A sequential analysis of "nú" and "núna" in Icelandic conversation

This thesis is an empirical study of how two words in Icelandic, "nú" and "núna", are used in contemporary Icelandic conversation. My aims in this study are, first, to explain the differences between the temporal functions of "nú" and "núna", and, second, to describe the non-temporal functions of "nú". In the analysis, a focus is placed on comparing the sequential placement of the two words, on their syntactical distribution, and on their prosodic realization. The empirical data comprise 14 hours and 11 minutes of naturally occurring conversation recorded between 1996 and 2003. The selected conversations represent a wide range of interactional contexts including informal dinner parties, institutional and non-institutional telephone conversations, radio programs for teenagers, phone-in programs, and, finally, a political debate on television. The theoretical and methodological framework is interactional linguistics, which can be described as linguistically oriented conversation analysis (CA). A comparison of "nú" and "núna" shows that the two words have different syntactic distributions. "Nú" has a clear tendency to occur in the front field, before the finite verb, while "núna" typically occurs in the end field, after the object. It is argued that this syntactic difference reflects a functional difference between "nú" and "núna". A sequential analysis of "núna" shows that the word refers to an unspecified period of time which includes the utterance time as well as some time in the past and in the future. This temporal relation is referred to as reference time. "Nú", by contrast, is mainly used in three different environments: a) in temporal comparisons, 2) in transitions, and 3) when the speaker is taking an affective stance. The non-temporal functions of "nú" are divided into three categories: a) "nú" as a tone particle, 2) "nú" as an utterance particle, and 3) "nú" as a dialogue particle. "Nú" as a tone particle is syntactically integrated and can occur in two syntactic positions: pre-verbally and post-verbally. I argue that these instances are employed in utterances in which a speaker is foregrounding information or marking it as particularly important. The study shows that, although these instances are typically prosodically non-prominent and unstressed, they are in some cases delivered with stress and with a higher pitch than the surrounding talk. "Nú" as an utterance particle occurs turn-initially and is syntactically non-integrated. By using "nú", speakers show continuity between turns and link new turns to prior ones. These instances initiate either continuations by the same speaker or new turns after speaker shifts. "Nú" as a dialogue particle occurs as a turn of its own. The study shows that these instances register informings in prior turns as unexpected or as a departure from the normal state of affairs. "Nú" as a dialogue particle is often delivered with a prolonged vowel and a recognizable intonation contour. A comparative sequential and prosodic analysis shows that in these cases there is a correlation between the function of "nú" and the intonation contour by which it is delivered. Finally, I argue that despite the many functions of "nú", all the instances can be said to have a common denominator, which is to display attention towards the present moment and the utterances which are produced prior or after the production of "nú". Instead of anchoring the utterances in external time or reference time, these instances position the utterance in discourse internal time, or discourse time.

Monte Carlo Simulations of Molecular Clusters in Nucleation

A better understanding of the limiting step in a first order phase transition, the nucleation process, is of major importance to a variety of scientific fields ranging from atmospheric sciences to nanotechnology and even to cosmology. This is due to the fact that in most phase transitions the new phase is separated from the mother phase by a free energy barrier. This barrier is crossed in a process called nucleation. Nowadays it is considered that a significant fraction of all atmospheric particles is produced by vapor-to liquid nucleation. In atmospheric sciences, as well as in other scientific fields, the theoretical treatment of nucleation is mostly based on a theory known as the Classical Nucleation Theory. However, the Classical Nucleation Theory is known to have only a limited success in predicting the rate at which vapor-to-liquid nucleation takes place at given conditions. This thesis studies the unary homogeneous vapor-to-liquid nucleation from a statistical mechanics viewpoint. We apply Monte Carlo simulations of molecular clusters to calculate the free energy barrier separating the vapor and liquid phases and compare our results against the laboratory measurements and Classical Nucleation Theory predictions. According to our results, the work of adding a monomer to a cluster in equilibrium vapour is accurately described by the liquid drop model applied by the Classical Nucleation Theory, once the clusters are larger than some threshold size. The threshold cluster sizes contain only a few or some tens of molecules depending on the interaction potential and temperature. However, the error made in modeling the smallest of clusters as liquid drops results in an erroneous absolute value for the cluster work of formation throughout the size range, as predicted by the McGraw-Laaksonen scaling law. By calculating correction factors to Classical Nucleation Theory predictions for the nucleation barriers of argon and water, we show that the corrected predictions produce nucleation rates that are in good comparison with experiments. For the smallest clusters, the deviation between the simulation results and the liquid drop values are accurately modelled by the low order virial coefficients at modest temperatures and vapour densities, or in other words, in the validity range of the non-interacting cluster theory by Frenkel, Band and Bilj. Our results do not indicate a need for a size dependent replacement free energy correction. The results also indicate that Classical Nucleation Theory predicts the size of the critical cluster correctly. We also presents a new method for the calculation of the equilibrium vapour density, surface tension size dependence and planar surface tension directly from cluster simulations. We also show how the size dependence of the cluster surface tension in equimolar surface is a function of virial coefficients, a result confirmed by our cluster simulations.

Monte Carlo simulations of molecular clusters in nucleation

A better understanding of the limiting step in a first order phase transition, the nucleation process, is of major importance to a variety of scientific fields ranging from atmospheric sciences to nanotechnology and even to cosmology. This is due to the fact that in most phase transitions the new phase is separated from the mother phase by a free energy barrier. This barrier is crossed in a process called nucleation. Nowadays it is considered that a significant fraction of all atmospheric particles is produced by vapor-to liquid nucleation. In atmospheric sciences, as well as in other scientific fields, the theoretical treatment of nucleation is mostly based on a theory known as the Classical Nucleation Theory. However, the Classical Nucleation Theory is known to have only a limited success in predicting the rate at which vapor-to-liquid nucleation takes place at given conditions. This thesis studies the unary homogeneous vapor-to-liquid nucleation from a statistical mechanics viewpoint. We apply Monte Carlo simulations of molecular clusters to calculate the free energy barrier separating the vapor and liquid phases and compare our results against the laboratory measurements and Classical Nucleation Theory predictions. According to our results, the work of adding a monomer to a cluster in equilibrium vapour is accurately described by the liquid drop model applied by the Classical Nucleation Theory, once the clusters are larger than some threshold size. The threshold cluster sizes contain only a few or some tens of molecules depending on the interaction potential and temperature. However, the error made in modeling the smallest of clusters as liquid drops results in an erroneous absolute value for the cluster work of formation throughout the size range, as predicted by the McGraw-Laaksonen scaling law. By calculating correction factors to Classical Nucleation Theory predictions for the nucleation barriers of argon and water, we show that the corrected predictions produce nucleation rates that are in good comparison with experiments. For the smallest clusters, the deviation between the simulation results and the liquid drop values are accurately modelled by the low order virial coefficients at modest temperatures and vapour densities, or in other words, in the validity range of the non-interacting cluster theory by Frenkel, Band and Bilj. Our results do not indicate a need for a size dependent replacement free energy correction. The results also indicate that Classical Nucleation Theory predicts the size of the critical cluster correctly. We also presents a new method for the calculation of the equilibrium vapour density, surface tension size dependence and planar surface tension directly from cluster simulations. We also show how the size dependence of the cluster surface tension in equimolar surface is a function of virial coefficients, a result confirmed by our cluster simulations.

Late-industrial sawmill customers.

The methods of secondary wood processing are assumed to evolve over time and to affect the requirements set for the wood material and its suppliers. The study aimed at analysing the industrial operating modes applied by joinery and furniture manufacturers as sawnwood users. Industrial operating mode was defined as a pattern of important decisions and actions taken by a company which describes the company's level of adjustment in the late-industrial transition. A non-probabilistic sample of 127 companies was interviewed, including companies from Denmark, Germany, the Netherlands, and Finland. Fifty-two of the firms were furniture manufacturers and the other 75 were producing windows and doors. Variables related to business philosophy, production operations, and supplier choice criteria were measured and used as a basis for a customer typology; variables related to wood usage and perceived sawmill performance were measured to be used to profile the customer types. Factor analysis was used to determine the latent dimensions of industrial operating mode. Canonical correlations analysis was applied in developing the final base for classifying the observations. Non-hierarchical cluster analysis was employed to build a five-group typology of secondary wood processing firms; these ranged from traditional mass producers to late-industrial flexible manufacturers. There is a clear connection between the amount of late-industrial elements in a company and the share of special and customised sawnwood it uses. Those joinery or furniture manufacturers that are more late-industrial also are likely to use more component-type wood material and to appreciate customer-oriented technical precision. The results show that the change is towards the use of late-industrial sawnwood materials and late-industrial supplier relationships.

Growth and Modification of Cluster-Assembled Thin Films

Thin film applications have become increasingly important in our search for multifunctional and economically viable technological solutions of the future. Thin film coatings can be used for a multitude of purposes, ranging from a basic enhancement of aesthetic attributes to the addition of a complex surface functionality. Anything from electronic or optical properties, to an increased catalytic or biological activity, can be added or enhanced by the deposition of a thin film, with a thickness of only a few atomic layers at the best, on an already existing surface. Thin films offer both a means of saving in materials and the possibility for improving properties without a critical enlargement of devices. Nanocluster deposition is a promising new method for the growth of structured thin films. Nanoclusters are small aggregates of atoms or molecules, ranging in sizes from only a few nanometers up to several hundreds of nanometers in diameter. Due to their large surface to volume ratio, and the confinement of atoms and electrons in all three dimensions, nanoclusters exhibit a wide variety of exotic properties that differ notably from those of both single atoms and bulk materials. Nanoclusters are a completely new type of building block for thin film deposition. As preformed entities, clusters provide a new means of tailoring the properties of thin films before their growth, simply by changing the size or composition of the clusters that are to be deposited. Contrary to contemporary methods of thin film growth, which mainly rely on the deposition of single atoms, cluster deposition also allows for a more precise assembly of thin films, as the configuration of single atoms with respect to each other is already predetermined in clusters. Nanocluster deposition offers a possibility for the coating of virtually any material with a nanostructured thin film, and therein the enhancement of already existing physical or chemical properties, or the addition of some exciting new feature. A clearer understanding of cluster-surface interactions, and the growth of thin films by cluster deposition, must, however, be achieved, if clusters are to be successfully used in thin film technologies. Using a combination of experimental techniques and molecular dynamics simulations, both the deposition of nanoclusters, and the growth and modification of cluster-assembled thin films, are studied in this thesis. Emphasis is laid on an understanding of the interaction between metal clusters and surfaces, and therein the behaviour of these clusters during deposition and thin film growth. The behaviour of single metal clusters, as they impact on clean metal surfaces, is analysed in detail, from which it is shown that there exists a cluster size and deposition energy dependent limit, below which epitaxial alignment occurs. If larger clusters are deposited at low energies, or cluster-surface interactions are weaker, non-epitaxial deposition will take place, resulting in the formation of nanocrystalline structures. The effect of cluster size and deposition energy on the morphology of cluster-assembled thin films is also determined, from which it is shown that nanocrystalline cluster-assembled films will be porous. Modification of these thin films, with the purpose of enhancing their mechanical properties and durability, without destroying their nanostructure, is presented. Irradiation with heavy ions is introduced as a feasible method for increasing the density, and therein the mechanical stability, of cluster-assembled thin films, without critically destroying their nanocrystalline properties. The results of this thesis demonstrate that nanocluster deposition is a suitable technique for the growth of nanostructured thin films. The interactions between nanoclusters and their supporting surfaces must, however, be carefully considered, if a controlled growth of cluster-assembled thin films, with precisely tailored properties, is to be achieved.

Semi-supervised learning of WLAN radio maps

In this thesis a manifold learning method is applied to the problem of WLAN positioning and automatic radio map creation. Due to the nature of WLAN signal strength measurements, a signal map created from raw measurements results in non-linear distance relations between measurement points. These signal strength vectors reside in a high-dimensioned coordinate system. With the help of the so called Isomap-algorithm the dimensionality of this map can be reduced, and thus more easily processed. By embedding position-labeled strategic key points, we can automatically adjust the mapping to match the surveyed environment. The environment is thus learned in a semi-supervised way; gathering training points and embedding them in a two-dimensional manifold gives us a rough mapping of the measured environment. After a calibration phase, where the labeled key points in the training data are used to associate coordinates in the manifold representation with geographical locations, we can perform positioning using the adjusted map. This can be achieved through a traditional supervised learning process, which in our case is a simple nearest neighbors matching of a sampled signal strength vector. We deployed this system in two locations in the Kumpula campus in Helsinki, Finland. Results indicate that positioning based on the learned radio map can achieve good accuracy, especially in hallways or other areas in the environment where the WLAN signal is constrained by obstacles such as walls.