<p>Neregularnost prostiranja radio talasa je uobičajeni fenomen koji<br />utiče na kvalitet radio veze u okviru bežične mreže, rezultujući<br />različitim obrascima prostiranja radio talasa. Ova teza daje<br />predlog nekoliko postupaka analize prostiranja radio talasa u cilju<br />bez-senzorskog otkrivanja prisustva i kretanja ljudi unutar postojeće<br />bežične mreže. Indikator primljene snage radio signala predstavlja<br />osnovni element analize, iz kog se izdvajaju informaciono,<br />amplitudsko i frekventno obeležje. Analizom navedenih obeležja<br />moguća je realizacija robusnog postupka bez-senzorske detekcije ljudi<br />koja se može primeniti u različitim rešenjima ambijentalne<br />inteligencije, zahtevajući minimalan broj elemenata fizičke<br />arhitekture, neophodnih za uspostavljanje korisnički svesnog<br />okruženja.</p> / <p>Radio irregularity is a common and non-negligible phenomenon that impacts<br />the connectivity and interference in a wireless network, by introducing<br />disturbances in radio signal&rsquo;s propagation pattern. In order to detect a<br />possible presence of a human subject within the existing radio network<br />sensorlessly, this thesis analyze the irregularity data expressed in a form of<br />received signal strength variation. The received signal strength variation is<br />decomposed into information, amplitude and frequency characteristics. The<br />combination of these three characteristics analysis enables the definition of<br />robust and cost-effective device-free human presence detection method that<br />can be exploited for various ambient intelligence solutions, requiring the<br />minimum hardware add-ons that are necessary for the establishment of a<br />user aware environment.</p>

Cette thèse est consacrée à l'étude de la transmission des chocs réels et financiers en Europe, en traitant le canal du capital bancaire. La démarche suivie consiste à combiner des approches théoriques et empiriques de façon à mettre en évidence empiriquement l'hétérogénéité de transmission au niveau européen et l'ampleur du canal du capital bancaire. Le premier chapitre consiste à faire un tour d’horizon sur les fonds propres et la structure financière des banques, tout en analysant leur impact au niveau micro et macroéconomique. D'après l’analyse de la littérature relative à ce champ, le processus de transmission semble bien influencé par la spécificité des banques et leur niveau de fonds propres réglementaires. La contrainte exercée sur ces derniers détermine l’ampleur de la transmission des chocs. Le deuxième chapitre est consacré à l'étude des déterminants de la réaction des banques face à un choc. D'après les résultats, le niveau ex ante des fonds propres mais également les différentes composantes du capital réglementaire influencent la réaction des banques. Le troisième chapitre analyse les effets de Bâle I et II sur le mécanisme de transmission des chocs à partir d’un modèle d’équilibre général. Les résultats des simulations montrent que la prise en compte simultanée d’un canal du capital bancaire et d’un mécanisme d’accélérateur financier amplifie la propagation des chocs monétaires à travers un effet prime de liquidité. Le dernier chapitre est consacré à examiner un aspect particulier de la réglementation prudentielle : la résolution des défaillances des institutions financières. L’accent est mis sur les banques d’importance systémique. L’analyse des politiques de résolution adoptées montre que ces dernières ne permettent pas de réduire le risque moral. Aussi, pour prévenir de leur défaut, des règles de fermeture sont mises en place. À cette fin, une modélisation théorique conduit à conclure que des sanctions monétaires, couplées à une surveillance accrue peuvent limiter les incitations des banques à prendre des risques excessifs. Cette présente thèse a apporté de nouveaux résultats par rapport à la littérature et elle a montré le rôle à court et long terme des différents éléments de la structure du bilan des banques résultant de l'estimation du modèle VECM. / In this thesis, we study the transmission of real and financial shocks in Europe focusing on the bank capital channel. In our approach, we consider both theoretical and empirical issues. The ai mis to empirically emphasize the heteregeneity in the transmission of shocks at a European level and the extent of the bank capital channel. In Chapter 1, we do a survey on the structure of bank capital and balance sheet to analyse their impact at micro and macro levels. Considering the existing literature on bank capital and transmission channel, the transmission process seems to be influenced by banks’ specificities and by their level of regulatory capital. Regulatory constraint on bank capital determines the magnitude of the transmission of shocks. In Chapter 2, we study the determinants of banks’ reaction to a shock. Or results show that, the ex ante level of capital and the various components of regulatory capital significantly impact banks’ behaviour. In Chapter 3, we focus on the impact of Basel I and II regulatory frameworks on the transmission of shocks from a general equilibrium model. The simulation results point out that considering simultaneously the bank capital channel and the financial accelerator mechanism increases the propagation of monetary shocks through the liquidity premium effect. In Chapter 4, we examine a singular aspect of the prudential regulation : the resolution of failing financial institutions. We focus on the systemic importance banks. Current policy statements have not reduced moral hazard behaviour of such financial institutions. Thus, to prevent the catastrophic consequences of their failure, bankruptcy laws have been adopted. Considering a theoretical model, we conclude that monetary sanctions, strengthen by stronger monitoring pressures may limit banks’ incentives to take excessive risks. This thesis provides new results to the existing literature. It emphasizes the role of the several components of bank balance sheet structure in both short and long runs, resulting from an estimated VECM.

A qualidade microbiológica de medicamentos é fundamental para garantir sua eficácia e segurança. Os métodos convencionais para identificação microbiana em produtos não estéreis são amplamente utilizados, entretanto são demorados e trabalhosos. O objetivo deste trabalho é desenvolver método microbiológico rápido (MMR) para a identificação de contaminantes em produtos farmacêuticos utilizando a espectrofotometria de infravermelho com transformada de Fourier com reflectância total atenuada (FTIR-ATR). Análise de componentes principais (PCA) e análise de discriminantes (LDA) foram utilizadas para obter um modelo de predição com a capacidade de diferenciar o crescimento de oriundo de contaminação por Bacillus subtilis (ATCC 6633), Candida albicans (ATCC 10231), Enterococcus faecium (ATCC 8459), Escherichia coli (ATCC 8739), Micrococcus luteus (ATCC 10240), Pseudomonas aeruginosa (ATCC 9027), Salmonella Typhimurium (ATCC 14028), Staphylococcus aureus (ATCC 6538) e Staphylococcus epidermidis (ATCC 12228). Os espectros de FTIR-ATR forneceram informações quanto à composição de proteínas, DNA/RNA, lipídeos e carboidratos provenientes do crescimento microbiano. As identificações microbianas fornecidas pelo modelo PCA/LDA baseado no método FTIR-ATR foram compatíveis com aquelas obtidas pelos métodos microbiológicos convencionais. O método de identificação microbiana rápida por FTIR-ATR foi validado quanto à sensibilidade (93,5%), especificidade (83,3%) e limite de detecção (17-23 UFC/mL de amostra). Portanto, o MMR proposto neste trabalho pode ser usado para fornecer uma identificação rápida de contaminantes microbianos em produtos farmacêuticos. / Microbiological quality of pharmaceuticals is fundamental in ensuring efficacy and safety of medicines. Conventional methods for microbial identification in non-sterile drugs are widely used, however are time-consuming and laborious. The aim of this paper was to develop a rapid microbiological method (RMM) for identification of contaminants in pharmaceutical products using Fourier transform infrared with attenuated total reflectance spectrometry (FTIR-ATR). Principal components analysis (PCA) and linear discriminant analysis (LDA) were used to obtain a predictive model with capable to distinguish Bacillus subtilis (ATCC 6633), Candida albicans (ATCC 10231), Enterococcus faecium (ATCC 8459), Escherichia coli (ATCC 8739), Micrococcus luteus (ATCC 10240), Pseudomonas aeruginosa (ATCC 9027), Salmonella Typhimurium (ATCC 14028), Staphylococcus aureus (ATCC 6538), and Staphylococcus epidermidis (ATCC 12228) microbial growth. FTIR-ATR spectra provide information of protein, DNA/RNA, lipids, and carbohydrates constitution of microbial growth. Microbial identification provided by PCA/LDA based on FTIR-ATR method were compatible to those obtained using conventional microbiological methods. FTIR-ATR method for rapid identification of microbial contaminants in pharmaceutical products was validated by assessing the sensitivity (93.5%), specificity (83.3%), and limit of detection (17-23 CFU/mL of sample). Therefore, the RMM proposed in this work may be used to provide a rapid identification of microbial contaminants in pharmaceutical products.

On suppose que des vecteurs de données de grande dimension arrivant en ligne sont des observations indépendantes d'un vecteur aléatoire. Dans le second chapitre, ce dernier, noté Z, est partitionné en deux vecteurs R et S et les observations sont supposées identiquement distribuées. On définit alors une méthode récursive d'estimation séquentielle des r premiers facteurs de l'ACP projetée de R par rapport à S. On étudie ensuite le cas particulier de l'analyse canonique, puis de l'analyse factorielle discriminante et enfin de l'analyse factorielle des correspondances. Dans chacun de ces cas, on définit plusieurs processus spécifiques à l'analyse envisagée. Dans le troisième chapitre, on suppose que l'espérance En du vecteur aléatoire Zn dont sont issues les observations varie dans le temps. On note Rn = Zn - En et on suppose que les vecteurs Rn forment un échantillon indépendant et identiquement distribué d'un vecteur aléatoire R. On définit plusieurs processus d'approximation stochastique pour estimer des vecteurs directeurs des axes principaux d'une analyse en composantes principales (ACP) partielle de R. On applique ensuite ce résultat au cas particulier de l'analyse canonique généralisée (ACG) partielle après avoir défini un processus d'approximation stochastique de type Robbins-Monro de l'inverse d'une matrice de covariance. Dans le quatrième chapitre, on considère le cas où à la fois l'espérance et la matrice de covariance de Zn varient dans le temps. On donne finalement des résultats de simulation dans le chapitre 5 / High dimensional data are supposed to be independent on-line observations of a random vector. In the second chapter, the latter is denoted by Z and sliced into two random vectors R et S and data are supposed to be identically distributed. A recursive method of sequential estimation of the factors of the projected PCA of R with respect to S is defined. Next, some particular cases are investigated : canonical correlation analysis, canonical discriminant analysis and canonical correspondence analysis ; in each case, several specific methods for the estimation of the factors are proposed. In the third chapter, data are observations of the random vector Zn whose expectation En varies with time. Let Rn = Zn - En be and suppose that the vectors Rn form an independent and identically distributed sample of a random vector R. Stochastic approximation processes are used to estimate on-line direction vectors of the principal axes of a partial principal components analysis (PCA) of ~Z. This is applied next to the particular case of a partial generalized canonical correlation analysis (gCCA) after defining a stochastic approximation process of the Robbins-Monro type to estimate recursively the inverse of a covariance matrix. In the fourth chapter, the case when both expectation and covariance matrix of Zn vary with time n is considered. Finally, simulation results are given in chapter 5

Após o ajuste individual das 55 vacas estudadas pelo modelo Gompertz difá- sico com estrutura de erros autorregressiva de ordem 1 (totalizando 7 parâmetros), notou-se que apenas 6 vacas tinham problemas nas estimativas de seus parâmetros (não convergentes ou não signicativos), dessa forma continuou-se o trabalho proposto com 49 animais. Com as estimativas de cada um dos parâmetros (variáveis nessa etapa) foi realizada a análise de componentes principais e observação do gráco biplot, sendo possível a constatação de que 2 dos parâmetros do modelo continham informações ambíguas com pelo menos um dos demais parâmetros e estes foram retirados da análise, restando 5 parâmetros para o estudo. A análise de componentes principais foi realizada novamente apenas com os 5 parâmetros restantes e os três primeiros componentes principais (escolhidos pelo critério da percentagem de variância original explicada) foram utilizados como variáveis em um processo de agrupamento hierárquico. Após a realização da análise de agrupamentos, observou-se que 5 grupos homogêneos de animais foram formados, cada um com caraterísticas distintas. Desta forma, foi possível identicar animais que se destacavam, positiva ou negativamente, no que tange ao seu peso assintótico e taxa de crescimento. / After individual adjustment of the 55 cows studied using the diphasic Gompertz model with autoregressive structure of errors (totalizing 7 parameters), it was noted that only 6 cows had problems on estimates of the parameters (not converged or not signicant), then the proposed work continued with 49 animals. With each of the parameters estimates (variables at this stage) was performed a principal component analysis and observation of the biplot, and it was possible to nd that two of the model parameters contained ambiguous information with at least one of the other parameters, then these 2 parameters were removed from the analysis, leaving 5 parameters for the study. The principal component analysis was performed again with only ve remaining parameters and the rst three principal components (chosen by the criterion of percentage of original explained variance) were used as variables in a process of hierarchical clustering. After performing the cluster analysis, we found that ve homogeneous groups of animals were formed, each with distinct characteristics. Thus, it was possible to identify animals that stood out, positively or negatively, in terms of their asymptotic weight and growth rate.

Neste trabalho foi utilizado um método matemático para classificar registros de potencial e corrente de ensaios de corrosão na técnica de amperimetria de resistência nula (ZRA). Foi aplicado o método estatístico de múltiplas variáveis simples chamado Análise dos Componentes Principais (PCA), cujo objetivo principal foi identificar padrões nestes dados de ruído eletroquímico. Foram testados o aço carbono UNS G10200, os aços inoxidáveis austenítico UNS S31600 e o superduplex UNS S32750 em meios de ácido sulfúrico (5% H2SO4), cloreto férrico (0,1 mol/L FeCl3) e hidróxido de sódio (0,1% NaOH). Os ensaios foram replicados com oito repetições para se ter reprodutibilidade e conhecimento dos aspectos estatísticos envolvidos. Os resultados mostraram que a análise de componentes principais pode ser utilizada como uma ferramenta para analisar sinais de ruído eletroquímico, identificando os clusters dos comportamentos potencial-tempo, corrente-tempo e acessoriamente identificar os outliersdos registros temporais. / In this study, a mathematical method was used to classify potential and current records of electrochemical noise tests in zero resistance ammeter (ZRA) configuration. The statistical method of multiple simple variables called Principal Components Analysis (PCA) was applied to identify patterns in these electrochemical noise data. The carbon steel UNS G10200, the austenitic stainless steels UNS S31600 and the super duplex UNS S32750 were tested in the solutions of sulfuric acid (5% H2SO4), ferric chloride (0.1 mol/L FeCl3) and sodium hydroxide (0.1% NaOH). The tests were replicated with eight repetitions to obtain reproducibility of the relatedstatistical aspects. The results showed that the principal components analysis could be used as a tool to analyze electrochemical noise signals, identifying behavior clusters of potential-time, current-time and also identifying the outliers in time domain.

Made available in DSpace on 2014-12-17T15:42:03Z (GMT). No. of bitstreams: 1 MariaFPV.pdf: 6083202 bytes, checksum: 8b9199df5753800b615ab0a90bae3e8e (MD5) Previous issue date: 2007-12-10 / Heavy metals can cause problems of human poisoning by ingestion of contaminated food, and the environment, a negative impact on the aquatic fauna and flora. And for the presence of these metals have been used for aquatic animals biomonitoramento environment. This research was done in order to assess the environmental impact of industrial and domestic sewage dumped in estuaries potiguares, from measures of heavy metals in mullet. The methods used for these determinations are those in the literature for analysis of food and water. Collections were 20 samples of mullet in several municipality of the state of Rio Grande do Norte, from the estuaries potiguares. Were analyzed the content of humidity, ash and heavy metals. The data were subjected to two methods of exploratory analysis: analysis of the main components (PCA), which provided a multivariate interpretation, showing that the samples are grouped according to similarities in the levels of metals and analysis of hierarchical groupings (HCA), producing similar results. These tests have proved useful for the treatment of the data producing information that would hardly viewed directly in the matrix of data. The analysis of the results shows the high levels of metallic species in samples Mugil brasiliensis collected in Estuaries /Potengi, Piranhas/A?u, Guara?ra / Papeba / Ar?s and Curimata? / Os metais pesados podem provocar problemas de intoxica??o humana pela ingest?o de alimentos contaminados e para o meio ambiente, uma repercuss?o negativa ? fauna e flora aqu?ticas. E para detectar a presen?a destes metais t?m-se utilizado animais aqu?ticos para o biomonitoramento ambiental. Esta pesquisa foi feita com o intuito de se avaliar o impacto ambiental de esgotos dom?sticos e industriais despejados nos estu?rios potiguares, a partir das medidas de metais pesados em tainha. Os m?todos utilizados para estas determina??es s?o aqueles constantes da literatura para an?lise de alimentos e de ?gua. Foram coletas 20 amostras de tainha em diversos munic?pios do Estado do Rio Grande do Norte, oriundas dos estu?rios potiguares. Foram analisados os teores de umidade, cinzas e metais pesados. Os dados foram submetidos a dois m?todos de an?lises explorat?rios: an?lise de componentes principais (PCA), que proporcionou uma interpreta??o multivariada, mostrando que as amostras s?o agrupadas de acordo com as similaridades de teores de metais e an?lise hier?rquica de agrupamentos (HCA), produzindo resultados semelhantes. Estas an?lises mostraram-se ?teis para o tratamento dos dados produzindo informa??es que dificilmente seriam visualizados diretamente na matriz de dados. A an?lise dos resultados mostra os altos teores de esp?cies met?licas em amostras coletadas em tainhas nos Estu?rios Potengi, Piranhas/A?u, Guara?ra/Papeba/Ares e Curimata?

Magistro baigiamajame darbe išanalizuota ir įvertinta valstybių kredito reitingų suteikimo metodologija, šio proceso kritika, pateikti pasiūlymai esamoms problemoms spręsti. Atlikta koreliacinė, regresinė, pagrindinių komponenčių analizė ir pasinaudojus trijų Baltijos šalių – Lietuvos, Latvijos ir Estijos, pavyzdžiu surasti trys atskiri modeliai, tiksliausiai prognozuojantys minėtų valstybių kredito reitingus, remiantis makroekonominiais rodikliais. Pirmoje darbo dalyje teoriniu aspektu nagrinėjama kredito reitingo samprata, jo reikšmė finansų rinkoms, apibrėžiamos priežastys, lemiančios kredito reitingų trūkumus ir pateikiami tobulinimo siūlymai. Antroje dalyje analizuojamos trijų pagrindinių kredito reitingo agentūrų – Standard and Poor‘s, Fitch ir Moody‘s valstybių kredito reitingo suteikimo metodologijos, tiriama mokslinė literatūra, nagrinėjanti kredito reitingo priklausomybę nuo makroekonominių rodiklių, pateikiamas tyrimo modelis, nagrinėjamos su juo susijusios problemos, apibrėžiama darbo eiga. Trečioje dalyje sudaromos tiesinės daugianarės regresijos lygtys, naudojamos prognozuoti Lietuvos, Latvijos ir Estijos kredito reitingą, atliekamas ateities kredito reitingų prognozavimas remiantis faktiniais 2012 m. IV ketvirčio duomenimis ir numatomais scenarijais. / Master's Work analyzed and evaluated methodology of sovereign credit ratings, the critique of the process itself and proposed solutions for existing problems. Correlation, regression and principal components analysis were used to determine distinct models for the three Baltic states – Lithuania, Latvia and Lithuania, that accurately predicts future credit ratings based on macro-economic indicators. The first part examines theoretical aspect of the concept of credit rating, its value to the global financial markets, defines the causes of the credit rating errors, presents possible solutions for the failures of credit ratings. In the second section methodologies used by Standard and Poor's, Fitch and Moody's to determine sovereign credit ratings are analyzed, scientific literature on the dependence of credit rating and macro-economic indicators are examined, research model and problems associated with it are presented, workflow is defined. In the third part linear multiple regression equations are derived which are used to predict future credit ratings of Lithuania, Latvia and Estonia, future credit ratings predictions are carried out based on actual year 2012 fourth quarter data and future scenarios.

The aim of this thesis is to model the dynamics of international term structure of interest rates taking into consideration several dependence channels.Thanks to a new international Treasury yield curve database, we observe that the explained variability decision criterion, suggested by the literature, is not able to select the best combination of factors characterizing the joint dynamics of yield curves. We propose a new methodology based on the maximisation of the likelihood function of a Gaussian state-space model with common and local factors. The associated identification problem is solved in an innovative way. By estimating several sets of countries, we select two global (and three local) factors which are also useful to forecast macroeconomic variables in each considered economy.In addition, our method allows us to detect hidden factors in the international bond returns. They are not visible through a classical principal component analysis of expected bond returns but they are helpful to forecast inflation and industrial production. Keywords: International treasury yield curves, common and local factors, state-space models, EM algorithm, International bond risk premia, principal components.

The incidence of many arboviral diseases is largely associated with social and environmental conditions. Ross River virus (RRV) is the most prevalent arboviral disease in Australia. It has long been recognised that the transmission pattern of RRV is sensitive to socio-ecological factors including climate variation, population movement, mosquito-density and vegetation types. This study aimed to assess the relationships between socio-environmental variability and the transmission of RRV using spatio-temporal analytic methods. Computerised data files of daily RRV disease cases and daily climatic variables in Brisbane, Queensland during 1985-2001 were obtained from the Queensland Department of Health and the Australian Bureau of Meteorology, respectively. Available information on other socio-ecological factors was also collected from relevant government agencies as follows: 1) socio-demographic data from the Australia Bureau of Statistics; 2) information on vegetation (littoral wetlands, ephemeral wetlands, open freshwater, riparian vegetation, melaleuca open forests, wet eucalypt, open forests and other bushland) from Brisbane City Council; 3) tidal activities from the Queensland Department of Transport; and 4) mosquito-density from Brisbane City Council. Principal components analysis (PCA) was used as an exploratory technique for discovering spatial and temporal pattern of RRV distribution. The PCA results show that the first principal component accounted for approximately 57% of the information, which contained the four seasonal rates and loaded highest and positively for autumn. K-means cluster analysis indicates that the seasonality of RRV is characterised by three groups with high, medium and low incidence of disease, and it suggests that there are at least three different disease ecologies. The variation in spatio-temporal patterns of RRV indicates a complex ecology that is unlikely to be explained by a single dominant transmission route across these three groupings. Therefore, there is need to explore socio-economic and environmental determinants of RRV disease at the statistical local area (SLA) level. Spatial distribution analysis and multiple negative binomial regression models were employed to identify the socio-economic and environmental determinants of RRV disease at both the city and local (ie, SLA) levels. The results show that RRV activity was primarily concentrated in the northeast, northwest and southeast areas in Brisbane. The negative binomial regression models reveal that RRV incidence for the whole of the Brisbane area was significantly associated with Southern Oscillation Index (SOI) at a lag of 3 months (Relative Risk (RR): 1.12; 95% confidence interval (CI): 1.06 - 1.17), the proportion of people with lower levels of education (RR: 1.02; 95% CI: 1.01 - 1.03), the proportion of labour workers (RR: 0.97; 95% CI: 0.95 - 1.00) and vegetation density (RR: 1.02; 95% CI: 1.00 - 1.04). However, RRV incidence for high risk areas (ie, SLAs with higher incidence of RRV) was significantly associated with mosquito density (RR: 1.01; 95% CI: 1.00 - 1.01), SOI at a lag of 3 months (RR: 1.48; 95% CI: 1.23 - 1.78), human population density (RR: 3.77; 95% CI: 1.35 - 10.51), the proportion of indigenous population (RR: 0.56; 95% CI: 0.37 - 0.87) and the proportion of overseas visitors (RR: 0.57; 95% CI: 0.35 - 0.92). It is acknowledged that some of these risk factors, while statistically significant, are small in magnitude. However, given the high incidence of RRV, they may still be important in practice. The results of this study suggest that the spatial pattern of RRV disease in Brisbane is determined by a combination of ecological, socio-economic and environmental factors. The possibility of developing an epidemic forecasting system for RRV disease was explored using the multivariate Seasonal Auto-regressive Integrated Moving Average (SARIMA) technique. The results of this study suggest that climatic variability, particularly precipitation, may have played a significant role in the transmission of RRV disease in Brisbane. This finding cannot entirely be explained by confounding factors such as other socio-ecological conditions because they have been unlikely to change dramatically on a monthly time scale in this city over the past two decades. SARIMA models show that monthly precipitation at a lag 2 months (=0.004,p=0.031) was statistically significantly associated with RRV disease. It suggests that there may be 50 more cases a year for an increase of 100 mm precipitation on average in Brisbane. The predictive values in the model were generally consistent with actual values (root-mean-square error (RMSE): 1.96). Therefore, this model may have applications as a decision support tool in disease control and risk-management planning programs in Brisbane. The Polynomial distributed lag (PDL) time series regression models were performed to examine the associations between rainfall, mosquito density and the occurrence of RRV after adjusting for season and auto-correlation. The PDL model was used because rainfall and mosquito density can affect not merely RRV occurring in the same month, but in several subsequent months. The rationale for the use of the PDL technique is that it increases the precision of the estimates. We developed an epidemic forecasting model to predict incidence of RRV disease. The results show that 95% and 85% of the variation in the RRV disease was accounted for by the mosquito density and rainfall, respectively. The predictive values in the model were generally consistent with actual values (RMSE: 1.25). The model diagnosis reveals that the residuals were randomly distributed with no significant auto-correlation. The results of this study suggest that PDL models may be better than SARIMA models (R-square increased and RMSE decreased). The findings of this study may facilitate the development of early warning systems for the control and prevention of this widespread disease. Further analyses were conducted using classification trees to identify major mosquito species of Ross River virus (RRV) transmission and explore the threshold of mosquito density for RRV disease in Brisbane, Australia. The results show that Ochlerotatus vigilax (RR: 1.028; 95% CI: 1.001 - 1.057) and Culex annulirostris (RR: 1.013, 95% CI: 1.003 - 1.023) were significantly associated with RRV disease cycles at a lag of 1 month. The presence of RRV was associated with average monthly mosquito density of 72 Ochlerotatus vigilax and 52 Culex annulirostris per light trap. These results may also have applications as a decision support tool in disease control and risk management planning programs. As RRV has significant impact on population health, industry, and tourism, it is important to develop an epidemic forecast system for this disease. The results of this study show the disease surveillance data can be integrated with social, biological and environmental databases. These data can provide additional input into the development of epidemic forecasting models. These attempts may have significant implications in environmental health decision-making and practices, and may help health authorities determine public health priorities more wisely and use resources more effectively and efficiently.