Introduction à la visualisation de données: l'analyse de réseau en histoire

The use of data visualization in history leads to contradictory reactions: some are fascinated by its heuristic potential and forget their critical faculties while others reject this practice, suspecting it of hiding explanatory weaknesses. This paper proposes a distinction between demonstration visualization and research visualization, reminding that scholars should not only use data visualization for communication purposes, but also for the research itself. It is particularly in its more complex form that this research visualization category will be approached here: network analysis.

Will climate change increase the risk of plant invasions into mountains?

Mountain ecosystems have been less adversely affected by invasions of non-native plants than most other ecosystems, partially because most invasive plants in the lowlands are limited by climate and cannot grow under harsher high-elevation conditions. However, with ongoing climate change, invasive species may rapidly move upwards and threaten mid- then high-elevation mountain ecosystems. We evaluated this threat by predicting current and future potential distributions of 48 invasive plant species distributed in Switzerland (CH) and New South Wales (NSW), two areas where climate interacts differently with the elevation gradient. Using a species distribution modeling approach combining two scales, which builds on high-resolution data (< 250 m) but accounts for the global climatic niche of species, we found that different environmental drivers limit the elevation range of invasive species in the two regions, leading to region-specific species responses to climate change. Whereas the optimal suitability for plant invaders is predicted to markedly shift from the lowland to the montane or subalpine zone in CH, such an upward shift is far less pronounced in NSW where montane and subalpine elevations are currently already suitable. Non-native species able to invade the upper reaches of mountains in a future climate will be cold-tolerant in the Swiss Alps but preferring wet soils in the Australian Alps. Other plant traits were only marginally associated with elevation limits. These results demonstrate that a more systematic consideration of future distributions of invasive species is required in conservation plans of not yet invaded mountainous ecosystems.

Computing the diameter of Coxeter groups

This thesis addresses the problem of computing the minimal and maximal diameter of the Cayley graph of Coxeter groups. We first present and assert relevant parts of polytope theory and related Coxeter theory. After this, a method of contracting the orthogonal projections of a polytope from Rd onto R2 and R3, d ¸ 3 is presented. This method is the Equality Set Projection algorithm that requires a constant number of linearprogramming problems per facet of the projection in the absence of degeneracy. The ESP algorithm allows us to compute also projected geometric diameters of high-dimensional polytopes. A representation set of projected polytopes is presented to illustrate the methods adopted in this thesis.

Eddy-current losses in rotor surface mounted permanent magnets

The aim of the work is to study the existing analytical calculation procedures found in literature to calculate the eddy-current losses in surface mounted permanent magnets within PMSM application. The most promising algorithms are implemented with MATLAB software under the dimensional data of LUT prototype machine. In addition finite elements analyze, utilized with help of Flux 2D software from Cedrat Ltd, is applied to calculate the eddy-current losses in permanent magnets. The results obtained from analytical methods are compared with numerical results.

Alueverkkojen yhteisöllisyyden edistäminen, vaihtoehtojen arviointi ja yhteisöverkkoportaalin toteutus

Internetin yhteisöpalvelut ovat saavuttaneet suuren suosion. Ne mahdollistavat digitaalisten yhteisöjen ja yhteisöllisyyden tunteiden aikaansaamisen käyttäjien välille. Kehittyneet verkkoyhteydet ja sisältötekniikat ovat antaneet mahdollisuuden monipuolisten vuorovaikutustyökalujen toteuttamiseksi. Sähköinen yhteisöllisyys on nouseva trendi, joka tukee arkipäivästä todellisuutta. Verkkojen paikallinen kehitys, niin laajakaistan kuin erilaisten alueverkkojen avulla on nostanut ajatuksia luoda myös paikallista yhteisöllisyyttä globaalien yhteisöpalvelujen rinnalle. Nopeiden alueverkkojen laajentuminen ovat tuoneet edistyneet verkkoyhteydet niin lähiöihin kuin taajamienkin ulkopuolelle. Avointen alueverkkojen mallissa verkko ja palvelukerros ovat eriytetty toisistaan. Ulkopuoliset palveluntarjoajat voivat tarjota palveluitaan suoraan alueverkon käyttäjille lähempänä verkkotasoa, verrattuna perinteiseen yhden verkkooperaattorin malliin. Tämä mahdollistaa uusien innovatiivisempien palveluiden kehittelyn. Tässä diplomityössä tutkittiin mahdollisuuksia joilla voidaan edistää yhteisöllisyyttä paikallisissa alueverkoissa ja hyödyntää niiden paikallista suorituskykyä, sekä resursseja palveluiden toteutuksessa. Työssä selvitettiin ensin mistä käsitteet yhteisö ja yhteisöllisyys ovat muodostuneet. Selvityksen pohjalta tutkittiin mitä teknisiä menetelmiä on yhteisöjen ja yhteisöllisyyden tunteen aikaansaamiseksi olemassa. Selvityksen tuloksena syntyi teknologinen tiekartta tietoverkkoyhteisöllisyyteen, sekä sosiaalisten palvelualustojen luokittelukaavio, joiden tarkoitus on yhdessä kuvastaa yhteisöllisyyttä tukevia palvelumahdollisuuksia. Työn viimeisessä vaiheessa toteutettiin yhteisöllinen alueverkkopalvelu, sekä yhteisövalvontajärjestelmä – lisäarvopalvelukonsepti, jotka pyrkivät hyödyntämään paikallisen alueverkon tarjoamaa suorituskykyä ja resursseja.

Chaos in a Two-Degree of Freedom Duffing Oscillator

High dimensional dynamical systems has intricate behavior either on temporal or on spatial evolution properties. Nevertheless, most of the work on chaotic dynamics has been concentrated on temporal behavior of low-dimensional systems. This contribution is concerned with the chaotic response of a two-degree of freedom Duffing oscillator. Since the equations of motion are associated with a five-dimensional system, the analysis is performed by considering two Duffing oscillators, both with single-degree of freedom, coupled by a spring-dashpot system. With this assumption, it is possible to analyze the transmissibility of motion between the two oscillators.

ZENODO - an open dependable home for the long-tail of science

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

Mittausdatan havainnollistaminen MATLAB animaationa

The visualization of measurement data is important in the fields of engineering for research analysis and presentation purposes. A suitable visualization method for scientific visualization is needed when handling measurement data. Visualization methods and techniques will be presented throughout this work. They are the bases of scientific visualization from the abstract visualization process to the applied techniques suited for each situation. This work also proposes a visualization tool using the MATLAB® software. The tool was designed as general as possible to encompass the most needs in terms of measurement data visualization. It offers possibilities for both static and dynamic visualization of the data.

Irtisanomisilmoitusten vaikutukset suomalaisten suuryritysten markkina-arvoihin

The objective of the thesis is to examine the market reaction of Finnish large-cap stocks to layoff announcements, using the event study methodology to gain insight in to whether the reaction is positive or negative, and whether it has changed over the years since the last studies were conducted. Another aim is also to examine whether the market reaction has changed during the times of the financial crisis, when the number of layoffs in Finland has been unusually high. The data consists of 128 publicly announced layoff announcements during the eight years from January 2006 to January 2014. The average market reaction to layoff announcements during different time periods within the overall sample was studied based on abnormal returns indicated by the event study methodology. The earlier research suggest that the overall market reaction to layoff announcements is negative. An overwhelming majority of these studies were conducted in the 1990s based on 80’s data. The market reaction found in this study was slightly positive, although the result was not statistically significant. The market reaction has decreased during the years of the financial crisis, but this result too, is not statistically significant.

Far infrared reflectance and optical properties of organic superconductor (TMTSF)2ClO4 /

Polarized reflectance measurements of the quasi I-D charge-transfer salt (TMTSFh CI04 were carried out using a Martin-Puplett-type polarizing interferometer and a 3He refrigerator cryostat, at several temperatures between 0.45 K and 26 K, in the far infrared, in the 10 to 70 cm- 1 frequency range. Bis-tetramethyl-tetraselena-fulvalene perchlorate crystals, grown electrochemically and supplied by K. Behnia, of dimensions 2 to 4 by 0.4 by 0.2 mm, were assembled on a flat surface to form a mosaic of 1.5 by 3 mm. The needle shaped crystals were positioned parallel to each other along their long axis, which is the stacking direction of the planar TMTSF cations, exposing the ab plane face (parallel to which the sheets of CI04 anions are positioned). Reflectance measurements were performed with radiation polarized along the stacking direction in the sample. Measurements were carried out following either a fast (15-20 K per minute) or slow (0.1 K per minute) cooling of the sample. Slow cooling permits the anions to order near 24 K, and the sample is expected to be superconducting below 1.2 K, while fast cooling yields an insulating state at low temperatures. Upon the slow cooling the reflectance shows dependence with temperature and exhibits the 28 cm- 1 feature reported previously [1]. Thermoreflectance for both the 'slow' and 'fast' cooling of the sample calculated relative to the 26 K reflectance data indicates that the reflectance is temperature dependent, for the slow cooling case only. A low frequency edge in the absolute reflectance is assigned an electronic origin given its strong temperature dependence in the relaxed state. We attribute the peak in the absolute reflectance near 30 cm-1 to a phonon coupled to the electronic background. Both the low frequency edge and the 30 cm-1 feature are noted te shift towards higher frequcncy, upon cntering the superconducting state, by an amount of the order of the expected superconducting energy gap. Kramers-Kronig analysis was carried out to determine the optical conductivity for the slowly cooled sample from the measured reflectance. In order to do so the low frequency data was extrapolated to zero frequency using a Hagen-Ru bens behaviour, and the high frequency data was extended with the data of Cao et al. [2], and Kikuchi et al. [3]. The real part of the optical conductivity exhibits an asymmetric peak at 35 cm-1, and its background at lower frequencies seems to be losing spectral weight with lowering of the temperature, leading us to presume that a narrow peak is forming at even lower frequencies.

Generating Aesthetically Pleasing Images in a Virtual Environment using Particle Swarm Optimization

This research focuses on generating aesthetically pleasing images in virtual environments using the particle swarm optimization (PSO) algorithm. The PSO is a stochastic population based search algorithm that is inspired by the flocking behavior of birds. In this research, we implement swarms of cameras flying through a virtual world in search of an image that is aesthetically pleasing. Virtual world exploration using particle swarm optimization is considered to be a new research area and is of interest to both the scientific and artistic communities. Aesthetic rules such as rule of thirds, subject matter, colour similarity and horizon line are all analyzed together as a multi-objective problem to analyze and solve with rendered images. A new multi-objective PSO algorithm, the sum of ranks PSO, is introduced. It is empirically compared to other single-objective and multi-objective swarm algorithms. An advantage of the sum of ranks PSO is that it is useful for solving high-dimensional problems within the context of this research. Throughout many experiments, we show that our approach is capable of automatically producing images satisfying a variety of supplied aesthetic criteria.

Macroeconomic News and Exchange Rates: Evidence of Unstable Effect

Although the link between macroeconomic news announcements and exchange rates is well documented in recent literature, this connection may be unstable. By using a broad set of macroeconomic news announcements and high frequency forex data for the Euro/Dollar, Pound/Dollar and Yen/Dollar from Nov 1, 2004 to Mar 31, 2014, we obtain two major findings with regards to this instability. First, many macroeconomic news announcements exhibit unstable effects with certain patterns in foreign exchange rates. These news effects may change in magnitude and even in their sign over time, over business cycles and crises within distinctive contexts. This finding is robust because the results are obtained by applying a Two-Regime Smooth Transition Regression Model, a Breakpoints Regression Model, and an Efficient Test of Parameter Instability which are all consistent with each other. Second, when we explore the source of this instability, we find that global risks and the reaction by central bank monetary policy to these risks to be possible factors causing this instability.

Macroeconomic News Effects and Foreign Exchange Jumps

This thesis investigates how macroeconomic news announcements affect jumps and cojumps in foreign exchange markets, especially under different business cycles. We use 5-min interval from high frequency data on Euro/Dollar, Pound/Dollar and Yen/Dollar from Nov. 1, 2004 to Feb. 28, 2015. The jump detection method was proposed by Andersen et al. (2007c), Lee & Mykland (2008) and then modified by Boudt et al. (2011a) for robustness. Then we apply the two-regime smooth transition regression model of Teräsvirta (1994) to explore news effects under different business cycles. We find that scheduled news related to employment, real activity, forward expectations, monetary policy, current account, price and consumption influences forex jumps, but only FOMC Rate Decisions has consistent effects on cojumps. Speeches given by major central bank officials near a crisis also significantly affect jumps and cojumps. However, the impacts of some macroeconomic news are not the same under different economic states.