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Late plagiogranite bodies in the Semail ophiolite have been previously suggested to represent late stage fractionates within an episodic spreading center magma chamber or the roots of seamount chains. Field and lab observations suggest that these late silicic magma chambers represent zones of repeated injection by dikes of intermediate to mafic composition. Multiple generations of intrusion, partial resorption and reintrusion are preserved in the plagiogranite as 1) relict phantom xenoliths, 2) angular xenoliths with quartz-rich margins, 3) deformed fine-grained dikes with distinct chilled margins, and 4) planes of rectangular blocks with cuspate margins or ellipsoids of similar fine grained mafic materials. The blocks and ellipsoids are actually dismembered mafic dikes that chilled by intruding a cooler silicic liquid and were either thermally fractured or ...

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Seismic transects in this area show a strongly reflective Moho of generally low relief, which, in the area of modern transects, consists of a thin zone (< 2 km thick) of short reflectors. The upper mantle is transparent and has a P{sub n} of 7.8-8.0 km/s similar to much of the western US. A lower crustal zone, 2-13 km thick, has variable internal reflectivity and a relatively low velocity of 6.6-6.8 km/s. Upper mantle peridotite xenoliths show both ductile and brittle deformational features and have structures and composition affected by magmatic intrusion; intrusions form complex dike systems and extensive zones of grain boundary infiltration in peridotite xenoliths. Whereas melt infiltration preceded and followed ductile deformation, brittle deformation, represented by closely spaced joint systems and faults, followed ductile deformation and is related to the youngest magmatic episodes. Lower crustal xenoliths are dominantly igneous-textured pyroxenites and ...

CERN Document Server

Particle Swarm Optimization

CERN Document Server

The periodic mode is analyzed together with two conventional boundary handling modes for particle swarm. By providing an infinite space that comprises periodic copies of original search space, it avoids possible disorganizing of particle swarm that is induced by the undesired mutations at the boundary. The results on benchmark functions show that particle swarm with periodic mode is capable of improving the search performance significantly, by compared with that of conventional modes and other algorithms.

CERN Document Server

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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A numerical optimization technique is used to obtain low-energy momentum transfer, j = 0 [yields] 2 rotational and v = 0 [yields] vibrational sections from measured electron swarm data for parahydrogen. The downhill simplex algorithm is used to find cross sections that represent the best numerical fit to the measured electron drift velocity and characteristic energy over a range of E/N. These results, which are in excellent agreement with published cross sections derived using traditional swarm analysis techniques, demonstrates the feasibility of using automated computational algorithms for swarm analysis involving the estimation of multiple cross sections. (Author).

CERN Document Server

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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The Sierra Madre Occidental of western Mexico is composed dominantly of Mid-Tertiary felsic and subordinate mafic volcanic rocks with only sparse outcrops of non-volcanic rocks. There are widely scattered but small exposure of plutonic rocks but regionally metamorphosed rocks are not known to occur in the Sierra. To this date the only known area where plutonic and metamorphic xenoliths have been found is near the village of Basaseachic in western Chihuahua where thick outcrops of the Cascada Tuff occur. The xenoliths are the only known occurrence of regionally metamorphosed rocks for a distance of about 400 km between exposures of Precambrian rocks to the west in Sonora and the east in central Chihuahua. Non-volcanic xenoliths from a few cm to about one meter in diameter occur most abundantly in the upper portions of the Cascada Tuff. They can be divided into four main groups in decreasing order of abundance as follows: (1) coarse-grained phaneritic felsic igneous ...

British Library Electronic Table of Contents (United Kingdom)

The Rosebel gold district is hosted in a Paleoproterozoic greenstone belt of the Guiana Shield and has many characteristics that enable classification of the ores as an orogenic gold deposit. Host rocks have undergone several phases of deformation. However, gold deposition occurred late in the structural history of the belt, and is considered part of a late regional metallogenic event with respect to the geotectonic evolution of the Guiana Shield. Economic gold mineralization is hosted in felsic to mafic volcanic rocks and two sedimentary successions that are differentiated into turbiditic and arenitic depositional packages. The detailed lithostratigraphic characterization and the geochemistry enable the correlation of the local rock types with the Paramaka, the Armina, and the Rosebel for...

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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Located in the Front Range of the Rocky Mountains approximately 30 miles west of Denver, in the community of Idaho Springs, are a series of thermal springs and wells. The temperature of these waters ranges from a low of 68/sup 0/F (20/sup 0/C) to a high of 127/sup 0/F (53/sup 0/C). To define the hydrothermal conditions of the Idaho Springs region in 1980, an investigation consisting of electrical geophysical surveys, soil mercury geochemical surveys, and reconnaissance geological and hydrogeological investigations was made. Due to topographic and cultural restrictions, the investigation was limited to the immediate area surrounding the thermal springs at the Indian Springs Resort. The bedrock of the region is faulted and fractured metamorphosed Precambrian gneisses and schists, locally intruded by Tertiary age plutons and dikes. The investigation showed that the thermal waters most likely are fault controlled and the thermal area does not have a large areal extent.

British Library Electronic Table of Contents (United Kingdom)

The Mylliem granitoids of the Meghalaya Plateau, northeastern India, represent one of the disharmonic Neoproterozoic igneous plutons, which are intrusive into low-grade Shillong Group of metasediments. Field studies indicate that the Mylliem granitoids cover an area of about 40 km2 and is characterized by development of variable attitude of primary foliations mostly marked along the margin of the pluton. Xenoliths of both Shillong Group of metasediments and mafic rocks have been found to occur within Mylliem granitoids. Structural study of the primary foliation is suggestive of funnel-shaped intrusion of Mylliem granitoids with no appreciable evidence of shearing. Petrographically, Mylliem granitoids are characterized by pink to white phenocrysts of prismatic microcline/perthite and lath-s...

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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 ...

CERN Document Server

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 ...

CERN Document Server

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.

CERN Document Server

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.

CERN Document Server

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.

CERN Document Server

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 ...

CERN Document Server

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.

CERN Document Server

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.

CERN Document Server

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.

Energy Technology Data Exchange (ETDEWEB)

A room-temperature process for stabilizing mineral waste streams has been developed, based on acid-base reaction between MgO and H3PO4 or acid phosphate solution. The resulting waste form sets into a hard ceramic in a few hours. In this way, various alumina industry wastes, such as red mud and treated potliner waste, can be solidified into ceramics which can be used as structural materials in waste management and construction industry. Red mud ceramics made by this process were low-porosity materials ({approx}2 vol%) with a compression strength equal to portland cement concrete (4944 psi). Bonding mechanism appears to be result of reactions of boehmite, goethite, and bayerite with the acid solution, and also encapsulation of red mud particles in Mg phosphate matrix. Possible applications include liners for ponds and thickned tailings disposal, dikes for waste ponds, and grouts. Compatability problems arising at the interface of the liner and the waste are avoided.

CERN Document Server

We propose the Particle Swarm Optimization (PSO) as an alternative method for locating periodic orbits in a three--dimensional (3D) model of barred galaxies. We develop an appropriate scheme that transforms the problem of finding periodic orbits into the problem of detecting global minimizers of a function, which is defined on the Poincar\\'{e} Surface of Section (PSS) of the Hamiltonian system. By combining the PSO method with deflection techniques, we succeeded in tracing systematically several periodic orbits of the system. The method succeeded in tracing the initial conditions of periodic orbits in cases where Newton iterative techniques had difficulties. In particular, we found families of 2D and 3D periodic orbits associated with the inner 8:1 to 12:1 resonances, between the radial 4:1 and corotation resonances of our 3D Ferrers bar model. The main advantages of the proposed algorithm is its simplicity, its ability to work using function values solely, as ...

CERN Document Server

In this paper the Sudoku problem is solved using stochastic search techniques and these are: Cultural Genetic Algorithm (CGA), Repulsive Particle Swarm Optimization (RPSO), Quantum Simulated Annealing (QSA) and the Hybrid method that combines Genetic Algorithm with Simulated Annealing (HGASA). The results obtained show that the CGA, QSA and HGASA are able to solve the Sudoku puzzle with CGA finding a solution in 28 seconds, while QSA finding a solution in 65 seconds and HGASA in 1.447 seconds. This is mainly because HGASA combines the parallel searching of GA with the flexibility of SA. The RPSO was found to be unable to solve the puzzle.

CERN Document Server

A new metaheuristic optimisation algorithm, called Cuckoo Search (CS), was developed recently by Yang and Deb (2009). This paper presents a more extensive comparison study using some standard test functions and newly designed stochastic test functions. We then apply the CS algorithm to solve engineering design optimisation problems, including the design of springs and welded beam structures. The optimal solutions obtained by CS are far better than the best solutions obtained by an efficient particle swarm optimiser. We will discuss the unique search features used in CS and the implications for further research.

CERN Document Server

The Proportional-Integral-Derivative Controller is widely used in industries for process control applications. Fractional-order PID controllers are known to outperform their integer-order counterparts. In this paper, we propose a new technique of fractional-order PID controller synthesis based on peak overshoot and rise-time specifications. Our approach is to construct an objective function, the optimization of which yields a possible solution to the design problem. This objective function is optimized using two popular bio-inspired stochastic search algorithms, namely Particle Swarm Optimization and Differential Evolution. With the help of a suitable example, the superiority of the designed fractional-order PID controller to an integer-order PID controller is affirmed and a comparative study of the efficacy of the two above algorithms in solving the optimization problem is also presented.

CERN Document Server

This contribution deals with identification of fractional-order dynamical systems. System identification, which refers to estimation of process parameters, is a necessity in control theory. Real processes are usually of fractional order as opposed to the ideal integral order models. A simple and elegant scheme of estimating the parameters for such a fractional order process is proposed. This method employs fractional calculus theory to find equations relating the parameters that are to be estimated, and then estimates the process parameters after solving the simultaneous equations. The said simultaneous equations are generated and updated using particle swarm optimization (PSO) technique, the fitness function being the sum of squared deviations from the actual set of observations. The data used for the calculations are intentionally corrupted to simulate real-life conditions. Results show that the proposed scheme offers a very high degree of accuracy even for ...

Energy Technology Data Exchange (ETDEWEB)

This paper presents an overview of research conducted with the support of the Australian Institute of Nuclear Science and Engineering, at the University of Melbourne, School of Earth Sciences, Radiochemical Neutron Activation Laboratory. The primary objective of this research is to realize the high potential of the platinum group elements (PGE) and gold to the solution of petrogenetic problems, the study of magma generation and magmatic processes in mafic/ultramafic rock suites, as tracers in hydrothermal ore formation. The PGEs (Os, Ru, Ir, Pt, Pd and Rh) are among the least abundant of all elements on earth with unique properties such as high melting points, high electrical and thermal conductivity, high density, strength and toughness as alloys. They exhibit both siderophile and chalcophile characteristics and are valuable tools in providing information about magmatic processes, in particular S-saturation, as well as crystal fractionation trends. Two distinct ...

CERN Document Server

Particle swarm optimization (PSO) is extensively used for real parameter optimization in diverse fields of study. This paper describes an application of PSO to the problem of designing a fractional-order proportional-integral-derivative (FOPID) controller whose parameters comprise proportionality constant, integral constant, derivative constant, integral order (lambda) and derivative order (delta). The presence of five optimizable parameters makes the task of designing a FOPID controller more challenging than conventional PID controller design. Our design method focuses on minimizing the Integral Time Absolute Error (ITAE) criterion. The digital realization of the deigned system utilizes the Tustin operator-based continued fraction expansion scheme. We carry out a simulation that illustrates the effectiveness of the proposed approach especially for realizing fractional-order plants. This paper also attempts to study the behavior of fractional PID controller ...

CERN Document Server

Because of the stochastic nature of traffic requirement matrix, it is very difficult to get the optimal traffic distribution to minimize the delay even with adaptive routing protocol in a fixed connection network where capacity already defined for each link. Hence there is a requirement to define such a method, which could generate the optimal solution very quickly and efficiently. This paper presenting a new concept to provide the adaptive optimal traffic distribution for dynamic condition of traffic matrix using nature based intelligence methods. With the defined load and fixed capacity of links, average delay for packet has minimized with various variations of evolutionary programming and particle swarm optimization. Comparative study has given over their performance in terms of converging speed. Universal approximation capability, the key feature of feed forward neural network has applied to predict the flow distribution on each link to minimize the average ...

CERN Document Server

In Internet Routing, the static shortest path (SP) problem has been addressed using well known intelligent optimization techniques like artificial neural networks, genetic algorithms (GAs) and particle swarm optimization. Advancement in wireless communication lead more and more mobile wireless networks, such as mobile networks [mobile ad hoc networks (MANETs)] and wireless sensor networks. Dynamic nature of the network is the main characteristic of MANET. Therefore, the SP routing problem in MANET turns into dynamic optimization problem (DOP). Here the nodes ae made aware of the environmental condition, thereby making it intelligent, which goes as the input for GA. The implementation then uses GAs with immigrants and memory schemes to solve the dynamic SP routing problem (DSPRP) in MANETS. In our paper, once the network topology changes, the optimal solutions in the new environment can be searched using the new immigrants or the useful information stored in the ...

CERN Document Server

This paper describes a study of comparison of global and one-dimensional local optimization methods to operating system scheduler tuning. The operating system scheduler we use is the Linux 2.6.23 Completely Fair Scheduler (CFS) running in simulator (LinSched). We have ported the Hackbench scheduler benchmark to this simulator and use this as the workload. The global optimization approach we use is Particle Swarm Optimization (PSO). We make use of Response Surface Methodology (RSM) to specify optimal parameters for our PSO implementation. The one-dimensional local optimization approach we use is the Golden Section method. In order to use this approach, we convert the scheduler tuning problem from one involving setting of three parameters to one involving the manipulation of one parameter. Our results show that the global optimization approach yields better response but the one- dimensional optimization approach converges to a solution faster than the global ...

CERN Document Server

Design of energy efficient schemes for data gathering is an important concern for lifetime enhancement of wireless sensor networks. Variation in the distances of nodes from the Base Station and differences in inter-nodal distances are primary factors causing unequal energy dissipation among the nodes. Thus energy difference between the various nodes increases with time resulting in degraded network performance. The LEACH and PEGASIS schemes which provided elegant solutions to the problem suffer basic drawbacks due to randomization of cluster heads and greedy chain formation respectively. In this paper, we propose an Optimized Lifetime Enhancement (OLE) Scheme which shows enhanced performance over these schemes. OLE increases the network performance by ensuring a sub-optimal energy dissipation of the individual nodes despite their random deployment. It employs modern heuristics like particle swarm optimization instead of the greedy algorithm as in PEGASIS to ...

Energy Technology Data Exchange (ETDEWEB)

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 ...