A Dynamic Migration Model for Self-adaptive Genetic Algorithms

In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters of population size, the number of points of crossover and mutation rate for each population are fixed adaptively. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions, when compared with Island model GA(IGA) and Simple GA(SGA).

Strength design of composite beam using gradient and particle swarm optimization

This work addresses the optimum design of a composite box-beam structure subject to strength constraints. Such box-beams are used as the main load carrying members of helicopter rotor blades. A computationally efficient analytical model for box-beam is used. Optimal ply orientation angles are sought which maximize the failure margins with respect to the applied loading. The Tsai-Wu-Hahn failure criterion is used to calculate the reserve factor for each wall and ply and the minimum reserve factor is maximized. Ply angles are used as design variables and various cases of initial starting design and loadings are investigated. Both gradient-based and particle swarm optimization (PSO) methods are used. It is found that the optimization approach leads to the design of a box-beam with greatly improved reserve factors which can be useful for helicopter rotor structures. While the PSO yields globally best designs, the gradient-based method can also be used with appropriate starting designs to obtain useful designs efficiently. (C) 2006 Elsevier Ltd. All rights reserved.

Depression in / by / for women : agency, feminism and self-help in groups

Depression in / by / for Women: Agency, Feminism and Self-Help in Groups on ensimmäinen väitöstasoinen tutkimus feministisestä terapiasta Suomessa sijoittuen psykologian, sosiaalitieteellisen mielenterveystutkimuksen sekä feministisen tutkimuksen alueille. Perinteisen näkemyksen mukaan feministisen tutkimuksen tulee olla ”naisista, naisten tekemää ja naisille kohdistettua”. Naiset ja masennus -projektitutkimus keskittyy naisten kokemaan masennukseen sisältäen mahdollisen miesten sekä patriarkaalisen hyvinvointivaltion osuuden masennukseen. Masennusta kokevat naiset ovat tutkimuksessa sekä tutkimuksen kohteena että aktiivisia osanottajia, mikä tuo heidän äänensä kuuluville. Tutkimus perustuu vuosien 1994-2000 välisenä aikana kerättyyn 11 ryhmän osallistujia koskevaan kvalitatiivisiin ja kvantitatiivisiin aineistoon. Irmeli Laitinen on ollut suunnittelemassa, keräämässä ja analysoimassa sitä yhdessä projektin muiden jäsenten kanssa. Tutkimuksessa mitattiin kuinka ryhmiin osallistuvien seka masennuksen tunteet että toiminnat muuttuivat yhden vuoden aikana. Tutkimuksen tavoitteena oli sekä masennuksesta kärsivien naisten osallistuminen feministiseen toimintatutkimukseen että ammatillisesti ohjatun oma-apuryhmämenetelmän kehittäminen suomalaiseen mielenterveyspalveluun. Projektin tutkimustulosten mukaan siihen osallistuneet naiset voimaantuivat ymmärtämään itseään sekä saivat luottamusta sosiaaliisiin taitoihinsa. Pidemmällä aikavälillä naisten tunteet muuttuivat myönteisiksi, heidän suhteensa itseensä positiivisemmaksi ja he aktivoituivat fyysisesti. Lisäksi tutkimustulokset viittaavat siihen, että masennus voi johtua näkymättömästä, sukupuolisesti virittyneestä jännitteestä naisystävällisessä hyvinvointivaltiossa paljastaen ”hyvinvointimasennusoireilun”. Suomalaisen sosiologi Erik Allardtin hyvinvointitypologian - having, loving, being – mukaisesti nämä ryhmään osallistuvat naiset eivät koe puutteita niinkään materiaalisessa hyvinvoinnissa (having) vaan pikeminkin suhteiden, sosiaalisen ja emotionaalisen hyvinvoinnin ulottuvuuksilla (loving ja being). Se, että masentuneet naiset pystyvät tuomaan esille pitkään vaiennettuja kokemuksiaan, voi merkitä paljon heidän paranemisessaan ja voimaantumisessaan. Ammatillisesti ohjatut oma-apuryhmät ja naisystävälliset hoitokäytännöt mahdollistivat tämänkaltaisen paranemisprosessin alkamisen tutkimukseen osallistuneissa ryhmissä.

Pareto-optimal solutions for multi-objective optimization of fed-batch bioreactors using nondominated sorting genetic algorithm

Many optimal control problems are characterized by their multiple performance measures that are often noncommensurable and competing with each other. The presence of multiple objectives in a problem usually give rise to a set of optimal solutions, largely known as Pareto-optimal solutions. Evolutionary algorithms have been recognized to be well suited for multi-objective optimization because of their capability to evolve a set of nondominated solutions distributed along the Pareto front. This has led to the development of many evolutionary multi-objective optimization algorithms among which Nondominated Sorting Genetic Algorithm (NSGA and its enhanced version NSGA-II) has been found effective in solving a wide variety of problems. Recently, we reported a genetic algorithm based technique for solving dynamic single-objective optimization problems, with single as well as multiple control variables, that appear in fed-batch bioreactor applications. The purpose of this study is to extend this methodology for solution of multi-objective optimal control problems under the framework of NSGA-II. The applicability of the technique is illustrated by solving two optimal control problems, taken from literature, which have usually been solved by several methods as single-objective dynamic optimization problems. (C) 2004 Elsevier Ltd. All rights reserved.

Primordial Perturbations from a Self-interacting Curvaton

Inflation is a period of accelerated expansion in the very early universe, which has the appealing aspect that it can create primordial perturbations via quantum fluctuations. These primordial perturbations have been observed in the cosmic microwave background, and these perturbations also function as the seeds of all large-scale structure in the universe. Curvaton models are simple modifications of the standard inflationary paradigm, where inflation is driven by the energy density of the inflaton, but another field, the curvaton, is responsible for producing the primordial perturbations. The curvaton decays after inflation as ended, where the isocurvature perturbations of the curvaton are converted into adiabatic perturbations. Since the curvaton must decay, it must have some interactions. Additionally realistic curvaton models typically have some self-interactions. In this work we consider self-interacting curvaton models, where the self-interaction is a monomial in the potential, suppressed by the Planck scale, and thus the self-interaction is very weak. Nevertheless, since the self-interaction makes the equations of motion non-linear, it can modify the behaviour of the model very drastically. The most intriguing aspect of this behaviour is that the final properties of the perturbations become highly dependent on the initial values. Departures of Gaussian distribution are important observables of the primordial perturbations. Due to the non-linearity of the self-interacting curvaton model and its sensitivity to initial conditions, it can produce significant non-Gaussianity of the primordial perturbations. In this work we investigate the non-Gaussianity produced by the self-interacting curvaton, and demonstrate that the non-Gaussianity parameters do not obey the analytically derived approximate relations often cited in the literature. Furthermore we also consider a self-interacting curvaton with a mass in the TeV-scale. Motivated by realistic particle physics models such as the Minimally Supersymmetric Standard Model, we demonstrate that a curvaton model within the mass range can be responsible for the observed perturbations if it can decay late enough.

Self-Assembly of Biopolymers on Colloidal Particles via Hydrogen Bonding

Fabrication of multilayer microcapsules via layer-by-layer approach through hydrogen bonding has attracted enormous interest due to its strong response to pH. In this communication, we have prepared hydrogen-bonded multilayer microcapsule without using any cross-linking agent by using DNA base pair (adenine and thymine) modified biocompatible polymers. The growth of the self-assembly on colloidal (melamine formaldehyde: MF) particles has been monitored with zeta potential measurement. The capsules were obtained on dissolution of MF particles at 0.1N HCl. The capsules were characterized with scanning electron microscopy. Moreover, we have observed the salt induced microscopic change in self-assembly of this system on the surface of colloidal particles.

A Dynamic Migration Model for self-adaptive Genetic Algorithms

In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters of population size, the number of points of crossover and mutation rate for each population are fixed adaptively. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions, when compared with Island model GA(IGA) and Simple GA(SGA).

Propagation of a spherical shock in an inhomogeneous self-gravitating or nongravitating system

The propagation of a shock wave of finite strength due to an explosion into inhomogeneous nongravitating and self-gravitating systems has been considered, using similarity principles, supposing that the density varies as an inverse power of distance from the centre of explosion. A large number of systems, characterised by different density exponents and different adiabatic coefficients of the gas have been considered for different shock strengths. The numerical integration from the shock inward has been continued to the surface of singularity where density tends to infinity and which acts like a piston in the self-gravitating case and to the surface where the velocity gradient tends to infinity in the nongravitating case. The effect of variation of shock strength, density exponent and adiabatic coefficient on the location of these singularities and on the distribution of flow parameters behind the shock has been studied. The initial energy of the system and the manner of release of the explosion energy influence strongly the flow behind the shock. The results have been graphically depicted.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time,recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through a pseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets of measurements involving various load cases, we expedite the speed of thePD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time, recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through apseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets ofmeasurements involving various load cases, we expedite the speed of the PD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small. Copyright (C) 2009 John Wiley & Sons, Ltd.

Extended self-similarity works for the Burgers equation and why

Extended self-similarity (ESS), a procedure that remarkably extends the range of scaling for structure functions in Navier-Stokes turbulence and thus allows improved determination of intermittency exponents, has never been fully explained. We show that ESS applies to Burgers turbulence at high Reynolds numbers and we give the theoretical explanation of the numerically observed improved scaling at both the IR and UV end, in total a gain of about three quarters of a decade: there is a reduction of subdominant contributions to scaling when going from the standard structure function representation to the ESS representation. We conjecture that a similar situation holds for three-dimensional incompressible turbulence and suggest ways of capturing subdominant contributions to scaling.

Instability of the self-similar flow into a cavity

In this paper we have investigated the instability of the self-similar flow behind the boundary of a collapsing cavity. The similarity solutions for the flow into a cavity in a fluid obeying a gas law p = Kργ, K = constant and 7 ≥ γ > 1 has been solved by Hunter, who finds that for the same value of γ there are two self-similar flows, one with accelerating cavity boundary and other with constant velocity cavity boundary. We find here that the first of these two flows is unstable. We arrive at this result only by studying the propagation of disturbances in the neighbourhood of the singular point.

On self-interacting oligoribonucleotides. I. Absorption and optical rotatory dispersion of 2′-5′- and 3′-5′-oligoguanylic acids

A series of 2′-5′-oligoguanylic acids are prepared by reacting G(cyclic)p with takadiastase T1 ribonuclease and separating the products chromatographically. The 3′-5′-oligoguanylic acids are obtained by separating the products of alkaline degradation of 3′-5′-poly(G). The optical rotatory dispersion and hypochromism of both 2′-5′- and 3′-5′-oligoguanylic acids are studied at two different pH. The optical rotatory dispersion spectrum of 2′-5′-GpG is significantly different from that of 3′-5′-GpG. The magnitude of rotation of the long-wavelength peak of 2′-5′-GpG is larger than that of 3′-5′-GpG. This finding contradicts the explanation that the extra stability and more intense circular dichroism band of other 3′-5′-dinucleoside monophosphates is due to H-bond formation between 2′-OH and either the base or the phosphate oxygen. The end phosphate group has a marked effect on the spectrum of GpG between 230 and 250 mμ. In addition the optical rotatory dispersion spectra of 2′-5′ exhibit strong pH, temperature, and solvent dependence between 230 and 250 mμ. ΔH and AS for order ⇌ disorder transition is estimated to be 9.7 kcal/mole and 35.2 eu, respectively. The optical rotatory dispersion spectra of guanine-rich oligoribonucleotides, GpGpC, GpGpU, GpGpGpC, and GpGpGpU are compared to the calculated optical rotatory dispersion from the semiempirical expression of Cantor and Tinoco, using measured optical rotatory dispersion of dimers. Contrary to previous studies, agreement is found not at all satisfactory. However, optical rotatory dispersion of 3′-5′-GpGpGpC and GpGpGpU can be estimated from the semiempirical expression, if a next-nearest interaction parameter is introduced empirically. Such interaction parameter can be calculated from the measured properties of trinucleotide sequences like GpGpG, GpGpC, and GpGpU, assuming that only the nearest-neighbor interaction is important. The optical rotatory dispersion of single-stranded poly(G) is also predicted. The importance of syn-anti equilibrium and next-nearest-neighbor interaction in oligoguanylic acids is suggested as a probable explanation.

Glucose-Triggered Drug Delivery from Borate Mediated Layer-by-Layer Self-Assembly

In this study, we report a novel approach for glucose-triggered anticancer drug delivery from the self-assembly of neutral poly(vinyln alcohol) (PVA) and chitosan. In the present study, we have fabricated multilayer thin film of PVA-borate and chitosan on colloidal particle (MF particle) and monitored the layer-by-layer growth using Zetapotential measurements. Formation of multilayer membrane on MF particle has been further characterized with transmission electron microscopy (TEM) and confocal laser scanning microscopy (CLSM). Subsequently,disintegration of multilayer thin film and microcapsules was observed in presence of glucose. We investigated the disassembly of PVA-borate and chitosan self-assembly under CLSM and atomic force microscopy. These results suggest that this multilayer thin film is very efficient for encapsulation and release of DOX molecules above certain concentration of glucose (25 mM). This glucose-sensitive self-assembly is relevant for the application of anticancer therapeutic drug delivery.

Possible use of self-calibration to reduce systematic uncertainties in determining distance-redshift relation via gravitational radiation from merging binaries

By observing mergers of compact objects, future gravity wave experiments would measure the luminosity distance to a large number of sources to a high precision but not their redshifts. Given the directional sensitivity of an experiment, a fraction of such sources (gold plated) can be identified optically as single objects in the direction of the source. We show that if an approximate distance-redshift relation is known then it is possible to statistically resolve those sources that have multiple galaxies in the beam. We study the feasibility of using gold plated sources to iteratively resolve the unresolved sources, obtain the self-calibrated best possible distance-redshift relation and provide an analytical expression for the accuracy achievable. We derive the lower limit on the total number of sources that is needed to achieve this accuracy through self-calibration. We show that this limit depends exponentially on the beam width and give estimates for various experimental parameters representative of future gravitational wave experiments DECIGO and BBO.