The present elemental analysis workhorse worldwide is Inductively Coupled Plasma (ICP) Atomic Emission Spectrometry (AES) and Mass Spectrometry (MS). Due to the high power requirements, large gas consumption and the more obvious attribute, size, the ICP is tethered to the lab. Usually, samples must be collected, bottled, sometimes stabilized by acids and then shipped back to the lab for analysis (hours to days to weeks turnover rate). Due to the demand for a portable analyzer this thesis will focus on further development of microplasma devices (MPDs) for portable on-site analysis, in (near) real-time. Mini-In-Torch Vapourization (mini-ITV) is the sample introduction method for MPDs which removes the need for sample preparation (further necessitates portability). Mini-ITV introduces the sample into the MPD via electrothermal vapourization of a dry (water-free) nano- to micro- volume sample. Pneumatic nebulization, the commercially available ICP sample introduction method would extinguish the microplasma. Microplasma stability is the first issue addressed by confining the microplasma to a quartz tube (“wall-stabilized”) in hopes of a more stable MPD background emission. Once stabilized MPD conditions were found key microplasma parameters were studied including MPD power, HVac frequency, operating mode, inter-electrode distance (IED) and observation location, in hopes of improved MPD analytical performance. Microplasma excitation mechanism and maximum energy available in the microplasma for analyte are discussed. Some fundamental characteristics such as excitation temperature (Texc) and changes in atom/ion population with variation in some of the key MPD parameters were also determined.

This thesis compared macrotexture measurements obtained using the volumetric method (Sand Patch) and three laser-based devices: MGPS system, ICC laser profiler, and Circular Texture Meter (CTMeter). The study used data from three sources: two controlled experiments conducted at the Virginia Smart Road, field data collected on eight newly constructed hot-mix-asphalt (HMA) roadway surfaces, and data collected on airport surfaces at the Wallops flight facility, Virginia. The data collected at the Virginia Smart Road, a controlled-access two-lane road that includes various HMA and concrete surfaces, was used for the main analysis. The other two sets of data were used for verification and validation of the model developed. The analysis of the data collected at the Virginia Smart Road showed that the CTMeter mean profile depth (MPD) has the highest correlation with the volumetric (Sand Patch) mean texture depth (MTD). Furthermore, texture convexity had a significant effect on the correlation between the measurements obtained with different devices. Two sets of models for converting the laser-based texture measurements to an estimated MTD (ETD) were developed. One set of equations considered all the data collected at the Virginia Smart Road, and the other excluded the measurements on the Open-Graded Friction Course (OGFC). The developed models were tested using measurements collected at eight roadway sections throughout Virginia and the Wallops flight facility. The model, excluding the OGFC section, was successfully applied to other sites. / Master of Science

The content of this master thesis project is about design and implementation of intelligent client application for Music Player Daemon (MPD), which searches and presents the metadata related to played content. The actual design precedes the theoretical analysis, which includes analysis of agent systems, methods of data classification, web communication protocols and languages for describing HTML document. At the same time is analyzed the MPD server and communication protocol used by clients application. Furthermore, this work describes the current client applications that presents metadata. In the last chapters of the thesis describes the design and implementation of intelligent client. It describes the methods of solution the implementation and solution of problems. Lastest chapters describes the testing result.

In the context of an ever-changing global environment, organisations must strive even harder than before to inspire employees to deliver outstanding results that will lead to a sustainable future. Engaged employees will deliver long term value, but most will not reach their full potential without a manager who understands and is committed to increase engagement in others. Managers are the key influencers to create meaningful engagements. The aim of this study was to investigate if employees’ experience of their managers as people developer (MPD) will have an effect on work engagement, and if work engagement will have an effect on subjective well-being, performance and turnover intention. The study also considered the possible mediating effect of work engagement. The primary focus therefore has been on the relationship between MPD and work engagement. Secondly, the study examined the relationship between MPD, subjective well-being, performance and turnover. The study followed a descriptive, cross-sectional and quantitative approach. The following measuring instruments were used: the Leader Empower Behaviour Questionnaire (LEBQ), the Empowering Leadership Questionnaire (ELQ), the Work Engagement Scale (WES), the Turnover Intention Scale (TIS), the Satisfaction with Life Scale (SWLS), the Affect Balance Scale (ABS), and the organisations performance rating scale. These instruments were used to test whether the measures of the constructs were consistent with the understanding of the nature of the constructs; also whether the data fitted the hypothesised measurement model. Structural Equation Modelling (SEM) was used to examine the structural relationships between the constructs. The results showed that significant relationships existed between MPD and work engagement, subjective well-being, performance and turnover intention. No significant relationship was found x between performance and turnover intention, and performance and subjective well-being. Regression analyses indicated that MPD had significant predictive value towards work engagement and turnover intention, and work engagement had significant predictive value towards turnover intention, subjective well-being and performance. An indirect effect was found from MPD (via work engagement) on subjective well-being and turnover intention, but an indirect effect from MPD on performance (via work engagement) was not found. Work engagement was found to have a direct effect on performance. It was therefore found that work engagement was a strong antecedent to subjective well-being and turnover intention. The implication of the results is that where managers coach and develop employees, it will lead to higher levels of work engagement and lower levels of turnover intention. / MA (Industrial Psychology)--North-West University, Vaal Triangle Campus, 2015.

In the context of an ever-changing global environment, organisations must strive even harder than before to inspire employees to deliver outstanding results that will lead to a sustainable future. Engaged employees will deliver long term value, but most will not reach their full potential without a manager who understands and is committed to increase engagement in others. Managers are the key influencers to create meaningful engagements. The aim of this study was to investigate if employees’ experience of their managers as people developer (MPD) will have an effect on work engagement, and if work engagement will have an effect on subjective well-being, performance and turnover intention. The study also considered the possible mediating effect of work engagement. The primary focus therefore has been on the relationship between MPD and work engagement. Secondly, the study examined the relationship between MPD, subjective well-being, performance and turnover. The study followed a descriptive, cross-sectional and quantitative approach. The following measuring instruments were used: the Leader Empower Behaviour Questionnaire (LEBQ), the Empowering Leadership Questionnaire (ELQ), the Work Engagement Scale (WES), the Turnover Intention Scale (TIS), the Satisfaction with Life Scale (SWLS), the Affect Balance Scale (ABS), and the organisations performance rating scale. These instruments were used to test whether the measures of the constructs were consistent with the understanding of the nature of the constructs; also whether the data fitted the hypothesised measurement model. Structural Equation Modelling (SEM) was used to examine the structural relationships between the constructs. The results showed that significant relationships existed between MPD and work engagement, subjective well-being, performance and turnover intention. No significant relationship was found x between performance and turnover intention, and performance and subjective well-being. Regression analyses indicated that MPD had significant predictive value towards work engagement and turnover intention, and work engagement had significant predictive value towards turnover intention, subjective well-being and performance. An indirect effect was found from MPD (via work engagement) on subjective well-being and turnover intention, but an indirect effect from MPD on performance (via work engagement) was not found. Work engagement was found to have a direct effect on performance. It was therefore found that work engagement was a strong antecedent to subjective well-being and turnover intention. The implication of the results is that where managers coach and develop employees, it will lead to higher levels of work engagement and lower levels of turnover intention. / MA (Industrial Psychology)--North-West University, Vaal Triangle Campus, 2015.

Les processus décisionnels de Markov (MDPs) modélisent des problèmes de décisionsséquentielles dans lesquels un utilisateur interagit avec l’environnement et adapte soncomportement en prenant en compte les signaux de récompense numérique reçus. La solutiond’unMDP se ramène à formuler le comportement de l’utilisateur dans l’environnementà l’aide d’une fonction de politique qui spécifie quelle action choisir dans chaque situation.Dans de nombreux problèmes de décision du monde réel, les utilisateurs ont despréférences différentes, donc, les gains de leurs actions sur les états sont différents et devraientêtre re-décodés pour chaque utilisateur. Dans cette thèse, nous nous intéressonsà la résolution des MDPs pour les utilisateurs ayant des préférences différentes.Nous utilisons un modèle nommé MDP à Valeur vectorielle (VMDP) avec des récompensesvectorielles. Nous proposons un algorithme de recherche-propagation qui permetd’attribuer une fonction de valeur vectorielle à chaque politique et de caractériser chaqueutilisateur par un vecteur de préférences sur l’ensemble des fonctions de valeur, où levecteur de préférence satisfait les priorités de l’utilisateur. Etant donné que le vecteurde préférences d’utilisateur n’est pas connu, nous présentons plusieurs méthodes pourrésoudre des MDP tout en approximant le vecteur de préférence de l’utilisateur.Nous introduisons deux algorithmes qui réduisent le nombre de requêtes nécessairespour trouver la politique optimale d’un utilisateur: 1) Un algorithme de recherchepropagation,où nous propageons un ensemble de politiques optimales possibles pourle MDP donné sans connaître les préférences de l’utilisateur. 2) Un algorithme interactifd’itération de la valeur (IVI) sur les MDPs, nommé algorithme d’itération de la valeurbasé sur les avantages (ABVI) qui utilise le clustering et le regroupement des avantages.Nous montrons également comment l’algorithme ABVI fonctionne correctement pourdeux types d’utilisateurs différents: confiant et incertain.Nous travaillons finalement sur une méthode d’approximation par critére de regret minimaxcomme méthode pour trouver la politique optimale tenant compte des informationslimitées sur les préférences de l’utilisateur. Dans ce système, tous les objectifs possiblessont simplement bornés entre deux limites supérieure et inférieure tandis que le systèmeine connaît pas les préférences de l’utilisateur parmi ceux-ci. Nous proposons une méthodeheuristique d’approximation par critère de regret minimax pour résoudre des MDPsavec des récompenses inconnues. Cette méthode est plus rapide et moins complexe queles méthodes existantes dans la littérature. / Markov decision processes (MDPs) are models for solving sequential decision problemswhere a user interacts with the environment and adapts her policy by taking numericalreward signals into account. The solution of an MDP reduces to formulate the userbehavior in the environment with a policy function that specifies which action to choose ineach situation. In many real world decision problems, the users have various preferences,and therefore, the gain of actions on states are different and should be re-decoded foreach user. In this dissertation, we are interested in solving MDPs for users with differentpreferences.We use a model named Vector-valued MDP (VMDP) with vector rewards. We propose apropagation-search algorithm that allows to assign a vector-value function to each policyand identify each user with a preference vector on the existing set of preferences wherethe preference vector satisfies the user priorities. Since the user preference vector is notknown we present several methods for solving VMDPs while approximating the user’spreference vector.We introduce two algorithms that reduce the number of queries needed to find the optimalpolicy of a user: 1) A propagation-search algorithm, where we propagate a setof possible optimal policies for the given MDP without knowing the user’s preferences.2) An interactive value iteration algorithm (IVI) on VMDPs, namely Advantage-basedValue Iteration (ABVI) algorithm that uses clustering and regrouping advantages. Wealso demonstrate how ABVI algorithm works properly for two different types of users:confident and uncertain.We finally work on a minimax regret approximation method as a method for findingthe optimal policy w.r.t the limited information about user’s preferences. All possibleobjectives in the system are just bounded between two higher and lower bounds while thesystem is not aware of user’s preferences among them. We propose an heuristic minimaxregret approximation method for solving MDPs with unknown rewards that is faster andless complex than the existing methods in the literature.

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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Hot Mix Asphalt (HMA) design has undergone years of development. Currently, many state agencies use the Superpave mix design method. While the Superpave mix design improved rutting, the implemented level 1 only considered volumetric properties and not mixture performance tests. Therefore, development in the asphalt community has addressed some of the issues with the Superpave mix design, e.g., cracking and raveling, with the Balance Mix Design (BMD) approaches. The Balance Mix Design incorporates performance testing elements that the level 1 Superpave mix design does not. The Virginia Department of Transportation (VDOT) aims to implement the Balance Mix Design by 2023. The objective of this thesis is to evaluate the initial frictional properties of mixes designed using the Balanced Mix Design method to verify that safety is not compromised to support the implementation of the BMD method within VDOT. It provides a further understanding of BMD mixtures surface properties provides insight into volumetric properties that may influence macrotexture. The thesis analyzed the initial friction and macrotexture of a series of experimental sections built to support VDOT BMD implementation efforts. A Side-Force Coefficient Road Investigation Machine (SCRIM) was used to measure friction and texture data on Control (Superpave Mix Design) and Balance Mix Design sections on several VDOT districts. Once the data was collected, it was analyzed using descriptive statistics and mean comparisons to determine any statistical differences in the friction and texture of the Control and BMD Mixes. The analysis showed that although statistically significant differences in friction and macrotexture were observed between some of the Superpave (Control) and Balance Mix Design mixes, the differences seem to be more prominent among districts than between the mix design method. In general, there were no difference in friction between control and BMD mixes in the same locations. On the other hand, there is statistically significant differences in the as-constructed macrotexture of Superpave and BMD mixes evaluated, with more BMD mixes having higher macrotexture than their control counterparts. Further analysis was conducted to create a macrotexture prediction model based on production volumetric properties obtained from VDOT databases. The model provided an initial assessment of the main HMA properties that influence MPD. A comparison of the macrotexture of the constructed in the various locations found that there is strong statistical evidence that the mean macrotexture of the pavement constructed in the various location was different. The analysis also showed that some projects produced sections with more uniform macrotexture than others. Comparison of mixes constructed in different years does not suggest any significant differences over the three-construction season evaluated. / Master of Science / Hot Mix Asphalt (HMA) is derived from various mix designs over the last hundred years. Currently, many highway agencies use the Superpave Mix Design in roadway development but only his basic level has been implemented. Most agencies do not use mechanical tests to verify that the mixes will perform properly when place on the pavement. To address some of issues with the current mix design approach, highway agencies have started to implement and use the Balance Mix Design (BMD). The Balance Mix Design incorporates performance tests for distresses such as rutting and cracking where the Superpave Mix Design did not. The Virginia Department of Transportation (VDOT) is working towards implementing the Balance Mix Design by 2023. The objective of this thesis is to evaluate the initial frictional properties of mixes designed using the Balanced Mix Design method to verify that safety is not compromised to support the implementation of the BMD method within VDOT. It helps agencies understand of BMD mixtures surface properties and what mix design properties may influence the safety of the road surface. The thesis analyzed the initial friction and macrotexture, properties that allow the vehicles to break and maintain control on curves, of a series of experimental sections built to support VDOT BMD implementation efforts. The Side-Force Coefficient Road Investigation Machine (SCRIM) is a large vehicle that continuously measures the pavement surface for friction, texture, and other elements using a skewed wheel and a laser system. The SCRIM was used in this thesis to measure friction and texture data on Control (Superpave Mix Design) and Balance Mix Design sections constructed on several VDOT districts. The data were analyzed using statistical analysis to determine any differences in the friction and texture of the Control and BMD Mixes. In general, there are no differences in friction between control and BMD mixes in the same locations. On the other hand, the analysis showed significant differences in the as-constructed macrotexture of Superpave and BMD mixes evaluated. In general, more BMD mixes had higher macrotexture than their control counterparts. Further analysis was conducted to create a macrotexture prediction model based on production volumetric properties obtained from VDOT databases. A comparison of the macrotexture of the constructed in the various locations found that there is strong statistical evidence that the average macrotexture of the pavement constructed in the various location was different.

O Processamento e Análise Digital de Imagens é utilizado cada vez mais para agilizar processos, aumentar a precisão, segurança e confiabilidade de dados extraídos de imagens nas mais diversas áreas de pesquisa. No entanto, muitas vezes é necessário que o pesquisador faça, ele próprio, o pré-processamento das imagens, mesmo não sendo um especialista nesta área. Isto coloca em risco o próprio objetivo do uso do Processamento e Análise Digital de Imagens. Este trabalho analisa a relação dos dados extraídos de uma imagem (micrografia) através do software livre ImageJ com relação ao seu processamento final desejado, avaliando assim, a necessidade ou não, de uma ou mais sequencias de pré-processamento para adequar a imagem para o processamento final, indicando ainda quais fatores de influência apresentam informações irrelevantes ou incompletas para o processamento final utilizando ferramentas da Lógica Paraconsistente Anotada. Os resultados obtidos mostram que esta abordagem carece de informações diversificadas sobre a imagem original capturada que possam subsidiar a tomada de decisão quanto aos procedimentos necessários e, para o pré-processamento adequado ao objetivo desejado. / Processing and Analysis of Digital Images is increasingly used to streamline processes, improve accuracy, safety and reliability of data extracted from images in various research areas. However, it is often necessary for the researcher to make himself, the preprocessing of images, although not an expert in this area. This puts at risk the very purpose of using the Processing and Analysis of Digital Images. This paper analyzes the relationship of the data extracted from an image (micrograph) through the free software ImageJ, with respect to its desired final processing. Thus, evaluating the necessity or not, of one or more sequences of preprocessing to adjust the image to the final processing, further indicating which factors influence presents incomplete or irrelevant information for final processing using tools of Annotaded Paraconsistent Logic. The results show that this approach lacks diversified information about the original image captured that can support decision making about procedures for appropriate preprocessing to the desired goal.