On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.

On Modelling, System Identification and Control of Servo-Systems with a Flexible Load

The present study was done with two different servo-systems. In the first system, a servo-hydraulic system was identified and then controlled by a fuzzy gainscheduling controller. The second servo-system, an electro-magnetic linear motor in suppressing the mechanical vibration and position tracking of a reference model are studied by using a neural network and an adaptive backstepping controller respectively. Followings are some descriptions of research methods. Electro Hydraulic Servo Systems (EHSS) are commonly used in industry. These kinds of systems are nonlinearin nature and their dynamic equations have several unknown parameters.System identification is a prerequisite to analysis of a dynamic system. One of the most promising novel evolutionary algorithms is the Differential Evolution (DE) for solving global optimization problems. In the study, the DE algorithm is proposed for handling nonlinear constraint functionswith boundary limits of variables to find the best parameters of a servo-hydraulic system with flexible load. The DE guarantees fast speed convergence and accurate solutions regardless the initial conditions of parameters. The control of hydraulic servo-systems has been the focus ofintense research over the past decades. These kinds of systems are nonlinear in nature and generally difficult to control. Since changing system parameters using the same gains will cause overshoot or even loss of system stability. The highly non-linear behaviour of these devices makes them ideal subjects for applying different types of sophisticated controllers. The study is concerned with a second order model reference to positioning control of a flexible load servo-hydraulic system using fuzzy gainscheduling. In the present research, to compensate the lack of dampingin a hydraulic system, an acceleration feedback was used. To compare the results, a pcontroller with feed-forward acceleration and different gains in extension and retraction is used. The design procedure for the controller and experimental results are discussed. The results suggest that using the fuzzy gain-scheduling controller decrease the error of position reference tracking. The second part of research was done on a PermanentMagnet Linear Synchronous Motor (PMLSM). In this study, a recurrent neural network compensator for suppressing mechanical vibration in PMLSM with a flexible load is studied. The linear motor is controlled by a conventional PI velocity controller, and the vibration of the flexible mechanism is suppressed by using a hybrid recurrent neural network. The differential evolution strategy and Kalman filter method are used to avoid the local minimum problem, and estimate the states of system respectively. The proposed control method is firstly designed by using non-linear simulation model built in Matlab Simulink and then implemented in practical test rig. The proposed method works satisfactorily and suppresses the vibration successfully. In the last part of research, a nonlinear load control method is developed and implemented for a PMLSM with a flexible load. The purpose of the controller is to track a flexible load to the desired position reference as fast as possible and without awkward oscillation. The control method is based on an adaptive backstepping algorithm whose stability is ensured by the Lyapunov stability theorem. The states of the system needed in the controller are estimated by using the Kalman filter. The proposed controller is implemented and tested in a linear motor test drive and responses are presented.

Two distinct plant respiratory physiotypes might exist which correspond to fast-growing and slow-growing species

The origin of the carbon atoms in CO2 respired by leaves in the dark of several plant species has been studied using 13C/12C stable isotopes. This study was conducted using an open gas exchange system for isotope labeling that was coupled to an elemental analyser and further linked to an isotope ratio mass spectrometer (EA-IRMS) or coupled to a gas chromatography-combustion-isotope ratio mass spectrometer (GC-C-IRMS). We demonstrate here that the carbon, which is recently assimilated during photosynthesis, accounts for nearly ca. 50% of the carbon in the CO2 lost through dark respiration after illumination in fast-growing and cultivated plants and trees and, accounts for only ca. 10% in slow-growing plants. Moreover, our study shows that fast- growing plants, which had the largest percentages of newly fixed carbon of leaf-respired CO2 , were also those with the largest shoot/root ratios, whereas slow-growing plants showed the lowest shoot/root values.

Fast Blue and Diamidino Yellow as retrograde tracers in peripheral nerves: efficacy of combined nerve injection and capsule application to transected nerves in the adult rat

Capsule application of Diamidino Yellow (DY) to the cut end of the sciatic nerve immediately followed by capsule application of Fast Blue (FB) resulted in approximate to 95% double-labelled dorsal root ganglion neurones (DRGn) and motoneurones (Mn). Nerve injection of DY followed either immediately or 2 months later by capsule application of FB resulted in approximate to 90% double-labelled DRGn and Mn, indicating that DY and FB label similar populations of DRGn and Mn, and that insignificant DY fading occurred during this period. Inversing the order of application, however, i.e. nerve injection of FB followed immediately by capsule application of DY, resulted in double labelling in only approximate to 10% of the DRGn and Mn. These percentages increased to 70% of the DRGn and 60% of the Mn when the FB injection was followed 1 or 2 months after by the DY application, indicating that DY uptake is blocked by recent administration of FB. The results indicate that DY and FB might be useful for sequential labelling before and after nerve injury as a tool to investigate the accuracy of sensory and motor regeneration.

Level Set Methods in Image Processing

This thesis gives an overview of the use of the level set methods in the field of image science. The similar fast marching method is discussed for comparison, also the narrow band and the particle level set methods are introduced. The level set method is a numerical scheme for representing, deforming and recovering structures in an arbitrary dimensions. It approximates and tracks the moving interfaces, dynamic curves and surfaces. The level set method does not define how and why some boundary is advancing the way it is but simply represents and tracks the boundary. The principal idea of the level set method is to represent the N dimensional boundary in the N+l dimensions. This gives the generality to represent even the complex boundaries. The level set methods can be powerful tools to represent dynamic boundaries, but they can require lot of computing power. Specially the basic level set method have considerable computational burden. This burden can be alleviated with more sophisticated versions of the level set algorithm like the narrow band level set method or with the programmable hardware implementation. Also the parallel approach can be used in suitable applications. It is concluded that these methods can be used in a quite broad range of image applications, like computer vision and graphics, scientific visualization and also to solve problems in computational physics. Level set methods and methods derived and inspired by it will be in the front line of image processing also in the future.

Sulautetun moniprosessorijärjestelmän suunnittelu sähkömoottorien ohjaus- ja valvontatarpeisiin

Universal Converter (UNICON) –projektin osana suunniteltiin sähkömoottorikäyttöjen ohjaukseen ja mittaukseen soveltuva digitaaliseen signaaliprosessoriin (DSP) pohjautuva sulautettu järjestelmä. Riittävän laskentatehon varmistamiseksi päädyttiin käyttämään moniprosessorijärjestelmää. Prosessorijärjestelmässä käytettävää DSP-piiriä valittaessa valintaperusteina olivat piirien tarjoama prosessointiteho ja moniprosessorituki. Analog Devices:n SHARC-sarjan DSP-piirit täyttivät parhaiten asetetut vaatimukset: Ne tarjoavat tehokkaan käskykannan lisäksi suuren sisäisen muistin ja sisäänrakennetun moniprosessorituen. Järjestelmän mittalaiteluonteisuudesta johtuen keskeinen suunnitteluparametri oli luoda nopeat tiedonsiirtoyhteydet mittausantureilta DSP-järjestelmään. Tämä toteutettiin käyttäen ohjelmointavia FPGA-logiikkapiirejä digitaalimuotoisen mittausdatan vastaanotossa ja esikäsittelyssä. Tiedonsiirtoyhteys PC-tietokoneelle toteutettiin käyttäen erityistä liityntäkorttia DSP-järjestelmän ja PC-tietokoneen välillä. Liityntäkortin päätehtävänä on puskuroida siirrettävä data. Järjestelyllä estetään PC-tietokoneen vaikutus DSP-järjestelmän toimintaan, jotta kyetään takaamaan järjestelmän reaaliaikainen toiminta kaikissa olosuhteissa.

Predicting drug metabolism: experiment and/or computation?

Drug metabolism can produce metabolites with physicochemical and pharmacological properties that differ substantially from those of the parent drug, and consequently has important implications for both drug safety and efficacy. To reduce the risk of costly clinical-stage attrition due to the metabolic characteristics of drug candidates, there is a need for efficient and reliable ways to predict drug metabolism in vitro, in silico and in vivo. In this Perspective, we provide an overview of the state of the art of experimental and computational approaches for investigating drug metabolism. We highlight the scope and limitations of these methods, and indicate strategies to harvest the synergies that result from combining measurement and prediction of drug metabolism.

Use of the dried blood spot sampling process coupled with fast gas chromatography and negative-ion chemical ionization tandem mass spectrometry: application to fluoxetine, norfluoxetine, reboxetine, and paroxetine analysis.

The objective of this work was to combine the advantages of the dried blood spot (DBS) sampling process with the highly sensitive and selective negative-ion chemical ionization tandem mass spectrometry (NICI-MS-MS) to analyze for recent antidepressants including fluoxetine, norfluoxetine, reboxetine, and paroxetine from micro whole blood samples (i.e., 10 microL). Before analysis, DBS samples were punched out, and antidepressants were simultaneously extracted and derivatized in a single step by use of pentafluoropropionic acid anhydride and 0.02% triethylamine in butyl chloride for 30 min at 60 degrees C under ultrasonication. Derivatives were then separated on a gas chromatograph coupled with a triple-quadrupole mass spectrometer operating in negative selected reaction monitoring mode for a total run time of 5 min. To establish the validity of the method, trueness, precision, and selectivity were determined on the basis of the guidelines of the "Société Française des Sciences et des Techniques Pharmaceutiques" (SFSTP). The assay was found to be linear in the concentration ranges 1 to 500 ng mL(-1) for fluoxetine and norfluoxetine and 20 to 500 ng mL(-1) for reboxetine and paroxetine. Despite the small sampling volume, the limit of detection was estimated at 20 pg mL(-1) for all the analytes. The stability of DBS was also evaluated at -20 degrees C, 4 degrees C, 25 degrees C, and 40 degrees C for up to 30 days. Furthermore, the method was successfully applied to a pharmacokinetic investigation performed on a healthy volunteer after oral administration of a single 40-mg dose of fluoxetine. Thus, this validated DBS method combines an extractive-derivative single step with a fast and sensitive GC-NICI-MS-MS technique. Using microliter blood samples, this procedure offers a patient-friendly tool in many biomedical fields such as checking treatment adherence, therapeutic drug monitoring, toxicological analyses, or pharmacokinetic studies.

Hippocampal Theta-Phase Modulation of Replay Correlates with Configural-Relational Short-Term Memory Performance

Thereis now growing evidencethatthe hippocampus generatestheta rhythmsthat can phase biasfast neural oscillationsinthe neocortex, allowing coordination of widespread fast oscillatory populations outside limbic areas. A recent magnetoencephalographic study showed that maintenance of configural-relational scene information in a delayed match-to-sample (DMS) task was associated with replay of that information during the delay period. The periodicity of the replay was coordinated by the phase of the ongoing theta rhythm, and the degree of theta coordination during the delay period was positively correlated with DMS performance. Here, we reanalyzed these data to investigate which brain regions were involved in generating the theta oscillations that coordinated the periodic replay of configural- relational information. We used a beamformer algorithm to produce estimates of regional theta rhythms and constructed volumetric images of the phase-locking between the local theta cycle and the instances of replay (in the 13- 80 Hz band). We found that individual differences in DMS performancefor configural-relational associations were relatedtothe degree of phase coupling of instances of cortical reactivations to theta oscillations generated in the right posterior hippocampus and the right inferior frontal gyrus. This demonstrates that the timing of memory reactivations in humans is biased toward hippocampal theta phase

Matkapuhelimen puhelinmuistiopalvelimen tietorakenteiden ja lajittelualgoritmien analysointi ja suunnittelu

Puhelinmuistio on yksi matkapuhelimen käytetyimmistä ominaisuuksista. Puhelinmuistion tulee siksi olla kaikissa tilanteissa mahdollisimman nopeasti käytettävissä. Tämä edellyttää puhelinmuistiopalvelimelta tehokkaita tietorakenteita ja lajittelualgoritmeja. Nokian matkapuhelimissa puhelinmuistiopalvelin käyttää hakurakenteena järjestettyjä taulukoita. Työn tavoitteena oli kehittää puhelinmuistiopalvelimen hakutaulukoiden lajittelu mahdollisimman nopeaksi. Useita eri lajittelualgoritmeja vertailtiin ja niiden suoritusaikoja analysoitiin eri tilanteissa. Insertionsort-lajittelualgoritmin todettiin olevan nopein algoritmi lähes järjestyksessä olevien taulukoiden lajitteluun. Analyysin perusteella Quicksort-algoritmi lajittelee nopeimmin satunnaisessa järjestyksessä olevat taulukot. Quicksort-insertionsort –hybridialgoritmin havaittiin olevan paras lajittelualgoritmi puhelinmuistion lajitteluun. Sopivalla parametroinnilla tämä algoritmi on nopea satunnaisessa järjestyksessä olevalle aineistolle. Se kykenee hyödyntämään lajiteltavassa aineistossa valmiina olevaa järjestystä. Algoritmi ei kasvata merkittävästi muistinkulutusta. Uuden algoritmin ansiosta hakutaulukoiden lajittelu nopeutuu parhaimmillaan useita kymmeniä prosentteja.

Populaation monimuotoisuuden mittaaminen liukulukukoodatuissa evoluutioalgoritmeissa

Diplomityössä esitetään menetelmä populaation monimuotoisuuden mittaamiseen liukulukukoodatuissa evoluutioalgoritmeissa, ja tarkastellaan kokeellisesti sen toimintaa. Evoluutioalgoritmit ovat populaatiopohjaisia menetelmiä, joilla pyritään ratkaisemaan optimointiongelmia. Evoluutioalgoritmeissa populaation monimuotoisuuden hallinta on välttämätöntä, jotta suoritettu haku olisi riittävän luotettavaa ja toisaalta riittävän nopeaa. Monimuotoisuuden mittaaminen on erityisen tarpeellista tutkittaessa evoluutioalgoritmien dynaamista käyttäytymistä. Työssä tarkastellaan haku- ja tavoitefunktioavaruuden monimuotoisuuden mittaamista. Toistaiseksi ei ole ollut olemassa täysin tyydyttäviä monimuotoisuuden mittareita, ja työn tavoitteena on kehittää yleiskäyttöinen menetelmä liukulukukoodattujen evoluutioalgoritmien suhteellisen ja absoluuttisen monimuotoisuuden mittaamiseen hakuavaruudessa. Kehitettyjen mittareiden toimintaa ja käyttökelpoisuutta tarkastellaan kokeellisesti ratkaisemalla optimointiongelmia differentiaalievoluutioalgoritmilla. Toteutettujen mittareiden toiminta perustuu keskihajontojen laskemiseen populaatiosta. Keskihajonnoille suoritetaan skaalaus, joko alkupopulaation tai nykyisen populaation suhteen, riippuen lasketaanko absoluuttista vai suhteellista monimuotoisuutta. Kokeellisessa tarkastelussa havaittiin kehitetyt mittarit toimiviksi ja käyttökelpoisiksi. Tavoitefunktion venyttäminen koordinaattiakseleiden suunnassa ei vaikuta mittarin toimintaan. Myöskään tavoitefunktion kiertäminen koordinaatistossa ei vaikuta mittareiden tuloksiin. Esitetyn menetelmän aikakompleksisuus riippuu lineaarisesti populaation koosta, ja mittarin toiminta on siten nopeaa suuriakin populaatioita käytettäessä. Suhteellinen monimuotoisuus antaa vertailukelpoisia tuloksia riippumatta parametrien lukumäärästä tai populaation koosta.

Efficacy of the fluorescent dyes Fast Blue, Fluoro-Gold, and Diamidino Yellow for retrograde tracing to dorsal root ganglia after subcutaneous injection

The present study was designed to investigate the efficacy of the fluorescent dyes Fast Blue (FB), Fluoro-Gold (FG), and Diamidino Yellow (DY) for retrograde tracing of lumbar dorsal root ganglia after their subcutaneous injection into different hindlimb digits. Injection of equal volumes (0.5 mu l) of 5% FB or 2% FG resulted in similar mean numbers of sensory neurones labelled by each tracer. Injection of equal volumes (0.5 mu l) of FB or FG in a single digit followed 10 days later by a second injection of the same volume of 5% DY into the same digit resulted in similar mean numbers of labelled sensory neurones for each of the three tracers. Furthermore, on average, 75% of all the FB-labelled cells and 74% of all FC-labelled cells also contained DY. Repeating the same experiment with an increased volume of DY (1.5 mu l) resulted in an increase in the mean number of double-labelled profiles to 82 and 84% for FB and FG, respectively. The results show that FB, FG and DY label similar numbers of cutaneous afferents and that a high level of double labelling may be obtained after sequential injections in digits. These properties make them suitable candidates in investigations where a combination of tracers with similar labelling efficacies is needed.

A Gradient based algorithm for blind inversion of Wiener System using multi-variate score functions

A Wiener system is a linear time-invariant filter, followed by an invertible nonlinear distortion. Assuming that the input signal is an independent and identically distributed (iid) sequence, we propose an algorithm for estimating the input signal only by observing the output of the Wiener system. The algorithm is based on minimizing the mutual information of the output samples, by means of a steepest descent gradient approach.

Improving algorithm speed in PNL mixture separation and Wiener system inversion

This paper proposes a very simple method for increasing the algorithm speed for separating sources from PNL mixtures or invertingWiener systems. The method is based on a pertinent initialization of the inverse system, whose computational cost is very low. The nonlinear part is roughly approximated by pushing the observations to be Gaussian; this method provides a surprisingly good approximation even when the basic assumption is not fully satisfied. The linear part is initialized so that outputs are decorrelated. Experiments shows the impressive speed improvement.