Ranking-Dominance Relation for (Evolutionary) Multi-Objective Optimization

An alternative relation to Pareto-dominance relation is proposed. The new relation is based on ranking a set of solutions according to each separate objective and an aggregation function to calculate a scalar fitness value for each solution. The relation is called as ranking-dominance and it tries to tackle the curse of dimensionality commonly observedin evolutionary multi-objective optimization. Ranking-dominance can beused to sort a set of solutions even for a large number of objectives when Pareto-dominance relation cannot distinguish solutions from one another anymore. This permits search to advance even with a large number of objectives. It is also shown that ranking-dominance does not violate Pareto-dominance. Results indicate that selection based on ranking-dominance is able to advance search towards the Pareto-front in some cases, where selection based on Pareto-dominance stagnates. However, in some cases it is also possible that search does not proceed into direction of Pareto-front because the ranking-dominance relation permits deterioration of individual objectives. Results also show that when the number of objectives increases, selection based on just Pareto-dominance without diversity maintenance is able to advance search better than with diversity maintenance. Therefore, diversity maintenance is connive at the curse of dimensionality.

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.

Evolutionary Ecology of Mountain Birch in Subarctic Stress Gradients: Interplay of Biotic and Abiotic Factors in Plant-Plant Interactions and Evolutionary Processes

In nature, variation for example in herbivory, wind exposure, moisture and pollution impact often creates variation in physiological stress and plant productivity. This variation is seldom clear-cut, but rather results in clines of decreasing growth and productivity towards the high-stress end. These clines of unidirectionally changing stress are generally known as ‘stress gradients’. Through its effect on plant performance, stress has the capacity to fundamentally alter the ecological relationships between individuals, and through variation in survival and reproduction it also causes evolutionary change, i.e. local adaptations to stress and eventually speciation. In certain conditions local adaptations to environmental stress have been documented in a matter of just a few generations. In plant-plant interactions, intensities of both negative interactions (competition) and positive ones (facilitation) are expected to vary along stress gradients. The stress-gradient hypothesis (SGH) suggests that net facilitation will be strongest in conditions of high biotic and abiotic stress, while a more recent ‘humpback’ model predicts strongest net facilitation at intermediate levels of stress. Plant interactions on stress gradients, however, are affected by a multitude of confounding factors, making studies of facilitation-related theories challenging. Among these factors are plant ontogeny, spatial scale, and local adaptation to stress. The last of these has very rarely been included in facilitation studies, despite the potential co-occurrence of local adaptations and changes in net facilitation in stress gradients. Current theory would predict both competitive effects and facilitative responses to be weakest in populations locally adapted to withstand high abiotic stress. This thesis is based on six experiments, conducted both in greenhouses and in the field in Russia, Norway and Finland, with mountain birch (Betula pubescens subsp. czerepanovii) as the model species. The aims were to study potential local adaptations in multiple stress gradients (both natural and anthropogenic), changes in plant-plant interactions under conditions of varying stress (as predicted by SGH), potential mechanisms behind intraspecific facilitation, and factors confounding plant-plant facilitation, such as spatiotemporal, ontogenetic, and genetic differences. I found rapid evolutionary adaptations (occurring within a time-span of 60 to 70 years) towards heavy-metal resistance around two copper-nickel smelters, a phenomenon that has resulted in a trade-off of decreased performance in pristine conditions. Heavy-metal-adapted individuals had lowered nickel uptake, indicating a possible mechanism behind the detected resistance. Seedlings adapted to heavy-metal toxicity were not co-resistant to others forms of abiotic stress, but showed co-resistance to biotic stress by being consumed to a lesser extent by insect herbivores. Conversely, populations from conditions of high natural stress (wind, drought etc.) showed no local adaptations, despite much longer evolutionary time scales. Due to decreasing emissions, I was unable to test SGH in the pollution gradients. In natural stress gradients, however, plant performance was in accordance with SGH, with the strongest host-seedling facilitation found at the high-stress sites in two different stress gradients. Factors confounding this pattern included (1) plant size / ontogenetic status, with seedling-seedling interactions being competition dominated and host-seedling interactions potentially switching towards competition with seedling growth, and (2) spatial distance, with competition dominating at very short planting distances, and facilitation being strongest at a distance of circa ¼ benefactor height. I found no evidence for changes in facilitation with respect to the evolutionary histories of plant populations. Despite the support for SGH, it may be that the ‘humpback’ model is more relevant when the main stressor is resource-related, while what I studied were the effects of ‘non-resource’ stressors (i.e. heavy-metal pollution and wind). The results have potential practical applications: the utilisation of locally adapted seedlings and plant facilitation may increase the success of future restoration efforts in industrial barrens as well as in other wind-exposed sites. The findings also have implications with regard to the effects of global change in subarctic environments: the documented potential by mountain birch for rapid evolutionary change, together with the general lack of evolutionary ‘dead ends’, due to not (over)specialising to current natural conditions, increase the chances of this crucial forest-forming tree persisting even under the anticipated climate change.

MCMC Analysis Of Classical Time Series Algorithms

Identification of order of an Autoregressive Moving Average Model (ARMA) by the usual graphical method is subjective. Hence, there is a need of developing a technique to identify the order without employing the graphical investigation of series autocorrelations. To avoid subjectivity, this thesis focuses on determining the order of the Autoregressive Moving Average Model using Reversible Jump Markov Chain Monte Carlo (RJMCMC). The RJMCMC selects the model from a set of the models suggested by better fitting, standard deviation errors and the frequency of accepted data. Together with deep analysis of the classical Box-Jenkins modeling methodology the integration with MCMC algorithms has been focused through parameter estimation and model fitting of ARMA models. This helps to verify how well the MCMC algorithms can treat the ARMA models, by comparing the results with graphical method. It has been seen that the MCMC produced better results than the classical time series approach.

The molecular mechanisms and evolutionary significance of plumage colour variation in pied flycatchers (Ficedula hypoleuca)

A common feature of natural populations is that individuals differ in morphology, physiologyand behavior (i.e .phenotype). A thorough understanding of the molecular mechanisms and evolutionary forces behind this phenotypic variation is a prerequisite for understanding evolution.This thesis examines the molecular mechanism and the roles of the different evolutionary forces in plumage colour variation in pied flycatchers (Ficedulahypoleuca). Malepied flycatchers exhibit marked variation in both pigmentary and structural plumage colourand the trait has repeatedly been suggested to be of adaptive significance. An examination of plumage colour variation on reproductive output trevealed that structural colouration, and more specifically the degree of ultraviolet (UV) reflectance had an effect on number of young sired. Paternity analyses of breeding males revealed that males that had been cuckolded by their social mate tended to be less UV reflectant than males that had not been cuckolded.Neither pigment-based norstructural colouration was found to affect the probability of siring young in other nests. Phenotypic differentiation was found to be markedly greater than differentiation at neutralgenetic markers across the pied flycatcher breeding range. Furthermore patterns of differentiationin phenotypes and selectively neutral genes were not uniform. Outlier tests searching for genomic footprints of selection revealed elevated levels of genetic divergence in a gene associated with feather development (and thus potentially structural colouration) and ultraviolet vision. Th eobserved differentiation in allelic frequencies was particularly pronounced in the Spanish piedflycatcher populations. Examining gene expression during feather development indicated that the TYRP1 gene (known to be involved in the production of black pigment) may be relevant in generating phenotypic variation in pied flycatcher plumage. Also, energy homeostasis related genesfeatured prominently among the genes found to be expressed in one extreme phenotype but not the other. This is of particular interest in light of what is known about the pleiotropy ofthe melanocortin system which underlies brown-black pigment production. The melanocortinsystem is also associated with energy homeostasis (among a number of other physiological functions) and thus the results could be pointing to the signalling function of brown-blackplumage. Plumage colour variation in pied flycatchers, both structural and pigmentary, can thus beconcluded to be exhibiting signals of non-neutral evolution. Structural colouration was found to play a role in sexual selection and putative signals of selection were further detected in acandidate gene for this trait. Evidence for non-neutral evolution of pigmentary colouration was also detected. These findings, together with the fact that preliminary evidence for an energy balance associated signalling function for plumage was found, present good starting points for further investigations into the meaning and mechanisms of plumage colour variation in piedflycatchers.

Scalable algorithms for height field illumination

Global illumination algorithms are at the center of realistic image synthesis and account for non-trivial light transport and occlusion within scenes, such as indirect illumination, ambient occlusion, and environment lighting. Their computationally most difficult part is determining light source visibility at each visible scene point. Height fields, on the other hand, constitute an important special case of geometry and are mainly used to describe certain types of objects such as terrains and to map detailed geometry onto object surfaces. The geometry of an entire scene can also be approximated by treating the distance values of its camera projection as a screen-space height field. In order to shadow height fields from environment lights a horizon map is usually used to occlude incident light. We reduce the per-receiver time complexity of generating the horizon map on N N height fields from O(N) of the previous work to O(1) by using an algorithm that incrementally traverses the height field and reuses the information already gathered along the path of traversal. We also propose an accurate method to integrate the incident light within the limits given by the horizon map. Indirect illumination in height fields requires information about which other points are visible to each height field point. We present an algorithm to determine this intervisibility in a time complexity that matches the space complexity of the produced visibility information, which is in contrast to previous methods which scale in the height field size. As a result the amount of computation is reduced by two orders of magnitude in common use cases. Screen-space ambient obscurance methods approximate ambient obscurance from the depth bu er geometry and have been widely adopted by contemporary real-time applications. They work by sampling the screen-space geometry around each receiver point but have been previously limited to near- field effects because sampling a large radius quickly exceeds the render time budget. We present an algorithm that reduces the quadratic per-pixel complexity of previous methods to a linear complexity by line sweeping over the depth bu er and maintaining an internal representation of the processed geometry from which occluders can be efficiently queried. Another algorithm is presented to determine ambient obscurance from the entire depth bu er at each screen pixel. The algorithm scans the depth bu er in a quick pre-pass and locates important features in it, which are then used to evaluate the ambient obscurance integral accurately. We also propose an evaluation of the integral such that results within a few percent of the ray traced screen-space reference are obtained at real-time render times.

Incest aversion : the evolutionary roots of individual regulation

Den evolutionära förklaringen till den allmänt utbredda incestaversionen, dvs. motviljan för sex med nära släktingar, försöker besvara såväl frågan om varför incestaversionen gynnats i det naturliga urvalet som frågan om hur denna aversion regleras på individuell nivå. Eftersom inavlade barn har en försämrad biologisk duglighet än andra barn, medför kostnaderna av denna icke-optimala reproduktion ett selektionstryck mot inavel. I en serie studier visade vi att eftersom kvinnor i allmänhet satsar mer biologiska resurser på sina barn än vad män gör, känner kvinnor starkare incestaversion än män och eftersom det endast är fertila kvinnor som riskerar satsa resurser i en inavlad avkomma har även fertila kvinnor högre incestaversion än icke-fertila kvinnor. Vi visade också att de biologiska kostnaderna av inavel inte begränsas till enbart de individer som har incest. Eftersom alla våra biologiska släktingar sannolikt delar våra alleler speglar incestaversionen även de biologiska kostnader som incest mellan våra släktingar medför åt oss. Den psykologiska mekanism med vilken incestsituationer bedöms har hittills varit okänd. I våra studier testades teorin om självreflekterande empati. Enligt den teorin bedöms sådana situationer emotionellt genom att man själv föreställer sig ha sex med motsvarande släkting och känslan som väcks i denna process ger därefter emotionell information till bedömningen av andras incest. I tre delstudier fann vi att självreflektion var positivt associerat med styrkan av aversion gentemot andras incest, vilket stöder teorin om självreflekterande empati.

Comparison between dSPACE and NI systems based on real-time intelligent control of a teleoperated hydraulic servo system

The Laboratory of Intelligent Machine researches and develops energy-efficient power transmissions and automation for mobile construction machines and industrial processes. The laboratory's particular areas of expertise include mechatronic machine design using virtual technologies and simulators and demanding industrial robotics. The laboratory has collaborated extensively with industrial actors and it has participated in significant international research projects, particularly in the field of robotics. For years, dSPACE tools were the lonely hardware which was used in the lab to develop different control algorithms in real-time. dSPACE's hardware systems are in widespread use in the automotive industry and are also employed in drives, aerospace, and industrial automation. But new competitors are developing new sophisticated systems and their features convinced the laboratory to test new products. One of these competitors is National Instrument (NI). In order to get to know the specifications and capabilities of NI tools, an agreement was made to test a NI evolutionary system. This system is used to control a 1-D hydraulic slider. The objective of this research project is to develop a control scheme for the teleoperation of a hydraulically driven manipulator, and to implement a control algorithm between human and machine interaction, and machine and task environment interaction both on NI and dSPACE systems simultaneously and to compare the results.

Achieving EU energy targets – Impacts of evolutionary and revolutionary transition paths on power systems

Ambitious energy targets set by EU put pressures to increase share of renewable electricity supply in this and next decades and therefore, some EU member countries have boosted increasing renewable energy generation capacity by implementing subsidy schemes on national level. In this study, two different change approaches to increase renewable energy supply and increase self-sufficiency of supply are assessed with respect to their impacts on power system, electricity market and electricity generation costs in Finland. It is obtained that the current electricity generation costs are high compared to opportunities of earnings from present-day investor’s perspective. In addition, the growth expectations of consumptions and the price forecasts do not stimulate investing in new generation capacity. Revolutionary transition path is driven by administrative and political interventions to achieve the energy targets. Evolutionary transition path is driven by market-based mechanisms, such as market itself and emission trading scheme. It is obtained in this study that in the revolutionary transition path operation of market-based mechanisms is distorted to some extent and it is likely that this path requires providing more public financial resources compared to evolutionary transition path. In the evolutionary transition path the energy targets are not achieved as quickly but market-based mechanisms function better and investment environment endures more stable compared to revolutionary transition path.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Hardware Accelarated Visual Tracking Algorithms. A Systematic Literature Review

Many industrial applications need object recognition and tracking capabilities. The algorithms developed for those purposes are computationally expensive. Yet ,real time performance, high accuracy and small power consumption are essential measures of the system. When all these requirements are combined, hardware acceleration of these algorithms becomes a feasible solution. The purpose of this study is to analyze the current state of these hardware acceleration solutions, which algorithms have been implemented in hardware and what modifications have been done in order to adapt these algorithms to hardware.