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Sample records for swarm size direction

  1. Topological Design of Planar Circularly Polarized Directional Antenna with Low Profile Using Particle Swarm Optimization

    National Research Council Canada - National Science Library

    Xiaonan Zhao; Junping Geng; Ronghong Jin; Yao Jin; Xiang Liu; Wenyan Yin

    2017-01-01

    ...) directional antenna with low profile was presented. By inserting two parasitic layers, generated by particle swarm optimization, between the equiangular spiral antenna and the ground, a low-profile wideband CP antenna with directional radiation...

  2. Topological Design of Planar Circularly Polarized Directional Antenna with Low Profile Using Particle Swarm Optimization

    OpenAIRE

    Xiaonan Zhao; Junping Geng; Ronghong Jin; Yao Jin; Xiang Liu; Wenyan Yin

    2017-01-01

    A topological method for the design and optimization of planar circularly polarized (CP) directional antenna with low profile was presented. By inserting two parasitic layers, generated by particle swarm optimization, between the equiangular spiral antenna and the ground, a low-profile wideband CP antenna with directional radiation pattern and high gain is achieved. The optimized antenna shows an impedance matching band (S11

  3. Optimization of Transformation Coefficients Using Direct Search and Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Manusov V.Z.

    2017-04-01

    Full Text Available This research considers optimization of tap position of transformers in power systems to reduce power losses. Now, methods based on heuristic rules and fuzzy logic, or methods that optimize parts of the whole system separately, are applied to this problem. The first approach requires expert knowledge about processes in the network. The second methods are not able to consider all the interrelations of system’s parts, while changes in segment affect the entire system. Both approaches are tough to implement and require adjustment to the tasks solved. It needs to implement algorithms that can take into account complex interrelations of optimized variables and self-adapt to optimization task. It is advisable to use algorithms given complex interrelations of optimized variables and independently adapting from optimization tasks. Such algorithms include Swarm Intelligence algorithms. Their main features are self-organization, which allows them to automatically adapt to conditions of tasks, and the ability to efficiently exit from local extremes. Thus, they do not require specialized knowledge of the system, in contrast to fuzzy logic. In addition, they can efficiently find quasi-optimal solutions converging to the global optimum. This research applies Particle Swarm Optimization algorithm (PSO. The model of Tajik power system used in experiments. It was found out that PSO is much more efficient than greedy heuristics and more flexible and easier to use than fuzzy logic. PSO allows reducing active power losses from 48.01 to 45.83 MW (4.5%. With al, the effect of using greedy heuristics or fuzzy logic is two times smaller (2.3%.

  4. Ideal Directed-Energy System To Defeat Small Unmanned Aircraft System Swarms

    Science.gov (United States)

    2017-05-21

    Administration (FAA) defines a UAS as “an aircraft that is operated without the possibility of direct human intervention from within or on the...100 to 500.20 One of Intel’s more recent sUAS swarms demonstrations occurred during the 2017 National Football League Super Bowl that generated a...Federal Aviation Administration , FAA Aerospace Forecast: Fiscal Years 2017-2037, 30, accessed April 22, 2017, https://www.faa.gov/data_research

  5. The Feasibility of Radio Direction Finding for Swarm Localization

    Science.gov (United States)

    2017-09-01

    to an intermediate frequency, and digitally sampled. The samples are passed to the PL (programmable logic) on the Zynq integrated circuit , where...same example with (0,0.025) Gaussian noise added to the Δ measurements. In Fig. 6 the phase points (Δ1,Δ2) no longer lie directly on the...level of noise increases, phase points may occur closer to the wrong phase line, resulting in erroneous values for 1 and 2. By designing the

  6. Topological Design of Planar Circularly Polarized Directional Antenna with Low Profile Using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Xiaonan Zhao

    2017-01-01

    Full Text Available A topological method for the design and optimization of planar circularly polarized (CP directional antenna with low profile was presented. By inserting two parasitic layers, generated by particle swarm optimization, between the equiangular spiral antenna and the ground, a low-profile wideband CP antenna with directional radiation pattern and high gain is achieved. The optimized antenna shows an impedance matching band (S11<-10 dB of 4–12 GHz with a whole-band stable directional pattern in 4–11.5 GHz, and the antenna gain peak is 8 dBi, which work well in the available band. Measured return loss, antenna gain, and far field patterns agree well with simulation results.

  7. A New Hybrid Nelder-Mead Particle Swarm Optimization for Coordination Optimization of Directional Overcurrent Relays

    Directory of Open Access Journals (Sweden)

    An Liu

    2012-01-01

    Full Text Available Coordination optimization of directional overcurrent relays (DOCRs is an important part of an efficient distribution system. This optimization problem involves obtaining the time dial setting (TDS and pickup current (Ip values of each DOCR. The optimal results should have the shortest primary relay operating time for all fault lines. Recently, the particle swarm optimization (PSO algorithm has been considered an effective tool for linear/nonlinear optimization problems with application in the protection and coordination of power systems. With a limited runtime period, the conventional PSO considers the optimal solution as the final solution, and an early convergence of PSO results in decreased overall performance and an increase in the risk of mistaking local optima for global optima. Therefore, this study proposes a new hybrid Nelder-Mead simplex search method and particle swarm optimization (proposed NM-PSO algorithm to solve the DOCR coordination optimization problem. PSO is the main optimizer, and the Nelder-Mead simplex search method is used to improve the efficiency of PSO due to its potential for rapid convergence. To validate the proposal, this study compared the performance of the proposed algorithm with that of PSO and original NM-PSO. The findings demonstrate the outstanding performance of the proposed NM-PSO in terms of computation speed, rate of convergence, and feasibility.

  8. Direction Tracking of Multiple Moving Targets Using Quantum Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Gao Hongyuan

    2016-01-01

    Full Text Available Based on weighted signal covariance (WSC matrix and maximum likelihood (ML estimation, a directionof-arrival (DOA estimation method of multiple moving targets is designed and named as WSC-ML in the presence of impulse noise. In order to overcome the shortcoming of the multidimensional search cost of maximum likelihood estimation, a novel continuous quantum particle swarm optimization (QPSO is proposed for this continuous optimization problem. And a tracking method of multiple moving targets in impulsive noise environment is proposed and named as QPSO-WSC-ML. Later, we make use of rank-one updating to update the weighted signal covariance matrix of WSC-ML. Simulation results illustrate the proposed QPSO-WSC-ML method is efficient and robust for the direction tracking of multiple moving targets in the presence of impulse noise.

  9. A Performance Study on Synchronous and Asynchronous Update Rules for A Plug-In Direct Particle Swarm Repetitive Controller

    Directory of Open Access Journals (Sweden)

    Ufnalski Bartlomiej

    2014-12-01

    Full Text Available In this paper two different update schemes for the recently developed plug-in direct particle swarm repetitive controller (PDPSRC are investigated and compared. The proposed approach employs the particle swarm optimizer (PSO to solve in on-line mode a dynamic optimization problem (DOP related to the control task in the constant-amplitude constant-frequency voltage-source inverter (CACF VSI with an LC output filter. The effectiveness of synchronous and asynchronous update rules, both commonly used in static optimization problems (SOPs, is assessed and compared in the case of PDPSRC. The performance of the controller, when synthesized using each of the update schemes, is studied numerically.

  10. The West Bohemian 2008-earthquake swarm: When, where, what size and data

    Czech Academy of Sciences Publication Activity Database

    Horálek, Josef; Fischer, Tomáš; Boušková, Alena; Michálek, Jan; Hrubcová, Pavla

    2009-01-01

    Roč. 53, č. 3 (2009), s. 351-358 ISSN 0039-3169 Institutional research plan: CEZ:AV0Z30120515 Keywords : West Bohemia/Vogtland * earthquake swarm * WEBNET Subject RIV: DC - Siesmology, Volcanology, Earth Structure Impact factor: 1.000, year: 2009

  11. Application of proper orthogonal decomposition and radial basis functions for crack size estimation using particle swarm optimization

    Science.gov (United States)

    Benaissa, B.; Köppen, M.; Abdel Wahab, M.; Khatir, S.

    2017-05-01

    Complex engineering problems require simulations, which are computationally expensive in cases of inverse identification tasks since they commonly requires hundreds of thousands of simulations. This paper propose a method based on model reduction for crack size estimation, combining the proper orthogonal decomposition method with radial basis functions. The reduced model is validated by comparing the obtained boundary displacements with the corresponding results from a finite element model. This inverse procedure is formulated as the minimization of the difference between the measured and computed values of displacement at selected boundary nodes, called sensor points, using particle swarm optimization algorithm. Convex and a non-convex specimens have been considered for investigations of crack presence, and identification of its size, different crack sizes have been tested to demonstrate the efficiency of the proposed approach.

  12. Particle Swarm Transport in Fracture Networks

    Science.gov (United States)

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

    2012-12-01

    intersections were larger in width than the individual fractures, enabling the swarm to expand freely because of less confinement from the fracture walls. When swarms were released in a fracture network supporting an ambient flow rate, the ability to transport cohesive swarms through the fracture network was a function of the flow rate and swarm volume. For low ambient flow rates ( 4 μl/min, large swarms (30 μl) remained cohesive (i.e. low loss of particles) as swarms were driven through the network both in the direction of and opposite to the direction of gravity. These experiments demonstrate conditions under which colloidal-size contaminants can be driven through a fracture network. High-speed transport of cohesive swarms depends on the volume of the swarm and the ambient flow rates that provide a balance of forces that prevents significant loss of particle from the swarm or deposition of particles along the flow path. Swarms that are transported cohesively travel along a highly localized path through a fracture network. Acknowledgment: The authors wish to acknowledge support of this work by the Geosciences Research Program, Office of Basic Energy Sciences US Department of Energy (DE-FG02-09ER16022) and NSF REU program in the Physics Department at Purdue University.

  13. Estimation of the particle size distribution of colloids from multiangle dynamic light scattering measurements with particle swarm optimization

    Directory of Open Access Journals (Sweden)

    Leonardo Antonio Bermeo Varón

    2015-01-01

    Full Text Available In this paper particle Swarm Optimization (PSO algorithms are applied to estimate the particle size distribution (PSD of a colloidal system from the average PSD diameters, which are measured by multi-angle dynamic light scattering. The system is considered a nonlinear inverse problem, and for this reason the estimation procedure requires a Tikhonov regularization method. The inverse problem is solved through several PSO strategies. The evaluated PSOs are tested through three simulated examples corresponding to polysty-rene (PS latexes with different PSDs, and two experimental examples obtained by simply mixing 2 PS standards. In general, the evalu-ation results of the PSOs are excellent; and particularly, the PSO with the Trelea’s parameter set shows a better performance than other implemented PSOs.

  14. Swarm size and iteration number effects to the performance of PSO algorithm in RFID tag coverage optimization

    Science.gov (United States)

    Prathabrao, M.; Nawawi, Azli; Sidek, Noor Azizah

    2017-04-01

    Radio Frequency Identification (RFID) system has multiple benefits which can improve the operational efficiency of the organization. The advantages are the ability to record data systematically and quickly, reducing human errors and system errors, update the database automatically and efficiently. It is often more readers (reader) is needed for the installation purposes in RFID system. Thus, it makes the system more complex. As a result, RFID network planning process is needed to ensure the RFID system works perfectly. The planning process is also considered as an optimization process and power adjustment because the coordinates of each RFID reader to be determined. Therefore, algorithms inspired by the environment (Algorithm Inspired by Nature) is often used. In the study, PSO algorithm is used because it has few number of parameters, the simulation time is fast, easy to use and also very practical. However, PSO parameters must be adjusted correctly, for robust and efficient usage of PSO. Failure to do so may result in disruption of performance and results of PSO optimization of the system will be less good. To ensure the efficiency of PSO, this study will examine the effects of two parameters on the performance of PSO Algorithm in RFID tag coverage optimization. The parameters to be studied are the swarm size and iteration number. In addition to that, the study will also recommend the most optimal adjustment for both parameters that is, 200 for the no. iterations and 800 for the no. of swarms. Finally, the results of this study will enable PSO to operate more efficiently in order to optimize RFID network planning system.

  15. Drone Swarms

    Science.gov (United States)

    2017-05-25

    motion,” provides a method that combines situational awareness, elusiveness, mass, speed, mobility, and surprise to physically and cognitively overwhelm...Napoleon’s Great Army at Ulm, provide operational shock and cognitive dissonance to opposing military systems and personnel. In Swarming and the...Scythians, Alexander used similar anti-swarm methods that bottlenose dolphins use to catch swarming fish. In order to catch fish utilizing swarms

  16. Optimal Sizing of a Photovoltaic-Hydrogen Power System for HALE Aircraft by means of Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Victor M. Sanchez

    2015-01-01

    Full Text Available Over the last decade there has been a growing interest in the research of feasibility to use high altitude long endurance (HALE aircrafts in order to provide mobile communications. The use of HALEs for telecommunication networks has the potential to deliver a wide range of communication services (from high-quality voice to high-definition videos, as well as high-data-rate wireless channels cost effectively. One of the main challenges of this technology is to design its power supply system, which must provide the enough energy for long time flights in a reliable way. In this paper a photovoltaic/hydrogen system is proposed as power system for a HALE aircraft due its high power density characteristic. In order to obtain the optimal sizing for photovoltaic/hydrogen system a particle swarm optimizer (PSO is used. As a case study, theoretical design of the photovoltaic/hydrogen power system for three different HALE aircrafts located at 18° latitude is presented. At this latitude, the range of solar radiation intensity was from 310 to 450 Wh/sq·m/day. The results obtained show that the photovoltaic/hydrogen systems calculated by PSO can operate during one year with efficacies ranging between 45.82% and 47.81%. The obtained sizing result ensures that the photovoltaic/hydrogen system supplies adequate energy for HALE aircrafts.

  17. 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.

  18. Minimum Fuel Trajectory Design in Multiple Dynamical Environments Utilizing Direct Transcription Methods and Particle Swarm Optimization

    Science.gov (United States)

    2016-03-01

    direction. Also, his sense of humor in the classroom setting was always a breath of fresh air during the rigors of academics. Dr. Matthew J. Dillsaver...If the number of design variables equals the number of constraints, then the () matrix is square and invertible . By the implicit function

  19. The Bi-Directional Prediction of Carbon Fiber Production Using a Combination of Improved Particle Swarm Optimization and Support Vector Machine.

    Science.gov (United States)

    Xiao, Chuncai; Hao, Kuangrong; Ding, Yongsheng

    2014-12-30

    This paper creates a bi-directional prediction model to predict the performance of carbon fiber and the productive parameters based on a support vector machine (SVM) and improved particle swarm optimization (IPSO) algorithm (SVM-IPSO). In the SVM, it is crucial to select the parameters that have an important impact on the performance of prediction. The IPSO is proposed to optimize them, and then the SVM-IPSO model is applied to the bi-directional prediction of carbon fiber production. The predictive accuracy of SVM is mainly dependent on its parameters, and IPSO is thus exploited to seek the optimal parameters for SVM in order to improve its prediction capability. Inspired by a cell communication mechanism, we propose IPSO by incorporating information of the global best solution into the search strategy to improve exploitation, and we employ IPSO to establish the bi-directional prediction model: in the direction of the forward prediction, we consider productive parameters as input and property indexes as output; in the direction of the backward prediction, we consider property indexes as input and productive parameters as output, and in this case, the model becomes a scheme design for novel style carbon fibers. The results from a set of the experimental data show that the proposed model can outperform the radial basis function neural network (RNN), the basic particle swarm optimization (PSO) method and the hybrid approach of genetic algorithm and improved particle swarm optimization (GA-IPSO) method in most of the experiments. In other words, simulation results demonstrate the effectiveness and advantages of the SVM-IPSO model in dealing with the problem of forecasting.

  20. The Bi-Directional Prediction of Carbon Fiber Production Using a Combination of Improved Particle Swarm Optimization and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Chuncai Xiao

    2014-12-01

    Full Text Available This paper creates a bi-directional prediction model to predict the performance of carbon fiber and the productive parameters based on a support vector machine (SVM and improved particle swarm optimization (IPSO algorithm (SVM-IPSO. In the SVM, it is crucial to select the parameters that have an important impact on the performance of prediction. The IPSO is proposed to optimize them, and then the SVM-IPSO model is applied to the bi-directional prediction of carbon fiber production. The predictive accuracy of SVM is mainly dependent on its parameters, and IPSO is thus exploited to seek the optimal parameters for SVM in order to improve its prediction capability. Inspired by a cell communication mechanism, we propose IPSO by incorporating information of the global best solution into the search strategy to improve exploitation, and we employ IPSO to establish the bi-directional prediction model: in the direction of the forward prediction, we consider productive parameters as input and property indexes as output; in the direction of the backward prediction, we consider property indexes as input and productive parameters as output, and in this case, the model becomes a scheme design for novel style carbon fibers. The results from a set of the experimental data show that the proposed model can outperform the radial basis function neural network (RNN, the basic particle swarm optimization (PSO method and the hybrid approach of genetic algorithm and improved particle swarm optimization (GA-IPSO method in most of the experiments. In other words, simulation results demonstrate the effectiveness and advantages of the SVM-IPSO model in dealing with the problem of forecasting.

  1. Effect of directional selection for body size on fluctuating asymmetry ...

    Indian Academy of Sciences (India)

    Madhsudhan

    and its relationship with stress. [Vishalakshi C and Singh B N 2009 Effect of directional selection for body size on fluctuating asymmetry in certain morphological traits in. Drosophila ananassae; J. Biosci. 34 275–285]. Keywords. Body size; directional selection; Drosophila ananassae; fluctuating asymmetry; hybridisation; ...

  2. Swarming behavior in plant roots.

    Directory of Open Access Journals (Sweden)

    Marzena Ciszak

    Full Text Available Interactions between individuals that are guided by simple rules can generate swarming behavior. Swarming behavior has been observed in many groups of organisms, including humans, and recent research has revealed that plants also demonstrate social behavior based on mutual interaction with other individuals. However, this behavior has not previously been analyzed in the context of swarming. Here, we show that roots can be influenced by their neighbors to induce a tendency to align the directions of their growth. In the apparently noisy patterns formed by growing roots, episodic alignments are observed as the roots grow close to each other. These events are incompatible with the statistics of purely random growth. We present experimental results and a theoretical model that describes the growth of maize roots in terms of swarming.

  3. Transport of Particle Swarms Through Fractures

    Science.gov (United States)

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

    2011-12-01

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

  4. Swarm robotics and minimalism

    Science.gov (United States)

    Sharkey, Amanda J. C.

    2007-09-01

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

  5. The Study of Fuzzy Proportional Integral Controllers Based on Improved Particle Swarm Optimization for Permanent Magnet Direct Drive Wind Turbine Converters

    Directory of Open Access Journals (Sweden)

    Yancai Xiao

    2016-05-01

    Full Text Available In order to meet the requirements of high precision and fast response of permanent magnet direct drive (PMDD wind turbines, this paper proposes a fuzzy proportional integral (PI controller associated with a new control strategy for wind turbine converters. The purpose of the control strategy is to achieve the global optimization for the quantization factors, ke and kec, and scale factors, kup and kui, of the fuzzy PI controller by an improved particle swarm optimization (PSO method. Thus the advantages of the rapidity of the improved PSO and the robustness of the fuzzy controller can be fully applied in the control process. By conducting simulations for 2 MW PMDD wind turbines with Matlab/Simulink, the performance of the fuzzy PI controller based on the improved PSO is demonstrated to be obviously better than that of the PI controller or the fuzzy PI controller without using the improved PSO under the situation when the wind speed changes suddenly.

  6. 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)....

  7. P-adic valued models of swarm behaviour

    Science.gov (United States)

    Schumann, Andrew

    2017-07-01

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

  8. Direct and indirect haptic calibration of visual size judgments.

    Directory of Open Access Journals (Sweden)

    Monica Gori

    Full Text Available It has long been suspected that touch plays a fundamental role in the calibration of visual perception, and much recent evidence supports this idea. However, as the haptic exploration workspace is limited by the kinematics of the body, the contribution of haptic information to the calibration process should occur only within the region of the haptic workspace reachable by a limb (peripersonal space. To test this hypothesis we evaluated visual size perception and showed that it is indeed more accurate inside the peripersonal space. We then show that allowing subjects to touch the (unseen stimulus after observation restores accurate size perception; the accuracy persists for some time, implying that calibration has occurred. Finally, we show that observing an actor grasp the object also produces accurate (and lasting size perception, suggesting that the calibration can also occur indirectly by observing goal-directed actions, implicating the involvement of the "mirror system".

  9. Swarm Intelligence Optimization and Its Applications

    Science.gov (United States)

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

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

  10. Optimisasi Koordinasi Directional Over Current Relay (DOCR pada Sistem Distribusi Mesh Menggunakan Modified Adaptive Particle Swarm Optimization (MAPSO dengan Pembangkit Tersebar

    Directory of Open Access Journals (Sweden)

    Aditya Descara Putra

    2017-01-01

    Full Text Available Pemilihan topologi jaringan distribusi mesh merupakan salah satu hal yang sangat penting dalam penyaluran sistem tenaga listrik. Apabila terjadi gangguan pada suatu saluran maka saluran yang lain dapat menggantikan untuk penyalurkan daya listrik. Akibat adanya gangguan dari suatu saluran diperlukan koordinasi proteksi yang baik pada sistem mesh. Di samping itu,  dengan adanya injeksi dari distributed generator pada sistem distribusi mesh, koordinasi proteksi yang dilakukan harus mempertimbangkan nilai arus gangguan dan arah arus gangguan. Arah arus gangguan harus diperhitungkan ,baik dalam arah forward maupun reverse. Dari permasalahan tersebut diperlukan sebuah metode penyelesaian untuk mengurangi kompleksitas koordinasi proteksi pada sistem mesh. Dalam hal ini algoritma Modified Adaptive Particle Swarm Optimization (MAPSO digunakan sebagai metode optimasi untuk  mengurangi kompleksitas dari perhitungan koordinasi proteksi pada sistem distribusi mesh. Algoritma MAPSO digunakan dalam optimasi koordinasi antar Directional Over Current Relay (DOCR. Parameter yang dioptimasi adalah TDS (Time Dial Setting dan waktu kerja rele. Nilai rata-rata waktu kerja rele primer dengan Algoritma MAPSO adalah 0,262 detik.

  11. Synchronized rotation in swarms of magnetotactic bacteria

    Science.gov (United States)

    Belovs, M.; Livanovičs, R.; CÄ`bers, A.

    2017-10-01

    Self-organizing behavior has been widely reported in both natural and artificial systems, typically distinguishing between temporal organization (synchronization) and spatial organization (swarming). Swarming has been experimentally observed in systems of magnetotactic bacteria under the action of external magnetic fields. Here we present a model of ensembles of magnetotactic bacteria in which hydrodynamic interactions lead to temporal synchronization in addition to the swarming. After a period of stabilization during which the bacteria form a quasiregular hexagonal lattice structure, the entire swarm begins to rotate in a direction opposite to the direction of the rotation of the magnetic field. We thus illustrate an emergent mechanism of macroscopic motion arising from the synchronized microscopic rotations of hydrodynamically interacting bacteria, reminiscent of the recently proposed concept of swarmalators.

  12. Sizing an isolated wind-solar-fuel cell generation system based on the particle swarm optimization method; Dimensionamiento de un sistema de generacion aislado eolico-solar-celda de combustible basado en el metodo de optimizacion de enjambre de particulas

    Energy Technology Data Exchange (ETDEWEB)

    Sanchez-Huerta, V; Ramirez-Arredondo, Juan M. [Universidad de Quintana Roo, Chetumal, Quintana Roo (Mexico)]. E-mail: vsanchez@gdl.cinvestav.mx; Arriaga-Hurtado, L. G. [CIDETEQ, Queretaro (Mexico)

    2009-09-15

    Sizing an electric energy system requires an analysis of investment, maintenance and operating costs. In the case of a generation system that uses renewable sources, optimal capacity becomes more complex compared to a conventional system, because of the randomness of renewable resources (wind, solar) and the still high costs of wind and photovoltage generator modules. This work presents the optimal sizing of a wind-solar-fuel cell generation system, minimizing the costs of the system while satisfying the energy demands of an isolated charge. The optimization method used is based on an evolutionary programming technique known as particle swarms (PSO-particle swarm optimization). The generation of energy with a hybrid system is discussed, based on the profile of insolation and wind availability at the site, with the objective of satisfying a specific electric demand. [Spanish] El dimensionamiento de un sistema de generacion de energia electrica requiere un analisis de los costos de inversion, mantenimiento y operacion. En el caso de un sistema de generacion que utiliza fuentes renovables la capacidad optima resulta mas compleja con respecto a un sistema convencional, debido a la aleatoriedad de los recursos renovables (eolico, solar), y a los aun altos costos de generadores eolicos y modulos fotovoltaicos. En este trabajo se presenta el dimensionamiento optimo de un sistema de generacion eolico-solar-celda de combustible minimizando los costos del sistema que satisfaga la energia demandada por una carga aislada. El metodo de optimizacion utilizado esta basado en una tecnica de programacion evolutiva conocida como enjambre de particulas (PSO por sus siglas en ingles: particle swarm optimization). Se plantea la generacion de energia del sistema hibrido con base a la insolacion y el perfil del viento disponible en sitio, con objeto de satisfacer una demanda electrica determinada.

  13. 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.

  14. 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.

  15. The size and direction of saccadic curvatures during reading.

    Science.gov (United States)

    Inhoff, Albrecht W; Seymour, Bradley A; Schad, Daniel; Greenberg, Seth

    2010-06-11

    Eye movements during the reading of multi-line pages of texts were analyzed to determine the trajectory of reading saccades. The results of two experiments showed that the trajectory of the majority of forward-directed saccades was negatively biased, i.e., the trajectory fell below the start and end location of the saccadic movement. This is attributed to a global top-to-bottom orienting of attention. The curvature size and the proportion of negative trajectories were diminished when linguistic processing demands were high and when the beginning lines of a page were read. Longer pre-saccadic fixations also yielded smaller saccadic curvatures, and they resulted in fewer negatively curved forward-directed saccades in Experiment 1 although not in Experiment 2. These findings indicate that the top-to-bottom pull of saccadic trajectories is modulated by processing demands and processing opportunities. The results are in general agreement with a time-locked attraction-inhibition hypothesis, according to which the horizontal movement component of a saccade is initially subject to an automatic top-to-bottom orienting of attention that is subsequently inhibited. Copyright 2010 Elsevier Ltd. All rights reserved.

  16. 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.

  17. Swarming UAS II

    Science.gov (United States)

    2010-05-05

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

  18. 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.

  19. 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...

  20. Collective motion of a class of social foraging swarms

    Energy Technology Data Exchange (ETDEWEB)

    Liu Bo [Intelligent Control Laboratory, Center for Systems and Control, Department of Industrial Engineering and Management, College of Engineering, Peking University, Beijing 100871 (China)], E-mail: boliu@mech.pku.edu.cn; Chu Tianguang [Intelligent Control Laboratory, Center for Systems and Control, Department of Industrial Engineering and Management, College of Engineering, Peking University, Beijing 100871 (China)], E-mail: chutg@pku.edu.cn; Wang Long; Wang Zhanfeng [Intelligent Control Laboratory, Center for Systems and Control, Department of Industrial Engineering and Management, College of Engineering, Peking University, Beijing 100871 (China)

    2008-10-15

    This paper considers a class of social foraging swarms with a nutrient profile (or an attractant/repellent) and an attraction-repulsion coupling function, which is chosen to guarantee collision avoidance between individuals. The paper also studies non-identical interaction ability or efficiency among different swarm individuals for different profiles. The swarm behavior is a result of a balance between inter-individual interplays as well as the interplays of the swarm individuals (agents) with their environment. It is proved that the individuals of a quasi-reciprocal swarm will aggregate and eventually form a cohesive cluster of finite size for different profiles. It is also shown that the swarm system is completely stable, that is, every solution converges to the set of equilibrium points of the system. Moreover, all the swarm individuals will converge to more favorable areas of the profile under certain conditions. For general non-reciprocal swarms, numerical simulations show that more complex self-organized rotation may occur in the swarms.

  1. 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...

  2. 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.

  3. A novel particle swarm optimization based on population category

    Science.gov (United States)

    Wang, Jingying; Qu, Jianhua

    2017-10-01

    This paper raised a novel particle swarm optimization algorithm based on population category. Traditional particle swarm optimization algorithm is easily to trap in local optimum. In order to avoid standard algorithm appearing premature convergence, this novel algorithm use population category strategy to find new directions for particles. At last, computational results show that the new method is effective and has a high-performance.

  4. New paleomagnetic results on 2367 Ma Dharwar giant dyke swarm ...

    Indian Academy of Sciences (India)

    N Ramesh Babu

    2018-02-14

    Feb 14, 2018 ... 2012). This direction is considered as primary magnetization of 2082 Ma radiating dyke swarm of. EDC (Kumar et al. 2015). Hence, we infer here that the source for component (B) is possibly the recently reported 2080 Ma spectacular radiating dyke swarm, which radiates beneath the Cudda- pah basin with ...

  5. 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

  6. Hybridization hotspots at bat swarming sites.

    Directory of Open Access Journals (Sweden)

    Wiesław Bogdanowicz

    Full Text Available During late summer and early autumn in temperate zones of the Northern Hemisphere, thousands of bats gather at caves, mainly for the purpose of mating. We demonstrated that this swarming behavior most probably leads not only to breeding among bats of the same species but also interbreeding between different species. Using 14 nuclear microsatellites and three different methods (the Bayesian assignment approaches of STRUCTURE and NEWHYBRIDS and a principal coordinate analysis of pairwise genetic distances, we analyzed 375 individuals belonging to three species of whiskered bats (genus Myotis at swarming sites across their sympatric range in southern Poland. The overall hybridization rate varied from 3.2 to 7.2%. At the species level, depending on the method used, these values ranged from 2.1-4.6% in M. mystacinus and 3.0-3.7% in M. brandtii to 6.5-30.4% in M. alcathoe. Hybrids occurred in about half of the caves we studied. In all three species, the sex ratio of hybrids was biased towards males but the observed differences did not differ statistically from those noted at the population level. In our opinion, factors leading to the formation of these admixed individuals and their relatively high frequency are: i swarming behaviour at swarming sites, where high numbers of bats belonging to several species meet; ii male-biased sex ratio during the swarming period; iii the fact that all these bats are generally polygynous. The highly different population sizes of different species at swarming sites may also play some role. Swarming sites may represent unique hybrid hotspots, which, as there are at least 2,000 caves in the Polish Carpathians alone, may occur on a massive scale not previously observed for any group of mammal species in the wild. Evidently, these sites should be treated as focal points for the conservation of biodiversity and evolutionary processes.

  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 of ...... of an extremely accurate and stable vector magnetometer, which is co-mounted in an optical bench together with a start tracker system to ensure mechanical stability of the measurements....

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

    Science.gov (United States)

    Sinhuber, Michael; Ouellette, Nicholas T.

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

  9. Transport of Particle Swarms Through Variable Aperture Fractures

    Science.gov (United States)

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

    2012-12-01

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

  10. 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

  11. Xarxa social (Swarm)

    OpenAIRE

    Capdevila Piro, Antonio

    2012-01-01

    Aquesta memòria presenta les línies generals que s'han seguit per tal d'implementar una aplicació anomenada SWARM. En aquest document es recullen les bases del nostre projecte utilitzant el llenguatge de programació C# i fent servir altres eines i frameworks per les diferents capes de què consta el projecte, com poden ser Silverlight o WCF. Esta memoria presenta las líneas generales que se han seguido para implementar una aplicación llamada SWARM. En este documento se recogen las bases de ...

  12. 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.

  13. Instantaneous movement of krill swarms in the Antarctic Circumpolar Current

    OpenAIRE

    Tarling, Geraint A.; Thorpe, Sally E.

    2014-01-01

    Antarctic krill are known to have strong swimming capabilities, but direct observations of the speed and direction of krill-swarm movement within their natural environment are rare. We identified and examined 4060 swarms within the main flow of the Antarctic Circumpolar Current (Scotia Sea) using a combination of an EK60 echosounder, a 153.6 kHz acoustic Doppler current profiler, and ground-truthing nets. Net displacement magnitude (m) and net angle of deviation (d) were determined by vector ...

  14. Persistent directional selection on body size and a resolution to the paradox of stasis.

    Science.gov (United States)

    Rollinson, Njal; Rowe, Locke

    2015-09-01

    Directional selection on size is common but often fails to result in microevolution in the wild. Similarly, macroevolutionary rates in size are low relative to the observed strength of selection in nature. We show that many estimates of selection on size have been measured on juveniles, not adults. Further, parents influence juvenile size by adjusting investment per offspring. In light of these observations, we help resolve this paradox by suggesting that the observed upward selection on size is balanced by selection against investment per offspring, resulting in little or no net selection gradient on size. We find that trade-offs between fecundity and juvenile size are common, consistent with the notion of selection against investment per offspring. We also find that median directional selection on size is positive for juveniles but no net directional selection exists for adult size. This is expected because parent-offspring conflict exists over size, and juvenile size is more strongly affected by investment per offspring than adult size. These findings provide qualitative support for the hypothesis that upward selection on size is balanced by selection against investment per offspring, where parent-offspring conflict over size is embodied in the opposing signs of the two selection gradients. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

  15. Social interactions in myxobacterial swarming.

    Directory of Open Access Journals (Sweden)

    Yilin Wu

    2007-12-01

    Full Text Available Swarming, a collective motion of many thousands of cells, produces colonies that rapidly spread over surfaces. In this paper, we introduce a cell-based model to study how interactions between neighboring cells facilitate swarming. We chose to study Myxococcus xanthus, a species of myxobacteria, because it swarms rapidly and has well-defined cell-cell interactions mediated by type IV pili and by slime trails. The aim of this paper is to test whether the cell contact interactions, which are inherent in pili-based S motility and slime-based A motility, are sufficient to explain the observed expansion of wild-type swarms. The simulations yield a constant rate of swarm expansion, which has been observed experimentally. Also, the model is able to quantify the contributions of S motility and A motility to swarming. Some pathogenic bacteria spread over infected tissue by swarming. The model described here may shed some light on their colonization process.

  16. An apparatus to measure electrical charge of bubble swarms.

    Science.gov (United States)

    Uddin, S; Jin, L; Mirnezami, M; Finch, J A

    2013-01-01

    An apparatus has been developed to characterize bubble charge by measuring the swarm potential of gas bubbles. The technique allows in-process measurement of all system variables associated with bubble surface electrical charge: swarm potential, solution conductivity, gas holdup, pH and bubble size distribution. The method was validated by comparing with literature iso-electric point (iep) values. Bubble swarm potential was measured as a function of concentration and pH for a series of non-ionic surfactant frothers, ionic surfactant collectors and multivalent metal ions. Results showed good agreement with established theory and prior experimental findings. The setup is a step towards measurement of charge on flotation size range of bubble swarms. Copyright © 2012 Elsevier Inc. All rights reserved.

  17. Direct and Indirect Evidence of Size-Selective Grazing on Pelagic Bacteria by Freshwater Nanoflagellates

    OpenAIRE

    Šimek, Karel; Chrzanowski, Thomas H.

    1992-01-01

    Size-selective grazing of three heterotrophic nanoflagellates (with cell sizes of 21, 44, and 66 μm3) isolated from Lake Arlington, Texas was examined by using a natural mixture of fluorescence labelled lake bacteria. Sizes of ingested bacteria in food vacuoles were directly measured. Larger bacterial cells were ingested at a frequency much higher than that at which they occurred in the assemblage, indicating preferential flagellate grazing on the larger size classes within the lake bacteriop...

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

    Science.gov (United States)

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

    2014-12-01

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

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

    Science.gov (United States)

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

    2011-12-01

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

  20. 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.

  1. 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.

  2. 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.

  3. Particle swarm inspired optimization algorithm without velocity equation

    Directory of Open Access Journals (Sweden)

    Mahmoud Mostafa El-Sherbiny

    2011-03-01

    Full Text Available This paper introduces Particle Swarm Without Velocity equation optimization algorithm (PSWV that significantly reduces the number of iterations required to reach good solutions for optimization problems. PSWV algorithm uses a set of particles as in particle swarm optimization algorithm but a different mechanism for finding the next position for each particle is used in order to reach a good solution in a minimum number of iterations. In PSWV algorithm, the new position of each particle is determined directly from the result of linear combination between its own best position and the swarm best position without using velocity equation. The results of PSWV algorithm and the results of different variations of particle swarm optimizer are experimentally compared. The performance of PSWV algorithm and the solution quality prove that PSWV is highly competitive and can be considered as a viable alternative to solve optimization problems.

  4. 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

    2014-01-01

    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.

  5. Pupil size directly modulates the feedforward response in human primary visual cortex independently of attention.

    Science.gov (United States)

    Bombeke, Klaas; Duthoo, Wout; Mueller, Sven C; Hopf, Jens-Max; Boehler, C Nico

    2016-02-15

    Controversy revolves around the question of whether psychological factors like attention and emotion can influence the initial feedforward response in primary visual cortex (V1). Although traditionally, the electrophysiological correlate of this response in humans (the C1 component) has been found to be unaltered by psychological influences, a number of recent studies have described attentional and emotional modulations. Yet, research into psychological effects on the feedforward V1 response has neglected possible direct contributions of concomitant pupil-size modulations, which are known to also occur under various conditions of attentional load and emotional state. Here we tested the hypothesis that such pupil-size differences themselves directly affect the feedforward V1 response. We report data from two complementary experiments, in which we used procedures that modulate pupil size without differences in attentional load or emotion while simultaneously recording pupil-size and EEG data. Our results confirm that pupil size indeed directly influences the feedforward V1 response, showing an inverse relationship between pupil size and early V1 activity. While it is unclear in how far this effect represents a functionally-relevant adaptation, it identifies pupil-size differences as an important modulating factor of the feedforward response of V1 and could hence represent a confounding variable in research investigating the neural influence of psychological factors on early visual processing. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. 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.

  7. Subduction megathrust segmentation correlated with earthquake swarm locations appears to be caused by increased stress heterogeneity

    Science.gov (United States)

    Holtkamp, S.; Brudzinski, M. R.

    2011-12-01

    For each Mw≥8.5 earthquake with a publicly available finite fault rupture model, we find slip is closely bounded along-strike by earthquake swarms, either prior or subsequent. These earthquake swarms tend to have much larger spatial extents than their cumulative moment would suggest, arguing against a static stress triggering mechanism. In Japan, Chile, Sumatra, and Alaska, earthquake swarms correlate with regions of the plate interface that exhibit low interseismic strain accumulation. This low fault coupling could be a result of aseismic slip during swarms or stress heterogeneity that leads to both swarm occurrence and great earthquake termination. Geodetic studies of earthquake swarms are limited but show several cases with no evidence for aseismic slip during swarms. Moreover, the 1964 Alaska and 2010 Maule earthquakes ruptured through regions with lower coupling than where they terminated, arguing that a factor other than small pre-stress controls where large earthquakes terminate. Large variations in coupling over small spatial scales could produce a fragmented set of small asperities conducive for generating a swarm of smaller earthquakes (Figure). Great earthquakes would be unlikely to rupture through that region as homogeneity of fault zone properties seems to be conducive for generating the largest megathrust earthquakes. Earthquake swarms are one of the better proxies for along-strike segmentation of subduction megathrusts, thereby potentially providing an new method for finding margins with the potential for devastating Mw~9 scale earthquakes. Figure: Cartoon illustrating our preferred hypothesis that increased stress heterogeneity causes earthquake swarm activity and stops large earthquake rupture propagation. Stress on the fault is in grayscale with black being high fault pre-stress. In this model, the heterogeneous stress distribution fosters swarm activity by limiting the size to which an earthquake can grow (leading to a high b

  8. Differences in Rate and Direction of Shifts between Phytoplankton Size Structure and Sea Surface Temperature

    Directory of Open Access Journals (Sweden)

    Hisatomo Waga

    2017-03-01

    Full Text Available Species distributions are changing with various rates and directions in response to recent global warming. The velocity of sea surface temperature (SST has been used to predict species migration and persistence as an expectation of how species track their thermal niches; however, several studies have found that evidence for species shifts has deviated from the velocity of SST. This study investigated whether estimation of the velocity of shifts in phytoplankton size structure using remote sensing data could contribute to better prediction of species shifts. A chlorophyll-a (Chla size distribution (CSD model was developed by quantifying the relationships between the size structure of the phytoplankton community and the spectral features of the phytoplankton absorption coefficient (aph(λ, based on the principal component analysis approach. Model validation demonstrated that the exponent of CSD (hereafter, CSD slope, which can describe the synoptic size structure of a phytoplankton community, was derived successfully with a relative root mean square error of 18.5%. The median velocity of CSD slope across the ocean was 485.2 km·decade−1, broadly similar to Chla (531.5 km·decade−1. These values were twice the velocity of SST, and the directions of shifts in CSD slope and Chla were quite different from that of SST. Because Chla is generally covariant with the size structure of a phytoplankton community, we believe that spatiotemporal changes in Chla can explain the variations of phytoplankton size structure. Obvious differences in both rate and direction of shifts were found between the phytoplankton size structure and SST, implying that shifts of phytoplankton size structure could be a powerful tool for assessing the distributional shifts of marine species. Our results will contribute to generate global and regional maps of expected species shifts in response to environmental forcing.

  9. Steering Micro-Robotic Swarm by Dynamic Actuating Fields

    NARCIS (Netherlands)

    Chao, Q.; Yu, J; Dai, C.; Xu, T; Zhang, L.; Wang, C.C.; Jin, X.

    2016-01-01

    We present a general solution for steering microrobotic
    swarm by dynamic actuating fields. In our approach, the
    motion of micro-robots is controlled by changing the actuating
    direction of a field applied to them. The time-series sequence
    of actuating field’s directions can be

  10. Favouring Small and Medium Sized Enterprises with Directive 2014/24/EU

    DEFF Research Database (Denmark)

    Trybus, Martin; Andrecka, Marta

    2017-01-01

    This article argues that the four main measures introduced in the 2014 reform of the Procurement Directives to promote Small andMediumSized Enterprises (SMEs) cannot be classified as measures favouring SMEs. A measure favours SMEs when it compromises the main objectives of competition, non...

  11. Estimation of direct response to truncation selection of litter size in ...

    African Journals Online (AJOL)

    Estimation of direct response to truncation selection of litter size in largewhite flock of swine in MidWestern Nigeria. ... Correlation coefficient among the traits was low and not significant with reproduction (FRINT) and LITSZ being negatively correlated. LITSZ, WWT and FRINT showed positive response to selection while ...

  12. Direct measurement of the matched spot size in a slow capillary discharge optical waveguide.

    Science.gov (United States)

    Antsiferov, Pavel S; Akdim, Mohamed R; van Dam, Herman T

    2007-12-01

    This communication presents direct method for experimental determining the matched spot size in a plasma optical waveguide, created in a slow capillary discharge. It can be used for Laser Wakefield Acceleration experiments in addition to interferometry for fast control of optical properties of discharge plasma. The measurements are done by means of the comparison of the laser beam size at the entrance and at the exit of the plasma channel. They are direct in the sense that the interpretation is made in terms of the refractive index without usage of the information about electron density distribution. The method can be used for matched spot size measurement in conditions of the nonlinear effects (transmission of high power laser pulses).

  13. Direct Online Determination of Laser-Induced Particle Size Distribution by ICPMS.

    Science.gov (United States)

    Donard, Ariane; Claverie, Fanny; Pointurier, Fabien; Blitz Frayret, Céline; Svatosova, Barbora; Pécheyran, Christophe

    2017-09-05

    The characterization of the aerosol (size, composition, and concentration) generated by Laser Ablation is of great interest due to its impact on the analytical performances when coupled to Inductively Coupled Plasma Mass Spectrometry (ICPMS). The capabilities of High Resolution ICPMS as a direct tool to characterize nanoparticles produced by femtosecond Laser Ablation of pure copper are presented. An analytical protocol, similar to the "single particle ICPMS" technique used to characterize the size distribution of nanoparticles in solution, was developed in order to observe the signals of individual particles produced by a single ablation shot. A Visual Basic for Applications (VBA) data processing was developed to count and sort the particles as a function of their size and thus determine the particle size distribution. To check the reliability of the method, the results were compared to a more conventional technique, namely, Electrical Low Pressure Impaction (ELPI) for 4000 shots. Detection limit for the particles produced by the laser ablation of a copper foil is of a few attograms corresponding to a nanoparticle of 14 nm. The direct online determination of particle size by ICPMS gave similar results than ELPI for copper particles ejected during the ablation shot by shot at a fixed spot, from 1 to 100 shots. Particles larger than 159 nm represented less than 1% of the aerosol whose distribution was centered on 25-51 nm.

  14. 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.

  15. Predation on rose galls: parasitoids and predators determine gall size through directional selection.

    Directory of Open Access Journals (Sweden)

    Zoltán László

    Full Text Available Both predators and parasitoids can have significant effects on species' life history traits, such as longevity or clutch size. In the case of gall inducers, sporadically there is evidence to suggest that both vertebrate predation and insect parasitoid attack may shape the optimal gall size. While the effects of parasitoids have been studied in detail, the influence of vertebrate predation is less well-investigated. To better understand this aspect of gall size evolution, we studied vertebrate predation on galls of Diplolepis rosae on rose (Rosa canina shrubs. We measured predation frequency, predation incidence, and predation rate in a large-scale observational field study, as well as an experimental field study. Our combined results suggest that, similarly to parasitoids, vertebrate predation makes a considerable contribution to mortality of gall inducer larvae. On the other hand, its influence on gall size is in direct contrast to the effect of parasitoids, as frequency of vertebrate predation increases with gall size. This suggests that the balance between predation and parasitoid attack shapes the optimal size of D. rosae galls.

  16. miR-11 regulates pupal size of Drosophila melanogaster via directly targeting Ras85D.

    Science.gov (United States)

    Li, Yao; Li, Shengjie; Jin, Ping; Chen, Liming; Ma, Fei

    2017-01-01

    MicroRNAs play diverse roles in various physiological processes during Drosophila development. In the present study, we reported that miR-11 regulates pupal size during Drosophila metamorphosis via targeting Ras85D with the following evidences: pupal size was increased in the miR-11 deletion mutant; restoration of miR-11 in the miR-11 deletion mutant rescued the increased pupal size phenotype observed in the miR-11 deletion mutant; ectopic expression of miR-11 in brain insulin-producing cells (IPCs) and whole body shows consistent alteration of pupal size; Dilps and Ras85D expressions were negatively regulated by miR-11 in vivo; miR-11 targets Ras85D through directly binding to Ras85D 3'-untranslated region in vitro; removal of one copy of Ras85D in the miR-11 deletion mutant rescued the increased pupal size phenotype observed in the miR-11 deletion mutant. Thus, our current work provides a novel mechanism of pupal size determination by microRNAs during Drosophila melanogaster metamorphosis. Copyright © 2017 the American Physiological Society.

  17. Cavern/Vault Disposal Concepts and Thermal Calculations for Direct Disposal of 37-PWR Size DPCs

    Energy Technology Data Exchange (ETDEWEB)

    Hardin, Ernest [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Hadgu, Teklu [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Clayton, Daniel James [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

    2015-03-01

    This report provides two sets of calculations not presented in previous reports on the technical feasibility of spent nuclear fuel (SNF) disposal directly in dual-purpose canisters (DPCs): 1) thermal calculations for reference disposal concepts using larger 37-PWR size DPC-based waste packages, and 2) analysis and thermal calculations for underground vault-type storage and eventual disposal of DPCs. The reader is referred to the earlier reports (Hardin et al. 2011, 2012, 2013; Hardin and Voegele 2013) for contextual information on DPC direct disposal alternatives.

  18. 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.

  19. Swarm, genetic and evolutionary programming algorithms applied to multiuser detection

    Directory of Open Access Journals (Sweden)

    Paul Jean Etienne Jeszensky

    2005-02-01

    Full Text Available In this paper, the particles swarm optimization technique, recently published in the literature, and applied to Direct Sequence/Code Division Multiple Access systems (DS/CDMA with multiuser detection (MuD is analyzed, evaluated and compared. The Swarm algorithm efficiency when applied to the DS-CDMA multiuser detection (Swarm-MuD is compared through the tradeoff performance versus computational complexity, being the complexity expressed in terms of the number of necessary operations in order to reach the performance obtained through the optimum detector or the Maximum Likelihood detector (ML. The comparison is accomplished among the genetic algorithm, evolutionary programming with cloning and Swarm algorithm under the same simulation basis. Additionally, it is proposed an heuristics-MuD complexity analysis through the number of computational operations. Finally, an analysis is carried out for the input parameters of the Swarm algorithm in the attempt to find the optimum parameters (or almost-optimum for the algorithm applied to the MuD problem.

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

    Science.gov (United States)

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

    2017-01-01

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

  1. Dynamic scaling in natural swarms

    Science.gov (United States)

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

    2017-09-01

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

  2. Camera Network Coverage Improving by Particle Swarm Optimization

    NARCIS (Netherlands)

    Xu, Y.C.; Lei, B.; Hendriks, E.A.

    2011-01-01

    This paper studies how to improve the field of view (FOV) coverage of a camera network. We focus on a special but practical scenario where the cameras are randomly scattered in a wide area and each camera may adjust its orientation but cannot move in any direction. We propose a particle swarm

  3. 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...

  4. Concurrent directional adaptation of reactive saccades and hand movements to target displacements of different size.

    Science.gov (United States)

    Borisova, Steliana; Bock, Otmar; Grigorova, Valentina

    2014-01-01

    When eye and hand movements are concurrently aimed at double-step targets that call for equal and opposite changes of response direction (-10° for the eyes, +10° for the hand), adaptive recalibration of both motor systems is strongly attenuated; instead, hand but not eye movements are changed by corrective strategies (V. Grigorova et al., 2013a). The authors introduce a complementary paradigm, where double-step targets call for a -10° change of eye and a -30° change for hand movements. If compared to control subjects adapting only the eyes or only the hand, adaptive improvements were comparable for the eyes but were twice as large for the hand; in contrast, eye and hand aftereffects were comparable to those in control subjects. The authors concluded that concurrent exposure of eyes and hand to steps of the same direction but different size facilitated hand strategies, but didn't affect recalibration. This finding together with previous one (V. Grigorova et al., 2013a), suggests that concurrent adaptation of eyes and hand reveals different mechanisms of recalibration for step sign and step size, which are shared by reactive saccades and hand movements. However, hand mostly benefits from strategies provoked by the difference in target step sign and size.

  5. 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.

  6. Particle Swarm Optimization with Double Learning Patterns

    Directory of Open Access Journals (Sweden)

    Yuanxia Shen

    2016-01-01

    Full Text Available 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.

  7. UAV Swarm Operational Risk Assessment System

    Science.gov (United States)

    2015-09-01

    distribution is unlimited UAV SWARM OPERATIONAL RISK ASSESSMENT SYSTEM by Team CQ Alpha Cohort 311-141A September 2015 Project Advisors: Gregory......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

  8. DIRECT AND INDIRECT ESTIMATES OF NEIGHBORHOOD AND EFFECTIVE POPULATION SIZE IN A TROPICAL PALM, ASTROCARYUM MEXICANUM.

    Science.gov (United States)

    Eguiarte, Luis E; Búrquez, Alberto; Rodríguez, Jorge; Martínez-Ramos, Miguel; Sarukhán, José; Pinero, Daniel

    1993-02-01

    To estimate the relative importance of genetic drift, the effective population size ∗∗∗(Ne ) can be used. Here we present estimates of the effective population size and related measures in Astrocaryum mexicanum, a tropical palm from Los Tuxtlas rain forest, Veracruz, Mexico. Seed and pollen dispersal were measured. Seeds are primarily dispersed by gravity and secondarily dispersed by small mammals. Mean primary and secondary dispersal distances for seeds were found to be small (0.78 m and 2.35 m, respectively). A. mexicanum is beetle pollinated and pollen movements were measured by different methods: a) using fluorescent dyes, b) as the minimum distance between active female and male inflorescences, and c) using rare allozyme alleles as genetic markers. All three estimates of pollen dispersal were similar, with a mean of approximately 20 m. Using the seed and pollen dispersal data, the genetic neighborhood area (A) was estimated to be 2,551 m(2) . To obtain the effective population size, three different overlapping generation methods were used to estimate an effective density with demographic data from six permanent plots. The effective density ranged from 0.040 to 0.351 individuals per m(2) . The product of effective density and neighborhood area yields a direct estimate of the neighborhood effective population size (Nb ). Nb ranged from 102 to 895 individuals. Indirect estimates of population size and migration rate (Nm) were obtained using Fst for five different allozymic loci for both adults and seeds. We obtained a range of Nm from 1.2 to 19.7 in adults and a range of Nm from 4.0 to 82.6 for seeds. We discuss possible causes of the smaller indirect estimates of Nm relative to the direct and compare our estimates with values from other plant populations. Gene dispersal distances, neighborhood size, and effective population size in A. mexicanum are relatively high, suggesting that natural selection, rather than genetic drift, may play a dominant role in

  9. Steering Micro-Robotic Swarm by Dynamic Actuating Fields

    OpenAIRE

    Chao, Q.; Yu, J.; Dai, C; Xu, T.; Zhang, L.; Wang, C. C.; Jin, X.

    2016-01-01

    We present a general solution for steering microroboticswarm by dynamic actuating fields. In our approach, themotion of micro-robots is controlled by changing the actuatingdirection of a field applied to them. The time-series sequenceof actuating field’s directions can be computed automatically.Given a target position in the domain of swarm, a governingfield is first constructed to provide optimal moving directions atevery points. Following these directions, a robot can be drivento the target...

  10. Direct measurements of the axial displacement and evolving size of optically trapped aerosol droplets

    Science.gov (United States)

    Knox, K. J.; Reid, J. P.; Hanford, K. L.; Hudson, A. J.; Mitchem, L.

    2007-08-01

    The axial displacement of optically tweezed liquid aerosol droplets has been studied directly through the application of side imaging at 90° to the trapping laser beam. In conjunction with imaging in the plane of the optical trap and cavity-enhanced Raman spectroscopy (CERS), the optical forces experienced by a trapped aerosol have been interrogated. By varying the power of the trapping laser and observing changes in the axial position of a trapped particle it has been possible to examine the fine balance between the gradient and scattering forces, a key parameter in optical manipulation. Clear differences observed in sizing trapped particles from bright field microscopy and CERS have been reconciled. As a consequence, a novel technique for probing the evolving size of a single aerosol particle is proposed.

  11. 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...... 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....

  12. System-size independence of directed flow at the RelativisticHeavy-Ion Collider

    Energy Technology Data Exchange (ETDEWEB)

    STAR Coll

    2008-09-20

    We measure directed flow (v{sub 1}) for charged particles in Au + Au and Cu + Cu collisions at {radical}s{sub NN} = 200 GeV and 62.4 GeV, as a function of pseudorapidity ({eta}), transverse momentum (p{sub t}) and collision centrality, based on data from the STAR experiment. We find that the directed flow depends on the incident energy but, contrary to all available model implementations, not on the size of the colliding system at a given centrality. We extend the validity of the limiting fragmentation concept to v{sub 1} in different collision systems, and investigate possible explanations for the observed sign change in v{sub 1}(p{sub t}).

  13. Wood surface roughness: an impact of wood species, grain direction and grit size

    Directory of Open Access Journals (Sweden)

    Justina Vitosytė

    2015-06-01

    Full Text Available For the research the samples of ash (Fraxinus excelsior L., birch (Betula L., black alder (Alnus glutinosa L., Scots pine (Pinus Sylvestris L. and spruce (Picea abies L. wood were used with dimensions of 270×215×15 mm. All wood samples were tangentially planed, defect free and kiln dried. Before the research, the average moisture content, wood density, number of annual rings per 1 cm, average width of annual ring and wood surface grain direction were evaluated. Different wood surface roughness of the samples was obtained sanding wood samples in the eccentric sanding stand, using standard open-type sandpaper with different grit size. The arithmetic mean value of the single roughness depths of consecutive sampling lengths parameter Rz of the sanded wood samples were measured in five sectors along the wood grain, across and in the angle of 45°, using a contact stylus profilometer. In total 1800 measurements were done during testing series. Obtained measurement results were processed by digital Gaussian filter according to DIN EN ISO 11562. In the research the dependence of wood surface on wood species, grain direction and grit size of abrasive material was evaluated.DOI: http://dx.doi.org/10.5755/j01.ms.21.2.5882

  14. 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.

  15. Directing vascular cell selectivity and hemocompatibility on patterned platforms featuring variable topographic geometry and size.

    Science.gov (United States)

    Ding, Yonghui; Yang, Zhilu; Bi, Cathy W C; Yang, Meng; Xu, Sherry Li; Lu, Xiong; Huang, Nan; Huang, Pingbo; Leng, Yang

    2014-08-13

    It is great challenge to generate multifunctionality of vascular grafts and stents to enable vascular cell selectivity and improve hemocompatibility. Micro/nanopatterning of vascular implant surfaces for such multifunctionality is a direction to be explored. We developed a novel patterned platform featuring two typical geometries (groove and pillar) and six pattern sizes (0.5-50 μm) in a single substrate to evaluate the response of vascular cells and platelets. Our results indicate that targeted multifunctionality can be indeed instructed by rationally designed surface topography. The pillars nonselectively inhibited the growth of endothelial and smooth muscle cells. By contrast, the grooves displayed selective effects: in a size-dependent manner, the grooves enhanced endothelialization but inhibited the growth of smooth muscle cells. Moreover, our studies suggest that topographic cues can affect response of vascular cells by regulating focal adhesion and stress fiber development, which define cytoskeleton organization and cell shape. Notably, both the grooves and the pillars at 1 μm size drastically reduced platelet adhesion and activation. Taken together, these findings suggest that the topographic pattern featuring 1 μm grooves may be the optimal design of surface multifunctionality that favors vascular cell selectivity and improves hemocompatibility.

  16. Particle sizing of pharmaceutical aerosols via direct imaging of particle settling velocities.

    Science.gov (United States)

    Fishler, Rami; Verhoeven, Frank; de Kruijf, Wilbur; Sznitman, Josué

    2018-02-15

    We present a novel method for characterizing in near real-time the aerodynamic particle size distributions from pharmaceutical inhalers. The proposed method is based on direct imaging of airborne particles followed by a particle-by-particle measurement of settling velocities using image analysis and particle tracking algorithms. Due to the simplicity of the principle of operation, this method has the potential of circumventing potential biases of current real-time particle analyzers (e.g. Time of Flight analysis), while offering a cost effective solution. The simple device can also be constructed in laboratory settings from off-the-shelf materials for research purposes. To demonstrate the feasibility and robustness of the measurement technique, we have conducted benchmark experiments whereby aerodynamic particle size distributions are obtained from several commercially-available dry powder inhalers (DPIs). Our measurements yield size distributions (i.e. MMAD and GSD) that are closely in line with those obtained from Time of Flight analysis and cascade impactors suggesting that our imaging-based method may embody an attractive methodology for rapid inhaler testing and characterization. In a final step, we discuss some of the ongoing limitations of the current prototype and conceivable routes for improving the technique. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. 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...

  18. behaved particle swarm optimization (QPSO)

    African Journals Online (AJOL)

    Administrator

    2011-06-13

    Jun 13, 2011 ... fermentation process, and consequently, it increased the yield of fermentation. Key words: Soft-sensing model, quantum-behaved particle swarm optimization algorithm, neural network. INTRODUCTION. In industrial production through fermentation, the main effect variables include physical variables (the ...

  19. 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.

  20. 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.

  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. Size-Induced Switching of Nanowire Growth Direction: a New Approach Toward Kinked Nanostructures

    KAUST Repository

    Shen, Youde

    2016-04-26

    Exploring self-assembled nanostructures with controllable architectures has been a central theme in nanoscience and nanotechnology because of the tantalizing perspective of directly integrating such bottom-up nanostructures into functional devices. Here, the growth of kinked single-crystal In2O3 nanostructures consisting of a nanocone base and a nanowire tip with an epitaxial and defect-free transition is demonstrated for the first time. By tailoring the growth conditions, a reliable switching of the growth direction from [111] to [110] or [112] is observed when the Au catalyst nanoparticles at the apexes of the nanocones shrink below ≈100 nm. The natural formation of kinked nanoarchitectures at constant growth pressures is related to the size-dependent free energy that changes for different orientations of the nanowires. The results suggest that the mechanism of forming such kinked nanocone-nanowire nanostructures in well-controlled growth environment may be universal for a wide range of functional materials. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. Phase Coexistence in Insect Swarms

    Science.gov (United States)

    Sinhuber, Michael; Ouellette, Nicholas T.

    2017-10-01

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

  4. Organic Computing and Swarm Intelligence

    Science.gov (United States)

    Merkle, Daniel; Middendorf, Martin; Scheidler, Alexander

    The relations between swarm intelligence and organic computing are discussed in this chapter. The aim of organic computing is to design and study computing systems that consist of many autonomous components and show forms of collective behavior. Such organic computing systems (OC systems) should possess self-x properties (e.g., self-healing, self-managing, self-optimizing), have a decentralized control, and be adaptive to changing requirements of their user. Examples of OC systems are described in this chapter and two case studies are presented that show in detail that OC systems share important properties with social insect colonies and how methods of swarm intelligence can be used to solve problems in organic computing.

  5. Electrical transport in transverse direction through silicon carbon alloy multilayers containing regular size silicon quantum dots

    Energy Technology Data Exchange (ETDEWEB)

    Mandal, Aparajita [Energy Research Unit, Indian Association for the Cultivation of Science, Jadavpur, Kolkata 700032 (India); Kole, Arindam, E-mail: erak@iacs.res.in [Energy Research Unit, Indian Association for the Cultivation of Science, Jadavpur, Kolkata 700032 (India); Dasgupta, Arup [Microscopy and Thermophysical Property Division, Indira Gandhi Centre for Atomic Research, Kalpakkam 603102 (India); Chaudhuri, Partha [Energy Research Unit, Indian Association for the Cultivation of Science, Jadavpur, Kolkata 700032 (India)

    2016-11-30

    Highlights: • Low temperature columnar growth of regular sized Si-quantum dots (Si-QDs) within a-SiC:H/μc-SiC:H multilayer structure by tuning the a-SiC:H layer thickness. • Thickness optimization of the a-SiC:H layers resulted in a sharp increase of the transverse current and a decrease of the trap concentrations. • The arrangements of the Si-QDs favor percolation paths for the transverse current. - Abstract: Electrical transport in the transverse direction has been studied through a series of hydrogenated silicon carbon alloy multilayers (SiC-MLs) deposited by plasma enhanced chemical vapor deposition method. Each SiC-ML consists of 30 cycles of the alternating layers of a nearly amorphous silicon carbide (a-SiC:H) and a microcrystalline silicon carbide (μc-SiC:H) that contains high density of silicon quantum dots (Si-QDs). A detailed investigation by cross sectional TEM reveals preferential growth of densely packed Si-QDs of regular sizes ∼4.8 nm in diameter in a vertically aligned columnar structure within the SiC-ML. More than six orders of magnitude increase in transverse current through the SiC-ML structure were observed for decrease in the a-SiC:H layer thickness from 13 nm to 2 nm. The electrical transport mechanism was established to be a combination of grain boundary or band tail hopping and Frenkel–Poole (F-P) type conduction depending on the temperature and externally applied voltage ranges. Evaluation of trap concentration within the multilayer structures from the fitted room temperature current voltage characteristics by F-P function shows reduction up-to two orders of magnitude indicating an improvement in the short range order in the a-SiC:H matrix for decrease in the thickness of a-SiC:H layer.

  6. A Review on Anatomical Variations of Mental Foramen (Number, Location, Shape, Symmetry, Direction and Size

    Directory of Open Access Journals (Sweden)

    F Ezoddini-Ardakani

    2016-02-01

    Full Text Available Mental foramen is located on the anterior aspect of the mandible that permits the terminal branch of the inferior alveolar nerve and blood vessels to exit. The anatomical variations of mental foramen are of considerable importance in local anesthesia, treatment of the fractures in the parasymphysis area, orthognatic surgeries, implant placement, etc. Regarding the importance of mental foramen in dentistry (from local anesthesia to invasive surgical procedures, this study intends to review the anatomical variations of mental foramen in this study. Absence of mental foramen is rare. On the other hand, prevalence of accessory mental foramen has been estimated lower than 15% in the most studies. The position of mental foramen is normally between first and second premolar teeth or under second premolar tooth in different ethnic groups and bilateral symmetry exists in regard with location in most cases. In most studies, the ratio of distance from mental foramen to symphysis to distance from symphysis to posterior border of ramus has been reported about 1/3.5 to 1/3. Mental foramen is oval or circular in shape and its most common direction is usually posterosuperior. Its size in different studies has been estimated about 2 to 5 millimeters and asymmetry in size is possible on both sides of mandible. Due to variations of mental foramen between various ethnic groups and even different individuals in the same ethnic group, using advanced imaging techniques such as CBCT is recommended in order to gain detailed knowledge of anatomy and morphology of mental foramen before applying invasive surgeries.

  7. Time Optimal Reachability Analysis Using Swarm Verification

    DEFF Research Database (Denmark)

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

    2016-01-01

    and planning problems, response time optimization etc. We propose swarm verification to accelerate time optimal reachability using the real-time model-checker Uppaal. In swarm verification, a large number of model checker instances execute in parallel on a computer cluster using different, typically randomized...... 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...

  8. 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...

  9. Melt-Pool Temperature and Size Measurement During Direct Laser Sintering

    Energy Technology Data Exchange (ETDEWEB)

    List, III, Frederick Alyious [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Dinwiddie, Ralph Barton [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Carver, Keith [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Gockel, Joy E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2017-08-01

    Additive manufacturing has demonstrated the ability to fabricate complex geometries and components not possible with conventional casting and machining. In many cases, industry has demonstrated the ability to fabricate complex geometries with improved efficiency and performance. However, qualification and certification of processes is challenging, leaving companies to focus on certification of material though design allowable based approaches. This significantly reduces the business case for additive manufacturing. Therefore, real time monitoring of the melt pool can be used to detect the development of flaws, such as porosity or un-sintered powder and aid in the certification process. Characteristics of the melt pool in the Direct Laser Sintering (DLS) process is also of great interest to modelers who are developing simulation models needed to improve and perfect the DLS process. Such models could provide a means to rapidly develop the optimum processing parameters for new alloy powders and optimize processing parameters for specific part geometries. Stratonics’ ThermaViz system will be integrated with the Renishaw DLS system in order to demonstrate its ability to measure melt pool size, shape and temperature. These results will be compared with data from an existing IR camera to determine the best approach for the determination of these critical parameters.

  10. Direct uranium isotope ratio analysis of single micrometer-sized glass particles

    Science.gov (United States)

    Kappel, Stefanie; Boulyga, Sergei F.; Prohaska, Thomas

    2012-01-01

    We present the application of nanosecond laser ablation (LA) coupled to a ‘Nu Plasma HR’ multi collector inductively coupled plasma mass spectrometer (MC-ICP-MS) for the direct analysis of U isotope ratios in single, 10–20 μm-sized, U-doped glass particles. Method development included studies with respect to (1) external correction of the measured U isotope ratios in glass particles, (2) the applied laser ablation carrier gas (i.e. Ar versus He) and (3) the accurate determination of lower abundant 236U/238U isotope ratios (i.e. 10−5). In addition, a data processing procedure was developed for evaluation of transient signals, which is of potential use for routine application of the developed method. We demonstrate that the developed method is reliable and well suited for determining U isotope ratios of individual particles. Analyses of twenty-eight S1 glass particles, measured under optimized conditions, yielded average biases of less than 0.6% from the certified values for 234U/238U and 235U/238U ratios. Experimental results obtained for 236U/238U isotope ratios deviated by less than −2.5% from the certified values. Expanded relative total combined standard uncertainties Uc (k = 2) of 2.6%, 1.4% and 5.8% were calculated for 234U/238U, 235U/238U and 236U/238U, respectively. PMID:22595724

  11. Universal size dependence of auger constants in direct- and indirect-gap semiconductor nanocrystals

    Energy Technology Data Exchange (ETDEWEB)

    Robel, Istvan [Los Alamos National Laboratory; Schaller, Richard D [Los Alamos National Laboratory; Klimov, Victor I [Los Alamos National Laboratory; Gresback, Ryan [U OF MINNESOTA; Kortshagen, Uwe [U OF MINNESOTA

    2008-01-01

    Three-dimensional (3D) spatial confinement of electronic wave functions in semiconductor nanocrystals (NCs) results in a significant enhancement of multi-electron phenomena including non radiative Auger recombination. In this process, a conduction-band electron recombines with a valence-band hole by transferring the recombination energy to a third carrier. Significant interest in Auger recombination in NCs has been stimulated by recent studies ofNC lasing, and generation-III photovoltaics enabled by carrier multiplication because in both of these prospective applications Auger recombination represents a dominant carrier-loss mechanism. Here, we perform a side-by-side comparison of Auger recombination rates in NCs of several different compositions including Ge, PbSe, InAs, and CdSe. We observe that the only factor, which has a significant effect on the measured recombination rates, is the size of the NCs but not the details of the material's electronic structure. Most surprisingly, comparable rates are measured for nanocrystals of directand indirect-gap semiconductor NCs despite a dramatic four-to-five orders of magnitude difference in respective bulk-semiconductor Auger constants. This unusual observation can be explained by confinement-induced relaxation of momentum conservation, which smears out the difference between direct- and indirect-gap materials.

  12. TUNING OF SIZE AND SHAPE OF AU-PT NANOCATALYST FOR DIRECT METHANOL FUEL CELLS

    Energy Technology Data Exchange (ETDEWEB)

    Murph, S.

    2011-04-20

    In this paper, we report the precise control of the size, shape and surface morphology of Au-Pt nanocatalysts (cubes, blocks, octahedrons and dogbones) synthesized via a seed-mediated approach. Gold 'seeds' of different aspect ratios (1 to 4.2), grown by a silver-assisted approach, were used as templates for high-yield production of novel Au-Pt nanocatalysts at a low temperature (40 C). Characterization by electron microscopy (SEM, TEM, HRTEM), energy dispersive X-ray analysis (EDX), UV-Vis spectroscopy, zeta-potential (surface charge), atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS) and inductively coupled plasma mass spectrometry (ICP-MS) were used to better understand their physico-chemical properties, preferred reactivities and underlying nanoparticle growth mechanism. A rotating disk electrode was used to evaluate the Au-Pt nanocatalysts electrochemical performance in the oxygen reduction reaction (ORR) and the methanol oxidation reaction (MOR) of direct methanol fuel cells. The results indicate the Au-Pt dogbones are partially and in some cases completely unaffected by methanol poisoning during the evaluation of the ORR. The ORR performance of the octahedron particles in the absence of MeOH is superior to that of the Au-Pt dogbones and Pt-black, however its performance is affected by the presence of MeOH.

  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. 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.

  15. DOA estimation for local scattered CDMA signals by particle swarm optimization.

    Science.gov (United States)

    Chang, Jhih-Chung

    2012-01-01

    This paper deals with the direction-of-arrival (DOA) estimation of local scattered code-division multiple access (CDMA) signals based on a particle swarm optimization (PSO) search. For conventional spectral searching estimators with local scattering, the searching complexity and estimating accuracy strictly depend on the number of search grids used during the search. In order to obtain high-resolution and accurate DOA estimation, a smaller grid size is needed. This is time consuming and it is unclear how to determine the required number of search grids. In this paper, a modified PSO is presented to reduce the required search grids for the conventional spectral searching estimator with the effects of local scattering. Finally, several computer simulations are provided for illustration and comparison.

  16. 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....

  17. 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...... Level-1b data products....

  18. Size-exclusion chromatography-mass spectrometry with m-nitrobenzyl alcohol as post-column additive for direct characterization of size variants of monoclonal antibodies.

    Science.gov (United States)

    Xu, Chong-Feng; Zang, Li; Weiskopf, Andrew

    2014-06-01

    Size-exclusion chromatography (SEC) is commonly used to monitor low molecular weight fragments and aggregates present in recombinant monoclonal antibody (mAb) biopharmaceuticals. It has been previously demonstrated that SEC could be coupled with mass spectrometry (MS) to directly measure the molecular weights of these protein species to aid in their identification. However, the use of certain mobile phase modifiers led to compromised sensitivity in MS detection. In this work, we demonstrate that the use of m-nitrobenzyl alcohol (m-NBA) as a post-column additive in an SEC-MS method is able to improve the ionization of antibody light chain and heavy chain approximately 7-fold and 2-fold, respectively, and thus allows the MS detection of low-abundance size variants present in mAb biopharmaceuticals. Application of the 15-min reducing SEC-UV/MS method enabled the direct identification of size variants present in an IgG1 mAb sample. One high molecular weight species observed under reducing conditions was identified to be a thioether-linked heterodimer of light chain and heavy chain. Multiple lower molecular weight species were found to result from cleavage of the heavy chain at a number of sites throughout the conserved sequence. The reducing SEC-UV/MS method provides a straightforward approach for identification of size variants present in mAb and may be applicable generally to all types of mAb biopharmaceuticals. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. 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 ...

  20. Insular species swarm goes underground

    DEFF Research Database (Denmark)

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

    2014-01-01

    -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......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...

  1. [Modeling of swarm formation as a consequence of autotaxis].

    Science.gov (United States)

    Senina, I N; Tiutiunov, Iu V

    2002-01-01

    The simple model of school and swarm formation is proposed within the frameworks of Eulerian space models (reaction-diffusion-advection system). Assuming that the schooling and the processes of birth-and-death act on different time scales, we have excluded the local kinetics of species (the reaction term) from the model. The spatial dynamics of animals is circumscribed by scalar field of density and vector field of velocity. The basis of animal aggregation in space is the ability of animals to move in certain direction, i.e. taxis. As an example of swarming strategy the behavior of midges is taken: we presume that individuals accelerate towards higher swarm density but change direction when the density exceeded some maximum. In other words, acceleration of movement is assumed to be proportional (with density-dependent coefficient of proportionality) to the gradient of species density. This statement poses the equation for species velocity. Thus, our model adds the differential equation for velocity of autotaxis to the standard advection-diffusion model. The linear analysis of 1D problem with zero-flux boundary conditions has showed that homogeneous nonzero equilibrium looses its stability when the movement rate of animals (coefficient of proportionality in velocity equation) overpasses some bifurcation value. The numerical experiments have confirmed analytical results, displaying stationary spatially heterogeneous solution (standing waves) for the detected supercritical value of the movement rate.

  2. Centimeter Precise Orbit Determination for SWARM Satellite via Reduced-dynamic Method

    Directory of Open Access Journals (Sweden)

    ZHANG Bingbing

    2016-11-01

    Full Text Available Combining dual-frequency satellite-borne GPS observations with reduced dynamic models, and introducing proper pseudo-stochastic pulse parameters into the satellite's motion equation, SWARM satellite precise orbit determination is implemented. The orbit accuracy is assessed using three methods, which include analysis satellite-borne GPS phase observation residuals, orbit overlaps and external orbit comparisons. The results indicate that the SWARM satellite-borne GPS phase observation residual RMS is in the range of 7 to 10 mm, radial, along-track and cross-track orbit overlap difference RMS of 6 hours are about 1 cm, three directions have no significant systematic errors, comparisons with orbits computed by European Space Agency (ESA, Radial orbit difference RMS is in the range of 2 to 5 cm, along-track orbit difference RMS is in the range of 2 to 5 cm, cross-track orbit difference RMS is in the range of 2 to 4 cm, 3D orbit difference RMS is in the range of 4 to 7 cm, SWARM-B orbit accuracy is better than SWARM-A and SWARM-C. This evaluations indicate that SWARM satellite precise orbit determination is practicable by using reduced-dynamic method and orbit determining strategy in the article, the orbit solution is well and stable, the orbit accuracy reaches centimeter level.

  3. Effect of netting direction and number of meshes around on size selection in the codend for Baltic cod (Gadus morhua)

    DEFF Research Database (Denmark)

    Wienbeck, Harald; Herrmann, Bent; Moderhak, Waldemar

    2011-01-01

    We investigated experimentally the effect that turning the netting direction 90° (T90) and halving the number of meshes around in the circumference in a diamond mesh codend had on size selection of Baltic cod. The results generally agreed with predictions of a previous simulation-based study. Both...... modifications had a significant positive effect on the size selection of cod. The best selection results were obtained for a codend in which both factors were applied together. For that codend, very little between-haul variation in cod size selection was detected, especially compared to the reference codend...

  4. 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

  5. Swarming dynamics in bacterial colonies

    Science.gov (United States)

    Zhang, Hepeng; Be'Er, Avraham; Smith, Rachel; Florin, E.-L.; Swinney, Harry L.

    2009-11-01

    Swarming is a widespread phenomenon observed in both biological and non-biological systems. Large mammal herds, fish schools, and bird flocks are among the most spectacular examples. Many theoretical and numerical efforts have been made to unveil the general principles of the phenomenon, but systematic experimental studies have been very limited. We determine the characteristic velocity, length, and time scales for bacterial motion in swarming colonies of Paenibacillus dendritiformis growing on semi-solid agar substrates. The bacteria swim within a thin fluid layer, and they form long-lived jets and vortices. These coherent structures lead to anisotropy in velocity spatial correlations and to a two-step relaxation in velocity temporal correlations. The mean squared displacement of passive tracers exhibits a short-time regime with nearly ballistic transport and a diffusive long-time regime. We find that various definitions of the correlation length all lead to length scales that are, surprisingly, essentially independent of the mean bacterial speed, while the correlation time is linearly proportional to the ratio of the correlation length to the mean speed.

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

    Science.gov (United States)

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

    2017-04-01

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

  7. Pause and utterance duration in child-directed speech in relation to child vocabulary size.

    Science.gov (United States)

    Marklund, Ulrika; Marklund, Ellen; Lacerda, Francisco; Schwarz, Iris-Corinna

    2015-09-01

    This study compares parental pause and utterance duration in conversations with Swedish speaking children at age 1;6 who have either a large, typical, or small expressive vocabulary, as measured by the Swedish version of the McArthur-Bates CDI. The adjustments that parents do when they speak to children are similar across all three vocabulary groups; they use longer utterances than when speaking to adults, and respond faster to children than they do to other adults. However, overall pause duration varies with the vocabulary size of the children, and as a result durational aspects of the language environment to which the children are exposed differ between groups. Parents of children in the large vocabulary size group respond faster to child utterances than do parents of children in the typical vocabulary size group, who in turn respond faster to child utterances than do parents of children in the small vocabulary size group.

  8. 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.

  9. A Local and Global Search Combined Particle Swarm Optimization Algorithm and Its Convergence Analysis

    Directory of Open Access Journals (Sweden)

    Weitian Lin

    2014-01-01

    Full Text Available Particle swarm optimization algorithm (PSOA is an advantage optimization tool. However, it has a tendency to get stuck in a near optimal solution especially for middle and large size problems and it is difficult to improve solution accuracy by fine-tuning parameters. According to the insufficiency, this paper researches the local and global search combine particle swarm algorithm (LGSCPSOA, and its convergence and obtains its convergence qualification. At the same time, it is tested with a set of 8 benchmark continuous functions and compared their optimization results with original particle swarm algorithm (OPSOA. Experimental results indicate that the LGSCPSOA improves the search performance especially on the middle and large size benchmark functions significantly.

  10. Physiological processes related to the bee swarming

    Directory of Open Access Journals (Sweden)

    Jiří Svoboda

    2010-01-01

    Full Text Available One of the essential genetically subjected behaviours of a bee-colony is swarming. However, in the time of queen breeding and technical approach to colony division, swarming constitutes a problem in the effectiveness of controlled beekeeping and subsequently in decreasing of the attainable economic profits. The intensity of swarming is a polyfactorial phenomenon whose characteristic feature is seasonality (the availability of breed, course of weather so the swarming intensity is different in particular years. This study is connected with the research carried out at the Department of Zoo­lo­gy, Fisheries, Hydrobiology and Apiculture at Mendel University in Brno. The experiment focused on the relationship between the swarming and biological state of bee-colony was realized in three seasons of the period 2003–2005. Experimental bee-colonies were stimulated to the swarming fever by zoo-technical practices, at the same time the biological status of given bee-colony was observed. Within the process of marking of newly emerged workers there was observed their number continuously during the particular season. The samples of 3- and 4-week-old workers were instrumental to the analysis of the development of their hypopharyngeal glands. The study has proved that a bee-colonies building higher number of queen cells are likely expected to be in swarming fever, b 3-week-old workers have hypopharyngeal glands in higher stage of development than 4-week-old workers, c higher stage of swarming fever is closely correlated with higher stage of de­ve­lop­ment of hypopharyngeal glands. These facts can contribute to the comprehension of the reason and relationships of the swarming.

  11. Morphologically and size uniform monodisperse particles and their shape-directed self-assembly

    Energy Technology Data Exchange (ETDEWEB)

    Collins, Joshua E.; Bell, Howard Y.; Ye, Xingchen; Murray, Christopher Bruce

    2017-09-12

    Monodisperse particles having: a single pure crystalline phase of a rare earth-containing lattice, a uniform three-dimensional size, and a uniform polyhedral morphology are disclosed. Due to their uniform size and shape, the monodisperse particles self assemble into superlattices. The particles may be luminescent particles such as down-converting phosphor particles and up-converting phosphors. The monodisperse particles of the invention have a rare earth-containing lattice which in one embodiment may be an yttrium-containing lattice or in another may be a lanthanide-containing lattice. The monodisperse particles may have different optical properties based on their composition, their size, and/or their morphology (or shape). Also disclosed is a combination of at least two types of monodisperse particles, where each type is a plurality of monodisperse particles having a single pure crystalline phase of a rare earth-containing lattice, a uniform three-dimensional size, and a uniform polyhedral morphology; and where the types of monodisperse particles differ from one another by composition, by size, or by morphology. In a preferred embodiment, the types of monodisperse particles have the same composition but different morphologies. Methods of making and methods of using the monodisperse particles are disclosed.

  12. Direct measurement of the critical pore size in a model membrane

    CERN Document Server

    Ilton, Mark; Dalnoki-Veress, Kari

    2016-01-01

    We study pore nucleation in a model membrane system, a freestanding polymer film. Nucleated pores smaller than a critical size close, while pores larger than the critical size grow. Holes of varying size were purposefully prepared in liquid polymer films, and their evolution in time was monitored using optical and atomic force microscopy to extract a critical radius. The critical radius scales linearly with film thickness for a homopolymer film. The results agree with a simple model which takes into account the energy cost due to surface area at the edge of the pore. The energy cost at the edge of the pore is experimentally varied by using a lamellar-forming diblock copolymer membrane. The underlying molecular architecture causes increased frustration at the pore edge resulting in an enhanced cost of pore formation.

  13. 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

    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. 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. The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (⩽9.2%) and ROA (⩽1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n  =  3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies

  14. 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 (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (⩽9.2%) and ROA (⩽1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n  =  3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon

  15. Geothermal hydrothermal direct heat use: US market size and market penetration estimates

    Energy Technology Data Exchange (ETDEWEB)

    El Sawy, A.H.; Entingh, D.J.

    1980-09-01

    This study estimates the future regional and national market penetration path of hydrothermal geothermal direct heat applications in the United States. A Technology Substitution Model (MARPEN) is developed and used to estimate the energy market shares captured by low-temperature (50 to 150/sup 0/C) hydrothermal geothermal energy systems over the period 1985 to 2020. The sensitivity of hydrothermal direct heat market shares to various government hydrothermal commercialization policies is examined. Several substantive recommendations to help accelerate commercialization of geothermal direct heat utilization in the United States are indicated and possible additional analyses are discussed.

  16. Combined use of leaf size and economics traits allows direct comparison of hydrophyte and terrestrial herbaceous adaptive strategies.

    Science.gov (United States)

    Pierce, Simon; Brusa, Guido; Sartori, Matteo; Cerabolini, Bruno E L

    2012-04-01

    Hydrophytes generally exhibit highly acquisitive leaf economics. However, a range of growth forms is evident, from small, free-floating and rapidly growing Lemniden to large, broad-leaved Nymphaeiden, denoting variability in adaptive strategies. Traits used to classify adaptive strategies in terrestrial species, such as canopy height, are not applicable to hydrophytes. We hypothesize that hydrophyte leaf size traits and economics exhibit sufficient overlap with terrestrial species to allow a common classification of plant functional types, sensu Grime's CSR theory. Leaf morpho-functional traits were measured for 61 species from 47 water bodies in lowland continental, sub-alpine and alpine bioclimatic zones in southern Europe and compared against the full leaf economics spectrum and leaf size range of terrestrial herbs, and between hydrophyte growth forms. Hydrophytes differed in the ranges and mean values of traits compared with herbs, but principal components analysis (PCA) demonstrated that both groups shared axes of trait variability: PCA1 encompassed size variation (area and mass), and PCA2 ranged from relatively dense, carbon-rich leaves to nitrogen-rich leaves of high specific leaf area (SLA). Most growth forms exhibited trait syndromes directly equivalent to herbs classified as R adapted, although Nymphaeiden ranged between C and SR adaptation. Our findings support the hypothesis that hydrophyte adaptive strategy variation reflects fundamental trade-offs in economics and size that govern all plants, and that hydrophyte adaptive strategies can be directly compared with terrestrial species by combining leaf economics and size traits.

  17. 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

  18. 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...

  19. 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

  20. 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 Swarm science objectives, the mission concept, the scientific instrumentation, and the expected contribution to the ILWS programme will be summarized. (C) 2007 Published by Elsevier Ltd on behalf of COSPAR....

  1. Resolution of the stochastic strategy spatial prisoner's dilemma by means of particle swarm optimization.

    Science.gov (United States)

    Zhang, Jianlei; Zhang, Chunyan; Chu, Tianguang; Perc, Matjaž

    2011-01-01

    We study the evolution of cooperation among selfish individuals in the stochastic strategy spatial prisoner's dilemma game. We equip players with the particle swarm optimization technique, and find that it may lead to highly cooperative states even if the temptations to defect are strong. The concept of particle swarm optimization was originally introduced within a simple model of social dynamics that can describe the formation of a swarm, i.e., analogous to a swarm of bees searching for a food source. Essentially, particle swarm optimization foresees changes in the velocity profile of each player, such that the best locations are targeted and eventually occupied. In our case, each player keeps track of the highest payoff attained within a local topological neighborhood and its individual highest payoff. Thus, players make use of their own memory that keeps score of the most profitable strategy in previous actions, as well as use of the knowledge gained by the swarm as a whole, to find the best available strategy for themselves and the society. Following extensive simulations of this setup, we find a significant increase in the level of cooperation for a wide range of parameters, and also a full resolution of the prisoner's dilemma. We also demonstrate extreme efficiency of the optimization algorithm when dealing with environments that strongly favor the proliferation of defection, which in turn suggests that swarming could be an important phenomenon by means of which cooperation can be sustained even under highly unfavorable conditions. We thus present an alternative way of understanding the evolution of cooperative behavior and its ubiquitous presence in nature, and we hope that this study will be inspirational for future efforts aimed in this direction.

  2. Foreign direct investment in Africa: The role of natural resources, market size, government policy, institutions and political instability

    OpenAIRE

    Asiedu, Elizabeth

    2005-01-01

    Data from several investor surveys suggest that macroeconomic instability, investment restrictions, corruption and political instability have a negative impact on foreign direct investment (FDI) to Africa. However, the relationship between FDI and these country characteristics has not been studied. This paper uses panel data for 22 countries over the period 1984-2000 to examine the impact of natural resources, market size, government policies, political instability and the quality of the host...

  3. Seed Size, the Only Factor Positively Affecting Direct Seeding Success in an Abandoned Field in Quebec, Canada

    OpenAIRE

    Annick St-Denis; Daniel Kneeshaw; Christian Messier

    2013-01-01

    Direct tree seeding is potentially an economical technique for restoring forests on abandoned fields. However, the success of tree establishment depends on many factors related to species and seed characteristics, environmental conditions, competition and predation. We compared seedling emergence, survival and growth of six tree species of different seed sizes in a forest restoration project of abandoned fields. Species were seeded in plots with and without herbaceous vegetation and with and ...

  4. Saturated Particle Transport in Porous Media: An Investigation into the Influence of Flow Direction and Particle Size Distribution

    Science.gov (United States)

    2015-06-28

    military and industrial operations. Contaminants can include PCBs, fuels, solvents, herbicides/pesticides, heavy metals, munitions materials, and...interpretation of laboratory or field experiments, and have led to the generation of a range of particle filtration and transport models that are thought...of flow direction and particle size distribution on particle filtration . To meet this objective, particle transport experiments were conducted in the

  5. Direct exfoliation of natural graphite into micrometre size few layers graphene sheets using ionic liquids.

    Science.gov (United States)

    Wang, Xiqing; Fulvio, Pasquale F; Baker, Gary A; Veith, Gabriel M; Unocic, Raymond R; Mahurin, Shannon M; Chi, Miaofang; Dai, Sheng

    2010-07-07

    Stable high-concentration suspensions (up to 0.95 mg mL(-1)) of non-oxidized few layer graphene (FLG), five or less sheets, with micrometre-long edges were obtained via direct exfoliation of natural graphite flakes in ionic liquids, such as 1-butyl-3-methyl-imidazolium bis(trifluoro-methane-sulfonyl)imide ([Bmim]-[Tf(2)N]), by tip ultrasonication.

  6. Reversed better-than-average effect in direct comparisons of nonsocial stimuli depends on the set size.

    Science.gov (United States)

    Niewiarowski, Jakub; Karyłowski, Jerzy J; Szutkiewicz-Szekalska, Karolina; Cypryańska, Marzena

    2014-05-01

    Studies on direct comparative judgments typically show that, for items that are positively evaluated, a single item randomly drawn from a larger set of similar items tends to be judged as better than average (the BTA effect). However, Windschitl, Conybeare, and Krizan (2008) demonstrated that, under timing conditions that do not favor focusing attention on the single item, the reversal of the BTA effect occurs. We report two experiments showing that the magnitude of the reversed BTA effect increases as a function of the size of a multiitem referent with which a single item target is compared. Specifically, in direct comparative judgments of the attractiveness of positively evaluated objects (nice-looking cloth buttons, attractive buildings, or cupcakes), underestimation of the attractiveness of singletons, as compared with a multiitem set (reversed BTA effect), increased with the increased set size. Analysis of absolute judgments obtained for singletons and for small and large multiitem sets suggests that, for attractive stimuli, both the reversed BTA effect in comparative judgments and its sensitivity to set size occur as a result of a positive relationship between set size and perceived attractiveness in absolute judgments.

  7. CALM regulates clathrin-coated vesicle size and maturation by directly sensing and driving membrane curvature.

    Science.gov (United States)

    Miller, Sharon E; Mathiasen, Signe; Bright, Nicholas A; Pierre, Fabienne; Kelly, Bernard T; Kladt, Nikolay; Schauss, Astrid; Merrifield, Christien J; Stamou, Dimitrios; Höning, Stefan; Owen, David J

    2015-04-20

    The size of endocytic clathrin-coated vesicles (CCVs) is remarkably uniform, suggesting that it is optimized to achieve the appropriate levels of cargo and lipid internalization. The three most abundant proteins in mammalian endocytic CCVs are clathrin and the two cargo-selecting, clathrin adaptors, CALM and AP2. Here we demonstrate that depletion of CALM causes a substantial increase in the ratio of "open" clathrin-coated pits (CCPs) to "necked"/"closed" CCVs and a doubling of CCP/CCV diameter, whereas AP2 depletion has opposite effects. Depletion of either adaptor, however, significantly inhibits endocytosis of transferrin and epidermal growth factor. The phenotypic effects of CALM depletion can be rescued by re-expression of wild-type CALM, but not with CALM that lacks a functional N-terminal, membrane-inserting, curvature-sensing/driving amphipathic helix, the existence and properties of which are demonstrated. CALM is thus a major factor in controlling CCV size and maturation and hence in determining the rates of endocytic cargo uptake. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  8. On Formal Specification of Emergent Behaviours in Swarm Robotic Systems

    Directory of Open Access Journals (Sweden)

    Alan FT Winfield

    2005-12-01

    Full Text Available It is a characteristic of swarm robotics that specifying overall emergent swarm behaviours in terms of the low-level behaviours of individual robots is very difficult. Yet if swarm robotics is to make the transition from the laboratory to real-world engineering realisation we need such specifications. This paper explores the use of temporal logic to formally specify, and possibly also prove, the emergent behaviours of a robotic swarm. The paper makes use of a simplified wireless connected swarm as a case study with which to illustrate the approach. Such a formal approach could be an important step toward a disciplined design methodology for swarm robotics.

  9. The October-November 2008 earthquake swarm in Vogtland/NW-Bohemia: first results of focal mechanism determinations

    Science.gov (United States)

    Plenefisch, T.

    2009-04-01

    Vogtland/NW-Bohemia, an area at the border between Germany and Czech Republic, is known as one of the most interesting earthquake swarm regions in Europe. This special type of seismicity is expressed by the accumulation of a huge number of events of similar magnitude and their episodic reoccurrence. During a swarm hundreds or thousands of earthquakes without a distinct main shock occur spatially and temporally clustered. The most recent swarm of 2008 occurred between the 6th of October and the middle of November. With more than 20000 detectable events and magnitudes up to 4 it is the most prominent one since the big swarm in 1985/86. Due to the strength of the swarm and the increased number of stations in the Vogtland/NW-Bohemia region the swarm of 2008 offers various possibilities to investigate the peculiarities of swarms and the special seismotectonic situation of the Vogtland/NW-Bohemia region. This study concentrates on the determination of earthquake focal mechanisms. Mechanisms for all events with magnitudes ML ≥ 2.7 have been calculated. The ensemble of focal mechanism is analysed with respect to variations within the swarm as well as changes with respect to the mechanisms of the former swarms of 2000 and 1985/86. For example, the focal mechanism of one of the strongest events (10.10.2008, 08:08 UT) represents a strike slip mechanism with a slight normal faulting component. It is similar to the mechanisms of the stronger events of 2000 and 1985/86. The strike direction of one nodal plane (almost N-S) reflects the strike of the Marianske Lazne fault zone and parallel striking fault systems. The focal mechanisms are used to invert for the regional stress field which then is compared to the stress field in Central Europe.

  10. 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....... The Swarm SCARF (Satellite Constellation Application and Research Facility) has been established with the goal of deriving Level-2 products by combination of data from the three satellites, and of the various instruments. The present paper describes the Swarm input data products (Level-1b and auxiliary data...

  11. 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.

  12. Towards Small-Sized Long Tail Business with the Dual-Directed Recommendation System

    Science.gov (United States)

    Takahashi, Masakazu; Yamada, Takashi; Tsuda, Kazuhiko; Terano, Takao

    This paper describes a novel architecture to promote retail businesses using information recommendation systems. The main features of the architecture are 1) Dual-directed Recommendation system, 2) Portal site for three kinds of users: Producers, Retailers, and Consumers, which are considered to be Prosumers, and 3) Agent-based implementation. We have developed a web-based system DAIKOC (Dynamic Advisor for Information and Knowledge Oriented Communities) with the above architecture. In this paper, we focus on the recommendation functions to extract the items that will achieve the large sales in the future from the ID (IDentification)-POS (Point-Of-Sales) data.

  13. Particle Swarm Optimization for Multiband Metamaterial Fractal Antenna

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    Balamati Choudhury

    2013-01-01

    Full Text Available The property of self-similarity, recursive irregularity, and space filling capability of fractal antennas makes it useful for various applications in wireless communication, including multiband miniaturized antenna designs. In this paper, an effort has been made to use the metamaterial structures in conjunction with the fractal patch antenna, which resonates at six different frequencies covering both C and X band. Two different types of square SRR are loaded on the fractal antenna for this purpose. Particle swarm optimization (PSO is used for optimization of these metamaterial structures. The optimized metamaterial structures, after loading upon, show significant increase in performance parameters such as bandwidth, gain, and directivity.

  14. 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...... altitude) orbits using a particular Swarm and Cluster conjunction. The Cluster signatures are interpreted and ordered through joint mapping of the ground/magnetospheric footprints and estimation of the auroral zone boundaries (taken as indication of the boundaries of Region 1 and Region 2 currents). We...

  15. Collective motion of predictive swarms.

    Directory of Open Access Journals (Sweden)

    Nathaniel Rupprecht

    Full Text Available Theoretical models of populations and swarms typically start with the assumption that the motion of agents is governed by the local stimuli. However, an intelligent agent, with some understanding of the laws that govern its habitat, can anticipate the future, and make predictions to gather resources more efficiently. Here we study a specific model of this kind, where agents aim to maximize their consumption of a diffusing resource, by attempting to predict the future of a resource field and the actions of other agents. Once the agents make a prediction, they are attracted to move towards regions that have, and will have, denser resources. We find that the further the agents attempt to see into the future, the more their attempts at prediction fail, and the less resources they consume. We also study the case where predictive agents compete against non-predictive agents and find the predictors perform better than the non-predictors only when their relative numbers are very small. We conclude that predictivity pays off either when the predictors do not see too far into the future or the number of predictors is small.

  16. Genetic Learning Particle Swarm Optimization.

    Science.gov (United States)

    Gong, Yue-Jiao; Li, Jing-Jing; Zhou, Yicong; Li, Yun; Chung, Henry Shu-Hung; Shi, Yu-Hui; Zhang, Jun

    2016-10-01

    Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This observation recently leads to hybridizing PSO with GA for performance enhancement. However, existing work uses a mechanistic parallel superposition and research has shown that construction of superior exemplars in PSO is more effective. Hence, this paper first develops a new framework so as to organically hybridize PSO with another optimization technique for "learning." This leads to a generalized "learning PSO" paradigm, the *L-PSO. The paradigm is composed of two cascading layers, the first for exemplar generation and the second for particle updates as per a normal PSO algorithm. Using genetic evolution to breed promising exemplars for PSO, a specific novel *L-PSO algorithm is proposed in the paper, termed genetic learning PSO (GL-PSO). In particular, genetic operators are used to generate exemplars from which particles learn and, in turn, historical search information of particles provides guidance to the evolution of the exemplars. By performing crossover, mutation, and selection on the historical information of particles, the constructed exemplars are not only well diversified, but also high qualified. Under such guidance, the global search ability and search efficiency of PSO are both enhanced. The proposed GL-PSO is tested on 42 benchmark functions widely adopted in the literature. Experimental results verify the effectiveness, efficiency, robustness, and scalability of the GL-PSO.

  17. Period Doubling Bifurcation Point Detection Strategy with Nested Layer Particle Swarm Optimization

    Science.gov (United States)

    Matsushita, Haruna; Tomimura, Yusho; Kurokawa, Hiroaki; Kousaka, Takuji

    2017-06-01

    This paper proposes a bifurcation point detection strategy based on nested layer particle swarm optimization (NLPSO). The NLPSO is performed by two particle swarm optimization (PSO) algorithms with a nesting structure. The proposed method is tested in detection experiments of period doubling bifurcation points in discrete-time dynamical systems. The proposed method directly detects the parameters of period doubling bifurcation regardless of the stability of the periodic point, but require no careful initialization, exact calculation or Lyapunov exponents. Moreover, the proposed method is an effective detection technique in terms of accuracy, robustness usability, and convergence speed.

  18. Smart swarms of bacteria-inspired agents with performance adaptable interactions.

    Directory of Open Access Journals (Sweden)

    Adi Shklarsh

    2011-09-01

    Full Text Available Collective navigation and swarming have been studied in animal groups, such as fish schools, bird flocks, bacteria, and slime molds. Computer modeling has shown that collective behavior of simple agents can result from simple interactions between the agents, which include short range repulsion, intermediate range alignment, and long range attraction. Here we study collective navigation of bacteria-inspired smart agents in complex terrains, with adaptive interactions that depend on performance. More specifically, each agent adjusts its interactions with the other agents according to its local environment--by decreasing the peers' influence while navigating in a beneficial direction, and increasing it otherwise. We show that inclusion of such performance dependent adaptable interactions significantly improves the collective swarming performance, leading to highly efficient navigation, especially in complex terrains. Notably, to afford such adaptable interactions, each modeled agent requires only simple computational capabilities with short-term memory, which can easily be implemented in simple swarming robots.

  19. Particle swarm optimization using multi-information characteristics of all personal-best information.

    Science.gov (United States)

    Huang, Song; Tian, Na; Wang, Yan; Ji, Zhicheng

    2016-01-01

    Convergence stagnation is the chief difficulty to solve hard optimization problems for most particle swarm optimization variants. To address this issue, a novel particle swarm optimization using multi-information characteristics of all personal-best information is developed in our research. In the modified algorithm, two positions are defined by personal-best positions and an improved cognition term with three positions of all personal-best information is used in velocity update equation to enhance the search capability. This strategy could make particles fly to a better direction by discovering useful information from all the personal-best positions. The validity of the proposed algorithm is assessed on twenty benchmark problems including unimodal, multimodal, rotated and shifted functions, and the results are compared with that obtained by some published variants of particle swarm optimization in the literature. Computational results demonstrate that the proposed algorithm finds several global optimum and high-quality solutions in most case with a fast convergence speed.

  20. Modeling and Flocking Consensus Analysis for Large-Scale UAV Swarms

    Directory of Open Access Journals (Sweden)

    Li Bing

    2013-01-01

    Full Text Available Recently, distributed coordination control of the unmanned aerial vehicle (UAV swarms has been a particularly active topic in intelligent system field. In this paper, through understanding the emergent mechanism of the complex system, further research on the flocking and the dynamic characteristic of UAV swarms will be given. Firstly, this paper analyzes the current researches and existent problems of UAV swarms. Afterwards, by the theory of stochastic process and supplemented variables, a differential-integral model is established, converting the system model into Volterra integral equation. The existence and uniqueness of the solution of the system are discussed. Then the flocking control law is given based on artificial potential with system consensus. At last, we analyze the stability of the proposed flocking control algorithm based on the Lyapunov approach and prove that the system in a limited time can converge to the consensus direction of the velocity. Simulation results are provided to verify the conclusion.

  1. Structural Preconditions of West Bohemia Earthquake Swarms

    Science.gov (United States)

    Novotný, M.; Špičák, A.; Weinlich, F. H.

    2013-07-01

    The West Bohemia and adjacent Vogtland are well known for quasi-periodical earthquake swarms persisting for centuries. The seismogenic area near Nový Kostel involved about 90 % of overall earthquake activity clustered here in space and time. The latest major earthquake swarm took place in August-September 2011. In 1994 and 1997, two minor earthquake swarms appeared in another location, near Lazy. Recently, the depth-recursive tomography yielded a velocity image with an improved resolution along the CEL09 refraction profile passing between these swarm areas. The resolution, achieved in the velocity image and its agreement with the inverse gravity modeling along the collateral 9HR reflection profile, enabled us to reveal the key structural background of these West Bohemia earthquake swarms. The CEL09 velocity image detected two deeply rooted high-velocity bodies adjacent to the Nový Kostel and Lazy focal zones. They correspond to two Variscan mafic intrusions influenced by the SE inclined slab of Saxothuringian crust that subducted beneath the Teplá-Barrandian terrane in the Devonian era. In their uppermost SE inclined parts, they roof both focal zones. The high P-wave velocities of 6,100-6,200 m/s, detected in both roofing caps, indicate their relative compactness and impermeability. The focal domains themselves are located in the almost gradient-free zones with the swarm foci spread near the axial planes of profound velocity depressions. The lower velocities of 5,950-6,050 m/s, observed in the upper parts of focal zones, are indicative of less compact rock complexes corrugated and tectonically disturbed by the SE bordering magma ascents. The high-velocity/high-density caps obviously seal the swarm focal domains because almost no magmatic fluids of mantle origin occur in the Nový Kostel and Lazy seismogenic areas of the West Bohemia/Vogtland territory, otherwise rich in the mantle-derived fluids. This supports the hypothesis of the fluid triggering of earthquake

  2. Evolution of intense laser pulse spot size propagating in collisional plasma embedded in magnetic field with variable direction

    Science.gov (United States)

    Malekshahi, Moslem

    2018-01-01

    In this study, propagation of an intense laser pulse through collisional, homogenous, magnetized plasma has been investigated. The plasma is embedded in an external magnetic field with the amplitude and variable direction being constant. The complex dispersion relation of the plasma medium has been obtained that predicates the Faraday rotation effect. The paraxial wave equation has been used for the study of propagation of laser pulse in plasma. The nonlinear current density vector as a source of wave equation is obtained by motion equation and continuity equation of plasma free electrons. Using the source dependent expansion method, the evolution of laser pulse spot size has been investigated. It is shown that the spot size of the laser pulse is dependent on the strength and direction of the external magnetic field significantly. The effect of collision frequency on the evolution of spot size has been studied. The space damping rate of laser pulse power along the propagation length due to collision is obtained. Results show that the increase in the external magnetic field strength increases the rate of laser energy loss.

  3. Speciation and extinction drive the appearance of directional range size evolution in phylogenies and the fossil record.

    Science.gov (United States)

    Pigot, Alex L; Owens, Ian P F; Orme, C David L

    2012-01-01

    While the geographic range of a species is a fundamental unit of macroecology and a leading predictor of extinction risk, the evolutionary dynamics of species' ranges remain poorly understood. Based on statistical associations between range size and species age, many studies have claimed support for general models of range evolution in which the area occupied by a species varies predictably over the course of its life. Such claims have been made using both paleontological data and molecular estimates of the age of extant species. However, using a stochastic model, we show that the appearance of trends in range size with species' age can arise even when range sizes have evolved at random through time. This occurs because the samples of species used in existing studies are likely to be biased with respect to range size: for example, only those species that happened to have large or expanding ranges are likely to survive to the present, while extinct species will tend to be those whose ranges, by chance, declined through time. We compared the relationship between the age and range size of species arising under our stochastic model to those observed across 1,269 species of extant birds and mammals and 140 species of extinct Cenozoic marine mollusks. We find that the stochastic model is able to generate the full spectrum of empirical age-area relationships, implying that such trends cannot be simply interpreted as evidence for models of directional range size evolution. Our results therefore challenge the theory that species undergo predictable phases of geographic expansion and contraction through time.

  4. Speciation and Extinction Drive the Appearance of Directional Range Size Evolution in Phylogenies and the Fossil Record

    Science.gov (United States)

    Pigot, Alex L.; Owens, Ian P. F.; Orme, C. David L.

    2012-01-01

    While the geographic range of a species is a fundamental unit of macroecology and a leading predictor of extinction risk, the evolutionary dynamics of species' ranges remain poorly understood. Based on statistical associations between range size and species age, many studies have claimed support for general models of range evolution in which the area occupied by a species varies predictably over the course of its life. Such claims have been made using both paleontological data and molecular estimates of the age of extant species. However, using a stochastic model, we show that the appearance of trends in range size with species' age can arise even when range sizes have evolved at random through time. This occurs because the samples of species used in existing studies are likely to be biased with respect to range size: for example, only those species that happened to have large or expanding ranges are likely to survive to the present, while extinct species will tend to be those whose ranges, by chance, declined through time. We compared the relationship between the age and range size of species arising under our stochastic model to those observed across 1,269 species of extant birds and mammals and 140 species of extinct Cenozoic marine mollusks. We find that the stochastic model is able to generate the full spectrum of empirical age–area relationships, implying that such trends cannot be simply interpreted as evidence for models of directional range size evolution. Our results therefore challenge the theory that species undergo predictable phases of geographic expansion and contraction through time. PMID:22371689

  5. Speciation and extinction drive the appearance of directional range size evolution in phylogenies and the fossil record.

    Directory of Open Access Journals (Sweden)

    Alex L Pigot

    Full Text Available While the geographic range of a species is a fundamental unit of macroecology and a leading predictor of extinction risk, the evolutionary dynamics of species' ranges remain poorly understood. Based on statistical associations between range size and species age, many studies have claimed support for general models of range evolution in which the area occupied by a species varies predictably over the course of its life. Such claims have been made using both paleontological data and molecular estimates of the age of extant species. However, using a stochastic model, we show that the appearance of trends in range size with species' age can arise even when range sizes have evolved at random through time. This occurs because the samples of species used in existing studies are likely to be biased with respect to range size: for example, only those species that happened to have large or expanding ranges are likely to survive to the present, while extinct species will tend to be those whose ranges, by chance, declined through time. We compared the relationship between the age and range size of species arising under our stochastic model to those observed across 1,269 species of extant birds and mammals and 140 species of extinct Cenozoic marine mollusks. We find that the stochastic model is able to generate the full spectrum of empirical age-area relationships, implying that such trends cannot be simply interpreted as evidence for models of directional range size evolution. Our results therefore challenge the theory that species undergo predictable phases of geographic expansion and contraction through time.

  6. Thumb motor performance varies by movement orientation, direction, and device size during single-handed mobile phone use.

    Science.gov (United States)

    Trudeau, Matthieu B; Udtamadilok, Tawan; Karlson, Amy K; Dennerlein, Jack T

    2012-02-01

    The aim of this study was to determine if thumb motor performance metrics varied by movement orientation, direction, and device size during single-handed use of a mobile phone device. With the increased use of mobile phones, understanding how design factors affect and improve performance can provide better design guidelines. A repeated measures laboratory experiment of 20 right-handed participants measured the thumb tip's 3-D position relative to a phone during reciprocal tapping tasks across four phone designs and four thumb tip movement orientations. Each movement orientation included two movement directions: an "outward" direction consisting in CMC (carpometacarpal) joint flexion or abduction movements and an "inward" direction consisting in CMC joint extension or adduction movements. Calculated metrics of the thumb's motor performance were Fitts' effective width and index of performance. Index of performance varied significantly across phones, with performance being generally better for the smaller devices. Performance was also significantly higher for adduction-abduction movement orientations compared to flexion-extension, and for "outward" compared to "inward" movement directions. For single-handed device use, adduction-abduction-type movements on smaller phones lead to better thumb performance. The results from this study can be used to design new mobile phone devices and keypad interfaces that optimize specific thumb motions to improve the user-interface experience during single-handed use.

  7. Visual Analysis of Swarm and Geomagnetic Model Data

    Science.gov (United States)

    Santillan Pedrosa, Daniel; Triebnig, Gerhard

    2016-08-01

    ESA Swarm data is available for anyone to use via the virtual research platform "VirES for Swarm" (http://vires.services). A highly interactive data manipulation and retrieval interface is provided for the magnetic products of the European Space Agency (ESA) Swarm constellation mission. It includes tools for studying various Earth magnetic models and for comparing them to the Swarm satellite measurements and given solar activity levels.

  8. Double Flight-Modes Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Wang Yong

    2013-01-01

    Full Text Available Getting inspiration from the real birds in flight, we propose a new particle swarm optimization algorithm that we call the double flight modes particle swarm optimization (DMPSO in this paper. In the DMPSO, each bird (particle can use both rotational flight mode and nonrotational flight mode to fly, while it is searching for food in its search space. There is a King in the swarm of birds, and the King controls each bird’s flight behavior in accordance with certain rules all the time. Experiments were conducted on benchmark functions such as Schwefel, Rastrigin, Ackley, Step, Griewank, and Sphere. The experimental results show that the DMPSO not only has marked advantage of global convergence property but also can effectively avoid the premature convergence problem and has good performance in solving the complex and high-dimensional optimization problems.

  9. Small And Medium-Sized Business Development In Regions: Establishment Of Priority Directions By The Example Of Sverdlovsk Region

    Directory of Open Access Journals (Sweden)

    Dmitry Yevgenyevich Tolmachev

    2015-03-01

    Full Text Available The paper presents the research of current small and medium-sized business development in Sverdlovsk region. It includes analysis of enterprise development statistics, Russian and international experience, sociological survey of entrepreneurs’ satisfaction of doing business conditions in Sverdlovsk region. The aim of the research was to develop proposals for business support system development in the long run for inclusion in the SME Development Strategy in Sverdlovsk region up to 2030. As a result, a set of strategic SME development directions was formulated. It includes measures aimed at business problems solving through the development of SME support tools and at addressing institutional problems of business support. The paper includes proposals for improvement of regional support system and implementation the priority SME development direction

  10. Compatibility of the IFRS for Small and Medium-sized Entities and the new EU-Accounting Directive

    Directory of Open Access Journals (Sweden)

    Gerrit Kaufhold

    2015-01-01

    Full Text Available The new EU-Accounting Directive of 26 June 2013 (DIRECTIVE 2013/34/EU has the intention to harmonize the accounting and financial reporting of enterprises in the European Union. “Think small first” is the central principle in the new EU-Accounting Directive and the new regulations have to be adopted in the laws of European member states by 20 July 2015. The International Financial Reporting Standard for Small and Medium-sized Entities (IFRS for SMEs was published in 2009 by the International Accounting Standards Board (IASB. The IASB intended to create simplified international financial reporting standards for the special needs of smaller and medium-sized enterprise. The IASB completed in May 2015 a comprehensive review of the IFRS for SMEs and made amendments to the Standard. The revised version of the IFRS for SMEs will be issued in the last quarter of 2015. The aim of the paper is to analyze the compatibility of the IFRS for SMEs and the new EU- Accounting Directive and the problems in connection with the harmonization of the European accounting legislation especially in Germany. Based on the results of the research most of the former incompatibilities could be removed, but the remaining complexity of the IFRS for SMEs and the lack of an option for the member states to adopt the IFRS for SMEs as an accounting and reporting standard besides or instead their local accounting principles will prevent the wide use of the IFRS for SMEs in Germany and in other member states of the European Union.

  11. 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.

  12. 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.

  13. 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.

  14. Extracting distinct behaviors from laboratory insect swarms

    Science.gov (United States)

    Puckett, James; Ouellette, Nicholas

    2014-03-01

    Throughout nature, self-organized collective motion in animal groups produces rich and complex behaviors. Many modeling approaches have been proposed from continuum to discrete agent based models which are capable of emulating the behavior observed in flocks and swarms. Most models assume uniformity in the way individuals interact and discard differences between individuals and changes of behavior with time. While in many cases individual differences may average out in large groups of animals, this is not likely the case for small groups. By measuring trajectories and kinematics of individual Chironomids in laboratory mating swarms, we assess the dynamics of individual behavior and discuss the impact of our results on current models.

  15. A Joint Optimal Decision on Shipment Size and Carbon Reduction under Direct Shipment and Peddling Distribution Strategies

    Directory of Open Access Journals (Sweden)

    Daiki Min

    2017-11-01

    Full Text Available Recently, much research has focused on lowering carbon emissions in logistics. This paper attempts to contribute to the literature on the joint shipment size and carbon reduction decisions by developing novel models for distribution systems under direct shipment and peddling distribution strategies. Unlike the literature that has simply investigated the effects of carbon costs on operational decisions, we address how to reduce carbon emissions and logistics costs by adjusting shipment size and making an optimal decision on carbon reduction investment. An optimal decision is made by analyzing the distribution cost including not only logistics and carbon trading costs but also the cost for adjusting carbon emission factors. No research has explicitly considered the two sources of carbon emissions, but we develop a model covering the difference in managing carbon emissions from transportation and storage. Structural analysis guides how to determine an optimal shipment size and emission factors in a closed form. Moreover, we analytically prove the possibility of reducing the distribution cost and carbon emissions at the same time. Numerical analysis follows validation of the results and demonstrates some interesting findings on carbon and distribution cost reduction.

  16. How do you tell how big something is without direct measurement? Estimating grain size using an image's spectrum

    Science.gov (United States)

    Buscombe, D.; Rubin, D. M.

    2011-12-01

    It is possible to estimate geometric properties of objects in an image without directly measuring any part of those object's geometries, using the stochastic properties of the image as revealed by its Fourier transform. The caveats are: a) there must be a sufficient number of those objects; b) there must only be one type of object (and not some other type of object as well); and c) the required attribute of those objects (for example, size) is fairly homogeneous in space. It also helps if those objects have no preferred orientation, although this is not a strict requirement. This approach is emerging as a viable alternative to thresholding-based techniques for uncovering the two-dimensional outlines of objects, from which geometrical attributes can be measured directly. These direct measurements often require operator-defined coefficients, or even an approximate idea of the size of an object in advance in order to scale filters, and they are often very sensitive to the sequence of operations performed. Individually and collectively, these make thresholding-based methods relatively inflexible. One example where direct reliable statistical estimates of geometrical form have been possible from images is in estimating mean and standard deviation of particle sizes from images of sediment. This is done by uncovering typical length scales of the particles from the image's two-dimensional power spectrum, without the need for tunable parameters. The mean and standard deviation of sizes are accurately estimated without having to measure each grain directly and compile a particle size-distribution. Simple methods have been developed for the cases of: a) images composed of a sediment surface, where the entire image is composed of irregularly shaped touching particles and there is no apparent void fraction; and b) images of irregularly shaped dilute (spatially distributed and non-touching) particles. The process of developing and testing these techniques has been hampered by: a

  17. Surgical membranes as directional delivery devices to generate tissue: testing in an ovine critical sized defect model.

    Directory of Open Access Journals (Sweden)

    Melissa L Knothe Tate

    Full Text Available PURPOSE: Pluripotent cells residing in the periosteum, a bi-layered membrane enveloping all bones, exhibit a remarkable regenerative capacity to fill in critical sized defects of the ovine femur within two weeks of treatment. Harnessing the regenerative power of the periosteum appears to be limited only by the amount of healthy periosteum available. Here we use a substitute periosteum, a delivery device cum implant, to test the hypothesis that directional delivery of endogenous periosteal factors enhances bone defect healing. METHODS: Newly adapted surgical protocols were used to create critical sized, middiaphyseal femur defects in four groups of five skeletally mature Swiss alpine sheep. Each group was treated using a periosteum substitute for the controlled addition of periosteal factors including the presence of collagen in the periosteum (Group 1, periosteum derived cells (Group 2, and autogenic periosteal strips (Group 3. Control group animals were treated with an isotropic elastomer membrane alone. We hypothesized that periosteal substitute membranes incorporating the most periosteal factors would show superior defect infilling compared to substitute membranes integrating fewer factors (i.e. Group 3>Group 2>Group 1>Control. RESULTS: Based on micro-computed tomography data, bone defects enveloped by substitute periosteum enabling directional delivery of periosteal factors exhibit superior bony bridging compared to those sheathed with isotropic membrane controls (Group 3>Group 2>Group 1, Control. Quantitative histological analysis shows significantly increased de novo tissue generation with delivery of periosteal factors, compared to the substitute periosteum containing a collagen membrane alone (Group 1 as well as compared to the isotropic control membrane. Greatest tissue generation and maximal defect bridging was observed when autologous periosteal transplant strips were included in the periosteum substitute. CONCLUSION: Periosteum

  18. 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...... 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....

  19. Swarming Bristle-Bots: Exploring Properties of Active Matter

    Science.gov (United States)

    Forstner, Martin B.; Beasock, Damian

    Active Matter describes an ubiquitous class of non-equilibrium systems that encompasses a diverse range of phenomena in the living and non-living realm. Examples are microscopic bio-filaments and their associated motor proteins, flocks of birds and fish, vibrated rods and disks, or nanoscale colloids actuated by catalytic activity on their surface. What unifies these systems is that they are all composed of self-driven units. In consequence, these systems are not driven into non-equilibrium by energy input at their boundary, but by local energy injection. As fascinating as these systems are, there are currently barely any laboratory systems that allow for controlled experiments in dry active matter. That is, systems not immersed in a fluid that can be observed without specialized equipment. Here we present a two-dimensional `active matter' system consisting of hundreds of macroscopic (~0.05 m long), modified, commercially available bristle-bots. We show that this swarm of toys classifies as active matter as it exhibits properties such as dynamic phase separation. Because of their straight forward implementation, their size and controllability, such swarms can not only answer scientific questions, but they have great potential as educational tools in teaching labs and classrooms.

  20. 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.

  1. Connective tissue differences in the strength of cooked meat across the muscle fibre direction due to test specimen size.

    Science.gov (United States)

    Lewis, G J; Purslow, P P

    1990-01-01

    Systematic variations in the tensile strenght of cooked beef M. semitendinosus across the muscle fibre direction due to the cross-sectional size of specimens are demonstrated in specimens from (a) longitudinal and (b) transverse slices. The strength perpendicular to the fibre direction of longitudinal slices of thickness 0·25-5·75 mm varied by a factor of 2, thicker slices being stronger. This factor of 2 is in approximate agreement with the difference in strength of transverse versus longitudinal slices across the fibre direction. These variations of strength due to specimen geometry are explained on the basis of the increasing likelihood of including a ribbon of the perimysial connective tissue network which is continuous along the whole length of the test piece in larger samples. The breaking strength of small cross-sectional area specimens is likely to be dominated by the strength of the endomysial-perimysial junction. Larger cross-sectioned specimens, by including continuous strands of the perimysial network, have higher strengths resulting from the necessity to break these strands. These findings highlight the need to specify specimen dimensions in tensile test results. They also show that by manipulating specimen geometry, the relative magnitude of the two mechanisms of connective tissue fracture (endomysial-perimysial separation and perimysial strand fracture) may be assessed. Copyright © 1990. Published by Elsevier Ltd.

  2. 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.

  3. 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...

  4. 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...

  5. Swarm controlled emergence for ant clustering

    DEFF Research Database (Denmark)

    Scheidler, Alexander; Merkle, Daniel; Middendorf, Martin

    2013-01-01

    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...

  6. Motion Planning Using a Memetic Evolution Algorithm for Swarm Robots

    Directory of Open Access Journals (Sweden)

    Chien-Chou Lin

    2012-05-01

    Full Text Available A hierarchical memetic algorithm (MA is proposed for the path planning and formation control of swarm robots. The proposed algorithm consists of a global path planner (GPP and a local motion planner (LMP. The GPP plans a trajectory within the Voronoi diagram (VD of the free space. An MA with a non-random initial population plans a series of configurations along the path given by the former stage. The MA locally adjusts the robot positions to search for better fitness along the gradient direction of the distance between the swarm robots and the intermediate goals (IGs. Once the optimal configuration is obtained, the best chromosomes are reserved as the initial population for the next generation. Since the proposed MA has a non-random initial population and local searching, it is more efficient and the planned path is faster compared to a traditional genetic algorithm (GA. The simulation results show that the proposed algorithm works well in terms of path smoothness and computation efficiency.

  7. Magnetic Investigations On The Okavango Giant Dyke Swarm (n Botswana)

    Science.gov (United States)

    Tshoso, G.; Dyment, J.; Aubourg, C.; Le Gall, B.; Tiercelin, J. J.; Féraud, G.; Bertrand, H.; Jourdan, F.; Kampunzu, H.

    The Okavango Giant Dyke Swarm is one of the largest mafic dyke complex world- wide. It extends as a 1500 x 100 km intrusive system across the Karoo igneous province of E. Namibia, N. Botswana and W. Zimbabwe. It is marked by prominent magnetic anomalies on the many aeromagnetic surveys acquired by mining compa- nies. Beyond the analysis of these data, ground truth evidence has been collected along a 100 km continuous section nearly perpendicular to the dyke swarm on the Shashe River, which present excellent exposures of dykes and basement host-rocks. Samples have been cored on 15 dykes for paleomagnetic and rock magnetic analy- ses. The paleomagnetic poles determined from most of the dykes is consistent with a Karoo age on the Apparent Polar Wander path for Africa and confirm the radio- metric results obtained by Ar-Ar dating technique. A very different pole is obtained for one basement dyke dated at 880 Ma. Magnetic susceptibility and natural rema- nent magnetization have been compiled and used to constrain forward modeling of the aeromagnetic anomalies. The direction of magmatic flow within individual dykes is investigated through the analysis of magnetic susceptibility anisotropy.

  8. Selecting Optimal Feature Set in High-Dimensional Data by Swarm Search

    Directory of Open Access Journals (Sweden)

    Simon Fong

    2013-01-01

    Full Text Available Selecting the right set of features from data of high dimensionality for inducing an accurate classification model is a tough computational challenge. It is almost a NP-hard problem as the combinations of features escalate exponentially as the number of features increases. Unfortunately in data mining, as well as other engineering applications and bioinformatics, some data are described by a long array of features. Many feature subset selection algorithms have been proposed in the past, but not all of them are effective. Since it takes seemingly forever to use brute force in exhaustively trying every possible combination of features, stochastic optimization may be a solution. In this paper, we propose a new feature selection scheme called Swarm Search to find an optimal feature set by using metaheuristics. The advantage of Swarm Search is its flexibility in integrating any classifier into its fitness function and plugging in any metaheuristic algorithm to facilitate heuristic search. Simulation experiments are carried out by testing the Swarm Search over some high-dimensional datasets, with different classification algorithms and various metaheuristic algorithms. The comparative experiment results show that Swarm Search is able to attain relatively low error rates in classification without shrinking the size of the feature subset to its minimum.

  9. Seed Size, the Only Factor Positively Affecting Direct Seeding Success in an Abandoned Field in Quebec, Canada

    Directory of Open Access Journals (Sweden)

    Annick St-Denis

    2013-06-01

    Full Text Available Direct tree seeding is potentially an economical technique for restoring forests on abandoned fields. However, the success of tree establishment depends on many factors related to species and seed characteristics, environmental conditions, competition and predation. We compared seedling emergence, survival and growth of six tree species of different seed sizes in a forest restoration project of abandoned fields. Species were seeded in plots with and without herbaceous vegetation and with and without protection from bird and mammal predation. Yellow birch (Betula alleghaniensis did not emerge in all treatments, paper birch (Betula papyrifera and tamarack (Larix laricina had a seedling emergence rate lower than 1%, and sugar maple (Acer saccharum had a low overall emergence rate of 6%. Seedling emergence reached 57% for northern red oak (Quercus rubra and 34% for red pine (Pinus resinosa, but survival of oak after one year was much higher (92% than pine seedlings (16%. Overall, protection from birds and mammals and elimination of the herbaceous vegetation cover had no detectable effects on seedling emergence, survival and height. Nonetheless, red oak seedlings growing in the presence of vegetation had a smaller diameter and shoot biomass and a larger specific leaf area. We conclude that only large seeded species, such as oak, should be used for forest restoration of abandoned fields by direct seeding in our region.

  10. An Improved Co-evolutionary Particle Swarm Optimization for Wireless Sensor Networks with Dynamic Deployment

    Directory of Open Access Journals (Sweden)

    Jun-Jie Ma

    2007-03-01

    Full Text Available The effectiveness of wireless sensor networks (WSNs depends on the coverage and target detection probability provided by dynamic deployment, which is usually supported by the virtual force (VF algorithm. However, in the VF algorithm, the virtual force exerted by stationary sensor nodes will hinder the movement of mobile sensor nodes. Particle swarm optimization (PSO is introduced as another dynamic deployment algorithm, but in this case the computation time required is the big bottleneck. This paper proposes a dynamic deployment algorithm which is named “virtual force directed co-evolutionary particle swarm optimization” (VFCPSO, since this algorithm combines the co-evolutionary particle swarm optimization (CPSO with the VF algorithm, whereby the CPSO uses multiple swarms to optimize different components of the solution vectors for dynamic deployment cooperatively and the velocity of each particle is updated according to not only the historical local and global optimal solutions, but also the virtual forces of sensor nodes. Simulation results demonstrate that the proposed VFCPSO is competent for dynamic deployment in WSNs and has better performance with respect to computation time and effectiveness than the VF, PSO and VFPSO algorithms.

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

    Directory of Open Access Journals (Sweden)

    Frédéric Mahé

    2015-12-01

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

  12. Swarm Satellite Antenna Phase Center Correction and Its Influence on the Precision Orbit Determination

    Directory of Open Access Journals (Sweden)

    TIAN Yingguo

    2016-12-01

    Full Text Available Receiver antenna phase center bias is a source of error must be considered in precise orbit determination using GPS. And PCV generally need multi-day observations data for joint estimation, so the estimation methods and its efficiency are particularly important. For the traditional PCV estimation method imperfect, such as the low computational efficiency, need to store days of normal equations and a priori information, this paper proposes an improved PCV synthesis method. By recursive way, the method doesn't need to store multi-day normal equations and the priori information about orbit, provide timely information PCV, then improve the efficiency of obtaining the PCV value, and provides a new way to achieve the Swarm satellite PCV solution. By the Swarm satellite precise orbit determination (POD, the result shows that the rapid PCV synthesis method can improve the efficiency of PCV synthesis, reducing the need for storage space. By comparing with external precision orbit, the result show that after the PCV correction, radial, tangential and normal precision of Swarm satellite orbit is improved, especially the normal precision most obviously, the average of about 23.3 mm; after the PCV correction, Swarm satellite orbit precision of all directions was superior to 2 cm.

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

    Science.gov (United States)

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

    2016-08-01

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

  14. Effect of directional selection for body size on fluctuating asymmetry in certain morphological traits in Drosophila ananassae.

    Science.gov (United States)

    Vishalakshi, C; Singh, B N

    2009-06-01

    Variation in the subtle differences between the right and left sides of bilateral characters or fluctuating asymmetry (FA) has been considered as an indicator of an organism's ability to cope with genetic and environmental stresses during development. However, due to inconsistency in the results of empirical studies, the relationship between FA and stress has been the subject of intense debate. In this study, we investigated whether stress caused by artificial bidirectional selection for body size has any effect on the levels of FA of different morphological traits in Drosophila ananassae. The realised heritability (h2) was higher in low-line females and high-line males, which suggests an asymmetrical response to selection for body size. Further, the levels of FA were compared across 10 generations of selection in different selection lines in both sexes for sternopleural bristle number, wing length, wing-to-thorax ratio, sex combtooth number and ovariole number. The levels of FA differed significantly among generations and selection lines but did not change markedly with directional selection. However, the levels of FA were higher in the G10 generation (at the end of selection) than G0 (at the start of selection) but lower than the G5 generation in different selection lines, suggesting that the levels of FA are not affected by the inbreeding generated during the course of selection. Also, the levels of FA in the hybrids of high and low lines were signifi cantly lower than the parental selection lines, suggesting that FA is influenced by hybridisation. These results are discussed in the framework of the literature available on FA and its relationship with stress.

  15. Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.

    Science.gov (United States)

    Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen

    2017-02-01

    Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.

  16. Scaling and spatial complementarity of tectonic earthquake swarms

    KAUST Repository

    Passarelli, Luigi

    2017-11-10

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

  17. Scaling and spatial complementarity of tectonic earthquake swarms

    Science.gov (United States)

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

    2018-01-01

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

  18. 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...

  19. A comprehensive review of swarm optimization algorithms.

    Directory of Open Access Journals (Sweden)

    Mohd Nadhir Ab Wahab

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

  20. A comprehensive review of swarm optimization algorithms.

    Science.gov (United States)

    Ab Wahab, Mohd Nadhir; Nefti-Meziani, Samia; Atyabi, Adham

    2015-01-01

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

  1. Macroscopic definition of distributed swarm morphogenesis

    Science.gov (United States)

    Aznar, Fidel; Pujol, Mar; Rizo, Ramón

    2012-12-01

    In this paper, we present a system that will be able to obtain microscopic assembly behaviours for a robotic swarm to achieve an assembly target (macroscopic model). It will be designed taking into consideration the essential features of a self-assembling system needed to be implemented in a real robotic swarm. This system is composed of a typology of generative languages PD0L, and an algorithm for generating individual rules to be processed by the robots. The assembly process will be performed in a distributed manner, and will be also designed to require minimal communication capabilities between robots. Both the expressive capacities of language and the rule generation algorithm will be demonstrated by evaluating their performance with a core set of test morphologies widely used in self-assembly tasks. Furthermore, we compare the assembly time and the number of messages required between a classic controller (centralised) and our distributed approach.

  2. 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.

  3. 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.

  4. Countering A2/AD with Swarming

    Science.gov (United States)

    2016-04-01

    inferior force can deny or delay a decisive engagement through time or attrition ultimately changing the political calculus.6 Using chess as an...deterrence in a non-nuclear scenario. Conventional deterrence is largely based on perceptions . Creating the wrong perception can cause conventional...necessarily defeat an enemy’s A2/AD strategy. Rather, the swarm needs to only create a perception that the U.S. is willing to fight within the A2/AD

  5. Two Invariants of Human-Swarm Interaction

    Science.gov (United States)

    2018-01-16

    often have formal attractors such as nest selection (Nevai & Passino, 2010) and many of the collective animal behaviors described by Sumpter (Sumpter...can be used to design swarm systems with desired fan-outs and workloads in mind . The key reason this is possible is that we are managing attractors...E., Giardina, I., et al. (2008). Interaction ruling animal collective behavior depends on topological rather than metric distance: Evidence from a

  6. Survey of Methods and Algorithms of Robot Swarm Aggregation

    Science.gov (United States)

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

    2017-01-01

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

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

    OpenAIRE

    I. A. Zikratov; A. V. Gurtov; T. V. Zikratova; Kozlova, E. V.

    2014-01-01

    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 inform...

  8. INHIBITION OF SWARMING BY UREA AND ITS DIAGNOSTIC ...

    African Journals Online (AJOL)

    The anti-swarming property of urea and effects on antibiotic susceptibility among 52 uropathogenic Proteus strains from Lagos, Nigeria were investigated. Urea caused a reduction in swarming and number of swarmed cells at 0.5% (n = 42, DOCZ = 15.5mm), 0.75% (n= 24, DOCZ = 10.7mm), 1% (n = 17, DOCZ = 3.4mm) and ...

  9. Foraging behavior analysis of swarm robotics system

    Directory of Open Access Journals (Sweden)

    Sakthivelmurugan E.

    2018-01-01

    Full Text Available Swarm robotics is a number of small robots that are synchronically works together to accomplish a given task. Swarm robotics faces many problems in performing a given task. The problems are pattern formation, aggregation, Chain formation, self-assembly, coordinated movement, hole avoidance, foraging and self-deployment. Foraging is most essential part in swarm robotics. Foraging is the task to discover the item and get back into the shell. The researchers conducted foraging experiments with random-movement of robots and they have end up with unique solutions. Most of the researchers have conducted experiments using the circular arena. The shell is placed at the centre of the arena and environment boundary is well known. In this study, an attempt is made to different strategic movements like straight line approach, parallel line approach, divider approach, expanding square approach, and parallel sweep approach. All these approaches are to be simulated by using player/stage open-source simulation software based on C and C++ programming language in Linux operating system. Finally statistical comparison will be done with task completion time of all these strategies using ANOVA to identify the significant searching strategy.

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

    Science.gov (United States)

    Sun, Tao; Xu, Ming-Hai

    2017-01-01

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

  11. Swarm: A constellation to study the Earth's magnetic field

    DEFF Research Database (Denmark)

    Friis-Christensen, Eigil; Luhr, H.; Hulot, G.

    2006-01-01

    attitude), thereby measuring the East-West gradient of the magnetic field, and the third one flying at higher attitude (530 km). High-precision and high-resolution measurements of the strength, direction and variation of the magnetic field, complemented by precise navigation, accelerometer and electric...... and its effect on Geospace, the vast region around the Earth where electrodynamic processes are influenced by the Earth's magnetic field. Scheduled for launch in 2010, the mission will comprise a constellation of three satellites, with two spacecraft flying side-by-side at lower attitude (450 km initial......The Swarm mission was selected as the 5th mission in ESA's Earth Explorer Programme in 2004. The mission will provide the best ever survey of the geomagnetic field and its temporal evolution that will lead to new insights into the Earth system by improving our understanding of the Earth's interior...

  12. Dynamic Alliance of Agriculture Productslogistics Based on Swarm Intelligence

    Science.gov (United States)

    Yao, Xinsheng; Cui, Yan; Ying, Jilai; Wei, Jianguang

    Along with the growing up of the Chinese generalized agriculture, the agriculture products logistics demands are increasing quickly in quality and quantity. Oppositely, the service of agriculture products logistics is slowly. It is very essential to study the logistics service mode suited to the tendency of the agriculture products logistics demand. The paper analyzes the common characteristic between the agriculture products logistics individual and the intelligence individual. Then, by the swarm intelligence, thedynamic alliance of agriculture products logistics is presented, the construction algorithm and the application method are given too. The paper provides a better operable development mode for the agriculture products logistics in China, which has directive meaning to improve the logistics efficiency for the socialistic new economy development and the New County Construction.

  13. Can hydroseismicity explain recurring earthquake swarms in NW-Bohemia?

    Science.gov (United States)

    Heinicke, Jens; Woith, Heiko; Alexandrakis, Catherine; Buske, Stefan; Telesca, Luciano

    2018-01-01

    Fluid driven seismicity has been observed worldwide. The occurrence of intraplate seismicity triggered by pore pressure perturbations is a widely accepted process. Past analysis of earthquake swarms in the NW-Bohemia/Vogtland region provided evidence for the diffusion of pore pressure fronts during the migration of earthquakes within each swarm. Here, we test the hypothesis whether the diffusion of hydraulically induced pore pressure perturbations from the surface to the hypocentral depth could be a valid trigger mechanism. We test this hypothesis for the earthquake swarms in the Nový Kostel focal zone based on the analysis of 121 earthquake swarms and microswarms which occurred between 1992 and 2016.

  14. Swarming behaviour and mass occurrences in the world's largest ...

    African Journals Online (AJOL)

    millipede species, Zoosphaerium neptunus, on Madagascar and its implication for conservation efforts (Diplopoda: Sphaerotheriida) ... Madagascar Conservation & Development ... KEY WORDS: Swarming behaviour, millipede, island gigantism.

  15. Characterization and Modeling of Insect Swarms Using tools from Fluid Dynamics

    Science.gov (United States)

    2016-09-01

    quantitatively measuring the flight trajectories of swarming insects and to use the resulting data to evaluate currently used models of collective...for quantitatively measuring the flight trajectories of swarming insects and to use the resulting data to evaluate currently used models of...exception was the introduction of a ground-based “swarm marker” to encourage swarm nucleation and to place the swarm in a convenient location. Once swarms

  16. Simulation of microcirculatory hemodynamics: estimation of boundary condition using particle swarm optimization.

    Science.gov (United States)

    Pan, Qing; Wang, Ruofan; Reglin, Bettina; Fang, Luping; Pries, Axel R; Ning, Gangmin

    2014-01-01

    Estimation of the boundary condition is a critical problem in simulating hemodynamics in microvascular networks. This paper proposed a boundary estimation strategy based on a particle swarm optimization (PSO) algorithm, which aims to minimize the number of vessels with inverted flow direction in comparison to the experimental observation. The algorithm took boundary values as the particle swarm and updated the position of the particles iteratively to approach the optimization target. The method was tested in a real rat mesenteric network. With random initial boundary values, the method achieved a minimized 9 segments with an inverted flow direction in the network with 546 vessels. Compared with reported literature, the current work has the advantage of a better fit with experimental observations and is more suitable for the boundary estimation problem in pulsatile hemodynamic models due to the experiment-based optimization target selection.

  17. A hybrid Radio-vision fault tolerant localization for mini UAV flying in swarm

    DEFF Research Database (Denmark)

    Latroch, Maamar; Abdelhafid, Omari; Koivo, Heikki N.

    2013-01-01

    This paper discuss the localization of one Unmanned Aerial Vehicle (UAV) when a failure of its GPS occurs and will propose a new solution based on the information collected by the swarm to localize it. we propose here an architecture for localization of a UAV with GPS signal failure in three...... dimensions based only on the estimation made by one Well Known Position UAV equipped with radio source and an Omni Directional Vision (ODV)....

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

    Science.gov (United States)

    Shapiro, S. A.

    2006-12-01

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

  19. Molecular interaction and cellular location of RecA and CheW proteins in Salmonella enterica during SOS response and their implication in swarming

    Directory of Open Access Journals (Sweden)

    Oihane Irazoki

    2016-10-01

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

  20. In search of genetic constraints limiting the evolution of egg size: direct and correlated responses to artificial selection on a prenatal maternal effector.

    Science.gov (United States)

    Pick, J L; Hutter, P; Tschirren, B

    2016-06-01

    Maternal effects are an important force in nature, but the evolutionary dynamics of the traits that cause them are not well understood. Egg size is known to be a key mediator of prenatal maternal effects with an established genetic basis. In contrast to theoretical expectations for fitness-related traits, there is a large amount of additive genetic variation in egg size observed in natural populations. One possible mechanism for the maintenance of this variation is through genetic constraints caused by a shared genetic basis among traits. Here we created replicated, divergent selection lines for maternal egg investment in Japanese quail (Coturnix japonica) to quantify the role of genetic constraints in the evolution of egg size. We found that egg size responds rapidly to selection, accompanied by a strong response in all egg components. Initially, we observed a correlated response in body size, but this response declined over time, showing that egg size and body size can evolve independently. Furthermore, no correlated response in fecundity (measured as the proportion of days on which a female laid an egg) was observed. However, the response to selection was asymmetrical, with egg size plateauing after one generation of selection in the high but not the low investment lines. We attribute this pattern to the presence of genetic asymmetries, caused by directional dominance or unequal allele frequencies. Such asymmetries may contribute to the evolutionary stasis in egg size observed in natural populations, despite a positive association between egg size and fitness.

  1. 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.

  2. 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.

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

    Science.gov (United States)

    2011-06-01

    energy options” [10]. The research of swarm robotics derives much of its inspiration from natural systems. Social insects are known to coordinate their...Monterey, California 9. CPT. Francisco J. Hederra Direccion de Investigacion , Programas y Desarrollo de la Armada Armada de Chile CHILE 10. CAPT Jeffrey Kline, USN(ret.) Naval Postgraduate School Monterey, California 91

  4. Improved cuckoo search with particle swarm optimization for ...

    Indian Academy of Sciences (India)

    Content based image retrieval (CBIR); image compression; partial recurrent neural network (PRNN); particle swarm optimization (PSO); HAARwavelet; Cuckoo Search ... are NP hard, a hybrid Particle Swarm Optimization (PSO) – Cuckoo Search algorithm (CS) is proposed to optimize the learning rate of the neural network.

  5. A new hybrid teaching–learning particle swarm optimization ...

    Indian Academy of Sciences (India)

    This paper proposes a novel hybrid teaching–learning particle swarm optimization (HTLPSO) algorithm, which merges two established nature-inspired algorithms, namely, optimization based on teaching–learning (TLBO) and particle swarm optimization (PSO). The HTLPSO merges the best half of population obtained after ...

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

    African Journals Online (AJOL)

    Swarming motility, a multicellular behaviour characterized by periodic concentric growth on solid media has severally been reported as a constraint in the clinical investigation of mixed-culture infections involving Proteus and as a requirement for virulence. While media are being formulated to restrain swarming in this ...

  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. Proteus mirabilis interkingdom swarming signals attract blow flies

    Science.gov (United States)

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

    2012-01-01

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

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

    African Journals Online (AJOL)

    Swarming motility, a multicellular behaviour characterized by periodic concentric growth on solid media has severally been reported as a constraint in the clinical ... The effects of 20 amino acids on swarming, extracellular protease activity, cellular RNA level and total protein concentration in 20 clinical Proteus strains from ...

  10. 21 CFR 201.307 - Sodium phosphates; package size limitation, warnings, and directions for over-the-counter sale.

    Science.gov (United States)

    2010-04-01

    ... sodium phosphates shall contain the following directions in boldface type immediately preceding the..., warnings, and directions for over-the-counter sale. 201.307 Section 201.307 Food and Drugs FOOD AND DRUG... directions for over-the-counter sale. (a) Reports in the medical literature and data accumulated by the Food...

  11. 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.

  12. Collective motion in Proteus mirabilis swarms

    Science.gov (United States)

    Haoran, Xu

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

  13. Human management of a robotic swarm

    OpenAIRE

    Salomons, N.; Kapellmann-Zafra, G.; Gross, R.

    2016-01-01

    This paper proposes a management algorithm that allows a human operator to organize a robotic swarm via a robot leader. When the operator requests a robot to become a leader, nearby robots suspend their activities. The operator can then request a count of the robots, and assign them into subgroups, one for each task. Once the operator releases the leader, the robots perform the tasks they were assigned to. We report a series of experiments conducted with up to 30 e-puck mobile robots. On aver...

  14. Particle Swarm Optimization and Regression Analysis II

    Science.gov (United States)

    Mohanty, Soumya D.

    2012-10-01

    In the first part of this article, Particle Swarm Optimization (PSO) was applied to the problem of optimizing knot placement in the regression spline method. Although promising for broadband signals having smooth, but otherwise unknown, waveforms, this simple approach fails in the case of narrowband signals when the carrier frequency as well as the amplitude and phase modulations are unknown. A method is presented that addresses this challenge by using PSO based regression splines for the in-phase and quadrature amplitudes separately. It is thereby seen that PSO is an effective tool for regression analysis of a broad class of signals.

  15. Test Frequency Selection Using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Zdenek Kincl

    2013-01-01

    Full Text Available The paper deals with the problem of test frequency selection for multi-frequency parametric fault diagnosis of analog linear circuits. An appropriate set of test frequencies is determined by minimizing the conditionality of the sensitivity matrix based on the system of fault equations using a global stochastic optimization. A novel method based on the Particle Swarm Optimization, which provides more accurate results and improves the convergence rate, is described. The paper provides several practical examples of its application to test frequency selection for active RC filters. A comparison of the results obtained by the proposed method and by the Genetic Algorithm is also presented.

  16. 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

    The European Space Agency (ESA) Swarm spacecraft mission is the first multisatellite ionospheric mission with two low-orbiting spacecraft that are flying in parallel at a distance of ~100–140 km, thus allowing derivation of spatial gradients of ionospheric parameters not only along the orbits...... but also in the direction perpendicular to them. A third satellite with a higher orbit regularly crosses the paths of the lower spacecraft. Using the Swarmmagnetic and electric field instruments,we present a novel technique that allows derivation of two-dimensional (2-D) maps of ionospheric conductances......, 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...

  17. A Parallel Adaptive Particle Swarm Optimization Algorithm for Economic/Environmental Power Dispatch

    Directory of Open Access Journals (Sweden)

    Jinchao Li

    2012-01-01

    Full Text Available A parallel adaptive particle swarm optimization algorithm (PAPSO is proposed for economic/environmental power dispatch, which can overcome the premature characteristic, the slow-speed convergence in the late evolutionary phase, and lacking good direction in particles’ evolutionary process. A search population is randomly divided into several subpopulations. Then for each subpopulation, the optimal solution is searched synchronously using the proposed method, and thus parallel computing is realized. To avoid converging to a local optimum, a crossover operator is introduced to exchange the information among the subpopulations and the diversity of population is sustained simultaneously. Simulation results show that the proposed algorithm can effectively solve the economic/environmental operation problem of hydropower generating units. Performance comparisons show that the solution from the proposed method is better than those from the conventional particle swarm algorithm and other optimization algorithms.

  18. Multi-Objective Optimization of Wire Antennas: Genetic Algorithms Versus Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Z. Raida

    2005-12-01

    Full Text Available The paper is aimed to the multi-objective optimization of wiremulti-band antennas. Antennas are numerically modeled using time-domainintegral-equation method. That way, the designed antennas can becharacterized in a wide band of frequencies within a single run of theanalysis. Antennas are optimized to reach the prescribed matching, toexhibit the omni-directional constant gain and to have the satisfactorypolarization purity. Results of the design are experimentally verified. The multi-objective cost function is minimized by the genetic algorithmand by the particle swarm optimization. Results of the optimization byboth the multi-objective methods are in detail compared. The combination of the time domain analysis and global optimizationmethods for the broadband antenna design and the detailed comparison ofthe multi-objective particle swarm optimization with themulti-objective genetic algorithm are the original contributions of thepaper.

  19. Solving a New Mathematical Model for Scheduling in Distribution Networks by Multi-Objective Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Rahmat Arab

    2014-01-01

    Full Text Available In this paper a novel, bi-objective mixed-integer mathematical programming has been proposed for a distribution network problem. One objective function minimizes the total purchasing, transportation and holding costs and the another objective minimizes the total amount of delayed or before time deliveries multiplied by respective durations, named "JIT distribution". Supplying the customer demand, holding and delivering products at warehouse are the most important constraints considered in this model. This model has been designed for a three-echelon distribution network consisting multiple suppliers, wholesalers and retailers to distribute multiple products with a deterministic amount of demand through either direct or indirect channels in a planning horizon. Since real-sized problems of the resulting bi-objective mixed-integer linear programming (MILP cannot be solved with exact methods, a multi objective particle swarm algorithm (MOPSO is designed of which, quality in small-sized problems is compared with the solutions obtained by the LINGO software. The computational results show that the proposed MOPSO algorithm finds good solutions in shorter times than LINGO and has acceptable running times in large-scale problems.

  20. 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.

  1. Adaptive Gradient Multiobjective Particle Swarm Optimization.

    Science.gov (United States)

    Han, Honggui; Lu, Wei; Zhang, Lu; Qiao, Junfei

    2017-10-09

    An adaptive gradient multiobjective particle swarm optimization (AGMOPSO) algorithm, based on a multiobjective gradient (stocktickerMOG) method and a self-adaptive flight parameters mechanism, is developed to improve the computation performance in this paper. In this AGMOPSO algorithm, the stocktickerMOG method is devised to update the archive to improve the convergence speed and the local exploitation in the evolutionary process. Meanwhile, the self-adaptive flight parameters mechanism, according to the diversity information of the particles, is then established to balance the convergence and diversity of AGMOPSO. Attributed to the stocktickerMOG method and the self-adaptive flight parameters mechanism, this AGMOPSO algorithm not only has faster convergence speed and higher accuracy, but also its solutions have better diversity. Additionally, the convergence is discussed to confirm the prerequisite of any successful application of AGMOPSO. Finally, with regard to the computation performance, the proposed AGMOPSO algorithm is compared with some other multiobjective particle swarm optimization algorithms and two state-of-the-art multiobjective algorithms. The results demonstrate that the proposed AGMOPSO algorithm can find better spread of solutions and have faster convergence to the true Pareto-optimal front.

  2. Joint global optimization of tomographic data based on particle swarm optimization and decision theory

    Science.gov (United States)

    Paasche, H.; Tronicke, J.

    2012-04-01

    In many near surface geophysical applications multiple tomographic data sets are routinely acquired to explore subsurface structures and parameters. Linking the model generation process of multi-method geophysical data sets can significantly reduce ambiguities in geophysical data analysis and model interpretation. Most geophysical inversion approaches rely on local search optimization methods used to find an optimal model in the vicinity of a user-given starting model. The final solution may critically depend on the initial model. Alternatively, global optimization (GO) methods have been used to invert geophysical data. They explore the solution space in more detail and determine the optimal model independently from the starting model. Additionally, they can be used to find sets of optimal models allowing a further analysis of model parameter uncertainties. Here we employ particle swarm optimization (PSO) to realize the global optimization of tomographic data. PSO is an emergent methods based on swarm intelligence characterized by fast and robust convergence towards optimal solutions. The fundamental principle of PSO is inspired by nature, since the algorithm mimics the behavior of a flock of birds searching food in a search space. In PSO, a number of particles cruise a multi-dimensional solution space striving to find optimal model solutions explaining the acquired data. The particles communicate their positions and success and direct their movement according to the position of the currently most successful particle of the swarm. The success of a particle, i.e. the quality of the currently found model by a particle, must be uniquely quantifiable to identify the swarm leader. When jointly inverting disparate data sets, the optimization solution has to satisfy multiple optimization objectives, at least one for each data set. Unique determination of the most successful particle currently leading the swarm is not possible. Instead, only statements about the Pareto

  3. New tools for characterizing swarming systems: A comparison of minimal models

    Science.gov (United States)

    Huepe, Cristián; Aldana, Maximino

    2008-05-01

    We compare three simple models that reproduce qualitatively the emergent swarming behavior of bird flocks, fish schools, and other groups of self-propelled agents by using a new set of diagnosis tools related to the agents’ spatial distribution. Two of these correspond in fact to different implementations of the same model, which had been previously confused in the literature. All models appear to undergo a very similar order-to-disorder phase transition as the noise level is increased if we only compare the standard order parameter, which measures the degree of agent alignment. When considering our novel quantities, however, their properties are clearly distinguished, unveiling previously unreported qualitative characteristics that help determine which model best captures the main features of realistic swarms. Additionally, we analyze the agent clustering in space, finding that the distribution of cluster sizes is typically exponential at high noise, and approaches a power-law as the noise level is reduced. This trend is sometimes reversed at noise levels close to the phase transition, suggesting a non-trivial critical behavior that could be verified experimentally. Finally, we study a bi-stable regime that develops under certain conditions in large systems. By computing the probability distributions of our new quantities, we distinguish the properties of each of the coexisting metastable states. Our study suggests new experimental analyses that could be carried out to characterize real biological swarms.

  4. Flight and swarming behaviour of Culicoides species (Diptera: Ceratopogonidae) on a livestock farm in Northern Spain.

    Science.gov (United States)

    Gonza Lez, Mikel; Alarco N-Elbal, Pedro M; Venter, Gert J; Lo Pez, Sergio

    2017-06-30

    The efficacy of sweep nets and a CDC white light-suction trap for the sampling of Culicoides species (Diptera: Ceratopogonidae) were compared on a livestock farm in Northern Spain during the Summer of 2013. A total of 6,082 specimens representing 26 species were collected with sweep nets in 4 areas at di erent heights (ground level, 1.5 m, and 3 m), and 8,463 specimens representing 28 species with a single white light trap. Eight species - Culicoides brunnicans, Culicoides punctatus, Culicoides obsoletus/Culicoides scoticus, Culicoides lupicaris, Culcoides picturatus, Culicoides achrayi, and Culicoides simulator - were dominant and accounted for 97.4% and 97.2% of the total specimens collected with both methods, sweep nets, and light traps, respectively. The sex ratios with sweep netting and light trapping were strongly female biased (78.4% and 97.1%, respectively). Nulliparous and parous females were predominantly captured with both methods. A high percentage (17%) of gravid females was, however, captured on manure at ground level while sweeping. Searches for male swarms revealed the presence of several C. punctatus swarms consisting of 26 to 196 males and 3 swarms of C. obsoletus that ranged from 1 to 12 males in size. This study suggested that both methods are suitable and complementary tools for Culicoides sampling.

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

    Science.gov (United States)

    Conn, Tracie; Dono Perez, Andres

    2017-01-01

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

  6. Water surface tension modulates the swarming mechanics of Bacillus subtilis.

    Science.gov (United States)

    Ke, Wan-Ju; Hsueh, Yi-Huang; Cheng, Yu-Chieh; Wu, Chih-Ching; Liu, Shih-Tung

    2015-01-01

    Many Bacillus subtilis strains swarm, often forming colonies with tendrils on agar medium. It is known that B. subtilis swarming requires flagella and a biosurfactant, surfactin. In this study, we find that water surface tension plays a role in swarming dynamics. B. subtilis colonies were found to contain water, and when a low amount of surfactin is produced, the water surface tension of the colony restricts expansion, causing bacterial density to rise. The increased density induces a quorum sensing response that leads to heightened production of surfactin, which then weakens water surface tension to allow colony expansion. When the barrier formed by water surface tension is breached at a specific location, a stream of bacteria swarms out of the colony to form a tendril. If a B. subtilis strain produces surfactin at levels that can substantially weaken the overall water surface tension of the colony, water floods the agar surface in a thin layer, within which bacteria swarm and migrate rapidly. This study sheds light on the role of water surface tension in regulating B. subtilis swarming, and provides insight into the mechanisms underlying swarming initiation and tendril formation.

  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. 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.

  9. 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.

  10. 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.

  11. Analog Circuit Fault Diagnosis Approach Based on Improved Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Ming-Fang WANG

    2014-07-01

    Full Text Available The basic thought of particle swarm optimization is introduced firstly, then particle swarm optimization algorithm model is established. The application of the improved particle swarm optimization algorithm to power supply system fault diagnosis is analyzed in accordance with problem of the algorithm, and migration strategy is added to particle swarm optimization algorithm. Finally the parameters of the wide area damping controller are adjusted by the improved particle swarm optimization algorithm.

  12. 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

  13. Adaptive Parameters for a Modified Comprehensive Learning Particle Swarm Optimizer

    Directory of Open Access Journals (Sweden)

    Yu-Jun Zheng

    2012-01-01

    Full Text Available Particle swarm optimization (PSO is a stochastic optimization method sensitive to parameter settings. The paper presents a modification on the comprehensive learning particle swarm optimizer (CLPSO, which is one of the best performing PSO algorithms. The proposed method introduces a self-adaptive mechanism that dynamically changes the values of key parameters including inertia weight and acceleration coefficient based on evolutionary information of individual particles and the swarm during the search. Numerical experiments demonstrate that our approach with adaptive parameters can provide comparable improvement in performance of solving global optimization problems.

  14. 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...

  15. Frog Swarms: Earthquake Precursors or False Alarms?

    Directory of Open Access Journals (Sweden)

    Rachel A. Grant

    2013-10-01

    Full Text Available In short-term earthquake risk forecasting, the avoidance of false alarms is of utmost importance to preclude the possibility of unnecessary panic among populations in seismic hazard areas. Unusual animal behaviour prior to earthquakes has been reported for millennia but has rarely been scientifically documented. Recently large migrations or unusual behaviour of amphibians have been linked to large earthquakes, and media reports of large frog and toad migrations in areas of high seismic risk such as Greece and China have led to fears of a subsequent large earthquake. However, at certain times of year large migrations are part of the normal behavioural repertoire of amphibians. News reports of “frog swarms” from 1850 to the present day were examined for evidence that this behaviour is a precursor to large earthquakes. It was found that only two of 28 reported frog swarms preceded large earthquakes (Sichuan province, China in 2008 and 2010. All of the reported mass migrations of amphibians occurred in late spring, summer and autumn and appeared to relate to small juvenile anurans (frogs and toads. It was concluded that most reported “frog swarms” are actually normal behaviour, probably caused by juvenile animals migrating away from their breeding pond, after a fruitful reproductive season. As amphibian populations undergo large fluctuations in numbers from year to year, this phenomenon will not occur on a yearly basis but will depend on successful reproduction, which is related to numerous climatic and geophysical factors. Hence, most large swarms of amphibians, particularly those involving very small frogs and occurring in late spring or summer, are not unusual and should not be considered earthquake precursors. In addition, it is likely that reports of several mass migration of small toads prior to the Great Sichuan Earthquake in 2008 were not linked to the subsequent M = 7.9 event (some occurred at a great distance from the epicentre

  16. 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.

  17. The 2012 Brawley swarm triggered by injection-induced aseismic slip

    Science.gov (United States)

    Wei, Shengji; Avouac, Jean-Philippe; Hudnut, Kenneth W.; Donnellan, Andrea; Parker, Jay W.; Graves, Robert W.; Helmberger, Don; Fielding, Eric; Liu, Zhen; Cappa, Frederic; Eneva, Mariana

    2015-07-01

    It has long been known that fluid injection or withdrawal can induce earthquakes, but the underlying mechanisms remain elusive. For example, the 2012 Brawley swarm, which produced two strike-slip shocks with magnitudes larger than 5.3 and surface ruptures in the close vicinity of a geothermal field, started with earthquakes about 5 km deeper than the injection depth (∼1.5 km). This makes the causality between the injection and seismicity unclear. Here, we jointly analyze broadband and strong motion waveforms, UAVSAR, leveling measurements and field observations to reveal the detailed seismic and aseismic faulting behaviors associated with the 2012 Brawley swarm. In particular, path calibration established from smaller events in the swarm allows waveform inversion to be conducted up to 3 Hz to resolve finite rupture process of the Mw 4.7 normal event. Our results show that the 2012 earthquake sequence was preceded by aseismic slip on a shallow normal fault beneath the geothermal field. Aseismic slip initiated in 2010 when injection rate rapidly increased and triggered the following earthquakes subsequently, including unusually shallow and relatively high frequency seismic excitations on the normal fault. In this example, seismicity is induced indirectly by fluid injection, a result of mediation by aseismic creep, rather than directly by a pore pressure increase at the location of the earthquakes.

  18. Homogeneous swarm of high-Reynolds-number bubbles rising within a thin gap. Part 1: Bubble dynamics

    OpenAIRE

    Bouche, Emmanuella; Roig, Véronique; Risso, Frédéric; Billet, Anne-Marie

    2012-01-01

    The spatial distribution, the velocity statistics and the dispersion of the gas phase have been investigated experimentally in a homogeneous swarm of bubbles confined within a thin gap. In the considered flow regime, the bubbles rise on oscillatory paths while keeping a constant shape. They are followed by unstable wakes which are strongly attenuated due to wall friction. According to the direction that is considered, the physical mechanisms are totally different. In the vertical direction, t...

  19. Swarm of bees and particles algorithms in the problem of gradual failure reliability assurance

    Directory of Open Access Journals (Sweden)

    M. F. Anop

    2015-01-01

    Full Text Available Probability-statistical framework of reliability theory uses models based on the chance failures analysis. These models are not functional and do not reflect relation of reliability characteristics to the object performance. At the same time, a significant part of the technical systems failures are gradual failures caused by degradation of the internal parameters of the system under the influence of various external factors.The paper shows how to provide the required level of reliability at the design stage using a functional model of a technical object. Paper describes the method for solving this problem under incomplete initial information, when there is no information about the patterns of technological deviations and degradation parameters, and the considered system model is a \\black box" one.To this end, we formulate the problem of optimal parametric synthesis. It lies in the choice of the nominal values of the system parameters to satisfy the requirements for its operation and take into account the unavoidable deviations of the parameters from their design values during operation. As an optimization criterion in this case we propose to use a deterministic geometric criterion \\reliability reserve", which is the minimum distance measured along the coordinate directions from the nominal parameter value to the acceptability region boundary rather than statistical values.The paper presents the results of the application of heuristic swarm intelligence methods to solve the formulated optimization problem. Efficiency of particle swarm algorithms and swarm of bees one compared with undirected random search algorithm in solving a number of test optimal parametric synthesis problems in three areas: reliability, convergence rate and operating time. The study suggests that the use of a swarm of bees method for solving the problem of the technical systems gradual failure reliability ensuring is preferred because of the greater flexibility of the

  20. IDENTIFICATION OF EARTHQUAKE AFTERSHOCK AND SWARM SEQUENCES IN THE BAIKAL RIFT ZONE

    Directory of Open Access Journals (Sweden)

    N. A. Radziminovich

    2015-09-01

    Full Text Available The catalog of earthquakes (КR³6.6 which occurred in the Baikal rift zone (BRZ was declastered, and the results are presented in the article. Aftershocks of seismic events (КR³12.5 were determined by the software developed by V.B. Smirnov (Lomonosov Moscow State University with application of the algorithm co-authored by G.M. Molchan and O.E. Dmitrieva. To ensure proper control of the software application, aftershocks were also selected manually. The results of declustering show that aftershocks of the earthquakes (КR³12.5 account for about 25 per cent of all seismic events in the regional catalog. Aftershocks accompanied 90 per cent of all the earthquakes considered as main shocks. Besides, earthquake swarms, including events with КR³11, were identified. The results of this study show that, in the BRZ, the swarms and strong events with aftershocks are not spatially separated, and this conclusion differs from the views of the previous studies that reviewed data from a shorter observation period. Moreover, it is noted that the swarms may consist of several main shocks accompanied by aftershocks. The data accumulated over the last fifty years of instrumental observations support the conclusion made earlier that the swarms in BRZ occur mainly in the north-eastward direction from Lake Baikal and also confirm the trend of a small number of aftershocks accompanying earthquakes in the south-western part of the Baikal rift zone.

  1. Inherent noise can facilitate coherence in collective swarm motion.

    Science.gov (United States)

    Yates, Christian A; Erban, Radek; Escudero, Carlos; Couzin, Iain D; Buhl, Jerome; Kevrekidis, Ioannis G; Maini, Philip K; Sumpter, David J T

    2009-04-07

    Among the most striking aspects of the movement of many animal groups are their sudden coherent changes in direction. Recent observations of locusts and starlings have shown that this directional switching is an intrinsic property of their motion. Similar direction switches are seen in self-propelled particle and other models of group motion. Comprehending the factors that determine such switches is key to understanding the movement of these groups. Here, we adopt a coarse-grained approach to the study of directional switching in a self-propelled particle model assuming an underlying one-dimensional Fokker-Planck equation for the mean velocity of the particles. We continue with this assumption in analyzing experimental data on locusts and use a similar systematic Fokker-Planck equation coefficient estimation approach to extract the relevant information for the assumed Fokker-Planck equation underlying that experimental data. In the experiment itself the motion of groups of 5 to 100 locust nymphs was investigated in a homogeneous laboratory environment, helping us to establish the intrinsic dynamics of locust marching bands. We determine the mean time between direction switches as a function of group density for the experimental data and the self-propelled particle model. This systematic approach allows us to identify key differences between the experimental data and the model, revealing that individual locusts appear to increase the randomness of their movements in response to a loss of alignment by the group. We give a quantitative description of how locusts use noise to maintain swarm alignment. We discuss further how properties of individual animal behavior, inferred by using the Fokker-Planck equation coefficient estimation approach, can be implemented in the self-propelled particle model to replicate qualitatively the group level dynamics seen in the experimental data.

  2. Inherent noise can facilitate coherence in collective swarm motion

    KAUST Repository

    Yates, C. A.

    2009-03-31

    Among the most striking aspects of the movement of many animal groups are their sudden coherent changes in direction. Recent observations of locusts and starlings have shown that this directional switching is an intrinsic property of their motion. Similar direction switches are seen in self-propelled particle and other models of group motion. Comprehending the factors that determine such switches is key to understanding the movement of these groups. Here, we adopt a coarse-grained approach to the study of directional switching in a self-propelled particle model assuming an underlying one-dimensional Fokker-Planck equation for the mean velocity of the particles. We continue with this assumption in analyzing experimental data on locusts and use a similar systematic Fokker-Planck equation coefficient estimation approach to extract the relevant information for the assumed Fokker-Planck equation underlying that experimental data. In the experiment itself the motion of groups of 5 to 100 locust nymphs was investigated in a homogeneous laboratory environment, helping us to establish the intrinsic dynamics of locust marching bands. We determine the mean time between direction switches as a function of group density for the experimental data and the self-propelled particle model. This systematic approach allows us to identify key differences between the experimental data and the model, revealing that individual locusts appear to increase the randomness of their movements in response to a loss of alignment by the group. We give a quantitative description of how locusts use noise to maintain swarm alignment. We discuss further how properties of individual animal behavior, inferred by using the Fokker-Planck equation coefficient estimation approach, can be implemented in the self-propelled particle model to replicate qualitatively the group level dynamics seen in the experimental data.

  3. On the link between particle size and deviations from the Beer-Lambert-Bouguer law for direct transmission

    Science.gov (United States)

    Larsen, Michael L.; Clark, Aaron S.

    2014-01-01

    Ballistic photon models of radiative transfer in discrete absorbing random media have demonstrated deviations from the Beer-Lambert-Bouguer law of exponential attenuation. A number of theoretical constructs to quantify the deviation from the Beer-Lambert-Bouguer law have appeared in the literature, several of which rely principally on a statistical measure related to the statistics of the absorber spatial positions alone. Here, we utilize a simple computational model to explore the interplay between the geometric size of the absorbing obstacles and the statistics governing the placement of the absorbers in the volume. We find that a description of the volume that depends on particle size and the spatial statistics of absorbers is not sufficient to fully characterize deviations from the Beer-Lambert-Bouguer law. Implications for future further theoretical and computational explorations of the problem are explored.

  4. 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.

  5. Particle Swarm Optimization and regression analysis I

    Science.gov (United States)

    Mohanty, Souyma D.

    2012-04-01

    Particle Swarm Optimization (PSO) is now widely used in many problems that require global optimization of high-dimensional and highly multi-modal functions. However, PSO has not yet seen widespread use in astronomical data analysis even though optimization problems in this field have become increasingly complex. In this two-part article, we first provide an overview of the PSO method in the concrete context of a ubiquitous problem in astronomy, namely, regression analysis. In particular, we consider the problem of optimizing the placement of knots in regression based on cubic splines (spline smoothing). The second part will describe an in-depth investigation of PSO in some realistic data analysis challenges.

  6. 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.

  7. Direct observation of enhanced magnetism in individual size- and shape-selected 3 d transition metal nanoparticles

    Science.gov (United States)

    Kleibert, Armin; Balan, Ana; Yanes, Rocio; Derlet, Peter M.; Vaz, C. A. F.; Timm, Martin; Fraile Rodríguez, Arantxa; Béché, Armand; Verbeeck, Jo; Dhaka, R. S.; Radovic, Milan; Nowak, Ulrich; Nolting, Frithjof

    2017-05-01

    Magnetic nanoparticles are critical building blocks for future technologies ranging from nanomedicine to spintronics. Many related applications require nanoparticles with tailored magnetic properties. However, despite significant efforts undertaken towards this goal, a broad and poorly understood dispersion of magnetic properties is reported, even within monodisperse samples of the canonical ferromagnetic 3 d transition metals. We address this issue by investigating the magnetism of a large number of size- and shape-selected, individual nanoparticles of Fe, Co, and Ni using a unique set of complementary characterization techniques. At room temperature, only superparamagnetic behavior is observed in our experiments for all Ni nanoparticles within the investigated sizes, which range from 8 to 20 nm. However, Fe and Co nanoparticles can exist in two distinct magnetic states at any size in this range: (i) a superparamagnetic state, as expected from the bulk and surface anisotropies known for the respective materials and as observed for Ni, and (ii) a state with unexpected stable magnetization at room temperature. This striking state is assigned to significant modifications of the magnetic properties arising from metastable lattice defects in the core of the nanoparticles, as concluded by calculations and atomic structural characterization. Also related with the structural defects, we find that the magnetic state of Fe and Co nanoparticles can be tuned by thermal treatment enabling one to tailor their magnetic properties for applications. This paper demonstrates the importance of complementary single particle investigations for a better understanding of nanoparticle magnetism and for full exploration of their potential for applications.

  8. 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

  9. Approaches for the Direct estimation of rate of increase in population size (λ) using capture-recapture data

    Science.gov (United States)

    James D. Nichols; Scott T. Sillett; James E. Hines; Richard T. Holmes

    2005-01-01

    Recent developments in the modeling of capture-recapture data permit the direct estimation and modeling of population growth rate Pradel (1996). Resulting estimates reflect changes in numbers of birds on study areas, and such changes result from movement as well as survival and reproductive recruitment. One measure of the “importance” of a...

  10. Bristle-Bots: a model system for locomotion and swarming

    Science.gov (United States)

    Giomi, Luca; Hawley-Weld, Nico; Mahadevan, L.

    2012-02-01

    The term swarming describes the ability of a group of similarly sized organisms to move coherently in space and time. This behavior is ubiquitous among living systems: it occurs in sub-cellular systems, bacteria, insects, fish, birds, pedestrians and in general in nearly any group of individuals endowed with the ability to move and sense. Here we address the problem of the origin of collective behavior in systems of self-propelled agents whose only social capability is given by aligning contact interactions. Our model system consists of a collection of Bristle-Bots, simple automata made from a toothbrush and the vibrating device of a cellular phone. When Bristle-Bots are confined in a limited space, increasing their number drives a transition from a disordered and uncoordinated motion to an organized collective behavior. This can occur through the formation of a swirling cluster of robots or a collective dynamical arrest, according to the type of locomotion implemented in the single devices. It is possible to move between these two major regimes by adjusting a single construction parameter.

  11. 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...

  12. Algorithmic requirements for swarm intelligence in differently coupled collective systems.

    Science.gov (United States)

    Stradner, Jürgen; Thenius, Ronald; Zahadat, Payam; Hamann, Heiko; Crailsheim, Karl; Schmickl, Thomas

    2013-05-01

    Swarm systems are based on intermediate connectivity between individuals and dynamic neighborhoods. In natural swarms self-organizing principles bring their agents to that favorable level of connectivity. They serve as interesting sources of inspiration for control algorithms in swarm robotics on the one hand, and in modular robotics on the other hand. In this paper we demonstrate and compare a set of bio-inspired algorithms that are used to control the collective behavior of swarms and modular systems: BEECLUST, AHHS (hormone controllers), FGRN (fractal genetic regulatory networks), and VE (virtual embryogenesis). We demonstrate how such bio-inspired control paradigms bring their host systems to a level of intermediate connectivity, what delivers sufficient robustness to these systems for collective decentralized control. In parallel, these algorithms allow sufficient volatility of shared information within these systems to help preventing local optima and deadlock situations, this way keeping those systems flexible and adaptive in dynamic non-deterministic environments.

  13. 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...

  14. 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.

  15. 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......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...

  16. 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.

  17. 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...

  18. 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.

  19. Seismotectonics of the Nicobar Swarm and the geodynamic implications for the 2004 Great Sumatran Earthquake

    Science.gov (United States)

    Lister, Gordon

    2017-04-01

    facilitated by hydrothermal activity related to a seamount, or by magma intrusion. However, the swarm is located where the transpressional regime of the Sumatran strike-slip fault system changes to that of the 'microplate-bounding' transtensional wrench involved in the Andaman Sea spreading centre. The swarm thus may be the result of the confluence of two tectonic modes of afterslip on the main rupture, with arc-normal compression to the south, and arc-normal extension to the north. The orientations of the controlling faults can be related to the right-lateral Sumatran strike-slip system, and to oceanic transforms in the spreading system. Faults parallel to the Andaman Sea spreading system axis reactivated as left-lateral strike-slip faults during the period of afterslip. Analysis of the orientation groups shows that the swarm involved synchronous but geometrically incompatible movements on opposing but conjugate fault plane sets with trends that are consistent with Mohr-Coulomb failure, even though the orientation groups delineated require slip in many different directions on these planes. The fault planes allow inference of regional deviatoric stress axes with the principal compressive stress parallel to the prior distortion inferred using satellite geodesy.

  20. Direct deposition of gas phase generated aerosol gold nanoparticles into biological fluids--corona formation and particle size shifts.

    Directory of Open Access Journals (Sweden)

    Christian R Svensson

    Full Text Available An ongoing discussion whether traditional toxicological methods are sufficient to evaluate the risks associated with nanoparticle inhalation has led to the emergence of Air-Liquid interface toxicology. As a step in this process, this study explores the evolution of particle characteristics as they move from the airborne state into physiological solution. Airborne gold nanoparticles (AuNP are generated using an evaporation-condensation technique. Spherical and agglomerate AuNPs are deposited into physiological solutions of increasing biological complexity. The AuNP size is characterized in air as mobility diameter and in liquid as hydrodynamic diameter. AuNP:Protein aggregation in physiological solutions is determined using dynamic light scattering, particle tracking analysis, and UV absorption spectroscopy. AuNPs deposited into homocysteine buffer form large gold-aggregates. Spherical AuNPs deposited in solutions of albumin were trapped at the Air-Liquid interface but was readily suspended in the solutions with a size close to that of the airborne particles, indicating that AuNP:Protein complex formation is promoted. Deposition into serum and lung fluid resulted in larger complexes, reflecting the formation of a more complex protein corona. UV absorption spectroscopy indicated no further aggregation of the AuNPs after deposition in solution. The corona of the deposited AuNPs shows differences compared to AuNPs generated in suspension. Deposition of AuNPs from the aerosol phase into biological fluids offers a method to study the protein corona formed, upon inhalation and deposition in the lungs in a more realistic way compared to particle liquid suspensions. This is important since the protein corona together with key particle properties (e.g. size, shape and surface reactivity to a large extent may determine the nanoparticle effects and possible translocation to other organs.

  1. 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....

  2. Investigating Ground Swarm Robotics Using Agent Based Simulation

    Science.gov (United States)

    2006-12-01

    interesting to see how alternatives like MANA (and even Pythagoras 3 ) measure up to the calling. If indeed MANA has rarely been dedicated to model swarm... Pythagoras is an agent based simulation package developed by Northrop Grumman 5 Figure 2. Simulation packages used to models robot swarms... Pythagoras , an agent based software platform developed by Northrop Grumman. 93 As mentioned before, the model is not complete without modeling the

  3. Information flow principles for plasticity in foraging robot swarms

    OpenAIRE

    Pitonakova, Lenka; Crowder, Richard; Bullock, Seth

    2016-01-01

    An important characteristic of a robot swarm that must operate in the real world is the ability to cope with changeable environments by exhibiting behavioural plasticity at the collective level. For example, a swarm of foraging robots should be able to repeatedly reorganise in order to exploit resource deposits that appear intermittently in different locations throughout their environment. In this paper, we report on simulation experiments with homogeneous foraging robot teams and show that a...

  4. Swarm Robot Systems Based on the Evolution of Personality Traits

    OpenAIRE

    Jr., Sidney Nascimento GIVIGI; SCHWARTZ, Howard M.

    2007-01-01

    Game theory may be very useful in modeling and analyzing swarms of robots. Using game theory in conjunction with traits of personalities, we achieve intelligent swarm robots. Traits of personality are characteristics of each robot that define the robots' behaviours. The environment is represented as a game and due to the evolution of the traits through a learning process, we show how the robots may react intelligently to changes in the environment. A proof of convergence f...

  5. 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.

  6. Multi-Robot Motion Planning Using Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Gerasimos G. Rigatos

    2008-06-01

    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.

  7. Effect of modulation of the particle size distributions in the direct solid analysis by total-reflection X-ray fluorescence

    Science.gov (United States)

    Fernández-Ruiz, Ramón; Friedrich K., E. Josue; Redrejo, M. J.

    2018-02-01

    The main goal of this work was to investigate, in a systematic way, the influence of the controlled modulation of the particle size distribution of a representative solid sample with respect to the more relevant analytical parameters of the Direct Solid Analysis (DSA) by Total-reflection X-Ray Fluorescence (TXRF) quantitative method. In particular, accuracy, uncertainty, linearity and detection limits were correlated with the main parameters of their size distributions for the following elements; Al, Si, P, S, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Rb, Sr, Ba and Pb. In all cases strong correlations were finded. The main conclusion of this work can be resumed as follows; the modulation of particles shape to lower average sizes next to a minimization of the width of particle size distributions, produce a strong increment of accuracy, minimization of uncertainties and limit of detections for DSA-TXRF methodology. These achievements allow the future use of the DSA-TXRF analytical methodology for development of ISO norms and standardized protocols for the direct analysis of solids by mean of TXRF.

  8. Chicken Swarm Optimization Based on Elite Opposition-Based Learning

    Directory of Open Access Journals (Sweden)

    Chiwen Qu

    2017-01-01

    Full Text Available Chicken swarm optimization is a new intelligent bionic algorithm, simulating the chicken swarm searching for food in nature. Basic algorithm is likely to fall into a local optimum and has a slow convergence rate. Aiming at these deficiencies, an improved chicken swarm optimization algorithm based on elite opposition-based learning is proposed. In cock swarm, random search based on adaptive t distribution is adopted to replace that based on Gaussian distribution so as to balance the global exploitation ability and local development ability of the algorithm. In hen swarm, elite opposition-based learning is introduced to promote the population diversity. Dimension-by-dimension greedy search mode is used to do local search for individual of optimal chicken swarm in order to improve optimization precision. According to the test results of 18 standard test functions and 2 engineering structure optimization problems, this algorithm has better effect on optimization precision and speed compared with basic chicken algorithm and other intelligent optimization algorithms.

  9. Seismotectonic significance of the 2008–2010 Walloon Brabant seismic swarm in the Brabant Massif, Belgium

    Science.gov (United States)

    Van Noten, Koen; Lecocq, Thomas; Shah, Anjana K.; Camelbeeck, Thierry

    2015-01-01

    Between 12 July 2008 and 18 January 2010 a seismic swarm occurred close to the town of Court-Saint-Etienne, 20 km SE of Brussels (Belgium). The Belgian network and a temporary seismic network covering the epicentral area established a seismic catalogue in which magnitude varies between ML -0.7 and ML 3.2. Based on waveform cross-correlation of co-located earthquakes, the spatial distribution of the hypocentre locations was improved considerably and shows a dense cluster displaying a 200 m-wide, 1.5-km long, NW-SE oriented fault structure at a depth range between 5 and 7 km, located in the Cambrian basement rocks of the Lower Palaeozoic Anglo-Brabant Massif. Waveform comparison of the largest events of the 2008–2010 swarm with an ML 4.0 event that occurred during swarm activity between 1953 and 1957 in the same region shows similar P- and S-wave arrivals at the Belgian Uccle seismic station. The geometry depicted by the hypocentral distribution is consistent with a nearly vertical, left-lateral strike-slip fault taking place in a current local WNW–ESE oriented local maximum horizontal stress field. To determine a relevant tectonic structure, a systematic matched filtering approach of aeromagnetic data, which can approximately locate isolated anomalies associated with hypocentral depths, has been applied. Matched filtering shows that the 2008–2010 seismic swarm occurred along a limited-sized fault which is situated in slaty, low-magnetic rocks of the Mousty Formation. The fault is bordered at both ends with obliquely oriented magnetic gradients. Whereas the NW end of the fault is structurally controlled, its SE end is controlled by a magnetic gradient representing an early-orogenic detachment fault separating the low-magnetic slaty Mousty Formation from the high-magnetic Tubize Formation. The seismic swarm is therefore interpreted as a sinistral reactivation of an inherited NW–SE oriented isolated fault in a weakened crust within the Cambrian core of

  10. Proterozoic Geomagnetic Field Geometry from Mafic Dyke Swarms

    Science.gov (United States)

    Panzik, J. E.; Evans, D. A.

    2012-12-01

    Pre-Mesozoic continental reconstructions and paleoclimatic inferences from paleomagnetism rely critically upon the assumption of a time-averaged geocentric axial dipole (GAD) magnetic field. We have been testing the GAD assumption empirically, by compiling paleomagnetic remanence directional variations among coeval volcanic rock suites distributed over large areas of the Earth's surface. We compute virtual geomagnetic poles (VGPs) from site-mean remanence data using either a pure GAD model, or alternative models with varying amounts of zonal quadrupole or octupole fields. Rastering through quadrupole vs. octupole space, we produce contour plots of precision/dispersion for the mean of VGPs in each computation. Using the 0-5 Ma volcanics global database as a test, our method shows results consistent with the compilations of Schneider & Kent (1990, Rev. Geophys. 28, 71-96) and McElhinny et al. (1996, JGR 101, 25007-25027), notably reproducing the reversal asymmetry in a significant (order 3%) quadrupolar contribution. Performing the same test on ancient mafic dyke swarms, the Karoo-Ferrar large igneous province (ca. 0.18 Ga) and the central Atlantic magmatic province (CAMP) (0.20 Ga) datasets are consistent with a range of models, including both GAD and independent estimates of non-GAD contributions derived from global tectonic reconstructions (Torsvik & Van der Voo, 2002, GJI 151, 771-794). The method is limited by paleolongitudinal restriction of ancient LIPs, for similarly restrictive sub-sampling of the 0-5 Ma volcanic data can generate results that differ dramatically from the global mean (e.g., the far-sided offset of VGPs relative to the spin axis). Analysis of pre-Pangean datasets is limited by the uncertainty of tectonic reconstructions, but within solely the intact North American (Laurentian) craton, the Franklin (ca. 0.72), Mackenzie (ca. 1.27) and Matachewan (2.45 Ga) dyke swarms are used as Pre-Mesozoic targets that have large areal coverage. None of the

  11. Athermal fiber laser for the SWARM absolute scalar magnetometer

    Science.gov (United States)

    Fourcault, W.; Léger, J.-M.; Costes, V.; Fratter, I.; Mondin, L.

    2017-11-01

    The Absolute Scalar Magnetometer (ASM) developed by CEA-LETI/CNES is an optically pumped 4He magnetic field sensor based on the Zeeman effect and an electronic magnetic resonance whose effects are amplified by a laser pumping process [1-2]. Consequently, the role of the laser is to pump the 4He atoms at the D0 transition as well as to allow the magnetic resonance signal detection. The ASM will be the scalar magnetic reference instrument of the three ESA Swarm satellites to be launched in 2012 in order to carry out the best ever survey of the Earth magnetic field and its temporal evolution. The sensitivity and accuracy of this magnetometer based on 4He optical pumping depend directly on the characteristics of its light source, which is the key sub-system of the sensor. We describe in this paper the selected fiber laser architecture and its wavelength stabilization scheme. Its main performance in terms of spectral emission, optical power at 1083 nm and intensity noise characteristics in the frequency bands used for the operation of the magnetometer, are then presented. Environmental testing results (thermal vacuum cycling, vibrations, shocks and ageing) are also reported at the end of this paper.

  12. Hemicellulose block copolymers made from woods for wide-range directed self-assembly lithography enabling wider range of applicable patterning size

    Science.gov (United States)

    Morita, Kazuyo; Yamamoto, Kimiko

    2017-03-01

    Xylan, one of hemicellulose family, block copolymer was newly developed for wide-range directed self-assembly lithography (DSA). Xylan is higher hydrophilic material because of having many hydroxy groups in one molecule. It means that xylan block copolymer has a possibility of high-chi block copolymer. Generally, DSA is focused on microphase separation for smaller size with high-chi block copolymer and not well known for larger size. In this study, xylan block copolymer was confirmed enabling wider range of patterning size, from smaller size to larger size. The key of xylan block copolymer is a new molecular structure of block copolymer and sugar chain control technology. Sugar content is the important parameter for not only micro-phase separation property but also line edge roughness (LER) and defects. Based on the sugar control technology, wide-range (hp 8.3nm to 26nm L/S and CD 10nm to 51nm hole) DSA patterning was demonstrated. Additionally it was confirmed that xylan block copolymer is suitable for sequential infiltration synthesis (SIS) process.

  13. Swarming and mating behavior of male Anopheles arabiensis Patton (Diptera: Culicidae) in an area of the Sterile Insect Technique Project in Dongola, northern Sudan.

    Science.gov (United States)

    Hassan, Mo'awia M; Zain, Hussam M; Basheer, Mohammed A; Elhaj, Hassab-Elrasoul F; El-Sayed, Badria B

    2014-04-01

    The problems facing the conventional mosquito control methods including resistance to insecticides have led to the development of alternative methods such as the Sterile Insect Technique (SIT) to suppress populations of the malaria vector Anopheles arabiensis in northern Sudan. This method entails the release of large numbers of irradiated males to compete against wild conspecifics for mating with virgin females in the field. The swarming and mating behaviors of this species were conducted at two field sites during the period 2009-2012 in Dongola, northern Sudan. Observations were made in the field sites and in a contained semi-field enclosure. In addition, participation of released irradiated-marked males in the swarms of wild mosquito was investigated. Swarms were observed on sunset in the vicinity of larval habitats around irrigation channel and stopped with the onset of the darkness about 21-25 min after the start. Swarms were observed above visual markers such as palm trees, bare ground, and manure. Several couples were observed leaving the swarms in copula in the direction of the sunlight. The majority of copulations were observed within 12-15 min of the start of swarming. Relatively low insemination rates (28%) of females collected from coupling pairs were observed. Irradiated-marked males were observed to join the natural swarms regularly, indicating their probable competitiveness with the other wild males. These findings enhance the feasibility of staging an SIT campaign against malaria vector in Northern State-Sudan. Copyright © 2013 International Atomic Energy Agency 2013. Published by Elsevier B.V. All rights reserved.

  14. Investigation of the effects of melt electrospinning parameters on the direct-writing fiber size using orthogonal design

    Science.gov (United States)

    He, Feng-Li; He, Jin; Deng, Xudong; Li, Da-Wei; Ahmad, Fiaz; Liu, Yang-Yang; Liu, Ya-Li; Ye, Ya-Jing; Zhang, Chen-Yan; Yin, Da-Chuan

    2017-10-01

    Melt electrospinning is a complex process, and many of the processing parameters can impact the result of fiber formation. In this paper, we conducted a systematic investigation on the impacts of the melt electrospinning parameters (including temperature, needle gauge, flow rate and collector speed) on the fiber diameter via an orthogonal design experiment. The straight single fibers were fabricated using melt electrospinning in a direct-writing way with a diameter varied from 9.68  ±  0.93 µm to 48.55  ±  3.72 µm. The results showed that the fiber diameter changed differently against different parameters: when the temperature or needle gauge increased, the fiber diameter increased first and then decreased; when the flow rate increased, the fiber diameter decreased first and then increased; when the collector speed increased, the fiber diameter decreased monotonously. We also found that the collector speed was the most influential factor while the needle gauge was least important in determining the diameter of the fiber. Moreover, the feasibility of melt electrospinning in a direct-writing way as a novel 3D printing technology had been demonstrated by fabricating both uniform and controllable structures with high accuracy, based on the optimal parameters from the orthogonal experiments. The promising results indicated that melt electrospinning can be developed as a powerful technique for fabricating miniatured parts with high resolution and controllable structures for versatile potential applications.

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

    Science.gov (United States)

    Zarzhitsky, Dimitri

    2008-07-01

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

  16. 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).

  17. Electrochemical characterization of nano-sized Pd-based catalysts as cathode materials in direct methanol fuel cells.

    Science.gov (United States)

    Choi, M; Han, C; Kim, I T; An, J C; Lee, J J; Lee, H K; Shim, J

    2011-01-01

    To improve the catalytic activity of palladium (Pd) as a cathode catalyst in direct methanol fuel cells (DMFCs), we prepared palladium-titanium oxide (Pd-TiO2) catalysts which the Pd and TiO2 nanoparticles were simultaneously impregnated on carbon. We selected Pd and TiO2 as catalytic materials because of their electrochemical stability in acid solution. The crystal structure and the loading amount of Pd and TiO2 on carbon were characterized by X-ray diffraction (XRD) and energy dispersive X-ray microanalysis (EDX). The electrochemical characterization of Pd-TiO2/C catalysts for the oxygen reduction reaction was carried out in half and single cell systems. The catalytic activities of the Pd-TiO2 catalysts were strongly influenced by the TiO2 content. In the single cell test, the Pd-TiO2 catalysts showed very comparable performance to the Pt catalyst.

  18. Effect of Kollidon VA®64 particle size and morphology as directly compressible excipient on tablet compression properties.

    Science.gov (United States)

    Chaudhary, R S; Patel, C; Sevak, V; Chan, M

    2018-01-01

    The study evaluates use of Kollidon VA®64 and a combination of Kollidon VA®64 with Kollidon VA®64 Fine as excipient in direct compression process of tablets. The combination of the two grades of material is evaluated for capping, lamination and excessive friability. Inter particulate void space is higher for such excipient due to the hollow structure of the Kollidon VA®64 particles. During tablet compression air remains trapped in the blend exhibiting poor compression with compromised physical properties of the tablets. Composition of Kollidon VA®64 and Kollidon VA®64 Fine is evaluated by design of experiment (DoE). A scanning electron microscopy (SEM) of two grades of Kollidon VA®64 exhibits morphological differences between coarse and fine grade. The tablet compression process is evaluated with a mix consisting of entirely Kollidon VA®64 and two mixes containing Kollidon VA®64 and Kollidon VA®64 Fine in ratio of 77:23 and 65:35. A statistical modeling on the results from the DoE trials resulted in the optimum composition for direct tablet compression as combination of Kollidon VA®64 and Kollidon VA®64 Fine in ratio of 77:23. This combination compressed with the predicted parameters based on the statistical modeling and applying main compression force between 5 and 15 kN, pre-compression force between 2 and 3 kN, feeder speed fixed at 25 rpm and compression range of 45-49 rpm produced tablets with hardness ranging between 19 and 21 kp, with no friability, capping, or lamination issue.

  19. Middleware Design for Swarm-Driving Robots Accompanying Humans

    Directory of Open Access Journals (Sweden)

    Min Su Kim

    2017-02-01

    Full Text Available 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.

  20. Towards large size substrates for III-V co-integration made by direct wafer bonding on Si

    Directory of Open Access Journals (Sweden)

    N. Daix

    2014-08-01

    Full Text Available We report the first demonstration of 200 mm InGaAs-on-insulator (InGaAs-o-I fabricated by the direct wafer bonding technique with a donor wafer made of III-V heteroepitaxial structure grown on 200 mm silicon wafer. The measured threading dislocation density of the In0.53Ga0.47As (InGaAs active layer is equal to 3.5 × 109 cm−2, and it does not degrade after the bonding and the layer transfer steps. The surface roughness of the InGaAs layer can be improved by chemical-mechanical-polishing step, reaching values as low as 0.4 nm root-mean-square. The electron Hall mobility in 450 nm thick InGaAs-o-I layer reaches values of up to 6000 cm2/Vs, and working pseudo-MOS transistors are demonstrated with an extracted electron mobility in the range of 2000–3000 cm2/Vs. Finally, the fabrication of an InGaAs-o-I substrate with the active layer as thin as 90 nm is achieved with a Buried Oxide of 50 nm. These results open the way to very large scale production of III-V-o-I advanced substrates for future CMOS technology nodes.

  1. Binary particle swarm optimization for operon prediction.

    Science.gov (United States)

    Chuang, Li-Yeh; Tsai, Jui-Hung; Yang, Cheng-Hong

    2010-07-01

    An operon is a fundamental unit of transcription and contains specific functional genes for the construction and regulation of networks at the entire genome level. The correct prediction of operons is vital for understanding gene regulations and functions in newly sequenced genomes. As experimental methods for operon detection tend to be nontrivial and time consuming, various methods for operon prediction have been proposed in the literature. In this study, a binary particle swarm optimization is used for operon prediction in bacterial genomes. The intergenic distance, participation in the same metabolic pathway, the cluster of orthologous groups, the gene length ratio and the operon length are used to design a fitness function. We trained the proper values on the Escherichia coli genome, and used the above five properties to implement feature selection. Finally, our study used the intergenic distance, metabolic pathway and the gene length ratio property to predict operons. Experimental results show that the prediction accuracy of this method reached 92.1%, 93.3% and 95.9% on the Bacillus subtilis genome, the Pseudomonas aeruginosa PA01 genome and the Staphylococcus aureus genome, respectively. This method has enabled us to predict operons with high accuracy for these three genomes, for which only limited data on the properties of the operon structure exists.

  2. “A Swarm in July”: Beekeeping Perspectives on the Old English Wið Ymbe Charm

    Directory of Open Access Journals (Sweden)

    Lori Ann Garner

    2011-10-01

    Full Text Available This exploration of an Old English charm against a swarm of bees (_wið ymbe_ augments and complements prior work on this enigmatic text by bringing knowledgeable and experienced beekeepers _directly_ into the discussion. Based on insights gained through sharing the text with them and inviting their reactions, this essay offers a highly collaborative and genuinely interdisciplinary interpretation of both the charm’s ritual instructions and the poetic incantation.

  3. Enabling the Direct Detection of Earth-Sized Exoplanets with the LBTI HOSTS Project: A Progress Report

    Science.gov (United States)

    Danchi, W.; Bailey, V.; Bryden, G.; Defrere, D.; Ertel, S.; Haniff, C.; Hinz, P.; Kennedy, G.; Mennesson, B.; Millan-Gabet, R.; hide

    2016-01-01

    NASA has funded a project called the Hunt for Observable Signatures of Terrestrial Systems (HOSTS) to survey nearby solar type stars to determine the amount of warm zodiacal dust in their habitable zones. The goal is not only to determine the luminosity distribution function but also to know which individual stars have the least amount of zodiacal dust. It is important to have this information for future missions that directly image exoplanets as this dust is the main source of astrophysical noise for them. The HOSTS project utilizes the Large Binocular Telescope Interferometer (LBTI), which consists of two 8.4-m apertures separated by a 14.4-m baseline on Mt. Graham, Arizona. The LBTI operates in a nulling mode in the mid-infrared spectral window (8-13 micrometers), in which light from the two telescopes is coherently combined with a 180 degree phase shift between them, producing a dark fringe at the location of the target star. In doing so the starlight is greatly reduced, increasing the contrast, analogous to a coronagraph operating at shorter wavelengths. The LBTI is a unique instrument, having only three warm reflections before the starlight reaches cold mirrors, giving it the best photometric sensitivity of any interferometer operating in the mid-infrared. It also has a superb Adaptive Optics (AO) system giving it Strehl ratios greater than 98% at 10 micrometers. In 2014 into early 2015 LBTI was undergoing commissioning. The HOSTS. project team passed its Operational Readiness Review (ORR) in April 2015. The team recently published papers on the target sample, modeling of the nulled disk images, and initial results such as the detection of warm dust around eta Corvi. Recently a paper was published on the data pipeline and on-sky performance. An additional paper is in preparation on Beta Leo. We will discuss the scientific and programmatic context for the LBTI project, and we will report recent progress, new results, and plans for the science verification

  4. New hybrid genetic particle swarm optimization algorithm to design multi-zone binary filter.

    Science.gov (United States)

    Lin, Jie; Zhao, Hongyang; Ma, Yuan; Tan, Jiubin; Jin, Peng

    2016-05-16

    The binary phase filters have been used to achieve an optical needle with small lateral size. Designing a binary phase filter is still a scientific challenge in such fields. In this paper, a hybrid genetic particle swarm optimization (HGPSO) algorithm is proposed to design the binary phase filter. The HGPSO algorithm includes self-adaptive parameters, recombination and mutation operations that originated from the genetic algorithm. Based on the benchmark test, the HGPSO algorithm has achieved global optimization and fast convergence. In an easy-to-perform optimizing procedure, the iteration number of HGPSO is decreased to about a quarter of the original particle swarm optimization process. A multi-zone binary phase filter is designed by using the HGPSO. The long depth of focus and high resolution are achieved simultaneously, where the depth of focus and focal spot transverse size are 6.05λ and 0.41λ, respectively. Therefore, the proposed HGPSO can be applied to the optimization of filter with multiple parameters.

  5. Hierarchical Swarm Model: A New Approach to Optimization

    Directory of Open Access Journals (Sweden)

    Hanning Chen

    2010-01-01

    Full Text Available This paper presents a novel optimization model called hierarchical swarm optimization (HSO, which simulates the natural hierarchical complex system from where more complex intelligence can emerge for complex problems solving. This proposed model is intended to suggest ways that the performance of HSO-based algorithms on complex optimization problems can be significantly improved. This performance improvement is obtained by constructing the HSO hierarchies, which means that an agent in a higher level swarm can be composed of swarms of other agents from lower level and different swarms of different levels evolve on different spatiotemporal scale. A novel optimization algorithm (named PS2O, based on the HSO model, is instantiated and tested to illustrate the ideas of HSO model clearly. Experiments were conducted on a set of 17 benchmark optimization problems including both continuous and discrete cases. The results demonstrate remarkable performance of the PS2O algorithm on all chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms.

  6. 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.

  7. Intelligent discrete particle swarm optimization for multiprocessor task scheduling problem

    Directory of Open Access Journals (Sweden)

    S Sarathambekai

    2017-03-01

    Full Text Available Discrete particle swarm optimization is one of the most recently developed population-based meta-heuristic optimization algorithm in swarm intelligence that can be used in any discrete optimization problems. This article presents a discrete particle swarm optimization algorithm to efficiently schedule the tasks in the heterogeneous multiprocessor systems. All the optimization algorithms share a common algorithmic step, namely population initialization. It plays a significant role because it can affect the convergence speed and also the quality of the final solution. The random initialization is the most commonly used method in majority of the evolutionary algorithms to generate solutions in the initial population. The initial good quality solutions can facilitate the algorithm to locate the optimal solution or else it may prevent the algorithm from finding the optimal solution. Intelligence should be incorporated to generate the initial population in order to avoid the premature convergence. This article presents a discrete particle swarm optimization algorithm, which incorporates opposition-based technique to generate initial population and greedy algorithm to balance the load of the processors. Make span, flow time, and reliability cost are three different measures used to evaluate the efficiency of the proposed discrete particle swarm optimization algorithm for scheduling independent tasks in distributed systems. Computational simulations are done based on a set of benchmark instances to assess the performance of the proposed algorithm.

  8. SWARM Observations of the Motion of Low-latitude Plasma Depletions Coordinated with Ground-based TEC Measurements

    Science.gov (United States)

    Valladares, C. E.; Pradipta, R.; Sheehan, R. E.; Coisson, P.; Knudsen, D. J.

    2015-12-01

    During the early phase of the SWARM mission, the distance between the trajectories of all three satellites of the constellation was tens of km and the temporal separation was of order one minute. This unique geometry allows us to conduct multiple and almost simultaneous in-situ measurements through the same low-latitude plasma depletion to investigate their spatial coherence and the motion of structures embedded within the equatorial plasma bubbles. We have used the number density measured with the Electric Field Instrument (EFI) on-board the three satellites of the SWARM constellation during December 2013 and January 2014 and concurrent TEC values obtained by ground-based GPS receivers to fully diagnose the bubble characteristics at multiple scale sizes. We have applied correlation and cross-spectra analysis to the density values measured by the EFI probes to derive the longitudinal variability of plasma density structures and their velocity. Our results indicate a very strong variability of the plasma bubbles in longitude. More specifically, it shows that structures with scale sizes corresponding to 100 and 10 seconds are not in phase. TEC values measures on the ground indicated that TEC plasma depletions moved with a velocity of order 100 m/s and have a westward tilt of order 10°. This presentation will show results for several specific days of SWARM observations during passes in the American sector.

  9. A Local and Global Search Combine Particle Swarm Optimization Algorithm for Job-Shop Scheduling to Minimize Makespan

    Directory of Open Access Journals (Sweden)

    Zhigang Lian

    2010-01-01

    Full Text Available The Job-shop scheduling problem (JSSP is a branch of production scheduling, which is among the hardest combinatorial optimization problems. Many different approaches have been applied to optimize JSSP, but for some JSSP even with moderate size cannot be solved to guarantee optimality. The original particle swarm optimization algorithm (OPSOA, generally, is used to solve continuous problems, and rarely to optimize discrete problems such as JSSP. In OPSOA, through research I find that it has a tendency to get stuck in a near optimal solution especially for middle and large size problems. The local and global search combine particle swarm optimization algorithm (LGSCPSOA is used to solve JSSP, where particle-updating mechanism benefits from the searching experience of one particle itself, the best of all particles in the swarm, and the best of particles in neighborhood population. The new coding method is used in LGSCPSOA to optimize JSSP, and it gets all sequences are feasible solutions. Three representative instances are made computational experiment, and simulation shows that the LGSCPSOA is efficacious for JSSP to minimize makespan.

  10. Simultaneous reconstruction of temperature field and radiative properties by inverse radiation analysis using stochastic particle swarm optimization

    Directory of Open Access Journals (Sweden)

    Liu Dong

    2016-01-01

    Full Text Available Simultaneous reconstruction of temperature field and radiative properties including scattering albedo and extinction coefficient is presented in a two-dimensional (2-D rectangular, absorbing, emitting and isotropically scattering gray medium from the knowledge of the exit radiative intensities received by charge-coupled device (CCD cameras at boundary surfaces. The inverse problem is formulated as a non-linear optimization problem and solved by stochastic particle swarm optimization. The effects of particle swarm size, generation number, measurement errors, and optical thickness on the accuracy of the estimation, and computing time were investigated and the results show that the temperature field and radiative properties can be reconstructed well for the exact and noisy data, but radiative properties are harder to obtain than temperature field. Moreover, the extinction coefficient is more difficult to reconstruct than scattering albedo.

  11. Effects of Annular Electromagnetic Stirring Coupled with Intercooling on Grain Refinement and Homogeneity During Direct Chill Casting of Large-Sized 7005 Alloy Billet

    Science.gov (United States)

    Luo, Yajun; Zhang, Zhifeng; Li, Bao; Gao, Mingwei; Qiu, Yang; He, Min

    2017-12-01

    To obtain a large-sized, high-quality aluminum alloy billet, an advanced uniform direct chill (UDC) casting method was developed by combining annular electromagnetic stirring (A-EMS) with intercooling in the sump. The 7005 alloy was chosen to investigate the effect of UDC on grain refinement and homogeneity during normal direct chill (NDC) casting. It was concluded that the microstructure consisting of both primary α-Al phase and secondary phases becomes finer and more homogeneous for the billets prepared with UDC casting compared to those prepared with NDC casting, and the forced cooling from both the inner and outer melt under A-EMS has a measurable effect on grain refinement and homogeneity.

  12. Effects of Annular Electromagnetic Stirring Coupled with Intercooling on Grain Refinement and Homogeneity During Direct Chill Casting of Large-Sized 7005 Alloy Billet

    Science.gov (United States)

    Luo, Yajun; Zhang, Zhifeng; Li, Bao; Gao, Mingwei; Qiu, Yang; He, Min

    2017-04-01

    To obtain a large-sized, high-quality aluminum alloy billet, an advanced uniform direct chill (UDC) casting method was developed by combining annular electromagnetic stirring (A-EMS) with intercooling in the sump. The 7005 alloy was chosen to investigate the effect of UDC on grain refinement and homogeneity during normal direct chill (NDC) casting. It was concluded that the microstructure consisting of both primary α-Al phase and secondary phases becomes finer and more homogeneous for the billets prepared with UDC casting compared to those prepared with NDC casting, and the forced cooling from both the inner and outer melt under A-EMS has a measurable effect on grain refinement and homogeneity.

  13. Position, swimming direction and group size of fin whales (Balaenoptera physalus in the presence of a fast-ferry in the Bay of Biscay

    Directory of Open Access Journals (Sweden)

    Ana S. Aniceto

    2016-07-01

    Full Text Available We analyze group size, swimming direction and the orientation of fin whales relative to a fast ferry in the Bay of Biscay. Fin whale groups (≥3 individuals were on average closer to the vessel than single individuals and pairs (F1,114 = 4.94, p = 0.028 and were more often observed within a high-risk angle ahead of the ferry (binomial probability: p = 7.60 × 10−11. Also, small groups tend to swim in the opposite direction (heading of 180° of the ferry at the starboard side (binomial test: p = 6.86 × 10−5 and at the portside (binomial test: p = 0.0156. These findings provide valuable information to improve shipping management procedures in areas at high risk for collisions.

  14. 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

  15. 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.

  16. 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.

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

    Science.gov (United States)

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

    2015-10-01

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

  18. 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...

  19. 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.       

  20. 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......) in trying to overcome the problem of premature convergence. It uses a diversity measure to control the swarm. The result is an algorithm that alternates between phases of attraction and repulsion. The performance of the ARPSO is compared to a basic PSO (bPSO) and a genetic algorithm (GA). The results show...... 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...

  1. 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.

  2. Particle swarm optimization with composite particles in dynamic environments.

    Science.gov (United States)

    Liu, Lili; Yang, Shengxiang; Wang, Dingwei

    2010-12-01

    In recent years, there has been a growing interest in the study of particle swarm optimization (PSO) in dynamic environments. This paper presents a new PSO model, called PSO with composite particles (PSO-CP), to address dynamic optimization problems. PSO-CP partitions the swarm into a set of composite particles based on their similarity using a "worst first" principle. Inspired by the composite particle phenomenon in physics, the elementary members in each composite particle interact via a velocity-anisotropic reflection scheme to integrate valuable information for effectively and rapidly finding the promising optima in the search space. Each composite particle maintains the diversity by a scattering operator. In addition, an integral movement strategy is introduced to promote the swarm diversity. Experiments on a typical dynamic test benchmark problem provide a guideline for setting the involved parameters and show that PSO-CP is efficient in comparison with several state-of-the-art PSO algorithms for dynamic optimization problems.

  3. 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.

  4. Modified Particle Swarm Optimization using Nonlinear Decreased Inertia Weight

    Directory of Open Access Journals (Sweden)

    Alrijadjis .

    2016-04-01

    Full Text Available Particle Swarm Optimization (PSO has demonstrated great performance in various optimization problems. However, PSO has weaknesses, namely premature convergence and easy to get stuck or fall into local optima for complex multimodal problems. One of the causes of these weaknesses is unbalance between exploration and exploitation ability in PSO. This paper proposes a Modified Particle Swarm Optimization (MPSO using nonlinearly decreased inertia weight called MPSO-NDW to improve the balance. The key idea of the proposed method is to control the period and decreasing rate of exploration-exploitation ability. The investigation with three famous benchmark functions shows that the accuracy, success rate, and convergence speed of the proposed MPSO-NDW is better than the common used PSO with linearly decreased inertia weight or called PSO-LDW Keywords: particle swarm optimization (PSO, premature convergence, local optima, exploration ability, exploitation ability.

  5. Estimation of Valve Stiction Using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    S. Sivagamasundari

    2011-06-01

    Full Text Available This paper presents a procedure for quantifying valve stiction in control loops based on particle swarm optimization. Measurements of the Process Variable (PV and Controller Output (OP are used to estimate the parameters of a Hammerstein system, consisting of connection of a non linear control valve stiction model and a linear process model. The parameters of the Hammerstein model are estimated using particle swarm optimization, from the input-output data by minimizing the error between the true model output and the identified model output. Using particle swarm optimization, Hammerstein models with known nonlinear structure and unknown parameters can be identified. A cost-effective optimization technique is adopted to find the best valve stiction models representing a more realistic valve behavior in the oscillating loop. Simulation and practical laboratory control system results are included, which demonstrates the effectiveness and robustness of the identification scheme.

  6. Dynamics and sources of last glacial aeolian deposition in southwest France derived from dune patterns, grain-size gradients and geochemistry, and reconstruction of efficient wind directions

    Science.gov (United States)

    Sitzia, Luca; Bertran, Pascal; Sima, Adriana; Chery, Philippe; Queffelec, Alain; Rousseau, Denis-Didier

    2017-08-01

    Dune pattern, grain-size gradients and geochemistry were used to investigate the sources and dynamics of aeolian deposition during the last glacial in southwest France. The coversands form widespread fields of low-amplitude ridges (zibars), whereas Younger Dryas parabolic dunes mainly concentrate in corridors and along rivers. Spatial modelling of grain-size gradients combined with geochemical analysis points to a genetic relationship between coversands and loess, the latter resulting primarily from dust produced by aeolian abrasion of the coversands. The alluvium of the Garonne river provided also significant amounts of dust at a more local scale. The geochemical composition of loess shows much lower scattering than that of coversands, due to stronger homogenisation during transport in the atmosphere. Overall, sandy loess and loess deposits decrease in thickness away from the coversands. Dune orientation and grain-size gradients suggest that the efficient winds blew respectively from the W to the NW during the glacial, and the W-SW during the Younger Dryas. A comparison between the wind directions derived from the proxy data and those provided by palaeoclimatic simulations suggests a change of the main transport season. Ground surface conditions and their evolution throughout the year, i.e. the length of the season with snow and frozen or moist topsoil, and the seasonal distribution of wind speeds able to cause deflation are thought to have been the main factors that controlled the transport season in the study area.

  7. Swarm intelligence metaheuristics for enhanced data analysis and optimization.

    Science.gov (United States)

    Hanrahan, Grady

    2011-09-21

    The swarm intelligence (SI) computing paradigm has proven itself as a comprehensive means of solving complicated analytical chemistry problems by emulating biologically-inspired processes. As global optimum search metaheuristics, associated algorithms have been widely used in training neural networks, function optimization, prediction and classification, and in a variety of process-based analytical applications. The goal of this review is to provide readers with critical insight into the utility of swarm intelligence tools as methods for solving complex chemical problems. Consideration will be given to algorithm development, ease of implementation and model performance, detailing subsequent influences on a number of application areas in the analytical, bioanalytical and detection sciences.

  8. MARTIAN SWARM EXPLORATION AND MAPPING USING LASER SLAM

    Directory of Open Access Journals (Sweden)

    S. Nowak

    2013-08-01

    Full Text Available 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.

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

    Science.gov (United States)

    Xu, Chuangbiao; Yang, Renhuan

    2017-12-01

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

  10. Gravity inversion of a fault by Particle swarm optimization (PSO).

    Science.gov (United States)

    Toushmalani, Reza

    2013-01-01

    Particle swarm optimization is a heuristic global optimization method and also an optimization algorithm, which is based on swarm intelligence. It comes from the research on the bird and fish flock movement behavior. In this paper we introduce and use this method in gravity inverse problem. We discuss the solution for the inverse problem of determining the shape of a fault whose gravity anomaly is known. Application of the proposed algorithm to this problem has proven its capability to deal with difficult optimization problems. The technique proved to work efficiently when tested to a number of models.

  11. 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...

  12. Nonlinear Adaptive Filters based on Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Faten BEN ARFIA

    2009-07-01

    Full Text Available This paper presents a particle swarm optimization (PSO algorithm to adjust the parameters of the nonlinear filter and to make this type of the filters more powerful for the elimination of the Gaussian noise and also the impulse noise. In this paper we apply the particle swarm optimization to the rational filters and we completed this work with the comparison between our results and other adaptive nonlinear filters like the LMS adaptive median filters and the no-adaptive rational filter.

  13. Robotic swarm concept for efficient oil spill confrontation.

    Science.gov (United States)

    Kakalis, Nikolaos M P; Ventikos, Yiannis

    2008-06-15

    This paper examines the behaviour of a distributed system/robotic swarm concept for the effective confrontation of oil spills. The system described consists of a number of identical robotic units of high-power autonomy that recover oil mechanically and are able to communicate with each other. A mathematical model that accounts for a multitude of oil weathering processes and for the concerted action of the autonomous units is implemented for this investigation. Computational assessment of the robotic swarm in weathering oil spills indicates the potential effectiveness of the method.

  14. Earthquake swarm associated with volcanic eruption, CuraCoa Reef Area, Northern Tonga, July 1973

    Directory of Open Access Journals (Sweden)

    G. K. SUTTON

    1974-06-01

    Full Text Available A submarine volcanic eruption near Curagoa Reef, first observed on 12 J u l y 1973 (U.T. f r om Tafalii Island, northern Tonga, was associated with an e a r t h q u a k e swarm in t h e same area. The swarm began about 03'1 on I I J u l y and died away gradually about 07'' on 13 J u l y , ft comprised 504 events of magnitude Mi, „2= 3.4, the largest being of magnitude Ml = 5.1. The swarm area for these comparatively low magnitude earthquakes was abnormally large The v a r i a t i o n in r a t e of e a r t h q u a k e occurrence during t h e s w a rm shows two distinct stages, one similar to t h a t in a foresliock sequence, and t h e other like t h a t in a n a f t e r s h o c k sequence, with t h e largest events occurring between t h e two. The average value of b, defining t h e f r e q u e n c y - m a g n i t u d e relationship, was high: 1.77 ± 0.15. Furthermore, this p a r a m e t e r varied during the course of t h e swarm, a decrease in t h e b value f r om 1.8 to 1.1 being followed by a sharp increase to 2.5 a f t e r t h e largest earthquakes and principal volcanic eruption. Values of seismic moment were obtained from A B for 118 e a r t h q u a k es which were well recorded by long-period seismographs. Other source charact e r i s t i c s were determined from the difference between t h e l o g a r i t hm of seismic moment and the local magnitude. The source sizes were found to he u n u s u a l l y large. There was a t i m e variation of source properties during the swarm. The v a r i a t i o n of t h e displacement shows an inverse correlation with t h e variation of the coefficient b. The swarm produced very d i s t i n c t i v e T phases, well recorded at a hydrophone near Wake Island and at seismograph stations s i t u a t e d on t h e oceanic side of the Tonga Trench: these were not recorded at seismograph stations within the island arcs.

  15. Automated Spectroscopic Analysis Using the Particle Swarm Optimization Algorithm: Implementing a Guided Search Algorithm to Autofit

    Science.gov (United States)

    Ervin, Katherine; Shipman, Steven

    2017-06-01

    While rotational spectra can be rapidly collected, their analysis (especially for complex systems) is seldom straightforward, leading to a bottleneck. The AUTOFIT program was designed to serve that need by quickly matching rotational constants to spectra with little user input and supervision. This program can potentially be improved by incorporating an optimization algorithm in the search for a solution. The Particle Swarm Optimization Algorithm (PSO) was chosen for implementation. PSO is part of a family of optimization algorithms called heuristic algorithms, which seek approximate best answers. This is ideal for rotational spectra, where an exact match will not be found without incorporating distortion constants, etc., which would otherwise greatly increase the size of the search space. PSO was tested for robustness against five standard fitness functions and then applied to a custom fitness function created for rotational spectra. This talk will explain the Particle Swarm Optimization algorithm and how it works, describe how Autofit was modified to use PSO, discuss the fitness function developed to work with spectroscopic data, and show our current results. Seifert, N.A., Finneran, I.A., Perez, C., Zaleski, D.P., Neill, J.L., Steber, A.L., Suenram, R.D., Lesarri, A., Shipman, S.T., Pate, B.H., J. Mol. Spec. 312, 13-21 (2015)

  16. 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.

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

    Science.gov (United States)

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

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

  18. Bead-size directed distribution of Pseudomonas aeruginosa results in distinct inflammatory response in a mouse model of chronic lung infection

    DEFF Research Database (Denmark)

    Christophersen, L J; Trøstrup, H; Damlund, Dina Silke Malling

    2012-01-01

    Chronic Pseudomonas aeruginosa lung infection in cystic fibrosis (CF) patients is characterized by biofilms, tolerant to antibiotics and host responses. Instead, immune responses contribute to the tissue damage. However, this may depend on localization of infection in the upper conductive...... or in the peripheral respiratory zone. To study this we produced two distinct sizes of small alginate beads (SB) and large beads (LB) containing P. aeruginosa. In total, 175 BALB/c mice were infected with either SB or LB. At day 1 the quantitative bacteriology was higher in the SB group compared to the LB group (P ... lung damage was demonstrated. Therefore, treatment of the chronic P. aeruginosa lung infection should be directed primarily at the peripheral lung zone by combined intravenous and inhalation antibiotic treatment....

  19. Human Simulated Intelligent Control with Double-Direction Dead-Zone Compensation for Joint Motion Control of a Large-Sized Boom System

    Directory of Open Access Journals (Sweden)

    Rongsheng Liu

    2015-01-01

    Full Text Available Joint motion control of a 52-meter-long five-boom system driven by proportional hydraulic system is developed. It has been considered difficult due to strong nonlinearities and parametric uncertainties, the effect of which increases with the size of booms. A human simulated intelligent control scheme is developed to improve control performance by modifying control mode and control parameters. In addition, considering the negative effects caused by frequent and redundant reverse actions of the proportional valve, a double-direction compensation scheme is proposed to deal with the dead-zone nonlinearity of proportional valve. Sinusoidal motions are implemented on a real boom system. The results indicate that HSIC controller can improve control accuracy, and dead-zone nonlinearity is effectively compensated by proposed compensation scheme without introducing frequent reverse actions of proportional valve.

  20. THE INFLUENCE OF THE SIZE OF THE ECONOMY AND EUROPEAN INTEGRATION ON FOREIGN DIRECT INVESTMENTS IN THE CENTRAL, SOUTHEASTERN AND EASTERN EUROPEAN STATES 1994-2013

    Directory of Open Access Journals (Sweden)

    Petar Kurecic

    2016-03-01

    Full Text Available The paper studies the interdependence of the economy size and foreign direct investments (FDI in the transitional economies of Central, Southeastern and Eastern Europe. In the global capitalist economy, foreign direct investments (FDI represent one of the key determinants of economic growth. Among some transitional economies, in the last 20 years, FDI represented one of factors that increased the economic growth, and in other transitional economies, the influence of FDI was minor or even negligible. In the literature devoted to the influence of FDI on economies, the research about the determinants of geographical pattern of FDI distribution usually focuses on the factors that determine why some states manage to draw FDI in higher levels than some other states. Our research focused on the transitional economies of Central, Southeastern and Eastern Europe, which were for the most part of the last 20 years net receivers of the FDI. Only a couple of these countries in the years of the current economic crisis have experienced FDI net outflow. Among the states studied, we have equally studied the EU members, as well as the non-EU members. We have tried to find similarities and differences between these two groups of states in order to determine the influence of EU membership on FDI per capita and how it correlates with the size of the state’s economy. We have also tried to answer the question of how much the GDP growth rate correlates to the FDI net inflow share in GDP for EU and non-EU members. The methodology is based on the statistical correlation between FDI in current US dollars and GDP per capita in current US dollars (World Bank data for each represented state, through the surveyed period from 1994 until 2013. The statistical correlation matrix (Pearson method determined whether any correlation between the average GDP growth rate (chain index and the average share of FDI in GDP per each state exists for each state surveyed.

  1. Endogenous control of sexual size dimorphism: Gonadal androgens have neither direct nor indirect effect on male growth in a Madagascar ground gecko (Paroedura picta).

    Science.gov (United States)

    Kubička, Lukáš; Starostová, Zuzana; Kratochvíl, Lukáš

    2015-12-01

    Changes in the effect of gonadal androgens on male growth are considered as a possible mechanism allowing shifts in magnitude and even direction of sexual size dimorphism in vertebrates, particularly squamate reptiles. Positive effects of gonadal androgens on male growth were found in several male-larger species of lizards. Contrastingly, we document that in the male-larger Madagascar ground gecko (Paroedura picta) gonadal androgens do not affect male growth under constant thermal conditions. However, the absence of a thermal gradient might prevent the potential indirect effect of gonadal androgens on growth via the influence of circulating hormones on an individual's thermoregulation and hence metabolic rate. In order to study this, we monitored the growth and body temperature of socially isolated sham-operated and castrated males of the same species in a thermal gradient. We also compared the oxygen consumption and activity between the treatment groups in the open field to test the effect of gonadal hormones on these traits potentially affecting growth. Even under a thermal gradient we found no effect of gonadal androgens on growth rate or final body dimensions. Castration also did not significantly affect oxygen consumption or activity in the open field test. Together with our previous findings, we can exclude both the direct effect of male gonadal androgens on the ontogeny of sexual size dimorphism via the influence on the growth axis, and the indirect influence of gonadal androgens acting on the ontogeny of SSD through the effect on thermoregulation, metabolic rate and activity. Copyright © 2015 Elsevier Inc. All rights reserved.

  2. 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...

  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. © FEMS 2014. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  4. Analysis of lineament swarms in a Precambrian metamorphic rocks ...

    Indian Academy of Sciences (India)

    Addressing the geologic significance of lineaments and their correlation with joints/fractures is still unclear. The present study attempts to analyse the lineament swarms developed in a Precambrian metamorphic terrain in India using both unfiltered and filtered techniques. The unfiltered analysis technique shows that the ...

  5. Handbook of swarm intelligence concepts, principles and applications

    CERN Document Server

    Shi, Yuhui; Panigrahi, Bijaya Ketan

    2011-01-01

    Recent work on the behavior of swarming creatures such as bees posits an innate collective intelligence that gives rise to myriad computational problem-solving techniques. This volume is both an introduction to the topic and a survey of leading-edge research.

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

    African Journals Online (AJOL)

    DR OKE

    All rights reserved. Optimal power flow by particle swarm optimization with an aging leader and challengers. Rudra Pratap Singh. 1. *, V. Mukherjee, S.P. Ghoshal. 1*Department of Electrical Engineering, Asansol Engineering College, INDIA. 2 Department of Electrical Engineering, Indian School of Mines Dhanabd, INDIA.

  7. Particle swarm optimization of a neural network model in a ...

    Indian Academy of Sciences (India)

    This paper presents a particle swarm optimization (PSO) technique to train an artificial neural network (ANN) for prediction of flank wear in drilling, and compares the network performance with that of the back propagation neural network (BPNN). This analysis is carried out following a series of experiments employing high ...

  8. Particle swarm optimization of a neural network model in a ...

    Indian Academy of Sciences (India)

    sets of cutting conditions and noting the root mean square (RMS) value of spindle motor current as well as ... A multi- objective optimization of hard turning using neural network modelling and swarm intelligence ... being used in this study), and these activated values in turn become the starting signals for the next adjacent ...

  9. Quantitative analysis of distributed control paradigms of robot swarms

    DEFF Research Database (Denmark)

    Ngo, Trung Dung

    2010-01-01

    Given a task of designing controller for mobile robots in swarms, one might wonder which distributed control paradigms should be selected. Until now, paradigms of robot controllers have been within either behaviour based control or neural network based control, which have been recognized as two...

  10. 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

  11. Particle Swarm Optimization Based of the Maximum Photovoltaic ...

    African Journals Online (AJOL)

    A photovoltaic system including a solar panel and PSO MPP tracker is modelled and simulated, it has been has been carried out which has shown the effectiveness of PSO to draw much energy and fast response against change in working conditions. Keywords: Particle Swarm Optimization (PSO), photovoltaic system, ...

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

    African Journals Online (AJOL)

    TonukariJ

    (Lopatkin et al., 2001; Pfau and Sacks, 1992). The re- occurrence of these diseases have been attributed to polymicrobial etiology through cultures, which is sometimes undetected (van Asten and Gaastra, 1999). Proteus exhibits swarming motility, a growth behavior that may overwhelm the growth of other pathogens.

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

    Science.gov (United States)

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

    2017-09-01

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

  14. Progressive Particle Swarm Optimization Algorithm for Solving Reactive Power Problem

    Directory of Open Access Journals (Sweden)

    Kanagasabai Lenin

    2015-11-01

    Full Text Available In this paper a Progressive particle swarm optimization algorithm (PPS is used to solve optimal reactive power problem. A Particle Swarm Optimization algorithm maintains a swarm of particles, where each particle has position vector and velocity vector which represents the potential solutions of the particles. These vectors are modernized from the information of global best (Gbest and personal best (Pbest of the swarm. All particles move in the search space to obtain optimal solution. In this paper a new concept is introduced of calculating the velocity of the particles with the help of Euclidian Distance conception. This new-fangled perception helps in finding whether the particle is closer to Pbest or Gbest and updates the velocity equation consequently. By this we plan to perk up the performance in terms of the optimal solution within a rational number of generations. The projected PPS has been tested on standard IEEE 30 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss with control variables are within the limits.

  15. 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...

  16. 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,…

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

    African Journals Online (AJOL)

    user

    compared with the Genetic Algorithm (GA) approach. Test results indicate that the proposed algorithm outperforms the Genetic. Algorithm approach with respect to total profit and convergence time. Keywords: Electricity Market, Market Clearing Price (MCP), Optimal bidding strategy, Particle Swarm Optimization (PSO).

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

    African Journals Online (AJOL)

    In this paper, a particle swarm optimization (PSO) with an aging leader and challengers (ALC-PSO) is applied for the solution of OPF problem of power system. This study is implemented on modified IEEE 30-bus test power system with different objectives that reflect minimization of either fuel cost or active power loss or sum ...

  19. Analysis of lineament swarms in a Precambrian metamorphic rocks ...

    Indian Academy of Sciences (India)

    Addressing the geologic significance of lineaments and their correlation with joints/fractures is still unclear. The present study attempts to analyse the lineament swarms developed in a Precambrian meta- morphic terrain in India using both unfiltered and filtered techniques. The unfiltered analysis technique shows that the ...

  20. THE OCCURENCE OF A HYBRID SWARM INVOLVING A. CHEV ...

    African Journals Online (AJOL)

    BIG TIMMY

    By the year 2000, the population of had declined and, by the year 2010, the population of had given way to as a result of massive rice farming. The intermediate plant forms that lined the bank of the largest impoundment had also disappeared. RESULTS AND OBSERVATIONS. Bolaji et al.: The Occurence of a Hybrid Swarm.

  1. Validation of Swarm accelerometer data by modelled nongravitational forces

    Czech Academy of Sciences Publication Activity Database

    Bezděk, Aleš; Sebera, J.; Klokočník, Jaroslav

    2017-01-01

    Roč. 59, č. 10 (2017), s. 2512-2521 ISSN 0273-1177 R&D Projects: GA MŠk(CZ) LG15003 Institutional support: RVO:67985815 Keywords : space-borne accelerometers * nongravitational accelerations * swarm mission Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 1.401, year: 2016

  2. Small-sized and contacting Pt-WC nanostructures on graphene as highly efficient anode catalysts for direct methanol fuel cells.

    Science.gov (United States)

    Wang, Ruihong; Xie, Ying; Shi, Keying; Wang, Jianqiang; Tian, Chungui; Shen, Peikang; Fu, Honggang

    2012-06-11

    The synergistic effect between Pt and WC is beneficial for methanol electro-oxidation, and makes Pt-WC catalyst a promising anode candidate for the direct methanol fuel cell. This paper reports on the design and synthesis of small-sized and contacting Pt-WC nanostructures on graphene that bring the synergistic effect into full play. Firstly, DFT calculations show the existence of a strong covalent interaction between WC and graphene, which suggests great potential for anchoring WC on graphene with formation of small-sized, well-dispersed WC particles. The calculations also reveal that, when Pt attaches to the pre-existing WC/graphene hybrid, Pt particles preferentially grow on WC rather than graphene. Our experiments confirmed that highly disperse WC nanoparticles (ca. 5 nm) can indeed be anchored on graphene. Also, Pt particles 2-3 nm in size are well dispersed on WC/graphene hybrid and preferentially grow on WC grains, forming contacting Pt-WC nanostructures. These results are consistent with the theoretical findings. X-ray absorption fine structure spectroscopy further confirms the intimate contact between Pt and WC, and demonstrates that the presence of WC can facilitate the crystallinity of Pt particles. This new Pt-WC/graphene catalyst exhibits a high catalytic efficiency toward methanol oxidation, with a mass activity 1.98 and 4.52 times those of commercial PtRu/C and Pt/C catalysts, respectively. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. 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

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

    Science.gov (United States)

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

    2017-01-01

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

  5. The Cartesian Path Planning of Free-Floating Space Robot using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Wenfu Xu

    2008-09-01

    Full Text Available The Cartesian path planning of free-floating space robot is much more complex than that of fixed-based manipulators, since the end-effector pose (position and orientation is path dependent, and the position-level kinematic equations can not be used to determine the joint angles. In this paper, a method based on particle swarm optimization (PSO is proposed to solve this problem. Firstly, we parameterize the joint trajectory using polynomial functions, and then normalize the parameterized trajectory. Secondly, the Cartesian path planning is transformed to an optimization problem by integrating the differential kinematic equations. The object function is defined according to the accuracy requirement, and it is the function of the parameters to be defined. Finally, we use the Particle Swarm Optimization (PSO algorithm to search the unknown parameters. The approach has the following traits: 1 The limits on joint angles, rates and accelerations are included in the planning algorithm; 2 There exist not any kinematic and dynamic singularities, since only the direct kinematic equations are used; 3 The attitude singularities do not exist, for the orientation is represented by quaternion; 4 The optimization algorithm is not affected by the initial parameters. Simulation results verify the proposed method.

  6. The Cartesian Path Planning of Free- Floating Space Robot using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Yangsheng Xu

    2008-11-01

    Full Text Available The Cartesian path planning of free-floating space robot is much more complex than that of fixed-based manipulators, since the end-effector pose (position and orientation is path dependent, and the position-level kinematic equations can not be used to determine the joint angles. In this paper, a method based on particle swarm optimization (PSO is proposed to solve this problem. Firstly, we parameterize the joint trajectory using polynomial functions, and then normalize the parameterized trajectory. Secondly, the Cartesian path planning is transformed to an optimization problem by integrating the differential kinematic equations. The object function is defined according to the accuracy requirement, and it is the function of the parameters to be defined. Finally, we use the Particle Swarm Optimization (PSO algorithm to search the unknown parameters. The approach has the following traits: 1 The limits on joint angles, rates and accelerations are included in the planning algorithm; 2 There exist not any kinematic and dynamic singularities, since only the direct kinematic equations are used; 3 The attitude singularities do not exist, for the orientation is represented by quaternion; 4 The optimization algorithm is not affected by the initial parameters. Simulation results verify the proposed method.

  7. Hybrid Bacterial Foraging and Particle Swarm Optimization for detecting Bundle Branch Block.

    Science.gov (United States)

    Kora, Padmavathi; Kalva, Sri Ramakrishna

    2015-01-01

    Abnormal cardiac beat identification is a key process in the detection of heart diseases. Our present study describes a procedure for the detection of left and right bundle branch block (LBBB and RBBB) Electrocardiogram (ECG) patterns. The electrical impulses that control the cardiac beat face difficulty in moving inside the heart. This problem is termed as bundle branch block (BBB). BBB makes it harder for the heart to pump blood effectively through the heart circulatory system. ECG feature extraction is a key process in detecting heart ailments. Our present study comes up with a hybrid method combining two heuristic optimization methods: Bacterial Forging Optimization (BFO) and Particle Swarm Optimization (PSO) for the feature selection of ECG signals. One of the major controlling forces of BFO algorithm is the chemotactic movement of a bacterium that models a test solution. The chemotaxis process of the BFO depends on random search directions which may lead to a delay in achieving the global optimum solution. The hybrid technique: Bacterial Forging-Particle Swarm Optimization (BFPSO) incorporates the concepts from BFO and PSO and it creates individuals in a new generation. This BFPSO method performs local search through the chemotactic movement of BFO and the global search over the entire search domain is accomplished by a PSO operator. The BFPSO feature values are given as the input for the Levenberg-Marquardt Neural Network classifier.

  8. Direct assessment of size and shape of noncircular vena contracta area in functional versus organic mitral regurgitation using real-time three-dimensional echocardiography.

    Science.gov (United States)

    Kahlert, Philipp; Plicht, Björn; Schenk, Ingmar M; Janosi, Rolf-Alexander; Erbel, Raimund; Buck, Thomas

    2008-08-01

    Vena contracta width (VCW) as an estimate of effective regurgitant orifice area (EROA) is an accepted parameter of mitral regurgitation (MR) severity. However, uncertainty exists in cases in which VCW at the same time appears narrow in 4-chamber (4CH) view and broad in 2-chamber (2CH) view as common in functional MR with noncircular or slit-like regurgitant orifices. We therefore hypothesized that new real-time 3-dimensional color Doppler echocardiography (RT3DE) can be used for direct assessment of the size and shape of vena contracta area (VCA) in an en face view and to determine the potential error of conventional VCW measurement on estimation of EROA. RT3DE was performed in 57 patients with relevant MR of different etiologies. Manual tracing of VCA in a cross-sectional plane through the vena contracta was compared with VCW in 4CH and 2CH views. As a comparative approach to VCA-3D, EROA was calculated using the hemispheric and hemielliptic proximal isovelocity surface (PISA) area method. Direct measurement of VCA-3D was feasible in all patients within 2.6 +/- 0.7 minutes. RT3DE revealed significant asymmetry of VCA in functional compared with organic MR (P PISA (r = .96, mean error: -0.09 +/- 0.14 cm(2)) compared with significant underestimation of hemispheric PISA in noncircular lesions. Direct assessment of VCA using RT3DE revealed significant asymmetry of VCA in functional MR compared with organic MR, resulting in poor estimation of EROA by single VCW measurements.

  9. Optimal PID Controller Tuning for Multivariable Aircraft Longitudinal Autopilot Based on Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Mostafa Lotfi Forushani

    2012-04-01

    Full Text Available This paper presents an optimized controller around the longitudinal axis of multivariable system in one of the aircraft flight conditions. The controller is introduced in order to control the angle of attack from the pitch attitude angle independently (that is required for designing a set of direct force-modes for the longitudinal axis based on particle swarm optimization (PSO algorithm. The autopilot system for military or civil aircraft is an essential component and in this paper, the autopilot system via 6 degree of freedom model for the control and guidance of aircraft in which the autopilot design will perform based on defining the longitudinal and the lateral-directional axes are supposed. The effectiveness of the proposed controller is illustrated by considering HIMAT aircraft. The simulation results verify merits of the proposed controller.

  10. Array Pattern Synthesis Using Particle Swarm Optimization with Dynamic Inertia Weight

    Directory of Open Access Journals (Sweden)

    Chuang Han

    2016-01-01

    Full Text Available A Feedback Particle Swarm Optimization (FPSO with a family of fitness functions is proposed to minimize sidelobe level (SLL and control null. In order to search in a large initial space and converge fast in local space to a refined solution, a FPSO with nonlinear inertia weight algorithm is developed, which is determined by a subtriplicate function with feedback taken from the fitness of the best previous position. The optimized objectives in the fitness function can obtain an accurate null level independently. The directly constrained SLL range reveals the capability to reduce SLL. Considering both element positions and complex weight coefficients, a low-level SLL, accurate null at specific directions, and constrained main beam are achieved. Numerical examples using a uniform linear array of isotropic elements are simulated, which demonstrate the effectiveness of the proposed array pattern synthesis approach.

  11. Surface hardness impairment of quorum sensing and swarming for Pseudomonas aeruginosa.

    Directory of Open Access Journals (Sweden)

    Nachiket G Kamatkar

    Full Text Available The importance of rhamnolipid to swarming of the bacterium Pseudomonas aeruginosa is well established. It is frequently, but not exclusively, observed that P. aeruginosa swarms in tendril patterns--formation of these tendrils requires rhamnolipid. We were interested to explain the impact of surface changes on P. aeruginosa swarm tendril development. Here we report that P. aeruginosa quorum sensing and rhamnolipid production is impaired when growing on harder semi-solid surfaces. P. aeruginosa wild-type swarms showed huge variation in tendril formation with small deviations to the "standard" swarm agar concentration of 0.5%. These macroscopic differences correlated with microscopic investigation of cells close to the advancing swarm edge using fluorescent gene reporters. Tendril swarms showed significant rhlA-gfp reporter expression right up to the advancing edge of swarming cells while swarms without tendrils (grown on harder agar showed no rhlA-gfp reporter expression near the advancing edge. This difference in rhamnolipid gene expression can be explained by the necessity of quorum sensing for rhamnolipid production. We provide evidence that harder surfaces seem to limit induction of quorum sensing genes near the advancing swarm edge and these localized effects were sufficient to explain the lack of tendril formation on hard agar. We were unable to artificially stimulate rhamnolipid tendril formation with added acyl-homoserine lactone signals or increasing the carbon nutrients. This suggests that quorum sensing on surfaces is controlled in a manner that is not solely population dependent.

  12. 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.

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

    Science.gov (United States)

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

    2013-09-01

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

  14. DISTRIBUTED UAV-SWARM-BASED REAL-TIME GEOMATIC DATA COLLECTION UNDER DYNAMICALLY CHANGING RESOLUTION REQUIREMENTS

    Directory of Open Access Journals (Sweden)

    M. Almeida

    2017-08-01

    Full Text Available Unmanned Aerial Vehicles (UAVs have been used for reconnaissance and surveillance missions as far back as the Vietnam War, but with the recent rapid increase in autonomy, precision and performance capabilities – and due to the massive reduction in cost and size – UAVs have become pervasive products, available and affordable for the general public. The use cases for UAVs are in the areas of disaster recovery, environmental mapping & protection and increasingly also as extended eyes and ears of civil security forces such as fire-fighters and emergency response units. In this paper we present a swarm algorithm that enables a fleet of autonomous UAVs to collectively perform sensing tasks related to environmental and rescue operations and to dynamically adapt to e.g. changing resolution requirements. We discuss the hardware used to build our own drones and the settings under which we validate the proposed approach.

  15. Neural Model with Particle Swarm Optimization Kalman Learning for Forecasting in Smart Grids

    Directory of Open Access Journals (Sweden)

    Alma Y. Alanis

    2013-01-01

    Full Text Available This paper discusses a novel training algorithm for a neural network architecture applied to time series prediction with smart grids applications. The proposed training algorithm is based on an extended Kalman filter (EKF improved using particle swarm optimization (PSO to compute the design parameters. The EKF-PSO-based algorithm is employed to update the synaptic weights of the neural network. The size of the regression vector is determined by means of the Cao methodology. The proposed structure captures more efficiently the complex nature of the wind speed, energy generation, and electrical load demand time series that are constantly monitorated in a smart grid benchmark. The proposed model is trained and tested using real data values in order to show the applicability of the proposed scheme.

  16. Distributed UAV-Swarm Real-Time Geomatic Data Collection Under Dynamically Changing Resolution Requirements

    Science.gov (United States)

    Almeida, Miguel; Hildmann, Hanno; Solmaz, Gürkan

    2017-08-01

    Unmanned Aerial Vehicles (UAVs) have been used for reconnaissance and surveillance missions as far back as the Vietnam War, but with the recent rapid increase in autonomy, precision and performance capabilities - and due to the massive reduction in cost and size - UAVs have become pervasive products, available and affordable for the general public. The use cases for UAVs are in the areas of disaster recovery, environmental mapping & protection and increasingly also as extended eyes and ears of civil security forces such as fire-fighters and emergency response units. In this paper we present a swarm algorithm that enables a fleet of autonomous UAVs to collectively perform sensing tasks related to environmental and rescue operations and to dynamically adapt to e.g. changing resolution requirements. We discuss the hardware used to build our own drones and the settings under which we validate the proposed approach.

  17. Principal Earthquakes: Theory and Observations from the 2008 West Bohemia Swarm

    Science.gov (United States)

    Vavrycuk, V.

    2011-12-01

    Earthquakes that occur on optimally oriented fault planes with respect to the tectonic stress regime display two distinct focal mechanisms and are fundamental characteristics of each seismically active region. These earthquakes, which we term 'principal', need not coincide with the strongest earthquakes or need not occur along the major active faults in the region. Theoretical stability analysis of diversely oriented fault planes under a given stress reveals that the focal mechanisms connected with unstable fault planes should not be very distinct from those of the principal earthquakes. The P/T axes form clusters with a typical two-wing or butterfly pattern. This pattern is particularly visible when constructing the failure curves defined as a projection of the Mohr-Coulomb failure criterion in the Mohr's diagram onto the focal sphere. The position, shape and size of the failure curves depend on the stress orientation, shape ratio, friction and on the size of the instability area in the Mohr's diagram. The theoretical analysis is tested using accurately determined focal mechanisms of 99 micro-earthquakes that occurred during the 2008 earthquake swarm in the West Bohemia/Vogtland region. The distribution of P/T axes reveals the butterfly wing pattern predicted in numerical modelling. The activated fault planes concentrate in the area of validity of the Mohr-Coulomb failure criterion. The average friction of faults is 0.5 and corresponds to a deviation of 32° of the principal faults from the σ1 axis. The left-lateral strike-slip principal fault was the most active fault during the swarm. It shows little geological expression at the surface but it is clearly defined by a linear cluster of hypocentres at depth. The right-lateral strike-slip principal fault was less active but it is geologically well manifested on the Earth's surface.

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

    Science.gov (United States)

    Huang, Tao; Wang, Hui; Hermann, Luehr

    2017-04-01

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

  19. The Effect of Monoterpenes on Swarming Differentiation and Haemolysin Activity in Proteus mirabilis

    Directory of Open Access Journals (Sweden)

    Sergio Echeverrigaray

    2008-12-01

    Full Text Available Urinary tract infection by Proteus mirabilis depends on several virulence properties that are coordinately regulated with swarming differentiation. Here we report the antibacterial and anti-swarming effect of seventeen terpenoids, and the effect of subinhibitory concentrations of five selected terpenoids on swarming, biofilm formation and haemolysin activity. The results showed that all the terpenes evaluated, particularly oxygenated terpenoids, inhibited P. mirabilis with MIC values ranging between 3 and 10 mg/L. Moreover, citral, citronellol and geraniol effectively inhibit P. mirabilis swarming in a dose dependent manner, reducing swimming/swarming cell differentiation and haemolysin activity at 1/10 MIC concentration. The inhibition of P. mirabilis swarming and virulence factor expression by selected oxygenated terpenoids suggest that essential oils with high concentration of these compounds have the potential to be developed as products for preventing P. mirabilis infections.

  20. 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.

  1. Creating Virtual Communities by Means of Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Lucian Hancu

    2011-01-01

    Full Text Available

    During centuries, observing the behavior of wild species has always been fascinating and full of mysteries. Modeling human interactions based on those revealed on the wilderness conducts to innovative solutions, but also poses unexpected issues. In this article, we describe our approach of creating communities of virtual entities by means of swarm intelligence. We discuss the algorithm of creating the virtual communities along with the issues that arise when modeling business entities as individuals of the swarm.

  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. 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.

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

    Science.gov (United States)

    Wei, Xiao-peng; Zhang, Jian-xia; Zhou, Dong-sheng; Zhang, Qiang

    2015-01-01

    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.

  5. A hierarchical particle swarm optimizer and its adaptive variant.

    Science.gov (United States)

    Janson, Stefan; Middendorf, Martin

    2005-12-01

    A hierarchical version of the particle swarm optimization (PSO) metaheuristic is introduced in this paper. In the new method called H-PSO, the particles are arranged in a dynamic hierarchy that is used to define a neighborhood structure. Depending on the quality of their so-far best-found solution, the particles move up or down the hierarchy. This gives good particles that move up in the hierarchy a larger influence on the swarm. We introduce a variant of H-PSO, in which the shape of the hierarchy is dynamically adapted during the execution of the algorithm. Another variant is to assign different behavior to the individual particles with respect to their level in the hierarchy. H-PSO and its variants are tested on a commonly used set of optimization functions and are compared to PSO using different standard neighborhood schemes.

  6. 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.

  7. Genetical Swarm Optimization of Multihop Routes in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Davide Caputo

    2010-01-01

    Full Text Available In recent years, wireless sensor networks have been attracting considerable research attention for a wide range of applications, but they still present significant network communication challenges, involving essentially the use of large numbers of resource-constrained nodes operating unattended and exposed to potential local failures. In order to maximize the network lifespan, in this paper, genetical swarm optimization (GSO is applied, a class of hybrid evolutionary techniques developed in order to exploit in the most effective way the uniqueness and peculiarities of two classical optimization approaches; particle swarm optimization (PSO and genetic algorithms (GA. This procedure is here implemented to optimize the communication energy consumption in a wireless network by selecting the optimal multihop routing schemes, with a suitable hybridization of different routing criteria, confirming itself as a flexible and useful tool for engineering applications.

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

    DEFF Research Database (Denmark)

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

    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......, position errors and data gaps. The magnitude of the different error sources is kept variable so that we not only compare the impact of different error sources, but investigate also the effects on the magnetic field reconstruction for different noise levels. Further extension of this approach will allow...... to test the influence of ionospheric residual signal or the impact of data selection on the lithospheric retrieval. Initially, the study considers one satellite and emphasises on the lithospheric field reconstruction, but in a second step it is extended to a realistic Swarm constellation of three...

  9. Subsurface imaging across the 2001 Spokane, Washington earthquake swarm

    Science.gov (United States)

    Finn, S.; Stephenson, W. J.; Wicks, C. W.; Pratt, T. L.; Odum, J. K.; Angster, S. J.

    2012-12-01

    We acquired 4 km of minivibe reflection seismic data in Spokane, Washington, to image subsurface deformation associated with the 2001 swarm of shallow (collected by USGS as part of ongoing earthquake hazards investigations in the area. In 2001 unexplained earthquake ground shaking as well as audible "booms" were reported over a span of six months (June to November) in the Emerson-Garfield and West Central neighborhoods of Spokane.; the area has since been seismically quiescent. Seismograph recordings of the earthquake swarm suggest shallow depths of hypocenters, yet the local subsurface geology is not well known. Although the source region of this swarm is poorly constrained within Spokane due to sparse seismic station coverage in the area at that time, recent InSAR data analysis has revealed a zone of surface deformation that may be related to the earthquake swarm. This surface deformation consists of an elliptical area about 3 km across that had as much as 15 mm of uplift during 2001. Preliminary processing of the two new seismic profiles provides the first subsurface images of the upper 500 m within the Spokane area across the inferred source region. One seismic profile through downtown Spokane shows a three-layer structure of Holocene valley fill and Quaternary Lake Missoula flood deposits underlain by Tertiary Columbia River basalts. We observe a Columbia River basalt bedrock high of 100 m located between seismic profiles and verified by geologic and aeromagnetic maps. The seismic data also image a paleochannel showing the migration of the Spokane River through time. An inflection within the Quaternary basin sediment reflections suggests uplift from faulting that is consistent with the sense of deformation observed in the InSAR data.

  10. 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

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

    Science.gov (United States)

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

    2007-12-01

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

  12. 2014 mainshock-aftershock activity versus earthquake swarms in West\

    Czech Academy of Sciences Publication Activity Database

    Jakoubková, Hana; Horálek, Josef; Fischer, T.

    2018-01-01

    Roč. 175, č. 1 (2018), s. 109-131 ISSN 0033-4553 R&D Projects: GA ČR GAP210/12/2336; GA MŠk(CZ) LM2015079 Institutional support: RVO:67985530 Keywords : West Bohemia/Vogtland * earthquake swarms * mainshock-aftershock sequence * total seismic moment * statistical characteristics of earthquake activities Subject RIV: DC - Siesmology, Volcanology, Earth Structure Impact factor: 1.591, year: 2016

  13. Optimized Landing of Autonomous Unmanned Aerial Vehicle Swarms

    Science.gov (United States)

    2012-06-01

    in a few hours. xvii THIS PAGE INTENTIONALLY LEFT BLANK xviii CHAPTER 1: INTRODUCTION 1.1 Background “The fiercest serpent may be overcome by a swarm... languages . Though Python has optimization-related packages and modeling languages such as Coopr and Pyomo, respectively, the lack of familiarity prevented...data structures that stay resident in the generating language , and/or using a compiled language . 32 Figure 3.12: Graphical Depiction of Scenario One

  14. Capability Driven Robotic Swarms in Reconnaissance-Based Operations

    Science.gov (United States)

    2008-05-02

    sensors is a TCRT1000 reflective optical sensor from ents. The first is a measurement of the norma 5 4 32 1 0 Scale 1:1 67 Figure 51 : Schematic of... IEEE International Conference on Robotics and Automation, pages 1464–1469, Taipei, Taiwan, Sept. 2003. [2] Barnes, L.; Alvis, W.; Fields, M...Valavanis, K.; Moreno, W., “Heterogeneous Swarm Formation Control Using Bivariate Normal Functions to Generate Potential Fields” IEEE Workshop on

  15. Synthesizing Sierpinski Antenna by Genetic Algorithm and Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Z. Raida

    2008-12-01

    Full Text Available The paper discusses the synthesis of the Sierpinski antenna operating at three prescribed frequencies: 0.9 GHz, 1.8 GHz (both GSM and 2.4 GHz (Bluetooth. In order to synthesize the antenna, a genetic algorithm and a particle swarm optimization were used. The numerical model of the antenna was developed in Zeland IE3D, optimization scripts were programmed in MATLAB. Results of both the optimization methods are compared and experimentally verified.

  16. The Information-Cost-Reward framework for understanding robot swarm foraging

    OpenAIRE

    Pitonakova, Lenka; Crowder, Richard; Bullock, Seth

    2017-01-01

    Demand for autonomous swarms, where robots can cooperate with each other without human intervention, is set to grow rapidly in the near future. Currently, one of the main challenges in swarm robotics is understanding how the behaviour of individual robots leads to an observed emergent collective performance. In this paper, a novel approach to understanding robot swarms that perform foraging is proposed in the form of the Information-Cost-Reward (ICR) framework. The framework relates the way i...

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

    Science.gov (United States)

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

    2004-01-01

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

  18. Mapping Ad Hoc Communications Network of a Large Number Fixed-Wing UAV Swarm

    Science.gov (United States)

    2017-03-01

    NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS MAPPING AD HOC COMMUNICATIONS NETWORK OF A LARGE NUMBER FIXED-WING UAV SWARM by Alexis...SUBTITLE MAPPING AD HOC COMMUNICATIONS NETWORK OF A LARGE NUMBER FIXED-WING UAV SWARM 5. FUNDING NUMBERS 6. AUTHOR(S) Alexis Pospischil 7. PERFORMING... UAVs ) simultaneously as a self-organizing swarm. These vehicles were able to execute behaviors based on message notification from a single ground

  19. Particle Swarm and Ant Colony Approaches in Multiobjective Optimization

    Science.gov (United States)

    Rao, S. S.

    2010-10-01

    The social behavior of groups of birds, ants, insects and fish has been used to develop evolutionary algorithms known as swarm intelligence techniques for solving optimization problems. This work presents the development of strategies for the application of two of the popular swarm intelligence techniques, namely the particle swarm and ant colony methods, for the solution of multiobjective optimization problems. In a multiobjective optimization problem, the objectives exhibit a conflicting nature and hence no design vector can minimize all the objectives simultaneously. The concept of Pareto-optimal solution is used in finding a compromise solution. A modified cooperative game theory approach, in which each objective is associated with a different player, is used in this work. The applicability and computational efficiencies of the proposed techniques are demonstrated through several illustrative examples involving unconstrained and constrained problems with single and multiple objectives and continuous and mixed design variables. The present methodologies are expected to be useful for the solution of a variety of practical continuous and mixed optimization problems involving single or multiple objectives with or without constraints.

  20. A Solution Quality Assessment Method for Swarm Intelligence Optimization Algorithms

    Science.gov (United States)

    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. PMID:25013845

  1. Solving Fractional Programming Problems based on Swarm Intelligence

    Science.gov (United States)

    Raouf, Osama Abdel; Hezam, Ibrahim M.

    2014-04-01

    This paper presents a new approach to solve Fractional Programming Problems (FPPs) based on two different Swarm Intelligence (SI) algorithms. The two algorithms are: Particle Swarm Optimization, and Firefly Algorithm. The two algorithms are tested using several FPP benchmark examples and two selected industrial applications. The test aims to prove the capability of the SI algorithms to solve any type of FPPs. The solution results employing the SI algorithms are compared with a number of exact and metaheuristic solution methods used for handling FPPs. Swarm Intelligence can be denoted as an effective technique for solving linear or nonlinear, non-differentiable fractional objective functions. Problems with an optimal solution at a finite point and an unbounded constraint set, can be solved using the proposed approach. Numerical examples are given to show the feasibility, effectiveness, and robustness of the proposed algorithm. The results obtained using the two SI algorithms revealed the superiority of the proposed technique among others in computational time. A better accuracy was remarkably observed in the solution results of the industrial application problems.

  2. 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.

  3. A Parallel Particle Swarm Optimization Algorithm Accelerated by Asynchronous Evaluations

    Science.gov (United States)

    Venter, Gerhard; Sobieszczanski-Sobieski, Jaroslaw

    2005-01-01

    A parallel Particle Swarm Optimization (PSO) algorithm is presented. Particle swarm optimization is a fairly recent addition to the family of non-gradient based, probabilistic search algorithms that is based on a simplified social model and is closely tied to swarming theory. Although PSO algorithms present several attractive properties to the designer, they are plagued by high computational cost as measured by elapsed time. One approach to reduce the elapsed time is to make use of coarse-grained parallelization to evaluate the design points. Previous parallel PSO algorithms were mostly implemented in a synchronous manner, where all design points within a design iteration are evaluated before the next iteration is started. This approach leads to poor parallel speedup in cases where a heterogeneous parallel environment is used and/or where the analysis time depends on the design point being analyzed. This paper introduces an asynchronous parallel PSO algorithm that greatly improves the parallel e ciency. The asynchronous algorithm is benchmarked on a cluster assembled of Apple Macintosh G5 desktop computers, using the multi-disciplinary optimization of a typical transport aircraft wing as an example.

  4. Support vector machine based on adaptive acceleration particle swarm optimization.

    Science.gov (United States)

    Abdulameer, Mohammed Hasan; Sheikh Abdullah, Siti Norul Huda; Othman, Zulaiha Ali

    2014-01-01

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

  5. Performance Evaluation of Hybrid Acoustic-Optical Underwater Swarm Networks

    Directory of Open Access Journals (Sweden)

    Samuela PERSIA

    2016-04-01

    Full Text Available The Underwater Swarm is a particular Underwater Network configuration characterized by nodes very close one to each other, with mobility capability. The structure of the network is that of a distributed network, in which the nodes, through the exchange of control information, will take decisions in collaborative manner. This type of network raises challenges for its effective design and development, for which the only use of acoustic communication as traditionally suggested in underwater communication could be not enough. A new emerging solution could be a hybrid solution that combines the use of acoustic and optical channel in order to overcome the acoustic channel limitations in underwater environment. In this work, we want to investigate how the acoustic and optical communications influence the Underwater Swarm performance by considering the Low Layers Protocols (Physical Layer, Data Link Layer and Network Layer effects over the two different propagation technologies. Performance simulations have been carried out to suggest how the new hybrid system could be designed. This study will permit to provide useful analysis for the real implementation of an Underwater Swarm based on hybrid communication technology.

  6. 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.

  7. 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

  8. Application of Cat Swarm Optimization in testing Static Load Models for Voltage Stability

    Directory of Open Access Journals (Sweden)

    G. Naveen Kumar

    2016-03-01

    Full Text Available Power System Load Modeling is a method which is used to model the power system and essential for voltage stability studies. Voltage stability defines the ability of a power network to maintain steady state voltages at all the buses under normal operating conditions, and when subjected to a disturbance. The research presented as part of this paper, deals with analysis of different static load models for voltage stability studies. The precision of the results are directly related to the load models used in this analysis. The method is analyzed using continuation power flow routine. Flexible AC Transmission System technology with a combination of Cat Swarm Optimization Meta Heuristic Search approach is applied to give a solution for the problem of instability. The effectiveness of the proposed method is demonstrated through quantitative simulation on standard IEEE 14 bus system for contingency condition.

  9. A New Logistic Dynamic Particle Swarm Optimization Algorithm Based on Random Topology

    Directory of Open Access Journals (Sweden)

    Qingjian Ni

    2013-01-01

    Full Text Available Population topology of particle swarm optimization (PSO will directly affect the dissemination of optimal information during the evolutionary process and will have a significant impact on the performance of PSO. Classic static population topologies are usually used in PSO, such as fully connected topology, ring topology, star topology, and square topology. In this paper, the performance of PSO with the proposed random topologies is analyzed, and the relationship between population topology and the performance of PSO is also explored from the perspective of graph theory characteristics in population topologies. Further, in a relatively new PSO variant which named logistic dynamic particle optimization, an extensive simulation study is presented to discuss the effectiveness of the random topology and the design strategies of population topology. Finally, the experimental data are analyzed and discussed. And about the design and use of population topology on PSO, some useful conclusions are proposed which can provide a basis for further discussion and research.

  10. A Corrective Strategy to Alleviate Overloading in Transmission Lines Based on Particle Swarm Optimization Method

    Directory of Open Access Journals (Sweden)

    Manoj Kumar Maharana

    2010-06-01

    Full Text Available This paper presents novel corrective control actions to alleviate overloads in transmission lines by the Particle Swarm Optimization (PSO method. Generator rescheduling and/or load shedding is performed locally, to restore the system from abnormal to normal operating state. The appropriate identification of generators and load buses to perform the corrective control action is an important task for the operators. Anew Direct Acyclic Graph (DAG technique for selection of participating generators and buses with respect to a contingency is presented. The effectiveness of the proposed approach is demonstrated with the help of the IEEE 30 bus system. The result shows that the proposed approach is computationally fast, reliable and efficient, in restoring the system to normal state after a contingency with minimal control actions.

  11. A new logistic dynamic particle swarm optimization algorithm based on random topology.

    Science.gov (United States)

    Ni, Qingjian; Deng, Jianming

    2013-01-01

    Population topology of particle swarm optimization (PSO) will directly affect the dissemination of optimal information during the evolutionary process and will have a significant impact on the performance of PSO. Classic static population topologies are usually used in PSO, such as fully connected topology, ring topology, star topology, and square topology. In this paper, the performance of PSO with the proposed random topologies is analyzed, and the relationship between population topology and the performance of PSO is also explored from the perspective of graph theory characteristics in population topologies. Further, in a relatively new PSO variant which named logistic dynamic particle optimization, an extensive simulation study is presented to discuss the effectiveness of the random topology and the design strategies of population topology. Finally, the experimental data are analyzed and discussed. And about the design and use of population topology on PSO, some useful conclusions are proposed which can provide a basis for further discussion and research.

  12. Particle Swarm and Bacterial Foraging Inspired Hybrid Artificial Bee Colony Algorithm for Numerical Function Optimization

    Directory of Open Access Journals (Sweden)

    Li Mao

    2016-01-01

    Full Text Available Artificial bee colony (ABC algorithm has good performance in discovering the optimal solutions to difficult optimization problems, but it has weak local search ability and easily plunges into local optimum. In this paper, we introduce the chemotactic behavior of Bacterial Foraging Optimization into employed bees and adopt the principle of moving the particles toward the best solutions in the particle swarm optimization to improve the global search ability of onlooker bees and gain a hybrid artificial bee colony (HABC algorithm. To obtain a global optimal solution efficiently, we make HABC algorithm converge rapidly in the early stages of the search process, and the search range contracts dynamically during the late stages. Our experimental results on 16 benchmark functions of CEC 2014 show that HABC achieves significant improvement at accuracy and convergence rate, compared with the standard ABC, best-so-far ABC, directed ABC, Gaussian ABC, improved ABC, and memetic ABC algorithms.

  13. An Entropy-Based Adaptive Hybrid Particle Swarm Optimization for Disassembly Line Balancing Problems

    Directory of Open Access Journals (Sweden)

    Shanli Xiao

    2017-11-01

    Full Text Available In order to improve the product disassembly efficiency, the disassembly line balancing problem (DLBP is transformed into a problem of searching for the optimum path in the directed and weighted graph by constructing the disassembly hierarchy information graph (DHIG. Then, combining the characteristic of the disassembly sequence, an entropy-based adaptive hybrid particle swarm optimization algorithm (AHPSO is presented. In this algorithm, entropy is introduced to measure the changing tendency of population diversity, and the dimension learning, crossover and mutation operator are used to increase the probability of producing feasible disassembly solutions (FDS. Performance of the proposed methodology is tested on the primary problem instances available in the literature, and the results are compared with other evolutionary algorithms. The results show that the proposed algorithm is efficient to solve the complex DLBP.

  14. Effect of Drive Cycle and Gasoline Particulate Filter on the Size and Morphology of Soot Particles Emitted from a Gasoline-Direct-Injection Vehicle.

    Science.gov (United States)

    Saffaripour, Meghdad; Chan, Tak W; Liu, Fengshan; Thomson, Kevin A; Smallwood, Gregory J; Kubsh, Joseph; Brezny, Rasto

    2015-10-06

    The size and morphology of particulate matter emitted from a light-duty gasoline-direct-injection (GDI) vehicle, over the FTP-75 and US06 transient drive cycles, have been characterized by transmission-electron-microscope (TEM) image analysis. To investigate the impact of gasoline particulate filters on particulate-matter emission, the results for the stock-GDI vehicle, that is, the vehicle in its original configuration, have been compared to the results for the same vehicle equipped with a catalyzed gasoline particulate filter (GPF). The stock-GDI vehicle emits graphitized fractal-like aggregates over all driving conditions. The mean projected area-equivalent diameter of these aggregates is in the 78.4-88.4 nm range and the mean diameter of primary particles varies between 24.6 and 26.6 nm. Post-GPF particles emitted over the US06 cycle appear to have an amorphous structure, and a large number of nucleation-mode particles, depicted as low-contrast ultrafine droplets, are observed in TEM images. This indicates the emission of a substantial amount of semivolatile material during the US06 cycle, most likely generated by the incomplete combustion of accumulated soot in the GPF during regeneration. The size of primary particles and soot aggregates does not vary significantly by implementing the GPF over the FTP-75 cycle; however, particles emitted by the GPF-equipped vehicle over the US06 cycle are about 20% larger than those emitted by the stock-GDI vehicle. This may be attributed to condensation of large amounts of organic material on soot aggregates. High-contrast spots, most likely solid nonvolatile cores, are observed within many of the nucleation-mode particles emitted over the US06 cycle by the GPF-equipped vehicle. These cores are either generated inside the engine or depict incipient soot particles which are partially carbonized in the exhaust line. The effect of drive cycle and the GPF on the fractal parameters of particles, such as fractal dimension and

  15. 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.

  16. Improved quantum-behaved particle swarm optimization with local search strategy

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    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.

  17. 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....... This product called L2-IBI is generated from magnetic field and plasma observations onboard Swarm, and gives information as to whether a Swarm magnetic field observation is affected by EPBs. We validate the performance of the L2-IBI product by using magnetic field and plasma measurements from the CHAMP...

  18. Special issue “Swarm science results after 2 years in space”

    DEFF Research Database (Denmark)

    Olsen, Nils; Stolle, Claudia; Floberghagen, Rune

    2016-01-01

    ) with an East-West separation of 1.4º in longitude corresponding to 155 km at the equator. The third satellite (Swarm Bravo) is in a slightly higher orbit (about 520 km altitude in September2016). Each of the three satellites carry a magnetometry package (consisting of absolute scalar magnetometer......Swarm is a three-satellite constellation mission launched by the European Space Agency (ESA) on 22 November2013. It consists of three identical spacecraft, two of which (Swarm Alpha and Swarm Charlie) are flying almost side-by-side in polar orbits at lower altitude (about 470 km in September 2016...

  19. 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.

  20. 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.

  1. 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.

  2. Carbohydrate-directed synthesis of silver and gold nanoparticles: effect of the structure of carbohydrates and reducing agents on the size and morphology of the composites.

    Science.gov (United States)

    Shervani, Zameer; Yamamoto, Yasushi

    2011-04-01

    A monosaccharide (β-D-glucose) and polysaccharide (soluble starch) were used as structure directing and subsequently stabilizing agents for the synthesis of spherical nanoparticles (NPs) and nanowires of silver and gold. Homogeneous monodispersed Ag(0) nanoparticles (Ag NPs) of 15 nm diameter were obtained when 10(-4)M AgNO(3) precursor salt was reduced in starch (1 wt%)-water gel by 1 wt% β-D-glucose. For a second preparation the effect of reducing agents on the synthesis of Au(0) metallic nanoparticles (Au NPs) of 2 × 10(-4)M concentration prepared in a β-D-glucose (0.03 M)-water dispersion was studied first in detail. Different equivalent amounts of NaBH(4) and a number of pH values were evaluated for the reduction of the Au salt HAuCl(4)·3H(2)O to obtain Au NPs. The type and the amount of reducing agent, as well as the pH of the solution was shown to affect the size and morphology of the NPs. NaBH(4) (4 equiv) produced the smallest (5.3 nm (σ 0.7)) metallic particles compared to larger particles (10.0 nm (σ 1.4)) when the salt was reduced by 1 equiv of NaBH(4). Addition of excess NaBH(4) caused the NPs to settle out as a precipitate forming a mesh or wire structure rather than monodispersed particles. Low pH (pH 6) resulted in incomplete reduction, while at pH 8 the salt was completely reduced. When the salt was reduced by NaOH at pH 8, the particles were larger (14.2 nm) and less homogeneous (σ 2.8) compared to those from NaBH(4) reduction. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. Swarming visual sensor network for real-time multiple object tracking

    Science.gov (United States)

    Baranov, Yuri P.; Yarishev, Sergey N.; Medvedev, Roman V.

    2016-04-01

    Position control of multiple objects is one of the most actual problems in various technology areas. For example, in construction area this problem is represented as multi-point deformation control of bearing constructions in order to prevent collapse, in mining - deformation control of lining constructions, in rescue operations - potential victims and sources of ignition location, in transport - traffic control and traffic violations detection, in robotics -traffic control for organized group of robots and many other problems in different areas. Usage of stationary devices for solving these problems is inappropriately due to complex and variable geometry of control areas. In these cases self-organized systems of moving visual sensors is the best solution. This paper presents a concept of scalable visual sensor network with swarm architecture for multiple object pose estimation and real-time tracking. In this article recent developments of distributed measuring systems were reviewed with consequent investigation of advantages and disadvantages of existing systems, whereupon theoretical principles of design of swarming visual sensor network (SVSN) were declared. To measure object coordinates in the world coordinate system using TV-camera intrinsic (focal length, pixel size, principal point position, distortion) and extrinsic (rotation matrix, translation vector) calibration parameters were needed to be determined. Robust camera calibration was a too resource-intensive task for using moving camera. In this situation position of the camera is usually estimated using a visual mark with known parameters. All measurements were performed in markcentered coordinate systems. In this article a general adaptive algorithm of coordinate conversion of devices with various intrinsic parameters was developed. Various network topologies were reviewed. Minimum error in objet tracking was realized by finding the shortest path between object of tracking and bearing sensor, which set

  4. The Aiguablava dyke swarm: emplacement and paleostress in a fractured basement

    Science.gov (United States)

    Martínez-Poza, Ana Isabel; Druguet, Elena; Castaño, Lina Marcela; Carreras, Jordi

    2013-04-01

    A structural analysis has been performed in the Upper Permian lamprophyric dyke swarm of Aiguablava (NE Spain). Dyke emplacement is related to the presence of a widespread joint network, likely developed during the cooling and decompression of the late Variscan granitic host rocks. In order to characterize the patterns of both the joint system and the dyke swarm, a trend frequency analysis has been performed using the circular scanlines method (Mauldon et al., 2001). The sub-vertical joint pattern consists on two major orthogonal sets at ≈N23°, ≈N113° and secondary sets at ≈N0° and ≈N90°, among others. These four fracture sets are interpreted as previous to the lamprophyre intrusion event, because they are either exploited or cross-cut by the lamprophyres. The subvertical dykes have a mean N113° trend, which corresponds to the trend of one of the main joint sets. Despite this overall orientation of dykes, segmentation is a noticeable feature at the Dm- to cm-scale, and this is probably related to the localized dyke intrusion into the other pre-existing secondary joint sets. Dyke opening directions has been measured from matching dyke jogs or markers in the host rock, with a mean orientation of 021/04. A three-dimensional paleostress analysis has been carried out from dyke orientations, applying the Mohr circle construction of Jolly and Sanderson (1997), and the parameters R' (driving pressure ratio, R'= 0.156) and φ (stress ratio, φ = 0.45) were calculated. From this analysis, we have obtained a sub-vertical maximum (σ1) and a NNE-SSW minimum (σ3) stress axes, consistent with the sub-horizontal mean trend of dyke opening measured in the field. It is inferred that many of the pre-existing joint sets were exploited by magmatic dykes, being the ≈N113° joint set (normal to σ3) the most favourable for dyke emplacement. At that time, magmatic pressure related to dyke intrusion, Pm, was lower than the intermediate principal stress axis, σ2 . Our

  5. An energy-spectrum shift in the interaction between a bubble swarm and oscillating-grid turbulence analyzed via recursive PIV

    Science.gov (United States)

    Saito, Takayuki; Morikawa, Koichi; Sanada, Toshiyuki

    2007-11-01

    In order to elucidate the liquid-phase turbulence modulation owing to dispersed bubbles, the authors employed both methods to generate arbitrary turbulence and control the bubble size and bubble number density of the bubble swarm. For the first purpose, a method of well-controlled oscillating-grid turbulence was employed; this method easily characterized integral scale and Taylor micro scale. For the second purpose, a bubble formation method using audio speakers was employed; this method completely controlled bubble size, bubble number density and launch timing. In the present study, the swarm of zigzagging rising bubbles in 2% void fraction was examined. Liquid phase velocities at two spatially-separate points were measured via two LDV probes, simultaneously. Furthermore, liquid-phase velocity field was measured via recursive PIV with a high-speed video camera. Motion of each bubble was obtained from visualization and 4-time-step tracking algorithm. From the two-point LDV data, turbulence intensity, spatial correlation, integral scale and Taylor micro scale were calculated and discussed. From the PIV results, energy spectra were obtained. On the basis of these results, interactions between the turbulence induced by the bubble swarm (i.e. dispersed bubbles) and ambient liquid-phase turbulence are quantitatively and systematically discussed.

  6. The chicken or the egg? Exploring bi-directional associations between Newcastle disease vaccination and village chicken flock size in rural Tanzania.

    Directory of Open Access Journals (Sweden)

    Julia de Bruyn

    Full Text Available Newcastle disease (ND is a viral disease of poultry with global importance, responsible for the loss of a potential source of household nutrition and economic livelihood in many low-income food-deficit countries. Periodic outbreaks of this endemic disease result in high mortality amongst free-ranging chicken flocks and may serve as a disincentive for rural households to invest time or resources in poultry-keeping. Sustainable ND control can be achieved through vaccination using a thermotolerant vaccine administered via eyedrop by trained "community vaccinators". This article evaluates the uptake and outcomes of fee-for-service ND vaccination programs in eight rural villages in the semi-arid central zone of Tanzania. It represents part of an interdisciplinary program seeking to address chronic undernutrition in children through improvements to existing poultry and crop systems. Newcastle disease vaccination uptake was found to vary substantially across communities and seasons, with a significantly higher level of vaccination amongst households participating in a longitudinal study of children's growth compared with non-participating households (p = 0.009. Two multivariable model analyses were used to explore associations between vaccination and chicken numbers, allowing for clustered data and socioeconomic and cultural variation amongst the population. Results demonstrated that both (a households that undertook ND vaccination had a significantly larger chicken flock size in the period between that vaccination campaign and the next compared with those that did not vaccinate (p = 0.018; and (b households with larger chicken flocks at the time of vaccination were significantly more likely to participate in vaccination programs (p < 0.001. Additionally, households vaccinating in all three vaccination campaigns held over 12 months were identified to have significantly larger chicken flocks at the end of this period (p < 0.001. Opportunities to

  7. 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...

  8. The impact of quorum sensing and swarming motility on Pseudomonas aeruginosa biofilm formation is nutritionally conditional

    DEFF Research Database (Denmark)

    Shrout, J.D.; Chopp, D.L.; Just, C.L.

    2006-01-01

    nutritionally conditional control of biofilm development through regulation of swarming motility. Examination of pilA and fliM mutant strains further supported the role of swarming motility in biofilm formation. These data led to a model proposing that the prevailing nutritional conditions dictate...

  9. 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......., which are similar to the shell structure of equatorial plasma bubbles suggested by previous studies....

  10. 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...

  11. An intelligent scheduling method based on improved particle swarm optimization algorithm for drainage pipe network

    Science.gov (United States)

    Luo, Yaqi; Zeng, Bi

    2017-08-01

    This paper researches the drainage routing problem in drainage pipe network, and propose an intelligent scheduling method. The method relates to the design of improved particle swarm optimization algorithm, the establishment of the corresponding model from the pipe network, and the process by using the algorithm based on improved particle swarm optimization to find the optimum drainage route in the current environment.

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

    Science.gov (United States)

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

    2016-01-01

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

  13. 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.

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

    Science.gov (United States)

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

    2016-01-01

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

  15. Emergent Runaway into an Avoidance Area in a Swarm of Soldier Crabs: e97870

    National Research Council Canada - National Science Library

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

    2014-01-01

    ... on mass effects are rare. In this study, we show that a swarm of soldier crabs could spontaneously enter a water pool, which are usually avoided, by forming densely populated part of a swarm at the edge of the water pool...

  16. 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

  17. Bare bones particle swarm optimization with scale matrix adaptation.

    Science.gov (United States)

    Campos, Mauro; Krohling, Renato A; Enriquez, Ivan

    2014-09-01

    Bare bones particle swarm optimization (BBPSO) is a swarm algorithm that has shown potential for solving single-objective unconstrained optimization problems over continuous search spaces. However, it suffers of the premature convergence problem that means it may get trapped into a local optimum when solving multimodal problems. In order to address this drawback and improve the performance of the BBPSO, we propose a variant of this algorithm, named by us as BBPSO with scale matrix adaptation (SMA), SMA-BBPSO for short reference. In the SMA-BBPSO, the position of a particle is selected from a multivariate t-distribution with a rule for adaptation of its scale matrix. We use the multivariate t-distribution in its hierarchical form, as a scale mixtures of normal distributions. The t -distribution has heavier tails than those of the normal distribution, which increases the ability of the particles to escape from a local optimum. In addition, our approach includes the normal distribution as a particular case. As a consequence, the t -distribution can be applied during the optimization process by maintaining the proper balance between exploration and exploitation. We also propose a simple update rule to adapt the scale matrix associated with a particle. Our strategy consists of adapting the scale matrix of a particle such that the best position found by any particle in its neighborhood is sampled with maximum likelihood in the next iteration. A theoretical analysis was developed to explain how the SMA-BBPSO works, and an empirical study was carried out to evaluate the performance of the proposed algorithm. The experimental results show the suitability of the proposed approach in terms of effectiveness to find good solutions for all benchmark problems investigated. Nonparametric statistical tests indicate that SMA-BBPSO shows a statistically significant improvement compared with other swarm algorithms.

  18. 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.

  19. 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

    significances. Our results indicate that swarming motility is restricted to a narrow range of high matric water potentials in the three pseudomonads tested (Pseudomonas sp. DSS73, Pseudomonas syringae B728a, and Pseudomonas aeruginosa PA14). The threshold below which no swarming was observed was about –0.45 k......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......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...

  20. Particle Swarm Optimization for HW/SW Partitioning

    OpenAIRE

    Abdelhalim, M. B.; Habib, S. E. &#;D.

    2009-01-01

    In this chapter, the recent introduction of the Particle Swarm Optimization technique to solve the HW/SW partitioning problem is reviewed, along with its “re-exited PSO” modification. The re-exited PSO algorithm is a recently-introduced restarting technique for PSO. The Re-exited PSO proved to be highly effective for solving the HW/SW partitioning problem. Efficient cost function formulation is of a paramount importance for an efficient optimization algorithm. Each component in the design...

  1. OPTIMIZATION OF GRID RESOURCE SCHEDULING USING PARTICLE SWARM OPTIMIZATION ALGORITHM

    Directory of Open Access Journals (Sweden)

    S. Selvakrishnan

    2010-10-01

    Full Text Available Job allocation process is one of the big issues in grid environment and it is one of the research areas in Grid Computing. Hence a new area of research is developed to design optimal methods. It focuses on new heuristic techniques that provide an optimal or near optimal solution for large grids. By learning grid resource scheduling and PSO (Particle Swarm Optimization algorithm, this proposed scheduler allocates an application to a host from a pool of available hosts and applications by selecting the best match. PSO-based algorithm is more effective in grid resources scheduling with the favor of reducing the executing time and completing time.

  2. Mining Customer Change Model Based on Swarm Intelligence

    Science.gov (United States)

    Jin, Peng; Zhu, Yunlong

    Understanding and adapting to changes of customer behavior is an important aspect of surviving in a continuously changing market environment for a modern company. The concept of customer change model mining is introduced and its process is analyzed in this paper. A customer change model mining method based on swarm intelligence is presented, and the strategies of pheromone updating and items searching are given. Finally, an examination on two customer datasets of a telecom company illuminates that this method can achieve customer change model efficiently.

  3. PID control for chaotic synchronization using particle swarm optimization

    Energy Technology Data Exchange (ETDEWEB)

    Chang, W.-D. [Department of Computer and Communication, Shu-Te University, Kaohsiung 824, Taiwan (China)], E-mail: wdchang@mail.stu.edu.tw

    2009-01-30

    In this paper, we attempt to use the proportional-integral-derivative (PID) controller to achieve the chaos synchronization for delayed discrete chaotic systems. Three PID control gains can be optimally determined by means of using a novel optimization algorithm, called the particle swarm optimization (PSO). The algorithm is motivated from the organism behavior of fish schooling and bird flocking, and involves the social psychology principles in socio-cognition human agents and evolutionary computations. It has a good numerical convergence for solving optimization problem. To show the validity of the PSO-based PID control for chaos synchronization, several cases with different initial populations are considered and some simulation results are shown.

  4. Available transfer capability enhancement with FACTS using Cat Swarm Optimization

    Directory of Open Access Journals (Sweden)

    T. Nireekshana

    2016-03-01

    Full Text Available Determination and enhancement of Available Transfer Capability (ATC are important issues in deregulated operation of power systems. This paper investigates the use of FACTS devices, such as SVC and TCSC, to maximize power transfer transactions during normal and contingency situations. ATC is computed using Continuation Power Flow (CPF method considering both the thermal limits and voltage profile. Cat Swarm Optimization (CSO is used as an optimization tool to determine the location and controlling parameters of SVC and TCSC. The suggested methodology is tested on IEEE 14-bus system and also on IEEE 24-bus reliability test system for normal and different contingency cases.

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

    DEFF Research Database (Denmark)

    Bouman, Johannes; Ebbing, Jörg; Kotsiaros, Stavros

    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...... 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...

  6. 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)

  7. Chaotic Hopfield Neural Network Swarm Optimization and Its Application

    Directory of Open Access Journals (Sweden)

    Yanxia Sun

    2013-01-01

    Full Text Available A new neural network based optimization algorithm is proposed. The presented model is a discrete-time, continuous-state Hopfield neural network and the states of the model are updated synchronously. The proposed algorithm combines the advantages of traditional PSO, chaos and Hopfield neural networks: particles learn from their own experience and the experiences of surrounding particles, their search behavior is ergodic, and convergence of the swarm is guaranteed. The effectiveness of the proposed approach is demonstrated using simulations and typical optimization problems.

  8. Ant Robotic Swarm for Visualizing Invisible Hazardous Substances

    Directory of Open Access Journals (Sweden)

    John Oyekan

    2013-01-01

    Full Text Available Inspired by the simplicity of how nature solves its problems, this paper presents a novel approach that would enable a swarm of ant robotic agents (robots with limited sensing, communication, computational and memory resources form a visual representation of distributed hazardous substances within an environment dominated by diffusion processes using a decentralized approach. Such a visual representation could be very useful in enabling a quicker evacuation of a city’s population affected by such hazardous substances. This is especially true if the ratio of emergency workers to the population number is very small.

  9. Differential Evolution and Particle Swarm Optimization for Partitional Clustering

    DEFF Research Database (Denmark)

    Krink, Thiemo; Paterlini, Sandra

    2006-01-01

    for numerical optimisation, which are hardly known outside the search heuristics field, are particle swarm optimisation (PSO) and differential evolution (DE). The performance of GAs for a representative point evolution approach to clustering is compared with PSO and DE. The empirical results show that DE...... is clearly and consistently superior compared to GAs and PSO for hard clustering problems, both with respect to precision as well as robustness (reproducibility) of the results. Only for simple data sets, the GA and PSO can obtain the same quality of results. Apart from superior performance, DE is easy...

  10. Particle Swarm Optimization Applied to the Economic Dispatch Problem

    Directory of Open Access Journals (Sweden)

    Rafik Labdani

    2006-06-01

    Full Text Available This paper presents solution of optimal power flow (OPF problem of a power system via a simple particle swarm optimization (PSO algorithm. The objective is to minimize the fuel cost and keep the power outputs of generators, bus voltages, shunt capacitors/reactors and transformers tap-setting in their secure limits.The effectiveness of PSO was compared to that of OPF by MATPOWER. The potential and superiority of PSO have been demonstrated through the results of IEEE 30-bus system

  11. PMSM Driver Based on Hybrid Particle Swarm Optimization and CMAC

    Science.gov (United States)

    Tu, Ji; Cao, Shaozhong

    A novel hybrid particle swarm optimization (PSO) and cerebellar model articulation controller (CMAC) is introduced to the permanent magnet synchronous motor (PMSM) driver. PSO can simulate the random learning among the individuals of population and CMAC can simulate the self-learning of an individual. To validate the ability and superiority of the novel algorithm, experiments and comparisons have been done in MATLAB/SIMULINK. Analysis among PSO, hybrid PSO-CMAC and CMAC feed-forward control is also given. The results prove that the electric torque ripple and torque disturbance of the PMSM driver can be reduced by using the hybrid PSO-CMAC algorithm.

  12. 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

  13. Impedance Controller Tuned by Particle Swarm Optimization for Robotic Arms

    Directory of Open Access Journals (Sweden)

    Haifa Mehdi

    2011-11-01

    Full Text Available This paper presents an efficient and fast method for fine tuning the controller parameters of robot manipulators in constrained motion. The stability of the robotic system is proved using a Lyapunov-based impedance approach whereas the optimal design of the controller parameters are tuned, in offline, by a Particle Swarm Optimization (PSO algorithm. For designing the PSO method, different index performances are considered in both joint and Cartesian spaces. A 3DOF manipulator constrained to a circular trajectory is finally used to validate the performances of the proposed approach. The simulation results show the stability and the performances of the proposed approach.

  14. Impedance Controller Tuned by Particle Swarm Optimization for Robotic Arms

    Directory of Open Access Journals (Sweden)

    Haifa Mehdi

    2011-11-01

    Full Text Available This paper presents an efficient and fast method for fine tuning the controller parameters of robot manipulators in constrained motion. The stability of the robotic system is proved using a Lyapunov‐based impedance approach whereas the optimal design of the controller parameters are tuned, in offline, by a Particle Swarm Optimization (PSO algorithm. For designing the PSOmethod,differentindexperformancesare considered in both joint and Cartesian spaces. A 3DOF manipulator constrained to a circular trajectory is finally used to validate the performances of the proposed approach. The simulation results show the stability and the performances of the proposed approach.

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

    Science.gov (United States)

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

    2017-04-01

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

  16. Analysis of carbohydrates in Fusarium verticillioides using size-exclusion HPLC – DRI and direct analysis in real time ionization – time-of-flight – mass spectrometry (DART-MS)

    Science.gov (United States)

    Direct analysis in real time ionization – time-of-flight – mass spectrometry (DART-MS) and size-exclusion HPLC – DRI are used, respectively, to qualitatively and quantitatively determine the carbohydrates extracted from the corn rot fungus Fusarium verticillioides. In situ permethylation in the DART...

  17. Direct Interval Forecasting of Wind Power

    DEFF Research Database (Denmark)

    Wan, Can; Xu, Zhao; Pinson, Pierre

    2013-01-01

    This letter proposes a novel approach to directly formulate the prediction intervals of wind power generation based on extreme learning machine and particle swarm optimization, where prediction intervals are generated through direct optimization of both the coverage probability and sharpness, wit......, without the prior knowledge of forecasting errors. The proposed approach has been proved to be highly efficient and reliable through preliminary case studies using real-world wind farm data, indicating a high potential of practical application.......This letter proposes a novel approach to directly formulate the prediction intervals of wind power generation based on extreme learning machine and particle swarm optimization, where prediction intervals are generated through direct optimization of both the coverage probability and sharpness...

  18. A new technique to design planar dipole antennas by using Bezier curve and Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Homsup Nuttaka

    2016-09-01

    Full Text Available This research presents a new technique which includes the principle of a Bezier curve and Particle Swarm Optimization (PSO together, in order to design the planar dipole antenna for the two different targets. This technique can improve the characteristics of the antennas by modifying copper textures on the antennas with a Bezier curve. However, the time to process an algorithm will be increased due to the expansion of the solution space in optimization process. So as to solve this problem, the suitable initial parameters need to be set. Therefore this research initialized parameters with reference antenna parameters (a reference antenna operates on 2.4 GHz for IEEE 802.11 b/g/n WLAN standards which resulted in the proposed designs, rapidly converted into the goals. The goal of the first design is to reduce the size of the antenna. As a result, the first antenna is reduced in the substrate size from areas of 5850 mm2 to 2987 mm2 (48.93% approximately and can also operates at 2.4 GHz (2.37 GHz to 2.51 GHz. The antenna with dual band application is presented in the second design. The second antenna is operated at 2.4 GHz (2.40 GHz to 2.49 GHz and 5 GHz (5.10 GHz to 5.45 GHz for IEEE 802.11 a/b/g/n WLAN standards.

  19. Electric motor efficiency as parameter for sizing a directly connected into transformer feeder cable; Rendimento de motor eletrico como parametro de dimensionamento de bitola de alimentador conectado diretamente ao transformador

    Energy Technology Data Exchange (ETDEWEB)

    Oliveira Filho, Delly; Lacerda Filho, Adilio F.; Martins, Jose H.; Queiroz, Josue M. [Universidade Federal de Vicosa (UFV), MG (Brazil). Dept. de Engenharia Agricola], Emails: delly@ufv.br, alacerda@ufv.br, jhmartins@ufv.br, josue.queiroz@ufv.br; Teixeira, Carlos A. [Universidade Federal Rural de Pernambuco, Serra Talhada, PE (Brazil). Dept. de Agronomia], E-mail: carlos.teixeira@uast.ufrpe.br

    2010-09-15

    The feeder conductors sizing does not take into account criterion for rational use of electricity. This study is about feeder conductors sizing evaluation for motors connected directly to transformers used in rural electrification. In the feeder conductors sizing indicate that besides the attendance of the technical standard (i.e. sizing as a function of the feeder current capacity and the allowable voltage drop) is also to be considered: the number of working hours, the feeder's electrical characteristic and price, the installation characteristics as length and engine's rate. According to the above, in some situations it may be advantageous to increase the gauge of the conductor. It was proven that in some situations it is advantageous to increase the conductor gauge beyond that required by the standards in order to save energy and expenses by the lower feeder losses and by the electric motor higher efficiency. (author)

  20. Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis

    Directory of Open Access Journals (Sweden)

    J. J. Jamian

    2014-01-01

    Full Text Available The Particle Swarm Optimization (PSO Algorithm is a popular optimization method that is widely used in various applications, due to its simplicity and capability in obtaining optimal results. However, ordinary PSOs may be trapped in the local optimal point, especially in high dimensional problems. To overcome this problem, an efficient Global Particle Swarm Optimization (GPSO algorithm is proposed in this paper, based on a new updated strategy of the particle position. This is done through sharing information of particle position between the dimensions (variables at any iteration. The strategy can enhance the exploration capability of the GPSO algorithm to determine the optimum global solution and avoid traps at the local optimum. The proposed GPSO algorithm is validated on a 12-benchmark mathematical function and compared with three different types of PSO techniques. The performance of this algorithm is measured based on the solutions’ quality, convergence characteristics, and their robustness after 50 trials. The simulation results showed that the new updated strategy in GPSO assists in realizing a better optimum solution with the smallest standard deviation value compared to other techniques. It can be concluded that the proposed GPSO method is a superior technique for solving high dimensional numerical function optimization problems.

  1. ADAPTIVE DISTRIBUTION OF A SWARM OF HETEROGENEOUS ROBOTS

    Directory of Open Access Journals (Sweden)

    Amanda Prorok

    2016-02-01

    Full Text Available We present a method that distributes a swarm of heterogeneous robots among a set of tasks that require specialized capabilities in order to be completed. We model the system of heterogeneous robots as a community of species, where each species (robot type is defined by the traits (capabilities that it owns. Our method is based on a continuous abstraction of the swarm at a macroscopic level as we model robots switching between tasks. We formulate an optimization problem that produces an optimal set of transition rates for each species, so that the desired trait distribution is reached as quickly as possible. Since our method is based on the derivation of an analytical gradient, it is very efficient with respect to state-of-the-art methods. Building on this result, we propose a real-time optimization method that enables an online adaptation of transition rates. Our approach is well-suited for real-time applications that rely on online redistribution of large-scale robotic systems.

  2. Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History

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    Danping Wang

    2017-01-01

    Full Text Available A hybrid coevolution particle swarm optimization algorithm with dynamic multispecies strategy based on K-means clustering and nonrevisit strategy based on Binary Space Partitioning fitness tree (called MCPSO-PSH is proposed. Previous search history memorized into the Binary Space Partitioning fitness tree can effectively restrain the individuals’ revisit phenomenon. The whole population is partitioned into several subspecies and cooperative coevolution is realized by an information communication mechanism between subspecies, which can enhance the global search ability of particles and avoid premature convergence to local optimum. To demonstrate the power of the method, comparisons between the proposed algorithm and state-of-the-art algorithms are grouped into two categories: 10 basic benchmark functions (10-dimensional and 30-dimensional, 10 CEC2005 benchmark functions (30-dimensional, and a real-world problem (multilevel image segmentation problems. Experimental results show that MCPSO-PSH displays a competitive performance compared to the other swarm-based or evolutionary algorithms in terms of solution accuracy and statistical tests.

  3. Effect of Correlations in Swarms on Collective Response.

    Science.gov (United States)

    Mateo, David; Kuan, Yoke Kong; Bouffanais, Roland

    2017-09-04

    Social interaction increases significantly the performance of a wide range of cooperative systems. However, evidence that natural swarms limit the number of interactions suggests potentially detrimental consequences of excessive interaction. Using a canonical model of collective motion, we find that the collective response to a dynamic localized perturbation-emulating a predator attack-is hindered when the number of interacting neighbors exceeds a certain threshold. Specifically, the effectiveness in avoiding the predator is enhanced by large integrated correlations, which are known to peak at a given level of interagent interaction. From the network-theoretic perspective, we uncover the same interplay between number of connections and effectiveness in group-level response for two distinct decision-making models of distributed consensus operating over a range of static networks. The effect of the number of connections on the collective response critically depends on the dynamics of the perturbation. While adding more connections improves the response to slow perturbations, the opposite is true for fast ones. These results have far-reaching implications for the design of artificial swarms or interaction networks.

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

    Science.gov (United States)

    Kesharaju, Manasa; Nagarajah, Romesh

    2017-03-01

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

  5. Cat swarm optimization based evolutionary framework for multi document summarization

    Science.gov (United States)

    Rautray, Rasmita; Balabantaray, Rakesh Chandra

    2017-07-01

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

  6. CFSO3: A New Supervised Swarm-Based Optimization Algorithm

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    Antonino Laudani

    2013-01-01

    Full Text Available We present CFSO3, an optimization heuristic within the class of the swarm intelligence, based on a synergy among three different features of the Continuous Flock-of-Starlings Optimization. One of the main novelties is that this optimizer is no more a classical numerical algorithm since it now can be seen as a continuous dynamic system, which can be treated by using all the mathematical instruments available for managing state equations. In addition, CFSO3 allows passing from stochastic approaches to supervised deterministic ones since the random updating of parameters, a typical feature for numerical swam-based optimization algorithms, is now fully substituted by a supervised strategy: in CFSO3 the tuning of parameters is a priori designed for obtaining both exploration and exploitation. Indeed the exploration, that is, the escaping from a local minimum, as well as the convergence and the refinement to a solution can be designed simply by managing the eigenvalues of the CFSO state equations. Virtually in CFSO3, just the initial values of positions and velocities of the swarm members have to be randomly assigned. Both standard and parallel versions of CFSO3 together with validations on classical benchmarks are presented.

  7. Collective Behavior of Animals: Swarming and Complex Patterns

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    Cañizo, J. A.

    2010-12-01

    Full Text Available In this short note we review some of the individual based models of the collective motion of agents, called swarming. These models based on ODEs (ordinary differential equations exhibit a complex rich asymptotic behavior in terms of patterns, that we show numerically. Moreover, we comment on how these particle models are connected to partial differential equations to describe the evolution of densities of individuals in a continuum manner. The mathematical questions behind the stability issues of these PDE (partial differential equations 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. Estos modelos se basan en EDOs (ecuaciones diferenciales ordinarias y muestran un comportamiento asintótico complejo y rico en patrones, que mostramos numéricamente. Además, comentamos cómo se conectan estos modelos de partículas con las ecuaciones en derivadas parciales para describir la evolución de densidades de individuos de forma continua. Las cuestiones matemáticas relacionadas con la estabilidad de de estos modelos de EDP's (ecuaciones en derivadas parciales despiertan gran interés en la investigación en biología matemática.

  8. Bio Inspired Swarm Algorithm for Tumor Detection in Digital Mammogram

    Science.gov (United States)

    Dheeba, J.; Selvi, Tamil

    Microcalcification clusters in mammograms is the significant early sign of breast cancer. Individual clusters are difficult to detect and hence an automatic computer aided mechanism will help the radiologist in detecting the microcalcification clusters in an easy and efficient way. This paper presents a new classification approach for detection of microcalcification in digital mammogram using particle swarm optimization algorithm (PSO) based clustering technique. Fuzzy C-means clustering technique, well defined for clustering data sets are used in combination with the PSO. We adopt the particle swarm optimization to search the cluster center in the arbitrary data set automatically. PSO can search the best solution from the probability option of the Social-only model and Cognition-only model. This method is quite simple and valid, and it can avoid the minimum local value. The proposed classification approach is applied to a database of 322 dense mammographic images, originating from the MIAS database. Results shows that the proposed PSO-FCM approach gives better detection performance compared to conventional approaches.

  9. Deployment Environment for a Swarm of Heterogeneous Robots

    Directory of Open Access Journals (Sweden)

    Tamer Abukhalil

    2016-10-01

    Full Text Available The objective of this work is to develop a framework that can deploy and provide coordination between multiple heterogeneous agents when a swarm robotic system adopts a decentralized approach; each robot evaluates its relative rank among the other robots in terms of travel distance and cost to the goal. Accordingly, robots are allocated to the sub-tasks for which they have the highest rank (utility. This paper provides an analysis of existing swarm control environments and proposes a software environment that facilitates a rapid deployment of multiple robotic agents. The framework (UBSwarm exploits our utility-based task allocation algorithm. UBSwarm configures these robots and assigns the group of robots a particular task from a set of available tasks. Two major tasks have been introduced that show the performance of a robotic group. This robotic group is composed of heterogeneous agents. In the results, a premature example that has prior knowledge about the experiment shows whether or not the robots are able to accomplish the task.

  10. Multivariable optimization of liquid rocket engines using particle swarm algorithms

    Science.gov (United States)

    Jones, Daniel Ray

    Liquid rocket engines are highly reliable, controllable, and efficient compared to other conventional forms of rocket propulsion. As such, they have seen wide use in the space industry and have become the standard propulsion system for launch vehicles, orbit insertion, and orbital maneuvering. Though these systems are well understood, historical optimization techniques are often inadequate due to the highly non-linear nature of the engine performance problem. In this thesis, a Particle Swarm Optimization (PSO) variant was applied to maximize the specific impulse of a finite-area combustion chamber (FAC) equilibrium flow rocket performance model by controlling the engine's oxidizer-to-fuel ratio and de Laval nozzle expansion and contraction ratios. In addition to the PSO-controlled parameters, engine performance was calculated based on propellant chemistry, combustion chamber pressure, and ambient pressure, which are provided as inputs to the program. The performance code was validated by comparison with NASA's Chemical Equilibrium with Applications (CEA) and the commercially available Rocket Propulsion Analysis (RPA) tool. Similarly, the PSO algorithm was validated by comparison with brute-force optimization, which calculates all possible solutions and subsequently determines which is the optimum. Particle Swarm Optimization was shown to be an effective optimizer capable of quick and reliable convergence for complex functions of multiple non-linear variables.

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

    Science.gov (United States)

    Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

    2016-01-01

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

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

    Science.gov (United States)

    Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

    2016-07-30

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

  13. Bell-shaped size selection in a bottom trawl: A case study for Nephrops directed fishery with reduced catches of cod

    DEFF Research Database (Denmark)

    Lövgren, Johan; Herrmann, Bent; Feekings, Jordan P.

    2016-01-01

    and size selectivity have motivated the development of selective systems in trawl fisheries that utilize more than one selective device simultaneously. An example can be found in the Swedish demersal trawl fishery targeting Norway lobster (Nephrops norvegicus), which simultaneously aims at avoiding catches...

  14. Quick look tools for magnetic field retrievals from Swarm satellite data

    DEFF Research Database (Denmark)

    Kotsiaros, Stavros; Plank, Gernot; Haagmans, Roger

    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 differe...... magnetic field retrievals are performed for each orbiting Swarm satellite. By an intercomparison of the monthly solutions a fast diagnosis of the Swarm system performance can be done.......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...... near polar orbits between 300 and 550 km altitude. Goal of the current study is to achieve a fast diagnosis of the Swarm system performance in orbit during commission phase and operations of the spacecraft. With the help of a specially developed software package datasets are analyzed in terms...

  15. A Review of Swarm-Based 1D/2D Signal Processing

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    Horia Mihail Teodorescu

    2012-10-01

    Full Text Available While swarming behavior, widely encountered in nature, has recently sparked numerous models and interest in domains as optimization, data clustering, and control, their application to signal processing remains sporadic. In this paper I provide a unitary treatment and a review of former results obtained in signal filtering and enhancement using swarms. General equations are presented for these procedures and stability issues are considered, with examples. The paper overviews several swarming model I introduced in previous papers and provides new evidence of the applicability of these models in signal processing. In all the models for 1D signal processing, the key idea is that the swarm hunts a prey that impersonates the filtered signal. In the 2D models, the signal (image represents the “landscape” over which the swarm moves at a distance, while the swarm interacts with the signal (landscape. I provide and discuss details of the underlying theory of the models for processing time-domain signals and images. While this paper partly follows and summarizes previous papers, it nevertheless includes supplementary theoretical and algorithmic considerations and new results for both 1D and 2D signal processing. Although following either biological models or physical models in swarm algorithms is not generally accepted for technical applications, we prefer to emphasize the analogies established by our biomimetic approach with these two groups of models.

  16. Direct measurement of particle size and 3D velocity of a gas-solid pipe flow with digital holographic particle tracking velocimetry.

    Science.gov (United States)

    Wu, Yingchun; Wu, Xuecheng; Yao, Longchao; Gréhan, Gérard; Cen, Kefa

    2015-03-20

    The 3D measurement of the particles in a gas-solid pipe flow is of great interest, but remains challenging due to curved pipe walls in various engineering applications. Because of the astigmatism induced by the pipe, concentric ellipse fringes in the hologram of spherical particles are observed in the experiments. With a theoretical analysis of the particle holography by an ABCD matrix, the in-focus particle image can be reconstructed by the modified convolution method and fractional Fourier transform. Thereafter, the particle size, 3D position, and velocity are simultaneously measured by digital holographic particle tracking velocimetry (DHPTV). The successful application of DHPTV to the particle size and 3D velocity measurement in a glass pipe's flow can facilitate its 3D diagnostics.

  17. Microstructure of TiN coatings synthesized by direct pulsed Nd:YAG laser nitriding of titanium: Development of grain size, microstrain, and grain orientation

    Science.gov (United States)

    Höche, D.; Schikora, H.; Zutz, H.; Queitsch, R.; Emmel, A.; Schaaf, P.

    2008-05-01

    Pure titanium was irradiated by pulsed Nd:YAG laser irradiation in nitrogen atmosphere. As a result, nitrogen uptake and diffusion occurred and a TiN layer was synthesized at the titanium surface. These TiN coatings were analyzed by X-ray diffraction and the diffraction patterns were investigated in detail, in order to obtain more information about the physical processes during the coating formation. The diffraction peaks were fitted by Pearson VII profiles and the grain size and the microstrain were determined by the analysis of line broadening and peak shifts, using the Williamson-Hall and the Warren-Averbach formalisms. Additional single-line analyses were performed by means of the method of Langford and Keijser to obtain information about the preferred grain orientation and the texture development. The maximum grain size was about 100 nm and a corresponding average lattice strain of 0.002 was found. A relation between the treatment parameters and the coating properties, such as grain size and microstrain, can be shown. Thus, it was possible to determine optimal scan parameters for material processing and to establish the physical limits of the coating properties.

  18. Nonlinear dynamics optimization with particle swarm and genetic algorithms for SPEAR3 emittance upgrade

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Xiaobiao; Safranek, James

    2014-09-01

    Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.

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

    DEFF Research Database (Denmark)

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

    More than two 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...... 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...

  20. Research on Multiple Particle Swarm Algorithm Based on Analysis of Scientific Materials

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    Zhao Hongwei

    2017-01-01

    Full Text Available This paper proposed an improved particle swarm optimization algorithm based on analysis of scientific materials. The core thesis of MPSO (Multiple Particle Swarm Algorithm is to improve the single population PSO to interactive multi-swarms, which is used to settle the problem of being trapped into local minima during later iterations because it is lack of diversity. The simulation results show that the convergence rate is fast and the search performance is good, and it has achieved very good results.

  1. Anaerobic respiration using a complete oxidative TCA cycle drives multicellular swarming in Proteus mirabilis.

    Science.gov (United States)

    Alteri, Christopher J; Himpsl, Stephanie D; Engstrom, Michael D; Mobley, Harry L T

    2012-10-30

    Proteus mirabilis rapidly migrates across surfaces using a periodic developmental process of differentiation alternating between short swimmer cells and elongated hyperflagellated swarmer cells. To undergo this vigorous flagellum-mediated motility, bacteria must generate a substantial proton gradient across their cytoplasmic membranes by using available energy pathways. We sought to identify the link between energy pathways and swarming differentiation by examining the behavior of defined central metabolism mutants. Mutations in the tricarboxylic acid (TCA) cycle (fumC and sdhB mutants) caused altered patterns of swarming periodicity, suggesting an aerobic pathway. Surprisingly, the wild-type strain swarmed on agar containing sodium azide, which poisons aerobic respiration; the fumC TCA cycle mutant, however, was unable to swarm on azide. To identify other contributing energy pathways, we screened transposon mutants for loss of swarming on sodium azide and found insertions in the following genes that involved fumarate metabolism or respiration: hybB, encoding hydrogenase; fumC, encoding fumarase; argH, encoding argininosuccinate lyase (generates fumarate); and a quinone hydroxylase gene. These findings validated the screen and suggested involvement of anaerobic electron transport chain components. Abnormal swarming periodicity of fumC and sdhB mutants was associated with the excretion of reduced acidic fermentation end products. Bacteria lacking SdhB were rescued to wild-type pH and periodicity by providing fumarate, independent of carbon source but dependent on oxygen, while fumC mutants were rescued by glycerol, independent of fumarate only under anaerobic conditions. These findings link multicellular swarming patterns with fumarate metabolism and membrane electron transport using a previously unappreciated configuration of both aerobic and anaerobic respiratory chain components. Bacterial locomotion and the existence of microbes were the first scientific

  2. An Improved Particle Swarm Optimization for the Automobile Spare Part Warehouse Location Problem

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    Zhen Yaobao

    2013-01-01

    Full Text Available This paper deals with a real-life warehouse location problem, which is an automobile spare part warehouse location problem. Since the automobile spare part warehouse location problem is a very complex problem, particle swarm optimization is used and some improved strategies are proposed to improve the performance of this algorithm. At last, the computational results of the benchmark problems about warehouse location problems are used to examine the effectiveness of particle swarm optimization. Then the results of the real-life automobile spare part warehouse location problem also indicate that the improved particle swarm optimization is a feasible method to solve the warehouse location problem.

  3. Swarming and complex pattern formation in Paenibacillus vortex studied by imaging and tracking cells

    Directory of Open Access Journals (Sweden)

    Jacob Eshel

    2008-02-01

    Full Text Available Abstract Background Swarming motility allows microorganisms to move rapidly over surfaces. The Gram-positive bacterium Paenibacillus vortex exhibits advanced cooperative motility on agar plates resulting in intricate colonial patterns with geometries that are highly sensitive to the environment. The cellular mechanisms that underpin the complex multicellular organization of such a simple organism are not well understood. Results Swarming by P. vortex was studied by real-time light microscopy, by in situ scanning electron microscopy and by tracking the spread of antibiotic-resistant cells within antibiotic-sensitive colonies. When swarming, P. vortex was found to be peritrichously flagellated. Swarming by the curved cells of P. vortex occurred on an extremely wide range of media and agar concentrations (0.3 to 2.2% w/v. At high agar concentrations (> 1% w/v rotating colonies formed that could be detached from the main mass of cells by withdrawal of cells into the latter. On lower percentage agars, cells moved in an extended network composed of interconnected "snakes" with short-term collision avoidance and sensitivity to extracts from swarming cells. P. vortex formed single Petri dish-wide "supercolonies" with a colony-wide exchange of motile cells. Swarming cells were coupled by rapidly forming, reversible and non-rigid connections to form a loose raft, apparently connected via flagella. Inhibitors of swarming (p-Nitrophenylglycerol and Congo Red were identified. Mitomycin C was used to trigger filamentation without inhibiting growth or swarming; this facilitated dissection of the detail of swarming. Mitomycin C treatment resulted in malcoordinated swarming and abortive side branch formation and a strong tendency by a subpopulation of the cells to form minimal rotating aggregates of only a few cells. Conclusion P. vortex creates complex macroscopic colonies within which there is considerable reflux and movement and interaction of cells. Cell

  4. Direct determination of highly size-resolved turbulent particle fluxes with the disjunct eddy covariance method and a 12 – stage electrical low pressure impactor

    Directory of Open Access Journals (Sweden)

    A. Schmidt

    2008-12-01

    Full Text Available During summer 2007, turbulent vertical particle mass and number fluxes were measured for a period of 98 days near the city centre of Münster in north-west Germany. For this purpose, a valve controlled disjunct eddy covariance system was mounted at 65 m a.g.l. on a military radio tower. The concentration values for 11 size bins with aerodynamic diameters (D50 from 0.03 to 10 μm were measured with an electrical low pressure impactor. After comparison with other fluxes obtained from 10 Hz measurements with the classical eddy covariance method, the loss of information concerning high frequent parts of the flux could be stated as negligible. The results offer an extended insight in the turbulent atmospheric exchange of aerosol particles by highly size-resolved particle fluxes covering 11 size bins and show that the city of Münster acts as a relevant source for aerosol particles.

    Significant differences occur between the fluxes of the various particle size classes. While the total particle number flux shows a pattern which is strictly correlated to the diurnal course of the turbulence regime and the traffic intensity, the total mass flux exhibits a single minimum in the evening hours when coarse particles start to deposit.

    As a result, a mean mass deposition of about 10 mg m−2 per day was found above the urban test site, covering the aerosol size range from 40 nm to 2.0 μm. By contrast, the half-hourly total number fluxes accumulated over the lower ELPI stages range from −4.29×107 to +1.44×108 particles m−2 s−1 and are clearly dominated by the sub-micron particle fraction of the impactor stages with diameters between 40 nm and 320 nm. The averaged number fluxes of particles with diameters between 2.0 and 6.4 μm show lower turbulent dynamics during daytime and partially remarkably high negative fluxes with mean deposition velocities of 2×10−3 m

  5. Direct determination of highly size-resolved turbulent particle fluxes with the disjunct eddy covariance method and a 12 - stage electrical low pressure impactor

    Science.gov (United States)

    Schmidt, A.; Klemm, O.

    2008-12-01

    During summer 2007, turbulent vertical particle mass and number fluxes were measured for a period of 98 days near the city centre of Münster in north-west Germany. For this purpose, a valve controlled disjunct eddy covariance system was mounted at 65 m a.g.l. on a military radio tower. The concentration values for 11 size bins with aerodynamic diameters (D50) from 0.03 to 10 μm were measured with an electrical low pressure impactor. After comparison with other fluxes obtained from 10 Hz measurements with the classical eddy covariance method, the loss of information concerning high frequent parts of the flux could be stated as negligible. The results offer an extended insight in the turbulent atmospheric exchange of aerosol particles by highly size-resolved particle fluxes covering 11 size bins and show that the city of Münster acts as a relevant source for aerosol particles. Significant differences occur between the fluxes of the various particle size classes. While the total particle number flux shows a pattern which is strictly correlated to the diurnal course of the turbulence regime and the traffic intensity, the total mass flux exhibits a single minimum in the evening hours when coarse particles start to deposit. As a result, a mean mass deposition of about 10 mg m-2 per day was found above the urban test site, covering the aerosol size range from 40 nm to 2.0 μm. By contrast, the half-hourly total number fluxes accumulated over the lower ELPI stages range from -4.29×107 to +1.44×108 particles m-2 s-1 and are clearly dominated by the sub-micron particle fraction of the impactor stages with diameters between 40 nm and 320 nm. The averaged number fluxes of particles with diameters between 2.0 and 6.4 μm show lower turbulent dynamics during daytime and partially remarkably high negative fluxes with mean deposition velocities of 2×10-3 m s-1 that appear temporary during noontime and in the evening hours.

  6. Swarm intelligence in fish? The difficulty in demonstrating distributed and self-organised collective intelligence in (some) animal groups.

    Science.gov (United States)

    Ioannou, Christos C

    2017-08-01

    Larger groups often have a greater ability to solve cognitive tasks compared to smaller ones or lone individuals. This is well established in social insects, navigating flocks of birds, and in groups of prey collectively vigilant for predators. Research in social insects has convincingly shown that improved cognitive performance can arise from self-organised local interactions between individuals that integrates their contributions, often referred to as swarm intelligence. This emergent collective intelligence has gained in popularity and been directly applied to groups of other animals, including fish. Despite being a likely mechanism at least partially explaining group performance in vertebrates, I argue here that other possible explanations are rarely ruled out in empirical studies. Hence, evidence for self-organised collective (or 'swarm') intelligence in fish is not as strong as it would first appear. These other explanations, the 'pool-of-competence' and the greater cognitive ability of individuals when in larger groups, are also reviewed. Also discussed is why improved group performance in general may be less often observed in animals such as shoaling fish compared to social insects. This review intends to highlight the difficulties in exploring collective intelligence in animal groups, ideally leading to further empirical work to illuminate these issues. Copyright © 2016 The Author. Published by Elsevier B.V. All rights reserved.

  7. Collision avoidance during group evasive manoeuvres: a comparison of real versus simulated swarms with manipulated vision and surface wave detectors.

    Science.gov (United States)

    Romey, William L; Miller, Magenta M; Vidal, Jose M

    2014-08-07

    Coordinated group motion has been studied extensively both in real systems (flocks, swarms and schools) and in simulations (self-propelled particle (SPP) models using attraction and repulsion rules). Rarely are attraction and repulsion rules manipulated, and the resulting emergent behaviours of real and simulation systems are compared. We compare swarms of sensory-deprived whirligig beetles with matching simulation models. Whirligigs live at the water's surface and coordinate their grouping using their eyes and antennae. We filmed groups of beetles in which antennae or eyes had been unilaterally obstructed and measured individual and group behaviours. We then developed and compared eight SPP simulation models. Eye-less beetles formed larger diameter resting groups than antenna-less or control groups. Antenna-less groups collided more often with each other during evasive group movements than did eye-less or control groups. Simulations of antenna-less individuals produced no difference from a control (or a slight decrease) in group diameter. Simulations of eye-less individuals produced an increase in group diameter. Our study is important in (i) differentiating between group attraction and repulsion rules, (ii) directly comparing emergent properties of real and simulated groups, and (iii) exploring a new sensory modality (surface wave detection) to coordinate group movement. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  8. Some possible correlations between electro-magnetic emission and seismic activity during West Bohemia 2008 earthquake swarm

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    P. Kolář

    2010-10-01

    Full Text Available A potential link between electromagnetic emission (EME and seismic activity (SA has been the subject of scientific speculations for a long time. EME versus SA relations obtained during the 2008 earthquake swarm which occurred in West Bohemia are presented. First, a brief characterisation of the seismic region and then the EME recording method and data analysis will be described. No simple direct link between EME and SA intensity was observed, nevertheless a deeper statistical analysis indicates: (i slight increase of EME activity in the time interval 60 to 30 min before a seismic event with prevalent periods about 10 min, (ii some gap in EME activity approximately 2 h after the event, and (iii again a flat maximum about 4 h after the seismic events. These results qualitatively correspond with the observations from other seismically active regions (Fraser-Smith et al., 1990. The global decrease of EME activity correlating with the swarm activity decay was also observed. Due to the incomplete EME data and short observation time, these results are limited in reliability and are indicative only.

  9. An Immune Cooperative Particle Swarm Optimization Algorithm for Fault-Tolerant Routing Optimization in Heterogeneous Wireless Sensor Networks

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    Yifan Hu

    2012-01-01

    Full Text Available The fault-tolerant routing problem is important consideration in the design of heterogeneous wireless sensor networks (H-WSNs applications, and has recently been attracting growing research interests. In order to maintain k disjoint communication paths from source sensors to the macronodes, we present a hybrid routing scheme and model, in which multiple paths are calculated and maintained in advance, and alternate paths are created once the previous routing is broken. Then, we propose an immune cooperative particle swarm optimization algorithm (ICPSOA in the model to provide the fast routing recovery and reconstruct the network topology for path failure in H-WSNs. In the ICPSOA, mutation direction of the particle is determined by multi-swarm evolution equation, and its diversity is improved by immune mechanism, which can enhance the capacity of global search and improve the converging rate of the algorithm. Then we validate this theoretical model with simulation results. The results indicate that the ICPSOA-based fault-tolerant routing protocol outperforms several other protocols due to its capability of fast routing recovery mechanism, reliable communications, and prolonging the lifetime of WSNs.

  10. A Serratia marcescens PigP Homolog Controls Prodigiosin Biosynthesis, Swarming Motility and Hemolysis and Is Regulated by cAMP-CRP and HexS

    Science.gov (United States)

    Shanks, Robert M. Q.; Lahr, Roni M.; Stella, Nicholas A.; Arena, Kristin E.; Brothers, Kimberly M.; Kwak, Daniel H.; Liu, Xinyu; Kalivoda, Eric J.

    2013-01-01

    Swarming motility and hemolysis are virulence-associated determinants for a wide array of pathogenic bacteria. The broad host-range opportunistic pathogen Serratia marcescens produces serratamolide, a small cyclic amino-lipid, that promotes swarming motility and hemolysis. Serratamolide is negatively regulated by the transcription factors HexS and CRP. Positive regulators of serratamolide production are unknown. Similar to serratamolide, the antibiotic pigment, prodigiosin, is regulated by temperature, growth phase, HexS, and CRP. Because of this co-regulation, we tested the hypothesis that a homolog of the PigP transcription factor of the atypical Serratia species ATCC 39006, which positively regulates prodigiosin biosynthesis, is also a positive regulator of serratamolide production in S. marcescens. Mutation of pigP in clinical, environmental, and laboratory strains of S. marcescens conferred pleiotropic phenotypes including the loss of swarming motility, hemolysis, and severely reduced prodigiosin and serratamolide synthesis. Transcriptional analysis and electrophoretic mobility shift assays place PigP in a regulatory pathway with upstream regulators CRP and HexS. The data from this study identifies a positive regulator of serratamolide production, describes novel roles for the PigP transcription factor, shows for the first time that PigP directly regulates the pigment biosynthetic operon, and identifies upstream regulators of pigP. This study suggests that PigP is important for the ability of S. marcescens to compete in the environment. PMID:23469212

  11. Single phase bi-directional AC-DC converter with reduced passive components size and common mode electro-magnetic interference

    Energy Technology Data Exchange (ETDEWEB)

    Mi, Chris; Li, Siqi

    2017-01-31

    A bidirectional AC-DC converter is presented with reduced passive component size and common mode electro-magnetic interference. The converter includes an improved input stage formed by two coupled differential inductors, two coupled common and differential inductors, one differential capacitor and two common mode capacitors. With this input structure, the volume, weight and cost of the input stage can be reduced greatly. Additionally, the input current ripple and common mode electro-magnetic interference can be greatly attenuated, so lower switching frequency can be adopted to achieve higher efficiency.

  12. Effect of Mo Dispersion Size and Water Vapor on Oxidation of Two-Phase Directionally Solidified NiAl-9Mo In-Situ Composites

    Energy Technology Data Exchange (ETDEWEB)

    Brady, Michael P [ORNL; Bei, Hongbin [ORNL; Meisner, Roberta Ann [ORNL; Lance, Michael J [ORNL; Tortorelli, Peter F [ORNL

    2014-01-01

    Oxidation of two-phase NiAl-9Mo eutectics with 3 different growth rates/2nd phase Mo dispersion sizes were investigated at 900 C in air and air with 10% water vapor. Good oxidation resistance via alumina formation was observed in dry air, with Mo volatilization loss minimized by fine submicron Mo dispersions. However, extensive Mo volatilization and in-place internal oxidation of prior Mo phase regions was observed in wet air oxidation. Ramifications of this phenomenon for the development of multi-phase high-temperature alloys are discussed

  13. Phased Array Synthesis Using Modified Particle Swarm Optimization

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    M. A. Zaman

    2011-01-01

    Full Text Available In this paper, a linear phased array is synthesized to produce a desired far field radiation pattern with a constraint on sidelobe level and beamwidth. The amplitude of the excitation current of each individual array element is optimized to give desired sidelobe level and beamwidth. A modified particle swarm optimization (PSO algorithm with a novel inertial weight variation function and modified stochastic variables is used here. The performance of the modified PSO is compared with standard PSO in terms of amount of iterations required to get desired fitness value and convergence rate. Using optimized excitation amplitudes, the far field radiation pattern of the phased array is analyzed to verify whether the design criterions are satisfied.

  14. Parallelizing Particle Swarm Optimization in a Functional Programming Environment

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    Pablo Rabanal

    2014-10-01

    Full Text Available Many bioinspired methods are based on using several simple entities which search for a reasonable solution (somehow independently. This is the case of Particle Swarm Optimization (PSO, where many simple particles search for the optimum solution by using both their local information and the information of the best solution found so far by any of the other particles. Particles are partially independent, and we can take advantage of this fact to parallelize PSO programs. Unfortunately, providing good parallel implementations for each specific PSO program can be tricky and time-consuming for the programmer. In this paper we introduce several parallel functional skeletons which, given a sequential PSO implementation, automatically provide the corresponding parallel implementations of it. We use these skeletons and report some experimental results. We observe that, despite the low effort required by programmers to use these skeletons, empirical results show that skeletons reach reasonable speedups.

  15. R2-Based Multi/Many-Objective Particle Swarm Optimization

    Science.gov (United States)

    Toscano, Gregorio; Barron-Zambrano, Jose Hugo; Tello-Leal, Edgar

    2016-01-01

    We propose to couple the R2 performance measure and Particle Swarm Optimization in order to handle multi/many-objective problems. Our proposal shows that through a well-designed interaction process we could maintain the metaheuristic almost inalterable and through the R2 performance measure we did not use neither an external archive nor Pareto dominance to guide the search. The proposed approach is validated using several test problems and performance measures commonly adopted in the specialized literature. Results indicate that the proposed algorithm produces results that are competitive with respect to those obtained by four well-known MOEAs. Additionally, we validate our proposal in many-objective optimization problems. In these problems, our approach showed its main strength, since it could outperform another well-known indicator-based MOEA. PMID:27656200

  16. A Triangle Mesh Standardization Method Based on Particle Swarm Optimization.

    Science.gov (United States)

    Wang, Wuli; Duan, Liming; Bai, Yang; Wang, Haoyu; Shao, Hui; Zhong, Siyang

    2016-01-01

    To enhance the triangle quality of a reconstructed triangle mesh, a novel triangle mesh standardization method based on particle swarm optimization (PSO) is proposed. First, each vertex of the mesh and its first order vertices are fitted to a cubic curve surface by using least square method. Additionally, based on the condition that the local fitted surface is the searching region of PSO and the best average quality of the local triangles is the goal, the vertex position of the mesh is regulated. Finally, the threshold of the normal angle between the original vertex and regulated vertex is used to determine whether the vertex needs to be adjusted to preserve the detailed features of the mesh. Compared with existing methods, experimental results show that the proposed method can effectively improve the triangle quality of the mesh while preserving the geometric features and details of the original mesh.

  17. Lifecycle-Based Swarm Optimization Method for Numerical Optimization

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    Hai Shen

    2014-01-01

    Full Text Available Bioinspired optimization algorithms have been widely used to solve various scientific and engineering problems. Inspired by biological lifecycle, this paper presents a novel optimization algorithm called lifecycle-based swarm optimization (LSO. Biological lifecycle includes four stages: birth, growth, reproduction, and death. With this process, even though individual organism died, the species will not perish. Furthermore, species will have stronger ability of adaptation to the environment and achieve perfect evolution. LSO simulates Biological lifecycle process through six optimization operators: chemotactic, assimilation, transposition, crossover, selection, and mutation. In addition, the spatial distribution of initialization population meets clumped distribution. Experiments were conducted on unconstrained benchmark optimization problems and mechanical design optimization problems. Unconstrained benchmark problems include both unimodal and multimodal cases the demonstration of the optimal performance and stability, and the mechanical design problem was tested for algorithm practicability. The results demonstrate remarkable performance of the LSO algorithm on all chosen benchmark functions when compared to several successful optimization techniques.

  18. MAKHA—A New Hybrid Swarm Intelligence Global Optimization Algorithm

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    Ahmed M.E. Khalil

    2015-06-01

    Full Text Available The search for efficient and reliable bio-inspired optimization methods continues to be an active topic of research due to the wide application of the developed methods. In this study, we developed a reliable and efficient optimization method via the hybridization of two bio-inspired swarm intelligence optimization algorithms, namely, the Monkey Algorithm (MA and the Krill Herd Algorithm (KHA. The hybridization made use of the efficient steps in each of the two original algorithms and provided a better balance between the exploration/diversification steps and the exploitation/intensification steps. The new hybrid algorithm, MAKHA, was rigorously tested with 27 benchmark problems and its results were compared with the results of the two original algorithms. MAKHA proved to be considerably more reliable and more efficient in tested problems.

  19. DESIGN OF MICROSTRIP RADIATOR USING PARTICLE SWARM OPTIMIZATION TECHNIQUE

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    Yogesh Kumar Choukiker

    2011-09-01

    Full Text Available An inset feed Microstrip radiator has been designed and developed for operation at 2.4GHz frequency. The Microstrip patch antenna (MPA parameters were designed using IE3D®TM EM simulator (version 14.0 and optimized with an evolutionary stochastic optimizer i.e. Particle Swarm Optimization (PSO technique. Optimized results show that the antenna has a bandwidth of 33.54 MHz (<-10dB in the range 2.38355 GHz to 2.41709 GHz and a maximum return loss of -43.87dB at the resonant frequency of 2.4 GHz. The patch antenna is fabricated and the important parameters like return loss, VSWR etc were measured. The measured parameters match with the simulated results well within the tolerable limits.

  20. Improving Vector Evaluated Particle Swarm Optimisation Using Multiple Nondominated Leaders

    Science.gov (United States)

    Lim, Kian Sheng; Buyamin, Salinda; Ahmad, Anita; Shapiai, Mohd Ibrahim; Naim, Faradila; Mubin, Marizan; Kim, Dong Hwa

    2014-01-01

    The vector evaluated particle swarm optimisation (VEPSO) algorithm was previously improved by incorporating nondominated solutions for solving multiobjective optimisation problems. However, the obtained solutions did not converge close to the Pareto front and also did not distribute evenly over the Pareto front. Therefore, in this study, the concept of multiple nondominated leaders is incorporated to further improve the VEPSO algorithm. Hence, multiple nondominated solutions that are best at a respective objective function are used to guide particles in finding optimal solutions. The improved VEPSO is measured by the number of nondominated solutions found, generational distance, spread, and hypervolume. The results from the conducted experiments show that the proposed VEPSO significantly improved the existing VEPSO algorithms. PMID:24883386