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Context: Our previous models of a giant planet migrating through an inner protoplanet/planetesimal disk find that the giant shepherds a portion of the material it encounters into interior orbits, whilst scattering the rest into external orbits. Scattering tends to dominate, leaving behind abundant material that can accrete into terrestrial planets. Aims: We add to the possible realism of our model by simulating type I migration forces which cause an inward drift, and strong eccentricity and inclination damping of protoplanetary bodies. This extra dissipation might be expected to enhance shepherding at the expense of scattering, possibly modifying our previous conclusions. Methods: We employ an N-body code that is linked to a viscous gas disk algorithm capable of simulating: gas accretion onto the central star; gap formation in the vicinity of the giant planet; type II migration of the giant planet; type I migration of protoplanets; and the ...

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Particle Swarm Optimization

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BackgroundWe examined the effects of short-term consumption of whey protein isolate on muscle proteins and force recovery after eccentrically-induced muscle damage in healthy individuals.MethodsSeventeen...Full Text Available

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A debris disk is a constituent of any planetary system surrounding a main sequence star. We study whether close stellar encounters can disrupt and strip a debris disk of its planetesimals in the expanding open cluster of its birth. Such stripping would affect the dust production and hence detectability of the disk. We tabulated the fractions of planetesimals stripped off during stellar flybys of miss distances between 100 and 1000 AU and for several mass ratios of the central to passing stars. We then estimated the numbers of close stellar encounters over the lifetime of several expanding open clusters characterized by their initial star densities. We found that a standard disk, with inner and outer radii of 40 and 100 AU, suffers no loss of planetesimals around a star born in a common embedded cluster with star density 20 000 pc^-3. In this environment, a disk loses >97% of its planetesimals around ...

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We present a new computation of the linear tidal interaction of a protoplanetary core with a thin gaseous disc in which it is fully embedded. For the first time a discussion of the orbital evolution of cores with eccentricity (e) significantly larger than the gas-disc scale height to radius ratio (H/r) is given. We find that the direction of orbital migration reverses for e>1.1H/r. This occurs as a result of the orbital crossing of resonances in the disc that do not overlap the orbit when the eccentricity is very small. Simple expressions giving approximate fits to the eccentricity damping rate and the orbital migration rate are presented. We go on to calculate the rate of increase of the mean eccentricity for a system of protoplanetary cores due to dynamical relaxation. By equating the eccentricity damping time-scale with the dynamical relaxation time-scale we deduce that an ...

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A dissipative particle swarm optimization is developed according to the self-organization of dissipative structure. The negative entropy is introduced to construct an opening dissipative system that is far-from-equilibrium so as to driving the irreversible evolution process with better fitness. The testing of two multimodal functions indicates it improves the performance effectively

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Computing Networks (CNs) are defined. These are used to generalize neural and swarm architectures, namely artificial neural networks, ant colony optimization, and particle swarm optimization. The description of these architectures as CNs allows their comparison, distinguishing which properties enable them to perform complex computations and exhibit complex cognitive abilities. In this context, the most relevant characteristics of CNs are the existence multiple dynamical and functional scales.

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Two general categories are discussed concerning the evolution of the solar system: the dualistic view, the planetesimal approach and the monistic view, the nebular hypothesis. The major points of each view are given and the models that are developed from these views are described. Possible applications of gamma ray astronomical observations to the question of the dynamic evolution of the solar system are discussed.

UK PubMed Central (United Kingdom)

The purpose of this study was to determine if there were any beneficial or detrimental effects regarding delayed onset muscle soreness (DOMS), serum creatine kinase (CK), and maximum concentric strength...Full Text Available

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Extrasolar debris disks that are bright enough to be observed are dense enough to be collision-dominated; i.e., the small grains that produce their infrared excess have collisional lifetimes shorter than their Poynting-Robertson decay times. This paper describes a numerical code for the modeling of such disks, including accretion and gravitational stirring as well as disruptive collisions. A constraint relating the mass of a debris disk and the sizes of the largest embedded bodies to its luminosity is demonstrated. The collisional code is applied to the debris disk around HD 12039, which has been intensively observed by the Spitzer Space Telescope. The evolution in time of the disk's luminosity is computed for a range of initial disk masses and planetesimal sizes. The luminosity at a given age depends on both the initial disk mass and the initial size of the planetesimals. Luminosity decays more rapidly for massive disks due to the combination ...

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Two-dimensional generalization of the original peak finding algorithm suggested earlier is given. The ideology of the algorithm emerged from the well known quantum mechanical tunneling property which enables small bodies to penetrate through narrow potential barriers. We further merge this ``quantum'' ideology with the philosophy of Particle Swarm Optimization to get the global optimization algorithm which can be called Quantum Swarm Optimization. The functionality of the newborn algorithm is tested on some benchmark optimization problems.

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This paper uses multi-pass iteration particle swarm optimization (MIPSO) to solve short term hydroelectric generation scheduling of a power system with wind turbine generators. MIPSO is a new algorithm for solving nonlinear optimal scheduling problems. A new index called iteration best (IB) is incorporated into particle swarm optimization (PSO) to improve solution quality. The concept of multi-pass dynamic programming is applied to modify PSO further and improve computation efficiency.The feasible operational regions of the hydro units and pumped storage plants over the whole scheduling time range must be determined before applying MIPSO to the problem. Wind turbine power generation then shaves the power system load curves. Next, MIPSO calculates hydroelectric generation scheduling. It beg...

UK PubMed Central (United Kingdom)

Xenorhabdus is a major insect pathogen symbiotically associated with nematodes of the family Steinernematidae. This motile bacterium displays swarming behavior on suitable media, but...Full Text Available

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In this paper we study different effects of excited molecules on swarm parameters, electron energy distribution functions and gas discharge modeling. First we discuss a possible experiment in parahydrogen to resolve the discrepancy in hydrogen vibrational excitation cross section data. Negative differential conductivity (NDC) is a kinetic phenomenon which manifests itself in a particular dependence of the drift velocity on E=N and it is affected by superelastic collisions with excited states. A complete kinetic scheme for argon required to model excited state densities in gas discharges is also described. These results are used to explain experiments in capacitively and inductively coupled RF plasmas used for processing. The paper illustrates the application of atomic and molecular collision data, swarm data and the theoretical techniques in modeling of gas discharges with large abundances of excited molecules. It is pointed out that ...

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Fiber delivered laser pulses emulsify thrombus by mechanical stresses that include a combination of pressure, tension and shear stress. Laser radiation is delivered to the locality of a thrombus and the radiation is absorbed by blood, blood dot, or other present materials. The combination of a leading pressure wave and subsequent vapor bubble cause efficient, emulsification of thrombus. Operating the laser in a low average power mode alleviates potential thermal complications. The laser is operated in a high repetition rate mode to take advantage of ultrasound frequency effects of thrombus dissolution as well as to decrease the total procedure time. Specific parameter ranges for operation are described. The device includes optical fibers surrounding a lumen intended for flow of a cooling agent. The fibers may be arranged concentrically around the lumen to deliver radiation and heat over as large an area as possible. An alternative design approach incorporates the optical fibers into ...

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This paper uses multi-pass iteration particle swarm optimization (MIPSO) to solve short term hydroelectric generation scheduling of a power system with wind turbine generators. MIPSO is a new algorithm for solving nonlinear optimal scheduling problems. A new index called iteration best (IB) is incorporated into particle swarm optimization (PSO) to improve solution quality. The concept of multi-pass dynamic programming is applied to modify PSO further and improve computation efficiency. The feasible operational regions of the hydro units and pumped storage plants over the whole scheduling time range must be determined before applying MIPSO to the problem. Wind turbine power generation then shaves the power system load curves. Next, MIPSO calculates hydroelectric generation scheduling. It begins with a coarse time stage and searching space and refines the time interval between two time stages and the search spacing pass by pass (iteration). With ...

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The intent and purpose of this work was to investigate and demonstrate cooperative behavior among a group of mobile robot machines. The specific goal of this work was to build a small swarm of identical machines and control them in such a way as to show a coordinated movement of the group in a flocking manner, similar to that observed in nature. Control of the swarm`s individual members and its overall configuration is available to the human user via a graphic man-machine interface running on a base station control computer. Any robot may be designated as the nominal leader through the interface tool, which then may be commanded to proceed to a particular geographic destination. The remainder of the flock follows the leader by maintaining their relative positions in formation, as specified by the human controller through the interface. The formation`s configuration can be altered manually through an interactive graphic-based tool. An ...

CERN Document Server

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

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A new particle swarm optimization (PSO) technique for electromagnetic applications is proposed. The method is based on quantum mechanics rather than the Newtonian rules assumed in all previous versions of PSO, which we refer to as classical PSO. A general procedure is suggested to derive many different versions of the quantum PSO algorithm (QPSO). The QPSO is applied first to linear array antenna synthesis, which is one of the standard problems used by antenna engineers. The performance of the QPSO is compared against an improved version of the classical PSO. The new algorithm outperforms the classical one most of the time in convergence speed and achieves better levels for the cost function. As another application, the algorithm is used to find a set of infinitesimal dipoles that produces the same near and far fields of a circular dielectric resonator antenna (DRA). In addition, the QPSO method is employed to find an equivalent circuit model for the DRA that can ...

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The detection and estimation of gravitational wave (GW) signals belonging to a parameterized family of waveforms requires, in general, the numerical maximization of a data-dependent function of the signal parameters. Due to noise in the data, the function to be maximized is often highly multi-modal with numerous local maxima. Searching for the global maximum then becomes computationally expensive, which in turn can limit the scientific scope of the search. Stochastic optimization is one possible approach to reducing computational costs in such applications. We report results from a first investigation of the Particle Swarm Optimization (PSO) method in this context. The method is applied to a testbed motivated by the problem of detection and estimation of a binary inspiral signal. Our results show that PSO works well in the presence of high multi-modality, making it a viable candidate method for further applications in GW data analysis.

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Term extraction is one of the layers in the ontology development process which has the task to extract all the terms contained in the input document automatically. The purpose of this process is to generate list of terms that are relevant to the domain of the input document. In the literature there are many approaches, techniques and algorithms used for term extraction. In this paper we propose a new approach using particle swarm optimization techniques in order to improve the accuracy of term extraction results. We choose five features to represent the term score. The approach has been applied to the domain of religious document. We compare our term extraction method precision with TFIDF, Weirdness, GlossaryExtraction and TermExtractor. The experimental results show that our propose approach achieve better precision than those four algorithm.

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We reconsider stochastic convergence analyses of particle swarm optimisation, and point out that previously obtained parameter conditions are not always sufficient to guarantee mean square convergence to a local optimum. We show that stagnation can in fact occur for non-trivial configurations in non-optimal parts of the search space, even for simple functions like SPHERE. The convergence properties of the basic PSO may in these situations be detrimental to the goal of optimisation, to discover a sufficiently good solution within reasonable time. To characterise optimisation ability of algorithms, we suggest the expected first hitting time (FHT), i.e., the time until a search point in the vicinity of the optimum is visited. It is shown that a basic PSO may have infinite expected FHT, while an algorithm introduced here, the Noisy PSO, has finite expected FHT on some functions.

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Obtaining the set of cosmological parameters consistent with observational data is an important exercise in current cosmological research. It involves finding the global maximum of the likelihood function in the multi-dimensional parameter space. Currently sampling based methods, which are in general stochastic in nature, like Markov-Chain Monte Carlo(MCMC), are being commonly used for parameter estimation. The beauty of stochastic methods is that the computational cost grows, at the most, linearly in place of exponentially (as in grid based approaches) with the dimensionality of the search space. MCMC methods sample the full joint probability distribution (posterior) from which one and two dimensional probability distributions, best fit (average) values of parameters and then error bars can be computed. In the present work we demonstrate the application of another stochastic method, named Particle Swarm Optimization (PSO), that is widely used in the field of ...

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System identification refers to estimation of process parameters and is a necessity in control theory. Physical systems usually have varying parameters. For such processes, accurate identification is particularly important. Online identification schemes are also needed for designing adaptive controllers. Real processes are usually of fractional order as opposed to the ideal integral order models. In this paper, we propose a simple and elegant scheme of estimating the parameters for such a fractional order process. A population of process models is generated and updated by particle swarm optimization (PSO) technique, the fitness function being the sum of squared deviations from the actual set of observations. Results show that the proposed scheme offers a high degree of accuracy even when the observations are corrupted to a significant degree. Additional schemes to improve the accuracy still further are also proposed and analyzed.

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Nature-inspired algorithms are among the most powerful algorithms for optimization. This paper intends to provide a detailed description of a new Firefly Algorithm (FA) for multimodal optimization applications. We will compare the proposed firefly algorithm with other metaheuristic algorithms such as particle swarm optimization (PSO). Simulations and results indicate that the proposed firefly algorithm is superior to existing metaheuristic algorithms. Finally we will discuss its applications and implications for further research.

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In this paper, we intend to formulate a new metaheuristic algorithm, called Cuckoo Search (CS), for solving optimization problems. This algorithm is based on the obligate brood parasitic behaviour of some cuckoo species in combination with the Levy flight behaviour of some birds and fruit flies. We validate the proposed algorithm against test functions and then compare its performance with those of genetic algorithms and particle swarm optimization. Finally, we discuss the implication of the results and suggestion for further research.

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We compare the accretion flow onto the neutron star induced by Roche lobe overflow with that by the overflow from the Be disk, in a zero eccentricity, short period binary with the same mass transfer rate, performing three-dimensional Smoothed Particle Hydrodynamics simulations. We find that a persistent accretion disk is formed around the neutron star in both cases. The circularization radius of the material transferred via Roche lobe overflow is larger than that of the material transfered from the Be disk. Thus, the growth of the accretion disk in the former case becomes significantly slower than in the latter case. In both cases, the mass accretion rate is very small and varies little with orbital phase, which is consistent with the observed X-ray behaviour of Be/X-ray binaries with circular orbits (e.g. XTE J1543-568).

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This paper presents a set of robust PI tuning formulae for a first order plus dead time process using particle swarm optimization. Also, tuning formulae for an integrating process with dead time, which is a special case of a first order plus dead time process, is given. The design problem considers three essential requirements of control problems, namely load disturbance rejection, setpoint regulation and robustness of closed-loop system against model uncertainties. The primary design goal is to optimize load disturbance rejection. Robustness is guaranteed by requiring that the maximum sensitivity is less than or equal to a specified value. In the first step, PI controller parameters are determined such that the IAE criterion to a load disturbance step is minimized and the robustness constraint on maximum sensitivity is satisfied. Using a structure with two degrees of freedom which introduces an extra parameter, the setpoint weight, good setpoint regulation is ...

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The Oklo natural fossil fission reactors in Gabon, Equatorial Africa, have been studied as a natural analogue for spent nuclear fuel in a geological environment. For these studies, it is important to know what has happened to these reactors since they formed. This review is focussed on existing geological and geochronological information concerning the Oklo reactors and the surrounding ore. A sequence of geological and geochemical events in the Oklo area, as described in the literature, is given. The data and the studies behind this established geochronology are discussed and evaluated. Of the regional geology, special attention is given to the dating of the Francevillian sediments, and the intrusion of a dolerite dyke swarm. The processes that led to the mineralisation at Oklo, the subsequent formation of the nuclear reactors and later migration of fission products are described. Further discussion concerns the studies of the dolerite dyke ...

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In this paper we have investigated the performance of PSO Particle Swarm Optimization based clustering on few real world data sets and one artificial data set. The performances are measured by two metric namely quantization error and inter-cluster distance. The K means clustering algorithm is first implemented for all data sets, the results of which form the basis of comparison of PSO based approaches. We have explored different variants of PSO such as gbest, lbest ring, lbest vonneumann and Hybrid PSO for comparison purposes. The results reveal that PSO based clustering algorithms perform better compared to K means in all data sets.

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System identification is a necessity in control theory. Classical control theory usually considers processes with integer order transfer functions. Real processes are usually of fractional order as opposed to the ideal integral order models. A simple and elegant scheme is presented for approximation of such a real world fractional order process by an ideal integral order model. A population of integral order process models is generated and updated by PSO technique, the fitness function being the sum of squared deviations from the set of observations obtained from the actual fractional order process. Results show that the proposed scheme offers a high degree of accuracy.

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Using a facility named SPHINX, which can accommodate a heat transfer test with CO{sub 2} at supercritical pressure, a series of tests was performed. The test geometries include tubes with the inner diameter of 4.4, 6.32 and 9 mm. a concentric annular passages with 8 x 10 mm, and an eccentric annular passages with 9.5 x 12.5 mm. Based on the test results, heat transfer correlations were developed and compared with the existing correlations. The heat transfer deterioration which may occur at certain conditions of heat and mass flux, were carefully studied and the published criteria were reviewed against our test results. Numerical calculation by using commercial CFD code, Fluent, were performed in order to provide the pre-test information for the heat transfer tests. Various turbulence models were evaluated and reliable models were suggested for each case

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Most of the presently identified exoplanets have masses similar to that of Jupiter and therefore are assumed to be gaseous objects. With the ever-increasing interest in discovering lower-mass planets, several of the so-called super-Earths (i.e., with masses in the interval 1 M_earth < M < 10 M_earth), which are predicted to be rocky, have already been found. Here we report the possible discovery of a planet around the M-type star GJ 436 with a minimum mass of 4.8+/-0.6 M_earth and a true mass of ~5 M_earth, which makes it the least massive planet around a main-sequence star found to date. In contrast with other discoveries, the planet is identified from its perturbations on an inner Neptune-mass transiting planet (GJ 436b), by pumping eccentricity and producing secular variations in the orbital inclination. Analysis of published radial velocity measurements indeed reveals a significant signal corresponding to an orbital period that is very close to the 2:1 ...

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Feature selection refers to the problem of selecting relevant features which produce the most predictive outcome. In particular, feature selection task is involved in datasets containing huge number of features. Rough set theory has been one of the most successful methods used for feature selection. However, this method is still not able to find optimal subsets. This paper proposes a new feature selection method based on Rough set theory hybrid with Bee Colony Optimization (BCO) in an attempt to combat this. This proposed work is applied in the medical domain to find the minimal reducts and experimentally compared with the Quick Reduct, Entropy Based Reduct, and other hybrid Rough Set methods such as Genetic Algorithm (GA), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO).

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FastSLAM is a framework for simultaneous localization using a Rao-Blackwellized particle filter. In FastSLAM, particle filter is used for the mobile robot pose (position and orientation) estimation, and an Extended Kalman Filter (EKF) is used for the feature location's estimation. However, FastSLAM degenerates over time. This degeneracy is due to the fact that a particle set estimating the pose of the robot loses its diversity. One of the main reasons for loosing particle diversity in FastSLAM is sample impoverishment. It occurs when likelihood lies in the tail of the proposal distribution. In this case, most of particle weights are insignificant. Another problem of FastSLAM relates to the design of an extended Kalman filter for landmark position's estimation. The performance of the EKF and the quality of the estimation depends heavily on correct a priori knowledge of the process and measurement noise covariance matrices (Q and R) that are in most applications unknown. On the other ...

International Nuclear Information System (INIS)

The paper develops a new design procedure for simultaneous coordinated designing of the thyristor controlled series capacitor (TCSC) damping controller and power system stabilizer (PSS) in multi-machine power system. The coordinated design problem of PSS and TCSC damping controllers over a wide range of loading conditions is converted to an optimization problem with the time domain-based objective function that is solved by a particle swarm optimization (PSO) technique which has a strong ability to find the most optimistic results. By minimizing the proposed fitness function in which oscillatory characteristics between areas are included and thus the interactions among the TCSC controller and PSS under transient conditions in the multi-machine power system are improved. To ensure the robustness of the proposed stabilizers, the design process takes a wide range of operating conditions into account. The effectiveness of the proposed controller is demonstrated through ...

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The relationship between the fractal dimensions of spatial distributions of aftershocks and pre-existing active faults is examined. Fourteen mainshocks taking place in Japan were followed by aftershocks, and the aftershocks occur in swarms around the mainshocks. The epicentral distributions of the aftershocks exhibit fractal properties, and the fractal dimensions are estimated by using the two-point correlation integral. The pre-existing active fault systems observed in the 14 aftershock regions have fractal structures, and the fractal dimensions are estimated by using the box-counting method. A positive correlation between the estimated fractal dimensions is found, and it is independent on the mainshock magnitude. The correlation shows that aftershock distributions become less clustered with increasing the fractal dimensions of active fault systems. Namely, the fractal clusters of aftershocks are put under the constraint of the fractal properties of the ...

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This paper introduces an indirect adaptive fuzzy controller as a power system stabilizer used to damp inter-area modes of oscillation following disturbances in power systems. Compared to the IEEE standard multi-band power system stabilizer (MB-PSS), indirect adaptive fuzzy-based stabilizers are more efficient because they can cope with oscillations at different operating points. A nominal model of the power system is identified on-line using a variable structure identifier. A feedback linearization-based control law is implemented using the identified model. The gains of the controller are tuned via a particle swarm optimization routine to ensure system stability and minimum sum of the squares of the speed deviations. A bench-mark problem of a 4-machine 2-area power system is used to demonstrate the performance of the proposed controller and to show its superiority over other conventional stabilizers used in the literature. (author)

International Nuclear Information System (INIS)

This paper introduces a robust searching hybrid evolutionary algorithm to solve the multi-objective Distribution Feeder Reconfiguration (DFR). The main objective of the DFR is to minimize the real power loss, deviation of the nodes' voltage, the number of switching operations, and balance the loads on the feeders. Because of the fact that the objectives are different and no commensurable, it is difficult to solve the problem by conventional approaches that may optimize a single objective. This paper presents a new approach based on norm3 for the DFR problem. In the proposed method, the objective functions are considered as a vector and the aim is to maximize the distance (norm2) between the objective function vector and the worst objective function vector while the constraints are met. Since the proposed DFR is a multi objective and non-differentiable optimization problem, a new hybrid evolutionary algorithm (EA) based on the combination of the Honey Bee Mating Optimization (HBMO) and ...

International Nuclear Information System (INIS)

The evaluate the signs of aortic intramural hematoma with helical CT and the diagnostic role of this technique in patients with this condition. It was reviewed the CT findings of 396 patients submitted to emergency examinations for suspected aortic dissection from 1995 to 1999. Only 18 patients (6 women and 12 men) had CT signs of aortic intramural hematoma. Helical CT studies were carried out with the following parameters: slice thickness 10 mm, reconstruction index 10, feed 1.5 mm, conventional algorithm with minimum values of 130 kV and 125mA. All patients were examined with dynamic contrast-enhanced CT, before and after a power injection of 130 mL ionic contrast material. It was studied: hematoma localization and longitudinal extension; thickness and density of aortic wall; presence and location of intimal calcifications; integrity of intimal wall; hemo mediastinum and/or hemo thorax. Aortic wall thickening appeared as a high density crescent-shaped area at baseline CT and had low ...

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Waveform correlation detectors compare a signal template with successive windows of a continuous data stream and report a detection when the correlation coefficient, or some comparable detection statistic, exceeds a specified threshold. Since correlation detectors exploit the fine structure of the full waveform, they are exquisitely sensitive when compared to power (STA/LTA) detectors. The drawback of correlation detectors is that they require complete knowledge of the signal to be detected, which limits such methods to instances of seismicity in which a very similar signal has already been observed by every station used. Such instances include earthquake swarms, aftershock sequences, repeating industrial seismicity, and many other forms of controlled explosions. The reduction in the detection threshold is even greater when the techniques are applied to arrays since stacking can be performed on the individual channel correlation traces to achieve significant array ...