A laser induced breakdown spectroscopy quantitative analysis method based on the robust least squares support vector machine regression model

Data fluctuation in multiple measurements of Laser Induced Breakdown Spectroscopy (LIBS) greatly affects the accuracy of quantitative analysis. A new LIBS quantitative analysis method based on the Robust Least Squares Support Vector Machine (RLS-SVM) regression model is proposed. The usual way to enhance the analysis accuracy is to improve the quality and consistency of the emission signal, such as by averaging the spectral signals or spectrum standardization over a number of laser shots. The proposed method focuses more on how to enhance the robustness of the quantitative analysis regression model. The proposed RLS-SVM regression model originates from the Weighted Least Squares Support Vector Machine (WLS-SVM) but has an improved segmented weighting function and residual error calculation according to the statistical distribution of measured spectral data. Through the improved segmented weighting function, the information on the spectral data in the normal distribution will be retained in the regression model while the information on the outliers will be restrained or removed. Copper elemental concentration analysis experiments of 16 certified standard brass samples were carried out. The average value of relative standard deviation obtained from the RLS-SVM model was 3.06% and the root mean square error was 1.537%. The experimental results showed that the proposed method achieved better prediction accuracy and better modeling robustness compared with the quantitative analysis methods based on Partial Least Squares (PLS) regression, standard Support Vector Machine (SVM) and WLS-SVM. It was also demonstrated that the improved weighting function had better comprehensive performance in model robustness and convergence speed, compared with the four known weighting functions.

Globalization of the Internet: Convergence or a multicultural community?

The purpose of this dissertation was to investigate cross-cultural differences in the use of the Internet. Hofstede's model of national culture was employed as the theoretical foundation for the analysis of cross-cultural differences. Davis's technology acceptance model was employed as the theoretical foundation for the analysis of Internet use. ^ Secondary data from an on-line survey of Internet users in 22 countries conducted in April 1997 by the Georgia Tech Research Corporation measured the dependent variables of Internet use and the independent variables of attitudes toward technology. Hofstede's stream of research measured the independent variables of the five dimensions of national culture. ^ Contrary to expectations, regression analyses at the country level of analysis did not detect cultural differences. As expected, regression analyses at the individual level of analysis did detect cultural differences. The results indicated that perceived usefulness was related to the frequency of Internet shopping in the Germanic and Anglo clusters, where masculinity was high. Perceived ease of use was related to the frequency of Internet shopping in the Latin cluster, where uncertainty avoidance was high. Neither perceived usefulness nor perceived ease of use was related to the frequency of Internet shopping in the Nordic cluster, where masculinity and uncertainty avoidance were low. ^ As expected, analysis of variance at the cluster level of analysis indicated that censorship was a greater concern in Germany and Anglo countries, where masculinity was high. Government regulation of the Internet was less preferred in Germany, where power distance was low. Contrary to expectations, concern for transaction security. was lower in the Latin cluster, where uncertainty avoidance was high. Concern for privacy issues was lower in the U.S., where individualism was high. ^ In conclusion, results suggested that Internet users represented a multicultural community, not a standardized virtual community. Based on the findings, specific guidance was provided on how international managers and marketers could develop culturally sensitive strategies for training and promoting Internet services. ^

Development of a mathematical and computer model to assess water quality impacts of hazardous compounds from minor gasoline spills in the inter-tidal zone of the Miami River, Florida

The objective of this study was to develop a model to predict transport and fate of gasoline components of environmental concern in the Miami River by mathematically simulating the movement of dissolved benzene, toluene, xylene (BTX), and methyl-tertiary-butyl ether (MTBE) occurring from minor gasoline spills in the inter-tidal zone of the river. Computer codes were based on mathematical algorithms that acknowledge the role of advective and dispersive physical phenomena along the river and prevailing phase transformations of BTX and MTBE. Phase transformations included volatilization and settling. ^ The model used a finite-difference scheme of steady-state conditions, with a set of numerical equations that was solved by two numerical methods: Gauss-Seidel and Jacobi iterations. A numerical validation process was conducted by comparing the results from both methods with analytical and numerical reference solutions. Since similar trends were achieved after the numerical validation process, it was concluded that the computer codes algorithmically were correct. The Gauss-Seidel iteration yielded at a faster convergence rate than the Jacobi iteration. Hence, the mathematical code was selected to further develop the computer program and software. The model was then analyzed for its sensitivity. It was found that the model was very sensitive to wind speed but not to sediment settling velocity. ^ A computer software was developed with the model code embedded. The software was provided with two major user-friendly visualized forms, one to interface with the database files and the other to execute and present the graphical and tabulated results. For all predicted concentrations of BTX and MTBE, the maximum concentrations were over an order of magnitude lower than current drinking water standards. It should be pointed out, however, that smaller concentrations than the latter reported standards and values, although not harmful to humans, may be very harmful to organisms of the trophic levels of the Miami River ecosystem and associated waters. This computer model can be used for the rapid assessment and management of the effects of minor gasoline spills on inter-tidal riverine water quality. ^

A static traffic assignment model combined with an artificial neural network delay model

As traffic congestion continues to worsen in large urban areas, solutions are urgently sought. However, transportation planning models, which estimate traffic volumes on transportation network links, are often unable to realistically consider travel time delays at intersections. Introducing signal controls in models often result in significant and unstable changes in network attributes, which, in turn, leads to instability of models. Ignoring the effect of delays at intersections makes the model output inaccurate and unable to predict travel time. To represent traffic conditions in a network more accurately, planning models should be capable of arriving at a network solution based on travel costs that are consistent with the intersection delays due to signal controls. This research attempts to achieve this goal by optimizing signal controls and estimating intersection delays accordingly, which are then used in traffic assignment. Simultaneous optimization of traffic routing and signal controls has not been accomplished in real-world applications of traffic assignment. To this end, a delay model dealing with five major types of intersections has been developed using artificial neural networks (ANNs). An ANN architecture consists of interconnecting artificial neurons. The architecture may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system. The ANN delay model has been trained using extensive simulations based on TRANSYT-7F signal optimizations. The delay estimates by the ANN delay model have percentage root-mean-squared errors (%RMSE) that are less than 25.6%, which is satisfactory for planning purposes. Larger prediction errors are typically associated with severely oversaturated conditions. A combined system has also been developed that includes the artificial neural network (ANN) delay estimating model and a user-equilibrium (UE) traffic assignment model. The combined system employs the Frank-Wolfe method to achieve a convergent solution. Because the ANN delay model provides no derivatives of the delay function, a Mesh Adaptive Direct Search (MADS) method is applied to assist in and expedite the iterative process of the Frank-Wolfe method. The performance of the combined system confirms that the convergence of the solution is achieved, although the global optimum may not be guaranteed.

A Static Traffic Assignment Model Combined with an Artificial Neural Network Delay Model

As traffic congestion continues to worsen in large urban areas, solutions are urgently sought. However, transportation planning models, which estimate traffic volumes on transportation network links, are often unable to realistically consider travel time delays at intersections. Introducing signal controls in models often result in significant and unstable changes in network attributes, which, in turn, leads to instability of models. Ignoring the effect of delays at intersections makes the model output inaccurate and unable to predict travel time. To represent traffic conditions in a network more accurately, planning models should be capable of arriving at a network solution based on travel costs that are consistent with the intersection delays due to signal controls. This research attempts to achieve this goal by optimizing signal controls and estimating intersection delays accordingly, which are then used in traffic assignment. Simultaneous optimization of traffic routing and signal controls has not been accomplished in real-world applications of traffic assignment. To this end, a delay model dealing with five major types of intersections has been developed using artificial neural networks (ANNs). An ANN architecture consists of interconnecting artificial neurons. The architecture may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system. The ANN delay model has been trained using extensive simulations based on TRANSYT-7F signal optimizations. The delay estimates by the ANN delay model have percentage root-mean-squared errors (%RMSE) that are less than 25.6%, which is satisfactory for planning purposes. Larger prediction errors are typically associated with severely oversaturated conditions. A combined system has also been developed that includes the artificial neural network (ANN) delay estimating model and a user-equilibrium (UE) traffic assignment model. The combined system employs the Frank-Wolfe method to achieve a convergent solution. Because the ANN delay model provides no derivatives of the delay function, a Mesh Adaptive Direct Search (MADS) method is applied to assist in and expedite the iterative process of the Frank-Wolfe method. The performance of the combined system confirms that the convergence of the solution is achieved, although the global optimum may not be guaranteed.

Scaling limits of a model for selection at two scales

The dynamics of a population undergoing selection is a central topic in evolutionary biology. This question is particularly intriguing in the case where selective forces act in opposing directions at two population scales. For example, a fast-replicating virus strain outcompetes slower-replicating strains at the within-host scale. However, if the fast-replicating strain causes host morbidity and is less frequently transmitted, it can be outcompeted by slower-replicating strains at the between-host scale. Here we consider a stochastic ball-and-urn process which models this type of phenomenon. We prove the weak convergence of this process under two natural scalings. The first scaling leads to a deterministic nonlinear integro-partial differential equation on the interval $[0,1]$ with dependence on a single parameter, $\lambda$. We show that the fixed points of this differential equation are Beta distributions and that their stability depends on $\lambda$ and the behavior of the initial data around $1$. The second scaling leads to a measure-valued Fleming-Viot process, an infinite dimensional stochastic process that is frequently associated with a population genetics.

A Computer Model of Drafting Effects on Collective Behavior in Elite 10,000 m Runners

Purpose Drafting in cycling influences collective behaviour of pelotons. Whilst evidence for collective behaviour in competitive running events exists, it is not clear if this results from energetic savings conferred by drafting. This study modelled the effects of drafting on behavior in elite 10,000 m runners. Methods Using performance data from a men’s elite 10,000 m track running event, computer simulations were constructed using Netlogo 5.1 to test the effects of three different drafting quantities on collective behaviour: no drafting, drafting to 3m behind with up to ~8% energy savings (a realistic running draft); and drafting up to 3m behind with up to 38% energy savings (a realistic cycling draft). Three measures of collective behaviour were analysed in each condition; mean speed, mean group stretch (distance between first and last placed runner), and Runner Convergence Ratio (RCR) which represents the degree of drafting benefit obtained by the follower in a pair of coupled runners. Results Mean speeds were 6.32±0.28m.s-1, 5.57±0.18 m.s-1, and 5.51±0.13 m.s-1 in the cycling draft, runner draft, and no draft conditions respectively (all P<0.001). RCR was lower in the cycling draft condition, but did not differ between the other two. Mean stretch did not differ between conditions. Conclusions Collective behaviours observed in running events cannot be fully explained through energetic savings conferred by realistic drafting benefits. They may therefore result from other, possibly psychological, processes. The benefits or otherwise of engaging in such behavior are, as yet, unclear.

Geometric versus Model Predictive Control based guidance algorithms for fixed-wing UAVs in the presence of very strong wind fields.

The recent years have witnessed increased development of small, autonomous fixed-wing Unmanned Aerial Vehicles (UAVs). In order to unlock widespread applicability of these platforms, they need to be capable of operating under a variety of environmental conditions. Due to their small size, low weight, and low speeds, they require the capability of coping with wind speeds that are approaching or even faster than the nominal airspeed. In this thesis, a nonlinear-geometric guidance strategy is presented, addressing this problem. More broadly, a methodology is proposed for the high-level control of non-holonomic unicycle-like vehicles in the presence of strong flowfields (e.g. winds, underwater currents) which may outreach the maximum vehicle speed. The proposed strategy guarantees convergence to a safe and stable vehicle configuration with respect to the flowfield, while preserving some tracking performance with respect to the target path. As an alternative approach, an algorithm based on Model Predictive Control (MPC) is developed, and a comparison between advantages and disadvantages of both approaches is drawn. Evaluations in simulations and a challenging real-world flight experiment in very windy conditions confirm the feasibility of the proposed guidance approach.

La régulation de l’économie numérique au Sénégal : la convergence des télécommunications et de l’audiovisuel

Établir une régulation de l’économie numérique au Sénégal représente un enjeu fondamental pour les gouvernants et l’ensemble des acteurs qui la compose. Suivant une démarche plus globalisée, d’énormes mutations normatives visant les rationalités et les mécanismes de réglementations ont évolué dans le temps donnant une place plus considérable au droit dans les politiques publiques des États. Différents modèles normatifs et institutionnels sont ainsi adaptés pour prendre en charge le phénomène de la convergence dépendamment du contexte réglementaire du pays. Pour ce qui est du contexte actuel du Sénégal, l’étanchéité des réglementations relatives aux télécommunications et à l’audiovisuel, désormais convergent, est fondée sur un modèle de réglementation sectorielle. Toutefois, leur convergence a provoqué un brouillage des frontières qui risque désormais de poser des conséquences énormes sur le plan normatif tel que des risques d’enchevêtrement sur le plan institutionnel ou réglementaire. Or au plan national, il n’existe à ce jour aucun texte visant à assoir les bases d’une régulation convergente. Ainsi, à la question de savoir si la régulation sectorielle est pertinente au regard de l’environnement du numérique marqué par la convergence, il s’est avéré qu’elle pourrait être adoptée comme modèle à court terme. Mais dans un but de réaliser des économies d’échelle pour réguler efficacement les différents secteurs et industries infrastructurelles, il faut un modèle de régulation unique marquée par la fusion de l’ARTP et du CNRA. D’une part, la régulation sectorielle permet d’accompagner la transition vers le numérique déjà lancée et d’autre part la régulation multisectorielle servira une fois la convergence des marchés établis.

Development of a Coupling Model for Fluid-Structure Interaction using the Mesh-free Finite Element Method and the Lattice Boltzmann Method

In the presented thesis work, the meshfree method with distance fields was coupled with the lattice Boltzmann method to obtain solutions of fluid-structure interaction problems. The thesis work involved development and implementation of numerical algorithms, data structure, and software. Numerical and computational properties of the coupling algorithm combining the meshfree method with distance fields and the lattice Boltzmann method were investigated. Convergence and accuracy of the methodology was validated by analytical solutions. The research was focused on fluid-structure interaction solutions in complex, mesh-resistant domains as both the lattice Boltzmann method and the meshfree method with distance fields are particularly adept in these situations. Furthermore, the fluid solution provided by the lattice Boltzmann method is massively scalable, allowing extensive use of cutting edge parallel computing resources to accelerate this phase of the solution process. The meshfree method with distance fields allows for exact satisfaction of boundary conditions making it possible to exactly capture the effects of the fluid field on the solid structure.

La régulation de l’économie numérique au Sénégal : la convergence des télécommunications et de l’audiovisuel

Établir une régulation de l’économie numérique au Sénégal représente un enjeu fondamental pour les gouvernants et l’ensemble des acteurs qui la compose. Suivant une démarche plus globalisée, d’énormes mutations normatives visant les rationalités et les mécanismes de réglementations ont évolué dans le temps donnant une place plus considérable au droit dans les politiques publiques des États. Différents modèles normatifs et institutionnels sont ainsi adaptés pour prendre en charge le phénomène de la convergence dépendamment du contexte réglementaire du pays. Pour ce qui est du contexte actuel du Sénégal, l’étanchéité des réglementations relatives aux télécommunications et à l’audiovisuel, désormais convergent, est fondée sur un modèle de réglementation sectorielle. Toutefois, leur convergence a provoqué un brouillage des frontières qui risque désormais de poser des conséquences énormes sur le plan normatif tel que des risques d’enchevêtrement sur le plan institutionnel ou réglementaire. Or au plan national, il n’existe à ce jour aucun texte visant à assoir les bases d’une régulation convergente. Ainsi, à la question de savoir si la régulation sectorielle est pertinente au regard de l’environnement du numérique marqué par la convergence, il s’est avéré qu’elle pourrait être adoptée comme modèle à court terme. Mais dans un but de réaliser des économies d’échelle pour réguler efficacement les différents secteurs et industries infrastructurelles, il faut un modèle de régulation unique marquée par la fusion de l’ARTP et du CNRA. D’une part, la régulation sectorielle permet d’accompagner la transition vers le numérique déjà lancée et d’autre part la régulation multisectorielle servira une fois la convergence des marchés établis.

Does international trade produce convergence?

In spite of increasing globalization around the world, the effects of international trade on economic growth are not very clear. I consider an endogenous economic growth model in an open economy with the Home Market Effect (HME) and non-homothetic preferences in order to identify some determinants of the different results in this relationship. The model shows how trade between similar countries leads to convergence in economic growth when knowledge spillovers are present, while trade between very asymmetric countries produces divergence and may become trade in a poverty or growth trap. The results for welfare move in the same direction as economic growth since convergence implies increases in welfare for both countries, while divergence leads to increases in welfare for the largest country and the opposite for its commercial partner in the absence of knowledge spillovers. International trade does not implicate greater welfare as is usual in a static context under CES preferences.

An approximate method for the solution of an influence function foil rolling model

Fleck and Johnson (Int. J. Mech. Sci. 29 (1987) 507) and Fleck et al. (Proc. Inst. Mech. Eng. 206 (1992) 119) have developed foil rolling models which allow for large deformations in the roll profile, including the possibility that the rolls flatten completely. However, these models require computationally expensive iterative solution techniques. A new approach to the approximate solution of the Fleck et al. (1992) Influence Function Model has been developed using both analytic and approximation techniques. The numerical difficulties arising from solving an integral equation in the flattened region have been reduced by applying an Inverse Hilbert Transform to get an analytic expression for the pressure. The method described in this paper is applicable to cases where there is or there is not a flat region.