Two-loop stability of a complex singlet extended Standard Model

Motivated by the dark matter and the baryon asymmetry problems, we analyze a complex singlet extension of the Standard Model with a Z(2) symmetry (which provides a dark matter candidate). After a detailed two-loop calculation of the renormalization group equations for the new scalar sector, we study the radiative stability of the model up to a high energy scale (with the constraint that the 126 GeV Higgs boson found at the LHC is in the spectrum) and find it requires the existence of a new scalar state mixing with the Higgs with a mass larger than 140 GeV. This bound is not very sensitive to the cutoff scale as long as the latter is larger than 10(10) GeV. We then include all experimental and observational constraints/measurements from collider data, from dark matter direct detection experiments, and from the Planck satellite and in addition force stability at least up to the grand unified theory scale, to find that the lower bound is raised to about 170 GeV, while the dark matter particle must be heavier than about 50 GeV.

An information model for lean, agile, resilient and green supply chain management

Dissertação para a obtenção de Grau de Mestre em Engenharia e Gestão Industrial

A framework for efficient model transformations

The reported productivity gains while using models and model transformations to develop entire systems, after almost a decade of experience applying model-driven approaches for system development, are already undeniable benefits of this approach. However, the slowness of higher-level, rule based model transformation languages hinders the applicability of this approach to industrial scales. Lower-level, and efficient, languages can be used but productivity and easy maintenance seize to exist. The abstraction penalty problem is not new, it also exists for high-level, object oriented languages but everyone is using them now. Why is not everyone using rule based model transformation languages then? In this thesis, we propose a framework, comprised of a language and its respective environment, designed to tackle the most performance critical operation of high-level model transformation languages: the pattern matching. This framework shows that it is possible to mitigate the performance penalty while still using high-level model transformation languages.

Conflict in cross-functional teams

The present study is a qualitative analysis of the tensions that occur in cross-functional teams (CFTs) and the way in which they can affect the teams' accomplishments. The research is focused on a single case, COHTTEC 2005, a program aimed at transforming new technologies into businesses that took place in Lisbon, Portugal, starting March 2005. In this program, participants were organized in cross-functional teams that included researchers and management students. Semi-structured interviews were made to a sample of 17 participants. These interviews were recorded and transcribed. A table was then elaborated based on the primary data provided by the subjects and these data were classified in different categories. A three-stage model of group dynamics is proposed. The major findings of this project point to the role of interpersonal relationships on group outcomes. More specifically, several patterns associated with team malfunction were uncovered, the clearest ones being autocratic decision-making and arrogant behavior from some team members, as well as escalation in relationship conflict. Implications from these results are discussed, both for future research and for practice.

Development of a methodology to incorporate risk and uncertainty in electricity power planning

Dissertação de mestrado em Engenharia Industrial

The use of classification and regression trees to predict the likelihood of seasonal influenza.

Background Individual signs and symptoms are of limited value for the diagnosis of influenza. Objective To develop a decision tree for the diagnosis of influenza based on a classification and regression tree (CART) analysis. Methods Data from two previous similar cohort studies were assembled into a single dataset. The data were randomly divided into a development set (70%) and a validation set (30%). We used CART analysis to develop three models that maximize the number of patients who do not require diagnostic testing prior to treatment decisions. The validation set was used to evaluate overfitting of the model to the training set. Results Model 1 has seven terminal nodes based on temperature, the onset of symptoms and the presence of chills, cough and myalgia. Model 2 was a simpler tree with only two splits based on temperature and the presence of chills. Model 3 was developed with temperature as a dichotomous variable (≥38°C) and had only two splits based on the presence of fever and myalgia. The area under the receiver operating characteristic curves (AUROCC) for the development and validation sets, respectively, were 0.82 and 0.80 for Model 1, 0.75 and 0.76 for Model 2 and 0.76 and 0.77 for Model 3. Model 2 classified 67% of patients in the validation group into a high- or low-risk group compared with only 38% for Model 1 and 54% for Model 3. Conclusions A simple decision tree (Model 2) classified two-thirds of patients as low or high risk and had an AUROCC of 0.76. After further validation in an independent population, this CART model could support clinical decision making regarding influenza, with low-risk patients requiring no further evaluation for influenza and high-risk patients being candidates for empiric symptomatic or drug therapy.

Optimization of the ink removal in deinking plant

Diplomityön tarkoituksena oli parantaa Stora Enso Sachsenin siistausprosessissa tuotetun uusiomassan vaaleuden kehitystä ja tutkia siihen vaikuttavia tekijöitä. Työn kirjallisessa osassa käsiteltiin uusiomassan kuidutusta ja vaahdotussiistausprosessia, sekä keräyspaperin ominaisuuksia ja käyttöä paperiteollisuuden raaka-aineena. Kokeellisessa osassa keskityttiin modifioidun natriumsilikaatin annostuksenoptimointiin ja vaikutuksiin laboratorio- ja prosessioloissa, sekä kesäefektin vaikutuksen tutkimiseen kuidutuksessa ja flotaation eri vaiheissa. Natriumsilikaatin laboratoriotutkimuksessa havaittiin, että korkein vaaleus suhteellisesti pienimmällä laboratorioflotaation häviöllä saavutettiin korkeimmalla tutkitulla natriumsilikaatin annostuksella, joka oli 1,1 %. Korkea natriumsilikaattiannostus yhdistettyinä korkeisiin vetyperoksidiannostukseen, 0,5 %, sekä korkeaan kokonaisalkaliteettiin, 0.33 %, johti korkeimpaan massan vaaleuteen ja pienimpiin häviöihin. Laboratoriotutkimuksen pohjalta modifioidulla natriumsilikaatilla suoritettiin koeajoja prosessissa. Noin 1 % natriumsilikaatin annostuksella havaittiin parempi pH:n bufferointikyky, pienempi kalsiumkarbonaatin määrä flotaation primäärivaiheissa, sekä lievästi parempi massan vaaleus verrattuna prosessissa aiemmin käytettyyn standardinatriumsilikaattiin. Kesäefektitutkimuksessa havaittiin, että kesäefektillä on suurin vaikutus esiflotaation primäärivaiheeseen, sillä primäärivaiheessa kuitujen osuus on huomattavasti suurempi kuin sekundäärivaiheissa. Esiflotaation primäärivaiheen uusiomassojen laboratorioflotaatioiden avulla saavutettujen maksimivaaleuksien ero kesän ja talven välillä oli noin 1,5 %ISO. Kesäefektin ei havaittu suuresti vaikuttavan flotaation sekundäärivaiheisiin.

Kehittämistarpeet investointihyödykkeitä valmistavassa kansainvälisessä konsernissa. Case: GWS Systems Oy

Tutkielman aiheena on case-yrityksen kansainvälisen liiketoiminnan kehittäminen. Tutkielmassa selvitetään, minkälaisiin toimenpiteisiin case-yrityksen olisi liiketoiminnallisin perustein lähitulevaisuudessa ryhdyttävä sen ulkomaisten myyntiyhtiöiden suhteen vientitoimintaa kehitettäessä. Tarkastelunäkökulma on strategialähtöinen. Johdon päätöksenteon tarpeisiin tähtäävä käsittely painottuu strategian ja laskentatoimen välisen ajankohtaisen vuorovaikutuksen käsittelyyn. Tutkimus on kvalitatiivinen tapaustutkimus. Tutkimusmenetelmä on käytetty osallistuvaa havainnointia sekä haastatteluja. Tutkimuksen tulosten mukaan case-yrityksen tulisi muuttaa vientitoimintamalliaan nykyisestä tytäryhtiömuotoisesta toimintamallista hallinnollisesti ja kustannusrakenteellisesti kevyempään suuntaan. Kannattavuuden parantamiseksi suositellaan lisäksi strategisen johdon laskentatoimen menetelmistä asiakaskannattavuusanalyysin käyttöönottoa myyntiyhtiöiden kannattavimpien asiakkuuksien tunnistamiseksi, jotta niukat resurssit voitaisiin kohdistaa niihin asiakkaisiin, jotka synnyttävät enemmän myyntiä ja parempia tuottoja.

Kannattavuuden simulointimallin rakentaminen: tapaustutkimus

Tämän tutkimuksen tavoitteena on rakentaa kannattavuuden simulointimalli, joka tukee Laminating Papers Oy:n Kotkan impregnointitehtaan johtoa optimaalisen tuotemixin, konelinjan ja työaikamuodon valintaan liittyvässä päätöksenteossa. Tutkimus on tapaustutkimus ja aineiston analyysitapa on kvalitatiivinen. Kohdeyrityksen mallin rakentamista lähestytään tuote- ja asiakaskannattavuuden sekä kustannusten mallintamisen teorian kautta. Pelkkä tuloslaskelma ei kerro tuote- ja asiakaskohtaisesta kannattavuudesta, minkä vuoksi johdon päätöksenteon tueksi tarvitaan erillisiä järjestelmiä ja malleja. Kustannusten mallintamisen myötä saatavaa informaatiota voidaan käyttää sekä operatiivisessa että strategisessa päätöksenteossa. Hyvän mallin aikaan saamiseksi mallintamisessa on tärkeää noudattaa järjestelmällisyyttä sekä huomioida johdon tarpeet, mallin tavoitteet ja kaikki kannattavuuden muodostumiseen vaikuttavat oleelliset tekijät.

Communicative and Anticipatory Decision-Making Supported by Bayesian Networks

The purpose of this research is to draw up a clear construction of an anticipatory communicative decision-making process and a successful implementation of a Bayesian application that can be used as an anticipatory communicative decision-making support system. This study is a decision-oriented and constructive research project, and it includes examples of simulated situations. As a basis for further methodological discussion about different approaches to management research, in this research, a decision-oriented approach is used, which is based on mathematics and logic, and it is intended to develop problem solving methods. The approach is theoretical and characteristic of normative management science research. Also, the approach of this study is constructive. An essential part of the constructive approach is to tie the problem to its solution with theoretical knowledge. Firstly, the basic definitions and behaviours of an anticipatory management and managerial communication are provided. These descriptions include discussions of the research environment and formed management processes. These issues define and explain the background to further research. Secondly, it is processed to managerial communication and anticipatory decision-making based on preparation, problem solution, and solution search, which are also related to risk management analysis. After that, a solution to the decision-making support application is formed, using four different Bayesian methods, as follows: the Bayesian network, the influence diagram, the qualitative probabilistic network, and the time critical dynamic network. The purpose of the discussion is not to discuss different theories but to explain the theories which are being implemented. Finally, an application of Bayesian networks to the research problem is presented. The usefulness of the prepared model in examining a problem and the represented results of research is shown. The theoretical contribution includes definitions and a model of anticipatory decision-making. The main theoretical contribution of this study has been to develop a process for anticipatory decision-making that includes management with communication, problem-solving, and the improvement of knowledge. The practical contribution includes a Bayesian Decision Support Model, which is based on Bayesian influenced diagrams. The main contributions of this research are two developed processes, one for anticipatory decision-making, and the other to produce a model of a Bayesian network for anticipatory decision-making. In summary, this research contributes to decision-making support by being one of the few publicly available academic descriptions of the anticipatory decision support system, by representing a Bayesian model that is grounded on firm theoretical discussion, by publishing algorithms suitable for decision-making support, and by defining the idea of anticipatory decision-making for a parallel version. Finally, according to the results of research, an analysis of anticipatory management for planned decision-making is presented, which is based on observation of environment, analysis of weak signals, and alternatives to creative problem solving and communication.

Tuotantostrateginen Make or buy -päätöksenteko metalliteollisuusalan yrityksessä

Tuotantostrategiaan perustuvien ostaa-valmistaa, eli Make or buy -päätösten merkitys on korostunut yritysten dynaamisen toimintaympäristön myötä. Päätöksissä tehdyt virheet voivat olla kohtalokkaita yrityksen kilpailukyvylle. Diplomityön tavoitteena on luoda Make or buy -päätöksentekoa ohjaava viitekehys yrityksen kansainväliseen käyttöön. Tavoitteeseen sisältyy luodun Make or buy -mallin toimivuuden todentaminen case-tutkimuksella. Make or buy -päätöksenteossa korostuvat talouden, osaamisen ja riskien näkökulmat. Tehtyjä päätöksiä tulee uudelleenarvioida ja tarvittaessa päivittää toimintaympäristön muuttuessa. Päätöksentekomallin tulee siis olla toistuvaa käyttöä ajatellen selkeä ja helppokäyttöinen. Työssä kehitetty kirjallisuusaineistoon perustuva Make or buy –päätöksenteon viitekehys ohjaa yritystä strategisen, taktisen ja operatiivisen tason päätöksissä. Lisäksi malli ohjaa organisaatiota päätöksentekoroolien määrittämisessä. Viitekehys sisältää strukturoidun päätöksentekomallin strategisiin ja taktisiin päätöksiin sekä yksinkertaisen valintamallin operatiivisiin päätöksiin. Operatiivisen tason eriyttämisellä pyritään helpottamaan mallien käyttöä. Työssä rakennetun strukturoidun viitekehyksen toimivuuden testaus esitetään empiirisessä vaiheessa.

Linguistic models for decision support

Linguistic modelling is a rather new branch of mathematics that is still undergoing rapid development. It is closely related to fuzzy set theory and fuzzy logic, but knowledge and experience from other fields of mathematics, as well as other fields of science including linguistics and behavioral sciences, is also necessary to build appropriate mathematical models. This topic has received considerable attention as it provides tools for mathematical representation of the most common means of human communication - natural language. Adding a natural language level to mathematical models can provide an interface between the mathematical representation of the modelled system and the user of the model - one that is sufficiently easy to use and understand, but yet conveys all the information necessary to avoid misinterpretations. It is, however, not a trivial task and the link between the linguistic and computational level of such models has to be established and maintained properly during the whole modelling process. In this thesis, we focus on the relationship between the linguistic and the mathematical level of decision support models. We discuss several important issues concerning the mathematical representation of meaning of linguistic expressions, their transformation into the language of mathematics and the retranslation of mathematical outputs back into natural language. In the first part of the thesis, our view of the linguistic modelling for decision support is presented and the main guidelines for building linguistic models for real-life decision support that are the basis of our modeling methodology are outlined. From the theoretical point of view, the issues of representation of meaning of linguistic terms, computations with these representations and the retranslation process back into the linguistic level (linguistic approximation) are studied in this part of the thesis. We focus on the reasonability of operations with the meanings of linguistic terms, the correspondence of the linguistic and mathematical level of the models and on proper presentation of appropriate outputs. We also discuss several issues concerning the ethical aspects of decision support - particularly the loss of meaning due to the transformation of mathematical outputs into natural language and the issue or responsibility for the final decisions. In the second part several case studies of real-life problems are presented. These provide background and necessary context and motivation for the mathematical results and models presented in this part. A linguistic decision support model for disaster management is presented here – formulated as a fuzzy linear programming problem and a heuristic solution to it is proposed. Uncertainty of outputs, expert knowledge concerning disaster response practice and the necessity of obtaining outputs that are easy to interpret (and available in very short time) are reflected in the design of the model. Saaty’s analytic hierarchy process (AHP) is considered in two case studies - first in the context of the evaluation of works of art, where a weak consistency condition is introduced and an adaptation of AHP for large matrices of preference intensities is presented. The second AHP case-study deals with the fuzzified version of AHP and its use for evaluation purposes – particularly the integration of peer-review into the evaluation of R&D outputs is considered. In the context of HR management, we present a fuzzy rule based evaluation model (academic faculty evaluation is considered) constructed to provide outputs that do not require linguistic approximation and are easily transformed into graphical information. This is achieved by designing a specific form of fuzzy inference. Finally the last case study is from the area of humanities - psychological diagnostics is considered and a linguistic fuzzy model for the interpretation of outputs of multidimensional questionnaires is suggested. The issue of the quality of data in mathematical classification models is also studied here. A modification of the receiver operating characteristics (ROC) method is presented to reflect variable quality of data instances in the validation set during classifier performance assessment. Twelve publications on which the author participated are appended as a third part of this thesis. These summarize the mathematical results and provide a closer insight into the issues of the practicalapplications that are considered in the second part of the thesis.

Factors affecting a woman's decision to leave an abusive relationship : the theory of planned behaviour /

The present study tested the appHcabiUty of Ajzen's (1985) theory of planned behaviour (TPB), an extension of Fishbein and Ajzen's (1975) theory of reasoned action (TRA), for the first time, in the context of abused women's decision to leave their abusive relationships. The TPB, as a means of predicting women's decision to leave their abusive partners' was drawn from Strube's (1988, 1991) proposed decision-making model based on the principle that the decision-making process is a rational, deliberative process, and regardless of outcome, was a result of a logical assessment of the available data. As a means of predicting those behaviours not under volitional control, Ajzen's (1985) TPB incorporated a measure of perceived behavioural control. Data were collected in two phases, ranging from 6 months to 1 year apart. It was hypothesized that, to the extent that an abused woman held positive attitudes, subjective norms conducive to leaving, and perceived control over leaving, she would form an intention to leave and thus, increase the likelihood of actually leaving her partner. Furthermore, it was expected that perceptions of control would predict leaving behaviour over and above attitude and subjective norm. In addition, severity and frequency of abuse were assessed, as were demographic variables. The TPB failed to account significantly for variability in either intentions or leaving behaviour. All of the variance was attributed to those variables associated with the theory of reasoned action, with social influence emerging as the strongest predictor of a woman's intentions. The poor performance of this model is attributed to measurement problems with aspects of attitude and perceived control, as well as a lack of power due to the small sample size. The insufficiency of perceived control to predict behaviour also suggests that, on the surface at least, other factors may be at work in this context. Implications of these results, and recommendations such as, the importance of obtaining representative samples, the inclusion of self-esteem and emotions as predictor variables in this model, a reevaluation of the target behaviovu" as nonvolitional, and longitudinal studies spanning a longer time period for future research within the context of decision-making are discussed.

Distributed conditional computation

L'objectif de cette thèse est de présenter différentes applications du programme de recherche de calcul conditionnel distribué. On espère que ces applications, ainsi que la théorie présentée ici, mènera à une solution générale du problème d'intelligence artificielle, en particulier en ce qui a trait à la nécessité d'efficience. La vision du calcul conditionnel distribué consiste à accélérer l'évaluation et l'entraînement de modèles profonds, ce qui est très différent de l'objectif usuel d'améliorer sa capacité de généralisation et d'optimisation. Le travail présenté ici a des liens étroits avec les modèles de type mélange d'experts. Dans le chapitre 2, nous présentons un nouvel algorithme d'apprentissage profond qui utilise une forme simple d'apprentissage par renforcement sur un modèle d'arbre de décisions à base de réseau de neurones. Nous démontrons la nécessité d'une contrainte d'équilibre pour maintenir la distribution d'exemples aux experts uniforme et empêcher les monopoles. Pour rendre le calcul efficient, l'entrainement et l'évaluation sont contraints à être éparse en utilisant un routeur échantillonnant des experts d'une distribution multinomiale étant donné un exemple. Dans le chapitre 3, nous présentons un nouveau modèle profond constitué d'une représentation éparse divisée en segments d'experts. Un modèle de langue à base de réseau de neurones est construit à partir des transformations éparses entre ces segments. L'opération éparse par bloc est implémentée pour utilisation sur des cartes graphiques. Sa vitesse est comparée à deux opérations denses du même calibre pour démontrer le gain réel de calcul qui peut être obtenu. Un modèle profond utilisant des opérations éparses contrôlées par un routeur distinct des experts est entraîné sur un ensemble de données d'un milliard de mots. Un nouvel algorithme de partitionnement de données est appliqué sur un ensemble de mots pour hiérarchiser la couche de sortie d'un modèle de langage, la rendant ainsi beaucoup plus efficiente. Le travail présenté dans cette thèse est au centre de la vision de calcul conditionnel distribué émis par Yoshua Bengio. Elle tente d'appliquer la recherche dans le domaine des mélanges d'experts aux modèles profonds pour améliorer leur vitesse ainsi que leur capacité d'optimisation. Nous croyons que la théorie et les expériences de cette thèse sont une étape importante sur la voie du calcul conditionnel distribué car elle cadre bien le problème, surtout en ce qui concerne la compétitivité des systèmes d'experts.

Análisis económico de las vacunas 10-valente y 13-valente contra neumococo: revisión sistemática

Introducción: Las vacunas clásicamente han representado un método económico y eficaz para el control y prevención de múltiples enfermedades infecciosas. En los últimos años se han introducido nuevas vacunas contra neumococo a precios elevados, y los diferentes análisis económicos a nivel mundial de estas vacunas no muestran tendencias. El objetivo de este trabajo era resumir la evidencia existente a través de los diferentes estudios económicos evaluando las dos vacunas de segunda generación contra neumococo en la población a riesgo. Metodología: En este trabajo se realizo una revisión sistemática de la literatura en 8 bases de datos localizadas en diferentes partes del mundo y también que tuvieran literatura gris. Los artículos fueron inicialmente evaluados acorde a su titulo y resumen, posteriormente los elegidos se analizaron en su totalidad. Resultados: Se encontraron 404 artículos, de los cuales 20 fueron incluidos en el análisis final. Se encontró que la mayoría de los estudios se realizaron en áreas donde la enfermedad tiene una carga baja, como es Norte América y Europa, mientras que en los lugares del mundo donde la carga es mas alta, se realizaron pocos estudios. De igual manera se observo que la mayoría de los estudios mostraron por los menos ser costo efectivos respecto a la no vacunación, y en su totalidad las dos vacunas de segunda generación mostraron costo efectividad respecto a la vacunación con PCV-7. Los resultados de los estudios son muy heterogéneos, hasta dentro del mismo país, señalando la necesidad de guías para la conducción de este tipo de estudios. De igual manera, la mayoría de los estudios fueron financiados por farmacéuticas, mientras en un numero muy reducido por entes gubernamentales. Conclusiones: La mayoría de los estudios económicos sobre las vacunas de segunda generación contra neumococo han sido realizados en países con un alto índice de desarrollo económico y patrocinados por farmacéuticas. Dado que la mayoría de la carga de la enfermedad se encuentran en regiones con un menor nivel de desarrollo económico se deberían realizar mas en estas zonas. De igual manera, al ser la vacunación un asunto de salud publica y con un importante impacto económico los gobiernos deberían estar mas involucrados en los mismos.