Contributions to the Theory of Finite-State Based Grammars

This dissertation is a theoretical study of finite-state based grammars used in natural language processing. The study is concerned with certain varieties of finite-state intersection grammars (FSIG) whose parsers define regular relations between surface strings and annotated surface strings. The study focuses on the following three aspects of FSIGs: (i) Computational complexity of grammars under limiting parameters In the study, the computational complexity in practical natural language processing is approached through performance-motivated parameters on structural complexity. Each parameter splits some grammars in the Chomsky hierarchy into an infinite set of subset approximations. When the approximations are regular, they seem to fall into the logarithmic-time hierarchyand the dot-depth hierarchy of star-free regular languages. This theoretical result is important and possibly relevant to grammar induction. (ii) Linguistically applicable structural representations Related to the linguistically applicable representations of syntactic entities, the study contains new bracketing schemes that cope with dependency links, left- and right branching, crossing dependencies and spurious ambiguity. New grammar representations that resemble the Chomsky-Schützenberger representation of context-free languages are presented in the study, and they include, in particular, representations for mildly context-sensitive non-projective dependency grammars whose performance-motivated approximations are linear time parseable. (iii) Compilation and simplification of linguistic constraints Efficient compilation methods for certain regular operations such as generalized restriction are presented. These include an elegant algorithm that has already been adopted as the approach in a proprietary finite-state tool. In addition to the compilation methods, an approach to on-the-fly simplifications of finite-state representations for parse forests is sketched. These findings are tightly coupled with each other under the theme of locality. I argue that the findings help us to develop better, linguistically oriented formalisms for finite-state parsing and to develop more efficient parsers for natural language processing. Avainsanat: syntactic parsing, finite-state automata, dependency grammar, first-order logic, linguistic performance, star-free regular approximations, mildly context-sensitive grammars

Silvicultural decisions based on simulation-optimization systems

Forest management is facing new challenges under climate change. By adjusting thinning regimes, conventional forest management can be adapted to various objectives of utilization of forest resources, such as wood quality, forest bioenergy, and carbon sequestration. This thesis aims to develop and apply a simulation-optimization system as a tool for an interdisciplinary understanding of the interactions between wood science, forest ecology, and forest economics. In this thesis, the OptiFor software was developed for forest resources management. The OptiFor simulation-optimization system integrated the process-based growth model PipeQual, wood quality models, biomass production and carbon emission models, as well as energy wood and commercial logging models into a single optimization model. Osyczka s direct and random search algorithm was employed to identify optimal values for a set of decision variables. The numerical studies in this thesis broadened our current knowledge and understanding of the relationships between wood science, forest ecology, and forest economics. The results for timber production show that optimal thinning regimes depend on site quality and initial stand characteristics. Taking wood properties into account, our results show that increasing the intensity of thinning resulted in lower wood density and shorter fibers. The addition of nutrients accelerated volume growth, but lowered wood quality for Norway spruce. Integrating energy wood harvesting into conventional forest management showed that conventional forest management without energy wood harvesting was still superior in sparse stands of Scots pine. Energy wood from pre-commercial thinning turned out to be optimal for dense stands. When carbon balance is taken into account, our results show that changing carbon assessment methods leads to very different optimal thinning regimes and average carbon stocks. Raising the carbon price resulted in longer rotations and a higher mean annual increment, as well as a significantly higher average carbon stock over the rotation.

Causes and consequences of inbreeding in the ant Formica exsecta

Human actions cause destruction and fragmentation of natural habitats, predisposing populations to loss of genetic diversity and inbreeding, which may further decrease their fitness and survival. Understanding these processes is a main concern in conservation genetics. Yet data from natural populations is scarce, particularly on invertebrates, owing to difficulties in measuring both fitness and inbreeding in the wild. Ants are social insects, and a prime example of an ecologically important group for which the effects of inbreeding remain largely unstudied. Social insects serve key roles in all terrestrial ecosystems, and the division of labor between the females in the colonies queens reproduce, workers tend to the developing brood probably is central to their ecological success. Sociality also has important implications for the effects of inbreeding. Despite their relative abundance, the effective population sizes of social insects tend to be small, owing to the low numbers of reproductive individuals relative to the numbers of sterile workers. This may subject social insects to loss of genetic diversity and subsequent inbreeding depression. Moreover, both the workers and queens can be inbred, with different and possibly multiplicative consequences. The aim of this study was to investigate causes and consequences of inbreeding in a natural population of ants. I used a combination of long-term field and genetic data from colonies of the narrow-headed ant Formica exsecta to examine dispersal, mating behavior and the occurrence of inbreeding, and its consequences on individual and colony traits. Mating in this species takes place in nuptial flights that have been assumed to be population-wide and panmictic. My results, however, show that dispersal is local, with queens establishing new colonies as close as 60 meters from their natal colony. Even though actual sib-mating was rare, individuals from different but related colonies pair, which causes the population to be inbred. Furthermore, multiple mates of queens were related to each other, which also indicates localized mating flights. Hence, known mechanisms of inbreeding avoidance, dispersal and multiple mating, were not effective in this population, as neither reduced inbreeding level of the future colony. Inbreeding had negative consequences both at the individual and colony level. A queen that has mated with a related male produces inbred workers, which impairs the colony s reproductive success. The inbred colonies were less productive and, specifically, produced fewer new queens, possibly owing to effects of inbreeding on the caste determination of female larvae. A striking finding was that males raised in colonies with inbred workers were smaller, which reflects an effect of the social environment as males, being haploid, cannot be inbred themselves. The queens produced in the inbred colonies, in contrast, were not smaller, but their immune response was up-regulated. Inbreeding had no effect on queen dispersal, but inbred queens had a lower probability of successfully founding a new colony. Ultimately, queens that survived through the colony founding phase had a shorter lifespan. This supports the idea that inbreeding imposes a genetic stress, leading to inbreeding depression on both the queen and the colony level. My results show that inbreeding can have profound consequences on insects in the wild, and that in social species the effects of inbreeding may be multiplicative and mediated through the diversity of the social environment, as well as the genetic makeup of the individuals themselves. This emphasizes the need to take into account all levels of organization when assessing the effects of genetic diversity in social animals.

Population structure and evolution in the ant Plagiolepis pygmaea and its two social parasites Plagiolepis xene and Plagiolepis grassei

Social behaviour affects dispersal of animals and is an important modifier of genetic population structures. The female sex is often philopatric, which maintains coancestry within the breeding groups and promotes cooperative behaviours. This enables also inclusive fitness returns from altruism and explains why some individuals sacrifice personal reproduction for the good of others in social insects such as ants. However, reduced dispersal and population substructuring at the level of colonies may also entail inbreeding, loss of genetic diversity, and vulnerability. In addition, the most vulnerable ants are species that are evolved to parasitize colonies of other ants, and which compromise between abilities to disperse and the efficiency to parasitize the host. On the other hand, certain social organisations of ant colonies may facilitate a species to disperse outside its natural range and become a pest. Altogether, knowledge on genetic structuring of ant populations, as well as the evolution of their life histories can contribute to conservation biology and population management. The aim of this thesis was to investigate population structures and phylogenetic evolution of the ant Plagiolepis pygmaea and its two obligatory, workerless social parasites (inquilines) P. xene and P. grassei with genetic markers and DNA sequence data. The results support the general assumption that populations of inquiline parasites are highly fragmented and genetically vulnerable. Comparison of the two parasites suggests that differences in their relative abundance may follow from their interaction with the host, i.e. how well the species is adapted to reproduce in the host colonies. The results also indicate that the most recent free living ancestor to these two parasite species is their common host. This is considered to provide evidence for the controversial issue of sympatric speciation. Further, given that the level of adaptations to parasitic life history depends on the evolutionary time since the free-living ancestor, the results establish a link between species rarity and its evolutionary age. The populations of the host species P. pygmaea displayed significantly reduced dispersal both among the females (queens) and males, and high levels of inbreeding which may enhance worker altruism. In addition, the queens were found to mate with multiple males. Given the high relatedness between the queens and their mates, this occurs probably for non-genetic reasons, e.g. without benefits associated in genetically more diverse offspring. The results hence caution that the contribution of non-genetic factors to the prevailing mating patterns and genetic population structures should not be underestimated.

Vision based indoor positioning in a retail environment

Modern smart phones often come with a significant amount of computational power and an integrated digital camera making them an ideal platform for intelligents assistants. This work is restricted to retail environments, where users could be provided with for example navigational in- structions to desired products or information about special offers within their close proximity. This kind of applications usually require information about the user's current location in the domain environment, which in our case corresponds to a retail store. We propose a vision based positioning approach that recognizes products the user's mobile phone's camera is currently pointing at. The products are related to locations within the store, which enables us to locate the user by pointing the mobile phone's camera to a group of products. The first step of our method is to extract meaningful features from digital images. We use the Scale- Invariant Feature Transform SIFT algorithm, which extracts features that are highly distinctive in the sense that they can be correctly matched against a large database of features from many images. We collect a comprehensive set of images from all meaningful locations within our domain and extract the SIFT features from each of these images. As the SIFT features are of high dimensionality and thus comparing individual features is infeasible, we apply the Bags of Keypoints method which creates a generic representation, visual category, from all features extracted from images taken from a specific location. A category for an unseen image can be deduced by extracting the corresponding SIFT features and by choosing the category that best fits the extracted features. We have applied the proposed method within a Finnish supermarket. We consider grocery shelves as categories which is a sufficient level of accuracy to help users navigate or to provide useful information about nearby products. We achieve a 40% accuracy which is quite low for commercial applications while significantly outperforming the random guess baseline. Our results suggest that the accuracy of the classification could be increased with a deeper analysis on the domain and by combining existing positioning methods with ours.

Kalman Filter Algorithm for Rating and Prediction in Basketball

The Thesis presents a state-space model for a basketball league and a Kalman filter algorithm for the estimation of the state of the league. In the state-space model, each of the basketball teams is associated with a rating that represents its strength compared to the other teams. The ratings are assumed to evolve in time following a stochastic process with independent Gaussian increments. The estimation of the team ratings is based on the observed game scores that are assumed to depend linearly on the true strengths of the teams and independent Gaussian noise. The team ratings are estimated using a recursive Kalman filter algorithm that produces least squares optimal estimates for the team strengths and predictions for the scores of the future games. Additionally, if the Gaussianity assumption holds, the predictions given by the Kalman filter maximize the likelihood of the observed scores. The team ratings allow probabilistic inference about the ranking of the teams and their relative strengths as well as about the teams’ winning probabilities in future games. The predictions about the winners of the games are correct 65-70% of the time. The team ratings explain 16% of the random variation observed in the game scores. Furthermore, the winning probabilities given by the model are concurrent with the observed scores. The state-space model includes four independent parameters that involve the variances of noise terms and the home court advantage observed in the scores. The Thesis presents the estimation of these parameters using the maximum likelihood method as well as using other techniques. The Thesis also gives various example analyses related to the American professional basketball league, i.e., National Basketball Association (NBA), and regular seasons played in year 2005 through 2010. Additionally, the season 2009-2010 is discussed in full detail, including the playoffs.