Multi-sensor Simultaneous Localization and Mapping

Simultaneous localization and mapping(SLAM) is a very important problem in mobile robotics. Many solutions have been proposed by different scientists during the last two decades, nevertheless few studies have considered the use of multiple sensors simultane¬ously. The solution is on combining several data sources with the aid of an Extended Kalman Filter (EKF). Two approaches are proposed. The first one is to use the ordinary EKF SLAM algorithm for each data source separately in parallel and then at the end of each step, fuse the results into one solution. Another proposed approach is the use of multiple data sources simultaneously in a single filter. The comparison of the computational com¬plexity of the two methods is also presented. The first method is almost four times faster than the second one.

Minimization of the experimental workload for the prediction of pollutants propagation in rivers. Mathematical modelling and knowledge re-use

The present thesis in focused on the minimization of experimental efforts for the prediction of pollutant propagation in rivers by mathematical modelling and knowledge re-use. Mathematical modelling is based on the well known advection-dispersion equation, while the knowledge re-use approach employs the methods of case based reasoning, graphical analysis and text mining. The thesis contribution to the pollutant transport research field consists of: (1) analytical and numerical models for pollutant transport prediction; (2) two novel techniques which enable the use of variable parameters along rivers in analytical models; (3) models for the estimation of pollutant transport characteristic parameters (velocity, dispersion coefficient and nutrient transformation rates) as functions of water flow, channel characteristics and/or seasonality; (4) the graphical analysis method to be used for the identification of pollution sources along rivers; (5) a case based reasoning tool for the identification of crucial information related to the pollutant transport modelling; (6) and the application of a software tool for the reuse of information during pollutants transport modelling research. These support tools are applicable in the water quality research field and in practice as well, as they can be involved in multiple activities. The models are capable of predicting pollutant propagation along rivers in case of both ordinary pollution and accidents. They can also be applied for other similar rivers in modelling of pollutant transport in rivers with low availability of experimental data concerning concentration. This is because models for parameter estimation developed in the present thesis enable the calculation of transport characteristic parameters as functions of river hydraulic parameters and/or seasonality. The similarity between rivers is assessed using case based reasoning tools, and additional necessary information can be identified by using the software for the information reuse. Such systems represent support for users and open up possibilities for new modelling methods, monitoring facilities and for better river water quality management tools. They are useful also for the estimation of environmental impact of possible technological changes and can be applied in the pre-design stage or/and in the practical use of processes as well.

Bankruptcy prediction using fuzzy methods

In this thesis, a classi cation problem in predicting credit worthiness of a customer is tackled. This is done by proposing a reliable classi cation procedure on a given data set. The aim of this thesis is to design a model that gives the best classi cation accuracy to e ectively predict bankruptcy. FRPCA techniques proposed by Yang and Wang have been preferred since they are tolerant to certain type of noise in the data. These include FRPCA1, FRPCA2 and FRPCA3 from which the best method is chosen. Two di erent approaches are used at the classi cation stage: Similarity classi er and FKNN classi er. Algorithms are tested with Australian credit card screening data set. Results obtained indicate a mean classi cation accuracy of 83.22% using FRPCA1 with similarity classi- er. The FKNN approach yields a mean classi cation accuracy of 85.93% when used with FRPCA2, making it a better method for the suitable choices of the number of nearest neighbors and fuzziness parameters. Details on the calibration of the fuzziness parameter and other parameters associated with the similarity classi er are discussed.

Localization, Frequency, and Functions of Filled Pauses: Five American Politicians’ Use of er and erm in the Talk Show Larry King Live

Tämän pro gradu– tutkielman tavoitteena oli testata täytettyjen taukojen (er ja erm) esiintymistiheyttä, sijaintia kieliopillisessa rakenteessa sekä funktioita Kjellmerin (2003) korpus-tutkimuksessa. Materiaalina käytin viiden yhdysvaltalaisen poliitikon puhetta keskusteluohjelmasta Larry King Live. Tutkimuksessani sovelsin Kjellmerin tutkimusmenetelmiä, joita muokkasin huomattavasti suppeampaan materiaaliini sopiviksi. Lähestymistapani oli täten induktiivinen toisin kuin testatussa tutkimuksessa. Materiaalini oli tarkoituksellisesti rajattu, sillä halusin selvittää, kuvaavatko Kjellmerin laajaan materiaaliin perustuvat tutkimustulokset myös täytettyjen taukojen käyttöä suppeammassa materiaalissa. Materiaalini (kokonaisuudessaan 101 minuuttia) transkriboin ortografisesti. Analyysissäni arvioin täytettyjen taukojen esiintymistiheyden puhujakohtaisesti ja koko ryhmälle suhteuttamalla täytettyjen taukojen lukumäärän kokonaissanamäärään. Tämän jälkeen tein perinteisen kielioppianalyysin rakenteista, joita edeltää tai joissa esiintyy täytetty tauko, ja täytettyjen taukojen sijainnin perusteella luokittelin ne sana-, lauseke-, ja lausetasolle. Lopuksi analysoin täytettyjen taukojen käyttöä soveltaen Kjellmerin ehdottamia funktioita (hesitaatio, vuorottelujäsennyksen merkitseminen, huomion herättäminen ja kontaktin luominen, korostus ja korjaus) ja niiden piirteitä omaan materiaaliini. Tutkimukseni perusteella täytetyt tauot esiintyvät tutkitun viiden poliitikon puheessa suhteellisen usein. Puhujakohtaiset eroavaisuudet olivat kuitenkin huomattavat. Kieliopillisen luokitteluni mukaan sana-, lauseke- ja lausetasot eivät täysin kuvaa täytettyjen taukojen sijoittumista, sillä täytetyt tauot edelsivät mm. määre-lauseita, jotka eivät vastaa lausetasoa englannin kielessä. Materiaalini funktioanalyysi osoitti, että täytetyt tauot yleensä vastaavat yhtä tai useampaa Kjellmerin ehdottamaa funktioita. Lisäksi tutkimukseni mukaan täytetyillä tauoilla on ainakin yksi rakenteellinen funktio. Analyysini perusteella Kjellmerin tutkimustulokset ovat siis pääosin sovellettavissa suppeampaan materiaaliin. Puutteiksi hänen tutkimuksessaan osoittautuivat funktioanalyysille tärkeän kontekstuaalisen informaation puute sekä keskittyminen täytettyihin taukoihin, jotka esiintyvät vain tietyissä kielioppirakenteissa. Yleisesti voin tutkimukseni pohjalta todeta, että täytetyt tauot ovat vielä vajaasti tunnettuja ja että kieliopillisen sijoituksen ja funktioiden lisätutkimus on tarpeellista.

Prediction of 3D structure and ligand-binding properties : ABC transporters and flavodiiron proteins from Synechocystis sp. strain PCC 6803

Cyanobacteria are unicellular, non-nitrogen-fixing prokaryotes, which perform photosynthesis similarly as higher plants. The cyanobacterium Synechocystis sp. strain PCC 6803 is used as a model organism in photosynthesis research. My research described herein aims at understanding the function of the photosynthetic machinery and how it responds to changes in the environment. Detailed knowledge of the regulation of photosynthesis in cyanobacteria can be utilized for biotechnological purposes, for example in the harnessing of solar energy for biofuel production. In photosynthesis, iron participates in electron transfer. Here, we focused on iron transport in Synechocystis sp. strain PCC 6803 and particularly on the environmental regulation of the genes encoding the FutA2BC ferric iron transporter, which belongs to the ABC transporter family. A homology model built for the ATP-binding subunit FutC indicates that it has a functional ATPbinding site as well as conserved interactions with the channel-forming subunit FutB in the transporter complex. Polyamines are important for the cell proliferation, differentiation and apoptosis in prokaryotic and eukaryotic cells. In plants, polyamines have special roles in stress response and in plant survival. The polyamine metabolism in cyanobacteria in response to environmental stress is of interest in research on stress tolerance of higher plants. In this thesis, the potd gene encoding an polyamine transporter subunit from Synechocystis sp. strain PCC 6803 was characterized for the first time. A homology model built for PotD protein indicated that it has capability of binding polyamines, with the preference for spermidine. Furthermore, in order to investigate the structural features of the substrate specificity, polyamines were docked into the binding site. Spermidine was positioned very similarly in Synechocystis PotD as in the template structure and had most favorable interactions of the docked polyamines. Based on the homology model, experimental work was conducted, which confirmed the binding preference. Flavodiiron proteins (Flv) are enzymes, which protect the cell against toxicity of oxygen and/or nitric oxide by reduction. In this thesis, we present a novel type of photoprotection mechanism in cyanobacteria by the heterodimer of Flv2/Flv4. The constructed homology model of Flv2/Flv4 suggests a functional heterodimer capable of rapid electron transfer. The unknown protein sll0218, encoded by the flv2-flv4 operon, is assumed to facilitate the interaction of the Flv2/Flv4 heterodimer and energy transfer between the phycobilisome and PSII. Flv2/Flv4 provides an alternative electron transfer pathway and functions as an electron sink in PSII electron transfer.

Two-dimensional atom localization and Raman cooling of tripod-type atoms

Both atom localization and Raman cooling, considered in the thesis, reflect recent progress in the area of all-optical methods. We focus on twodimensional (2D) case, using a four-level tripod-type atomic scheme for atom localization within the optical half-wavelength as well as for efficient subrecoil Raman cooling. In the first part, we discuss the principles of 1D atom localization, accompanying by an example of the measurement of a spontaneously-emitted photon. Modifying this example, one archives sub-wavelength localization of a three-level -type atom, measuring the population in its upper state. We go further and obtain 2D sub-wavelength localization for a four-level tripod-type atom. The upper-state population is classified according to the spatial distribution, which in turn forms such structures as spikes, craters and waves. The second part of the thesis is devoted to Raman cooling. The cooling process is controlled by a sequence of velocity-selective transfers from one to another ground state. So far, 1D deep subrecoil cooling has been carried out with the sequence of square or Blackman pulses, applied to -type atoms. In turn, we discuss the transfer of atoms by stimulated Raman adiabatic passage (STIRAP), which provides robustness against the pulse duration if the cooling time is not in any critical role. A tripod-type atomic scheme is used for the purpose of 2D Raman cooling, allowing one to increase the efficiency and simplify the realization of the cooling.

Indoor Localization Solutions for a Marine Industry Augmented Reality Tool

In this report are described means for indoor localization in special, challenging circum-stances in marine industry. The work has been carried out in MARIN project, where a tool based on mobile augmented reality technologies for marine industry is developed. The tool can be used for various inspection and documentation tasks and it is aimed for improving the efficiency in design and construction work by offering the possibility to visualize the newest 3D-CAD model in real environment. Indoor localization is needed to support the system in initialization of the accurate camera pose calculation and auto-matically finding the right location in the 3D-CAD model. The suitability of each indoor localization method to the specific environment and circumstances is evaluated.

Linear prediction in optical spectroscopy

A linear prediction procedure is one of the approved numerical methods of signal processing. In the field of optical spectroscopy it is used mainly for extrapolation known parts of an optical signal in order to obtain a longer one or deduce missing signal samples. The first is needed particularly when narrowing spectral lines for the purpose of spectral information extraction. In the present paper the coherent anti-Stokes Raman scattering (CARS) spectra were under investigation. The spectra were significantly distorted by the presence of nonlinear nonresonant background. In addition, line shapes were far from Gaussian/Lorentz profiles. To overcome these disadvantages the maximum entropy method (MEM) for phase spectrum retrieval was used. The obtained broad MEM spectra were further underwent the linear prediction analysis in order to be narrowed.

Prediction of market switching and delisting events from OMX First North Nordic multilateral stock exchange

This thesis studies the predictability of market switching and delisting events from OMX First North Nordic multilateral stock exchange by using financial statement information and market information from 2007 to 2012. This study was conducted by using a three stage process. In first stage relevant theoretical framework and initial variable pool were constructed. Then, explanatory analysis of the initial variable pool was done in order to further limit and identify relevant variables. The explanatory analysis was conducted by using self-organizing map methodology. In the third stage, the predictive modeling was carried out with random forests and support vector machine methodologies. It was found that the explanatory analysis was able to identify relevant variables. The results indicate that the market switching and delisting events can be predicted in some extent. The empirical results also support the usability of financial statement and market information in the prediction of market switching and delisting events.