Campylobacter species are the primary cause of bacterial food-borne diarrhoea worldwide. Comparative genomic analyses of Campylobacter strains reveal genome plasticity providing insight into the evolution of virulence traits. The goal of this study was to identify genes important for infectivity and for naturally occurring variability in phenotypic traits in C. jejuni and C. coli strains. Transcriptome and phenotype analyses were conducted to determine if genetic and phenotypic characteristics could be attributed to the source of the strains. Isolates from water sources had higher biofilm formation than animal strains. Clinical strains had decreased sensitivity to hydrogen peroxide as well as increased adherence and invasion when compared to animal strains. A number of genetic differences were observed; however, without further analysis it is difficult to determine which of these impact virulence in Campylobacter. Ultimately, this project will lead to the identification of markers associated with strains of Campylobacter causing illness.

Campylobacter species are the primary cause of bacterial food-borne diarrhoea worldwide. Comparative genomic analyses of Campylobacter strains reveal genome plasticity providing insight into the evolution of virulence traits. The goal of this study was to identify genes important for infectivity and for naturally occurring variability in phenotypic traits in C. jejuni and C. coli strains. Transcriptome and phenotype analyses were conducted to determine if genetic and phenotypic characteristics could be attributed to the source of the strains. Isolates from water sources had higher biofilm formation than animal strains. Clinical strains had decreased sensitivity to hydrogen peroxide as well as increased adherence and invasion when compared to animal strains. A number of genetic differences were observed; however, without further analysis it is difficult to determine which of these impact virulence in Campylobacter. Ultimately, this project will lead to the identification of markers associated with strains of Campylobacter causing illness.

O presente trabalho aborda a determinação de conteúdo na fase de planejamento do documento no pipeline de Geração de Língua Natural (GLN) usando fatores de personalidade do modelo dos Cinco Grandes Fatores (CGF). O principal objetivo deste trabalho é gerar modelos computacionais de determinação de conteúdo baseados nos fatores de personalidade CGF. O trabalho aplicará técnicas já existentes de GLN para determinação de conteúdo, levando em conta os fatores de personalidade mapeados pelo modelo CGF. São utilizados os conceitos descritos por substantivos e os conceitos descritos por adjetivos relacionados aos substantivos na tarefa de descrição de cenas para a determinação de conteúdo. As principais contribuições desse trabalho são uma investigação de se e como a determinação de conteúdo de descrições textuais é influenciada pela personalidade do autor, além de entregar um modelo de determinação de conteúdo baseado em personalidade para os conceitos em que o trabalho foi aplicado, entre outras entregas. É apresentado o embasamento teórico com os conceitos fundamentais de GLN, e mais especificamente de determinação de conteúdo, foco dessa pesquisa. Além disso, são apresentados os modelos de personalidade humana, com destaque ao modelo CGF e inventários CGF, utilizados para a coleta de dados e execução dessa proposta. São apresentados também os principais trabalhos relacionados à GLN e modelo CGF, mesmo que não tratem especificamente da influência dos CGF na determinação de conteúdo. Um experimento para coleta do córpus utilizado na pesquisa é descrito, e também os modelos para determinação de conteúdo no âmbito de conceitos representando entidades visuais e seus predicados, assim como a avaliação desses modelos. Por fim, são apresentadas as conclusões obtidas com os modelos desenvolvidos e experimentos realizados / The present research approaches the content determination in the document planning phase of the Natural Language Generation (NLG) pipeline using personality factors of the Big Five Factor (BFF) model. The main objective of this research is to generate computational models of content determination based on the BFF personality factors. This research will apply existing NLG models to the content determination, taking into account the personality factors mapped by the BFF model. The concepts described by nouns and the concepts described by adjectives related to nouns in the task of describing scenes for content determination are used. The main contributions of this research are an investigation of if and how the content determination of textual descriptions is influenced by the personality of the author, in addition to providing a personality-based content determination model for the concepts in which the research was applied, among others deliveries. This document presents the theoretical basis and the fundamental NLG concepts, and more specifically the concept of content determination, which is the focus of this research. In addition, human personality models are presented, with emphasis on the BFF model and BFF inventories, used both for data collection and development of this proposal. The main studies related to NLG and the BFF model, even if they do not specifically address the influence of BFF in content determination, are also presented. An experiment for collecting the corpus used in the research is described, also the models to determine content in the scope of concepts representing visual entities and their predicates, as well as an evaluation of these models. Finally, the conclusions obtained with the developed models and experiments are presented

O presente trabalho aborda a determinação de conteúdo na fase de planejamento do documento no pipeline de Geração de Língua Natural (GLN) usando fatores de personalidade do modelo dos Cinco Grandes Fatores (CGF). O principal objetivo deste trabalho é gerar modelos computacionais de determinação de conteúdo baseados nos fatores de personalidade CGF. O trabalho aplicará técnicas já existentes de GLN para determinação de conteúdo, levando em conta os fatores de personalidade mapeados pelo modelo CGF. São utilizados os conceitos descritos por substantivos e os conceitos descritos por adjetivos relacionados aos substantivos na tarefa de descrição de cenas para a determinação de conteúdo. As principais contribuições desse trabalho são uma investigação de se e como a determinação de conteúdo de descrições textuais é influenciada pela personalidade do autor, além de entregar um modelo de determinação de conteúdo baseado em personalidade para os conceitos em que o trabalho foi aplicado, entre outras entregas. É apresentado o embasamento teórico com os conceitos fundamentais de GLN, e mais especificamente de determinação de conteúdo, foco dessa pesquisa. Além disso, são apresentados os modelos de personalidade humana, com destaque ao modelo CGF e inventários CGF, utilizados para a coleta de dados e execução dessa proposta. São apresentados também os principais trabalhos relacionados à GLN e modelo CGF, mesmo que não tratem especificamente da influência dos CGF na determinação de conteúdo. Um experimento para coleta do córpus utilizado na pesquisa é descrito, e também os modelos para determinação de conteúdo no âmbito de conceitos representando entidades visuais e seus predicados, assim como a avaliação desses modelos. Por fim, são apresentadas as conclusões obtidas com os modelos desenvolvidos e experimentos realizados / The present research approaches the content determination in the document planning phase of the Natural Language Generation (NLG) pipeline using personality factors of the Big Five Factor (BFF) model. The main objective of this research is to generate computational models of content determination based on the BFF personality factors. This research will apply existing NLG models to the content determination, taking into account the personality factors mapped by the BFF model. The concepts described by nouns and the concepts described by adjectives related to nouns in the task of describing scenes for content determination are used. The main contributions of this research are an investigation of if and how the content determination of textual descriptions is influenced by the personality of the author, in addition to providing a personality-based content determination model for the concepts in which the research was applied, among others deliveries. This document presents the theoretical basis and the fundamental NLG concepts, and more specifically the concept of content determination, which is the focus of this research. In addition, human personality models are presented, with emphasis on the BFF model and BFF inventories, used both for data collection and development of this proposal. The main studies related to NLG and the BFF model, even if they do not specifically address the influence of BFF in content determination, are also presented. An experiment for collecting the corpus used in the research is described, also the models to determine content in the scope of concepts representing visual entities and their predicates, as well as an evaluation of these models. Finally, the conclusions obtained with the developed models and experiments are presented

In large scale entity-level military force-on-force simulations it is essential to know when one entity can visibly see another entity. This visibility determination plays an important role in the simulation and can affect the outcome of the simulation. When virtual Computer Generated Forces (CGF) are introduced into the simulation these intervisibilities must now be calculated by the virtual entities on the battlefield. But as the simulation size increases so does the complexity of calculating visibility between entities. This thesis presents an algorithm for performing these visibility calculations using Graphical Processing Units (GPU) instead of the Central Processing Units (CPU) that have been traditionally used in CGF simulations. This algorithm can be distributed across multiple GPUs in a cluster and its scalability exceeds that of CGF-based algorithms. The poor correlations of the two visibility algorithms are demonstrated showing that the GPU algorithm provides a necessary condition for a "Fair Fight" when paired with visual simulations.

Coopetition, a combined word for cooperation and competition, is a business strategy in which two or more parties within a competing market use a cooperative action. This concept is mainly practical in situations where companies are rich in resources and have considerable assets. For example, one industry that could use coopetitive strategies is the public transport sector. Trafikförvaltningen is the organization that is responsible for public transportation in Stockholm County, along with subcontractors known as traffic operating firms (TOFs). Every 8 to 10 years, so-called traffic area contracts are open for bidding where these TOFs have the opportunity to bid on these areas where they operate their traffic and maintain their depots. For this reason, these TOFs can be considered competitors to each other, thus sharing a reluctance to cooperate. Therefore, since bus lines do not always end their travels in the same traffic area they started, the organization can end up with high annual costs in terms of empty travels from traveling back to their traffic area. The study‘s aim is to: investigate the possibilities and potential outcomes for the public transport sector to use cooperative strategies. The focus has been on a strategy in the form of co-sharing of Trafikförvaltningen’s bus depots between its TOFs. A financial calculation analysis has also been performed, estimating how much the organization can save on this. The study is in the form of a case study and takes an intensive research approach. The data collection consists of so-called in-depth and focused interviews with individuals from different companies. The results of this study show an annual saving of 59.5 Million Swedish Krona in the case of Trafikförvaltningen. This case study concludes that establishing a coopetition governance function (CGF) is crucial for implementing a coopetitive strategy within the public transport sector. / Coopetition, ett kombinerat ord för samarbete och konkurrens, är en affärsstrategi där två eller fler parter inom en konkurrerande marknad använder sig av en samarbetshandling. Denna typ av koncept är främst praktisk i situationer där företagen är rika på resurser och har stora tillgångar. En bransch som skulle kunna få god användning av affärsstrategier inom coopetition är kollektivtrafikbranschen. Trafikförvaltningen är organisationen som ansvarar för den allmänna kollektivtrafiken i Stockholms län tillsammans med ett antal underleverantörer som kallas för trafikutövare (TOFs). Varje årtionden sker en budgivning där dessa trafikutövare får möjligheten till att buda på så kallade trafikområden där de utövar sin trafik och har depåer i drift. Av denna anledning kan dessa trafikutövare anses vara konkurrenter till varandra. Eftersom busslinjer inte alltid avslutar sin resa inom samma trafikområde som de startade i kan detta även resultera stora årliga kostnader för organisationen i form av tomkörning. Syftet med denna studie kan sammanfattas som: att undersöka möjligheterna och de potentiella utfallen för kollektivtrafikssektorn att använda sig av konkurrenssamarbetsstrategier. Studiens fokus har därför varit på en strategi i form av samutnyttjande av Trafikförvaltningens bussdepåer mellan dessa trafikutövare. En finansiell beräkningsanalys har även utförts som uppskattat hur mycket organisationen skulle kunna bespara på detta. Studien är i formen av en fallstudie och tar en intensiv forskningsansats. Datasamlingen bestod huvudsakligen av en blandning av så kallade djup- och fokuserade intervjuer med individer från de olika företagen. Resultatet för denna studie visar att en årlig besparing på totalt 59,5 miljoner svenska kronor skulle kunna möjliggöras i Trafikförvaltningens fall. Slutsatsen i denna fallstudie är att etablera en styrgupp för konkurrens- och samarbetsförhållandet (CGF) för att framgångsrikt lyckas effektivisera de rådande omständigheterna inom kollektivtrafikbraschen.