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This paper applies and extends Machado and Mata's parametric quantile decomposition method and a similar nonparametric technique to explore changes in welfare in Zimbabwe between 1995 and 2001. These methods allow us to construct a counterfactual distribution in order to decompose the shift into the part due to changes in endowments and that due to changes in returns. We examine two subsets of a nationally representative dataset and find that endowments had a positive effect but that returns account for more of the difference. In communal farming areas, the effect of returns was positive while, in urban Harare, it was negative. / Master of Science

Electronic textiles provide an effective platform to contain wearable computing elements, especially components geared towards the application of activity recognition. An activity recogni tion system built into a wearable textile substrate can be utilized in a variety of areas including health monitoring, military applications, entertainment, and fashion. Many of the activity recognition and motion capture systems previously developed have several drawbacks and limitations with regard to their respective designs and implementations. Some such systems are often times expensive, not conducive to mass production, and may be difficult to calibrate. An effective system must also be scalable and should be deployable in a variety of environments and contexts. This thesis presents the design and implementation of a self-contained motion sensing wearable electronic textile system with an emphasis toward the application of activity recognition. The system is developed with scalability and deployability in mind, and as such, utilizes a two-tier hierarchical model combined with a network infrastructure and wireless connectivity. An example prototype system, in the form of a jumpsuit garment, is presented and is constructed from relatively inexpensive components and materials. / Master of Science

No / This paper presents a new approach to estimate the unknown frequencies of the constituent sinusoids in a noiseless signal. The signal comprising of unknown number of sinusoids of unknown amplitudes and unknown phases is measured in the time domain. The Hankel matrix of measured samples is used as a basis for further analysis in the Pisarenko harmonic decomposition. A new constraint, the Existence Factor (EF), has been introduced in the methodology based on the relationship between the frequencies of the unknown sinusoids and the eigenspace of Hankel matrix of signal's samples. The accuracy of the method has been tested through multiple simulations on different signals with an unknown number of sinusoidal components. Results showed that the proposed method has efficiently estimated all the unknown frequencies.

This dissertation consists of three essays studying the occupational wages, skills, and gender wage gap in U.S. and other OECD countries. The analysis especially focuses on how the gender differences in skill levels and skill returns could explain the gender wage gaps and changes. The first chapter outlines the dissertation by briefly discussing the motivations, methods, and main findings in each of the following chapters. Chapter 2 focuses on the well-documented wage and employment polarizations in the U.S.. The occupations moving into the lower tail ("in" occupations) have more immigrant workers, more part-time workers, and less female workers. In addition, the wage gaps between domestic/immigrant, full-time/part-time, and male/female workers are also larger in "in" occupations. The opposite facts hold true in the occupations moving out of the lower tail ("out" occupations). Utilizing the regional differences, we also find stronger spillover effect from high-wage occupations to the "out" occupations than the effect to the "in" occupations. Chapter 3 investigates how gender differences in skills beyond education and experience can account for the observed gender wage gap and its changes between 1980 and 2015 by using data from the Dictionary of Occupational Titles (DOT) and the Occupational Information Network (O*NET). The main empirical finding is that female workers possess much higher level of caring skills, and the returns to caring skills are significantly negative but have increased over time, accounting for a major part of the persistent gender wage gap and the narrowing gender wage gap from 1980 to 2015. Another significant portion of the narrowed gender wage gap can be attributed to the faster growth in female workers' average directness skills and the fact that the returns to directness skills are significantly positive and stable over time. In the last chapter, we document significant cross-country variation in gender wage gaps among OECD countries by using the data from Survey of Adult Skills (PIAAC). We find significant cross-country variation in the gender differences in returns. The gender differences in returns to basic labor and experience are the most important factors in explaining the gender wage gap. In addition, gender differences in returns to cognitive and directness skills are playing milder but substantial roles in explaining the wage gap. We also find the social institutions and attitudes indicators are related to the cross-country variation in gender differences. / Ph. D. / This dissertation makes effort to understand the changes in wages in the U.S. and other OECD countries. I focus on two important features of the changes, namely, wage polarization and change in gender wage gap. Wage polarization describes the uneven changes in wages in different occupations; there is fast wage growth in the high-wage occupations, mild wage growth in the low-wage occupations, and slow even negative wage growth in middle-wage occupations. The analysis shows that technology advancement has increased the productivity of the high-wage occupations. Therefore, the wages in these occupations also increase. Meanwhile, there is strong spillover effect from the high-wage occupations to the low-wage occupations because low-wage occupations mostly provide services to the high-wage occupations. The spillover effect is the most likely cause on the wage growth in the low-wage occupations. In contrast, jobs in the middle-wage occupations are crowded out by the technology advancement. This harms the wage growth in these occupations. Gender wage gap is defined as the gender difference in the social average wages. In the U.S., female workers only earned 55% of what male workers earned in 1980. This number has increased to 70%. In our analysis, we argue that genders have different skills in the daily interaction with people. Female workers have much stronger skills in caring for others. However, this caring skills are negatively rewarded. Fortunately, the rewards to the caring skills are increasing. The negative reward to caring skills and changes in the rewards could account for the remaining gender wage gap and its change. Gender wage gap also presents a significant cross-country variation. Slovenia has gender wage gap at a level of 4% but Japan has a level of 40%. The analysis shows that potential explanation to the variation is social institutions and social attitudes. In a society emphasizing on competition or providing better benefits to maternity leaves, low-skill female workers are more likely to receive lower average wages.

Ammonia decomposition plays a crucial role in various industrial and environmental processes, including the production of hydrogen, clean energy storage. Plasma catalysis presents a promising option that utilizes the unique properties of plasma to drive chemical reactions at a lower temperature than traditional methods. This study examines the effectiveness of plasma catalysis for ammonia decomposition on ruthenium (Ru) supported on alumina (Al₂O₃) as the catalyst. The research indicates that the catalytic performance of Ru is significantly impacted by its loading on the alumina support. The study identifies optimal Ru loading conditions, which lead to substantial improvements in ammonia decomposition. The incorporation of alkali metal promoters, such as sodium (Na), potassium (K), lithium (Li), and cesium (Cs), enhances the catalytic activity, especially at lower Ru loadings (0.01%). This study highlights the potential of Ru-based catalysts with alkali metal promoters in plasma catalytic systems for efficient ammonia decomposition.

The ultimate goal of this work is to facilitate the design of gas turbine engine particle separators by reducing the computational expense to accurately simulate the fluid flow and particle motion inside the separator. It has been well-documented that particle ingestion yields many detrimental impacts for gas turbine engines. The consequences of ice particle ingestion can range from surface-wear abrasion to engine power loss. It is known that sufficiently small particles, characterized by small particle response times (τp), closely follow the fluid trajectory whereas large particles deviate from the streamlines. Rather than manually deriving how the particle acceleration varies from the fluid acceleration, this work chooses to implicitly derive this relationship using machine learning (ML). Inertial particle separators are devices designed to remove particles from the engine intake flow, which contributes to both elongating the lifespan and promoting safer operation of aviation gas turbine engines. Complex flows, such as flow through a particle separator, naturally have rotation and strain present throughout the flow field. This study attempts to understand if the motion of particles within rotational and strained canonical flows can be accurately predicted using supervised ML. This report suggests that preprocessing the ML training data to the fluid streamline coordinates can improve model training. ML models were developed for predicting particle acceleration in laminar, fully rotational/irrotational flows and combined laminar flows with rotation and strain. Lastly, the ML model is applied to particle data extracted from a Computational Fluid Dynamics (CFD) study of particle-laden flow around a louver-geometry. However, the model trained with particle data from combined canonical flows fails to accurately predict particle accelerations in the CFD flow field. / Master of Science / Aviation gas turbine engine particle ingestion is known to reduce engine lifespans and even pose a threat to safe operation in the worst case. Particles being ingested into an engine can be modeled using multiphase flow techniques. Devices called inertial particle separators are designed to remove particles from the flow into the engine. One challenge with designing such a separator is figuring out how to efficiently expel the small particles from the flow while not unnecessarily increasing pressure loss with excessive twists and turns in the geometry. Designers usually have to develop such geometries using multiphase flow computational fluid dynamics (CFD) that solve the fluid and particle dynamics. The abundance of data associated with CFD, and especially multiphase flows make it an ideal application to study with machine learning (ML). Because such multiphase simulations are very computationally expensive, it is desirable to develop "cheaper" methods. This is the long term goal of this work; we want to create ML surrogates that decrease the computational cost of simulating the particle and fluid flow in particle separator geometries such that designs can be iterated more quickly. In this work we introduce how artificial neural networks (ANNs), which are a tool used in ML, can be used to predict particle acceleration in fluid flow. The ANNs are shown to learn the acceleration predictions with acceptable accuracy for the training data generated with canonical flow cases. However, the ML model struggles to become generalizable to actual CFD simulations.

Thesis (MSc)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: Inorganic fertilizer applications are common practice in commercial agriculture, yet not much is known regarding their interaction with organic matter and soil biota. Much research has been done on the effect of inorganic N on forest litter decomposition, yet very little research has focused on the effect of inorganic fertilizers on crop litters and, to our knowledge, none on composted organic matter. Furthermore none of the research has been done in South Africa. The main aim of this research project was to determine the effect of inorganic fertilizer applications on the decomposition of selected organic matter sources commonly used in South African agriculture and forestry. Two decomposition studies were conducted over a 3-month period, one on composts and the other on plant litters, using a local, sandy soil. In the first experiment a lower quality compost, compost A (C:N ratio, 17.67), and higher quality compost, compost B (C:N ratio, 4.92) was treated with three commercially used fertilizer treatments. Two were typical blends used for vegetable (tomato and cabbage) production: tomato fertilizer (10:2:15) (100 kg N, 20 kg P, 150 kg K per ha) and cabbage fertilizer (5:2:4) (250 kg N, 100 kg P, 200 kg K per ha). The third fertilizer blend, an equivalent mass application of N and P applied at 150 kg of each element per ha, is more commonly used in pastures. In the second experiment, five commonly encountered crop and forestry litters, namely kikuyu grass, lucerne residues, pine needles, sugar cane trash and wheat straw, were selected to represent the labile organic matter sources. The litters were treated with the tomato and cabbage fertilizer applications rates. Both decomposition experiments were conducted under ambient laboratory conditions at field water capacity. Decomposition rates were monitored by determining CO2 emissions, DOC production, β-glucosidase and polyphenol oxidase activity (PPO). At the start and end of decomposition study, loss on ignition was performed to assess the total loss of OM. Based on the results obtained from these two experiments, it was concluded that the addition of high N containing inorganic fertilizers enhanced the decomposition of both composted and labile organic matter. For both compost and plant litters, DOC production was greatly enhanced with the addition of inorganic fertilizers regardless of the organic matter quality. The conclusion can be made that inherent N in organic matter played a role in the response of decomposition to inorganic fertilizer application with organic matter low in inherent N showing greater responses in decomposition changes. For labile organic matter polyphenol and cellulose content also played a role in the responses observed from inorganic fertilizer applications. / AFRIKAANSE OPSOMMING: Anorganiese kunsmis toedieningss is algemene praktyk in die kommersiële landbou sektor,maar nog min is bekend oor hul interaksie met organiese materiaal en grond biota. Baie navorsing is reeds oor die uitwerking van anorganiese N op woud en plantasiereste se ontbinding gedoen. Baie min navorsing het gefokus op die uitwerking van anorganiese kunsmis op die gewasreste en tot ons kennis, is daar geen navorsing gedoen op die invloed van anorganiese kunsmis op gekomposteer organiese material nie. Verder is geeneen van die navorsing studies is in Suid-Afrika gedoen nie. Die hoofdoel van hierdie navorsingsprojek was om die effek van anorganiese kunsmis toedienings op die ontbinding van geselekteerde organiese materiaal bronne, wat algemeen gebruik word in die Suid-Afrikaanse landbou en bosbou, te bepaal. Twee ontbinding studies is gedoen oor 'n 3-maande-tydperk, een op kompos en die ander op die plantreste, met die gebruik van 'n plaaslike, sanderige grond. In die eerste eksperiment is ‘n laer gehalte kompos, kompos A (C: N verhouding, 17.67), en 'n hoër gehalte kompos, kompos B (C: N verhouding, 4.92) met drie kommersieel anorganiese bemesting behandelings behandel. Twee was tipiese versnitte gebruik vir die groente (tamatie en kool) produksie: tamatie kunsmis (10: 2:15) (100 kg N, 20 kg P, 150 kg K per ha) en kool kunsmis (5: 2: 4) (250 kg N, 100 kg P, 200 kg K per ha). Die derde kunsmis versnit was 'n ekwivalente massa toepassing van N en P van 150 kg van elke element per ha, wat meer algemeen gebruik word in weiding. In die tweede eksperiment was vyf algemeen gewas en bosbou reste, naamlik kikoejoegras, lusern reste, dennenaalde, suikerriet reste en koring strooi, gekies om die labiele organiese materiaal bronne te verteenwoordig. Die reste is met die tamatie en kool kunsmis toedienings behandel. Beide ontbinding eksperimente is uitgevoer onder normale laboratorium toestande by veldwaterkapasiteit. Ontbinding tempo is deur die bepaling van die CO2-vrystellings, opgelosde organiese koolstof (OOK) produksie, β-glukosidase en polifenol oksidase aktiwiteit (PPO) gemonitor. Aan die begin en einde van ontbinding studie, is verlies op ontbranding uitgevoer om die totale verlies van OM te evalueer. Gebaseer op die resultate van hierdie twee eksperimente, was die gevolgtrekking dat die toevoeging van hoë N bevattende anorganiese bemestingstowwe die ontbinding van beide komposte en plant reste verhoog. Vir beide kompos en plantreste word OOK produksie verhoog met die toevoeging van anorganiese bemesting, ongeag van die organiese materiaal gehalte. Die gevolgtrekking kan gemaak word dat die inherente N in organiese materiaal 'n rol gespeel het in die reaksie van ontbinding op anorganiese bemesting toedienings met die grootste reaksie in organiese material laag in inherente N. Vir labiele organiese material het polifenol en sellulose inhoud ook 'n rol gespeel in die reaksie waargeneeming op anorganiese bemesting.

En algorithmique et en complexité, la plus grande part de la recherche se base sur l’hypothèse que P ≠ NP (Polynomial time et Non deterministic Polynomial time), c'est-à-dire qu'il existe des problèmes dont la solution peut être vérifiée mais non construite en temps polynomial. Si cette hypothèse est admise, de nombreux problèmes naturels ne sont pas dans P (c'est-à-dire, n'admettent pas d'algorithme efficace), ce qui a conduit au développement de nombreuses branches de l'algorithmique. L'une d'elles est la complexité paramétrée. Elle propose des algorithmes exacts, dont l'analyse est faite en fonction de la taille de l'instance et d'un paramètre. Ce paramètre permet une granularité plus fine dans l'analyse de la complexité.Un algorithme sera alors considéré comme efficace s'il est à paramètre fixé, c'est-à-dire, lorsque sa complexité est exponentielle en fonction du paramètre et polynomiale en fonction de la taille de l'instance. Ces algorithmes résolvent les problèmes de la classe FPT (Fixed Parameter Tractable).L'extraction de noyaux est une technique qui permet, entre autre, d’élaborer des algorithmes à paramètre fixé. Elle peut être vue comme un pré-calcul de l'instance, avec une garantie sur la compression des données. Plus formellement, une extraction de noyau est une réduction polynomiale depuis un problème vers lui même, avec la contrainte supplémentaire que la taille du noyau (l'instance réduite) est bornée en fonction du paramètre. Pour obtenir l’algorithme à paramètre fixé, il suffit de résoudre le problème dans le noyau, par exemple par une recherche exhaustive (de complexité exponentielle, en fonction du paramètre). L’existence d'un noyau implique donc l'existence d'un algorithme à paramètre fixé, la réciproque est également vraie. Cependant, l’existence d'un algorithme à paramètre fixé efficace ne garantit pas un petit noyau, c'est a dire un noyau dont la taille est linéaire ou polynomiale. Sous certaines hypothèses, il existe des problèmes n’admettant pas de noyau (c'est-à-dire hors de FPT) et il existe des problèmes de FPT n’admettant pas de noyaux polynomiaux.Un résultat majeur dans le domaine des noyaux est la construction d'un noyau linéaire pour le problème Domination dans les graphes planaires, par Alber, Fellows et Niedermeier.Tout d'abord, la méthode de décomposition en régions proposée par Alber, Fellows et Niedermeier, a permis de construire de nombreux noyaux pour des variantes de Domination dans les graphes planaires. Cependant cette méthode comportait un certain nombre d’imprécisions, ce qui rendait les preuves invalides. Dans la première partie de notre thèse, nous présentons cette méthode sous une forme plus rigoureuse et nous l’illustrons par deux problèmes : Domination Rouge Bleue et Domination Totale.Ensuite, la méthode a été généralisée, d'une part, sur des classes de graphes plus larges (de genre borné, sans-mineur, sans-mineur-topologique), d'autre part, pour une plus grande variété de problèmes. Ces méta-résultats prouvent l’existence de noyaux linéaires ou polynomiaux pour tout problème vérifiant certaines conditions génériques, sur une classe de graphes peu denses. Cependant, pour atteindre une telle généralité, il a fallu sacrifier la constructivité des preuves : les preuves ne fournissent pas d'algorithme d'extraction constructif et la borne sur le noyau n'est pas explicite. Dans la seconde partie de notre thèse nous effectuons un premier pas vers des méta-résultats constructifs ; nous proposons un cadre général pour construire des noyaux linéaires en nous inspirant des principes de la programmation dynamique et d'un méta-résultat de Bodlaender, Fomin, Lokshtanov, Penninkx, Saurabh et Thilikos. / In the fields of Algorithmic and Complexity, a large area of research is based on the assumption that P ≠ NP(Polynomial time and Non deterministic Polynomial time), which means that there are problems for which a solution can be verified but not constructed in polynomial time. Many natural problems are not in P, which means, that they have no efficient algorithm. In order to tackle such problems, many different branches of Algorithmic have been developed. One of them is called Parametric Complexity. It consists in developing exact algorithms whose complexity is measured as a function of the size of the instance and of a parameter. Such a parameter allows a more precise analysis of the complexity. In this context, an algorithm will be considered to be efficient if it is fixed parameter tractable (fpt), that is, if it has a complexity which is exponential in the parameter and polynomial in the size of the instance. Problems that can be solved by such an algorithm form the FPT class.Kernelisation is a technical that produces fpt algorithms, among others. It can be viewed as a preprocessing of the instance, with a guarantee on the compression of the data. More formally, a kernelisation is a polynomial reduction from a problem to itself, with the additional constraint that the size of the kernel, the reduced instance, is bounded by a function of the parameter. In order to obtain an fpt algorithm, it is sufficient to solve the problem in the reduced instance, by brute-force for example (which has exponential complexity, in the parameter). Hence, the existence of a kernelisiation implies the existence of an fpt algorithm. It holds that the converse is true also. Nevertheless, the existence of an efficient fpt algorithm does not imply a small kernel, meaning a kernel with a linear or polynomial size. Under certain hypotheses, it can be proved that some problems can not have a kernel (that is, are not in FPT) and that some problems in FPT do not have a polynomial kernel.One of the main results in the field of Kernelisation is the construction of a linear kernel for the Dominating Set problem on planar graphs, by Alber, Fellows and Niedermeier.To begin with, the region decomposition method proposed by Alber, Fellows and Niedermeier has been reused many times to develop kernels for variants of Dominating Set on planar graphs. Nevertheless, this method had quite a few inaccuracies, which has invalidated the proofs. In the first part of our thesis, we present a more thorough version of this method and we illustrate it with two examples: Red Blue Dominating Set and Total Dominating Set.Next, the method has been generalised to larger classes of graphs (bounded genus, minor-free, topological-minor-free), and to larger families of problems. These meta-results prove the existence of a linear or polynomial kernel for all problems verifying some generic conditions, on a class of sparse graphs. As a price of generality, the proofs do not provide constructive algorithms and the bound on the size of the kernel is not explicit. In the second part of our thesis, we make a first step to constructive meta-results. We propose a framework to build linear kernels based on principles of dynamic programming and a meta-result of Bodlaender, Fomin, Lokshtanov, Penninkx, Saurabh and Thilikos.