Dans les domaines de la modélisation et de la simulation numérique, les simulateurs développés prennent parfois en compte de nombreux paramètres dont l'impact sur les sorties n'est pas toujours bien connu. L'objectif principal de l'analyse de sensibilité est d'aider à mieux comprendre comment les sorties d'un modèle sont sensibles aux variations de ces paramètres. L'approche la mieux adaptée pour appréhender ce problème dans le cas de modèles potentiellement complexes et fortement non linéaires repose sur la décomposition ANOVA et les indices de Sobol'. En particulier, ces derniers permettent de quantifier l'influence de chacun des paramètres sur la réponse du modèle. Dans cette thèse, nous nous intéressons au problème de l'estimation des indices de Sobol'. Dans une première partie, nous réintroduisons de manière rigoureuse des méthodes existantes au regard de l'analyse harmonique discrète sur des groupes cycliques et des tableaux orthogonaux randomisés. Cela nous permet d'étudier les propriétés théoriques de ces méthodes et de les généraliser. Dans un second temps, nous considérons la méthode de Monte Carlo spécifique à l'estimation des indices de Sobol' et nous introduisons une nouvelle approche permettant de l'améliorer. Cette amélioration est construite autour des hypercubes latins et permet de réduire le nombre de simulations nécessaires pour estimer les indices de Sobol' par cette méthode. En parallèle, nous mettons en pratique ces différentes méthodes sur un modèle d'écosystème marin.

Recruitment of pelagic fish populations is believed to be regulated during the planktonic larval stage due to high rates of mortality during the early life stages. Starvation is thought to be one of the main sources of mortality, despite the fact that there is rarely a strong correlation between the feeding success of larval fish and food availability as measured in the field. This lack of relationship may be caused in part by (i) inadequate sampling of larval fish prey and (ii) the use of total zooplankton abundance or biomass as proxies for larval food availability. Many feeding studies rely on measures of average prey abundance which do not adequately capture the variability, or patchiness, of the prey field as experienced by larval fish. Previous studies have shown that larvae may rely on these patches to increase their feeding success. I assess the variability in the availability of larval fish prey over a range of scales and model the small-scale distribution of prey in Conception Bay, Newfoundland. I show that the greatest variability in zooplankton abundance existed at the meter scale, and that larval fish prey were not randomly distributed within the upper mixed layer. This will impact both how well we can model the stochastic nature of larval fish cohorts, as well as how well we can study larval fish feeding from gut content analyses. Expanding on six years of previous lab and field studies on larval Radiated Shanny (Ulvaria subbifurcata) from Conception Bay, Newfoundland, I assess the feeding success, niche breadth (S) and weight-specific feeding rates (SPC, d-1) of the larvae to determine whether there are size-based patterns evident across the years. I found that both the amount of food in the guts and the niche breadth of larvae increased with larval size. There was a shift from low to high SPC with increasing larval size, suggesting that foraging success increases as the larvae grow. My results suggest that efforts should be made to estimate the variability of prey abundance at scales relevant to larval fish foraging rather than using large-scale average abundance estimates, since small-scale prey patchiness likely plays a role in larval fish feeding dynamics. In addition, the characteristics of zooplankton (density, size and behaviour) should be assessed as not all zooplankton are preyed upon equally by all sizes of larval fish. Overall, this thesis demonstrates that indices based on averages fail to account for the variability in the environment and in individual larval fish, which may be confounding the relationship between food availability and larval growth.

A trend in natural science and especially in analytical chemistry is the increasing need for analysis of a large number of complex samples with low analyte concentrations. Biological samples (urine, blood, plasma, cerebral spinal fluid, tissue etc.) are often suitable for analysis with liquid separation mass spectrometry (LS-MS), resulting in two-way data tables (time vs. m/z). Such biological 'fingerprints' taken for all samples in a study correspond to a large amount of data. Detailed characterization requires a high sampling rate in combination with high mass resolution and wide mass range, which presents a challenge in data handling and exploration. This thesis describes methods for managing and exploring large data sets made up of such detailed 'fingerprints' (represented as data matrices). The methods were implemented as scripts and functions in Matlab, a wide-spread environment for matrix manipulations. A single-file structure to hold the imported data facilitated both easy access and fast manipulation. Routines for baseline removal and noise reduction were intended to reduce the amount of data without loosing relevant information. A tool for visualizing and exploring single runs was also included. When comparing two or more 'fingerprints' they usually have to be aligned due to unintended shifts in analyte positions in time and m/z. A PCA-like multivariate method proved to be less sensitive to such shifts, and an ANOVA implementation made it easier to find systematic differences within the data sets. The above strategies and methods were applied to complex samples such as plasma, protein digests, and urine. The field of application included urine profiling (paracetamole intake; beverage effects), peptide mapping (different digestion protocols) and search for potential biomarkers (appendicitis diagnosis) . The influence of the experimental factors was visualized by PCA score plots as well as clustering diagrams (dendrograms).

Recruitment of pelagic fish populations is believed to be regulated during the planktonic larval stage due to high rates of mortality during the early life stages. Starvation is thought to be one of the main sources of mortality, despite the fact that there is rarely a strong correlation between the feeding success of larval fish and food availability as measured in the field. This lack of relationship may be caused in part by (i) inadequate sampling of larval fish prey and (ii) the use of total zooplankton abundance or biomass as proxies for larval food availability. Many feeding studies rely on measures of average prey abundance which do not adequately capture the variability, or patchiness, of the prey field as experienced by larval fish. Previous studies have shown that larvae may rely on these patches to increase their feeding success. I assess the variability in the availability of larval fish prey over a range of scales and model the small-scale distribution of prey in Conception Bay, Newfoundland. I show that the greatest variability in zooplankton abundance existed at the meter scale, and that larval fish prey were not randomly distributed within the upper mixed layer. This will impact both how well we can model the stochastic nature of larval fish cohorts, as well as how well we can study larval fish feeding from gut content analyses. Expanding on six years of previous lab and field studies on larval Radiated Shanny (Ulvaria subbifurcata) from Conception Bay, Newfoundland, I assess the feeding success, niche breadth (S) and weight-specific feeding rates (SPC, d-1) of the larvae to determine whether there are size-based patterns evident across the years. I found that both the amount of food in the guts and the niche breadth of larvae increased with larval size. There was a shift from low to high SPC with increasing larval size, suggesting that foraging success increases as the larvae grow. My results suggest that efforts should be made to estimate the variability of prey abundance at scales relevant to larval fish foraging rather than using large-scale average abundance estimates, since small-scale prey patchiness likely plays a role in larval fish feeding dynamics. In addition, the characteristics of zooplankton (density, size and behaviour) should be assessed as not all zooplankton are preyed upon equally by all sizes of larval fish. Overall, this thesis demonstrates that indices based on averages fail to account for the variability in the environment and in individual larval fish, which may be confounding the relationship between food availability and larval growth.

Social Capital and Open Innovation are important for organisational growth, as both of them influence Innovation, Learning and Job Satisfaction. The literature indicates that informal network measured as social capital and formal network measured as open innovation influences positively to organizational innovation performance, learning and job satisfaction. Most of the studies in this area have been carried out using univariate approaches, and only few dimensions of both Social Capital and Open Innovation have been considered. Current literature outlines the positive influence of Social Capital and Open Innovation on Learning, Innovation and Job Satisfaction. In this study, an attempt has been made to develop a multi-dimensional framework for Social Capital and Open Innovation, in order to better understand the nuances of Learning, Innovation and Job Satisfaction in an R&D setting. Another important factor influencing the R&D outcomes is Absorptive Capacity; it is the capacity of the organisation to identify and use external knowledge. The direct and moderating role of Absorptive Capacity has been examined. Both theoretical and conceptual models have been proposed, and a measurement scale in form of a questionnaire has been developed. Data was collected from 35 organisations across India operating in the field of defence R&D. The sample included Government-run R&D organisations, Public Sector Units (PSUs) and private firms, and total of 331 engineers/scientists responded to the survey. Data was analysed using statistical methods such as Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), Common Method Variance (CMV), and Analysis of Variance (ANOVA). Reliability and validity of the proposed scales for the constructs have been verified using appropriate techniques, and further inferences have been drawn by using regression techniques and Structural Equation Modeling (SEM) to assess the proposed relationships. It has been found that both Social Capital and Open Innovation have positive influence on Learning, Innovation and Job Satisfaction. Further, it was found that Absorptive Capacity had a positive association with both Innovation and Learning. However, Absorptive Capacity did not moderate the relationship of Social Capital with both Innovation and Learning, but was found to moderate the relationship between Open Innovation and Innovation, for both outbound and inbound approaches of Open Innovation. Bonding Social Capital had a relatively stronger positive association with Learning, while Bridging Social Capital was found to have a stronger relationship with Innovation. In summary, networking factors Social Capital and Open Innovation have strong positive association with R&D outcomes measured as innovation performance, learning and job satisfaction.

The basic purpose of this study was to examine the influence of service quality on customer satisfaction, perceived customer value and behavioral intentions, in three, four and five star hotels in Ethiopia. Additionally, an attempt was made to assess the differences pertaining to these constructs across customer profile (e.g., gender, nationality etc.) and hotel characteristics (e.g., star ratings etc.). A quantitative survey approach was used to obtain primary data from the respondents (hotels’ guests/customers) by administering the structured questionnaire. The original SERVPERF dimensions and related items were modified to best fit with hotel sector, by using desk review and preliminary interviews with manager, consultants and corporate clients of the hotels. A pilot study was carried out with 35 hotel customers to test the initial reliability and validity of the instrument. The final questionnaire was distributed to 440 respondents from 44 hotels (under three, four and five star categories), by using stratified (proportionate) random sampling. Of the distributed questionnaires, 435 were collected back (over 98% return rate), as completely filled, and used for the purpose of analysis. Descriptive statistics (mean score and standard deviation) were used to examine the customers’ perceptions of service quality, customer value, satisfaction and behavioral intentions. To identify the key service quality dimensions in the Ethiopian hotel sector, Principal Component Analysis (PCA) was employed. The results revealed six underlying factors, namely: Assurance, Reliability, Responsiveness, Empathy, Room Tangibles and Food & Beverage Tangibles. Regression analysis was carried out to examine the relationship between the study constructs, whereby perceived service quality was found to be maintaining significantly (p<0.05) positive influence on customer value, satisfaction and behavioral intentions (measured as customer revisits and word-of-mouth recommendations) in the Ethiopian hotel sector. Moreover, both customer value and satisfaction were observed to be partially mediating the influence of service quality on behavioral intentions, with higher contribution from satisfaction than perceived value. Finally, the respondents’ nationality, gender, visit purpose, length of stay, hotel location and star category were found to be determining their perceptions of overall service quality. However, further research is needed before generalizing these relationships to other sectors/contexts. / Business Management / D.B.L.

The purpose of this study was to explore solution strategies that can enhance the achievement of low-performing Grade 12 learners in the following mathematical aspects: finding the general term of a quadratic sequence, factorising third degree polynomials, determining the centre and radius of a circle, and calculating the angle between two lines. A convenience sample of twenty-five low-performing Grade 12 learners from a secondary school in Capricorn District of Limpopo Province participated in the study which adopted a repeated-measures research design. Learners were exposed to multiple solution strategies and data were collected using achievement tests. Findings indicated significant differences in learners‟ average scores due to the solution strategies used. In determining the general term of a quadratic sequence, learners‟ scores were significantly higher when they used formula and the table method than with the method of residues and solving simultaneous equations. Synthetic division made learners to achieve better scores than long division and equating coefficients in factorising third degree polynomials. The use of formulae to find the centre and radius of a circle made learners to have better achievement scores than completing the square. In calculating the angle between two lines learners‟ scores were better using formula and the cosine rule than using theorems. It was concluded that exposing low-performing Grade 12 learners to multiple solution strategies would enhance their achievement in the mathematical aspects explored in the study. Some of the solution strategies that made learners to achieve better results were not in the prescribed mathematics textbooks. The study therefore recommends that mathematics teaching should not be textbook-driven and that low-performing Grade 12 learners should not be regarded as beyond redemption. / Mathematics Education / M.Sc. (Mathematics, Science and Technology Education)

La diseguaglianza dei redditi è comunemente analizzata e misurata attraverso l’impiego di varie misure quali l’indice di Gini, il coefficiente di variazione, l’indice di Theil, la varianza dei logaritmi ed altri ancora (Sen, 1970). A partire dagli anni ’90 l’applicazione di tecniche di scomposizione relative, ad esempio, all’indice di Theil hanno reso possibile quantificare due diverse componenti della diseguaglianza ovvero la disuguaglianza legata allo sforzo individuale e la disuguaglianza dovuta alle ineguali opportunità. Questa seconda componente dipende esclusivamente da fattori esogeni, non controllabili dall’individuo, e, per questa ragione, è a ragione considerata una diseguaglianza “ingiusta”. Alla componente residua della scomposizione è di solito attribuito, invece, il significato di disuguaglianza nello sforzo, ovvero quanto ciascun individuo si è impegnato per raggiungere un determinato obiettivo di successo economico. L’applicazione di questo approccio alle misure di diseguaglianza ha permesso di studiare quale tipo di disuguaglianza prevalga all’interno di un Paese e, soprattutto, quali siano le circostanze esogene che incrementano la disparità nelle opportunità. Il presente lavoro si muove lungo questa linea di ricerca proponendo un metodo per testare il peso relativo delle due componenti e la loro significativita’. Come misura di diseguaglianza si e’ scelto di considerare il coefficiente di variazione in modo da ricondurre il test ad un problema di Analisi della varianza (ANOVA) a piu’ vie. Il test viene presentato facendo riferimento ai dati dell’ISTAT e dell'indagine Bankitalia sui redditi delle famiglie. Dopo quest'analisi preliminare sulle determinanti della diseguaglianza di opportunità in Italia, si utilizza la scomposizione della diseguaglianza nelle sue due componenti: diseguaglianza di opportunità e diseguaglianza legata all'impegno, per definire univocamente l'effetto della diseguaglianza sulla crescita economica. L'analisi econometria è svolta sui dati dell'indagine sulla ricchezza e sui redditi delle famiglie forniti dalla Banca d'Italia. L'effetto viene stimato utilizzando il modello panel dinamico con il metodo di stima GMM. / While the analysis of inequality has been central to economic studies for cen- turies, in recent years many studies concentrated on the distinction between in- equality of opportunity (IO) and inequality of returns to effort (IE) and attempted empirical estimates of the two components, e.g. in US and in Europe. The decompo- sition of a general inequality index into these two components allows to analyze the prevalence of fair or unfair income inequality within a country. This paper suggests to test the differences between the two sources of inequality in a simple way using the ANOVA framework adapted to decompose the coefficient of variation, to better suit the requirements of an inequality index. The proposed procedure is applied to the Italian Survey on Income and Living Condition (IT-SILC data, wave 2005 and 2011). The analysis of the results help identifying the circumstances that foster the rise of inequality of opportunities in Italy. Our analysis shows in particular, that father education, region of residence and gender result as the most relevant circumstances determining inequality of opportunity. On the other side, the role of mother education starting from a lower level, as an inequality of opportunity factor, is increasing its influence over time. The decomposition of inequality index in two components allows not only to analyze the prevalence of fair or unfair income inequality in a country, but also to find a clearer relation between inequality and growth. In fact, it is still missing an analysis of the relation between inequality of opportunity and economic growth in Italy. This paper aims at filling in that gap, by using Italian data from Bank of Italys Survey on Income and Wealth from 1998 to 2014. We choose the coefficient of variation to measure inequality of opportunity at the regional level and, then, we studied its relation with economic growth using Dynamic Panel Data models estimated through System- GMM. Finally, in order to check if the coefficient of variation could be a measure as good as the Entropy’s index, I will compare the results of the estimated panel models with the two different inequality of opportunity indeces. We evaluate the effect of inequality of opportunity on different length of the economic growth rate, going from a short term (2 years) to a very long term growth rate (10 years). Our results shows that, in Italy, inequality of opportunity is negative in the short period, but it does not have any effect on long run growth.

The eco-friendly alternatives use is increasing momentum in a conscious effort towards sustainability. In this regards, the relevance and the economic value of using copper slag as a concrete aggregate are explored in this study in order to contribute towards metallurgical waste recycling. Emphasis is placed on the evaluation of the concretes strengthening prepared with copper slag contents and produced under four curing methods: water immersion, water spraying, plastic sheet covering and air-drying. In each curing case excluding for water immersion, was duplicated in indoors (i.e. in the laboratory) and outdoor exposure (so was prone to varying environmental conditions). This was specifically aimed at capturing the effects of tropical weather conditions typical of the Lualaba province in the Democratic Republic of Congo. The control mix was designed to reach 25 MPa of compressive strength. Copper slag was successively incorporated as sand replacement at the following mass fractions: 20 %, 40 % and 60 %. Freshly mixed concrete samples were evaluated for workability. Cube specimens were cast accordingly, cured for 28 days and then tested for density and compressive strength. Results indicated an increase in strength up to 20 % of replacement rate for all the curing methods. Further additions resulted in reduction in the strength, but the rate of reduction depended on curing conditions. The increase in strength was mainly credited to the physical properties of copper slag that could have contributed to the cohesion of the concrete matrix. It has been found that appropriate ways of curing can still achieve greater results than that of the control mix since 80 % of humidity is ensure. The two-way ANOVA test performed on the 28-days compressive strength values confirmed the significant influence of the curing methods, of copper slag content and the interaction between them. It has been found that considerable influence is attributed to copper slag content and that warm environmental conditions further extend the concrete strengthening. / College of Engineering, Science and Technology / M. Tech. (Chemical Engineering)

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