Fiber flows in global paper and pulp industry. A panel data approach.

The purpose of this thesis is to study factors that explain the bilateral fiber trade flows. This is done by analyzing bilateral trade flows during 1990-2006. It will be studied also, whether there are differences between fiber types. This thesis uses a gravity model approach to study the trade flows. Gravity model is mostly used to study the aggregate data between trading countries. In this thesis the gravity model is applied to single fibers. This model is then applied to panel data set. Results from the regression show clearly that there are benefits in studying different fibers in separate. The effects differ considerably from each other. Furthermore, this thesis speaks for the existence of Linder’s effect in certain fiber types.

Customer driven business model – connecting customer value to firm resources in ICT value networks

The objective of this thesis is to provide a business model framework that connects customer value to firm resources and explains the change logic of the business model. Strategic supply management and especially dynamic value network management as its scope, the dissertation is based on basic economic theories, transaction cost economics and the resource-based view. The main research question is how the changing customer values should be taken into account when planning business in a networked environment. The main question is divided into questions that form the basic research problems for the separate case studies presented in the five Publications. This research adopts the case study strategy, and the constructive research approach within it. The material consists of data from several Delphi panels and expert workshops, software pilot documents, company financial statements and information on investor relations on the companies’ web sites. The cases used in this study are a mobile multi-player game value network, smart phone and “Skype mobile” services, the business models of AOL, eBay, Google, Amazon and a telecom operator, a virtual city portal business system and a multi-play offering. The main contribution of this dissertation is bridging the gap between firm resources and customer value. This has been done by theorizing the business model concept and connecting it to both the resource-based view and customer value. This thesis contributes to the resource-based view, which deals with customer value and firm resources needed to deliver the value but has a gap in explaining how the customer value changes should be connected to the changes in key resources. This dissertation also provides tools and processes for analyzing the customer value preferences of ICT services, constructing and analyzing business models and business concept innovation and conducting resource analysis.

Parallel declines in species and genetic diversity driven by anthropogenic disturbance: a multispecies approach in a French Atlantic dune system.

Numerous studies assess the correlation between genetic and species diversities, but the processes underlying the observed patterns have only received limited attention. For instance, varying levels of habitat disturbance across a region may locally reduce both diversities due to extinctions, and increased genetic drift during population bottlenecks and founder events. We investigated the regional distribution of genetic and species diversities of a coastal sand dune plant community along 240 kilometers of coastline with the aim to test for a correlation between the two diversity levels. We further quantify and tease apart the respective contributions of natural and anthropogenic disturbance factors to the observed patterns. We detected significant positive correlation between both variables. We further revealed a negative impact of urbanization: Sites with a high amount of recreational infrastructure within 10 km coastline had significantly lowered genetic and species diversities. On the other hand, a measure of natural habitat disturbance had no effect. This study shows that parallel variation of genetic and species diversities across a region can be traced back to human landscape alteration, provides arguments for a more resolute dune protection, and may help to design priority conservation areas.

General Equilibrium Long-Run Determinants for Spanish FDI: A Spatial Panel Data Approach

While general equilibrium theories of trade stress the role of third-country effects, little work has been done in the empirical foreign direct investment (FDI) literature to test such spatial linkages. This paper aims to provide further insights into long-run determinants of Spanish FDI by considering not only bilateral but also spatially weighted third-country determinants. The few studies carried out so far have focused on FDI flows in a limited number of countries. However, Spanish FDI outflows have risen dramatically since 1995 and today account for a substantial part of global FDI. Therefore, we estimate recently developed Spatial Panel Data models by Maximum Likelihood (ML) procedures for Spanish outflows (1993-2004) to top-50 host countries. After controlling for unobservable effects, we find that spatial interdependence matters and provide evidence consistent with New Economic Geography (NEG) theories of agglomeration, mainly due to complex (vertical) FDI motivations. Spatial Error Models estimations also provide illuminating results regarding the transmission mechanism of shocks.

Open Access Research Data Repository for Corpus Linguistic Data – A Modular Approach

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

A Bayesian Approach for Forecasting Heat Load in a District Heating System

The growing population in cities increases the energy demand and affects the environment by increasing carbon emissions. Information and communications technology solutions which enable energy optimization are needed to address this growing energy demand in cities and to reduce carbon emissions. District heating systems optimize the energy production by reusing waste energy with combined heat and power plants. Forecasting the heat load demand in residential buildings assists in optimizing energy production and consumption in a district heating system. However, the presence of a large number of factors such as weather forecast, district heating operational parameters and user behavioural parameters, make heat load forecasting a challenging task. This thesis proposes a probabilistic machine learning model using a Naive Bayes classifier, to forecast the hourly heat load demand for three residential buildings in the city of Skellefteå, Sweden over a period of winter and spring seasons. The district heating data collected from the sensors equipped at the residential buildings in Skellefteå, is utilized to build the Bayesian network to forecast the heat load demand for horizons of 1, 2, 3, 6 and 24 hours. The proposed model is validated by using four cases to study the influence of various parameters on the heat load forecast by carrying out trace driven analysis in Weka and GeNIe. Results show that current heat load consumption and outdoor temperature forecast are the two parameters with most influence on the heat load forecast. The proposed model achieves average accuracies of 81.23 % and 76.74 % for a forecast horizon of 1 hour in the three buildings for winter and spring seasons respectively. The model also achieves an average accuracy of 77.97 % for three buildings across both seasons for the forecast horizon of 1 hour by utilizing only 10 % of the training data. The results indicate that even a simple model like Naive Bayes classifier can forecast the heat load demand by utilizing less training data.

Implementing Green IT approach for transferring Big Data over Parallel Data Link

The whole research of the current Master Thesis project is related to Big Data transfer over Parallel Data Link and my main objective is to assist the Saint-Petersburg National Research University ITMO research team to accomplish this project and apply Green IT methods for the data transfer system. The goal of the team is to transfer Big Data by using parallel data links with SDN Openflow approach. My task as a team member was to compare existing data transfer applications in case to verify which results the highest data transfer speed in which occasions and explain the reasons. In the context of this thesis work a comparison between 5 different utilities was done, which including Fast Data Transfer (FDT), BBCP, BBFTP, GridFTP, and FTS3. A number of scripts where developed which consist of creating random binary data to be incompressible to have fair comparison between utilities, execute the Utilities with specified parameters, create log files, results, system parameters, and plot graphs to compare the results. Transferring such an enormous variety of data can take a long time, and hence, the necessity appears to reduce the energy consumption to make them greener. In the context of Green IT approach, our team used Cloud Computing infrastructure called OpenStack. It’s more efficient to allocated specific amount of hardware resources to test different scenarios rather than using the whole resources from our testbed. Testing our implementation with OpenStack infrastructure results that the virtual channel does not consist of any traffic and we can achieve the highest possible throughput. After receiving the final results we are in place to identify which utilities produce faster data transfer in different scenarios with specific TCP parameters and we can use them in real network data links.

A virtual reality approach to the study of visually driven postural control in developing and aging humans

L'être humain utilise trois systèmes sensoriels distincts pour réguler le maintien de la station debout: la somesthésie, le système vestibulaire, et le système visuel. Le rôle de la vision dans la régulation posturale demeure peu connu, notamment sa variabilité en fonction de l'âge, du type développemental, et des atteintes neurologiques. Dans notre travail, la régulation posturale induite visuellement a été évaluée chez des participants au développement et vieillissement normaux âgés de 5-85 ans, chez des individus autistes (développement atypique) âgés de 12-33 ans, ainsi que chez des enfants entre 9-18 ans ayant subi un TCC léger. À cet effet, la réactivité posturale des participants en réponse à un tunnel virtuel entièrement immersif, se mouvant à trois niveaux de vélocité, a été mesurée; des conditions contrôles, où le tunnel était statique ou absent, ont été incluses. Les résultats montrent que la réactivité (i.e. instabilité) posturale induite visuellement est plus élevée chez les jeunes enfants; ensuite, elle s'atténue pour rejoindre des valeurs adultes vers 16-19 ans et augmente de façon linéaire en fonction de l'âge après 45 ans jusqu'à redevenir élevée vers 60 ans. De plus, à la plus haute vélocité du tunnel, les plus jeunes participants autistes ont manifesté significativement moins de réactivité posturale comparativement à leurs contrôles; cette différence n'était pas présente chez des participants plus âgés (16-33 ans). Enfin, les enfants ayant subi un TCC léger, et qui étaient initialement modérément symptomatiques, ont montré un niveau plus élevé d'instabilité posturale induite visuellement que les contrôles, et ce jusqu'à 12 semaines post-trauma malgré le fait que la majorité d'entre eux (89%) n'étaient plus symptomatiques à ce stade. En somme, cela suggère la présence d'une importante période de transition dans la maturation des systèmes sous-tendant l'intégration sensorimotrice impliquée dans le contrôle postural vers l'âge de 16 ans, et d'autres changements sensorimoteurs vers l'âge de 60 ans; cette sur-dépendance visuelle pour la régulation posturale chez les enfants et les aînés pourrait guider l'aménagement d'espaces et l'élaboration d'activités ajustés à l'âge des individus. De plus, le fait que l'hypo-réactivité posturale aux informations visuelles chez les autistes dépende des caractéristiques de l'environnement visuel et de l'âge chronologique, affine notre compréhension des anomalies sensorielles propres à l'autisme. Par ailleurs, le fait que les enfants ayant subi un TCC léger montrent des anomalies posturales jusqu'à 3 mois post-trauma, malgré une diminution significative des symptômes rapportés, pourrait être relié à une altération du traitement de l'information visuelle dynamique et pourrait avoir des implications quant à la gestion clinique des patients aux prises avec un TCC léger, puisque la résolution des symptômes est actuellement le principal critère utilisé pour la prise de décision quant au retour aux activités. Enfin, les résultats obtenus chez une population à développement atypique (autisme) et une population avec atteinte neurologique dite transitoire (TCC léger), contribuent non seulement à une meilleure compréhension des mécanismes d'intégration sensorimotrice sous-tendant le contrôle postural mais pourraient aussi servir comme marqueurs sensibles et spécifiques de dysfonction chez ces populations. Mots-clés : posture, équilibre, vision, développement/vieillissement sensorimoteur, autisme, TCC léger symptomatique, réalité virtuelle.

Genetic Programming meets Model-Driven Development

Genetic programming is known to provide good solutions for many problems like the evolution of network protocols and distributed algorithms. In such cases it is most likely a hardwired module of a design framework that assists the engineer to optimize specific aspects of the system to be developed. It provides its results in a fixed format through an internal interface. In this paper we show how the utility of genetic programming can be increased remarkably by isolating it as a component and integrating it into the model-driven software development process. Our genetic programming framework produces XMI-encoded UML models that can easily be loaded into widely available modeling tools which in turn posses code generation as well as additional analysis and test capabilities. We use the evolution of a distributed election algorithm as an example to illustrate how genetic programming can be combined with model-driven development. This example clearly illustrates the advantages of our approach – the generation of source code in different programming languages.

A compositional approach to stable isotope data analysis

Isotopic data are currently becoming an important source of information regarding sources, evolution and mixing processes of water in hydrogeologic systems. However, it is not clear how to treat with statistics the geochemical data and the isotopic data together. We propose to introduce the isotopic information as new parts, and apply compositional data analysis with the resulting increased composition. Results are equivalent to downscale the classical isotopic delta variables, because they are already relative (as needed in the compositional framework) and isotopic variations are almost always very small. This methodology is illustrated and tested with the study of the Llobregat River Basin (Barcelona, NE Spain), where it is shown that, though very small, isotopic variations comp lement geochemical principal components, and help in the better identification of pollution sources

Option pricing in market models driven by telegraph processes with jumps

Esta tesis está dividida en dos partes: en la primera parte se presentan y estudian los procesos telegráficos, los procesos de Poisson con compensador telegráfico y los procesos telegráficos con saltos. El estudio presentado en esta primera parte incluye el cálculo de las distribuciones de cada proceso, las medias y varianzas, así como las funciones generadoras de momentos entre otras propiedades. Utilizando estas propiedades en la segunda parte se estudian los modelos de valoración de opciones basados en procesos telegráficos con saltos. En esta parte se da una descripción de cómo calcular las medidas neutrales al riesgo, se encuentra la condición de no arbitraje en este tipo de modelos y por último se calcula el precio de las opciones Europeas de compra y venta.