Viewpoint-Based Ambient Occlusion

We've developed a new ambient occlusion technique based on an information-theoretic framework. Essentially, our method computes a weighted visibility from each object polygon to all viewpoints; we then use these visibility values to obtain the information associated with each polygon. So, just as a viewpoint has information about the model's polygons, the polygons gather information on the viewpoints. We therefore have two measures associated with an information channel defined by the set of viewpoints as input and the object's polygons as output, or vice versa. From this polygonal information, we obtain an occlusion map that serves as a classic ambient occlusion technique. Our approach also offers additional applications, including an importance-based viewpoint-selection guide, and a means of enhancing object features and producing nonphotorealistic object visualizations

Point sampling with uniformly distributed lines

In this paper we address the problem of extracting representative point samples from polygonal models. The goal of such a sampling algorithm is to find points that are evenly distributed. We propose star-discrepancy as a measure for sampling quality and propose new sampling methods based on global line distributions. We investigate several line generation algorithms including an efficient hardware-based sampling method. Our method contributes to the area of point-based graphics by extracting points that are more evenly distributed than by sampling with current algorithms

Evapotranspiration and crop coefficients of melon plants measured by lysimeter and estimated according to FAO 56 methodology

Aiming at contributing to an adequate management of water resources, this study aimed to analyze and compare evapotranspiration (ETc) and crop coefficients (Kc) of melon plants measured by a lysimeter and estimated according to the FAO 56 methodology, in the city of Mossoró, state of Rio Grande do Norte (RN), Brazil. In order to measure ETc, weighing lysimeters with an area of 2.25m² were used, with two repetitions. The Penman-Monteith equation parameterized by FAO was used to estimate the reference evapotranspiration, and crop coefficients were those recommended in FAO-56 Bulletin adjusted to local climatic conditions. The required climatic data and lysimeter measurements were collected by an automatic weather station installed at the site. The results were compared by means of statistical indicators: of precision (r), of accuracy (d), and performance (c), in daily and weekly intervals. The data estimated by the FAO 56 methodology were adjusted optimally to the values measured by the lysimeters in accordance with index "c" in the two time scales assessed, indicating the potential of the method proposed by FAO to irrigation management in the climatic conditions of Agripole Assú-Mossoró.

Qualitative Characteristics and Quantitative Measures of Solution's Reliability in Discrete Optimization: Traditional Analytical Approaches, Innovative Computational Methods and Applicability

The purpose of this thesis is twofold. The first and major part is devoted to sensitivity analysis of various discrete optimization problems while the second part addresses methods applied for calculating measures of solution stability and solving multicriteria discrete optimization problems. Despite numerous approaches to stability analysis of discrete optimization problems two major directions can be single out: quantitative and qualitative. Qualitative sensitivity analysis is conducted for multicriteria discrete optimization problems with minisum, minimax and minimin partial criteria. The main results obtained here are necessary and sufficient conditions for different stability types of optimal solutions (or a set of optimal solutions) of the considered problems. Within the framework of quantitative direction various measures of solution stability are investigated. A formula for a quantitative characteristic called stability radius is obtained for the generalized equilibrium situation invariant to changes of game parameters in the case of the H¨older metric. Quality of the problem solution can also be described in terms of robustness analysis. In this work the concepts of accuracy and robustness tolerances are presented for a strategic game with a finite number of players where initial coefficients (costs) of linear payoff functions are subject to perturbations. Investigation of stability radius also aims to devise methods for its calculation. A new metaheuristic approach is derived for calculation of stability radius of an optimal solution to the shortest path problem. The main advantage of the developed method is that it can be potentially applicable for calculating stability radii of NP-hard problems. The last chapter of the thesis focuses on deriving innovative methods based on interactive optimization approach for solving multicriteria combinatorial optimization problems. The key idea of the proposed approach is to utilize a parameterized achievement scalarizing function for solution calculation and to direct interactive procedure by changing weighting coefficients of this function. In order to illustrate the introduced ideas a decision making process is simulated for three objective median location problem. The concepts, models, and ideas collected and analyzed in this thesis create a good and relevant grounds for developing more complicated and integrated models of postoptimal analysis and solving the most computationally challenging problems related to it.

On state and parameter estimation in chaotic systems

State-of-the-art predictions of atmospheric states rely on large-scale numerical models of chaotic systems. This dissertation studies numerical methods for state and parameter estimation in such systems. The motivation comes from weather and climate models and a methodological perspective is adopted. The dissertation comprises three sections: state estimation, parameter estimation and chemical data assimilation with real atmospheric satellite data. In the state estimation part of this dissertation, a new filtering technique based on a combination of ensemble and variational Kalman filtering approaches, is presented, experimented and discussed. This new filter is developed for large-scale Kalman filtering applications. In the parameter estimation part, three different techniques for parameter estimation in chaotic systems are considered. The methods are studied using the parameterized Lorenz 95 system, which is a benchmark model for data assimilation. In addition, a dilemma related to the uniqueness of weather and climate model closure parameters is discussed. In the data-oriented part of this dissertation, data from the Global Ozone Monitoring by Occultation of Stars (GOMOS) satellite instrument are considered and an alternative algorithm to retrieve atmospheric parameters from the measurements is presented. The validation study presents first global comparisons between two unique satellite-borne datasets of vertical profiles of nitrogen trioxide (NO3), retrieved using GOMOS and Stratospheric Aerosol and Gas Experiment III (SAGE III) satellite instruments. The GOMOS NO3 observations are also considered in a chemical state estimation study in order to retrieve stratospheric temperature profiles. The main result of this dissertation is the consideration of likelihood calculations via Kalman filtering outputs. The concept has previously been used together with stochastic differential equations and in time series analysis. In this work, the concept is applied to chaotic dynamical systems and used together with Markov chain Monte Carlo (MCMC) methods for statistical analysis. In particular, this methodology is advocated for use in numerical weather prediction (NWP) and climate model applications. In addition, the concept is shown to be useful in estimating the filter-specific parameters related, e.g., to model error covariance matrix parameters.

Hyperbolic Type Geometries in Subdomains

This Licentiate thesis deals with hyperbolic type geometries in planar subdomains. It is known that hyperbolic type distance is always greater in a subdomain than in the original domain. In this work we obtain certain lower estimates for hyperbolic type distances in subdomains in terms of hyperbolic type distances of the original domains. In particular the domains that we consider are cyclic polygons and their circumcircles, sectors and supercircles.

Insights into the role of hydration in protein structure and stability obtained through hydrostatic pressure studies

A thorough understanding of protein structure and stability requires that we elucidate the molecular basis for the effects of both temperature and pressure on protein conformational transitions. While temperature effects are relatively well understood and the change in heat capacity upon unfolding has been reasonably well parameterized, the state of understanding of pressure effects is much less advanced. Ultimately, a quantitative parameterization of the volume changes (at the basis of pressure effects) accompanying protein conformational transitions will be required. The present report introduces a qualitative hypothesis based on available model compound data for the molecular basis of volume change upon protein unfolding and its dependence on temperature.

Pituusleikkureiden 3D-suunnittelun kehittäminen

Tämä diplomityö tehtiin Valmet Technologies Oy:n Järvenpään toimipisteelle. Työn tavoitteena oli tutkia miten pituusleikkureiden 3D-suunnittelua voidaan tehostaa hyödyntämällä uuden 3D-CAD -järjestelmän ominaisuuksia optimaalisesti. Työ koostuu teoriaosuudesta, haastattelututkimuksesta sekä käytännön osuudesta. Teoriaosuudessa perehdytään pituusleikkurin toimintaan ja rakenteeseen, 3D-suunnittelun teoriaan sekä CATIA-järjestelmään. Teoriaosuudessa etsitään myös uusia näkökulmia 3D-suunnitteluun. Haastattelututkimuksessa kartoitetaan nykyinen suunnitteluprosessi, suunnittelun kehitettäviä kohteita, sekä käytössä olevia suunnittelumenetelmiä, jotka ovat todettu toimiviksi. Haastattelututkimuksessa haastatellaan Valmet Technologies Oy:n Järvenpään toimipisteessä työskenteleviä pituusleikkureiden pääsuunnittelijoita sekä heidän esimiehiään. Lisäksi erillisten haastattelujen avulla kerätään kokemuksia CATIA V6 -ohjelmiston käytöstä sekä suunnitteluohjelmiston vaihtumisesta. Käytännön osuuden tavoitteena on arvioida pituusleikkurin parametroitujen mallirakenteiden siirtämiseen sekä korjauksiin kuluvia aikamääriä kyseisiin toimenpiteisiin tarvittavien resurssien määrittämiseksi. Käytännön osuudessa siirretään kaksi Valmet OptiWin Drum Compact -pituusleikkurin parametroitua osakokonaisuutta uuteen CAD-järjestelmään ja niille suoritetaan tarvittavat korjaustoimenpiteet Tutkimuksen tulosten perusteella yhteisen mallinnusmetodologian puuttuminen on merkittävin kehityskohde suunnittelun kehittämisessä. Lopuksi luotiin kehitysehdotukset sekä implementointisuunnitelma, joiden avulla pituusleikkureiden 3D-suunnittelua voidaan kehittää ja CATIA V6 -ohjelmisto voidaan ottaa käyttöön tehokkaasti.

Efficient Algorithms for Coastal Geographic Problems

The increasing performance of computers has made it possible to solve algorithmically problems for which manual and possibly inaccurate methods have been previously used. Nevertheless, one must still pay attention to the performance of an algorithm if huge datasets are used or if the problem iscomputationally difficult. Two geographic problems are studied in the articles included in this thesis. In the first problem the goal is to determine distances from points, called study points, to shorelines in predefined directions. Together with other in-formation, mainly related to wind, these distances can be used to estimate wave exposure at different areas. In the second problem the input consists of a set of sites where water quality observations have been made and of the results of the measurements at the different sites. The goal is to select a subset of the observational sites in such a manner that water quality is still measured in a sufficient accuracy when monitoring at the other sites is stopped to reduce economic cost. Most of the thesis concentrates on the first problem, known as the fetch length problem. The main challenge is that the two-dimensional map is represented as a set of polygons with millions of vertices in total and the distances may also be computed for millions of study points in several directions. Efficient algorithms are developed for the problem, one of them approximate and the others exact except for rounding errors. The solutions also differ in that three of them are targeted for serial operation or for a small number of CPU cores whereas one, together with its further developments, is suitable also for parallel machines such as GPUs.

Middle Ordovician (Whiterockian-Chazyan) trilobites from the Sunblood Formation, District of Mackenzie

The Middle Ordovician Sunblood Formation in the South Nahanni River area, District of Mackenzie, comprises mainly limestones and dolostones of intertidal and shallow subtidal origin as indicated by the presence of desiccation polygons, fenestral fabric, and oncolites. The study of well preserved, silicified trilobites from low diversity, Bathyurus-dominated, Nearshore Biofacies faunas of Whiterockian and Chazyan age collected in six stratigraphic sections through the Sunblood Formation permits the recognition of three new Whiterockian zones, and two previously established Chazyan zones. The Bathyurus mackenziensis, Bathyurus sunbloodensis, and Bathyurus margareti zones (Whiterockian), together with the Bathyurus nevadensis and Bathyurus granu/osus zones (Chazyan) represent the Nearshore Biofacies components of a dual biostratigraphic scheme that considers both temporal and spatial distribution patterns, and are compositionally distinct from faunas in correlative strata around North America that represent other biofacies. Twenty-six species belonging to eighteen genera are described and illustrated. Ludvigsenella ellipsepyga is established as a new bathyurine genus, in addition to four new species of Bathyurus : Bathyurus mackenziensis, Bathyurus sunbloodensis, Bathyurus margareti and Bathyurus acanthopyga. Other genera present are: Basilicus, Isote/us, ///aenus, Bumastoides, Fail/eana, Phorocepha/a,Ceraurinella, Acanthoparypha, Xystocrania, Cydonocephalus, Ectenonotus, Pseudomera, Encrinuroides, Calyptaulax, Amphilichas and Hemiarges.

Square Root Finding In Graphs

Abstract: Root and root finding are concepts familiar to most branches of mathematics. In graph theory, H is a square root of G and G is the square of H if two vertices x,y have an edge in G if and only if x,y are of distance at most two in H. Graph square is a basic operation with a number of results about its properties in the literature. We study the characterization and recognition problems of graph powers. There are algorithmic and computational approaches to answer the decision problem of whether a given graph is a certain power of any graph. There are polynomial time algorithms to solve this problem for square of graphs with girth at least six while the NP-completeness is proven for square of graphs with girth at most four. The girth-parameterized problem of root fining has been open in the case of square of graphs with girth five. We settle the conjecture that recognition of square of graphs with girth 5 is NP-complete. This result is providing the complete dichotomy theorem for square root finding problem.

Explaining the Transition Between Exchange Rate Regimes

This paper studies the transition between exchange rate regimes using a Markov chain model with time-varying transition probabilities. The probabilities are parameterized as nonlinear functions of variables suggested by the currency crisis and optimal currency area literature. Results using annual data indicate that inflation, and to a lesser extent, output growth and trade openness help explain the exchange rate regime transition dynamics.

MODELING HETEROTACHY IN PHYLOGENETICS

Il a été démontré que l’hétérotachie, variation du taux de substitutions au cours du temps et entre les sites, est un phénomène fréquent au sein de données réelles. Échouer à modéliser l’hétérotachie peut potentiellement causer des artéfacts phylogénétiques. Actuellement, plusieurs modèles traitent l’hétérotachie : le modèle à mélange des longueurs de branche (MLB) ainsi que diverses formes du modèle covarion. Dans ce projet, notre but est de trouver un modèle qui prenne efficacement en compte les signaux hétérotaches présents dans les données, et ainsi améliorer l’inférence phylogénétique. Pour parvenir à nos fins, deux études ont été réalisées. Dans la première, nous comparons le modèle MLB avec le modèle covarion et le modèle homogène grâce aux test AIC et BIC, ainsi que par validation croisée. A partir de nos résultats, nous pouvons conclure que le modèle MLB n’est pas nécessaire pour les sites dont les longueurs de branche diffèrent sur l’ensemble de l’arbre, car, dans les données réelles, le signaux hétérotaches qui interfèrent avec l’inférence phylogénétique sont généralement concentrés dans une zone limitée de l’arbre. Dans la seconde étude, nous relaxons l’hypothèse que le modèle covarion est homogène entre les sites, et développons un modèle à mélanges basé sur un processus de Dirichlet. Afin d’évaluer différents modèles hétérogènes, nous définissons plusieurs tests de non-conformité par échantillonnage postérieur prédictif pour étudier divers aspects de l’évolution moléculaire à partir de cartographies stochastiques. Ces tests montrent que le modèle à mélanges covarion utilisé avec une loi gamma est capable de refléter adéquatement les variations de substitutions tant à l’intérieur d’un site qu’entre les sites. Notre recherche permet de décrire de façon détaillée l’hétérotachie dans des données réelles et donne des pistes à suivre pour de futurs modèles hétérotaches. Les tests de non conformité par échantillonnage postérieur prédictif fournissent des outils de diagnostic pour évaluer les modèles en détails. De plus, nos deux études révèlent la non spécificité des modèles hétérogènes et, en conséquence, la présence d’interactions entre différents modèles hétérogènes. Nos études suggèrent fortement que les données contiennent différents caractères hétérogènes qui devraient être pris en compte simultanément dans les analyses phylogénétiques.

Asset Pricing in a Production Economy with Chew–Dekel Preferences

In this paper we provide a thorough characterization of the asset returns implied by a simple general equilibrium production economy with Chew–Dekel risk preferences and convex capital adjustment costs. When households display levels of disappointment aversion consistent with the experimental evidence, a version of the model parameterized to match the volatility of output and consumption growth generates unconditional expected asset returns and price of risk in line with the historical data. For the model with Epstein–Zin preferences to generate similar statistics, the relative risk aversion coefficient needs to be about 55, two orders of magnitude higher than the available estimates. We argue that this is not surprising, given the limited risk imposed on agents by a reasonably calibrated stochastic growth model.

Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.