958 resultados para multivariate binary data


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In this paper we design and develop several filtering strategies for the analysis of data generated by a resonant bar gravitational wave (GW) antenna, with the goal of assessing the presence (or absence) therein of long-duration monochromatic GW signals, as well as the eventual amplitude and frequency of the signals, within the sensitivity band of the detector. Such signals are most likely generated in the fast rotation of slightly asymmetric spinning stars. We develop practical procedures, together with a study of their statistical properties, which will provide us with useful information on the performance of each technique. The selection of candidate events will then be established according to threshold-crossing probabilities, based on the Neyman-Pearson criterion. In particular, it will be shown that our approach, based on phase estimation, presents a better signal-to-noise ratio than does pure spectral analysis, the most common approach.

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BACKGROUND AND PURPOSE: There are few data on long-term clinical results and tolerance of brachytherapy in anal canal cancer. We present one of the largest retrospective analyses of anal canal cancers treated with external beam radiotherapy with/without (±) chemotherapy followed by a brachytherapy boost. MATERIALS AND METHODS: We performed a retrospective analysis of clinical results in terms of efficacy and toxicity. The impact of different clinical and therapeutic variables on these outcomes was studied. RESULTS: From May 1992 to December 2009, 209 patients received brachytherapy after external beam radiotherapy ± chemotherapy. Of these patients, 163 were stage II or stage IIIA (UICC 2002) and 58 were N1-3. According to age, ECOG performance status (PS), and comorbidities, patients received either radiotherapy alone (58/209) or radiochemotherapy (151/209). The median follow-up was 72.8 months. The 5- and 10-year local control rates were 78.6 and 73.9 %, respectively. Globally, severe acute and late G3-4 reactions (NCI-CTC scale v. 4.0) occurred in 11.2 and 6.3 % of patients, respectively. Univariate analysis showed the statistical impact of the pelvic treatment volume (p = 0.046) and of the total dose (p = 0.02) on the risk of severe acute and late toxicities, respectively. Only six patients required permanent colostomy because of severe late anorectal toxicities. CONCLUSION: After a long follow-up time, brachytherapy showed an acceptable toxicity profile and high local control rates in patients with anal canal cancer.

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BACKGROUND: Globally, Africans and African Americans experience a disproportionate burden of type 2 diabetes, compared to other race and ethnic groups. The aim of the study was to examine the association of plasma glucose with indices of glucose metabolism in young adults of African origin from 5 different countries. METHODS: We identified participants from the Modeling the Epidemiologic Transition Study, an international study of weight change and cardiovascular disease (CVD) risk in five populations of African origin: USA (US), Jamaica, Ghana, South Africa, and Seychelles. For the current study, we included 667 participants (34.8 ± 6.3 years), with measures of plasma glucose, insulin, leptin, and adiponectin, as well as moderate and vigorous physical activity (MVPA, minutes/day [min/day]), daily sedentary time (min/day), anthropometrics, and body composition. RESULTS: Among the 282 men, body mass index (BMI) ranged from 22.1 to 29.6 kg/m(2) in men and from 25.8 to 34.8 kg/m(2) in 385 women. MVPA ranged from 26.2 to 47.1 min/day in men, and from 14.3 to 27.3 min/day in women and correlated with adiposity (BMI, waist size, and % body fat) only among US males after controlling for age. Plasma glucose ranged from 4.6 ± 0.8 mmol/L in the South African men to 5.8 mmol/L US men, while the overall prevalence for diabetes was very low, except in the US men and women (6.7 and 12 %, respectively). Using multivariate linear regression, glucose was associated with BMI, age, sex, smoking hypertension, daily sedentary time but not daily MVPA. CONCLUSION: Obesity, metabolic risk, and other potential determinants vary significantly between populations at differing stages of the epidemiologic transition, requiring tailored public health policies to address local population characteristics.

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An important aspect of immune monitoring for vaccine development, clinical trials, and research is the detection, measurement, and comparison of antigen-specific T-cells from subject samples under different conditions. Antigen-specific T-cells compose a very small fraction of total T-cells. Developments in cytometry technology over the past five years have enabled the measurement of single-cells in a multivariate and high-throughput manner. This growth in both dimensionality and quantity of data continues to pose a challenge for effective identification and visualization of rare cell subsets, such as antigen-specific T-cells. Dimension reduction and feature extraction play pivotal role in both identifying and visualizing cell populations of interest in large, multi-dimensional cytometry datasets. However, the automated identification and visualization of rare, high-dimensional cell subsets remains challenging. Here we demonstrate how a systematic and integrated approach combining targeted feature extraction with dimension reduction can be used to identify and visualize biological differences in rare, antigen-specific cell populations. By using OpenCyto to perform semi-automated gating and features extraction of flow cytometry data, followed by dimensionality reduction with t-SNE we are able to identify polyfunctional subpopulations of antigen-specific T-cells and visualize treatment-specific differences between them.

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Context. The understanding of Galaxy evolution can be facilitated by the use of population synthesis models, which allow to test hypotheses on the star formation history, star evolution, as well as chemical and dynamical evolution of the Galaxy. Aims. The new version of the Besanc¸on Galaxy Model (hereafter BGM) aims to provide a more flexible and powerful tool to investigate the Initial Mass Function (IMF) and Star Formation Rate (SFR) of the Galactic disc. Methods. We present a new strategy for the generation of thin disc stars which assumes the IMF, SFR and evolutionary tracks as free parameters. We have updated most of the ingredients for the star count production and, for the first time, binary stars are generated in a consistent way. We keep in this new scheme the local dynamical self-consistency as in Bienayme et al (1987). We then compare simulations from the new model with Tycho-2 data and the local luminosity function, as a first test to verify and constrain the new ingredients. The effects of changing thirteen different ingredients of the model are systematically studied. Results. For the first time, a full sky comparison is performed between BGM and data. This strategy allows to constrain the IMF slope at high masses which is found to be close to 3.0, excluding a shallower slope such as Salpeter"s one. The SFR is found decreasing whatever IMF is assumed. The model is compatible with a local dark matter density of 0.011 M pc−3 implying that there is no compelling evidence for significant amount of dark matter in the disc. While the model is fitted to Tycho2 data, a magnitude limited sample with V<11, we check that it is still consistent with fainter stars. Conclusions. The new model constitutes a new basis for further comparisons with large scale surveys and is being prepared to become a powerful tool for the analysis of the Gaia mission data.

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This thesis develops a comprehensive and a flexible statistical framework for the analysis and detection of space, time and space-time clusters of environmental point data. The developed clustering methods were applied in both simulated datasets and real-world environmental phenomena; however, only the cases of forest fires in Canton of Ticino (Switzerland) and in Portugal are expounded in this document. Normally, environmental phenomena can be modelled as stochastic point processes where each event, e.g. the forest fire ignition point, is characterised by its spatial location and occurrence in time. Additionally, information such as burned area, ignition causes, landuse, topographic, climatic and meteorological features, etc., can also be used to characterise the studied phenomenon. Thereby, the space-time pattern characterisa- tion represents a powerful tool to understand the distribution and behaviour of the events and their correlation with underlying processes, for instance, socio-economic, environmental and meteorological factors. Consequently, we propose a methodology based on the adaptation and application of statistical and fractal point process measures for both global (e.g. the Morisita Index, the Box-counting fractal method, the multifractal formalism and the Ripley's K-function) and local (e.g. Scan Statistics) analysis. Many measures describing the space-time distribution of environmental phenomena have been proposed in a wide variety of disciplines; nevertheless, most of these measures are of global character and do not consider complex spatial constraints, high variability and multivariate nature of the events. Therefore, we proposed an statistical framework that takes into account the complexities of the geographical space, where phenomena take place, by introducing the Validity Domain concept and carrying out clustering analyses in data with different constrained geographical spaces, hence, assessing the relative degree of clustering of the real distribution. Moreover, exclusively to the forest fire case, this research proposes two new methodologies to defining and mapping both the Wildland-Urban Interface (WUI) described as the interaction zone between burnable vegetation and anthropogenic infrastructures, and the prediction of fire ignition susceptibility. In this regard, the main objective of this Thesis was to carry out a basic statistical/- geospatial research with a strong application part to analyse and to describe complex phenomena as well as to overcome unsolved methodological problems in the characterisation of space-time patterns, in particular, the forest fire occurrences. Thus, this Thesis provides a response to the increasing demand for both environmental monitoring and management tools for the assessment of natural and anthropogenic hazards and risks, sustainable development, retrospective success analysis, etc. The major contributions of this work were presented at national and international conferences and published in 5 scientific journals. National and international collaborations were also established and successfully accomplished. -- Cette thèse développe une méthodologie statistique complète et flexible pour l'analyse et la détection des structures spatiales, temporelles et spatio-temporelles de données environnementales représentées comme de semis de points. Les méthodes ici développées ont été appliquées aux jeux de données simulées autant qu'A des phénomènes environnementaux réels; nonobstant, seulement le cas des feux forestiers dans le Canton du Tessin (la Suisse) et celui de Portugal sont expliqués dans ce document. Normalement, les phénomènes environnementaux peuvent être modélisés comme des processus ponctuels stochastiques ou chaque événement, par ex. les point d'ignition des feux forestiers, est déterminé par son emplacement spatial et son occurrence dans le temps. De plus, des informations tels que la surface bru^lée, les causes d'ignition, l'utilisation du sol, les caractéristiques topographiques, climatiques et météorologiques, etc., peuvent aussi être utilisées pour caractériser le phénomène étudié. Par conséquent, la définition de la structure spatio-temporelle représente un outil puissant pour compren- dre la distribution du phénomène et sa corrélation avec des processus sous-jacents tels que les facteurs socio-économiques, environnementaux et météorologiques. De ce fait, nous proposons une méthodologie basée sur l'adaptation et l'application de mesures statistiques et fractales des processus ponctuels d'analyse global (par ex. l'indice de Morisita, la dimension fractale par comptage de boîtes, le formalisme multifractal et la fonction K de Ripley) et local (par ex. la statistique de scan). Des nombreuses mesures décrivant les structures spatio-temporelles de phénomènes environnementaux peuvent être trouvées dans la littérature. Néanmoins, la plupart de ces mesures sont de caractère global et ne considèrent pas de contraintes spatiales com- plexes, ainsi que la haute variabilité et la nature multivariée des événements. A cet effet, la méthodologie ici proposée prend en compte les complexités de l'espace géographique ou le phénomène a lieu, à travers de l'introduction du concept de Domaine de Validité et l'application des mesures d'analyse spatiale dans des données en présentant différentes contraintes géographiques. Cela permet l'évaluation du degré relatif d'agrégation spatiale/temporelle des structures du phénomène observé. En plus, exclusif au cas de feux forestiers, cette recherche propose aussi deux nouvelles méthodologies pour la définition et la cartographie des zones périurbaines, décrites comme des espaces anthropogéniques à proximité de la végétation sauvage ou de la forêt, et de la prédiction de la susceptibilité à l'ignition de feu. A cet égard, l'objectif principal de cette Thèse a été d'effectuer une recherche statistique/géospatiale avec une forte application dans des cas réels, pour analyser et décrire des phénomènes environnementaux complexes aussi bien que surmonter des problèmes méthodologiques non résolus relatifs à la caractérisation des structures spatio-temporelles, particulièrement, celles des occurrences de feux forestières. Ainsi, cette Thèse fournit une réponse à la demande croissante de la gestion et du monitoring environnemental pour le déploiement d'outils d'évaluation des risques et des dangers naturels et anthro- pogéniques. Les majeures contributions de ce travail ont été présentées aux conférences nationales et internationales, et ont été aussi publiées dans 5 revues internationales avec comité de lecture. Des collaborations nationales et internationales ont été aussi établies et accomplies avec succès.

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La tècnica de l’electroencefalograma (EEG) és una de les tècniques més utilitzades per estudiar el cervell. En aquesta tècnica s’enregistren els senyals elèctrics que es produeixen en el còrtex humà a través d’elèctrodes col•locats al cap. Aquesta tècnica, però, presenta algunes limitacions a l’hora de realitzar els enregistraments, la principal limitació es coneix com a artefactes, que són senyals indesitjats que es mesclen amb els senyals EEG. L’objectiu d’aquest treball de final de màster és presentar tres nous mètodes de neteja d’artefactes que poden ser aplicats en EEG. Aquests estan basats en l’aplicació de la Multivariate Empirical Mode Decomposition, que és una nova tècnica utilitzada per al processament de senyal. Els mètodes de neteja proposats s’apliquen a dades EEG simulades que contenen artefactes (pestanyeigs), i un cop s’han aplicat els procediments de neteja es comparen amb dades EEG que no tenen pestanyeigs, per comprovar quina millora presenten. Posteriorment, dos dels tres mètodes de neteja proposats s’apliquen sobre dades EEG reals. Les conclusions que s’han extret del treball són que dos dels nous procediments de neteja proposats es poden utilitzar per realitzar el preprocessament de dades reals per eliminar pestanyeigs.

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Recent years have produced great advances in the instrumentation technology. The amount of available data has been increasing due to the simplicity, speed and accuracy of current spectroscopic instruments. Most of these data are, however, meaningless without a proper analysis. This has been one of the reasons for the overgrowing success of multivariate handling of such data. Industrial data is commonly not designed data; in other words, there is no exact experimental design, but rather the data have been collected as a routine procedure during an industrial process. This makes certain demands on the multivariate modeling, as the selection of samples and variables can have an enormous effect. Common approaches in the modeling of industrial data are PCA (principal component analysis) and PLS (projection to latent structures or partial least squares) but there are also other methods that should be considered. The more advanced methods include multi block modeling and nonlinear modeling. In this thesis it is shown that the results of data analysis vary according to the modeling approach used, thus making the selection of the modeling approach dependent on the purpose of the model. If the model is intended to provide accurate predictions, the approach should be different than in the case where the purpose of modeling is mostly to obtain information about the variables and the process. For industrial applicability it is essential that the methods are robust and sufficiently simple to apply. In this way the methods and the results can be compared and an approach selected that is suitable for the intended purpose. Differences in data analysis methods are compared with data from different fields of industry in this thesis. In the first two papers, the multi block method is considered for data originating from the oil and fertilizer industries. The results are compared to those from PLS and priority PLS. The third paper considers applicability of multivariate models to process control for a reactive crystallization process. In the fourth paper, nonlinear modeling is examined with a data set from the oil industry. The response has a nonlinear relation to the descriptor matrix, and the results are compared between linear modeling, polynomial PLS and nonlinear modeling using nonlinear score vectors.

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The synthesis and characterization of crosslinked chitosan microbeads and their application in the removal of Cr(VI) are described. New kinetic and thermodynamic parameters of Cr(VI) adsorptions processes were found using continuous isothermal calorimetry. All adsorption processes are exothermic in nature. However, a multivariate statistical analysis have pointed out that adsorption enthalpies were affected by important binary interactions of the initial Cr(VI) in solution and temperature. The adsorption energetic data were well fitted to a kinetic exponential model, which have indicated fractionary adsorption kinetic orders.

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The optimization of the anaerobic degradation of the azo dye Remazol golden yellow RNL was performed according to multivariate experimental designs: a 2² full-factorial design and a central composite design (CCD). The CCD revealed that the best incubation conditions (90% color removal) for the degradation of the azo dye (50 mg L- 1) were achieved with 350 mg L- 1 of yeast extract and 45 mL of anaerobic supernatant (free cell extract) produced from the incubation of 650 mg L- 1 of anaerobic microorganisms and 250 mg L- 1 of glucose. A first-order kinetics model best fit the experimental data (k = 0.0837 h- 1, R² = 0.9263).

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The aim of this present work was to provide a more fast, simple and less expensive to analyze sulfur content in diesel samples than by the standard methods currently used. Thus, samples of diesel fuel with sulfur concentrations varying from 400 and 2500 mgkg-1 were analyzed by two methodologies: X-ray fluorescence, according to ASTM D4294 and by Fourier transform infrared spectrometry (FTIR). The spectral data obtained from FTIR were used to build multivariate calibration models by partial least squares (PLS). Four models were built in three different ways: 1) a model using the full spectra (665 to 4000 cm-1), 2) two models using some specific spectrum regions and 3) a model with variable selected by classic method of variable selection stepwise. The model obtained by variable selection stepwise and the model built with region spectra between 665 and 856 cm-1 and 1145 and 2717 cm-1 showed better results in the determination of sulfur content.

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Abstract This doctoral thesis concerns the active galactic nucleus (AGN) most often referred to with the catalogue number OJ287. The publications in the thesis present new discoveries of the system in the context of a supermassive binary black hole model. In addition, the introduction discusses general characteristics of the OJ287 system and the physical fundamentals behind these characteristics. The place of OJ287 in the hierarchy of known types of AGN is also discussed. The introduction presents a large selection of fundamental physics required to have a basic understanding of active galactic nuclei, binary black holes, relativistic jets and accretion disks. Particularly the general relativistic nature of the orbits of close binaries of supermassive black holes is explored with some detail. Analytic estimates of some of the general relativistic effects in such a binary are presented, as well as numerical methods to calculate the effects more precisely. It is also shown how these results can be applied to the OJ287 system. The binary orbit model forms the basis for models of the recurring optical outbursts in the OJ287 system. In the introduction, two physical outburst models are presented in some detail and compared. The radiation hydrodynamics of the outbursts are discussed and optical light curve predictions are derived. The precursor outbursts studied in Paper III are also presented, and tied into the model of OJ287. To complete the discussion of the observable features of OJ287, the nature of the relativistic jets in the system, and in active galactic nuclei in general, is discussed. Basic physics of relativistic jets are presented, with additional detail added in the form of helical jet models. The results of Papers II, IV and V concerning the jet of OJ287 are presented, and their relation to other facets of the binary black hole model is discussed. As a whole, the introduction serves as a guide, though terse, for the physics and numerical methods required to successfully understand and simulate a close binary of supermassive black holes. For this purpose, the introduction necessarily combines a large number of both fundamental and specific results from broad disciplines like general relativity and radiation hydrodynamics. With the material included in the introduction, the publications of the thesis, which present new results with a much narrower focus, can be readily understood. Of the publications, Paper I presents newly discovered optical data points for OJ287, detected on archival astronomical plates from the Harvard College Observatory. These data points show the 1900 outburst of OJ287 for the first time. In addition, new data points covering the 1913 outburst allowed the determination of the start of the outburst with more precision than was possible before. These outbursts were then successfully numerically modelled with an N-body simulation of the OJ287 binary and accretion disc. In Paper II, mechanisms for the spin-up of the secondary black hole in OJ287 via interaction with the primary accretion disc and the magnetic fields in the system are discussed. Timescales for spin-up and alignment via both processes are estimated. It is found that the secondary black hole likely has a high spin. Paper III reports a new outburst of OJ287 in March 2013. The outburst was found to be rather similar to the ones reported in 1993 and 2004. All these outbursts happened just before the main outburst season, and are called precursor outbursts. In this paper, a mechanism was proposed for the precursor outbursts, where the secondary black hole collides with a gas cloud in the primary accretion disc corona. From this, estimates of brightness and timescales for the precursor were derived, as well as a prediction of the timing of the next precursor outburst. In Paper IV, observations from the 2004–2006 OJ287 observing program are used to investigate the existence of short periodicities in OJ287. The existence of a _50 day quasiperiodic component is confirmed. In addition, statistically significant 250 day and 3.5 day periods are found. Primary black hole accretion of a spiral density wave in the accretion disc is proposed as the source of the 50 day period, with numerical simulations supporting these results. Lorentz contracted jet re-emission is then proposed as the reason for the 3.5 day timescale. Paper V fits optical observations and mm and cm radio observations of OJ287 with a helical jet model. The jet is found to have a spine–sheath structure, with the sheath having a much lower Lorentz gamma factor than the spine. The sheath opening angle and Lorentz factor, as well as the helical wavelength of the jet are reported for the first time. Tiivistelmä Tässä väitöskirjatutkimuksessa on keskitytty tutkimaan aktiivista galaksiydintä OJ287. Väitöskirjan osana olevat tieteelliset julkaisut esittelevät OJ287-systeemistä saatuja uusia tuloksia kaksoismusta-aukkomallin kontekstissa. Väitöskirjan johdannossa käsitellään OJ287:n yleisiä ominaisuuksia ja niitä fysikaalisia perusilmiöitä, jotka näiden ominaisuuksien taustalla vaikuttavat. Johdanto selvittää myös OJ287-järjestelmän sijoittumisen aktiivisten galaksiytimien hierarkiassa. Johdannossa käydään läpi joitakin perusfysiikan tuloksia, jotka ovat tarpeen aktiivisten galaksiydinten, mustien aukkojen binäärien, relativististen suihkujen ja kertymäkiekkojen ymmärtämiseksi. Kahden toisiaan kiertävän mustan aukon keskinäisen radan suhteellisuusteoreettiset perusteet käydään läpi yksityiskohtaisemmin. Johdannossa esitetään joitakin analyyttisiä tuloksia tällaisessa binäärissä havaittavista suhteellisuusteoreettisista ilmiöistä. Myös numeerisia menetelmiä näiden ilmiöiden tarkempaan laskemiseen esitellään. Tuloksia sovelletaan OJ287-systeemiin, ja verrataan havaintoihin. OJ287:n mustien aukkojen ratamalli muodostaa pohjan systeemin toistuvien optisten purkausten malleille. Johdannossa esitellään yksityiskohtaisemmin kaksi fysikaalista purkausmallia, ja vertaillaan niitä. Purkausten säteilyhydrodynamiikka käydään läpi, ja myös ennusteet purkausten valokäyrille johdetaan. Johdannossa esitellään myös Julkaisussa III johdettu prekursoripurkausten malli, ja osoitetaan sen sopivan yhteen OJ287:n binäärimallin kanssa. Johdanto esittelee myös relativististen suihkujen fysiikkaa sekä OJ287- systeemiin liittyen että aktiivisten galaksiydinten kontekstissa yleisesti. Relativististen suihkujen perusfysiikka esitellään, kuten myös malleja kierteisistä suihkuista. Julkaisujen II, IV ja V OJ287-systeemin suihkuja koskevat tulokset esitellään binäärimallin kontekstissa. Kokonaisuutena johdanto palvelee suppeana oppaana, joka esittelee tarvittavan fysiikan ja tarpeelliset numeeriset menetelmät mustien aukkojen binäärijärjestelmän ymmärtämiseen ja simulointiin. Tätä tarkoitusta varten johdanto yhdistää sekä perustuloksia että joitakin syvällisempiä tuloksia laajoilta fysiikan osa-alueilta kuten suhteellisuusteoriasta ja säteilyhydrodynamiikasta. Johdannon sisältämän materiaalin avulla väitöskirjan julkaisut, ja niiden esittämät tulokset, ovat hyvin ymmärrettävissä. Väitöskirjan julkaisuista ensimmäinen esittelee uusia OJ287-systeemistä saatuja havaintopisteitä, jotka on paikallistettu Harvardin yliopiston observatorion arkiston valokuvauslevyiltä. OJ287:n vuonna 1900 tapahtunut purkaus nähdään ensimmäistä kertaa näissä havaintopisteissä. Uudet havaintopisteet mahdollistivat myös vuoden 1913 purkauksen alun ajoittamisen tarkemmin kuin aiemmin oli mahdollista. Havaitut purkaukset mallinnettiin onnistuneesti simuloimalla OJ287-järjestelmän mustien aukkojen paria ja kertymäkiekkoa. Julkaisussa II käsitellään mekanismeja OJ287:n sekundäärisen mustan aukon spinin kasvamiseen vuorovaikutuksessa primäärin kertymäkiekon ja systeemin magneettikenttien kanssa. Julkaisussa arvioidaan maksimispinin saavuttamisen ja spinin suunnan vakiintumisen aikaskaalat kummallakin mekanismilla. Tutkimuksessa havaitaan sekundäärin spinin olevan todennäköisesti suuri. Julkaisu III esittelee OJ287-systeemissä maaliskuussa 2013 tapahtuneen purkauksen. Purkauksen havaittiin muistuttavan vuosina 1993 ja 2004 tapahtuneita purkauksia, joita kutsutaan yhteisnimityksellä prekursoripurkaus (precursor outburst). Julkaisussa esitellään purkauksen synnylle mekanismi, jossa OJ287-systeemin sekundäärinen musta aukko osuu primäärisen mustan aukon kertymäkiekon koronassa olevaan kaasupilveen. Mekanismin avulla johdetaan arviot prekursoripurkausten kirkkaudelle ja aikaskaalalle. Julkaisussa johdetaan myös ennuste seuraavan prekursoripurkauksen ajankohdalle. Julkaisussa IV käytetään vuosina 2004–2006 kerättyjä havaintoja OJ287- systeemistä lyhyiden jaksollisuuksien etsintään. Julkaisussa varmennetaan systeemissä esiintyvä n. 50 päivän kvasiperiodisuus. Lisäksi tilastollisesti merkittävät 250 päivän ja 3,5 päivän jaksollisuudet havaitaan. Julkaisussa esitetään malli, jossa primäärisen mustan aukon kertymäkiekossa oleva spiraalitiheysaalto aiheuttaa 50 päivän jaksollisuuden. Mallista tehty numeerinen simulaatio tukee tulosta. Systeemin relativistisen suihkun emittoima aikadilatoitunut säteily esitetään aiheuttajaksi 3,5 päivän jaksollisuusaikaskaalalle. Julkaisussa V sovitetaan kierresuihkumalli OJ287-systeemistä tehtyihin optisiin havaintoihin ja millimetri- sekä senttimetriaallonpituuden radiohavaintoihin. Suihkun rakenteen havaitaan olevan kaksijakoinen ja koostuvan ytimestä ja kuoresta. Suihkun kuorella on merkittävästi pienempi Lorentzin gamma-tekijä kuin suihkun ytimellä. Kuoren avautumiskulma ja Lorentztekijä sekä suihkun kierteen aallonpituus raportoidaan julkaisussa ensimmäistä kertaa.

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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.

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Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented

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In this paper, we propose several finite-sample specification tests for multivariate linear regressions (MLR) with applications to asset pricing models. We focus on departures from the assumption of i.i.d. errors assumption, at univariate and multivariate levels, with Gaussian and non-Gaussian (including Student t) errors. The univariate tests studied extend existing exact procedures by allowing for unspecified parameters in the error distributions (e.g., the degrees of freedom in the case of the Student t distribution). The multivariate tests are based on properly standardized multivariate residuals to ensure invariance to MLR coefficients and error covariances. We consider tests for serial correlation, tests for multivariate GARCH and sign-type tests against general dependencies and asymmetries. The procedures proposed provide exact versions of those applied in Shanken (1990) which consist in combining univariate specification tests. Specifically, we combine tests across equations using the MC test procedure to avoid Bonferroni-type bounds. Since non-Gaussian based tests are not pivotal, we apply the “maximized MC” (MMC) test method [Dufour (2002)], where the MC p-value for the tested hypothesis (which depends on nuisance parameters) is maximized (with respect to these nuisance parameters) to control the test’s significance level. The tests proposed are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995. Our empirical results reveal the following. Whereas univariate exact tests indicate significant serial correlation, asymmetries and GARCH in some equations, such effects are much less prevalent once error cross-equation covariances are accounted for. In addition, significant departures from the i.i.d. hypothesis are less evident once we allow for non-Gaussian errors.