as biofilms. Using GeneChip® Affymetrix microarrays, we obtained the transcriptomic profiles of both bacterial populations located at the tip of migrating tendrils and swarm center of swarming colonies and compared these profiles to that of a bacterial control population grown on the same media but solidified to not allow swarming motility. Results Microarray raw data were corrected for background noise with the RMA algorithm and quantile normalized. Differentially expressed genes between the three conditions were selected using a threshold of 1.5 log2-fold, which gave a total of 378 selected genes (6.3% of the predicted open reading frames of strain PA14. Major shifts in gene expression patterns are observed in each growth conditions, highlighting the presence of distinct bacterial subpopulations within a swarming colony (tendril tips vs. swarm center. Unexpectedly, microarrays expression data reveal that a minority of genes are up-regulated in tendril tip populations. Among them, we found energy metabolism, ribosomal protein and transport of small molecules related genes. On the other hand, many well-known virulence factors genes were globally repressed in tendril tip cells. Swarm center cells are distinct and appear to be under oxidative and copper stress responses. Conclusions Results reported in this study show that, as opposed to

  12. Creativity and Autonomy in Swarm Intelligence Systems

    OpenAIRE

    al-Rifaie, Mohammad Majid; Bishop,Mark; Caines, Suzanne

    2012-01-01

    This work introduces two swarm intelligence algorithms -- one mimicking the behaviour of one species of ants (\\emph{Leptothorax acervorum}) foraging (a `Stochastic Diffusion Search', SDS) and the other algorithm mimicking the behaviour of birds flocking (a `Particle Swarm Optimiser', PSO) -- and outlines a novel integration strategy exploiting the local search properties of the PSO with global SDS behaviour. The resulting hybrid algorithm is used to sketch novel drawings of an input image, ex...

  13. UAV Swarm Operational Risk Assessment system

    OpenAIRE

    Marfo, Sariyu; Ehler, Shane; Fields, Ryan; Negron, Jamaries Benitez; Skopak, Shane; Junek, John; Zarzaca, Justin; Perrotta, Robert; Team CQ Alpha; Cohort 311-141A

    2015-01-01

    Approved for public release; distribution is unlimited This paper examines the need for a UAV Swarm Risk Assessment Tool and how it can assist the Navy’s decision makers in assessing risk of UAV swarm threats in littoral environments, near potentially hostile countries, based on the latest intelligence. Human-centered design principles help determine the needs of experienced battle commanders. These needs form the basis of requirements and functional analysis. The system design concept con...

  14. The Swarm Computing Approach to Business Intelligence

    Directory of Open Access Journals (Sweden)

    Schumann Andrew

    2015-07-01

    Full Text Available We have proposed to use some features of swarm behaviours in modelling business processes. Due to these features we deal with a propagation of business processes in all accessible directions. This propagation is involved into our formalization instead of communicating sequential processes. As a result, we have constructed a business process diagram language based on the swarm behavior and an extension of that language in the form of reflexive management language.

  15. Gravitational Lens Modeling with Genetic Algorithms and Particle Swarm Optimizers

    CERN Document Server

    Rogers, Adam

    2011-01-01

    Strong gravitational lensing of an extended object is described by a mapping from source to image coordinates that is nonlinear and cannot generally be inverted analytically. Determining the structure of the source intensity distribution also requires a description of the blurring effect due to a point spread function. This initial study uses an iterative gravitational lens modeling scheme based on the semilinear method to determine the linear parameters (source intensity profile) of a strongly lensed system. Our 'matrix-free' approach avoids construction of the lens and blurring operators while retaining the least squares formulation of the problem. The parameters of an analytical lens model are found through nonlinear optimization by an advanced genetic algorithm (GA) and particle swarm optimizer (PSO). These global optimization routines are designed to explore the parameter space thoroughly, mapping model degeneracies in detail. We develop a novel method that determines the L-curve for each solution automa...

  16. Heterogeneous architecture to process swarm optimization algorithms

    Directory of Open Access Journals (Sweden)

    Maria A. Dávila-Guzmán

    2014-01-01

    Full Text Available Since few years ago, the parallel processing has been embedded in personal computers by including co-processing units as the graphics processing units resulting in a heterogeneous platform. This paper presents the implementation of swarm algorithms on this platform to solve several functions from optimization problems, where they highlight their inherent parallel processing and distributed control features. In the swarm algorithms, each individual and dimension problem are parallelized by the granularity of the processing system which also offer low communication latency between individuals through the embedded processing. To evaluate the potential of swarm algorithms on graphics processing units we have implemented two of them: the particle swarm optimization algorithm and the bacterial foraging optimization algorithm. The algorithms’ performance is measured using the acceleration where they are contrasted between a typical sequential processing platform and the NVIDIA GeForce GTX480 heterogeneous platform; the results show that the particle swarm algorithm obtained up to 36.82x and the bacterial foraging swarm algorithm obtained up to 9.26x. Finally, the effect to increase the size of the population is evaluated where we show both the dispersion and the quality of the solutions are decreased despite of high acceleration performance since the initial distribution of the individuals can converge to local optimal solution.

  17. Guidance and control of swarms of spacecraft

    Science.gov (United States)

    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

  18. Mapping future changes in livelihood security and environmental sustainability based on perceptions of small farmers in the Brazilian Amazon

    Directory of Open Access Journals (Sweden)

    Fabio H. Diniz

    2015-06-01

    Full Text Available Deforestation is a widely recognized problem in the Brazilian Amazon. Small farmers play a key role in this process in that they earn their livelihood by ranching and farming. Many studies have addressed the link between deforestation and livelihood strategies adopted by small farmers. Most have focused on advanced monitoring systems, simulation models, and GIS approaches to analyze the interaction of both dimensions, i.e., livelihoods and forest cover change. Although the current toolbox of methods has proved successful in increasing our understanding of these interactions, the models and approaches employed do not consider small farmers' perspectives. On the assumption that local small farmers are agents of land-cover change, understanding how they perceive their own situation is essential to elucidate their actions. Our objective is to explore future changes in livelihood security and environmental sustainability as envisaged by local small farmers in the Brazilian Amazon. Previous livelihood cluster analysis of small farmers located in southeast Pará was integrated with fuzzy cognitive mapping to determine present perceptions and to explore future changes, using global scenarios downscaled to the local situation. Overall, system description differs only on details; all results indicate a strong trade-off between livelihood security and environmental sustainability in all livelihood systems, as identified by the small farmers. However, fundamentally different outcomes are obtained from the future analysis, depending on the livelihood strategy cluster. Achieving win-win outcomes does not necessarily imply a positive scenario, especially if small farmers are dependent on income transfers from the government to provide their livelihood.

  19. Swarming behavior of Aedes polynesiensis (Diptera: Culicidae) and characterization of swarm markers in American Samoa.

    Science.gov (United States)

    Tuten, H C; Stone, C M; Dobson, S L

    2013-07-01

    We characterize the swarming behavior of male Aedes polynesiensis (Marks) in American Samoa. Instead of swarming around a blood host, males used the base of certain trees as a marker. Repeated sampling proved nondestructive and allowed us to investigate the impact of static (e.g., tree species) and dynamic (e.g., barometric pressure) characters on the likelihood of swarm presence and intensity. Tree circumference and oviposition activity (number of Ae. polynesiensis reared from oviposition cups) were significant positive predictors of the number of males in a swarm. Tree circumference and diameter were significantly positively associated, and canopy height was significantly negatively associated, with swarm occurrence. Comparisons between males swarming early and late during the swarming period allowed for insight into swarm composition in terms of male size and the amount of putative fluid (e.g., nectar) in the crop, indicators of energetic reserves. Males collected during the late period had significantly larger wings and less crop contents than did males of the early cohort. Because the ecology of male Ae. polynesiensis remains understudied, we consider how the current results could facilitate further studies related to applied autocidal strategies as well as the evolution of host-based mating behavior.

  20. Merging the fields of swarm robotics and new media: Perceiving swarm robotics as new media

    Directory of Open Access Journals (Sweden)

    Monika O. Ivanova

    2014-06-01

    Full Text Available The aim of this paper is to provide evidence that swarm robotic systems can be perceived as new media objects. A thorough description of the five principles of new media proposed by Lev Manovich in “The Language of New Media” is presented. This is complemented by a state of the art on swarm robotics with an in-depth comparison of the characteristics of both fields. Also presented are examples of swarm robotics used in new media installations in order to illustrate the cutting-edge applications of robotics and artificial intelligence achieved through the unity of bothfields. The hypothesis of this research is that a novel point of view would be introduced by examining the field of swarm robotics through the scope of new media, which would benefit thework of both new media and swarm robotic researchers.

  1. Precise Localization and Formation Control of Swarm Robots via Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Han Wu

    2014-01-01

    Full Text Available Precise localization and formation control are one of the key technologies to achieve coordination and control of swarm robots, which is also currently a bottleneck for practical applications of swarm robotic systems. Aiming at overcoming the limited individual perception and the difficulty of achieving precise localization and formation, a localization approach combining dead reckoning (DR with wireless sensor network- (WSN- based methods is proposed in this paper. Two kinds of WSN localization technologies are adopted in this paper, that is, ZigBee-based RSSI (received signal strength indication global localization and electronic tag floors for calibration of local positioning. First, the DR localization information is combined with the ZigBee-based RSSI position information using the Kalman filter method to achieve precise global localization and maintain the robot formation. Then the electronic tag floors provide the robots with their precise coordinates in some local areas and enable the robot swarm to calibrate its formation by reducing the accumulated position errors. Hence, the overall performance of localization and formation control of the swarm robotic system is improved. Both of the simulation results and the experimental results on a real schematic system are given to demonstrate the success of the proposed approach.

  2. The Fate of Colloidal Swarms in Fractures

    Science.gov (United States)

    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

  3. The Characteristics of Earthquake Swarms in and around Jiangsu Province

    Institute of Scientific and Technical Information of China (English)

    Huang Yun; Tian Jianming; Miao Ali

    2011-01-01

    This paper systematically analyzed 36 earthquake swarms in and around Jiangsu Province, summarized their characteristics and discussed the relationship between earthquske swarms and subsequent strong earthquakes. It also analyzed the judgment criteria for precursory earthquake swarms. Earthquake swarms in Jiangsu Province are concentrated in several areas. Most of them were of magnitude ML2. 0 ~ 3. 9. For most earthquake swarms, the number of earthquakes was less than 30. Time duration for about 55% of earthquake swarms was less than 15 days. The biggest magnitude of one earthquake swarm was not proportional to the number of earthquakes and time duration. There are 78% of earthquake swarms corresponded to the forthcoming earthquakes of M 〉 4. 6 in which there're 57% occured in one year, This shows a medium- and short-term criterion. Distance between earthquake swarm and future earthquake was distributed dispersedly. There were no earthquakes occurring in the same location as earthquake swarms. There was no good correlation between the magnitude and the corresponding rate of future earthquakes and the intensity of earthquake swarms. There was also no good correlation between the number of earthquakes in an earthquake swarm and the corresponding rate. The study also shows that it's better to use U-p or whole-combination to determine the type of earthquake swarm.

  4. Neuroanatomical substrates of action perception and understanding: an anatomic likelihood estimation meta-analysis of lesion-symptom mapping studies in brain injured patients.

    Directory of Open Access Journals (Sweden)

    Cosimo eUrgesi

    2014-05-01

    Full Text Available Several neurophysiologic and neuroimaging studies suggested that motor and perceptual systems are tightly linked along a continuum rather than providing segregated mechanisms supporting different functions. Using correlational approaches, these studies demonstrated that action observation activates not only visual but also motor brain regions. On the other hand, brain stimulation and brain lesion evidence allows tackling the critical question of whether our action representations are necessary to perceive and understand others’ actions. In particular, recent neuropsychological studies have shown that patients with temporal, parietal and frontal lesions exhibit a number of possible deficits in the visual perception and the understanding of others’ actions. The specific anatomical substrates of such neuropsychological deficits however are still a matter of debate. Here we review the existing literature on this issue and perform an anatomic likelihood estimation meta-analysis of studies using lesion-symptom mapping methods on the causal relation between brain lesions and non-linguistic action perception and understanding deficits. The meta-analysis encompassed data from 361 patients tested in 11 studies and identified regions in the inferior frontal cortex, the inferior parietal cortex and the middle/superior temporal cortex, whose damage is consistently associated with poor performance in action perception and understanding tasks across studies. Interestingly, these areas correspond to the three nodes of the action observation network that are strongly activated in response to visual action perception in neuroimaging research and that have been targeted in previous brain stimulation studies. Thus, brain lesion mapping research provides converging causal evidence that premotor, parietal and temporal regions play a crucial role in action recognition and understanding.

  5. Comparative biochemical and molecular evaluation of swarming of ...

    African Journals Online (AJOL)

    Administrator

    swarming of Proteus and effects of anti-swarm agents. Iwalokun BA1* ... virulent Proteus strains, the laboratory use of urea and SDS is suggested. Key words: ... strains is not yet advanced. ... swarm agents were extracted using the alkaline lysis procedure of ... Proteus strain standardized to 1 x 108 cfu/ml with phosphate.

  6. Modified chaotic ant swarm to function optimization

    Institute of Scientific and Technical Information of China (English)

    LI Yu-ying; WEN Qiao-yan; LI Li-xiang

    2009-01-01

    The chaotic ant swarm algorithm (CAS) is an optimization algorithm based on swarm intelligence theory, and it is inspired by the chaotic and self-organizing behavior of the ants in nature. Based on the analysis of the properties of the CAS, this article proposes a variation on the CAS called the modified chaotic ant swarm (MCAS), which employs two novel strategies to significantly improve the performance of the original algorithm. This is achieved by restricting the variables to search ranges and making the global best ant to learn from different ants' best information in the end. The simulation of the MCAS on five benchmark functions shows that the MCAS improves the precision of the solution.

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

    DEFF Research Database (Denmark)

    Olsen, Nils; Friis-Christensen, Eigil; Floberghagen, R.

    2013-01-01

    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...

  8. Bacterial Swarming: social behaviour or hydrodynamics?

    Science.gov (United States)

    Vermant, Jan

    2010-03-01

    Bacterial swarming of colonies is typically described as a social phenomenon between bacteria, whereby groups of bacteria collectively move atop solid surfaces. This multicellular behavior, during which the organized bacterial populations are embedded in an extracellular slime layer, is connected to important features such as biofilm formation and virulence. Despite the possible intricate quorum sensing mechanisms that regulate swarming, several physico-chemical phenomena may play a role in the dynamics of swarming and biofilm formation. Especially the striking fingering patterns formed by some swarmer colonies on relatively soft sub phases have attracted the attention as they could be the signatures of an instability. Recently, a parallel has been drawn between the swarming patterns and the spreading of viscous drops under the influence of a surfactant, which lead to similar patterns [1]. Starting from the observation that several of the molecules, essential in swarming systems, are strong biosurfactants, the possibility of flows driven by gradients in surface tension, has been proposed. This Marangoni flows are known to lead to these characteristic patterns. For Rhizobium etli not only the pattern formation, but also the experimentally observed spreading speed has been shown to be consistent with the one expected for Marangoni flows for the surface pressures, thickness, and viscosities that have been observed [2]. We will present an experimental study of swarming colonies of the bacteria Pseudomonas aeruginosa, the pattern formation, the surfactant gradients and height profiles in comparison with predictions of a thin film hydrodynamic model.[4pt] [1] Matar O.K. and Troian S., Phys. Fluids 11 : 3232 (1999)[0pt] [2] Daniels, R et al., PNAS, 103 (40): 14965-14970 (2006)

  9. Automatic identification of seismic swarms and other spatio-temporal clustering from catalogs

    Science.gov (United States)

    Nava, F. Alejandro; Glowacka, Ewa

    1994-06-01

    Statistical analysis of seismic catalogs usually requires identification of swarms and foreshocks-main event-aftershocks sequences-a tedious and time-consuming chore. SWaRMSHoW, a simple but versatile QBASIC program for PC, graphically displays on screen catalog epicentral activity, with optional temporal distribution scaling; identifies spatio-temporal hypocentral clusters (SwrSeq) which may be swarms or foreshocks-main event-aftershocks sequences and discriminates between these; and displays SwrSeq locations and limits, and assigns them equivalent magnitudes corresponding to those of single events having seismic energy equal to that of the whole SwrSeq. SWaRMSHoW features optional detailed disk output of swarms and clusters, including origin time, location, constituent events, equivalent magnitudes, and current parameters, that allows easy application of results. Graphic screen display includes optional maps and drawings. Operation can be completely automatic or interactive. Working parameters can be reset at any time during operation. Besides swarm and sequence identification, this program's modeling of the seismicity, scaled in both space and time, is useful for studying many aspects of spatio-temporal seismicity, such as fault activation, migration of activity, quiescence, etc.

  10. Software Engineering and Swarm-Based Systems

    Science.gov (United States)

    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.

  11. Swarm Optimization Methods in Microwave Imaging

    Directory of Open Access Journals (Sweden)

    Andrea Randazzo

    2012-01-01

    Full Text Available Swarm intelligence denotes a class of new stochastic algorithms inspired by the collective social behavior of natural entities (e.g., birds, ants, etc.. Such approaches have been proven to be quite effective in several applicative fields, ranging from intelligent routing to image processing. In the last years, they have also been successfully applied in electromagnetics, especially for antenna synthesis, component design, and microwave imaging. In this paper, the application of swarm optimization methods to microwave imaging is discussed, and some recent imaging approaches based on such methods are critically reviewed.

  12. Particle Swarm Optimization with Adaptive Mutation

    Institute of Scientific and Technical Information of China (English)

    LU Zhen-su; HOU Zhi-rong; DU Juan

    2006-01-01

    A new adaptive mutation particle swarm optimizer,which is based on the variance of the population's fitness,is presented in this paper.During the rtmning time,the mutation probability for the current best particle is determined by two factors:the variance of the population's fitness and the current optimal solution.The ability of particle swarm optimization (PSO) algorithm to break away from the local optimum is greatly improved by the mutation.The experimental results show that the new algorithm not only has great advantage of convergence property over genetic algorithm and PSO,but can also avoid the premature convergence problem effectively.

  13. Chaotic ant swarm optimization to economic dispatch

    Energy Technology Data Exchange (ETDEWEB)

    Cai, Jiejin; Ma, Xiaoqian [Electric Power College, South China University of Technology, Guangzhou 510640 (China); Li, Lixiang; Yang, Yixian [Information Security Center, Department of Information Engineering, Beijing University of Posts and Telecommunications, Beijing 100876 (China); State Key Laboratory of Networking and Switching, Beijing University of Posts and Telecommunications, Beijing 100876 (China); Peng, Haipeng [Information Security Center, Department of Information Engineering, Beijing University of Posts and Telecommunications, Beijing 100876 (China); State Key Laboratory of Networking and Switching, Beijing University of Posts and Telecommunications, Beijing 100876 (China); School of Information Science and Engineering, Shenyang University of Technology, Shenyang 110023 (China); Wang, Xiangdong [School of Information Science and Engineering, Shenyang University of Technology, Shenyang 110023 (China)

    2007-08-15

    This paper developed a novel algorithm named chaotic ant swarm optimization (CASO) for solving the economic dispatch (ED) problems of thermal generators in power systems. This algorithm combines with the chaotic and self-organization behavior of ants in the foraging process. It includes both effects of chaotic dynamics and swarm-based search. The algorithm was employed to solve the ED problems of thermal generators. The proposed method was applied to three examples of power systems. Simulation results demonstrated that the method can obtain feasible and effective solutions, and it is a promising alternative approach for solving the ED problems in practical power systems. (author)

  14. Swarms of UAVs and fighter aircraft

    Energy Technology Data Exchange (ETDEWEB)

    Trahan, M.W.; Wagner, J.S.; Stantz, K.M.; Gray, P.C.; Robinett, R.

    1998-11-01

    This paper describes a method of modeling swarms of UAVs and/or fighter aircraft using particle simulation concepts. Recent investigations into the use of genetic algorithms to design neural networks for the control of autonomous vehicles (i.e., robots) led to the examination of methods of simulating large collections of robots. This paper describes the successful implementation of a model of swarm dynamics using particle simulation concepts. Several examples of the complex behaviors achieved in a target/interceptor scenario are presented.

  15. Lunar Resource Exploitation with Team Hakuto Swarm Rovers

    Science.gov (United States)

    Acierno, Kyle

    2016-07-01

    While much research has been done on the exploration, extraction and utilization of the Moon's resources, little attention has been given to exploring the economic opportunities that exist in the exploitation of those resources with the use of swam rovers. In order to develop a holistic view of lunar resources, this paper will first investigate the most important volatiles and minerals that are known to exist on the Moon. Next, Google Lunar XPRIZE Team Hakuto's technology and current robotic set up will be given. Finally, TEAM HAKUTO's 2017 Lunar mission plan will be outlined, providing an overview of future architectures using future swarm robotics to search for, map and eventually exploit the resources and volatiles.

  16. An Improved Particle Swarm Optimization for Traveling Salesman Problem

    Science.gov (United States)

    Liu, Xinmei; Su, Jinrong; Han, Yan

    In allusion to particle swarm optimization being prone to get into local minimum, an improved particle swarm optimization algorithm is proposed. The algorithm draws on the thinking of the greedy algorithm to initialize the particle swarm. Two swarms are used to optimize synchronously. Crossover and mutation operators in genetic algorithm are introduced into the new algorithm to realize the sharing of information among swarms. We test the algorithm with Traveling Salesman Problem with 14 nodes and 30 nodes. The result shows that the algorithm can break away from local minimum earlier and it has high convergence speed and convergence ratio.

  17. Swarm Dynamics of a Group of Mobile Autonomous Agents

    Institute of Scientific and Technical Information of China (English)

    LIU Bo; CHU Tian-Guang; WANG Long; WANG Zhan-Feng

    2005-01-01

    @@ We propose a simple swarm model to study collective behaviour ofa group of mobile autonomous agents interact ing through a long range attraction and short range repulsion function. It is shown that the individuals (agents) will aggregate and eventually form a cohesive cluster of finite size around the swarm centre in a finite time, and the size depends only on the parameters of the swarm model. Furthermore, it is also shown that all the individuals will converge to equilibrium positions of the swarm model, and thus the configuration of the swarm converges to a constant constellation. Numerical simulations are also worked out to illustrate the analytical results.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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).

  20. A swarm-assisted integrated communication and sensing network

    Science.gov (United States)

    Vincent, Patrick J.; Rubin, Izhak

    2004-07-01

    We present a design concept for an integrated communication and sensor network that employs swarms of Unmanned Aerial Vehicles (UAVs). UAVs are deployed in two types of swarms: sensor swarms or communication swarms. Sensor swarms are motivated by the belief that adversaries will force future confrontations into urban settings, where advantages in surveillance and weapons are diminished. A sensor system is needed which can provide high-resolution imagery and an unobstructed view of a hazardous environment fraught with obstructions. These requirements can be satisfied by a swarm of inexpensive UAVs which "work together" by arranging themselves into a flight configuration that optimizes their integrated sensing capability. If a UAV is shot down, the swarm reconfigures its topology to continue the mission with the surviving assets. We present a methodology that integrates the agents into a formation that enhances the sensing operations while minimizing the transmission of control information for topology adaptation. We demonstrate the performance tradeoff between search time and number of UAVs employed, and present an algorithm that determines the minimum swarm size necessary to meet a targeted search completion time within probabilistic guarantees. A communication swarm provides an infrastructure to distribute information provided by the sensor swarms, and enables communication between dispersed ground locations. UAVs are "guided" to locations that provide the best support for an underlying ground-based communication network and for dissemination of data collected by sensor swarms.

  1. Fuzzy entropy image segmentation based on particle Swarm optimization

    Institute of Scientific and Technical Information of China (English)

    Linyi Li; Deren Li

    2008-01-01

    Partide swaFnl optimization is a stochastic global optimization algorithm that is based on swarm intelligence.Because of its excellent performance,particle swarm optimization is introduced into fuzzy entropy image segmentation to select the optimal fuzzy parameter combination and fuzzy threshold adaptively.In this study,the particles in the swarm are constructed and the swarm search strategy is proposed to meet the needs of the segmentation application.Then fuzzy entropy image segmentation based on particle swarm opti-mization is implemented and the proposed method obtains satisfactory results in the segmentation experiments.Compared with the exhaustive search method,particle swarm optimization can give the salne optimal fuzzy parameter combination and fuzzy threshold while needing less search time in the segmentation experiments and also has good search stability in the repeated experiments.Therefore,fuzzy entropy image segmentation based on particle swarm optimization is an efficient and promising segmentation method.

  2. Mapping the Development of a New MA Programme in Higher Education: Comparing Privately Held Perceptions of a Public Endeavour

    Science.gov (United States)

    Kinchin, Ian; Hosein, Anesa; Medland, Emma; Lygo-Baker, Simon; Warburton, Steven; Gash, Darren; Rees, Roger; Loughlin, Colin; Woods, Rick; Price, Shirley; Usherwood, Simon

    2017-01-01

    After spending a year working on the development of a new online Master's programme in higher education, members of the development team were interviewed to reveal their thoughts about the nature of the programme. The dialogue of each interview was summarised as a concept map. Analysis of the resulting maps included a modified Bernsteinian…

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

    Science.gov (United States)

    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.

  4. Role of tumbling in bacterial swarming

    Science.gov (United States)

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

    2017-08-01

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

  5. Novelty-driven Particle Swarm Optimization

    DEFF Research Database (Denmark)

    Galvao, Diana; Lehman, Joel Anthony; Urbano, Paulo

    2015-01-01

    Particle Swarm Optimization (PSO) is a well-known population-based optimization algorithm. Most often it is applied to optimize objective-based fitness functions that reward progress towards a desired objective or behavior. As a result, search increasingly focuses on higher-fitness areas. However...

  6. Selectively-informed particle swarm optimization.

    Science.gov (United States)

    Gao, Yang; Du, Wenbo; Yan, Gang

    2015-03-19

    Particle swarm optimization (PSO) is a nature-inspired algorithm that has shown outstanding performance in solving many realistic problems. In the original PSO and most of its variants all particles are treated equally, overlooking the impact of structural heterogeneity on individual behavior. Here we employ complex networks to represent the population structure of swarms and propose a selectively-informed PSO (SIPSO), in which the particles choose different learning strategies based on their connections: a densely-connected hub particle gets full information from all of its neighbors while a non-hub particle with few connections can only follow a single yet best-performed neighbor. Extensive numerical experiments on widely-used benchmark functions show that our SIPSO algorithm remarkably outperforms the PSO and its existing variants in success rate, solution quality, and convergence speed. We also explore the evolution process from a microscopic point of view, leading to the discovery of different roles that the particles play in optimization. The hub particles guide the optimization process towards correct directions while the non-hub particles maintain the necessary population diversity, resulting in the optimum overall performance of SIPSO. These findings deepen our understanding of swarm intelligence and may shed light on the underlying mechanism of information exchange in natural swarm and flocking behaviors.

  7. Observatory data and the Swarm mission

    DEFF Research Database (Denmark)

    Macmillan, S.; Olsen, Nils

    2013-01-01

    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...

  8. A Profound Survey on Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Manish Mahant

    2012-03-01

    Full Text Available Swarm Intelligence (SI is the collective behavior of decentralized, self-organized systems, natural or artificial. The concept is employed in work on artificial intelligence. The inspiration often comes from nature, especially biological systems. The expression was introduced by Gerardo Beni and Jing Wang in 1989, in the context of cellular robotic systems. SI systems are typically made up of a population of simple agents or boids interacting locally with one another and their environment. The agents follow very simple rules, and although there is no centralized control structure dictating how individual agents should behave, local, and to a certain degree random, interaction between such agents lead to the emergence of “intelligent” global behavior, unknown to the individual agents. Swarm Intelligence is a relatively new paradigm being applied in a host of research settings to improve the management and control of large numbers of interacting entities such as communications, computer and sensor networks, satellite constellations and more. Attempts to take advantage of this paradigm and mimic the behavior of insect swarms however often lead to many different implementations of SI. Natural examples of SI include ant colonies, bird flocking, animal herding, bacterial growth and fish schooling. This article provides a set of general principle of Swarm Intelligence.

  9. Chip-scale spacecraft swarms: Dynamics, control, and exploration

    Science.gov (United States)

    Weis, Lorraine

    Chip-scale spacecraft (chipsats) swarms will open new avenues for space exploration, both near Earth and in interplanetary space. The ability to create distributed sensor networks through swarms of low-cost, low-mass spacecraft shall enable the exploration of asteroids, icy moons, and the Earths magnetosphere become more feasible. This research develops new techniques for analyzing swarm dynamics, both in the limited case of the Kepler problem, and in general gravity environments, investigates several techniques for providing chipsat propulsion, and develops possible mission strategies. This work applies the Kustaanheimo-Stiefel (KS) transformation to the stochastic exploration presented by chipsat swarms. The contributions towards understanding swarm dynamics include analytical and numerical study of swarms in the purely Kepler problem as well as in general potential fields. A study of swarm evolution near an asteroid provides an example of the richness of behaviors that can be provided by chip-scale spacecraft swarms. Swarm actuation can be achieved through a number of means. This research presents a novel attitude control and propulsion system for chipsat swarms near Earth using a mutliple electrodynamic tethers. A numerical study of tether configurations for the greatest control authority is also presented. In addition, active solar sails are evaluated for swarm actuation beyond Earth, and a visualization of available control authority is presented. An example mission of swarm deployment near the Earth-Moon Lagrange point highlights the utility of swarm-based exploration. The candidate mission shows that a swarm with minimal actuation and a simple control scheme might provide distributed sensors in the region for a year or more, or dissipate quickly if uncontrolled. Such a chip-spacecraft mission would be a valuable precursor to further space development in these regions.

  10. The discovery of the Neoarchean mafic dyke swarm in Hengshan and reinterpretation of the previous "Wutai greenstone belt"

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The structural mapping and section study indicate that the "greenstone belts" in the southern to central parts of Hengshan were intensively sheared and transposed mafic dyke swarm,which originally intruded into the Neoarchean grey gneiss and high-pressure granulite terrain(HPGT).The HPGT is characterized by flat-dipping structures,to the south it became steep and was cut by the Dianmen mafic dyke swarm.After high-pressure granulite-facies metamorphic event,the mafic dyke swarm occurred,and was associated with the extensional setting and reworked by the late strike-slip shearing.The zircon age dating proves that the Dianmen mafic dyke swarm was emplaced during the period between 2499±4 Ma and 2512±3 Ma,followed by late tectonothermal reworking.The Dianmen mafic dyke swarm further documents the extensional episode in the central to northern parts of North China Craton(NCC),providing the important constraint for the limit between Archean and Proterozoic and correlation between NCC and other cratonic blocks of the world.

  11. The discovery of the Neoarchean mafic dyke swarm in Hengshan and reinterpretation of the previous “Wutai greenstone belt”

    Institute of Scientific and Technical Information of China (English)

    李江海; 张志强; 黄雄南

    2002-01-01

    The structural mapping and section study indicate thai the "greenstone belts" in the southern to central parts of Hengshan were intensively sheared and transposed mafic dyke swarm, which originally intruded into the Neoarchean grey gneiss and nigh-pressure granulite terrain (HPGT). The HPGT is characterized by flat-dipping structures, to the south it became steep and was cut by the Dianmen mafic dyke swarm. After high-pressure; granulite-facies metamorphic event, the mafic dyke swarm occurred, and was associated with the extensional setting and reworked by the late strike-slip shearing. The zircon age dating proves that the Dianmen mafic dyke swarm was emplaced during the period between 2499±4 Ma and 2512±3 Ma, followed by late tectonothermal reworking. The Dianmen mafic dyke swarm further documents the extensional episode in the central to northern parts of North China Craton (NCC), providing the important constraint for the limit between Archean and Proterozoic and correlation between NCC and other e

  12. Studying the influence of packaging design on consumer perceptions (of dairy products) using categorizing and perceptual mapping

    NARCIS (Netherlands)

    Gelici-Zeko, M.M.; Lutters, D.; Klooster, ten R.; Weijzen, P.

    2012-01-01

    Food packaging plays an important role in attracting consumers' attention and generating expectations in the consumer that in turn affect their product perception and buying behaviour. In the present study, ‘categorizing’ and ‘perceptual mapping’—diametrically opposed methods (predefined criteria vs

  13. Mapping the Developmental Trajectory and Correlates of Enhanced Pitch Perception on Speech Processing in Adults with ASD.

    Science.gov (United States)

    Mayer, Jennifer L; Hannent, Ian; Heaton, Pamela F

    2016-05-01

    Whilst enhanced perception has been widely reported in individuals with Autism Spectrum Disorders (ASDs), relatively little is known about the developmental trajectory and impact of atypical auditory processing on speech perception in intellectually high-functioning adults with ASD. This paper presents data on perception of complex tones and speech pitch in adult participants with high-functioning ASD and typical development, and compares these with pre-existing data using the same paradigm with groups of children and adolescents with and without ASD. As perceptual processing abnormalities are likely to influence behavioural performance, regression analyses were carried out on the adult data set. The findings revealed markedly different pitch discrimination trajectories and language correlates across diagnostic groups. While pitch discrimination increased with age and correlated with receptive vocabulary in groups without ASD, it was enhanced in childhood and stable across development in ASD. Pitch discrimination scores did not correlate with receptive vocabulary scores in the ASD group and for adults with ASD superior pitch perception was associated with sensory atypicalities and diagnostic measures of symptom severity. We conclude that the development of pitch discrimination, and its associated mechanisms markedly distinguish those with and without ASD.

  14. Studying the influence of packaging design on consumer perceptions (of dairy products) using categorizing and perceptual mapping

    NARCIS (Netherlands)

    Gelici-Zeko, Marina; Lutters, Diederick; ten Klooster, Roland; Weijzen, P.

    2012-01-01

    Food packaging plays an important role in attracting consumers' attention and generating expectations in the consumer that in turn affect their product perception and buying behaviour. In the present study, ‘categorizing’ and ‘perceptual mapping’—diametrically opposed methods (predefined criteria vs

  15. An Improved Particle Swarm Optimization for Feature Selection

    Institute of Scientific and Technical Information of China (English)

    Yuanning Liu; Gang Wang; Huiling Chen; Hao Dong; Xiaodong Zhu; Sujing Wang

    2011-01-01

    Particle Swarm Optimization (PSO) is a popular and bionic algorithm based on the social behavior associated with bird flocking for optimization problems. To maintain the diversity of swarms, a few studies of multi-swarm strategy have been reported. However, the competition among swarms, reservation or destruction of a swarm, has not been considered further. In this paper, we formulate four rules by introducing the mechanism for survival of the fittest, which simulates the competition among the swarms. Based on the mechanism, we design a modified Multi-Swarm PSO (MSPSO) to solve discrete problems,which consists of a number of sub-swarms and a multi-swarm scheduler that can monitor and control each sub-swarm using the rules. To further settle the feature selection problems, we propose an Improved Feature Selection (IFS) method by integrating MSPSO, Support Vector Machines (SVM) with F-score method. The IFS method aims to achieve higher generalization capability through performing kernel parameter optimization and feature selection simultaneously. The performance of the proposed method is compared with that of the standard PSO based, Genetic Algorithm (GA) based and the grid search based methods on 10 benchmark datasets, taken from UCI machine learning and StatLog databases. The numerical results and statistical analysis show that the proposed IFS method performs significantly better than the other three methods in terms of prediction accuracy with smaller subset of features.

  16. Particle Swarm Optimization Based Support Vector Regression for Blind Image Restoration

    Institute of Scientific and Technical Information of China (English)

    Ratnakar Dash; Pankaj Kumar Sa; Banshidhar Majhi

    2012-01-01

    This paper presents a swarm intelligence based parameter optimization of the support vector machine (SVM)for blind image restoration.In this work,SVM is used to solve a regression problem.Support vector regression (SVR)has been utilized to obtain a true mapping of images from the observed noisy blurred images.The parameters of SVR are optimized through particle swarm optimization (PSO) technique.The restoration error function has been utilized as the fitness function for PSO.The suggested scheme tries to adapt the SVM parameters depending on the type of blur and noise strength and the experimental results validate its effectiveness.The results show that the parameter optimization of the SVR model gives better performance than conventional SVR model as well as other competent schemes for blind image restoration.

  17. A closed-loop particle swarm optimizer for multivariable process controller design

    Institute of Scientific and Technical Information of China (English)

    Kai HAN; Jun ZHAO; Zu-hua XU; Ji-xin QIAN

    2008-01-01

    Design of general multivariable process controllers is an attractive and practical alternative to optimizing design by evolutionary algorithms (EAs) since it can be formulated as an optimization problem.A closed-loop particle swarm optimization (CLPSO) algorithm is proposed by mapping PSO elements into the closed-loop system based on control theories.At each time step,a proportional integral (PI) controller is used to calculate an updated inertia weight for each particle in swarms from its last fitness.With this modification,limitations caused by a uniform inertia weight for the whole population are avoided,and the particles have enough diversity.After the effectiveness,efficiency and robustness are tested by benchmark functions,CLPSO is applied to design a multivariable proportional-integral-derivative (PID) controller for a solvent dehydration tower in a chemical plant and has improved its performances.

  18. Object Detection In Image Using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Nirbhowjap Singh

    2010-12-01

    Full Text Available Image matching is a key component in almost any image analysis process. Image matching is crucial to a wide range of applications, such as in navigation, guidance, automatic surveillance, robot vision, and in mapping sciences. Any automated system for three-dimensional point positioning must include a potent procedure for image matching. Most biological vision systems have the talent to cope with changing world. Computer vision systems have developed in the same way. For a computer vision system, the ability to cope withmoving and changing objects, changing illumination, and changing viewpoints is essential to perform several tasks. Object detection is necessary for surveillance applications, for guidance of autonomous vehicles, for efficient video compression, for smart tracking of moving objects, for automatic target recognition (ATR systems and for many other applications. Cross-correlation and related techniqueshave dominated the field since the early fifties. Conventional template matching algorithm based on cross-correlation requires complex calculation and large time for object detection, which makes difficult to use them in real time applications. The shortcomings of this class of image matching methods have caused a slow-down in the development of operational automated correlation systems. In the proposed work particle swarm optimization & its variants basedalgorithm is used for detection of object in image. Implementation of this algorithm reduces the time required for object detection than conventional template matching algorithm. Algorithm can detect object in less number of iteration & hence less time & energy than the complexity of conventional template matching. This feature makes the method capable for real time implementation. In this thesis a study of particle Swarm optimization algorithm is done & then formulation of the algorithm for object detection using PSO & its variants is implemented for validating its effectiveness.

  19. A hybrid multi-swarm particle swarm optimization to solve constrained optimization problems

    Institute of Scientific and Technical Information of China (English)

    Yong WANG; Zixing CAI

    2009-01-01

    In the real-world applications, most optimization problems are subject to different types of constraints. These problems are known as constrained optimization problems (COPs). Solving COPs is a very important area in the optimization field. In this paper, a hybrid multi-swarm particle swarm optimization (HMPSO) is proposed to deal with COPs. This method adopts a parallel search operator in which the current swarm is partitioned into several subswarms and particle swarm optimization (PSO) is severed as the search engine for each sub-swarm. Moreover, in order to explore more promising regions of the search space, differential evolution (DE) is incorporated to improve the personal best of each particle. First, the method is tested on 13 benchmark test functions and compared with three stateof-the-art approaches. The simulation results indicate that the proposed HMPSO is highly competitive in solving the 13 benchmark test functions. Afterward, the effectiveness of some mechanisms proposed in this paper and the effect of the parameter setting were validated by various experiments. Finally, HMPSO is further applied to solve 24 benchmark test functions collected in the 2006 IEEE Congress on Evolutionary Computation (CEC2006) and the experimental results indicate that HMPSO is able to deal with 22 test functions.

  20. Perceptions of Private Sector towards the Pollutant Release and Transfer Register: A Case Study on Petrochemical Industry in the Map Ta Phut Industrial Estate, Rayong, Thailand

    Directory of Open Access Journals (Sweden)

    Marie Kondo

    2013-01-01

    Full Text Available Under the Rio Declaration and Agenda 21 from the United Nations Conference on Environment and Development in 1992 as well as other international agreements, Thailand is currently in the process of adopting the Pollutant Release and Transfer Register (PRTR through a pilot project in Rayong province with assistance from the Japan International Cooperation Agency (JICA. This research aimed to study perceptions of private sector towards the PRTR through a case study on petrochemical industry in the Map Ta Phut Industrial Estate. Through semi-structured questionnaires and in-depth interviews, the study found that the petrochemical industry viewed that benefits of the PRTR for the government and civil society is quite clear, while each petrochemical company has different understanding on such benefit for private sector to be as sustainable industrial management. Various incentive measures and concerns on the PRTR were also indicated in this study.

  1. Thermospheric neutral densities derived from Swarm accelerometer and GPS data

    DEFF Research Database (Denmark)

    Doornbos, Eelco; Encarnacao, Joao; van den IJss, Jose;

    approach, affects the possibility of determining densities from the accelerometer measurements of the Swarm A and B satellites. We also investigate the possibility of determining crosswind speeds from Swarm data.In the meantime, we have investigated the possibility of deriving thermosphere neutral density...... affected and most promising data for scientific use. The goal to make the Swarm C accelerometer along-track axis data ready for further processing into level 2 thermosphere density data has now been accomplished, with the help of information on the satellite motion from the GPS tracking as well...... data from the Swarm GPS observations only, with a much lower temporal resolution. We analyse the differences in the data between the three Swarm satellites as well as between the accelerometer-derived and GPS-only-derived densities for Swarm C....

  2. Orientational hysteresis in swarms of active particles in external field

    CERN Document Server

    Romensky, Maksym

    2015-01-01

    Structure and ordering in swarms of active particles have much in common with condensed matter systems like magnets or liquid crystals. A number of important characteristics of such materials can be obtained via dynamic tests such as hysteresis. In this work, we show that dynamic hysteresis can be observed also in swarms of active particles and possesses similar properties to the counterparts in magnetic materials. To study the swarm dynamics, we use computer simulation of the active Brownian particle model with dissipative interactions. The swarm is confined to a narrow linear channel and one-dimensional polar order parameter is measured. In an oscillating external field, the order parameter demonstrates dynamic hysteresis with the shape of the loop and its area varying with the amplitude and frequency of the applied field, swarm density and the noise intensity. We measure the scaling exponents for the hysteresis loop area, which can be associated with the controllability of the swarm. Although the exponents...

  3. Swarm Products and Space Weather Applications

    DEFF Research Database (Denmark)

    Stolle, Claudia; Olsen, Nils; Martini, Daniel

    and plasmaspheric electron content and GPS and accelerometer data are used to derive information on thermospheric density.Continuous data sets from LEO satellites, such as Swarm, and often combined with ground observations have been useful in developing empirical models of the temporal occurrence and local......, continuous radio navigation and communication (e.g., Galileo, GPS) through the development of severe ionospheric plasma gradients, e.g., during geomagnetic storms.This paper will discuss opportunities from LEO satellites for imaging the actual state of the magnetosphere and upper atmosphere for applications......The Swarm satellite constellation mission provides high precision magnetic field data and models and other observations that enable us to explore near Earth space for example in terms of in situ electron density and electric fields. On board GPS observables can be used for sounding ionospheric...

  4. Time Optimal Reachability Analysis Using Swarm Verification

    DEFF Research Database (Denmark)

    Zhang, Zhengkui; Nielsen, Brian; Larsen, Kim Guldstrand

    2016-01-01

    Time optimal reachability analysis employs model-checking to compute goal states that can be reached from an initial state with a minimal accumulated time duration. The model-checker may produce a corresponding diagnostic trace which can be interpreted as a feasible schedule for many scheduling a...... algorithms work much faster than sequential algorithms, and especially two using combinations of random-depth-first and breadth-first show very promising performance....... search strategies. We develop four swarm algorithms and evaluate them with four models in terms scalability, and time- and memory consumption. Three of these cooperate by exchanging costs of intermediate solutions to prune the search using a branch-and-bound approach. Our results show that swarm...

  5. Thermoregulation and adaptation in honeybee swarms

    Science.gov (United States)

    Ocko, Samuel; Mahadevan, L.

    2012-11-01

    Swarming is an essential part of honeybee behavior, wherein thousands of bees cling onto each other to form a dense cluster that is exposed to the environment for up to several days. This cluster has the ability to maintain its core temperature actively without a central controller raising the question of mechanism. Inspired by experimental observations, we treat the swarm cluster as an active porous structure with a variable metabolism that needs to adjust to outside conditions to control heat loss and regulate its core temperature. Using a continuum model that takes the form of a set of advection-diffusion equations for heat transfer in a mobile porous medium, we show that effective thermoregulation can result from the collective behavior of individual bees in the cluster.

  6. Two Invariants of Human-Swarm Interaction

    Science.gov (United States)

    2017-08-15

    2002). Humans and automation: System design and research issues. John Wiley and Sons. 29 Brown et al., Two Invariants of Human Swarm Interaction...Daniel S. Brown AFRL Information Directorate and Michael A. Goodrich, Shin-Young Jung, and Sean Kerman Brigham Young University The search for...publication in this journal. Journal of Human-Robot Interaction, Vol. 1, No. 1, 2012, Pages 78-95. DOI 10.5898/JHRI.1.1.Tanaka Brown et al., Two Invariants

  7. Countering A2/AD with Swarming

    Science.gov (United States)

    2016-04-01

    flexibility, and surprise .”19 The U.S.’s desire to fight war the American way, has influenced every aspect of the current strategy and has led to...strategy that combines the tenets of maneuver warfare with those of mass warfare. A swarm uses a combination of mass and maneuver for amazing ...to the environment and collectively accomplish something far more amazing than any individual unit could alone. Some of the most successful species

  8. Swarm intelligence for autonomous UAV control

    OpenAIRE

    Frantz, Natalie R.

    2005-01-01

    Unmanned Aerial Vehicles (UAVs) are becoming vital warfare platforms because they significantly reduce the risk of human life while accomplishing important missions. A UAV can be used for example, as stand-in sensor for the detection of mobile, low-probability-of-intercept battlefield surveillance and fire control emitters. With many UAVs acting together as a swarm, the location and frequency characteristics of each emitter can be accurately determined to continuously provide complete batt...

  9. Evolution of Task Partitioning in Swarm Robotics

    OpenAIRE

    Ferrante, Eliseo,; Duenez-Guzman, E.; Turgut, A. E.; Wenseleers, Tom

    2013-01-01

    International audience; Task-partitioning refers to the process whereby a task is divided into two or more sub-tasks. Through task partitioning both efficiency and effectiveness can be improved provided the right environmental conditions. We synthesize self-organized task partitioning behaviors for a swarm of mobile robots using artificial evolution. Through validation experiments, we show that the synthesized behaviors exploits behavioral specialization despite being based on homogeneous ind...

  10. A Game Theoretic Approach to Swarm Robotics

    Directory of Open Access Journals (Sweden)

    S. N. Givigi

    2006-01-01

    Full Text Available In this article, we discuss some techniques for achieving swarm intelligent robots through the use of traits of personality. Traits of personality are characteristics of each robot that, altogether, define the robot's behaviours. We discuss the use of evolutionary psychology to select a set of traits of personality that will evolve due to a learning process based on reinforcement learning. The use of Game Theory is introduced, and some simulations showing its potential are reported.

  11. Earth Observing Satellite Orbit Design Via Particle Swarm Optimization

    Science.gov (United States)

    2014-08-01

    Earth Observing Satellite Orbit Design Via Particle Swarm Optimization Sharon Vtipil ∗ and John G. Warner ∗ US Naval Research Laboratory, Washington...number of passes per day given a satellite’s orbital altitude and inclination. These are used along with particle swarm optimization to determine optimal...well suited to use within a meta-heuristic optimization method such as the Particle Swarm Optimizer (PSO). This method seeks to find the optimal set

  12. Adaptive Swarm Formation Control for Hybrid Ground and Aerial Assets

    OpenAIRE

    Barnes, Laura; Garcia, Richard; Fields, Mary Anne; Valavanis, Kimon

    2010-01-01

    In this work, a methodology for control and coordination of UAVs and UGVs has been presented. UAVs and UGVs were integrated into a single team and were able to adapt their formation accordingly. Potential field functions together with limiting functions can be successfully utilized to control UGV and UAV swarm formation, obstacle avoidance and the overall swarm movement. A single UAV was also successfully used to pull the UGV swarm into formation. These formations can move as a un...

  13. A feature extraction method of the particle swarm optimization algorithm based on adaptive inertia weight and chaos optimization for Brillouin scattering spectra

    Science.gov (United States)

    Zhang, Yanjun; Zhao, Yu; Fu, Xinghu; Xu, Jinrui

    2016-10-01

    A novel particle swarm optimization algorithm based on adaptive inertia weight and chaos optimization is proposed for extracting the features of Brillouin scattering spectra. Firstly, the adaptive inertia weight parameter of the velocity is introduced to the basic particle swarm algorithm. Based on the current iteration number of particles and the adaptation value, the algorithm can change the weight coefficient and adjust the iteration speed of searching space for particles, so the local optimization ability can be enhanced. Secondly, the logical self-mapping chaotic search is carried out by using the chaos optimization in particle swarm optimization algorithm, which makes the particle swarm optimization algorithm jump out of local optimum. The novel algorithm is compared with finite element analysis-Levenberg Marquardt algorithm, particle swarm optimization-Levenberg Marquardt algorithm and particle swarm optimization algorithm by changing the linewidth, the signal-to-noise ratio and the linear weight ratio of Brillouin scattering spectra. Then the algorithm is applied to the feature extraction of Brillouin scattering spectra in different temperatures. The simulation analysis and experimental results show that this algorithm has a high fitting degree and small Brillouin frequency shift error for different linewidth, SNR and linear weight ratio. Therefore, this algorithm can be applied to the distributed optical fiber sensing system based on Brillouin optical time domain reflection, which can effectively improve the accuracy of Brillouin frequency shift extraction.

  14. Geomagnetic Jerks in the Swarm Era

    Science.gov (United States)

    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.

  15. Mapping stiffness perception in the brain with an fMRI-compatible particle-jamming haptic interface.

    Science.gov (United States)

    Menon, Samir; Stanley, Andrew A; Zhu, Jack; Okamura, Allison M; Khatib, Oussama

    2014-01-01

    We demonstrate reliable neural responses to changes in haptic stiffness perception using a functional magnetic resonance imaging (fMRI) compatible particle-jamming haptic interface. Our haptic interface consists of a silicone tactile surface whose stiffness we can control by modulating air-pressure in a sub-surface pouch of coarsely ground particles. The particles jam together as the pressure decreases, which stiffens the surface. During fMRI acquisition, subjects performed a constant probing task, which involved continuous contact between the index fingertip and the interface and rhythmic increases and decreases in fingertip force (1.6 Hz) to probe stiffness. Without notifying subjects, we randomly switched the interface's stiffness (switch time, 300-500 ms) from soft (200 N/m) to hard (1400 N/m). Our experiment design's constant motor activity and cutaneous tactile sensation helped disassociate neural activation for both from stiffness perception, which helped localized it to a narrow region in somatosensory cortex near the supra-marginal gyrus. Testing different models of neural activation, we found that assuming indepedent stiffness-change responses at both soft-hard and hard-soft transitions provides the best explanation for observed fMRI measurements (three subjects; nine four-minute scan runs each). Furthermore, we found that neural activation related to stiffness-change and absolute stiffness can be localized to adjacent but disparate anatomical locations. We also show that classical finger-tapping experiments activate a swath of cortex and are not suitable for localizing stiffness perception. Our results demonstrate that decorrelating motor and sensory neural activation is essential for characterizing somatosensory cortex, and establish particle-jamming haptics as an attractive low-cost method for fMRI experiments.

  16. Detection of earthquake swarms in subduction zones around Japan

    Science.gov (United States)

    Nishikawa, T.; Ide, S.

    2015-12-01

    Earthquake swarms in subduction zones are likely to be related with slow slip events (SSEs) and locking on the plate interface. In the Boso-Oki region in central Japan, swarms repeatedly occur accompanying SSEs (e.g, Hirose et al., 2012). It is pointed out that ruptures of great earthquakes tend to terminate in regions with recurring swarm activity because of reduced and heterogeneous locking there (Holtkamp and Brudzinsiki, 2014). Given these observations, we may be able to infer aseismic slips and spatial variations in locking on the plate interface by investigating swarm activity in subduction zones. It is known that swarms do not follow Omori's law and have much higher seismicity rates than predicted by the ETAS model (e.g., Llenos et al., 2009). Here, we devised a statistical method to detect unexpectedly frequent earthquakes using the space-time ETAS model (Zhuang et al., 2002). We applied this method to subduction zones around Japan (Tohoku, Ibaraki-Boso-oki, Hokkaido, Izu, Tonankai, Nankai, and Kyushu) and detected swarms in JMA catalog (M ≥ 3) from 2001 to 2010. We detected recurring swarm activities as expected in the Boso-Oki region and also in the Ibaraki-Oki region (see Figures), where intensive foreshock activity was found by Maeda and Hirose (2011). In Tohoku, regions with intensive foreshock activity also appear to roughly correspond to regions with recurring swarm activity. Given that both foreshocks and swarms are triggered by SSEs (e.g., Bouchon et al., 2013), these results suggest that the regions with foreshock activity and swarm activity such as the Ibaraki-Oki region are characterized by extensive occurrences of SSEs just like the Boso-Oki region. Besides Ibaraki-Oki and Boso-Oki, we detected many swarms in Tohoku, Hokkaido, Izu, and Kyushu. On the other hand, swarms are rare in the rupture areas of the 1944 Tonankai and 1946 Nankai earthquakes. These variations in swarm activity may reflect variations in SSE activity among subduction zones

  17. Nature-Inspired Swarm Intelligence and Its Applications

    Directory of Open Access Journals (Sweden)

    Sangita Roy

    2014-12-01

    Full Text Available In 1989 Gerardo Beni and Jing Wang first proposed the name "Swarm Intelligence" in their paper "Swarm Intelligence in Cellular Robotic Systems". Some remarkable observations of different researchers are studied in this paper, like the proximity principle, the quality principle, the principle of diverse response, the principle of stability, the principle of adaptability. To enhance the capabilities of robot and different systems, researchers started to exploit the behavior of natural systems. Swarm groups are governed by three rules, move in the same direction as your neighbor, remain close to your neighbor, and avoid collision with your neighbor .Characteristics of swarm groups are emergence and stigmergy. Different insects like ants, wasps, termites carry out a work locally for global goal with sufficient flexibility as they are not controlled centrally. In this paper the existing research works are analysed to show the behavior in social insects by using self-organization, positive feedback, negative feedback, amplification of fluctuation, multiple interactions. It has also been observed that these insects are almost blind and memoryless, still they communicate indirectly among themselves for stigmergic effect by using pheromone. Implementation of swarm intelligence in robotics i.e., swarm robots are narrated. The limitations of swarm robots as well as factors behind the success of swarm robotics have also been encompassed. Finally authors focus on swarm robots applications in telecommunication fields, civil engineering and digital image processing.

  18. A comparative analysis of chaotic particle swarm optimizations for detecting single nucleotide polymorphism barcodes.

    Science.gov (United States)

    Chuang, Li-Yeh; Moi, Sin-Hua; Lin, Yu-Da; Yang, Cheng-Hong

    2016-10-01

    Evolutionary algorithms could overcome the computational limitations for the statistical evaluation of large datasets for high-order single nucleotide polymorphism (SNP) barcodes. Previous studies have proposed several chaotic particle swarm optimization (CPSO) methods to detect SNP barcodes for disease analysis (e.g., for breast cancer and chronic diseases). This work evaluated additional chaotic maps combined with the particle swarm optimization (PSO) method to detect SNP barcodes using a high-dimensional dataset. Nine chaotic maps were used to improve PSO method results and compared the searching ability amongst all CPSO methods. The XOR and ZZ disease models were used to compare all chaotic maps combined with PSO method. Efficacy evaluations of CPSO methods were based on statistical values from the chi-square test (χ(2)). The results showed that chaotic maps could improve the searching ability of PSO method when population are trapped in the local optimum. The minor allele frequency (MAF) indicated that, amongst all CPSO methods, the numbers of SNPs, sample size, and the highest χ(2) value in all datasets were found in the Sinai chaotic map combined with PSO method. We used the simple linear regression results of the gbest values in all generations to compare the all methods. Sinai chaotic map combined with PSO method provided the highest β values (β≥0.32 in XOR disease model and β≥0.04 in ZZ disease model) and the significant p-value (p-valuechaotic map was found to effectively enhance the fitness values (χ(2)) of PSO method, indicating that the Sinai chaotic map combined with PSO method is more effective at detecting potential SNP barcodes in both the XOR and ZZ disease models. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. Projective mapping

    DEFF Research Database (Denmark)

    Dehlholm, Christian; Brockhoff, Per B.; Bredie, Wender Laurentius Petrus

    2012-01-01

    Projective Mapping (Risvik et.al., 1994) and its Napping (Pagès, 2003) variations have become increasingly popular in the sensory field for rapid collection of spontaneous product perceptions. It has been applied in variations which sometimes are caused by the purpose of the analysis and sometime...

  20. Perceptual Dominant Color Extraction by Multidimensional Particle Swarm Optimization

    Science.gov (United States)

    Kiranyaz, Serkan; Uhlmann (Eurasip Member), Stefan; Ince, Turker; Gabbouj, Moncef

    2010-12-01

    Color is the major source of information widely used in image analysis and content-based retrieval. Extracting dominant colors that are prominent in a visual scenery is of utmost importance since the human visual system primarily uses them for perception and similarity judgment. In this paper, we address dominant color extraction as a dynamic clustering problem and use techniques based on Particle Swarm Optimization (PSO) for finding optimal (number of) dominant colors in a given color space, distance metric and a proper validity index function. The first technique, so-called Multidimensional (MD) PSO can seek both positional and dimensional optima. Nevertheless, MD PSO is still susceptible to premature convergence due to lack of divergence. To address this problem we then apply Fractional Global Best Formation (FGBF) technique. In order to extract perceptually important colors and to further improve the discrimination factor for a better clustering performance, an efficient color distance metric, which uses a fuzzy model for computing color (dis-) similarities over HSV (or HSL) color space is proposed. The comparative evaluations against MPEG-7 dominant color descriptor show the superiority of the proposed technique.

  1. Perceptual Dominant Color Extraction by Multidimensional Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Moncef Gabbouj

    2009-01-01

    Full Text Available Color is the major source of information widely used in image analysis and content-based retrieval. Extracting dominant colors that are prominent in a visual scenery is of utmost importance since the human visual system primarily uses them for perception and similarity judgment. In this paper, we address dominant color extraction as a dynamic clustering problem and use techniques based on Particle Swarm Optimization (PSO for finding optimal (number of dominant colors in a given color space, distance metric and a proper validity index function. The first technique, so-called Multidimensional (MD PSO can seek both positional and dimensional optima. Nevertheless, MD PSO is still susceptible to premature convergence due to lack of divergence. To address this problem we then apply Fractional Global Best Formation (FGBF technique. In order to extract perceptually important colors and to further improve the discrimination factor for a better clustering performance, an efficient color distance metric, which uses a fuzzy model for computing color (dis- similarities over HSV (or HSL color space is proposed. The comparative evaluations against MPEG-7 dominant color descriptor show the superiority of the proposed technique.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  4. A hybrid search algorithm for swarm robots searching in an unknown environment.

    Science.gov (United States)

    Li, Shoutao; Li, Lina; Lee, Gordon; Zhang, Hao

    2014-01-01

    This paper proposes a novel method to improve the efficiency of a swarm of robots searching in an unknown environment. The approach focuses on the process of feeding and individual coordination characteristics inspired by the foraging behavior in nature. A predatory strategy was used for searching; hence, this hybrid approach integrated a random search technique with a dynamic particle swarm optimization (DPSO) search algorithm. If a search robot could not find any target information, it used a random search algorithm for a global search. If the robot found any target information in a region, the DPSO search algorithm was used for a local search. This particle swarm optimization search algorithm is dynamic as all the parameters in the algorithm are refreshed synchronously through a communication mechanism until the robots find the target position, after which, the robots fall back to a random searching mode. Thus, in this searching strategy, the robots alternated between two searching algorithms until the whole area was covered. During the searching process, the robots used a local communication mechanism to share map information and DPSO parameters to reduce the communication burden and overcome hardware limitations. If the search area is very large, search efficiency may be greatly reduced if only one robot searches an entire region given the limited resources available and time constraints. In this research we divided the entire search area into several subregions, selected a target utility function to determine which subregion should be initially searched and thereby reduced the residence time of the target to improve search efficiency.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Sanjay Saini

    Full Text Available 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.

  7. Level-2 product generation for the Swarm satellite constellation mission

    DEFF Research Database (Denmark)

    Olsen, Poul Erik Holmdahl; Tøffner-Clausen, Lars; Olsen, Nils

    In order to take advantage of the unique constellation aspect of ESA's Swarm constellation mission, considerably advanced data analysis tools have been developed. The Swarm ESL/SCARF (Satellite Constellation Application and Research Facility), a consortium of several research institutions, derives...

  8. Level-2 product generation for the Swarm satellite constellation mission

    DEFF Research Database (Denmark)

    Olsen, Poul Erik Holmdahl; Tøffner-Clausen, Lars; Olsen, Nils

    In order to take advantage of the unique constellation aspect of ESA's Swarm constellation mission, considerably advanced data analysis tools have been developed. The Swarm ESL/SCARF (Satellite Constellation Application and Research Facility), a consortium of several research institutions, derives...

  9. Taurid swarm exists only in southern branch (STA)

    Science.gov (United States)

    Shiba, Yasuo

    2016-06-01

    I present some features of the Taurid meteor shower in data obtained by the Japanese automatic TV meteor observation `SonotaCo Network' from 2007 to 2015. (i) The Taurid shower is enhanced when the Earth encounters the Taurid swarm center at less than 30 in mean anomaly as described by Asher and Izumi (1998). A little enhancement was detected in 2011 when it was 71 from the center in mean anomaly. (ii) The Taurid meteor swarm exists only in the southern branch (STA) but not in the northern branch (NTA). (iii) The Taurid meteor swarm includes bright meteors more than the annual year components as also described in Asher & Izumi (1998). (iv) The STA swarm orbital period is equal to the 2:7 resonance with Jupiter. This orbital period agrees with the suggestion in Asher & Izumi (1998). However, the NTA orbital period also matches the 2:7 resonance with Jupiter, though no swarm exists. (v) The Taurid swarm longitude of perihelion is constant at 158 over its whole period. (vi) NTA orbit features vary smoothly over the season. No complex structure could be recognized in NTA in this study of observations by small video camera. (vii) The Taurid swarm orbit differs from the annual STA orbit at its peak, but is close to the annual component at the end of swarm activity. (viii) The annual STA component consists of some similar orbital streams.

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

    Science.gov (United States)

    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.

  11. LinkMind: Link Optimization in Swarming Mobile Sensor Networks

    DEFF Research Database (Denmark)

    Ngo, Trung Dung

    2012-01-01

    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...

  12. An Ecological Approach to the Supervisory Control of UAV Swarms

    NARCIS (Netherlands)

    Fuchs, C.; Borst, C.; De Croon, G.C.H.E.; Van Paassen, M.M.; Mulder, M.

    2014-01-01

    This research employs ecological interface design to improve the human machine interface of an existing ground control station for the supervisory control of UAV swarms. As a case study, a general ground surveillance mission with four UAVs is envisioned. An analysis of the swarming work domain is pe

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

    Science.gov (United States)

    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...

  14. Swarm-Optimization-Based Affective Product Design Illustrated by a Mobile Phone Case-Study

    Directory of Open Access Journals (Sweden)

    Koffka Khan

    2012-05-01

    Full Text Available This paper presents a new approach of user-oriented design for transforming users’ perception into product elements design. An experimental study on mobile phones is conducted to examine how product form and product design parameters affect consumer’s perception of a product. The concept of Kansei Engineering is used to extract the experimental samples as a data base for neural networks (NNs with particle swarm optimization (PSO analysis. The result of numerical analysis suggests that mobile phone makers need to focus on particular design parameters to attract specific target user groups, in addition to product forms. This paper demonstrates the advantage of using KE-PSO for determining the optimal combination of product design parameters. Based on the analysis, we can use KE-PSO to suggest customers’ preferences for mobile phone design attributes that would be considered optimal by various user groups of all surveyed. They can be used for improvement and development of new future products.

  15. Modified constriction particle swarm optimization algorithm

    Institute of Scientific and Technical Information of China (English)

    Zhe Zhang; Limin Jia; Yong Qin

    2015-01-01

    To deal with the demerits of constriction particle swarm optimization (CPSO), such as relapsing into local optima, slow convergence velocity, a modified CPSO algorithm is proposed by improving the velocity update formula of CPSO. The random ve-locity operator from local optima to global optima is added into the velocity update formula of CPSO to accelerate the convergence speed of the particles to the global optima and reduce the likeli-hood of being trapped into local optima. Final y the convergence of the algorithm is verified by calculation examples.

  16. Swarming Robot Design, Construction and Software Implementation

    Science.gov (United States)

    Stolleis, Karl A.

    2014-01-01

    In this paper is presented an overview of the hardware design, construction overview, software design and software implementation for a small, low-cost robot to be used for swarming robot development. In addition to the work done on the robot, a full simulation of the robotic system was developed using Robot Operating System (ROS) and its associated simulation. The eventual use of the robots will be exploration of evolving behaviors via genetic algorithms and builds on the work done at the University of New Mexico Biological Computation Lab.

  17. Pattern formation and functionality in swarm models

    CERN Document Server

    Rauch, E M; Chialvo, D R; Rauch, Erik M; Millonas, Mark M; Chialvo, Dante R

    1995-01-01

    We explore a simplified class of models we call swarms, which are inspired by the collective behavior of social insects. We perform a mean-field stability analysis and perform numerical simulations of the model. Several interesting types of behavior emerge in the vicinity of a second-order phase transition in the model, including the formation of stable lines of traffic flow, and memory reconstitution and bootstrapping. In addition to providing an understanding of certain classes of biological behavior, these models bear a generic resemblance to a number of pattern formation processes in the physical sciences.

  18. A Novel Adaptive Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Xiaobing Yu

    2012-07-01

    Full Text Available Particle swarm optimization (PSO is a stochastic search technique for solving optimization problems, which has been proven to be efficient and effective in wide applications. However, the PSO can easily fly into the local optima and lack the ability to jump out of the local optima. A novel adaptive PSO is proposed by evaluating convergence of the fitness value. The novel mechanism is to ensure the diversity of particles. Simulations for benchmark test functions have illustrated that the proposed algorithm possesses better ability to find the global optima than other variants and is an effective global optimization tool.

  19. Brain dysfunction in psychiatric patients during music perception measured by EEG mapping: relation to motor dysfunction and influence of neuroleptic drugs.

    Science.gov (United States)

    Günther, W; Steinberg, R; Streck, P; Banquet, J P; Bscheid, I; Raith, L; Riedel, R; Klages, U; Stiltz, I

    1991-05-01

    We report here our findings on music perception obtained as a companion study to the investigation with 16-channel EEG mapping in psychiatric patients during motor activation, published recently elsewhere. We decided to add on a study of this functional circuit, since there is evidence that it is disturbed in various psychiatric patient groups (another "functio laesa"). Involved in the study were 23 male and 25 female schizophrenics, 11 male and 18 female non-endogenously depressed patients (not presently under medication, i.e. drug-naive or wash-out period from 1 week to 17 years), 26 male and 37 female endogenously depressed patients (medicated with tri- or tetracyclic antidepressants and/or benzodiazepines; no lithium), and 22 male and 17 female control subjects (i.e. n = 179). We compared resting conditions after a special relaxation procedure with three music perception tasks: (1) a standardised rumba rhythm generated by a keyboard and delivered binaurally by earphones, (2) the same as an arpeggio in D major, and (3) the same as an arpeggio with a tonic-subdominant-dominant cadence. Major results were obtained in the delta and alpha frequency bands, yielding signs of "diffuse hyperactivation", most prominent in schizophrenic males, and not observed to a similar extent in any other patient group or in normal controls. Interestingly, there were major sex differences, yielding a more diffuse EEG activation pattern in normal females than in males and thus possibly obscuring signs of brain function diffusion in female patients. Viewing our broader evidence of similar brain dysfunction when examining motor functional circuits, especially in schizophrenics, these findings provide further evidence of a brain disorganization with lack of laterality/diffusion which may be found in subgroups of these patients and not in other psychiatric disorders. In schizophrenic patients, these EEG signs of "diffuse hyperactivation" on simple motor and/or music stimulation were

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

    Science.gov (United States)

    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.

  1. Antarctic krill swarm characteristics in the Southeast Atlantic sector of the Southern Ocean

    KAUST Repository

    Krafft, BA

    2012-09-28

    Knowledge about swarm dynamics and underlying causes is essential to understand the ecology and distribution of Antarctic krill Euphausia superba. We collected acoustic data and key environmental data continuously across extensive gradients in the little-studied Southeast Atlantic sector of the Southern Ocean. A total of 4791 krill swarms with swarm descriptors including swarm height and length, packing density, swimming depth and inter-swarm distance were extracted. Through multivariate statistics, swarms were categorized into 4 groups. Group 2 swarms were largest (median length 108 m and thickness 18 m), whereas swarms in both Groups 1 and 4 were on average small, but differed markedly in depth distribution (median: 52 m for Group 1 vs. 133 m for Group 4). There was a strong spatial autocorrelation in the occurrence of swarms, and an autologistic regression model found no prediction of swarm occurrence from environmental variables for any of the Groups 1, 2 or 4. Probability of occurrence of Group 3 swarms, however, increased with increasing depth and temperature. Group 3 was the most distinctive swarm group with an order of magnitude higher packing density (median: 226 ind. m−3) than swarms from any of the other groups and about twice the distance to nearest neighbor swarm (median: 493 m). The majority of the krill were present in Group 3 swarms, and the absence of association with hydrographic or topographic concentrating mechanisms strongly suggests that these swarms aggregate through their own locomotion, possibly associated with migration.

  2. Chaotic Inertia Weight Particle Swarm Optimization for PCR Primer Design

    Directory of Open Access Journals (Sweden)

    Cheng-Huei Yang

    2013-06-01

    Full Text Available In order to provide feasible primer sets for performing a polymerase chain reaction (PCR experiment, many primer design methods have been proposed. However, the majority of these methods require a long time to obtain an optimal solution since large quantities of template DNA need to be analyzed, and the designed primer sets usually do not provide a specific PCR product size. In recent years, particle swarm optimization (PSO has been applied to solve many problems and yielded good results. In this paper, a logistic map is proposed to determine the value of inertia weight of PSO (CIWPSO to design feasible primers. Accuracies for the primer design of the Homo sapiens RNA binding motif protein 11 (RBM11, mRNA (NM_144770, and the Homo sapiens G protein-coupled receptor 78 (GPR78, mRNA (NM_080819 were calculated. Five hundred runs of PSO and the CIWPSO primer design method were performed on different PCR product lengths and the different methods of calculating the melting temperature. A comparison of the accuracy results for PSO and CIWPSO primer design showed that CIWPSO is superior to the PSO for primer design. The proposed method could effectively find optimal or near-optimal primer sets.

  3. Local fluid transport by planktonic swarms

    Science.gov (United States)

    Martinez-Ortiz, Monica; Dabiri, John

    2013-11-01

    Energy transport in the ocean occurs through an intricate set of pathways mainly powered by physical phenomena. The hypothesis that vertical migrations of aquatic fauna may contribute to this process through the action of the induced drift mechanism has been investigated in recent years. Microscale measurements by Kunze et al. (1), in Saanich Inlet have shown the presence of high kinetic energy dissipation rates in the vicinity of vertically migrating krill swarms. However, it remains uncertain if energy is being introduced at scales large enough to induce the transport of fluid across surfaces of equal density. Within this context, the present study aims to provide experimental insight of fluid transport by planktonic swarms. The vertical migration of Artemia salina is triggered and controlled by means of a system of stationary and translating luminescent signals. High speed flow visualizations elucidate the competing effects of upward drift by the passive sections of the organisms and downward flow induced by the appendages. The resulting fluid transport is assessed by using PIV at different stages of the migration. The kinetic energy spectrum is computed using velocity correlation functions to determine the length scales at which the animals introduce energy to the flow.

  4. Surfactin restores and enhances swarming motility under heavy metal stress.

    Science.gov (United States)

    Singh, Anil Kumar; Dhanjal, Soniya; Cameotra, Swaranjit Singh

    2014-04-01

    The present work reports the importance of lipopeptide biosurfactant on swarming motility of multi-metal resistant (MMR) bacterium under heavy metal stress. The MMR bacteria strain CM100B, identified as Bacillus cereus, was isolated from the coal mine sample. The strain was able to grow and reduce several metals namely Cd(2+), Co(2+), Cu(2+), Ni(2+), Mn(2+) and Pb(2+) ions which are common environmental pollutants. Presence of toxic heavy metal ions in the swarming medium significantly altered the motility of CM100B. Presence of Cd(2+) and Pb(2+) ions inhibited development of peritrichous flagella, thus inhibiting swarming motility. However, the addition of anionic biosurfactant surfactin restored (in case of Cd(2+) and Pb(2+) ions) or enhanced (in case of Co(2+), Cu(2+), Ni(2+) and Mn(2+)) the swarming ability of CM100B. Zeta potential studies for determining bacterial cell surface charge indicated that surfactin provided a suitable swarming environment to bacteria even under metal stress by chelating to cationic metal ions. Non-ionic surfactant Triton X-100 was unable to restore swarming under Cd(2+) and Pb(2+) ion stress. Thus, suggesting that surfactin can aid in motility not only by reducing the surface tension of swarming medium but also by binding to metal ions in the presence of metal ions stress.

  5. Colias: An Autonomous Micro Robot for Swarm Robotic Applications

    Directory of Open Access Journals (Sweden)

    Farshad Arvin

    2014-07-01

    Full Text Available Robotic swarms that take inspiration from nature are becoming a fascinating topic for multi-robot researchers. The aim is to control a large number of simple robots in order to solve common complex tasks. Due to the hardware complexities and cost of robot platforms, current research in swarm robotics is mostly performed by simulation software. The simulation of large numbers of these robots in robotic swarm applications is extremely complex and often inaccurate due to the poor modelling of external conditions. In this paper, we present the design of a low-cost, open-platform, autonomous micro-robot (Colias for robotic swarm applications. Colias employs a circular platform with a diameter of 4 cm. It has a maximum speed of 35 cm/s which enables it to be used in swarm scenarios very quickly over large arenas. Long-range infrared modules with an adjustable output power allow the robot to communicate with its direct neighbours at a range of 0.5 cm to 2 m. Colias has been designed as a complete platform with supporting software development tools for robotics education and research. It has been tested in both individual and swarm scenarios, and the observed results demonstrate its feasibility for use as a micro-sized mobile robot and as a low-cost platform for robot swarm applications.

  6. Chaotic Particle Swarm Optimization with Mutation for Classification

    Science.gov (United States)

    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

  7. Particle Swarm Optimization With Interswarm Interactive Learning Strategy.

    Science.gov (United States)

    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.

  8. Chaotic particle swarm optimization with mutation for classification.

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  10. A minimal model of predator-swarm interactions.

    Science.gov (United States)

    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.

  11. Fractional order Darwinian particle swarm optimization applications and evaluation of an evolutionary algorithm

    CERN Document Server

    Couceiro, Micael

    2015-01-01

    This book examines the bottom-up applicability of swarm intelligence to solving multiple problems, such as curve fitting, image segmentation, and swarm robotics. It compares the capabilities of some of the better-known bio-inspired optimization approaches, especially Particle Swarm Optimization (PSO), Darwinian Particle Swarm Optimization (DPSO) and the recently proposed Fractional Order Darwinian Particle Swarm Optimization (FODPSO), and comprehensively discusses their advantages and disadvantages. Further, it demonstrates the superiority and key advantages of using the FODPSO algorithm, suc

  12. Confidential and Authenticated Communications in a Large Fixed-Wing UAV Swarm

    Science.gov (United States)

    2016-12-01

    swarms are a nascent technology promising useful military and civilian solutions to difficult problems. Securing data communications within the swarm is...civilian solutions to difficult problems. Securing data communications within the swarm is essential to accomplishing swarm objectives. The Naval...Source: [3]. The swarm communicates with an ALFA AWUS036NEH Long Range Wi-Fi Radio and processes information on an ODroid U3 computer with Ubuntu

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

    Science.gov (United States)

    2014-05-01

    impedes scalable human interaction with large bio -inspired robot swarms, namely how do you know what the swarm is doing if you can’t observe every agent...samples from a small subset of agents. We present a novel framework for classifying the collective behavior of a bio -inspired robot swarm using...locally-based approximations of a swarm’s global features. We apply this framework to two bio -inspired models of swarming that exhibit a flock and torus

  14. Buzz: An Extensible Programming Language for Self-Organizing Heterogeneous Robot Swarms

    OpenAIRE

    Pinciroli, Carlo; Lee-Brown, Adam; Beltrame, Giovanni

    2015-01-01

    We present Buzz, a novel programming language for heterogeneous robot swarms. Buzz advocates a compositional approach, offering primitives to define swarm behaviors both from the perspective of the single robot and of the overall swarm. Single-robot primitives include robot-specific instructions and manipulation of neighborhood data. Swarm-based primitives allow for the dynamic management of robot teams, and for sharing information globally across the swarm. Self-organization stems from the c...

  15. UAV swarm tactics: an agent-based simulation and Markov process analysis

    OpenAIRE

    Gaerther, Uwe

    2013-01-01

    Approved for public release; distribution is unlimited The rapid increase in the use of unmanned aerial vehicles (UAVs) in recent decades lead to their potential use as saturation or swarm threats to Allied Forces. One possible counter measure is the design and deployment of a defensive UAV swarm. This thesis identifies a future concept of swarm-versus-swarm UAV combat, focusing on the implications of swarm tactics and identifies important factors for such engagements. This work provides i...

  16. POLICE OFFICE MODEL IMPROVEMENT FOR SECURITY OF SWARM ROBOTIC SYSTEMS

    Directory of Open Access Journals (Sweden)

    I. A. Zikratov

    2014-09-01

    Full Text Available This paper focuses on aspects of information security for group of mobile robotic systems with swarm intellect. The ways for hidden attacks realization by the opposing party on swarm algorithm are discussed. We have fulfilled numerical modeling of potentially destructive information influence on the ant shortest path algorithm. We have demonstrated the consequences of attacks on the ant algorithm with different concentration in a swarm of subversive robots. Approaches are suggested for information security mechanisms in swarm robotic systems, based on the principles of centralized security management for mobile agents. We have developed the method of forming a self-organizing information security management system for robotic agents in swarm groups implementing POM (Police Office Model – a security model based on police offices, to provide information security in multi-agent systems. The method is based on the usage of police station network in the graph nodes, which have functions of identification and authentication of agents, identifying subversive robots by both their formal characteristics and their behavior in the swarm. We have suggested a list of software and hardware components for police stations, consisting of: communication channels between the robots in police office, nodes register, a database of robotic agents, a database of encryption and decryption module. We have suggested the variants of logic for the mechanism of information security in swarm systems with different temporary diagrams of data communication between police stations. We present comparative analysis of implementation of protected swarm systems depending on the functioning logic of police offices, integrated in swarm system. It is shown that the security model saves the ability to operate in noisy environments, when the duration of the interference is comparable to the time necessary for the agent to overcome the path between police stations.

  17. Study of Subsidence and Earthquake Swarms in the Western Pakistan

    Directory of Open Access Journals (Sweden)

    Jingqiu Huang

    2016-11-01

    Full Text Available In recent years, the Quetta Valley and surrounding areas have experienced unprecedented levels of subsidence, which has been attributed mainly to groundwater withdrawal. However, this region is also tectonically active and is home to several regional strike-slip faults, including the north–south striking left-lateral Chaman Fault System. Several large earthquakes have occurred recently in this area, including one deadly Mw 6.4 earthquake that struck on 28 October 2008. This study integrated Interferometric Synthetic Aperture Radar (InSAR results with GPS, gravity, seismic reflection profiles, and earthquake centroid-moment-tensor (CMT data to identify the impact of tectonic and anthropogenic processes on subsidence and earthquake patterns in this region. To detect and map the spatial-temporal features of the processes that led to the surface deformation, this study used two Synthetic Aperture Radar (SAR time series, i.e., 15 Phased Array L-band Synthetic Aperture Radar (PALSAR images acquired by an Advanced Land Observing Satellite (ALOS from 2006–2011 and 40 Environmental Satellite (ENVISAT Advanced Synthetic Aperture Radar (ASAR images spanning 2003–2010. A Small Baseline Subset (SBAS technique was used to investigate surface deformation. Five seismic lines totaling ~60 km, acquired in 2003, were used to map the blind thrust faults beneath a Quaternary alluvium layer. The median filtered SBAS-InSAR average velocity profile supports groundwater withdrawal as the dominant source of subsidence, with some contribution from tectonic subsidence in the Quetta Valley. Results of SBAS-InSAR multi-temporal analysis provide a better explanation for the pre-, co-, and post-seismic displacement pattern caused by the 2008 earthquake swarms across two strike-slip faults.

  18. A Particle Swarm Optimization with Adaptive Multi-Swarm Strategy for Capacitated Vehicle Routing Problem

    Directory of Open Access Journals (Sweden)

    Kui-Ting CHEN

    2015-12-01

    Full Text Available Capacitated vehicle routing problem with pickups and deliveries (CVRPPD is one of the most challenging combinatorial optimization problems which include goods delivery/pickup optimization, vehicle number optimization, routing path optimization and transportation cost minimization. The conventional particle swarm optimization (PSO is difficult to find an optimal solution of the CVRPPD due to its simple search strategy. A PSO with adaptive multi-swarm strategy (AMSPSO is proposed to solve the CVRPPD in this paper. The proposed AMSPSO employs multiple PSO algorithms and an adaptive algorithm with punishment mechanism to search the optimal solution, which can deal with large-scale optimization problems. The simulation results prove that the proposed AMSPSO can solve the CVRPPD with the least number of vehicles and less transportation cost, simultaneously.

  19. Maxime Miranda in Minimis: Reimagining Swarm Consciousness and Planetary Responsibility

    OpenAIRE

    Ask Nunes, Denise

    2015-01-01

    This essay explores Swarm Consciousness in relation to the novels Ender’s Game by Orson Scott Card, Remembering Babylon by David Malouf, and the manga Nausicaä of the Valley of the Wind by Hayao Miyazaki. Through these novels, Swarm Consciousness can be reimagined in order to challenge the ways insects have previously been considered in literature. Swarm Consciousness is originally a concept from biology that explains the self-organizing systems of social insects such as for example bees or a...

  20. Swarms of particles settling under gravity in a viscous fluid

    CERN Document Server

    Ekiel-Jezewska, Maria L

    2012-01-01

    We investigate swarms made of a small number of particles settling under gravity in a viscous fluid. The particles do not touch each other and can move relative to each other. The dynamics is analyzed in the point-particle approximation. A family of swarms is found with periodic oscillations of all the settling particles. In the presence of an additional particle above the swarm, the trajectories are horizontally repelled from the symmetry axis, and flattened vertically. The results are used to explain how a spherical cloud, made of a large number of particles distributed at random, evolves and destabilizes.

  1. Software Project Scheduling Management by Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Dinesh B. Hanchate

    2014-12-01

    Full Text Available PSO (Particle Swarm Optimization is, like GA, a heuristic global optimization method based on swarm intelligence. In this paper, we present a particle swarm optimization algorithm to solve software project scheduling problem. PSO itself inherits very efficient local search method to find the near optimal and best-known solutions for all instances given as inputs required for SPSM (Software Project Scheduling Management. At last, this paper imparts PSO and research situation with SPSM. The effect of PSO parameter on project cost and time is studied and some better results in terms of minimum SCE (Software Cost Estimation and time as compared to GA and ACO are obtained.

  2. Adaptive swarm-based routing in communication networks

    Institute of Scientific and Technical Information of China (English)

    吕勇; 赵光宙; 苏凡军; 历小润

    2004-01-01

    Swarm intelligence inspired by the social behavior of ants boasts a number of attractive features, including adaptation, robustness and distributed, decentralized nature, which are well suited for routing in modern communication networks. This paper describes an adaptive swarm-based routing algorithm that increases convergence speed, reduces routing instabilities and oscillations by using a novel variation of reinforcement learning and a technique called momentum.Experiment on the dynamic network showed that adaptive swarm-based routing learns the optimum routing in terms of convergence speed and average packet latency.

  3. Adaptive swarm-based routing in communication networks

    Institute of Scientific and Technical Information of China (English)

    吕勇; 赵光宙; 苏凡军; 历小润

    2004-01-01

    Swarm intelligence inspired by the social behavior of ants boasts a number of attractive features,including adaptation,robustness and distributed,decentralized nature,which are well suited for routing in modern communication networks.This paper describes an adaptive swarm-based routing algorithm that increases convergence speed,reduces routing instabilities and oscillations by using a novel variation of reinforcement learning and a technique called momentum.Experiment on the dynamic network showed that adaptive swarm-based routing learns the optimum routing in terms of convergence speed and average packet latency.

  4. A Machine Learning and Optimization Toolkit for the Swarm

    Science.gov (United States)

    2014-11-17

    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...design  by   •  Exploi0ng  component-­‐level  interac0ons  in  the   swarm   •  Restoring  the  system  level  roots

  5. Maxime Miranda in Minimis: Reimagining Swarm Consciousness and Planetary Responsibility

    OpenAIRE

    Ask Nunes, Denise

    2015-01-01

    This essay explores Swarm Consciousness in relation to the novels Ender’s Game by Orson Scott Card, Remembering Babylon by David Malouf, and the manga Nausicaä of the Valley of the Wind by Hayao Miyazaki. Through these novels, Swarm Consciousness can be reimagined in order to challenge the ways insects have previously been considered in literature. Swarm Consciousness is originally a concept from biology that explains the self-organizing systems of social insects such as for example bees or a...

  6. Self-organization in bacterial swarming: lessons from myxobacteria

    Science.gov (United States)

    Wu, Yilin; Jiang, Yi; Kaiser, A. Dale; Alber, Mark

    2011-10-01

    When colonizing surfaces, many bacteria are able to self-organize into an actively expanding biofilm, in which millions of cells move smoothly and orderly at high densities. This phenomenon is known as bacterial swarming. Despite the apparent resemblance to patterns seen in liquid crystals, the dynamics of bacterial swarming cannot be explained by theories derived from equilibrium statistical mechanics. To understand how bacteria swarm, a central question is how order emerges in dense and initially disorganized populations of bacterial cells. Here we briefly review recent efforts, with integrated computational and experimental approaches, in addressing this question.

  7. Collective Energy Foraging of Robot Swarms and Robot Organisms

    CERN Document Server

    Kernbach, Serge

    2011-01-01

    Cooperation and competition among stand-alone swarm agents increase collective fitness of the whole system. A principally new kind of collective systems is demonstrated by some bacteria and fungi, when they build symbiotic organisms. Symbiotic life forms emerge new functional and self-developmental capabilities, which allow better survival of swarm agents in different environments. In this paper we consider energy foraging scenario for two robotic species, swarm robots and symbiotic robot organism. It is indicated that aggregation of microrobots into a robot organism can provide better functional fitness for the whole group. A prototype of microrobots capable of autonomous aggregation and disaggregation are shown.

  8. Simultaneous field-aligned currents at Swarm and Cluster satellites

    DEFF Research Database (Denmark)

    Dunlop, M. W.; Yang, J. Y.; Yang, Y. Y.

    2015-01-01

    We show for the first time, with direct, multispacecraft calculations of electric current density, and other methods, matched signatures of field-aligned currents (FACs) sampled simultaneously near the ionosphere at low (∼500km altitude) orbit and in the magnetosphere at medium (similar to 2.5 RE...... find clear evidence of both small-scale and large-scale FACs and clear matching of the behavior and structure of the large-scale currents at both Cluster and Swarm. The methodology is made possible through the joint operations of Cluster and Swarm, which contain, in the first several months of Swarm...... operations, a number of close three-spacecraft configurations....

  9. A new hybrid optimization method inspired from swarm intelligence: Fuzzy adaptive swallow swarm optimization algorithm (FASSO

    Directory of Open Access Journals (Sweden)

    Mehdi Neshat

    2015-11-01

    Full Text Available In this article, the objective was to present effective and optimal strategies aimed at improving the Swallow Swarm Optimization (SSO method. The SSO is one of the best optimization methods based on swarm intelligence which is inspired by the intelligent behaviors of swallows. It has been able to offer a relatively strong method for solving optimization problems. However, despite its many advantages, the SSO suffers from two shortcomings. Firstly, particles movement speed is not controlled satisfactorily during the search due to the lack of an inertia weight. Secondly, the variables of the acceleration coefficient are not able to strike a balance between the local and the global searches because they are not sufficiently flexible in complex environments. Therefore, the SSO algorithm does not provide adequate results when it searches in functions such as the Step or Quadric function. Hence, the fuzzy adaptive Swallow Swarm Optimization (FASSO method was introduced to deal with these problems. Meanwhile, results enjoy high accuracy which are obtained by using an adaptive inertia weight and through combining two fuzzy logic systems to accurately calculate the acceleration coefficients. High speed of convergence, avoidance from falling into local extremum, and high level of error tolerance are the advantages of proposed method. The FASSO was compared with eleven of the best PSO methods and SSO in 18 benchmark functions. Finally, significant results were obtained.

  10. Performance Evaluation of OLSR Using Swarm Intelligence and Hybrid Particle Swarm Optimization Using Gravitational Search Algorithm

    Directory of Open Access Journals (Sweden)

    S. Meenakshi Sundaram

    2014-04-01

    Full Text Available The aim of this research is to evaluate the performance of OLSR using swarm intelligence and HPSO with Gravitational search algorithm to lower the jitter time, data drop and end to end delay and improve the network throughput. Simulation was carried out for multimedia traffic and video streamed network traffic using OPNET Simulator. Routing is exchanging of information from one host to another in a network. Routing forwards packets to destination using an efficient path. Path efficiency is measured through metrics like hop number, traffic and security. Each host node acts as a specialized router in Ad-hoc networks. A table driven proactive routing protocol Optimized Link State Protocol (OLSR has available topology information and routes. OLSR’s efficiency depends on Multipoint relay selection. Various studies were conducted to decrease control traffic overheads through modification of existing OLSR routing protocol and traffic shaping based on packet priority. This study proposes a modification of OLSR using swarm intelligence, Hybrid Particle Swarm Optimization (HPSO using Gravitational Search Algorithm (GSA and evaluation of performance of jitter, end to end delay, data drop and throughput. Simulation was carried out to investigate the proposed method for the network’s multimedia traffic.

  11. Interactive Sonification of Spontaneous Movement of Children - Cross-modal Mapping and the Perception of Body Movement Qualities through Sound

    Directory of Open Access Journals (Sweden)

    Emma Frid

    2016-11-01

    -modal mapping of body motion qualitiesfrom bodily movement to sounds. Sound can be translated and understood from bodily motion,conveyed through sound visualizations in the shape of drawings and translated back from sound visualizations to audio. The work underlines the potential of using interactive sonification to communicate high-level features of human movement data.

  12. Interactive Sonification of Spontaneous Movement of Children—Cross-Modal Mapping and the Perception of Body Movement Qualities through Sound

    Science.gov (United States)

    Frid, Emma; Bresin, Roberto; Alborno, Paolo; Elblaus, Ludvig

    2016-01-01

    cross-modal mapping of body motion qualities from bodily movement to sounds. Sound can be translated and understood from bodily motion, conveyed through sound visualizations in the shape of drawings and translated back from sound visualizations to audio. The work underlines the potential of using interactive sonification to communicate high-level features of human movement data. PMID:27891074

  13. Antenna optimization using Particle Swarm Optimization algorithm

    Directory of Open Access Journals (Sweden)

    Golubović Ružica M.

    2006-01-01

    Full Text Available We present the results for two different antenna optimization problems that are found using the Particle Swarm Optimization (PSO algorithm. The first problem is finding the maximal forward gain of a Yagi antenna. The second problem is finding the optimal feeding of a broadside antenna array. The optimization problems have 6 and 20 optimization variables, respectively. The preferred values of the parameters of the PSO algorithm are found for presented problems. The results show that the preferred parameters of PSO are somewhat different for optimization problems with different number of dimensions of the optimization space. The results that are found using the PSO algorithm are compared with the results that are found using other optimization algorithms, in order to estimate the efficiency of the PSO.

  14. Improvements To Glowworm Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Piotr Oramus

    2010-01-01

    Full Text Available Glowworm Swarm Optimization algorithm is applied for the simultaneous capture of multipleoptima of multimodal functions. The algorithm uses an ensemble of agents, which scan thesearch space and exchange information concerning a fitness of their current position. Thefitness is represented by a level of a luminescent quantity called luciferin. An agent movesin direction of randomly chosen neighbour, which broadcasts higher value of the luciferin.Unfortunately, in the absence of neighbours, the agent does not move at all. This is anunwelcome feature, because it diminishes the performance of the algorithm. Additionally,in the case of parallel processing, this feature can lead to unbalanced loads. This paperpresents simple modifications of the original algorithm, which improve performance of thealgorithm by limiting situations, in which the agent cannot move. The paper provides resultsof comparison of an original and modified algorithms calculated for several multimodal testfunctions.

  15. Particle Swarm Optimization for Outdoor Lighting Design

    Directory of Open Access Journals (Sweden)

    Ana Castillo-Martinez

    2017-01-01

    Full Text Available Outdoor lighting is an essential service for modern life. However, the high influence of this type of facility on energy consumption makes it necessary to take extra care in the design phase. Therefore, this manuscript describes an algorithm to help light designers to get, in an easy way, the best configuration parameters and to improve energy efficiency, while ensuring a minimum level of overall uniformity. To make this possible, we used a particle swarm optimization (PSO algorithm. These algorithms are well established, and are simple and effective to solve optimization problems. To take into account the most influential parameters on lighting and energy efficiency, 500 simulations were performed using DIALux software (4.10.0.2, DIAL, Ludenscheid, Germany. Next, the relation between these parameters was studied using to data mining software. Subsequently, we conducted two experiments for setting parameters that enabled the best configuration algorithm in order to improve efficiency in the proposed process optimization.

  16. SWARM - An earth Observation Mission investigating Geospace

    DEFF Research Database (Denmark)

    Friis-Christensen, Eigil; Lühr, H.; Knudsen, D.;

    2008-01-01

    The Swarm mission was selected as the 5th mission in ESA's Earth Explorer Programme in 2004. This mission aims at measuring the Earth's magnetic field with unprecedented accuracy. This will be done by a constellation of three satellites, where two will fly at lower altitude, measuring the gradient...... of the magnetic field, and one satellite will fly at higher altitude. The measured magnetic field is the sum of many contributions including both magnetic fields and currents in the Earth's interior and electrical currents in Geospace. In order to separate all these sources electric field and plasma measurements...... will also be made to complement the primary magnetic field measurements. Together these will allow the deduction of information on a series of solid earth processes responsible for the creation of the fields measured. The completeness of the measurements on each satellite and the constellation aspect...

  17. Semisupervised Particle Swarm Optimization for Classification

    Directory of Open Access Journals (Sweden)

    Xiangrong Zhang

    2014-01-01

    Full Text Available A semisupervised classification method based on particle swarm optimization (PSO is proposed. The semisupervised PSO simultaneously uses limited labeled samples and large amounts of unlabeled samples to find a collection of prototypes (or centroids that are considered to precisely represent the patterns of the whole data, and then, in principle of the “nearest neighborhood,” the unlabeled data can be classified with the obtained prototypes. In order to validate the performance of the proposed method, we compare the classification accuracy of PSO classifier, k-nearest neighbor algorithm, and support vector machine on six UCI datasets, four typical artificial datasets, and the USPS handwritten dataset. Experimental results demonstrate that the proposed method has good performance even with very limited labeled samples due to the usage of both discriminant information provided by labeled samples and the structure information provided by unlabeled samples.

  18. Apical-dominant particle swarm optimization

    Institute of Scientific and Technical Information of China (English)

    Zhihua Cui; Xingjuan Cai; Jianchao Zeng; Guoji Sun

    2008-01-01

    Particle swarm optimization (PSO) is a new stochastic population-based search methodology by simulating the animal social behaviors such as birds flocking and fish schooling.Many improvements have been proposed within the framework of this biological assumption.However,in this paper,the search pattern of PSO is used to model the branch growth process of natural plants.It provides a different poten-tial manner from artificial plant.To illustrate the effectiveness of this new model,apical dominance phenomenon is introduced to construct a novel variant by emphasizing the influence of the phototaxis.In this improvement,the population is divided into three different kinds of buds associated with their performances.Furthermore,a mutation strategy is applied to enhance the ability escaping from a local optimum.Sim-ulation results demonstrate good performance of the new method when solving high-dimensional multi-modal problems.

  19. Cosmological parameter estimation using Particle Swarm Optimization

    Science.gov (United States)

    Prasad, J.; Souradeep, T.

    2014-03-01

    Constraining parameters of a theoretical model from observational data is an important exercise in cosmology. There are many theoretically motivated models, which demand greater number of cosmological parameters than the standard model of cosmology uses, and make the problem of parameter estimation challenging. It is a common practice to employ Bayesian formalism for parameter estimation for which, in general, likelihood surface is probed. For the standard cosmological model with six parameters, likelihood surface is quite smooth and does not have local maxima, and sampling based methods like Markov Chain Monte Carlo (MCMC) method are quite successful. However, when there are a large number of parameters or the likelihood surface is not smooth, other methods may be more effective. In this paper, we have demonstrated application of another method inspired from artificial intelligence, called Particle Swarm Optimization (PSO) for estimating cosmological parameters from Cosmic Microwave Background (CMB) data taken from the WMAP satellite.

  20. Optimizing Information Credibility in Social Swarming Applications

    CERN Document Server

    Liu, Bin; Bar-Noyz, Amotz; Govindan, Ramesh; Neely, Michael J

    2010-01-01

    With the advent of smartphone technology, it has become possible to conceive of entirely new classes of applications. Social swarming, in which users armed with smartphones are directed by a central director to report on events in the physical world, has several real-world applications: search and rescue, coordinated fire-fighting, and the DARPA balloon hunt challenge. In this paper, we focus on the following problem: how does the director optimize the selection of reporters to deliver credible corroborating information about an event. We first propose a model, based on common intuitions of believability, about the credibility of information. We then cast the problem posed above as a discrete optimization problem, and introduce optimal centralized solutions and an approximate solution amenable to decentralized implementation whose performance is about 20% off on average from the optimal (on real-world datasets derived from Google News) while being 3 orders of magnitude more computationally efficient. More int...

  1. Swarm intelligence in animals and humans.

    Science.gov (United States)

    Krause, Jens; Ruxton, Graeme D; Krause, Stefan

    2010-01-01

    Electronic media have unlocked a hitherto largely untapped potential for swarm intelligence (SI; generally, the realisation that group living can facilitate solving cognitive problems that go beyond the capacity of single animals) in humans with relevance for areas such as company management, prediction of elections, product development and the entertainment industry. SI is a rapidly developing topic that has become a hotbed for both innovative research and wild speculation. Here, we tie together approaches from seemingly disparate areas by means of a general definition of SI to unite SI work on both animal and human groups. Furthermore, we identify criteria that are important for SI to operate and propose areas in which further progress with SI research can be made.

  2. Pattern Clustering Using a Swarm Intelligence Approach

    Science.gov (United States)

    Das, Swagatam; Abraham, Ajith

    Clustering aims at representing large datasets by a fewer number of prototypes or clusters. It brings simplicity in modeling data and thus plays a central role in the process of knowledge discovery and data mining. Data mining tasks, in these days, require fast and accurate partitioning of huge datasets, which may come with a variety of attributes or features. This, in turn, imposes severe computational requirements on the relevant clustering techniques. A family of bio-inspired algorithms, well-known as Swarm Intelligence (SI) has recently emerged that meets these requirements and has successfully been applied to a number of real world clustering problems. This chapter explores the role of SI in clustering different kinds of datasets. It finally describes a new SI technique for partitioning a linearly non-separable dataset into an optimal number of clusters in the kernel- induced feature space. Computer simulations undertaken in this research have also been provided to demonstrate the effectiveness of the proposed algorithm.

  3. Acceleration Factor Harmonious Particle Swarm Optimizer

    Institute of Scientific and Technical Information of China (English)

    Jie Chen; Feng Pan; Tao Cai

    2006-01-01

    A Particle Swarm Optimizer (PSO) exhibits good performance for optimization problems, although it cannot guarantee convergence to a global, or even local minimum. However, there are some adjustable parameters, and restrictive conditions, which can affect the performance of the algorithm. In this paper, the sufficient conditions for the asymptotic stability of an acceleration factor and inertia weight are deduced, the value of the inertia weight ω is enhanced to (-1, 1).Furthermore a new adaptive PSO algorithm - Acceleration Factor Harmonious PSO (AFHPSO) is proposed, and is proved to be a global search algorithm. AFHPSO is used for the parameter design of a fuzzy controller for a linear motor driving servo system. The performance of the nonlinear model for the servo system demonstrates the effectiveness of the optimized fuzzy controller and AFHPSO.

  4. Acoustic network event classification using swarm optimization

    Science.gov (United States)

    Burman, Jerry

    2013-05-01

    Classifying acoustic signals detected by distributed sensor networks is a difficult problem due to the wide variations that can occur in the transmission of terrestrial, subterranean, seismic and aerial events. An acoustic event classifier was developed that uses particle swarm optimization to perform a flexible time correlation of a sensed acoustic signature to reference data. In order to mitigate the effects from interference such as multipath, the classifier fuses signatures from multiple sensors to form a composite sensed acoustic signature and then automatically matches the composite signature with reference data. The approach can classify all types of acoustic events but is particularly well suited to explosive events such as gun shots, mortar blasts and improvised explosive devices that produce an acoustic signature having a shock wave component that is aperiodic and non-linear. The classifier was applied to field data and yielded excellent results in terms of reconstructing degraded acoustic signatures from multiple sensors and in classifying disparate acoustic events.

  5. Particle Swarm Optimization Based Reactive Power Optimization

    CERN Document Server

    Sujin, P R; Linda, M Mary

    2010-01-01

    Reactive power plays an important role in supporting the real power transfer by maintaining voltage stability and system reliability. It is a critical element for a transmission operator to ensure the reliability of an electric system while minimizing the cost associated with it. The traditional objectives of reactive power dispatch are focused on the technical side of reactive support such as minimization of transmission losses. Reactive power cost compensation to a generator is based on the incurred cost of its reactive power contribution less the cost of its obligation to support the active power delivery. In this paper an efficient Particle Swarm Optimization (PSO) based reactive power optimization approach is presented. The optimal reactive power dispatch problem is a nonlinear optimization problem with several constraints. The objective of the proposed PSO is to minimize the total support cost from generators and reactive compensators. It is achieved by maintaining the whole system power loss as minimum...

  6. Investigating the auroral electrojets using Swarm

    Science.gov (United States)

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

    2016-04-01

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

  7. Particle swarm optimization based optimal bidding strategy in an ...

    African Journals Online (AJOL)

    user

    Particle swarm optimization based optimal bidding strategy in an open ... relaxation-based approach for strategic bidding in England-Wales pool type electricity market has ... presents the mathematical formulation of optimal bidding problem.

  8. Swarming modulatory effects of some amino acids on Proteus ...

    African Journals Online (AJOL)

    TonukariJ

    Key words: Proteus strains, swarming motility, amino acids, Lagos. INTRODUCTION ... motility on nutrient and blood agar media were recruited for study. They were ... determine the concentration of total protein secreted by the Proteus strains ...

  9. SCARF - The Swarm Satellite Constellation Application and Research Facility

    DEFF Research Database (Denmark)

    Olsen, Nils

    2014-01-01

    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. In order to take advantage of the unique constellation aspect of Swarm, considerably advanced data analysis tools have been developed. Scientific users will also benefit significantly from...... derived products, the so-called Level-2 products, that take into account the features of the constellation. The Swarm SCARF (Satellite Constellation Application and Research Facility), a consortium of several research institutions, has been established with the goal of deriving Level-2 products...

  10. Self-Assembling Wireless Autonomous Reconfigurable Modules (SWARM) Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Payload Systems Inc. and the MIT Space Systems Laboratory propose Self-assembling, Wireless, Autonomous, Reconfigurable Modules (SWARM) as an innovative approach to...

  11. Behavior-Based Formation Control of Swarm Robots

    Directory of Open Access Journals (Sweden)

    Dongdong Xu

    2014-01-01

    Full Text Available Swarm robotics is a specific research field of multirobotics where a large number of mobile robots are controlled in a coordinated way. Formation control is one of the most challenging goals for the coordination control of swarm robots. In this paper, a behavior-based control design approach is proposed for two kinds of important formation control problems: efficient initial formation and formation control while avoiding obstacles. In this approach, a classification-based searching method for generating large-scale robot formation is presented to reduce the computational complexity and speed up the initial formation process for any desired formation. The behavior-based method is applied for the formation control of swarm robot systems while navigating in an unknown environment with obstacles. Several groups of experimental results demonstrate the success of the proposed approach. These methods have potential applications for various swarm robot systems in both the simulation and the practical environments.

  12. Collective Behavior of Animals: Swarming and Complex Patterns

    National Research Council Canada - National Science Library

    Cañizo, J. A; Rosado, J; Carrillo, J. A

    2010-01-01

    ...) models are questions of actual interest in mathematical biology research. En esta nota repasamos algunos modelos basados en individuos para describir el movimiento colectivo de agentes, a lo que nos referimos usando la voz inglesa swarming...

  13. code_swarm: a design study in organic software visualization.

    Science.gov (United States)

    Ogawa, Michael; Ma, Kwan-Liu

    2009-01-01

    In May of 2008, we published online a series of software visualization videos using a method called code_swarm. Shortly thereafter, we made the code open source and its popularity took off. This paper is a study of our code swarm application, comprising its design, results and public response. We share our design methodology, including why we chose the organic information visualization technique, how we designed for both developers and a casual audience, and what lessons we learned from our experiment. We validate the results produced by code_swarm through a qualitative analysis and by gathering online user comments. Furthermore, we successfully released the code as open source, and the software community used it to visualize their own projects and shared their results as well. In the end, we believe code_swarm has positive implications for the future of organic information design and open source information visualization practice.

  14. APPLICATION OF A PARTICLE SWARM OPTIMIZATION IN AN ...

    African Journals Online (AJOL)

    Key words: Load flow, Optimal Power Flow, Power System, Particle Swarm ... the PSO method has been employed to solve economic dispatch problem. .... Once the reconstruction operators have been applied and the control variables values.

  15. Intermittent swarming of copepods in Versova mangrove, Mumbai

    Digital Repository Service at National Institute of Oceanography (India)

    Stephen, R.; Jayalakshmy, K.V.; Nair, V.R.

    suggested as an adaptive advantage for feeding, propagation, protection and dispersal by currents. Copepod swarms are usually monospecific and are composed of adult and late stage copepodites. While studying the copepod composition of Versova mangrove...

  16. Femto-satellite Swarm State and Density Estimation Project

    Data.gov (United States)

    National Aeronautics and Space Administration — NASA is planning future missions involving fleets of small satellites in LEO and GEO that can exhibit autonomous collective behavior. Such a "swarm of...

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

    Science.gov (United States)

    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.

  18. Swarm-based Sequencing Recommendations in E-learning

    NARCIS (Netherlands)

    Van den Berg, Bert; Tattersall, Colin; Janssen, José; Brouns, Francis; Kurvers, Hub; Koper, Rob

    2005-01-01

    Van den Berg, B., Tattersall, C., Janssen, J., Brouns, F., Kurvers, H., & Koper, R. (2006). Swarm-based Sequencing Recommendations in E-learning. International Journal of Computer Science & Applications, III(III), 1-11.

  19. A Markov Chain Approach to Probabilistic Swarm Guidance

    Science.gov (United States)

    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.

  20. Formation Control of Robotic Swarm Using Bounded Artificial Forces

    Directory of Open Access Journals (Sweden)

    Long Qin

    2013-01-01

    Full Text Available 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Wenwu, E-mail: wenwuyu@gmail.com [Department of Mathematics, Southeast University, Nanjing 210096 (China); School of Electrical and Computer Engineering, RMIT University, Melbourne VIC 3001 (Australia); Chen, Guanrong [Department of Electronic Engineering, City University of Hong Kong, Hong Kong (China); Cao, Ming [Faculty of Mathematics and Natural Sciences, ITM, University of Groningen (Netherlands); Lü, Jinhu [Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190 (China); Zhang, Hai-Tao [Department of Control Science and Engineering, State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China)

    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 agent 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.

  2. The Swarm Initial Field Model for the 2014 geomagnetic field

    DEFF Research Database (Denmark)

    Olsen, Nils; Hulot, Gauthier; Lesur, Vincent;

    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...

  3. Swimming and swarming motility properties of peanut-nodulating rhizobia.

    Science.gov (United States)

    Vicario, Julio C; Dardanelli, Marta S; Giordano, Walter

    2015-01-01

    Motility allows populations of bacteria to rapidly reach and colonize new microniches or microhabitats. The motility of rhizobia (symbiotic nitrogen-fixing bacteria that nodulate legume roots) is an important factor determining their competitive success. We evaluated the effects of temperature, incubation time, and seed exudates on swimming and swarming motility of five strains of Bradyrhizobium sp. (peanut-nodulating rhizobia). Swimming motility was increased by exudate exposure for all strains except native Pc34. In contrast, swarming motility was increased by exudate exposure for native 15A but unchanged for the other four strains. All five strains displayed the ability to differentiate into swarm cells. Morphological examination by scanning electron microscopy showed that the length of the swarm cells was variable, but generally greater than that of vegetative cells. Our findings suggest the importance of differential motility properties of peanut-nodulating rhizobial strains during agricultural inoculation and early steps of symbiotic interaction with the host.

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

    Science.gov (United States)

    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.

  5. Interaction field modeling of mini-UAV swarm

    Science.gov (United States)

    Liou, William W.; Ro, Kapseong; Szu, Harold

    2006-05-01

    A behavior-based, simple interaction model inspired by molecular interaction field depicted by the Lennard-Jones function is examined for the averaged interaction in swarming. The modeled kinematic equation of motion contains only one variable, instead of a multiple state variable dependence a more complete dynamics entails. The model assumes a spatial distribution of the potential associate with the swarm. The model has been applied to examine the formation of swarm and the results are reported. The modeling can be reflected in an equilibrium theory for the operation of a swarm of mini-UAVs pioneered by Szu, where every member serves the mission while exploiting other's loss, resulting in a zero-sum game among the team members.

  6. LinkMind: Link Optimization in Swarming Mobile Sensor Networks

    Directory of Open Access Journals (Sweden)

    Trung Dung Ngo

    2011-08-01

    Full Text Available 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.

  7. Stable swarming using adaptive long-range interactions

    Science.gov (United States)

    Gorbonos, Dan; Gov, Nir S.

    2017-04-01

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

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

    Science.gov (United States)

    Yu, Wenwu; Chen, Guanrong; Cao, Ming; Lü, Jinhu; Zhang, Hai-Tao

    2013-12-01

    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 agent 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.

  9. Percepção e estruturação de problemas sociais utilizando mapas cognitivos Perception and structuring of social problems using cognitive maps

    Directory of Open Access Journals (Sweden)

    Milena Estanislau Diniz

    2012-01-01

    Full Text Available Este trabalho propõe a estruturação de dois problemas sociais complexos baseados na construção e análise de mapas cognitivos. Esta estruturação está baseada na percepção das pessoas, mais precisamente dos estados mentais captados do discurso, relativos ao comportamento de agentes de áreas sociais. O estudo visou estender a compreensão de problemas sociais como o de segurança pública e saúde pública através da realização de dois estudos de caso. A elaboração dos mapas cognitivos permitiu explicitar as inferências dos especialistas referentes à tomada de decisão e nas ações. Uma visão mais integrada dos problemas da segurança pública e da crise dos hospitais universitários foi obtida. Além disso, o presente trabalho disponibilizou um registro da visão estratégica dos entrevistados diante de dois problemas sociais complexos que impactam diretamente a qualidade de vida da sociedade.This work proposes a systematization of social problems based on the construction and analysis of cognitive maps. This arrangement is based on the perception of people; more precisely, on the inference of mental states regarding the behavior of social agents given in speech of experts. This study aimed to broaden the understanding of social problems, such as public safety and health, through the analyses of two case studies. The development of cognitive maps has clarified the implications of the experts concerning decision-making and actions. A more integrated view of the problems of public security and the crisis in university hospitals was obtained. In addition, this study provided a record of strategic view of the interviewees facing two complex social problems that directly impact the society's quality of life.

  10. Multi-Robot Motion Planning Using Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Gerasimos G. Rigatos

    2008-11-01

    Full Text Available Swarm intelligence theory is proposed for motion planning of multi-robot systems. Multiple particles start from different points in the solutions space and interact to each other while moving towards the goal position. Swarm intelligence theory is a derivative-free approach to the problem of multi-robotcooperation which works by searching iteratively in regions defined by each robot's best previous move and the best previous move of its neighbors. The method's performance is evaluated through simulation tests.

  11. Extending Particle Swarm Optimisers with Self-Organized Criticality

    DEFF Research Database (Denmark)

    Løvbjerg, Morten; Krink, Thiemo

    2002-01-01

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

  12. A Comparative Study of Several Hybrid Particle Swarm Algorithms for Function Optimization

    Directory of Open Access Journals (Sweden)

    Yanhua Zhong

    2012-11-01

    Full Text Available Currently, the researchers have made a lot of hybrid particle swarm algorithm in order to solve the shortcomings that the Particle Swarm Algorithms is easy to converge to local extremum, these algorithms declare that there has been better than the standard particle swarm. This study selects three kinds of representative hybrid particle swarm optimizations (differential evolution particle swarm optimization, GA particle swarm optimization, quantum particle swarm optimization and the standard particle swarm optimization to test with three objective functions. We compare evolutionary algorithm performance by a fixed number of iterations of the convergence speed and accuracy and the number of iterations under the fixed convergence precision; analyzing these types of hybrid particle swarm optimization results and practical performance. Test results show hybrid particle algorithm performance has improved significantly.

  13. A Comparative Study of Several Hybrid Particle Swarm Algorithms for Function Optimization

    Directory of Open Access Journals (Sweden)

    Yanhua Zhong

    2013-01-01

    Full Text Available Currently, the researchers have made a lot of hybrid particle swarm algorithm in order to solve the shortcomings that the Particle Swarm Algorithms is easy to converge to local extremum, these algorithms declare that there has been better than the standard particle swarm. This study selects three kinds of representative hybrid particle swarm optimizations (differential evolution particle swarm optimization, GA particle swarm optimization, quantum particle swarm optimization and the standard particle swarm optimization to test with three objective functions. We compare evolutionary algorithm performance by a fixed number of iterations of the convergence speed and accuracy and the number of iterations under the fixed convergence precision, analyzing these types of hybrid particle swarm optimization results and practical performance. Test results show hybrid particle algorithm performance has improved significantly.

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

    Science.gov (United States)

    Mier-y-Teran-Romero, Luis; Forgoston, Eric; Schwartz, Ira B.

    2013-01-01

    We consider a general swarm model of self-propelling agents interacting through a pairwise potential in the presence of noise and communication time delay. Previous work has shown that a communication time delay in the swarm induces a pattern bifurcation that depends 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 spatiotemporal scales of the swarm structures, as well as demonstrate how the complicated interplay of coupling strength, time delay, noise intensity, and choice of initial conditions can affect the swarm. In particular, our studies show 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. PMID:24255625

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

    Science.gov (United States)

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

    2017-04-01

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

  16. Non-swarming grasshoppers exhibit density-dependent phenotypic plasticity reminiscent of swarming locusts.

    Science.gov (United States)

    Gotham, Steven; Song, Hojun

    2013-11-01

    Locusts are well known for exhibiting an extreme form of density-dependent phenotypic plasticity known as locust phase polyphenism. At low density, locust nymphs are cryptically colored and shy, but at high density they transform into conspicuously colored and gregarious individuals. Most of what we know about locust phase polyphenism come from the study of the desert locust Schistocerca gregaria (Forskål), which is a devastating pest species affecting many countries in North Africa and the Middle East. The desert locust belongs to the grasshopper genus Schistocerca Stål, which includes mostly non-swarming, sedentary species. Recent phylogenetic studies suggest that the desert locust is the earliest branching lineage within Schistocerca, which raises a possibility that the presence of density-dependent phenotypic plasticity may be a plesiomorphic trait for the whole genus. In order to test this idea, we have quantified the effect of rearing density in terms of the resulting behavior, color, and morphology in two non-swarming Schistocerca species native to Florida. When reared in both isolated and crowded conditions, the two non-swarming species, Schistocerca americana (Drury) and Schistocerca serialis cubense (Saussure) clearly exhibited plastic reaction norms in all traits measured, which were reminiscent of the desert locust. Specifically, we found that both species were more active and more attracted to each other when reared in a crowded condition than in isolation. They were mainly bright green in color when isolated, but developed strong black patterns and conspicuous background colors when crowded. We found a strong effect of rearing density in terms of size. There were also more mechanoreceptor hairs on the outer face of the hind femora in the crowded nymphs in both species. Although both species responded similarly, there were some clear species-specific differences in terms of color and behavior. Furthermore, we compare and contrast our findings with

  17. Analysis of Changing Swarm Rate using Volumetric Strain

    Science.gov (United States)

    Kumazawa, T.; Ogata, Y.; Kimura, K.; Maeda, K.; Kobayashi, A.

    2015-12-01

    Near the eastern coast of Izu peninsula is an active submarine volcanic region in Japan, where magma intrusions have been observed many times. The forecast of earthquake swarm activities and eruptions are serious concern particularly in nearby hot spring resort areas. It is well known that temporal durations of the swarm activities have been correlated with early volumetric strain changes at a certain observation station of about 20 km distance apart. Therefore the Earthquake Research Committee (2010) investigated some empirical statistical relations to predict sizes of the swarm activity. Here we looked at the background seismicity rate changes during these swarm periods using the non-stationary ETAS model (Kumazawa and Ogata, 2013, 2014), and have found the followings. The modified volumetric strain data, by removing the effect of earth tides, precipitation and coseismic jumps, have significantly higher cross-correlations to the estimated background rates of the ETAS model than to the swarm rate-changes. Specifically, the background seismicity rate synchronizes clearer to the strain change by the lags around a half day. These relations suggest an enhanced prediction of earthquakes in this region using volumetric strain measurements. Hence we propose an extended ETAS model where the background rate is modulated by the volumetric strain data. We have also found that the response function to the strain data can be well approximated by an exponential functions with the same decay rate, but that their intersects are inversely proportional to the distances between the volumetric strain-meter and the onset location of the swarm. Our numerical results by the same proposed model show consistent outcomes for the various major swarms in this region.

  18. Middleware Design for Swarm-Driving Robots Accompanying Humans

    Science.gov (United States)

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

    2017-01-01

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

  19. Towards Mobile Microrobot Swarms for Additive Micromanufacturing

    Directory of Open Access Journals (Sweden)

    David Cappelleri

    2014-09-01

    Full Text Available In this paper, a novel approach to achieving the independent control of multiple magnetic microrobots is presented. The approach utilizes a specialized substrate consisting of a fine grid of planar, MEMS-fabricated micro coils of the same size as the microrobots (≤ 500 μm. The coils can be used to generate real magnetic potentials and, therefore, attractive and repulsive forces in the workspace to control the trajectories of the microrobots. Initial work on modelling the coil and microrobot behavior is reported along with simulation results for navigating one and two microrobots along independent desired trajectories. Qualitative results from a scaled-up printed circuit board version of the specialized substrate operating on permanent magnets are presented and offer proof-of-concept results for the approach. These tests also provide insights for practical implementations of such a system, which are similarly reported. The ultimate goal of this work is to use swarms of independently controlled microrobots in advanced, additive manufacturing applications.

  20. Flash Expansion Threshold in Whirligig Swarms.

    Directory of Open Access Journals (Sweden)

    William L Romey

    Full Text Available In the selfish herd hypothesis, prey animals move toward each other to avoid the likelihood of being selected by a predator. However, many grouped animals move away from each other the moment before a predator attacks. Very little is known about this phenomenon, called flash expansion, such as whether it is triggered by one individual or a threshold and how information is transferred between group members. We performed a controlled experiment with whirligig beetles in which the ratio of sighted to unsighted individuals was systematically varied and emergent flash expansion was measured. Specifically, we examined: the percentage of individuals in a group that startled, the resulting group area, and the longevity of the flash expansion. We found that one or two sighted beetles in a group of 24 was not enough to cause a flash expansion after a predator stimulus, but four sighted beetles usually initiated a flash expansion. Also, the more beetles that were sighted the larger the resulting group area and the longer duration of the flash expansion. We conclude that flash expansion is best described as a threshold event whose adaptive value is to prevent energetically costly false alarms while quickly mobilizing an emergent predator avoidance response. This is one of the first controlled experiments of flash expansion, an important emergent property that has applications to understanding collective motion in swarms, schools, flocks, and human crowds. Also, our study is a convincing demonstration of social contagion, how the actions of one individual can pass through a group.

  1. Searching for Planets using Particle Swarm Optimization

    Science.gov (United States)

    Chambers, John E.

    2008-05-01

    The Doppler radial velocity technique has been highly successful in discovering planetary-mass companions in orbit around nearby stars. A typical data set contains around one hundred instantaneous velocities for the star, spread over a period of several years,with each observation measuring only the radial component of velocity. From this data set, one would like to determine the masses and orbital parameters of the system of planets responsible for the star's reflex motion. Assuming coplanar orbits, each planet is characterized by five parameters, with an additional parameter for each telescope used to make observations, representing the instrument's velocity offset. The large number of free parameters and the relatively sparse data sets make the fitting process challenging when multiple planets are present, especially if some of these objects have low masses. Conventional approaches using periodograms often perform poorly when the orbital periods are not separated by large amounts or the longest period is comparable to the length of the data set. Here, I will describe a new approach to fitting Doppler radial velocity sets using particle swarm optimization (PSO). I will describe how the PSO method works, and show examples of PSO fits to existing radial velocity data sets, with comparisons to published solutions and those submitted to the Systemic website (http://www.oklo.org).

  2. Swarm intelligence: when uncertainty meets conflict.

    Science.gov (United States)

    Conradt, Larissa; List, Christian; Roper, Timothy J

    2013-11-01

    Good decision making is important for the survival and fitness of stakeholders, but decisions usually involve uncertainty and conflict. We know surprisingly little about profitable decision-making strategies in conflict situations. On the one hand, sharing decisions with others can pool information and decrease uncertainty (swarm intelligence). On the other hand, sharing decisions can hand influence to individuals whose goals conflict. Thus, when should an animal share decisions with others? Using a theoretical model, we show that, contrary to intuition, decision sharing by animals with conflicting goals often increases individual gains as well as decision accuracy. Thus, conflict-far from hampering effective decision making-can improve decision outcomes for all stakeholders, as long as they share large-scale goals. In contrast, decisions shared by animals without conflict were often surprisingly poor. The underlying mechanism is that animals with conflicting goals are less correlated in individual choice errors. These results provide a strong argument in the interest of all stakeholders for not excluding other (e.g., minority) factions from collective decisions. The observed benefits of including diverse factions among the decision makers could also be relevant to human collective decision making.

  3. Towards Mobile Microrobot Swarms for Additive Micromanufacturing

    Directory of Open Access Journals (Sweden)

    David Cappelleri

    2014-09-01

    Full Text Available In this paper, a novel approach to achieving the independent control of multiple magnetic microrobots is presented. The approach utilizes a specialized substrate consisting of a fine grid of planar, MEMS-fabricated micro coils of the same size as the microrobots (≤ 500 μm. The coils can be used to generate real magnetic potentials and, therefore, attractive and repulsive forces in the workspace to control the trajectories of the microrobots. Initial work on modelling the coil and microrobot behavior is reported along with simulation results for navigating one and two microrobots along independent desired trajectories. Qualitative results from a scaled-up printed circuit board version of the specialized substrate operating on permanent magnets are presented and offer proof-of-concept results for the approach. These tests also provide insights for practical implementations of such a system, which are similarly reported. The ultimate goal of this work is to use swarms of independently controlled microrobots in advanced, additive manufacturing applications.

  4. Particle Swarm Optimization for Structural Design Problems

    Directory of Open Access Journals (Sweden)

    Hamit SARUHAN

    2010-02-01

    Full Text Available The aim of this paper is to employ the Particle Swarm Optimization (PSO technique to a mechanical engineering design problem which is minimizing the volume of a cantilevered beam subject to bending strength constraints. Mechanical engineering design problems are complex activities which are computing capability are more and more required. The most of these problems are solved by conventional mathematical programming techniques that require gradient information. These techniques have several drawbacks from which the main one is becoming trapped in local optima. As an alternative to gradient-based techniques, the PSO does not require the evaluation of gradients of the objective function. The PSO algorithm employs the generation of guided random positions when they search for the global optimum point. The PSO which is a nature inspired heuristics search technique imitates the social behavior of bird flocking. The results obtained by the PSO are compared with Mathematical Programming (MP. It is demonstrated that the PSO performed and obtained better convergence reliability on the global optimum point than the MP. Using the MP, the volume of 2961000 mm3 was obtained while the beam volume of 2945345 mm3 was obtained by the PSO.

  5. Swarms, Phase Transitions, and Collective Intelligence

    CERN Document Server

    Millonas, M M

    1993-01-01

    A spacially extended model of the collective behavior of a large number of locally acting organisms is proposed in which organisms move probabilistically between local cells in space, but with weights dependent on local morphogenetic substances, or morphogens. The morphogens are in turn are effected by the passage of an organism. The evolution of the morphogens, and the corresponding flow of the organisms constitutes the collective behavior of the group. Such models have various types of phase transitions and self-organizing properties controlled both by the level of the noise, and other parameters. The model is then applied to the specific case of ants moving on a lattice. The local behavior of the ants is inspired by the actual behavior observed in the laboratory, and analytic results for the collective behavior are compared to the corresponding laboratory results. It is hoped that the present model might serve as a paradigmatic example of a complex cooperative system in nature. In particular swarm models c...

  6. Constructing a Graphic Organizer in the Classroom: Introductory Students' Perception of Achievement Using a Decision Map to Solve Aqueous Acid-Base Equilibria Problems

    Science.gov (United States)

    DeMeo, Stephen

    2007-01-01

    Common examples of graphic organizers include flow diagrams, concept maps, and decision trees. The author has created a novel type of graphic organizer called a decision map. A decision map is a directional heuristic that helps learners solve problems within a generic framework. It incorporates questions that the user must answer and contains…

  7. Induction of tryptophanase in short cells and swarm cells of Proteus vulgaris.

    OpenAIRE

    Hoffman, P S; Falkinham, J O

    1981-01-01

    Tryptophanase was noninducible in swarm cells of Proteus vulgaris despite transport of the inducer tryptophan. Further, cyclic AMP, which stimulated increased levels of tryptophanase in short cells, had no effect on swarm cells.

  8. Novel Particle Swarm Optimization and Its Application in Calibrating the Underwater Transponder Coordinates

    Directory of Open Access Journals (Sweden)

    Zheping Yan

    2014-01-01

    Full Text Available A novel improved particle swarm algorithm named competition particle swarm optimization (CPSO is proposed to calibrate the Underwater Transponder coordinates. To improve the performance of the algorithm, TVAC algorithm is introduced into CPSO to present an extension competition particle swarm optimization (ECPSO. The proposed method is tested with a set of 10 standard optimization benchmark problems and the results are compared with those obtained through existing PSO algorithms, basic particle swarm optimization (BPSO, linear decreasing inertia weight particle swarm optimization (LWPSO, exponential inertia weight particle swarm optimization (EPSO, and time-varying acceleration coefficient (TVAC. The results demonstrate that CPSO and ECPSO manifest faster searching speed, accuracy, and stability. The searching performance for multimodulus function of ECPSO is superior to CPSO. At last, calibration of the underwater transponder coordinates is present using particle swarm algorithm, and novel improved particle swarm algorithm shows better performance than other algorithms.

  9. Dyke Swarms of the Paraná Triple Junction, Southern Brazil

    Directory of Open Access Journals (Sweden)

    José Moacyr Vianna Coutinho

    2008-10-01

    Full Text Available This work intends primarily to survey the field, mineralogical and petrographic characters of the mafic dykes which occuron a stretch of 650 km along the Southeastern coast of Brazil, between the city of São Sebastião, and the island of SantaCatarina. New chemical and geochronological data are also presented. The coastal dyke swarms are envisaged as the northernand southern arms of a plume-generated triple junction system centered on the Paraná State coast, and related to the initialopening of the South Atlantic. Mafic magma intruded as dyke swarms along three directions: N-S (the southern arm, along theParaná-Santa Catarina coast, NW-SE (Ponta Grossa arch and NE-SW (the northern arm along the São Paulo coast. Fiftytwo dykes, almost all tholeiitic diabases, were mapped and sampled along the south arm coast. The Ponta Grossa arch dykes are chiefly composed of tholeiitic diabases and lesser intrusions of andesitic to rhyolitic composition. Over 240 dykes were sampled and identified along the north arm west of São Sebastião. Lamprophyres are here abundant, followed by diabases, microdiorite porphyries and lesser amounts of trachy-andesite, carbonatite and Precambrian dykes. Special attention was given to the study of lamprophyres, their field appearance relative abundance, mineral and chemical composition, enclaves and relations to neighboring alkaline intrusions.

  10. Lattice dynamical wavelet neural networks implemented using particle swarm optimization for spatio-temporal system identification.

    Science.gov (United States)

    Wei, Hua-Liang; Billings, Stephen A; Zhao, Yifan; Guo, Lingzhong

    2009-01-01

    In this brief, by combining an efficient wavelet representation with a coupled map lattice model, a new family of adaptive wavelet neural networks, called lattice dynamical wavelet neural networks (LDWNNs), is introduced for spatio-temporal system identification. A new orthogonal projection pursuit (OPP) method, coupled with a particle swarm optimization (PSO) algorithm, is proposed for augmenting the proposed network. A novel two-stage hybrid training scheme is developed for constructing a parsimonious network model. In the first stage, by applying the OPP algorithm, significant wavelet neurons are adaptively and successively recruited into the network, where adjustable parameters of the associated wavelet neurons are optimized using a particle swarm optimizer. The resultant network model, obtained in the first stage, however, may be redundant. In the second stage, an orthogonal least squares algorithm is then applied to refine and improve the initially trained network by removing redundant wavelet neurons from the network. An example for a real spatio-temporal system identification problem is presented to demonstrate the performance of the proposed new modeling framework.

  11. Dynamic Network Traffic Flow Prediction Model based on Modified Quantum-Behaved Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Hongying Jin

    2013-10-01

    Full Text Available This paper aims at effectively predicting the dynamic network traffic flow based on quantum-behaved particle swarm optimization algorithm. Firstly, the dynamic network traffic flow prediction problem is analyzed through formal description. Secondly, the structure of the network traffic flow prediction model is given. In this structure, Users can used a computer to start the traffic flow prediction process, and data collecting module can collect and return the data through the destination device. Thirdly, the dynamic network traffic flow prediction model is implemented based on BP Neural Network. Particularly, in this paper, the BP Neural Network is trained by a modified quantum-behaved particle swarm optimization(QPSO. We modified the QPSO by utilizing chaos signals to implement typical logistic mapping and pursuing the fitness function of a particle by a set of optimal parameters. Afterwards, based on the above process, dynamic network traffic flow prediction model is illustrated. Finally, a series of experiments are conduct to make performance evaluation, and related analyses for experimental results are also given

  12. Discrete ternary particle swarm optimization for area optimization of MPRM circuits

    Institute of Scientific and Technical Information of China (English)

    Yu Haizhen; Wang Pengjun; Wang Disheng; Zhang Huihong

    2013-01-01

    Having the advantage of simplicity,robustness and low computational costs,the particle swarm optimization (PSO) algorithm is a powerful evolutionary computation tool for synthesis and optimization of ReedMuller logic based circuits.Exploring discrete PSO and probabilistic transition rules,the discrete ternary particle swarm optimization (DTPSO) is proposed for mixed polarity Reed-Muller (MPRM) circuits.According to the characteristics of mixed polarity OR/XNOR expression,a tabular technique is improved,and it is applied in the polarity conversion of MPRM functions.DTPSO is introduced to search the best polarity for an area of MPRM circuits by building parameter mapping relationships between particles and polarities.The computational results show that the proposed DTPSO outperforms the reported method using maxterm conversion starting from POS Boolean functions.The average saving in the number of terms is about 11.5%; the algorithm is quite efficient in terms of CPU time and achieves 12.2% improvement on average.

  13. Numerical simulation of the 2008 West-Bohemian earthquake swarm

    Science.gov (United States)

    Heinze, Thomas; Hamidi, Sahar; Galvan, Boris; Miller, Stephen A.

    2017-01-01

    CO2 has long been suspected of driving the Bohemian earthquake swarms because of the migrating nature of the swarms and expressions of CO2 degassing at the surface. Modeling to date primarily employed linear diffusion models, but more sophisticated modeling that includes a coupled fluid - and rock mechanical model has been lacking. In this work, we apply a model that couples mechanics to heat and flow of a super-critical CO2 through a fracture network. We present a continuum mechanical approach to derive the seismic moment magnitude using the deviatoric strain as an indicator of rupturing processes during individual events. We use a peak-detection algorithm to identify rapid changes in deviatoric strain, indicative of slip events. This method has been shown to work very well in dry and fluid-induced fracturing experiments at the laboratory scale, and in this work we extend the method to the scale of the West Bohemia/Vogtland earthquake swarms. We show very good agreement between model results and observations of the 2008 swarm, further supporting the hypothesis that the Bohemian earthquake swarms are predominately fluid-driven.

  14. Rapid movement and instability of an invasive hybrid swarm.

    Science.gov (United States)

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

    2016-07-01

    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 hot spot 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.

  15. Discordant introgression in a rapidly expanding hybrid swarm

    Science.gov (United States)

    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.

  16. Simulation Study of Swarm Intelligence Based on Life Evolution Behavior

    Directory of Open Access Journals (Sweden)

    Yanmin Liu

    2015-01-01

    Full Text Available Swarm intelligence (SI is a new evolutionary computation technology, and its performance efficacy is usually affected by each individual behavior in the swarm. According to the genetic and sociological theory, the life evolution behavior process is influenced by the external and internal factors, so the mechanisms of external and internal environment change must be analyzed and explored. Therefore, in this paper, we used the thought of the famous American genetic biologist Morgan, “life = DNA + environment + interaction of environment + gene,” to propose the mutation and crossover operation of DNA fragments by the environmental change to improve the performance efficiency of intelligence algorithms. Additionally, PSO is a random swarm intelligence algorithm with the genetic and sociological property, so we embed the improved mutation and crossover operation to particle swarm optimization (PSO and designed DNA-PSO algorithm to optimize single and multiobjective optimization problems. Simulation experiments in single and multiobjective optimization problems show that the proposed strategies can effectively improve the performance of swarm intelligence.

  17. Modelling Oil-Spill Detection with Swarm Drones

    Directory of Open Access Journals (Sweden)

    F. Aznar

    2014-01-01

    Full Text Available Nowadays, swarm robotics research is having a great increase due to the benefits derived from its use, such as robustness, parallelism, and flexibility. Unlike distributed robotic systems, swarm robotics emphasizes a large number of robots, and promotes scalability. Among the multiple applications of such systems we could find are exploring unstructured environments, resource monitoring, or distributed sensing. Two of these applications, monitoring, and perimeter/area detection of a given resource, have several ecological uses. One of them is the detection and monitoring of pollutants to delimit their perimeter and area accurately. Maritime activity has been increasing gradually in recent years. Many ships carry products such as oil that can adversely affect the environment. Such products can produce high levels of pollution in case of being spilled into sea. In this paper we will present a distributed system which monitors, covers, and surrounds a resource by using a swarm of homogeneous low cost drones. These drones only use their local sensory information and do not require any direct communication between them. Taking into account the properties of this kind of oil spills we will present a microscopic model for a swarm of drones, capable of monitoring these spills properly. Furthermore, we will analyse the proper macroscopic operation of the swarm. The analytical and experimental results presented here show the proper evolution of our system.

  18. Swarm Robotics with Circular Formation Motion Including Obstacles Avoidance

    Directory of Open Access Journals (Sweden)

    Nabil M. Hewahi

    2017-07-01

    Full Text Available The robots science has been developed over the past few years, where robots have become used to accomplish difficult, repetitive or accurate tasks, which are very hard for humans to carry out. In this paper, we propose an algorithm to control the motion of a swarm of robots and make them able to avoid obstacles. The proposed solution is based on forming the robots in circular fashion. A group set of robots consists of multiple groups of robots, each group of robots consists of robots forming a circular shape and each group set is a circular form of robots. The proposed algorithm is concerned with first locating the randomly generated robots in groups and secondly with the swarm robot motion and finally with the swarm obstacle avoidance and swarm reorganization after crossing the obstacle. The proposed algorithm has been simulated with five different obstacles with various numbers of randomly generated robots. The results show that the swarm in the circular form can deal with the obstacles very effectively by passing the obstacles smoothly. The proposed algorithm has been compared with flocking algorithm and it is shown that the circular formation algorithm does not need extensive computation after obstacle avoidance whereas the flocking algorithm needs extensive computation. In addition, the circular formation algorithm maintains every robot in its group after avoiding the obstacles whereas with flocking algorithm does not.

  19. Confidential and authenticated communications in a large fixed-wing UAV swarm

    OpenAIRE

    Thompson, Richard B

    2016-01-01

    Approved for public release; distribution is unlimited Large unmanned aerial vehicle (UAV) swarms are a nascent technology promising useful military and civilian solutions to difficult problems. Securing data communications within the swarm is essential to accomplishing swarm objectives. The Naval Postgraduate School has successfully demonstrated the launch, flight and landing of 50 UAVs. The communications architecture to support a UAV swarm is unique. The practical challenges of creating...

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

    Science.gov (United States)

    2014-05-09

    UAV path planning and applies to some constant-speed, non-holonomic ground robots [5]. Similar to the Couzin model of biological swarms [3] and the...BEHAVIORS IN BIO-INSPIRED SWARMS 5a. CONTRACT NUMBER IN-HOUSE 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62788F 6. AUTHOR(S) Daniel S. Brown (AFRL... swarming and modes of controlling them are numerous; however, to date swarm researchers have mostly ignored a fundamental problem that impedes

  1. Laboratory and Modeling Studies of Insect Swarms

    Science.gov (United States)

    2016-03-10

    control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. Yale University Office of Sponsored Projects 25 Science Park - 3rd Floor New Haven...Center for the Study of Ecological Perception and Action, Department of Psychology, University of Connecticut (October, 2014) (invited seminar

  2. Swarm prevention and spring treatment against Varroa destructor in honey bee colonies (Apis mellifera)

    NARCIS (Netherlands)

    Cornelissen, B.; Gerritsen, L.J.M.

    2006-01-01

    In 2004 and 2005 experiments were carried out to test the efficacy and efficiency of Varroa control combined with swarm prevention methods in spring. Honey bee colonies were split in an artificial swarm and a brood carrier. Hereafter the swarms were treated with oxalic acid and the brood carriers ei

  3. Space-time continuous models of swarm robotic systems supporting global-to-local programming

    CERN Document Server

    Hamann, Heiko; Nakamura, Yoshihiko

    2010-01-01

    Space-Time Continuous Models of Swarm Robotic Systems presents a control-algorithm-based model that predicts the behavior of large self-organizing robot groups, or robot swarms. Readers will find an extensive look into the interdisciplinary research field of swarm robotics.

  4. Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Alejandro Carrasco Elizalde

    2008-01-01

    Full Text Available The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.

  5. Network Traffic Prediction based on Particle Swarm BP Neural Network

    Directory of Open Access Journals (Sweden)

    Yan Zhu

    2013-11-01

    Full Text Available The traditional BP neural network algorithm has some bugs such that it is easy to fall into local minimum and the slow convergence speed. Particle swarm optimization is an evolutionary computation technology based on swarm intelligence which can not guarantee global convergence. Artificial Bee Colony algorithm is a global optimum algorithm with many advantages such as simple, convenient and strong robust. In this paper, a new BP neural network based on Artificial Bee Colony algorithm and particle swarm optimization algorithm is proposed to optimize the weight and threshold value of BP neural network. After network traffic prediction experiment, we can conclude that optimized BP network traffic prediction based on PSO-ABC has high prediction accuracy and has stable prediction performance.

  6. Recent advances in swarm intelligence and evolutionary computation

    CERN Document Server

    2015-01-01

    This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others. As a timely review, this book can serve as an ideal reference f...

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

    Science.gov (United States)

    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.

  8. Implementasi Algoritma Particle Swarm untuk Menyelesaikan Sistem Persamaan Nonlinear

    Directory of Open Access Journals (Sweden)

    Ardiana Rosita

    2012-09-01

    Full Text Available Penyelesaian sistem persamaan nonlinear merupakan salah satu permasalahan yang sulit pada komputasi numerik dan berbagai aplikasi teknik. Beberapa metode telah dikembangkan untuk menyelesaikan sistem persamaan ini dan metode Newton merupakan metode yang paling sering digunakan. Namun metode ini memerlukan perkiraan solusi awal dan memilih perkiraan solusi awal yang baik untuk sebagian besar sistem persamaan nonlinear tidaklah mudah. Pada makalah ini, algoritma Particle Swarm yang diusulkan oleh Jaberipour dan kawan-kawan[1] diimplementasikan. Algoritma ini merupakan pengembangan dari algoritma Particle Swarm Optimization (PSO. Algoritma ini meyelesaikan sistem persamaan nonlinear yang sebelumnya telah diubah menjadi permasalahan optimasi. Uji coba dilakukan terhadap beberapa fungsi dan sistem persamaan nonlinear untuk menguji kinerja dan efisiensi algoritma. Berdasarkan hasil uji coba, beberapa fungsi dan sistem persamaan nonlinear telah konvergen pada iterasi ke 10 sampai 20 dan terdapat fungsi yang konvergen pada iterasi ke 200. Selain itu, solusi yang dihasilkan algoritma Particle Swarm mendekati solusi eksak.

  9. A Novel Particle Swarm Optimization Algorithm for Global Optimization.

    Science.gov (United States)

    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.

  10. Multi-objective swarm intelligence theoretical advances and applications

    CERN Document Server

    Jagadev, Alok; Panda, Mrutyunjaya

    2015-01-01

    The aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO.       

  11. Collisional Cascade Caclulations for Irregular Satellite Swarms in Fomalhaut b

    CERN Document Server

    Kenyon, Scott J

    2015-01-01

    We describe an extensive suite of numerical calculations for the collisional evolution of irregular satellite swarms around 1--300 M-earth planets orbiting at 120 AU in the Fomalhaut system. For 10--100 M-earth planets, swarms with initial masses of roughly 1% of the planet mass have cross-sectional areas comparable to the observed cross-sectional area of Fomalhaut b. Among 30--300 M-earth planets, our calculations yield optically thick swarms of satellites for ages of 1-10 Myr. Observations with HST and ground-based AO instruments can constrain the frequency of these systems around stars in the beta Pic moving group and possibly other nearby associations of young stars.

  12. Investigating the polar electrojet using Swarm satellite magnetic data

    DEFF Research Database (Denmark)

    Aakjær, Cecilie Drost; Olsen, Nils; Finlay, Chris

    The aim of this study is to investigate the magnetic perturbations caused by the polar electrojets, which are described by means of a model consisting of a series of infinite line currents placed at the height of the ionosphere along QD latitudes. The method is applied to Swarm magnetic scalar pe...... of the polar electrojets as well as their temporal evolution. In addition, applying the method to data taken by the Swarm satellites Alpha and Beta allows investigating longitudinal differences of the electrojets.......The aim of this study is to investigate the magnetic perturbations caused by the polar electrojets, which are described by means of a model consisting of a series of infinite line currents placed at the height of the ionosphere along QD latitudes. The method is applied to Swarm magnetic scalar...

  13. Swarming collapse under limited information flow between individuals

    CERN Document Server

    Komareji, Mohammad; Bouffanais, Roland

    2014-01-01

    The emergence of collective decision in swarms and their coordinated response to complex environments underscore the central role played by social transmission of information. Here, the different possible origins of information flow bottlenecks are identified, and the associated effects on dynamic collective behaviors revealed using a combination of network-, control- and information-theoretic elements applied to a group of interacting self-propelled particles. We find a sufficient condition on the agents' bandwidth $B_{\\textrm{\\scriptsize n}}$ that guarantees the effectiveness of swarming while also highlighting the profound connection with the topology of the underlying interaction network. We also show that when decreasing $B_{\\textrm{\\scriptsize n}}$, the swarming behavior invariably vanishes following a second-order phase transition irrespectively of the intrinsic noise level.

  14. Towards diagnostic tools for analysing Swarm data through model retrievals

    DEFF Research Database (Denmark)

    Kotsiaros, Stavros; Plank, Gernot; Haagmans, R.

    The objective of the Swarm mission is to provide the best ever survey of the geomagnetic field and its temporal dependency, and to gain new insights into improving our knowledge of the Earth’s interior and climate. The Swarm concept consists of a constellation of three satellites in three different...... polar orbits between 300 and 550 km altitude. Goal of the current study is to build tools and to analyze datasets, in order to allow a fast diagnosis of the Swarm system performance in orbit during the commission phase and operations of the spacecraft. The effects on the reconstruction of the magnetic...... field resulting from various error sources are investigated. By using a specially developed software package closed loop simulations are performed aiming at different scenarios. We start from the simple noise-free case and move on to more complex and realistic situations which include attitude errors...

  15. A novel autonomous self-assembly distributed swarm flying robot

    Institute of Scientific and Technical Information of China (English)

    Wei Hongxing; Li Ning; Liu Miao; Tan Jindong

    2013-01-01

    Swarm intelligence embodied by many species such as ants and bees has inspired scholars in swarm robotic researches.This paper presents a novel autonomous self-assembly distributed swarm flying robot-DSFR,which can drive on the ground,autonomously accomplish self-assembly and then fly in the air coordinately.Mechanical and electrical designs ofa DSFR module,as well as the kinematics and dynamics analysis,are specifically investigated.Meanwhile,this paper brings forward a generalized adjacency matrix to describe configurations of DSFR structures.Also,the distributed flight control model is established for vertical taking-off and horizontal hovering,which can be applied to control of DSFR systems with arbitrary configurations.Finally,some experiments are carried out to testify and validate the DSFR design,the autonomous self-assembly strategy and the distributed flight control laws.

  16. Fractional particle swarm optimization in multidimensional search space.

    Science.gov (United States)

    Kiranyaz, Serkan; Ince, Turker; Yildirim, Alper; Gabbouj, Moncef

    2010-04-01

    In this paper, we propose two novel techniques, which successfully address several major problems in the field of particle swarm optimization (PSO) and promise a significant breakthrough over complex multimodal optimization problems at high dimensions. The first one, which is the so-called multidimensional (MD) PSO, re-forms the native structure of swarm particles in such a way that they can make interdimensional passes with a dedicated dimensional PSO process. Therefore, in an MD search space, where the optimum dimension is unknown, swarm particles can seek both positional and dimensional optima. This eventually removes the necessity of setting a fixed dimension a priori, which is a common drawback for the family of swarm optimizers. Nevertheless, MD PSO is still susceptible to premature convergences due to lack of divergence. Among many PSO variants in the literature, none yields a robust solution, particularly over multimodal complex problems at high dimensions. To address this problem, we propose the fractional global best formation (FGBF) technique, which basically collects all the best dimensional components and fractionally creates an artificial global best (aGB) particle that has the potential to be a better "guide" than the PSO's native gbest particle. This way, the potential diversity that is present among the dimensions of swarm particles can be efficiently used within the aGB particle. We investigated both individual and mutual applications of the proposed techniques over the following two well-known domains: 1) nonlinear function minimization and 2) data clustering. An extensive set of experiments shows that in both application domains, MD PSO with FGBF exhibits an impressive speed gain and converges to the global optima at the true dimension regardless of the search space dimension, swarm size, and the complexity of the problem.

  17. The dance of male Anopheles gambiae in wild mating swarms.

    Science.gov (United States)

    Butail, Sachit; Manoukis, Nicholas C; Diallo, Moussa; Ribeiro, José M C; Paley, Derek A

    2013-05-01

    An important element of mating in the malaria vector Anopheles gambiae Giles in nature is the crepuscular mating aggregation (swarm) composed almost entirely of males, where most coupling and insemination is generally believed to occur. In this study, we mathematically characterize the oscillatory movement of male An. gambiae in terms of an established individual-based mechanistic model that parameterizes the attraction of a mosquito toward the center of the swarm using the natural frequency of oscillation and the resistance to its motion, characterized by the damping ratio. Using three-dimensional trajectory data of ten wild mosquito swarms filmed in Mali, Africa, we show two new results for low and moderate wind conditions, and indicate how these results may vary in high wind. First, we show that in low and moderate wind the vertical component of the mosquito motion has a lower frequency of oscillation and higher damping ratio than horizontal motion. In high wind, the vertical and horizontal motions are similar to one another and the natural frequencies are higher than in low and moderate wind. Second, we show that the predicted average disagreement in the direction of motion of swarming mosquitoes moving randomly is greater than the average disagreement we observed between each mosquito and its three closest neighbors, with the smallest level of disagreement occurring for the nearest neighbor in seven out of 10 swarms. The alignment of the direction of motion between nearest neighbors is the highest in high wind. This result provides evidence for flight-path coordination between swarming male mosquitoes.

  18. Optimal PMU Placement By Improved Particle Swarm Optimization

    DEFF Research Database (Denmark)

    Rather, Zakir Hussain; Liu, Leo; Chen, Zhe;

    2013-01-01

    This paper presents an improved method of binary particle swarm optimization (IBPSO) technique for optimal phasor measurement unit (PMU) placement in a power network for complete system observability. Various effective improvements have been proposed to enhance the efficiency and convergence rate...... of conventional particle swarm optimization method. The proposed method of IBPSO ensures optimal PMU placement with and without consideration of zero injection measurements. The proposed method has been applied to standard test systems like 17 bus, IEEE 24-bus, IEEE 30-bus, New England 39-bus, IEEE 57-bus system...

  19. Design of Low Noise Microwave Amplifiers Using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Sadık Ülker

    2012-07-01

    Full Text Available This short paper presents a work on the design of low noise microwave amplifiers using particle swarm optimization (PSO technique. Particle Swarm Optimization is used as a method that is applied to a single stage amplifier circuit to meet two criteria: desired gain and desired low noise. The aim is to get the best optimized design using the predefined constraints for gain and low noise values. The code is written to apply the algorithm to meet the desired goals and the obtained results are verified using different simulators. The results obtained show that PSO can be applied very efficiently for this kind of design problems with multiple constraints.

  20. Research of stochastic weight strategy for extended particle swarm optimizer

    Institute of Scientific and Technical Information of China (English)

    XU Jun-jie; YUE Xin; XIN Zhan-hong

    2008-01-01

    To improve the performance of extended particle swarm optimizer, a novel means of stochastic weight deployment is proposed for the iterative equation of velocity updation. In this scheme, one of the weights is specified to a random number within the range of [0, 1] and the other two remain constant configurations. The simulations show that this weight strategy outperforms the previous deterministic approach with respect to success rate and convergence speed. The experi- ments also reveal that if the weight for global best neighbor is specified to a stochastic number, extended particle swarm optimizer achieves high and robust performance on the given multi-modal function.

  1. Particle Swarm Optimizaton A Physics-Based Approach

    CERN Document Server

    Mikki, Said M

    2008-01-01

    This work aims to provide new introduction to the particle swarm optimization methods using a formal analogy with physical systems. By postulating that the swarm motion behaves similar to both classical and quantum particles, we establish a direct connection between what are usually assumed to be separate fields of study, optimization and physics. Within this framework, it becomes quite natural to derive the recently introduced quantum PSO algorithm from the Hamiltonian or the Lagrangian of the dynamical system. The physical theory of the PSO is used to suggest some improvements in the algorit

  2. Characteristics of equatorial electrojet derived from Swarm satellites

    Science.gov (United States)

    Thomas, Neethal; Vichare, Geeta; Sinha, A. K.

    2017-03-01

    The vector magnetic field measurements from three satellite constellation, Swarm mission (Alpha 'Swarm-A', Bravo 'Swarm-B', and Charlie 'Swarm-C') during the quiet days (daily ∑Kp ⩽ 10) of the years 2014-2015 are used to study the characteristic features of equatorial electrojet (EEJ). A program is developed to identify the EEJ signature in the X (northward) component of the magnetic field recorded by the satellite. An empirical model is fitted into the observed EEJ signatures separately for both the hemispheres, to obtain the parameters of electrojet current such as peak current density, total eastward current, the width of EEJ, position of the electrojet axis, etc. The magnetic field signatures of EEJ at different altitudes are then estimated. Swarm B and C are orbiting at different heights (separation ∼50 km) and during the month of April 2014, both the satellites were moving almost simultaneously over nearby longitudes. Therefore, we used those satellite passes to validate the methodology used in the present study. The magnetic field estimates at the location of Swarm-C obtained using the observations of Swarm B are compared with the actual observations of Swarm-C. A good correlation between the actual and the computed values (correlation coefficient = 0.98) authenticates the method of analysis. The altitudinal variation of the amplitude and the width of the EEJ signatures are also depicted. The ratio of the total eastward flowing forward to westward return currents is found to vary between 0.1 and 1.0. The forward and return current values in the northern hemisphere are found to be ∼0.5 to 2 times of those in the southern hemisphere, thereby indicating the hemispheric asymmetry. The latitudinal extents of the forward and return currents are found to have longitudinal dependence similar to that of the amplitude and the width of EEJ showing four peak structures. Local time dependence of EEJ parameters has also been investigated. In general, the results

  3. Investigating Ground Swarm Robotics Using Agent Based Simulation

    Science.gov (United States)

    2006-12-01

    beyond the capabilities of a single one (Sahin, 2005). The origins of swarm robotics can be traced back to nature, where ant and termite colonies have...McLurkin’s experimental swarm robots “fit the bill,” a good counter-example is that of a robo-soccer team found in Robocup competitions (D’Andrea, 2003) as...accessed Nov 2006. Cioppa, T., “Efficient Nearly Orthogonal and Space-filling Experimental Designs for High-dimensional Complex Models,” Ph.D

  4. Particle swarm optimization - Genetic algorithm (PSOGA) on linear transportation problem

    Science.gov (United States)

    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.

  5. Entropy Diversity in Multi-Objective Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Eduardo J. Solteiro Pires

    2013-12-01

    Full Text Available Multi-objective particle swarm optimization (MOPSO is a search algorithm based on social behavior. Most of the existing multi-objective particle swarm optimization schemes are based on Pareto optimality and aim to obtain a representative non-dominated Pareto front for a given problem. Several approaches have been proposed to study the convergence and performance of the algorithm, particularly by accessing the final results. In the present paper, a different approach is proposed, by using Shannon entropy to analyze the MOPSO dynamics along the algorithm execution. The results indicate that Shannon entropy can be used as an indicator of diversity and convergence for MOPSO problems.

  6. Purely hydrodynamic origin for swarming of swimming particles

    Science.gov (United States)

    Oyama, Norihiro; Molina, John Jairo; Yamamoto, Ryoichi

    2016-04-01

    Three-dimensional simulations with fully resolved hydrodynamics are performed to study the collective motion of model swimmers in bulk and confinement. Calculating the dynamic structure factor, we clarified that the swarming in bulk systems can be understood as a pseudoacoustic mode. Under confinement between flat parallel walls, this pseudoacoustic mode leads to a traveling wavelike motion. This swarming behavior is due purely to the hydrodynamic interactions between the swimmers and depends strongly on the type and strength of swimming (i.e., pusher or puller).

  7. Particle Swarm Optimization with Watts-Strogatz Model

    Science.gov (United States)

    Zhu, Zhuanghua

    Particle swarm optimization (PSO) is a popular swarm intelligent methodology by simulating the animal social behaviors. Recent study shows that this type of social behaviors is a complex system, however, for most variants of PSO, all individuals lie in a fixed topology, and conflict this natural phenomenon. Therefore, in this paper, a new variant of PSO combined with Watts-Strogatz small-world topology model, called WSPSO, is proposed. In WSPSO, the topology is changed according to Watts-Strogatz rules within the whole evolutionary process. Simulation results show the proposed algorithm is effective and efficient.

  8. NEURAL NETWORK TRAINING WITH PARALLEL PARTICLE SWARM OPTIMIZER

    Institute of Scientific and Technical Information of China (English)

    Qin Zheng; Liu Yu; Wang Yu

    2006-01-01

    Objective To reduce the execution time of neural network training. Methods Parallel particle swarm optimization algorithm based on master-slave model is proposed to train radial basis function neural networks, which is implemented on a cluster using MPI libraries for inter-process communication. Results High speed-up factor is achieved and execution time is reduced greatly. On the other hand, the resulting neural network has good classification accuracy not only on training sets but also on test sets. Conclusion Since the fitness evaluation is intensive, parallel particle swarm optimization shows great advantages to speed up neural network training.

  9. CriPS: Critical Dynamics in Particle Swarm Optimization

    OpenAIRE

    Erskine, Adam; Herrmann, J Michael

    2014-01-01

    Particle Swarm Optimisation (PSO) makes use of a dynamical system for solving a search task. Instead of adding search biases in order to improve performance in certain problems, we aim to remove algorithm-induced scales by controlling the swarm with a mechanism that is scale-free except possibly for a suppression of scales beyond the system size. In this way a very promising performance is achieved due to the balance of large-scale exploration and local search. The resulting algorithm shows e...

  10. Improved cuckoo search with particle swarm optimization for classification of compressed images

    Indian Academy of Sciences (India)

    Vamsidhar Enireddy; Reddi Kiran Kumar

    2015-12-01

    The need for a general purpose Content Based Image Retrieval (CBIR) system for huge image databases has attracted information-technology researchers and institutions for CBIR techniques development. These techniques include image feature extraction, segmentation, feature mapping, representation, semantics, indexing and storage, image similarity-distance measurement and retrieval making CBIR system development a challenge. Since medical images are large in size running to megabits of data they are compressed to reduce their size for storage and transmission. This paper investigates medical image retrieval problem for compressed images. An improved image classification algorithm for CBIR is proposed. In the proposed method, RAW images are compressed using Haar wavelet. Features are extracted using Gabor filter and Sobel edge detector. The extracted features are classified using Partial Recurrent Neural Network (PRNN). Since training parameters in Neural Network are NP hard, a hybrid Particle Swarm Optimization (PSO) – Cuckoo Search algorithm (CS) is proposed to optimize the learning rate of the neural network.

  11. Macroseismic investigation of the 2008-2010 low magnitude seismic swarm in the Brabant Massif, Belgium. The link between macroseismic intensity and geomorphology

    Science.gov (United States)

    Van Noten, Koen; Lecocq, Thomas; Vleminckx, Bart; Camelbeeck, Thierry

    2013-04-01

    Between July 2008 and January 2010 a seismic swarm took place in a region 20 km south of Brussels, Belgium. The sequence started on the 12th of July 2008 with a ML = 2.2 event and was followed the day after by the largest event in the sequence (ML = 3.2). Thanks to a locally installed temporary seismic monitoring system more than 300 low magnitude events, with events as low as ML = -0.7, have been detected. Results of the relocations of the different hypocenters and analysis of the focal mechanisms show that the majority of these earthquakes took place at several km's depth (3 to 6 km) along a (possibly blind) 1.5 km long NW-SE fault (zone) situated in the Cambrian basement rocks of the Brabant Massif. Remarkably, 60 events (0.6 ˜ ML ˜ 3.2) were felt, or heard only sometimes, by the local population. This was detected by the "Did you feel it?" macroseismic inquiries on the ROB seismology website (www.seismology.be). For each event a classical macroseismic intensity map has been constructed based on the average macroseismic intensity of each community. Within a single community, however, the reported macroseismic intensities locally often vary ranging between non-damaging intensities of I and IV (on the EMS-98 scale). Using the average macroseismic intensity of a community therefore often oversimplificates the local intensity, especially in hilly areas in which local site effects could have influenced the impact of the earthquakes at the surface. In this presentation we investigate if the perception of the people of how they experienced the small events (sound, vibrations) was influenced by local geomorphological site effects. First, based on available borehole and outcrop data a sediment thickness map of the Cenozoic and Quaternary cover above the basement rocks of the Brabant Massif is constructed in a 200 km2 area around the different epicenters. Second, several electrical resistivity tomography (ERT) profiles are conducted in order to locally improve the

  12. Dependence of swarming in Escherichia coli K-12 on spermidine and the spermidine importer.

    Science.gov (United States)

    Kurihara, Shin; Suzuki, Hideyuki; Tsuboi, Yuichi; Benno, Yoshimi

    2009-05-01

    In a previous work, it was observed that the swarming of polyamine-deficient Proteus mirabilis (speB::sm) was severely inhibited on Luria-Bertani (LB) swarming plates (LBSw) (LB, 0.5% glucose, 0.5% agar), and it was clarified that extracellular putrescine was important as a signaling molecule for the induction of swarming in P. mirabilis. However, a polyamine-deficient strain (delta-speAB delta-speC) of Escherichia coli swarmed as well as the parental strain on LBSw plates. We report that the swarming phenotype of a polyamine-deficient E. coli strain is dependent on spermidine and PotABCD, a spermidine importer.

  13. Characteristics and Implication of the Earthquake Swarm Occurred in Fuzhou in September 1999

    Institute of Scientific and Technical Information of China (English)

    Yuan Dingqiang; Wang Jian

    2001-01-01

    On September 23, 1999, an earthquake swarm occurred in Fuzhou. Because the swarm occurred in the region where earthquakes occurred scarcely before and very close to the center of the city as well as shortly after the Jiji earthquake with Ms7.6 in Taiwan, September 21, 1999, has aroused interest broadly. In this paper, we analyzed the characteristics of spatial and temporal distribution of the earthquake swarm and validated magnitude-number constituent of the swarm is special. In present theory, the earthquake swarm means that a small scale macro original rupture has formed in the layer of the crust in Fuzhou region where moderately strong earthquake risk exists.

  14. Design and simulation of equilateral triangular microstrip antenna using particle swarm optimization (PSO) and advanced particle swarm optimization (APSO)

    Indian Academy of Sciences (India)

    PRABAL PRATAP; RAVINDER SINGH BHATIA; BINOD KUMAR

    2016-07-01

    In this paper a new design is proposed in microstrip antenna family. In this paper, a review design of microstrip antenna design using particle swarm optimization (PSO) and advanced particle swarm optimization (APSO) has been presented which optimizes the parameters and both results are compared. This technique helps antenna engineers to design, analyze, and simulate antenna efficiently and effectively. An advanced PSO driven antenna has been developed to calculate resonant frequency of slit-cut stacked equilateral triangular microstrip antenna. The paper presents simplicity, accuracy and comparison of result between PSO and APSO.

  15. Swarming populations of Salmonella represent a unique physiological state coupled to multiple mechanisms of antibiotic resistance

    Directory of Open Access Journals (Sweden)

    Kim Wook

    2003-01-01

    Full Text Available Salmonella enterica serovar Typhimurium is capable of swarming over semi-solid surfaces. Although its swarming behavior shares many readily observable similarities with other swarming bacteria, the phenomenon remains somewhat of an enigma in this bacterium since some attributes skew away from the better characterized systems. Swarming is quite distinct from the classic swimming motility, as there is a prerequisite for cells to first undergo a morphological transformation into swarmer cells. In some organisms, swarming is controlled by quorum sensing, and in others, swarming has been shown to be coupled to increased expression of important virulence factors. Swarming in serovar Typhimurium is coupled to elevated resistance to a wide variety of structurally and functionally distinct classes of antimicrobial compounds. As serovar Typhimurium differentiates into swarm cells, the pmrHFIJKLM operon is up-regulated, resulting in a more positively charged LPS core. Furthermore, as swarm cells begin to de-differentiate, the pmr operon expression is down-regulated, rapidly reaching the levels observed in swim cells. This is one potential mechanism which confers swarm cells increased resistance to antibiotics such as the cationic antimicrobial peptides. However, additional mechanisms are likely associated with the cells in the swarm state that confer elevated resistance to such a broad spectrum of antimicrobial agents.

  16. Research on Glowworm Swarm Optimization with Ethnic Division

    Directory of Open Access Journals (Sweden)

    Huabei Nie

    2014-02-01

    Full Text Available Glowworm swarm optimization (GSO algorithm is a new intelligent optimization algorithm. Based on the problems of GSO, such as easy to fall into local optimum, slow convergence speed and low optimization precision, an improved GSO with group division is presented. Using shuffled frog leaping algorithm (SFLA, glowworms are divide into different ethnic groups, and local search and global information exchange method improves the GSO performance. The mechanism based on particle position update mechanism in PSO is proposed in order to improve glowworm diversity. By using chaos optimization technique, glowworm groups are initialized, and the algorithm can obtain high quality initial solutions group. Finally, with the classical test functions, the simulation results show that, the GSO with hybrid behavior has better convergence speed and precision. According to the different types of firefly and cold light color is not the same, the glowworm swarm is divided into two sub group, to complete the aspects of paired glowworm swarm population quantity change. Then the cloth Valley bird search algorithm, cloth Valley bird by Levi to fly to the best way to choose size, this kind of flying mode with the machine more strong, will this flight mode into two populations of fireflies swarm evolutionary algorithm. Finish the fireflies optimization path of improvement

  17. Study of the Artificial Fish Swarm Algorithm for Hybrid Clustering

    Directory of Open Access Journals (Sweden)

    Hongwei Zhao

    2015-06-01

    Full Text Available The basic Artificial Fish Swarm (AFS Algorithm is a new type of an heuristic swarm intelligence algorithm, but it is difficult to optimize to get high precision due to the randomness of the artificial fish behavior, which belongs to the intelligence algorithm. This paper presents an extended AFS algorithm, namely the Cooperative Artificial Fish Swarm (CAFS, which significantly improves the original AFS in solving complex optimization problems. K-medoids clustering algorithm is being used to classify data, but the approach is sensitive to the initial selection of the centers with low quality of the divided cluster. A novel hybrid clustering method based on the CAFS and K-medoids could be used for solving clustering problems. In this work, first, CAFS algorithm is used for optimizing six widely-used benchmark functions, coming up with comparative results produced by AFS and CAFS, then Particle Swarm Optimization (PSO is studied. Second, the hybrid algorithm with K-medoids and CAFS algorithms is used for data clustering on several benchmark data sets. The performance of the hybrid algorithm based on K-medoids and CAFS is compared with AFS and CAFS algorithms on a clustering problem. The simulation results show that the proposed CAFS outperforms the other two algorithms in terms of accuracy and robustness.

  18. Reversals and collisions optimize protein exchange in bacterial swarms

    Energy Technology Data Exchange (ETDEWEB)

    Amiri, Aboutaleb; Harvey, Cameron; Buchmann, Amy; Christley, Scott; Shrout, Joshua D.; Aranson, Igor S.; Alber, Mark

    2017-03-01

    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. xanthus 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.

  19. Swarm-based wayfinding support in open and distance learning

    NARCIS (Netherlands)

    Tattersall, Colin; Manderveld, Jocelyn; Van den Berg, Bert; Van Es, René; Janssen, José; Koper, Rob

    2005-01-01

    Please refer to the original source: Tattersall, C. Manderveld, J., Van den Berg, B., Van Es, R., Janssen, J., & Koper, R. (2005). Swarm-based wayfinding support in open and distance learning. In Alkhalifa, E.M. (Ed). Cognitively Informed Systems: Utilizing Practical Approaches to Enrich Information

  20. On the premature convergence of particle swarm optimization

    DEFF Research Database (Denmark)

    Larsen, Rie B.; Jouffroy, Jerome; Lassen, Benny

    2016-01-01

    This paper discusses convergence issues of the basic particle swarm optimization algorithm for different pa- rameters. For the one-dimensional case, it is shown that, for a specific range of parameters, the particles will converge prematurely, i.e. away from the actual minimum of the objective...

  1. Youth on YouTube as Smart Swarms

    Science.gov (United States)

    Duncum, Paul

    2014-01-01

    Viewing YouTube culture as a creative, collaborative process similar to animal swarms can help art educators understand and embrace youth's digital practices. School-age youth are among the most prolific contributors to YouTube, not just as viewers, but also as producers. Even preschoolers now produce videos (McClure, 2010). So pervasive,…

  2. Toward more complete magnetic gradiometry with the Swarm mission

    DEFF Research Database (Denmark)

    Kotsiaros, Stavros

    2016-01-01

    similar signal content as the theoretical radial gradient ΓΓ(0)={[∇∇B]rr}. These results demonstrate the ability of multi-satellite missions such as Swarm, which cannot directly measure the radial gradient, to retrieve similar signal content by means of the horizontal gradients. Finally, lithospheric...

  3. Reversals and collisions optimize protein exchange in bacterial swarms

    Science.gov (United States)

    Amiri, Aboutaleb; Harvey, Cameron; Buchmann, Amy; Christley, Scott; Shrout, Joshua D.; Aranson, Igor S.; Alber, Mark

    2017-03-01

    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 a mechanism of intercellular signaling for the bacterium Myxococcus xanthus. A detailed biologically calibrated computational model is used to study how M. xanthus 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.

  4. LinkMind: Link Optimization in Swarming Mobile Sensor Networks

    DEFF Research Database (Denmark)

    Ngo, Trung Dung

    2012-01-01

    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...

  5. A minimal model of predator-swarm interactions

    CERN Document Server

    Chen, Yuxin

    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 are able to escape by "confusing" the predator: the prey forms a ring with the predator at the center. 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 (due to a Hopf bifurcation) from confusion state to chasing dynamics, and we compute ...

  6. Auto-Clustering using Particle Swarm Optimization and Bacterial Foraging

    DEFF Research Database (Denmark)

    Rutkowski Olesen, Jakob; Cordero, Jorge; Zeng, Yifeng

    2009-01-01

    This paper presents a hybrid approach for clustering based on particle swarm optimization (PSO) and bacteria foraging algorithms (BFA). The new method AutoCPB (Auto-Clustering based on particle bacterial foraging) makes use of autonomous agents whose primary objective is to cluster chunks of data...

  7. Optimal power flow by particle swarm optimization with an aging ...

    African Journals Online (AJOL)

    DR OKE

    International Journal of Engineering, Science and Technology, Vol. 7, No. ... improve the swarm and gets old, new particles emerge to challenge and claim the leadership, which brings in diversity. ..... QC-10 (p.u.). 0.00 ..... College, Asansol, in 2006; MBA in Power Management from University of Petroleum & Energy Studies, ...

  8. A continuum three-zone model for swarms.

    Science.gov (United States)

    Miller, Jennifer M; Kolpas, Allison; Juchem Neto, Joao Plinio; Rossi, Louis F

    2012-03-01

    We present a progression of three distinct three-zone, continuum models for swarm behavior based on social interactions with neighbors in order to explain simple coherent structures in popular biological models of aggregations. In continuum models, individuals are replaced with density and velocity functions. Individual behavior is modeled with convolutions acting within three interaction zones corresponding to repulsion, orientation, and attraction, respectively. We begin with a variable-speed first-order model in which the velocity depends directly on the interactions. Next, we present a variable-speed second-order model. Finally, we present a constant-speed second-order model that is coordinated with popular individual-based models. For all three models, linear stability analysis shows that the growth or decay of perturbations in an infinite, uniform swarm depends on the strength of attraction relative to repulsion and orientation. We verify that the continuum models predict the behavior of a swarm of individuals by comparing the linear stability results with an individual-based model that uses the same social interaction kernels. In some unstable regimes, we observe that the uniform state will evolve toward a radially symmetric attractor with a variable density. In other unstable regimes, we observe an incoherent swarming state.

  9. Copepod swarm in the Campbell Bay (Andaman Sea)

    Digital Repository Service at National Institute of Oceanography (India)

    Goswami, S.C.; Rao, T.S.S.

    During the 68th cruise of R.V.Gaveshani, an unusual abundance of calanoid copepods of family Pontellidae was observed in the Campbell Bay (lat.6 degrees 30'-6 degrees 59'N and long 93 degrees 56'-94 degrees 15'E) Swarm density (25974 to 138420/m 3...

  10. A Survey of Formal Methods for Intelligent Swarms

    Science.gov (United States)

    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

  11. Targeting male mosquito swarms to control malaria vector density

    Science.gov (United States)

    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

  12. Swarm GPS Receiver Performance under the Influence of Ionospheric Scintillation

    Science.gov (United States)

    Ren, Le; Schön, Steffen

    2016-04-01

    The Swarm mission launched on 22 November 2013 is ESA's first constellation of satellites to study the dynamics of the Earth's magnetic field and its interaction with the Earth system. This mission consists of three identical satellites in near-polar orbits , two flying almost side-by-side at an initial altitude of 460 km, the third flying in a higher orbit of about 530 km. Each satellite is equipped with a high precision 8-channels dual-frequency receiver for the precise orbit determination, which is also the essential fundament in order to take full advantage of the data information provided by this constellation, e.g. for the recovery of gravity field. The quality of the final orbit determination depends on the observation data from the receivers. In this contribution, we will analyze the performance of the Swarm on-board receivers, especially under the influence of ionospheric scintillation caused by ionospheric irregularities. This is a prerequisite for high quality satellite positioning as well as a sound study of the ionosphere. Ionospheric scintillation can lead to the phase disturbances, cycle slips or even loss of signal tracking. The RINEX observation data from Swarm Level 1b products are used to analyze the Swarm receiver performance. We will demonstrate the signal strength, code and phase noise, different linear combinations (geometry free, ionosphere free), as well as GDOP values for the 3 Swarm satellites. The first results show that the observation data are severely disturbed and the signals could be lost around the geomagnetic equator and geomagnetic poles where the ionosphere is active. The results also show that the receivers are more stable in those areas after the update in October 2015.

  13. Exopolysaccharides play a role in the swarming of the benthic bacterium Pseudoalteromonas sp. SM9913

    Directory of Open Access Journals (Sweden)

    Ang eLiu

    2016-04-01

    Full Text Available Most marine bacteria secrete exopolysaccharide (EPS, which is important for bacterial survival in the marine environment. However, it is still unclear whether the self-secreted EPS is involved in marine bacterial motility. Here we studied the role of EPS in the lateral flagella-driven swarming motility of benthic bacterium Pseudoalteromonas sp. SM9913 (SM9913 by a comparison of wild SM9913 and ΔepsT, an EPS synthesis defective mutant. Reduction of EPS production in ΔepsT did not affect the growth rate or the swimming motility, but significantly decreased the swarming motility on a swarming plate, suggesting that the EPS may play a role in SM9913 swarming. However, the expression and assembly of lateral flagella in ΔepsT were not affected. Instead, ΔepsT had a different swarming behavior from wild SM9913. The swarming of ΔepsT did not have an obvious rapid swarming period, and its rate became much lower than that of wild SM9913 after 35 h incubation. An addition of surfactin or SM9913 EPS on the surface of the swarming plate could rescue the swarming level. These results indicate that the self-secreted EPS is required for the swarming of SM9913. This study widens our understanding of the function of the EPS of benthic bacteria.

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

    Science.gov (United States)

    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

  15. Emergency preparedness activities during an ongoing seismic swarm: the experience of the 2011-2012 Pollino (Southern Italy) sequence

    Science.gov (United States)

    Masi, A.; Mucciarelli, M.; Chiauzzi, L.; De Costanzo, G.; Loperte, G.

    2012-04-01

    Facing natural disasters effects can be a very difficult task lacking suitable activities and tools to preventively prepare the involved community (people, authorities, professionals, …) to the expected events. Therefore, a suite of preventive actions should be carried out to mitigate natural risks, in particular working to reduce the territorial vulnerability with respect to the specific natural hazard at hand, and to increase people response capacity. In fact, building social capacity helps to increase the risk perception and the people capacity to adapt to and cope with natural hazards. Since October 2011 a seismic swarm is affecting the Pollino mountain range, Southern Italy. At present the sequence is still ongoing, with more than 500 events with M>1, at least 40 well perceived by the population and a maximum magnitude at 3.6. The area mainly affected by the seismic sequence includes 12 villages, with a total population of about 50.000 inhabitants and, according to the current seismic hazard map it has high seismicity level. Such area was hit by a magnitude Ml=5.7 event in 1998 that produced macroseismic intensity not higher that VII-VIII degree of MCS scale and caused one dead, some injured and widespread damage in at least six municipalities. During the sequence, the National Department of Civil Protection (DPC) and the Civil Protection of Basilicata Region decided to put in action some measures aimed at verifying and enhancing emergency preparedness. These actions have been carried out with a constant and fruitful collaboration among the main stakeholders involved (scientific community, local and national governmental agencies, civil protection volunteers, etc) trough the following main activities: 1. collaboration between scientific community and the local and national offices of Civil Protection especially in the relationship with local authorities (e.g. mayors, which are civil protection authorities in their municipality); 2. interaction between DPC

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

    Science.gov (United States)

    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.

  17. Analysis of the Emergence in Swarm Model Based on Largest Lyapunov Exponent

    Directory of Open Access Journals (Sweden)

    Yu Wu

    2011-01-01

    Full Text Available Emergent behaviors of collective intelligence systems, exemplified by swarm model, have attracted broad interests in recent years. However, current research mostly stops at observational interpretations and qualitative descriptions of emergent phenomena and is essentially short of quantitative analysis and evaluation. In this paper, we conduct a quantitative study on the emergence of swarm model by using chaos analysis of complex dynamic systems. This helps to achieve a more exact understanding of emergent phenomena. In particular, we evaluate the emergent behaviors of swarm model quantitatively by using the chaos and stability analysis of swarm model based on largest Lyapunov exponent. It is concluded that swarm model is at the edge of chaos when emergence occurs, and whether chaotic or stable at the beginning, swarm model will converge to stability with the elapse of time along with interactions among agents.

  18. The paleomagnetism and geological significance of Meso- proterozoic dyke swarms in the central North China Craton

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The Mesoproterozoic mafic dyke swarms are extensively distributedin the central North China Craton(NCC) including North Shanxi, Wutai and Lüliang areas, which are not deformed and metamorphic but high magnetic, so the dyke swarms become the mark to compare the high meta-morphic rock areas in magnetism. Based on the analysis of paleomagnetism of mafic dyke swarms in North Shanxi, Wutai and Lüliang areas, NCC inclined southward about 18° so that North Shanxi lifted up and rotated 10° left to Wutai area. The dyke swarms in Lüliang developed later than in North Shanxi and Wutai area. The NNW-trending and WNW-trending dyke swarms developed in Lüliang while the North China Plate moved northward consistently so that the paleomagnetism of dyke swarms in Lüliang is greatly different from North Shanxi and Wutai area.

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

    Science.gov (United States)

    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.

  20. A Model of the Earth's Magnetic Field From Two Years of Swarm Satellite Constellation Data

    Science.gov (United States)

    Olsen, N.; Finlay, C. C.; Kotsiaros, S.

    2015-12-01

    Two years of data from ESA's Swarm constellation mission are used to derive a model of the Earth's magnetic field and its time variation (secular variation). The model describes contributions from the core and lithosphere as well as large-scale contributions from the magnetosphere (and its Earth-induced counterpart). We use data from geomagnetic quiet times and co-estimate the Euler angles describing the rotation between the vector magnetometer instrument frame and the North-East-Center (NEC) frame. In addition to the magnetic field observations provided by each of the three Swarm satellites and alongtrack first differences we include the East-west magnetic gradient information provided by the lower Swarm satellite pair, thereby explicitly taking advantage of the constellation aspect of Swarm. We assess the spatial and temporal model resolution that can be obtained from two years of Swarm satellite data by comparison with other recent models that also include non-Swarm magnetic observations.

  1. Binary Particle Swarm Optimization based Biclustering of Web usage Data

    CERN Document Server

    Bagyamani, R Rathipriya K Thangavel J

    2011-01-01

    Web mining is the nontrivial process to discover valid, novel, potentially useful knowledge from web data using the data mining techniques or methods. It may give information that is useful for improving the services offered by web portals and information access and retrieval tools. With the rapid development of biclustering, more researchers have applied the biclustering technique to different fields in recent years. When biclustering approach is applied to the web usage data it automatically captures the hidden browsing patterns from it in the form of biclusters. In this work, swarm intelligent technique is combined with biclustering approach to propose an algorithm called Binary Particle Swarm Optimization (BPSO) based Biclustering for Web Usage Data. The main objective of this algorithm is to retrieve the global optimal bicluster from the web usage data. These biclusters contain relationships between web users and web pages which are useful for the E-Commerce applications like web advertising and marketin...

  2. Glowworm Swarm Optimization and Its Application to Blind Signal Separation

    Directory of Open Access Journals (Sweden)

    Zhucheng Li

    2016-01-01

    Full Text Available Traditional optimization algorithms for blind signal separation (BSS are mainly based on the gradient, which requires the objective function to be continuous and differentiable, so the applications of these algorithms are very limited. Moreover, these algorithms have problems with the convergence speed and accuracy. To overcome these drawbacks, this paper presents a modified glowworm swarm optimization (MGSO algorithm based on a novel step adjustment rule and then applies MGSO to BSS. Taking kurtosis of the mixed signals as the objective function of BSS, MGSO-BSS succeeds in separating the mixed signals in Matlab environment. The simulation results prove that MGSO is more effective in capturing the global optimum of the objective function of the BSS algorithm and has faster convergence speed and higher accuracy, compared with particle swarm optimization (PSO and GSO.

  3. A Swarm Intelligence Based Model for Mobile Cloud Computing

    Directory of Open Access Journals (Sweden)

    Ahmed S. Salama

    2015-01-01

    Full Text Available Mobile Computing (MC provides multi services and a lot of advantages for millions of users across the world over the internet. Millions of business customers have leveraged cloud computing services through mobile devices to get what is called Mobile Cloud Computing (MCC. MCC aims at using cloud computing techniques for storage and processing of data on mobile devices, thereby reducing their limitations. This paper proposes architecture for a Swarm Intelligence Based Mobile Cloud Computing Model (SIBMCCM. A model that uses a proposed Parallel Particle Swarm Optimization (PPSO algorithm to enhance the access time for the mobile cloud computing services which support different E Commerce models and to better secure the communication through the mobile cloud and the mobile commerce transactions.

  4. Celestial Navigation Fix Based on Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Tsou Ming-Cheng

    2015-09-01

    Full Text Available A technique for solving celestial fix problems is proposed in this study. This method is based on Particle Swarm Optimization from the field of swarm intelligence, utilizing its superior optimization and searching abilities to obtain the most probable astronomical vessel position. In addition to being applicable to two-body fix, multi-body fix, and high-altitude observation problems, it is also less reliant on the initial dead reckoning position. Moreover, by introducing spatial data processing and display functions in a Geographical Information System, calculation results and chart work used in Circle of Position graphical positioning can both be integrated. As a result, in addition to avoiding tedious and complicated computational and graphical procedures, this work has more flexibility and is more robust when compared to other analytical approaches.

  5. The HIVE Tool for Informed Swarm State Space Exploration

    CERN Document Server

    Wijs, Anton

    2011-01-01

    Swarm verification and parallel randomised depth-first search are very effective parallel techniques to hunt bugs in large state spaces. In case bugs are absent, however, scalability of the parallelisation is completely lost. In recent work, we proposed a mechanism to inform the workers which parts of the state space to explore. This mechanism is compatible with any action-based formalism, where a state space can be represented by a labelled transition system. With this extension, each worker can be strictly bounded to explore only a small fraction of the state space at a time. In this paper, we present the HIVE tool together with two search algorithms which were added to the LTSmin tool suite to both perform a preprocessing step, and execute a bounded worker search. The new tool is used to coordinate informed swarm explorations, and the two new LTSmin algorithms are employed for preprocessing a model and performing the individual searches.

  6. Electronic Commerce Logistics Network Optimization Based on Swarm Intelligent Algorithm

    Directory of Open Access Journals (Sweden)

    Yabing Jiao

    2013-09-01

    Full Text Available This article establish an efficient electronic commerce logistics operation system to reduce distribution costs and build a logistics network operation model based on around the B2C electronic commerce enterprise logistics network operation system. B2C electronic commerce transactions features in the enterprise network platform. To solve the NP-hard problem this article use hybrid ant colony algorithm, particle swarm algorithm and group swarm intelligence algorithm to get a best solution. According to the intelligent algorithm, design of electronic commerce logistics network optimization system, enter the national 22 electronic commerce logistics network for validation. Through the experiment to verify the optimized logistics cost greatly decreased. This research can help B2C electronic commerce enterprise logistics network to optimize decision-making under the premise of ensuring the interests of consumers and service levels also can be an effective way for enterprises to improve the efficiency of logistics services and reduce operation costs

  7. Usage of the particle swarm optimization in problems of mechanics

    Directory of Open Access Journals (Sweden)

    Hajžman M.

    2016-06-01

    Full Text Available This paper deals with the optimization method called particle swarm optimization and its usage in mechanics. Basic versions of the method is introduced and several improvements and modifications are applied for better convergence of the algorithms. The performance of the optimization algorithm implemented in an original in-house software is investigated by means of three basic and one complex problems of mechanics. The goal of the first problem is to find optimal parameters of a dynamic absorber of vibrations. The second problem is about the tunning of eigenfrequencies of beam bending vibrations. The third problem is to optimize parameters of a clamped beam with various segments. The last complex problem is the optimization of a tilting mechanism with multilevel control. The presented results show that the particle swarm optimization can be efficiently used in mechanical tasks.

  8. Intrinsic Fluctuations and Driven Response of Insect Swarms

    Science.gov (United States)

    Ni, Rui; Puckett, James G.; Dufresne, Eric R.; Ouellette, Nicholas T.

    2015-09-01

    Animals of all sizes form groups, as acting together can convey advantages over acting alone; thus, collective animal behavior has been identified as a promising template for designing engineered systems. However, models and observations have focused predominantly on characterizing the overall group morphology, and often focus on highly ordered groups such as bird flocks. We instead study a disorganized aggregation (an insect mating swarm), and compare its natural fluctuations with the group-level response to an external stimulus. We quantify the swarm's frequency-dependent linear response and its spectrum of intrinsic fluctuations, and show that the ratio of these two quantities has a simple scaling with frequency. Our results provide a new way of comparing models of collective behavior with experimental data.

  9. Multiswarm Particle Swarm Optimization with Transfer of the Best Particle

    Directory of Open Access Journals (Sweden)

    Xiao-peng Wei

    2015-01-01

    Full Text Available We propose an improved algorithm, for a multiswarm particle swarm optimization with transfer of the best particle called BMPSO. In the proposed algorithm, we introduce parasitism into the standard particle swarm algorithm (PSO in order to balance exploration and exploitation, as well as enhancing the capacity for global search to solve nonlinear optimization problems. First, the best particle guides other particles to prevent them from being trapped by local optima. We provide a detailed description of BMPSO. We also present a diversity analysis of the proposed BMPSO, which is explained based on the Sphere function. Finally, we tested the performance of the proposed algorithm with six standard test functions and an engineering problem. Compared with some other algorithms, the results showed that the proposed BMPSO performed better when applied to the test functions and the engineering problem. Furthermore, the proposed BMPSO can be applied to other nonlinear optimization problems.

  10. Swarm magnetic and GOCE gravity gradient grids for lithospheric modelling

    DEFF Research Database (Denmark)

    Bouman, Johannes; Ebbing, Jörg; Kotsiaros, Stavros

    We explore how Swarm magnetic gradient and GOCE gravity gradient data can improve modelling of the Earth’s lithosphere and thereby contribute to a better understanding of Earth’s dynamic processes. We study the use of gradient grids to provide improved information about the lithosphere and upper...... mantle in the well-surveyed North-East Atlantic Margin. In particular, we present the computation of magnetic and gravity gradient grids at satellite altitude (roughly 450 km and 250 km above the Earth for Swarm and GOCE respectively). It is shown that regional solutions based on a tesseroid approach may...... contain more signal content than global models do. The patchwork of regional grids is presented as well as the subsequent error reduction through iterative downward and upward continuation using the Poisson integral equation. The promises and pitfalls are discussed of using grids at mean satellite...

  11. How Many Insects Does It Take to Make a Swarm?

    Science.gov (United States)

    Ouellette, Nicholas

    2014-03-01

    Aggregations of social animals, such as flocks of birds, schools of fish, or swarms of insects, are beautiful, natural examples of self-organized behavior far from equilibrium. They tend to display a range of emergent properties, from enhanced sensing to the rapid propagation of information throughout the aggregate. Many classes of models have been proposed to describe these systems, including agent-based models that specify explicit social forces between individuals and continuum models that abstract the interactions between individuals into some smooth advecting velocity field. Assessing these various modeling approaches requires comparison with empirical data. We will discuss measurements of laboratory mating swarms of the non-biting midge Chironomus riparius in the context of model assessment. In particular, we focus on the question of the small-number limit: how large must the population be before collective properties emerge?

  12. A Diversity-Guided Particle Swarm Optimizer - the ARPSO

    DEFF Research Database (Denmark)

    Vesterstrøm, Jacob Svaneborg; Riget, Jacques

    2002-01-01

    The particle swarm optimization (PSO) algorithm is a new population based search strat- egy, which has exhibited good performance on well-known numerical test problems. How- ever, on strongly multi-modal test problems the PSO tends to suffer from premature convergence. This is due to a decrease...... that the ARPSO prevents premature convergence to a high degree, but still keeps a rapid convergence like the basic PSO. Thus, it clearly outperforms the basic PSO as well as the implemented GA in multi-modal optimization. Keywords Particle Swarm Optimization, Diversity-Guided Search 1 Introduction The PSO model...... is a new population based optimization strategy introduced by J. Kennedy et al. in 1995 (Kennedy95). It has already shown to be comparable in performance with tra- ditional optimization algorithms such as simulated annealing (SA) and the genetic algorithm (GA) (Angeline98; Eberhart98; Krink01; Vesterstrom...

  13. Swarm intelligence optimization and its application in geophysical data inversion

    Institute of Scientific and Technical Information of China (English)

    Yuan Sanyi; Wang Shangxu; Tian Nan

    2009-01-01

    The inversions of complex geophysical data always solve multi-parameter, nonlinear, and multimodal optimization problems. Searching for the optimal inversion solutions is similar to the social behavior observed in swarms such as birds and ants when searching for food. In this article, first the particle swarm optimization algorithm was described in detail, and ant colony algorithm improved. Then the methods were applied to three different kinds of geophysical inversion problems: (1) a linear problem which is sensitive to noise, (2) a synchronous inversion of linear and nonlinear problems, and (3) a nonlinear problem. The results validate their feasibility and efficiency. Compared with the conventional genetic algorithm and simulated annealing, they have the advantages of higher convergence speed and accuracy. Compared with the quasi-Newton method and Levenberg-Marquardt method, they work better with the ability to overcome the locally optimal solutions.

  14. Glowworm Swarm Optimization and Its Application to Blind Signal Separation

    OpenAIRE

    Zhucheng Li; Xianglin Huang

    2016-01-01

    Traditional optimization algorithms for blind signal separation (BSS) are mainly based on the gradient, which requires the objective function to be continuous and differentiable, so the applications of these algorithms are very limited. Moreover, these algorithms have problems with the convergence speed and accuracy. To overcome these drawbacks, this paper presents a modified glowworm swarm optimization (MGSO) algorithm based on a novel step adjustment rule and then applies MGSO to BSS. Takin...

  15. Research on Glowworm Swarm Optimization with Ethnic Division

    OpenAIRE

    Huabei Nie; Jianqiao Shen; Xiaoping Li

    2014-01-01

    Glowworm swarm optimization (GSO) algorithm is a new intelligent optimization algorithm. Based on the problems of GSO, such as easy to fall into local optimum, slow convergence speed and low optimization precision, an improved GSO with group division is presented. Using shuffled frog leaping algorithm (SFLA), glowworms are divide into different ethnic groups, and local search and global information exchange method improves the GSO performance. The mechanism based on particle position update m...

  16. Time Evolution of the Electron Swarm Energy Distribution Function

    Science.gov (United States)

    1989-06-28

    25 Characteristic energy c and mobility g in a pulsed electric field in air lasting 25 ns ....... ............................... 55 26...Characteristic energy E and mobility tz in a pulsed electric field in air lasting 100 ns ........ ............................... 56 27 Electron energy...originally thermal swarm in a rapidly varying pulsed electric field . We do so in air in spite of the fact that it stresses the Fokker-Planck

  17. Particle swarm optimization for programming deep brain stimulation arrays

    Science.gov (United States)

    Peña, Edgar; Zhang, Simeng; Deyo, Steve; Xiao, YiZi; Johnson, Matthew D.

    2017-02-01

    Objective. Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Approach. Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. Main results. The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (disabling electrodes (n  =  3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies of  <1% between approaches. Significance. The PSO algorithm provides a computationally efficient way to program DBS systems especially those with higher electrode counts.

  18. Instantly Basing Locust Swarms: New Options for Future Air Operations

    Science.gov (United States)

    2012-06-01

    railguns may also help alleviate concerns involving the deployment of RPA swarm armaments; however, the Research, Development, Testing, and Evaluation...to hundreds of kilowatts for self-defense and, eventually, precision ground attack.”102 Railgun technology is also significant because it uses...87 and faster than traditional gun systems.103 Furthermore, railgun projectiles destroy their targets with their large kinetic energy instead

  19. Human Factors Issues for Interaction with Bio-Inspired Swarms

    Science.gov (United States)

    2012-10-01

    subtle leaders of fish schools. Pheromone trails also suggest a way to support human interaction as has been explored to a limited extent... Human Factors issues for Interaction with Bio-Inspired Swarms Michael Lewis*, Michael Goodrich**, Katia Sycara+, Mark Steinberg++ * School of...Enabling a human to control such bio-inspired systems is a considerable challenge due to the limitations of each individual robot and the sheer

  20. Genetic algorithm and particle swarm optimization combined with Powell method

    Science.gov (United States)

    Bento, David; Pinho, Diana; Pereira, Ana I.; Lima, Rui

    2013-10-01

    In recent years, the population algorithms are becoming increasingly robust and easy to use, based on Darwin's Theory of Evolution, perform a search for the best solution around a population that will progress according to several generations. This paper present variants of hybrid genetic algorithm - Genetic Algorithm and a bio-inspired hybrid algorithm - Particle Swarm Optimization, both combined with the local method - Powell Method. The developed methods were tested with twelve test functions from unconstrained optimization context.

  1. EXPERIENCE WITH SYNCHRONOUS GENERATOR MODEL USING PARTICLE SWARM OPTIMIZATION TECHNIQUE

    OpenAIRE

    N.RATHIKA; Dr.A.Senthil kumar; A.ANUSUYA

    2014-01-01

    This paper intends to the modeling of polyphase synchronous generator and minimization of power losses using Particle swarm optimization (PSO) technique with a constriction factor. Usage of Polyphase synchronous generator mainly leads to the total power circulation in the system which can be distributed in all phases. Another advantage of polyphase system is the fault at one winding does not lead to the system shutdown. The Process optimization is the chastisement of adjusting a process so as...

  2. Adaptive Remote-Sensing Techniques Implementing Swarms of Mobile Agents

    Energy Technology Data Exchange (ETDEWEB)

    Cameron, S.M.; Loubriel, G.M.; Rbinett, R.D. III; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

    1999-04-01

    This paper focuses on our recent work at Sandia National Laboratories toward engineering a physics-based swarm of mobile vehicles for distributed sensing applications. Our goal is to coordinate a sensor array that optimizes sensor coverage and multivariate signal analysis by implementing artificial intelligence and evolutionary computational techniques. These intelligent control systems integrate both globally operating decision-making systems and locally cooperative information-sharing modes using genetically-trained neural networks. Once trained, neural networks have the ability to enhance real-time operational responses to dynamical environments, such as obstacle avoidance, responding to prevailing wind patterns, and overcoming other natural obscurants or interferences (jammers). The swarm realizes a collective set of sensor neurons with simple properties incorporating interactions based on basic community rules (potential fields) and complex interconnecting functions based on various neural network architectures, Therefore, the swarm is capable of redundant heterogeneous measurements which furnishes an additional degree of robustness and fault tolerance not afforded by conventional systems, while accomplishing such cognitive tasks as generalization, error correction, pattern recognition, and sensor fission. The robotic platforms could be equipped with specialized sensor devices including transmit/receive dipole antennas, chemical or biological sniffers in combination with recognition analysis tools, communication modulators, and laser diodes. Our group has been studying the collective behavior of an autonomous, multi-agent system applied to emerging threat applications. To accomplish such tasks, research in the fields of robotics, sensor technology, and swarms are being conducted within an integrated program. Mission scenarios under consideration include ground penetrating impulse radar (GPR) for detection of under-ground structures, airborne systems, and plume

  3. A Communications Modeling System for Swarm-Based Sensors

    Science.gov (United States)

    2003-09-01

    novel by Michael Crichton (31) about a particle swarm: In the Nevada desert, an experiment has gone horribly wrong. A cloud of nanoparticles...Routing Protocol Performance Issues and Evaluation Considerations.” The Internet Society, January 1999. RFC2501. 31. Crichton , Michael . Prey . New York...www.afrlhorizons.com/Briefs/Jun02/VA0201.html. 28. Corr, Michael G. and C. Okino. A Study of Distributed Smart Sensor Networks. Technical Report, Thayer

  4. Particle Swarm Optimization-Proximal Point Algorithm for Nonlinear Complementarity Problems

    OpenAIRE

    Chai Jun-Feng; Wang Shu-Yan

    2013-01-01

    A new algorithm is presented for solving the nonlinear complementarity problem by combining the particle swarm and proximal point algorithm, which is called the particle swarm optimization-proximal point algorithm. The algorithm mainly transforms nonlinear complementarity problems into unconstrained optimization problems of smooth functions using the maximum entropy function and then optimizes the problem using the proximal point algorithm as the outer algorithm and particle swarm algorithm a...

  5. Use of the Comprehensive Inversion method for Swarm satellite data analysis

    DEFF Research Database (Denmark)

    Sabaka, T. J.; Tøffner-Clausen, Lars; Olsen, Nils

    2013-01-01

    An advanced algorithm, known as the “Comprehensive Inversion” (CI), is presented for the analysis of Swarm measurements to generate a consistent set of Level-2 data products to be delivered by the Swarm “Satellite Constellation Application and Research Facility” (SCARF) to the European Space Agen...... data from a full simulation of the Swarm mission, where it is found to significantly exceed all mandatory and most target accuracy requirements....

  6. A Network-Centric Formalism for Disturbance Rejection Design and Human Swarm Interaction

    Science.gov (United States)

    2015-07-06

    AFRL-AFOSR-VA-TR-2016-0007 Formalism for Disturbance Rejection Design and Human- swarm Interaction Mehran Mesbahi UNIVERSITY OF WASHINGTON Final...SUBTITLE A Network-centric Formalism for Disturbance Rejection Design and Human Swarm Interaction 5a. CONTRACT NUMBER FA9550-12-1-0203 5b. GRANT NUMBER...proposed research is to examine fundamental structural bounds on the disturbance rejection and human- swarm interaction properties of a network of

  7. Human Robotic Swarm Interaction Using An Artificial Physics Approach (Briefing Charts)

    Science.gov (United States)

    2014-12-01

    Human Robotic Swarm Interaction Using An Artificial Physics Approach LT Brenton Campbell ADVISORS: Asst Professor Dr. Timothy Chung Senior Lecturer...REPORT DATE DEC 2014 2. REPORT TYPE 3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE Human Robotic Swarm Interaction Using An...and R. Heil, “Distributed, physics-based control of swarms of vehicles,” Autonomous Robots, pp. 137–162, 2004. [Online]. Available: http

  8. Swarm prevention and spring treatment against Varroa destructor in honey bee colonies (Apis mellifera)

    OpenAIRE

    Cornelissen, B; Gerritsen, L.J.M.

    2006-01-01

    In 2004 and 2005 experiments were carried out to test the efficacy and efficiency of Varroa control combined with swarm prevention methods in spring. Honey bee colonies were split in an artificial swarm and a brood carrier. Hereafter the swarms were treated with oxalic acid and the brood carriers either with formic acid (2004) or Thymovar (2005). Both the oxalic acid and the formic acid were very effective, resulting in an average efficacy of 97% and 96%, respectively. There was some worker b...

  9. Swarm Flooding Attack against Directed Diffusion in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ibrahim S. I. Abuhaiba

    2012-11-01

    Full Text Available The objective of this paper is to study the vulnerabilities of sensor networks, design, and implement new approaches for routing attack. As one of the cornerstones of network infrastructure, routing systems are facing more threats than ever; they are vulnerable by nature and challenging to protect. We present a new attack, Swarm Flooding Attack, against Directed Diffusion based WSNs, which targets the consumption of sensors computational resources, such as bandwidth, disk space, or processor time. Two variants of swarm attack have been introduced: Bee and Ant. Both approaches are inspired from the natural swarming difference between bees and ants. In all cases, the strategy used to mount an attack is the same. An attack consists of a set of malicious user queries represented by interests that are inserted into the network. However, the two forms of attack vary in the synchronization aspects among attackers. These types of attacks are hard to defend against as illustrated. For each of the proposed attack models, we present analysis, simulation, and experimental measurements. We show that the system achieves maximal damage on system performance represented by many metrics.

  10. Biobotic insect swarm based sensor networks for search and rescue

    Science.gov (United States)

    Bozkurt, Alper; Lobaton, Edgar; Sichitiu, Mihail; Hedrick, Tyson; Latif, Tahmid; Dirafzoon, Alireza; Whitmire, Eric; Verderber, Alexander; Marin, Juan; Xiong, Hong

    2014-06-01

    The potential benefits of distributed robotics systems in applications requiring situational awareness, such as search-and-rescue in emergency situations, are indisputable. The efficiency of such systems requires robotic agents capable of coping with uncertain and dynamic environmental conditions. For example, after an earthquake, a tremendous effort is spent for days to reach to surviving victims where robotic swarms or other distributed robotic systems might play a great role in achieving this faster. However, current technology falls short of offering centimeter scale mobile agents that can function effectively under such conditions. Insects, the inspiration of many robotic swarms, exhibit an unmatched ability to navigate through such environments while successfully maintaining control and stability. We have benefitted from recent developments in neural engineering and neuromuscular stimulation research to fuse the locomotory advantages of insects with the latest developments in wireless networking technologies to enable biobotic insect agents to function as search-and-rescue agents. Our research efforts towards this goal include development of biobot electronic backpack technologies, establishment of biobot tracking testbeds to evaluate locomotion control efficiency, investigation of biobotic control strategies with Gromphadorhina portentosa cockroaches and Manduca sexta moths, establishment of a localization and communication infrastructure, modeling and controlling collective motion by learning deterministic and stochastic motion models, topological motion modeling based on these models, and the development of a swarm robotic platform to be used as a testbed for our algorithms.

  11. Electrochemical 'bubble swarm' enhancement of ultrasonic surface cleaning.

    Science.gov (United States)

    Birkin, P R; Offin, D G; Vian, C J B; Leighton, T G

    2015-09-07

    An investigation of surface cleaning using a swarm of gas bubbles within an acoustically activated stream is presented. Electrolysis of water at Pt microwires (100 μm diameter) to produce both hydrogen and oxygen bubbles is shown to enhance the extent of ultrasonic surface cleaning in a free flowing water stream containing an electrolyte (0.1 M Na2SO4) and low surfactant concentration (2 mM SDS). The surfactant was employed to allow control of the average size of the bubble population within the swarm. The electrochemical bubble swarm (EBS) is shown to perturb acoustic transmission through the stream. To optimise the cleaning process both the ultrasonic field and the electrochemical current are pulsed and synchronized but with different duty cycles. Cleaning action is demonstrated on structured surfaces (porcine skin and finger mimics) loaded with fluorescent particles. This action is shown to be significantly enhanced compared to that found with an inherent bubble population produced by the flow and acoustic regime alone under the same conditions.

  12. Designing Artificial Neural Networks Using Particle Swarm Optimization Algorithms.

    Science.gov (United States)

    Garro, Beatriz A; Vázquez, Roberto A

    2015-01-01

    Artificial Neural Network (ANN) design is a complex task because its performance depends on the architecture, the selected transfer function, and the learning algorithm used to train the set of synaptic weights. In this paper we present a methodology that automatically designs an ANN using particle swarm optimization algorithms such as Basic Particle Swarm Optimization (PSO), Second Generation of Particle Swarm Optimization (SGPSO), and a New Model of PSO called NMPSO. The aim of these algorithms is to evolve, at the same time, the three principal components of an ANN: the set of synaptic weights, the connections or architecture, and the transfer functions for each neuron. Eight different fitness functions were proposed to evaluate the fitness of each solution and find the best design. These functions are based on the mean square error (MSE) and the classification error (CER) and implement a strategy to avoid overtraining and to reduce the number of connections in the ANN. In addition, the ANN designed with the proposed methodology is compared with those designed manually using the well-known Back-Propagation and Levenberg-Marquardt Learning Algorithms. Finally, the accuracy of the method is tested with different nonlinear pattern classification problems.

  13. Combinatorial particle swarm optimization for solving blocking flowshop scheduling problem

    Directory of Open Access Journals (Sweden)

    Mansour Eddaly

    2016-10-01

    Full Text Available This paper addresses to the flowshop scheduling problem with blocking constraints. The objective is to minimize the makespan criterion. We propose a hybrid combinatorial particle swarm optimization algorithm (HCPSO as a resolution technique for solving this problem. At the initialization, different priority rules are exploited. Experimental study and statistical analysis were performed to select the most adapted one for this problem. Then, the swarm behavior is tested for solving a combinatorial optimization problem such as a sequencing problem under constraints. Finally, an iterated local search algorithm based on probabilistic perturbation is sequentially introduced to the particle swarm optimization algorithm for improving the quality of solution. The computational results show that our approach is able to improve several best known solutions of the literature. In fact, 76 solutions among 120 were improved. Moreover, HCPSO outperforms the compared methods in terms of quality of solutions in short time requirements. Also, the performance of the proposed approach is evaluated according to a real-world industrial problem.

  14. The equatorial electrojet current modelling from SWARM satellite data

    Science.gov (United States)

    Benaissa, Mahfoud

    2016-07-01

    Equatorial ElectroJet (EEJ) is an intense eastward electric current circulating in the ionospheric magnetic equator band between 100 and 130 km of altitude in E region. These currents vary by day, by season, by solar activity, and also with the main magnetic field of internal origin. The irregularity of the ionosphere has a major impact on the performance of communication systems and navigation (GPS), industry.... Then it becomes necessary study the characteristics of EEJ. In this paper, we present a study of the equatorial electrojet (EEJ) phenomenon along one year (2014) period. In addition, the satellite data used in this study are obtained with SWARM satellite scalar magnetometer data respecting magnetically quiet days with KP < 2. In this paper, we process to separate and extract the electrojet intensity signal from other recorded signal-sources interfering with the main signal and reduce considerably the signal to noise ratio during the SWARM measurements. This pre-processing step allows removing all external contributions in regard to EEJ intensity value. Key words: Ionosphere (Equatorial ionosphere; Electric fields and currents; Equatorial electrojet (EEJ)); SWARM.

  15. Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Mohammed Hasan Abdulameer

    2014-01-01

    Full Text Available Existing face recognition methods utilize particle swarm optimizer (PSO and opposition based particle swarm optimizer (OPSO to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM. In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented.

  16. Emergent motion patterns of delay-coupled swarms

    Science.gov (United States)

    Szwaykowska, Klementyna; Mier-Y-Teran-Romero, Luis; Schwartz, Ira

    Emergent pattern-forming behaviours of aggregates of interacting autonomous agents are a topic of great interest in complex systems research, with applications including biology, environmental monitoring, and defence. We model, and experimentally verify, pattern formation in a swarm of delay-coupled agents, using a simple but general model of agent interactions. Using mean-field dynamics, we perform a thorough analytical study of the bifurcation structure as a function of network connectivity and delay to describe the emergence of pattern formation. We show that swarm motion patterns observed for a homogeneous swarm with all-to-all communication are robust to decreasing network connectivity and to heterogeneity in the parameters governing individual agent behaviours. We perform systematic numerical studies to show where the mean-field theory deviates from simulation and experiment. This research is funded by the Office of Naval Research (ONR) (Contract No. N0001412WX20083 and NRL Base Funding Contract No. N0001414WX00023). KS holds a NRC Research Associateship Award. LMR is a post-doctoral fellow at JHU, supported by NIH.

  17. Designing Artificial Neural Networks Using Particle Swarm Optimization Algorithms

    Directory of Open Access Journals (Sweden)

    Beatriz A. Garro

    2015-01-01

    Full Text Available Artificial Neural Network (ANN design is a complex task because its performance depends on the architecture, the selected transfer function, and the learning algorithm used to train the set of synaptic weights. In this paper we present a methodology that automatically designs an ANN using particle swarm optimization algorithms such as Basic Particle Swarm Optimization (PSO, Second Generation of Particle Swarm Optimization (SGPSO, and a New Model of PSO called NMPSO. The aim of these algorithms is to evolve, at the same time, the three principal components of an ANN: the set of synaptic weights, the connections or architecture, and the transfer functions for each neuron. Eight different fitness functions were proposed to evaluate the fitness of each solution and find the best design. These functions are based on the mean square error (MSE and the classification error (CER and implement a strategy to avoid overtraining and to reduce the number of connections in the ANN. In addition, the ANN designed with the proposed methodology is compared with those designed manually using the well-known Back-Propagation and Levenberg-Marquardt Learning Algorithms. Finally, the accuracy of the method is tested with different nonlinear pattern classification problems.

  18. Improvement of Interior Ballistic Performance Utilizing Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Hazem El Sadek

    2014-01-01

    Full Text Available This paper investigates the interior ballistic propelling charge design using the optimization methods to select the optimum charge design and to improve the interior ballistic performance. The propelling charge consists of a mixture propellant of seven-perforated granular propellant and one-hole tubular propellant. The genetic algorithms and some other evolutionary algorithms have complex evolution operators such as crossover, mutation, encoding, and decoding. These evolution operators have a bad performance represented in convergence speed and accuracy of the solution. Hence, the particle swarm optimization technique is developed. It is carried out in conjunction with interior ballistic lumped-parameter model with the mixture propellant. This technique is applied to both single-objective and multiobjective problems. In the single-objective problem, the optimization results are compared with genetic algorithm and the experimental results. The particle swarm optimization introduces a better performance of solution quality and convergence speed. In the multiobjective problem, the feasible region provides a set of available choices to the charge’s designer. Hence, a linear analysis method is adopted to give an appropriate set of the weight coefficients for the objective functions. The results of particle swarm optimization improved the interior ballistic performance and provided a modern direction for interior ballistic propelling charge design of guided projectile.

  19. Particle swarm optimization applied to impulsive orbital transfers

    Science.gov (United States)

    Pontani, Mauro; Conway, Bruce A.

    2012-05-01

    The particle swarm optimization (PSO) technique is a population-based stochastic method developed in recent years and successfully applied in several fields of research. It mimics the unpredictable motion of bird flocks while searching for food, with the intent of determining the optimal values of the unknown parameters of the problem under consideration. At the end of the process, the best particle (i.e. the best solution with reference to the objective function) is expected to contain the globally optimal values of the unknown parameters. The central idea underlying the method is contained in the formula for velocity updating. This formula includes three terms with stochastic weights. This research applies the particle swarm optimization algorithm to the problem of optimizing impulsive orbital transfers. More specifically, the following problems are considered and solved with the PSO algorithm: (i) determination of the globally optimal two- and three-impulse transfer trajectories between two coplanar circular orbits; (ii) determination of the optimal transfer between two coplanar, elliptic orbits with arbitrary orientation; (iii) determination of the optimal two-impulse transfer between two circular, non-coplanar orbits; (iv) determination of the globally optimal two-impulse transfer between two non-coplanar elliptic orbits. Despite its intuitiveness and simplicity, the particle swarm optimization method proves to be capable of effectively solving the orbital transfer problems of interest with great numerical accuracy.

  20. Parallel and Cooperative Particle Swarm Optimizer for Multimodal Problems

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    Geng Zhang

    2015-01-01

    Full Text Available Although the original particle swarm optimizer (PSO method and its related variant methods show some effectiveness for solving optimization problems, it may easily get trapped into local optimum especially when solving complex multimodal problems. Aiming to solve this issue, this paper puts forward a novel method called parallel and cooperative particle swarm optimizer (PCPSO. In case that the interacting of the elements in D-dimensional function vector X=[x1,x2,…,xd,…,xD] is independent, cooperative particle swarm optimizer (CPSO is used. Based on this, the PCPSO is presented to solve real problems. Since the dimension cannot be split into several lower dimensional search spaces in real problems because of the interacting of the elements, PCPSO exploits the cooperation of two parallel CPSO algorithms by orthogonal experimental design (OED learning. Firstly, the CPSO algorithm is used to generate two locally optimal vectors separately; then the OED is used to learn the merits of these two vectors and creates a better combination of them to generate further search. Experimental studies on a set of test functions show that PCPSO exhibits better robustness and converges much closer to the global optimum than several other peer algorithms.

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

    Science.gov (United States)

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

    2014-01-01

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

  2. An efficient repeating signal detector to investigate earthquake swarms

    Science.gov (United States)

    Skoumal, Robert J.; Brudzinski, Michael R.; Currie, Brian S.

    2016-08-01

    Repetitive earthquake swarms have been recognized as key signatures in fluid injection induced seismicity, precursors to volcanic eruptions, and slow slip events preceding megathrust earthquakes. We investigate earthquake swarms by developing a Repeating Signal Detector (RSD), a computationally efficient algorithm utilizing agglomerative clustering to identify similar waveforms buried in years of seismic recordings using a single seismometer. Instead of relying on existing earthquake catalogs of larger earthquakes, RSD identifies characteristic repetitive waveforms by rapidly identifying signals of interest above a low signal-to-noise ratio and then grouping based on spectral and time domain characteristics, resulting in dramatically shorter processing time than more exhaustive autocorrelation approaches. We investigate seismicity in four regions using RSD: (1) volcanic seismicity at Mammoth Mountain, California, (2) subduction-related seismicity in Oaxaca, Mexico, (3) induced seismicity in Central Alberta, Canada, and (4) induced seismicity in Harrison County, Ohio. In each case, RSD detects a similar or larger number of earthquakes than existing catalogs created using more time intensive methods. In Harrison County, RSD identifies 18 seismic sequences that correlate temporally and spatially to separate hydraulic fracturing operations, 15 of which were previously unreported. RSD utilizes a single seismometer for earthquake detection which enables seismicity to be quickly identified in poorly instrumented regions at the expense of relying on another method to locate the new detections. Due to the smaller computation overhead and success at distances up to ~50 km, RSD is well suited for real-time detection of low-magnitude earthquake swarms with permanent regional networks.

  3. Galactic Building Blocks Seen Swarming Around Andromeda

    Science.gov (United States)

    2004-02-01

    Green Bank, WV - A team of astronomers using the National Science Foundation's Robert C. Byrd Green Bank Telescope (GBT) has made the first conclusive detection of what appear to be the leftover building blocks of galaxy formation -- neutral hydrogen clouds -- swarming around the Andromeda Galaxy, the nearest large spiral galaxy to the Milky Way. This discovery may help scientists understand the structure and evolution of the Milky Way and all spiral galaxies. It also may help explain why certain young stars in mature galaxies are surprisingly bereft of the heavy elements that their contemporaries contain. Andromeda Galaxy This image depicts several long-sought galactic "building blocks" in orbit of the Andromeda Galaxy (M31). The newfound hydrogen clouds are depicted in a shade of orange (GBT), while gas that comprises the massive hydrogen disk of Andromeda is shown at high-resolution in blue (Westerbork Sythesis Radio Telescope). CREDIT: NRAO/AUI/NSF, WSRT (Click on Image for Larger Version) "Giant galaxies, like Andromeda and our own Milky Way, are thought to form through repeated mergers with smaller galaxies and through the accretion of vast numbers of even lower mass 'clouds' -- dark objects that lack stars and even are too small to call galaxies," said David A. Thilker of the Johns Hopkins University in Baltimore, Maryland. "Theoretical studies predict that this process of galactic growth continues today, but astronomers have been unable to detect the expected low mass 'building blocks' falling into nearby galaxies, until now." Thilker's research is published in the Astrophysical Journal Letters. Other contributors include: Robert Braun of the Netherlands Foundation for Research in Astronomy; Rene A.M. Walterbos of New Mexico State University; Edvige Corbelli of the Osservatorio Astrofisico di Arcetri in Italy; Felix J. Lockman and Ronald Maddalena of the National Radio Astronomy Observatory (NRAO) in Green Bank, West Virginia; and Edward Murphy of the

  4. Improved quantum-behaved particle swarm optimization with local search strategy

    Directory of Open Access Journals (Sweden)

    Maolong Xi

    2017-03-01

    Full Text Available Quantum-behaved particle swarm optimization, which was motivated by analysis of particle swarm optimization and quantum system, has shown compared performance in finding the optimal solutions for many optimization problems to other evolutionary algorithms. To address the problem of premature, a local search strategy is proposed to improve the performance of quantum-behaved particle swarm optimization. In proposed local search strategy, a super particle is presented which is a collection body of randomly selected particles’ dimension information in the swarm. The selected probability of particles in swarm is different and determined by their fitness values. To minimization problems, the fitness value of one particle is smaller; the selected probability is more and will contribute more information in constructing the super particle. In addition, in order to investigate the influence on algorithm performance with different local search space, four methods of computing the local search radius are applied in local search strategy and propose four variants of local search quantum-behaved particle swarm optimization. Empirical studies on a suite of well-known benchmark functions are undertaken in order to make an overall performance comparison among the proposed methods and other quantum-behaved particle swarm optimization. The simulation results show that the proposed quantum-behaved particle swarm optimization variants have better advantages over the original quantum-behaved particle swarm optimization.

  5. An Orthogonal Multi-Swarm Cooperative PSO Algorithm with a Particle Trajectory Knowledge Base

    Directory of Open Access Journals (Sweden)

    Jun Yang

    2017-01-01

    Full Text Available A novel orthogonal multi-swarm cooperative particle swarm optimization (PSO algorithm with a particle trajectory knowledge base is presented in this paper. Different from the traditional PSO algorithms and other variants of PSO, the proposed orthogonal multi-swarm cooperative PSO algorithm not only introduces an orthogonal initialization mechanism and a particle trajectory knowledge base for multi-dimensional optimization problems, but also conceives a new adaptive cooperation mechanism to accomplish the information interaction among swarms and particles. Experiments are conducted on a set of benchmark functions, and the results show its better performance compared with traditional PSO algorithm in aspects of convergence, computational efficiency and avoiding premature convergence.

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

    Science.gov (United States)

    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.

  7. Initiation of absconding-swarm emigration in the social wasp Polybia occidentalis.

    Science.gov (United States)

    Sonnentag, Peter J; Jeanne, Robert L

    2009-01-01

    When a colony of the swarm-founding social wasp Polybia occidentals loses its nest to severe weather or predation, the adult population evacuates and temporarily clusters on nearby foliage. Most of the adults remain inactive in the cluster, while foragers bring in nectar and scout wasps search the surrounding area for a new nesting site. After several hours, the scouts stimulate the rest of the swarm to leave the cluster and follow their pheromone trail to the chosen site. How scouts communicate to their swarm-mates that a site has been chosen and how they induce the swarm to depart are unknown. Video records of six Costa Rican swarms were used to quantitatively document changes in the frequencies of social behaviors leading to swarm departure. This was accomplished by going backward through the video record and following the behavior of individuals prior to their departure. Analysis of the behavior of scouts and inactive wasps indicated an increase in the frequency with which scouts bump into inactive wasps prior to swarm departure, as well as a shift in the behavior of inactive wasps from primarily receiving bumps to bumping others before departure. Thus, bumping is propagated by recently activated individuals before they take off. These observations suggest that not only is bumping an activation stimulus that causes swarm members to depart for the new nest site, but it is contagious, leading to its amplification throughout the swarm.

  8. PERFORMANCE OF PID CONTROLLER OF NONLINEAR SYSTEM USING SWARM INTELLIGENCE TECHNIQUES

    Directory of Open Access Journals (Sweden)

    Neeraj Jain

    2016-07-01

    Full Text Available In this paper swarm intelligence based PID controller tuning is proposed for a nonlinear ball and hoop system. Particle swarm optimization (PSO, Artificial bee colony (ABC, Bacterial foraging optimization (BFO is some example of swarm intelligence techniques which are focused for PID controller tuning. These algorithms are also tested on perturbed ball and hoop model. Integral square error (ISE based performance index is used for finding the best possible value of controller parameters. Matlab software is used for designing the ball and hoop model. It is found that these swarm intelligence techniques have easy implementation & lesser settling & rise time compare to conventional methods.

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

    Directory of Open Access Journals (Sweden)

    Huanqing Cui

    2017-03-01

    Full Text Available 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.

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

    Science.gov (United States)

    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

  11. Co-combustion of peanut hull and coal blends: Artificial neural networks modeling, particle swarm optimization and Monte Carlo simulation.

    Science.gov (United States)

    Buyukada, Musa

    2016-09-01

    Co-combustion of coal and peanut hull (PH) were investigated using artificial neural networks (ANN), particle swarm optimization, and Monte Carlo simulation as a function of blend ratio, heating rate, and temperature. The best prediction was reached by ANN61 multi-layer perception model with a R(2) of 0.99994. Blend ratio of 90 to 10 (PH to coal, wt%), temperature of 305°C, and heating rate of 49°Cmin(-1) were determined as the optimum input values and yield of 87.4% was obtained under PSO optimized conditions. The validation experiments resulted in yields of 87.5%±0.2 after three replications. Monte Carlo simulations were used for the probabilistic assessments of stochastic variability and uncertainty associated with explanatory variables of co-combustion process.

  12. Swarm Absolute Scalar Magnetometers first in-orbit results

    Science.gov (United States)

    Fratter, Isabelle; Léger, Jean-Michel; Bertrand, François; Jager, Thomas; Hulot, Gauthier; Brocco, Laura; Vigneron, Pierre

    2016-04-01

    The ESA Swarm mission will provide the best ever survey of the Earth's magnetic field and its temporal evolution. This will be achieved by a constellation of three identical satellites, launched together on the 22nd of November 2013. In order to observe the magnetic field thoroughly, each satellite carries two magnetometers: a Vector Field Magnetometer (VFM) coupled with a star tracker camera, to measure the direction of the magnetic field in space, and an Absolute Scalar Magnetometer (ASM), to measure its intensity. The ASM is the French contribution to the Swarm mission. This new generation instrument was designed by CEA-Leti and developed in close partnership with CNES, with scientific support from IPGP. Its operating principle is based on the atomic spectroscopy of the helium 4 metastable state. It makes use of the Zeeman's effect to transduce the magnetic field into a frequency, the signal being amplified by optical pumping. The primary role of the ASM is to provide absolute measurements of the magnetic field's strength at 1 Hz, for the in-flight calibration of the VFM. As the Swarm magnetic reference, the ASM scalar performance is crucial for the mission's success. Thanks to its innovative design, the ASM offers the best precision, resolution and absolute accuracy ever attained in space, with similar performance all along the orbit. In addition, thanks to an original architecture, the ASM implements on an experimental basis a capacity for providing simultaneously vector measurements at 1 Hz. This new feature makes it the first instrument capable of delivering both scalar and vector measurements simultaneously at the same point. Swarm offers a unique opportunity to validate the ASM vector data in orbit by comparison with the VFM's. Furthermore, the ASM can provide scalar data at a much higher sampling rate, when run in "burst" mode at 250 Hz, with a 100 Hz measurement bandwidth. An analysis of the spectral content of the magnetic field above 1 Hz becomes thus

  13. Particle swarm optimization of ascent trajectories of multistage launch vehicles

    Science.gov (United States)

    Pontani, Mauro

    2014-02-01

    Multistage launch vehicles are commonly employed to place spacecraft and satellites in their operational orbits. If the rocket characteristics are specified, the optimization of its ascending trajectory consists of determining the optimal control law that leads to maximizing the final mass at orbit injection. The numerical solution of a similar problem is not trivial and has been pursued with different methods, for decades. This paper is concerned with an original approach based on the joint use of swarming theory and the necessary conditions for optimality. The particle swarm optimization technique represents a heuristic population-based optimization method inspired by the natural motion of bird flocks. Each individual (or particle) that composes the swarm corresponds to a solution of the problem and is associated with a position and a velocity vector. The formula for velocity updating is the core of the method and is composed of three terms with stochastic weights. As a result, the population migrates toward different regions of the search space taking advantage of the mechanism of information sharing that affects the overall swarm dynamics. At the end of the process the best particle is selected and corresponds to the optimal solution to the problem of interest. In this work the three-dimensional trajectory of the multistage rocket is assumed to be composed of four arcs: (i) first stage propulsion, (ii) second stage propulsion, (iii) coast arc (after release of the second stage), and (iv) third stage propulsion. The Euler-Lagrange equations and the Pontryagin minimum principle, in conjunction with the Weierstrass-Erdmann corner conditions, are employed to express the thrust angles as functions of the adjoint variables conjugate to the dynamics equations. The use of these analytical conditions coming from the calculus of variations leads to obtaining the overall rocket dynamics as a function of seven parameters only, namely the unknown values of the initial state

  14. Impact of Swarm GPS receiver updates on POD performance

    Science.gov (United States)

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

    2016-05-01

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

  15. Viewpoint Selection Using Hybrid Simplex Search and Particle Swarm Optimization for Volume Rendering

    Directory of Open Access Journals (Sweden)

    Zhang You-sai,,,

    2012-09-01

    Full Text Available In this paper we proposed a novel method of viewpoint selection using the hybrid Nelder-Mead (NM simplex search and particle swarm optimization (PSO to improve the efficiency and the intelligent level of volume rendering. This method constructed the viewpoint quality evaluation function in the form of entropy by utilizing the luminance and structure features of the two-dimensional projective image of volume data. During the process of volume rendering, the hybrid NM-PSO algorithm intended to locate the globally optimal viewpoint or a set of the optimized viewpoints automatically and intelligently. Experimental results have shown that this method avoids redundant interactions and evidently improves the efficiency of volume rendering. The optimized viewpoints can focus on the important structural features or the region of interest in volume data and exhibit definite correlation with the perception character of human visual system. Compared with the methods based on PSO or NM simplex search, our method has the better performance of convergence rate, convergence accuracy and robustness.

  16. A fuzzy-based particle swarm optimisation approach for task assignment in home healthcare

    Directory of Open Access Journals (Sweden)

    Mutingi, Michael

    2014-11-01

    Full Text Available Home healthcare (HHC organisations provide coordinated healthcare services to patients at their homes. Motivated by the ever-increasing need for home-based care, the assignment of tasks to available healthcare staff is a common and complex problem in homecare organisations. Designing high quality task schedules is critical for improving worker morale, job satisfaction, service efficiency, service quality, and competitiveness over the long term. The desire is to provide high quality task assignment schedules that satisfy the patient, the care worker, and the management. This translates to maximising schedule fairness in terms of workload assignments, avoiding task time window violation, and meeting management goals as much as possible. However, in practice, these desires are often subjective as they involve imprecise human perceptions. This paper develops a fuzzy multi-criteria particle swarm optimisation (FPSO approach for task assignment in a home healthcare setting in a fuzzy environment. The proposed approach uses a fuzzy evaluation method from a multi-criteria point of view. Results from illustrative computational experiments show that the approach is promising.

  17. A Method for Consensus Reaching in Product Kansei Evaluation Using Advanced Particle Swarm Optimization

    Science.gov (United States)

    2017-01-01

    Consumers' opinions toward product design alternatives are often subjective and perceptual, which reflect their perception about a product and can be described using Kansei adjectives. Therefore, Kansei evaluation is often employed to determine consumers' preference. However, how to identify and improve the reliability of consumers' Kansei evaluation opinions toward design alternatives has an important role in adding additional insurance and reducing uncertainty to successful product design. To solve this problem, this study employs a consensus model to measure consistence among consumers' opinions, and an advanced particle swarm optimization (PSO) algorithm combined with Linearly Decreasing Inertia Weight (LDW) method is proposed for consensus reaching by minimizing adjustment of consumers' opinions. Furthermore, the process of the proposed method is presented and the details are illustrated using an example of electronic scooter design evaluation. The case study reveals that the proposed method is promising for reaching a consensus through searching optimal solutions by PSO and improving the reliability of consumers' evaluation opinions toward design alternatives according to Kansei indexes. PMID:28316619

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Bingbing Zhang

    2017-03-01

    Full Text Available 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.

  1. Bodily maps of emotions.

    Science.gov (United States)

    Nummenmaa, Lauri; Glerean, Enrico; Hari, Riitta; Hietanen, Jari K

    2014-01-14

    Emotions are often felt in the body, and somatosensory feedback has been proposed to trigger conscious emotional experiences. Here we reveal maps of bodily sensations associated with different emotions using a unique topographical self-report method. In five experiments, participants (n = 701) were shown two silhouettes of bodies alongside emotional words, stories, movies, or facial expressions. They were asked to color the bodily regions whose activity they felt increasing or decreasing while viewing each stimulus. Different emotions were consistently associated with statistically separable bodily sensation maps across experiments. These maps were concordant across West European and East Asian samples. Statistical classifiers distinguished emotion-specific activation maps accurately, confirming independence of topographies across emotions. We propose that emotions are represented in the somatosensory system as culturally universal categorical somatotopic maps. Perception of these emotion-triggered bodily changes may play a key role in generating consciously felt emotions.

  2. Estimation of the magnetic field gradient tensor using the Swarm constellation

    DEFF Research Database (Denmark)

    Kotsiaros, Stavros; Finlay, Chris; Olsen, Nils

    2014-01-01

    For the first time, part of the magnetic field gradient tensor is estimated in space by the Swarm mission. We investigate the possibility of a more complete estimation of the gradient tensor exploiting the Swarm constellation. The East-West gradients can be approximated by observations from...

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

    DEFF Research Database (Denmark)

    Park, Jaeheung; Luehr, Hermann; Michaelis, Ingo;

    2015-01-01

    In this study we investigate the three-dimensional structure of low-latitude plasma blobs using multi-instrument and multisatellite observations of the Swarm constellation. During the early commissioning phase the Swarm satellites were flying at the same altitude with zonal separation of about 0...

  4. Swarming of the Formosan Subteranean Termite (Isoptera: Rhinotermitidae) in Southern Mississippi

    Science.gov (United States)

    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...

  5. ArDroneXT - Ar.Drone 2 eXTension for swarming and service hosting

    OpenAIRE

    Autefage, Vincent; Chaumette, Serge

    2013-01-01

    This is an Operating System Setup Guide.; This report explains how to upgrade an Ar.Drone 2 for swarming and services hosting. In other words, it gives the technical information required to easily create a swarm of Ar.Drone 2 sharing a Wi-Fi network. Moreover, it describes the process to install new services and applications on the drone.

  6. An iron detection system determines bacterial swarming initiation and biofilm formation

    NARCIS (Netherlands)

    Lin, Chuan-Sheng; Tsai, Yu-Huan; Chang, Chih-Jung; Tseng, Shun-Fu; Wu, Tsung-Ru; Lu, Chia-Chen; Wu, Ting-Shu; Lu, Jang-Jih; Horng, Jim-Tong; Martel, Jan; Ojcius, David M.; Lai, Hsin-Chih; Young, John D.; Andrews, S. C.; Robinson, A. K.; Rodriguez-Quinones, F.; Touati, D.; Yeom, J.; Imlay, J. A.; Park, W.; Marx, J. J.; Braun, V.; Hantke, K.; Cornelis, P.; Wei, Q.; Vinckx, T.; Troxell, B.; Hassan, H. M.; Verstraeten, N.; Lewis, K.; Hall-Stoodley, L.; Costerton, J. W.; Stoodley, P.; Kearns, D. B.; Losick, R.; Butler, M. T.; Wang, Q.; Harshey, R. M.; Lai, S.; Tremblay, J.; Deziel, E.; Overhage, J.; Bains, M.; Brazas, M. D.; Hancock, R. E.; Partridge, J. D.; Kim, W.; Surette, M. G.; Givskov, M.; Rather, P. N.; Houdt, R. Van; Michiels, C. W.; Mukherjee, S.; Inoue, T.; Frye, J. G.; McClelland, M.; McCarter, L.; Silverman, M.; Matilla, M. A.; Wu, Y.; Outten, F. W.; Singh, P. K.; Parsek, M. R.; Greenberg, E. P.; Welsh, M. J.; Banin, E.; Vasil, M. L.; Wosten, M. M.; Kox, L. F.; Chamnongpol, S.; Soncini, F. C.; Groisman, E. A.; Laub, M. T.; Goulian, M.; Krell, T.; Lai, H. C.; Lin, C. S.; Soo, P. C.; Tsai, Y. H.; Wei, J. R.; Wyckoff, E. E.; Mey, A. R.; Leimbach, A.; Fisher, C. F.; Payne, S. M.; Livak, K. J.; Schmittgen, T. D.; Clarke, M. B.; Hughes, D. T.; Zhu, C.; Boedeker, E. C.; Sperandio, V.; Stintzi, A.; Clarke-Pearson, M. F.; Brady, S. F.; Drake, E. J.; Gulick, A. M.; Qaisar, U.; Rowland, M. A.; Deeds, E. J.; Garcia, C. A.; Alcaraz, E. S.; Franco, M. A.; Rossi, B. N. Passerini de; Mehi, O.; Skaar, E. P.; Visaggio, D.; Nishino, K.; Dietz, P.; Gerlach, G.; Beier, D.; Bustin, S. A.; Schwyn, B.; Neilands, J. B.

    2016-01-01

    Iron availability affects swarming and biofilm formation in various bacterial species. However, how bacteria sense iron and coordinate swarming and biofilm formation remains unclear. Using Serratia marcescens as a model organism, we identify here a stage-specific iron-regulatory machinery comprising

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

    Directory of Open Access Journals (Sweden)

    Miguel Duarte

    Full Text Available 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.

  8. The Ionospheric Bubble Index deduced from magnetic field and plasma observations onboard Swarm

    DEFF Research Database (Denmark)

    Park, Jaeheung; Noja, Max; Stolle, Claudia

    2013-01-01

    In the post-sunset tropical ionospheric F-region plasma density often exhibits depletions, which are usually called equatorial plasma bubbles (EPBs). In this paper we give an overview of the Swarm Level 2 Ionospheric Bubble Index (IBI), which is a standard scientific data of the Swarm mission. Th...

  9. An iron detection system determines bacterial swarming initiation and biofilm formation

    NARCIS (Netherlands)

    Lin, Chuan-Sheng; Tsai, Yu-Huan; Chang, Chih-Jung; Tseng, Shun-Fu; Wu, Tsung-Ru; Lu, Chia-Chen; Wu, Ting-Shu; Lu, Jang-Jih; Horng, Jim-Tong; Martel, Jan; Ojcius, David M.; Lai, Hsin-Chih; Young, John D.; Andrews, S. C.; Robinson, A. K.; Rodriguez-Quinones, F.; Touati, D.; Yeom, J.; Imlay, J. A.; Park, W.; Marx, J. J.; Braun, V.; Hantke, K.; Cornelis, P.; Wei, Q.; Vinckx, T.; Troxell, B.; Hassan, H. M.; Verstraeten, N.; Lewis, K.; Hall-Stoodley, L.; Costerton, J. W.; Stoodley, P.; Kearns, D. B.; Losick, R.; Butler, M. T.; Wang, Q.; Harshey, R. M.; Lai, S.; Tremblay, J.; Deziel, E.; Overhage, J.; Bains, M.; Brazas, M. D.; Hancock, R. E.; Partridge, J. D.; Kim, W.; Surette, M. G.; Givskov, M.; Rather, P. N.; Houdt, R. Van; Michiels, C. W.; Mukherjee, S.; Inoue, T.; Frye, J. G.; McClelland, M.; McCarter, L.; Silverman, M.; Matilla, M. A.; Wu, Y.; Outten, F. W.; Singh, P. K.; Parsek, M. R.; Greenberg, E. P.; Welsh, M. J.; Banin, E.; Vasil, M. L.; Wosten, M. M.; Kox, L. F.; Chamnongpol, S.; Soncini, F. C.; Groisman, E. A.; Laub, M. T.; Goulian, M.; Krell, T.; Lai, H. C.; Lin, C. S.; Soo, P. C.; Tsai, Y. H.; Wei, J. R.; Wyckoff, E. E.; Mey, A. R.; Leimbach, A.; Fisher, C. F.; Payne, S. M.; Livak, K. J.; Schmittgen, T. D.; Clarke, M. B.; Hughes, D. T.; Zhu, C.; Boedeker, E. C.; Sperandio, V.; Stintzi, A.; Clarke-Pearson, M. F.; Brady, S. F.; Drake, E. J.; Gulick, A. M.; Qaisar, U.; Rowland, M. A.; Deeds, E. J.; Garcia, C. A.; Alcaraz, E. S.; Franco, M. A.; Rossi, B. N. Passerini de; Mehi, O.; Skaar, E. P.; Visaggio, D.; Nishino, K.; Dietz, P.; Gerlach, G.; Beier, D.; Bustin, S. A.; Schwyn, B.; Neilands, J. B.

    2016-01-01

    Iron availability affects swarming and biofilm formation in various bacterial species. However, how bacteria sense iron and coordinate swarming and biofilm formation remains unclear. Using Serratia marcescens as a model organism, we identify here a stage-specific iron-regulatory machinery comprising

  10. The Swarm Initial Field Model – a Model of the Earth’s Magnetic Field for 2014 Determined From One Year of Swarm Satellite Constellation Data

    DEFF Research Database (Denmark)

    Olsen, Nils; Hulot, Gauthier; Lesur, Vincent;

    Almost one year of data from ESA's Swarm constellation mission are used to derive a model of the Earth’s magnetic field and its time variation (secular variation). The model describes contributions from the core and lithosphere as well as large-scale contributions from the magnetosphere (and its......) frame. In addition to the magnetic field observations provided by each of the three Swarm satellites we include the East-west magnetic gradient information provided by the lower Swarm satellite pair, thereby explicitly taking advantage of the constellation aspect of Swarm. We assess the spatial...... Earth-induced counterpart). We use data from geomagnetic quiet times (Kp less than 2o, time change of Dst-index less than 2 nT/hr) and dark regions (sun below horizon) and co-estimate the Euler angles describing the rotation between the vector magnetometer instrument frame and the North-East-Center (NEC...

  11. Triggered Swarms and Induced Aftershock Sequences in Geothermal Systems

    Science.gov (United States)

    Shcherbakov, R.; Turcotte, D. L.; Yikilmaz, M. B.; Kellogg, L. H.; Rundle, J. B.

    2015-12-01

    Natural geothermal systems, which are used for energy generation, are usually associated with high seismic activity. This can be related to the large-scale injection and extraction of fluids to enhance geothermal recovery. This results in the changes of the pore pressure and pore-elastic stress field and can stimulate the occurrence of earthquakes. These systems are also prone to triggering of seismicity by the passage of seismic waves generated by large distant main shocks. In this study, we analyze clustering and triggering of seismicity at several geothermal fields in California. Particularly, we consider the seismicity at the Geysers, Coso, and Salton Sea geothermal fields. We analyze aftershock sequences generated by local large events with magnitudes greater than 4.0 and earthquake swarms generated by several significant long distant main shocks. We show that the rate of the aftershock sequences generated by the local large events in the two days before and two days after the reference event can be modelled reasonably well by the time dependent Epidemic Type Aftershock Sequence (ETAS) model. On the other hand, the swarms of activity triggered by large distant earthquakes cannot be described by the ETAS model. To model the increase in the rate of seismicity associated with triggering by large distant main shocks we introduce an additional time-dependent triggering mechanism into the ETAS model. In almost all cases the frequency-magnitude statistics of triggered sequences follow Gutenberg-Richter scaling to a good approximation. The analysis indicates that the seismicity triggered by relatively large local events can initiate sequences similar to regular aftershock sequences. In contrast, the distant main shocks trigger swarm like activity with faster decaying rates.

  12. Performance Evaluation of Content Based Image Retrieval on Feature Optimization and Selection Using Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Kirti Jain

    2016-03-01

    Full Text Available The diversity and applicability of swarm intelligence is increasing everyday in the fields of science and engineering. Swarm intelligence gives the features of the dynamic features optimization concept. We have used swarm intelligence for the process of feature optimization and feature selection for content-based image retrieval. The performance of content-based image retrieval faced the problem of precision and recall. The value of precision and recall depends on the retrieval capacity of the image. The basic raw image content has visual features such as color, texture, shape and size. The partial feature extraction technique is based on geometric invariant function. Three swarm intelligence algorithms were used for the optimization of features: ant colony optimization, particle swarm optimization (PSO, and glowworm optimization algorithm. Coral image dataset and MatLab software were used for evaluating performance.

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

    Energy Technology Data Exchange (ETDEWEB)

    Maiden, Wendy M. [Washington State Univ., Pullman, WA (United States)

    2010-05-01

    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 still 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.

  14. Modelling and stability analysis of emergent behavior of scalable swarm system

    Institute of Scientific and Technical Information of China (English)

    CHEN Shi-ming; FANG Hua-jing

    2006-01-01

    In this paper we propose a two-layer emergent model for scalable swarm system. The first layer describes the individual flocking behavior to the local goal position (the center of minimal circumcircle decided by the neighbors in the positive visual set of individuals) resulting from the individual motion to one or two farthest neighbors in its positive visual set; the second layer describes the emergent aggregating swarm behavior resulting from the individual motion to its local goal position. The scale of the swarm will not be limited because only local individual information is used for modelling in the two-layer topology. We study the stability properties of the swarm emergent behavior based on Lyapunov stability theory. Simulations showed that the swarm system can converge to goal regions while maintaining cohesiveness.

  15. Pseudomonad Swarming Motility Is Restricted to a Narrow Range of High Matric Water Potentials

    DEFF Research Database (Denmark)

    Dechesne, Arnaud; Smets, Barth F.

    2012-01-01

    Using a novel experimental system that allows control of the matric potential of an agar slab, we explored the hydration conditions under which swarming motility is possible. If there is recognition that this physical parameter is a key determinant of swarming, it is usually neither controlled nor...... measured rigorously but only manipulated through proxies, namely, the agar concentration and the drying time of "soft" agar plates (swarming plates). We contend that this not only obscures the biophysical mechanisms underlying swarming but also impedes a full assessment of its clinical and environmental......Pa for the first and about –0.1 kPa for the latter two. Above the threshold, the expansion rate of DSS73 swarms increased exponentially with the matric potential. Mutants deficient in surfactant production were totally or partially unable to expand rapidly on the surface of the agar slab. Our results thus suggest...

  16. Combined Data with Particle Swarm Optimization for Structural Damage Detection

    Directory of Open Access Journals (Sweden)

    Fei Kang

    2013-01-01

    Full Text Available This paper proposes a damage detection method based on combined data of static and modal tests using particle swarm optimization (PSO. To improve the performance of PSO, some immune properties such as selection, receptor editing, and vaccination are introduced into the basic PSO and an improved PSO algorithm is formed. Simulations on three benchmark functions show that the new algorithm performs better than PSO. The efficiency of the proposed damage detection method is tested on a clamped beam, and the results demonstrate that it is more efficient than PSO, differential evolution, and an adaptive real-parameter simulated annealing genetic algorithm.

  17. Learning Bayesian Networks from Data by Particle Swarm Optimization

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Learning Bayesian network is an NP-hard problem. When the number of variables is large, the process of searching optimal network structure could be very time consuming and tends to return a structure which is local optimal. The particle swarm optimization (PSO) was introduced to the problem of learning Bayesian networks and a novel structure learning algorithm using PSO was proposed. To search in directed acyclic graphs spaces efficiently, a discrete PSO algorithm especially for structure learning was proposed based on the characteristics of Bayesian networks. The results of experiments show that our PSO based algorithm is fast for convergence and can obtain better structures compared with genetic algorithm based algorithms.

  18. Multidimensional particle swarm optimization for machine learning and pattern recognition

    CERN Document Server

    Kiranyaz, Serkan; Gabbouj, Moncef

    2013-01-01

    For many engineering problems we require optimization processes with dynamic adaptation as we aim to establish the dimension of the search space where the optimum solution resides and develop robust techniques to avoid the local optima usually associated with multimodal problems. This book explores multidimensional particle swarm optimization, a technique developed by the authors that addresses these requirements in a well-defined algorithmic approach.  After an introduction to the key optimization techniques, the authors introduce their unified framework and demonstrate its advantages in chal

  19. Hybrid particle swarm optimization for solving resource-constrained FMS

    Institute of Scientific and Technical Information of China (English)

    Dongyun Wang; Liping Liu

    2008-01-01

    In this paper,an approach for resource-constrained flexible manufacturing system(FMS)scheduling was proposed,which is based on the particle swarm optimization(PSO)algorithm and simulated annealing(SA)algorithm.First,the formulation for resource-con-strained FMS scheduling problem was introduced and cost function for this problem was obtained.Then.a hybrid algorithm of PSO and SA was employed to obtain optimal solution.The simulated results show that the approach can dislodge a state from a local min-imum and guide it to the global minimum.

  20. Optimization of mechanical structures using particle swarm optimization

    Energy Technology Data Exchange (ETDEWEB)

    Leite, Victor C.; Schirru, Roberto, E-mail: victor.coppo.leite@lmp.ufrj.br [Coordenacao dos Programas de Pos-Graduacao em Engenharia (LMP/PEN/COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Lab. de Monitoracao de Processos

    2015-07-01

    Several optimization problems are dealed with the particle swarm optimization (PSO) algorithm, there is a wide kind of optimization problems, it may be applications related to logistics or the reload of nuclear reactors. This paper discusses the use of the PSO in the treatment of problems related to mechanical structure optimization. The geometry and material characteristics of mechanical components are important for the proper functioning and performance of the systems were they are applied, particularly to the nuclear field. Calculations related to mechanical aspects are all made using ANSYS, while the PSO is programed in MATLAB. (author)