Analyse d’implantation du programme de prévention de la transmission du VIH de la mère à l’enfant au Bénin

Problématique : Implanté en 2004 au Bénin, le programme national de prévention de la transmission du VIH de la mère à l’enfant (PTME) semble globalement bien implanté. Toutefois une enquête, en 2005, révèle certaines difficultés, particulièrement au niveau de la couverture du programme: seulement 70 à 75 % des femmes enceintes vues en consultations prénatales ont été dépistées et 33 % des 1150 femmes dépistées séropositives ont accouché suivant le protocole de PTME. En outre, d’un site à un autre, on relève une grande variation dans la couverture en termes de dépistage et de suivi des femmes enceintes infectées. Cette faiblesse dans la couverture nous a amené à questionner le contexte organisationnel dans lequel le programme est implanté. Objectif : L’objectif général de cette thèse est d’analyser l'implantation de la PTME au Bénin. Le premier objectif spécifique consiste à identifier et comprendre les enjeux reliés à la façon de rejoindre les femmes enceintes dans le cadre du dépistage. Le second consiste à comprendre le contexte d’implantation et son influence sur la mise en œuvre de la PTME. Méthodologie : Cette recherche évaluative s’appuie sur une étude de cas. Six maternités ont été sélectionnées avec le souhait de représenter les différents contextes d’organisation des services. Les données ont été collectées par observation non participante, entrevues semi-dirigées (n=41) réalisées avec des prestataires de services, analyse documentaire des rapports d’activités des maternités et par questionnaires administrés aux femmes enceintes en consultations prénatales (n=371). Résultats : Le premier article a permis d'apprécier le caractère libre et éclairé du consentement au dépistage. Une majorité des femmes enceintes, suivies dans les centres privés, ont été dépistées sans être effectivement informées de la PTME alors que les femmes fréquentant les autres maternités connaissent mieux les composantes de la PTME. Le caractère volontaire du consentement des femmes est généralement respecté sur tous les sites. Le deuxième article porte sur l'analyse de la qualité du conseil pré-test. Seulement 54% des femmes enceintes ont participé à un conseil en groupe et 80% à un conseil individuel. Dans les centres où sont dispensées des séances d'information de groupe, la qualité est meilleure que dans les centres qui dispensent un conseil individuel exclusif. Le troisième article analyse l'influence du contexte d'implantation sur la mise en œuvre du programme. Parmi les facteurs qui contribuent favorablement à la mise en œuvre on relève la proximité d’un centre de référence et la coordination des activités de PTME dans une zone géographique, la responsabilisation du prestataire dédié à la PTME, la supervision formative régulière accompagnée de séances de discussion collective et l’implication des médiatrices dans la recherche active des perdues de vues. A l’opposé, la responsabilisation des médiatrices pour la réalisation du conseil individuel et du dépistage ne favorise pas une bonne mise en œuvre de la PTME. Conclusion : Nos résultats montrent qu'il est possible de jouer sur l'organisation des services de santé dans le cadre du programme du PTME pour améliorer la façon dont le programme est implanté tant dans les centres privés que publics, sans que cela ne représente un ajout net de ressources. C'est le cas de l’amélioration de la qualité du conseil et du dépistage, de l’implantation du processus interne d’apprentissage organisationnel et de la coordination des services.

Réflexion juridique autours de la notion de désinformation eu égard à la transmission de métavirus

Nous sommes quotidiennement envahis pour d’innombrables messages électroniques non sollicités, qu’il s’agisse d’annonces publicitaires, de virus ou encore de ce qu’on appelle désormais les métavirus. Ces derniers sont des canulars transmis aux internautes leur suggérant de poser tel ou tel geste, lequel causera des dommages plus ou moins importants au système de l’utilisateur. L’auteur se penche sur la problématique que suscitent ces métavirus au niveau de la responsabilité civile de leurs émetteurs. Il en vient à la conclusion que ce régime, bien qu’applicable en théorie, demeure mal adapté au problème notamment au niveau de la preuve des éléments de la responsabilité civile. Il faut d’abord établir la capacité de discernement (ou l’incapacité) de l’émetteur, la connaissance ou non de cet état par le destinataire et la preuve d’un comportement fautif de la part de l’émetteur voire même des deux parties. Reste à savoir quelle aurait été l’attitude raisonnable dans la situation. À noter que la victime pourrait être trouvée partiellement responsable pour ses propres dommages. Reste alors à prouver le lien de causalité entre l’acte et le dommage ce qui, compte tenu de la situation factuelle, peut s’avérer une tâche ardue. L’auteur conclut que l’opportunité d’un tel recours est très discutable puisque les coûts sont disproportionnés aux dommages et car les chances pour qu’un juge retienne la responsabilité de celui qui a envoyé le métavirus sont assez faibles. La meilleure solution, ajoute-t-il, reste la prudence.

A Reinforcement Learning Algorithm to Economic Dispatch Considering Transmission Losses

Reinforcement Learning (RL) refers to a class of learning algorithms in which learning system learns which action to take in different situations by using a scalar evaluation received from the environment on performing an action. RL has been successfully applied to many multi stage decision making problem (MDP) where in each stage the learning systems decides which action has to be taken. Economic Dispatch (ED) problem is an important scheduling problem in power systems, which decides the amount of generation to be allocated to each generating unit so that the total cost of generation is minimized without violating system constraints. In this paper we formulate economic dispatch problem as a multi stage decision making problem. In this paper, we also develop RL based algorithm to solve the ED problem. The performance of our algorithm is compared with other recent methods. The main advantage of our method is it can learn the schedule for all possible demands simultaneously.

Reinforcement Learning approaches to Economic Dispatch problem

This paper presents Reinforcement Learning (RL) approaches to Economic Dispatch problem. In this paper, formulation of Economic Dispatch as a multi stage decision making problem is carried out, then two variants of RL algorithms are presented. A third algorithm which takes into consideration the transmission losses is also explained. Efficiency and flexibility of the proposed algorithms are demonstrated through different representative systems: a three generator system with given generation cost table, IEEE 30 bus system with quadratic cost functions, 10 generator system having piecewise quadratic cost functions and a 20 generator system considering transmission losses. A comparison of the computation times of different algorithms is also carried out.

A parallel genetic algorithm for the Steiner Problem in Networks

This paper presents a parallel genetic algorithm to the Steiner Problem in Networks. Several previous papers have proposed the adoption of GAs and others metaheuristics to solve the SPN demonstrating the validity of their approaches. This work differs from them for two main reasons: the dimension and the characteristics of the networks adopted in the experiments and the aim from which it has been originated. The reason that aimed this work was namely to build a comparison term for validating deterministic and computationally inexpensive algorithms which can be used in practical engineering applications, such as the multicast transmission in the Internet. On the other hand, the large dimensions of our sample networks require the adoption of a parallel implementation of the Steiner GA, which is able to deal with such large problem instances.

Reduction of vestigial sideband effects due to multipath transmission in terrestrial broadcast television

In terrestrial television transmission multiple paths of various lengths can occur between the transmitter and the receiver. Such paths occur because of reflections from objects outside the direct transmission path. The multipath signals arriving at the receiver are all detected along with the intended signal causing time displaced replicas called 'ghosts' to appear on the television picture. With an increasing number of people living within built up areas, ghosting is becoming commonplace and therefore deghosting is becoming increasingly important. This thesis uses a deterministic time domain approach to deghosting, resulting in a simple solution to the problem of removing ghosts. A new video detector is presented which reduces the synchronous detector local oscillator phase error, caused by any practical size of ghost, to a lower level than has ever previously been achieved. From the new detector, dispersion of the video signal is minimised and a known closed-form time domain description of the individual ghost components within the detected video is subsequently obtained. Developed from mathematical descriptions of the detected video, a new specific deghoster filter structure is presented which is capable of removing both inphase (I) and also the phase quadrature (Q) induced ghost signals derived from the VSB operation. The new deghoster filter requires much less hardware than any previous deghoster which is capable of removing both I and Q ghost components. A new channel identification algorithm was also required and written which is based upon simple correlation techniques to find the delay and complex amplitude characteristics of individual ghosts. The result of the channel identification is then passed to the new I and Q deghoster filter for ghost cancellation. Generated from the research work performed for this thesis, five papers have been published. D

Transmission of wireless power by magnetic resonance

The work involves investigation of a type of wireless power system wherein its analysis will yield the construction of a prototype modeled as a singular technological artifact. It is through exploration of the artifact that forms the intellectual basis for not only its prototypical forms, but suggestive of variant forms not yet discovered. Through the process it is greatly clarified the role of the artifact, its most suitable application given the constraints on the delivery problem, and optimization strategies to improve it. In order to improve maturity and contribute to a body of knowledge, this document proposes research utilizing mid-field region, efficient inductive-transfer for the purposes of removing wired connections and electrical contacts. While the description seems enough to state the purpose of this work, it does not convey the compromises of having to redraw the lines of demarcation between near and far-field in the traditional method of broadcasting. Two striking scenarios are addressed in this thesis: Firstly, the mathematical explanation of wireless power is due to J.C. Maxwell's original equations, secondly, the behavior of wireless power in the circuit is due to Joseph Larmor's fundamental works on the dynamics of the field concept. A model of propagation will be presented which matches observations in experiments. A modified model of the dipole will be presented to address the phenomena observed in the theory and experiments. Two distinct sets of experiments will test the concept of single and two coupled-modes. In a more esoteric context of the zero and first-order magnetic field, the suggestion of a third coupled-mode is presented. Through the remaking of wireless power in this context, it is the intention of the author to show the reader that those things lost to history, bound to a path of complete obscurity, are once again innovative and useful ideas.

Global stabilizing feedback law for a problem of biological control of mosquito-borne diseases

The control of the spread of dengue fever by introduction of the intracellular parasitic bacterium Wolbachia in populations of the vector Aedes aegypti, is presently one of the most promising tools for eliminating dengue, in the absence of an efficient vaccine. The success of this operation requires locally careful planning to determine the adequate number of mosquitoes carrying the Wolbachia parasite that need to be introduced into the natural population. The latter are expected to eventually replace the Wolbachia-free population and guarantee permanent protection against the transmission of dengue to human. In this paper, we propose and analyze a model describing the fundamental aspects of the competition between mosquitoes carrying Wolbachia and mosquitoes free of the parasite. We then introduce a simple feedback control law to synthesize an introduction protocol, and prove that the population is guaranteed to converge to a stable equilibrium where the totality of mosquitoes carry Wolbachia. The techniques are based on the theory of monotone control systems, as developed after Angeli and Sontag. Due to bistability, the considered input-output system has multivalued static characteristics, but the existing results are unable to prove almost-global stabilization, and ad hoc analysis has to be conducted.

A modified Primal-Dual Logarithmic-Barrier Method for solving the Optimal Power Flow problem with discrete and continuous control variables

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An efficient Hopfield network to solve economic dispatch problems with transmission system representation

Economic dispatch (ED) problems have recently been solved by artificial neural network approaches. Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. The ability of neural networks to realize some complex non-linear function makes them attractive for system optimization. All ED models solved by neural approaches described in the literature fail to represent the transmission system. Therefore, such procedures may calculate dispatch policies, which do not take into account important active power constraints. Another drawback pointed out in the literature is that some of the neural approaches fail to converge efficiently toward feasible equilibrium points. A modified Hopfield approach designed to solve ED problems with transmission system representation is presented in this paper. The transmission system is represented through linear load flow equations and constraints on active power flows. The internal parameters of such modified Hopfield networks are computed using the valid-subspace technique. These parameters guarantee the network convergence to feasible equilibrium points, which represent the solution for the ED problem. Simulation results and a sensitivity analysis involving IEEE 14-bus test system are presented to illustrate efficiency of the proposed approach. (C) 2004 Elsevier Ltd. All rights reserved.

Interior point algorithm for linear programming used in transmission network synthesis

This article presents a well-known interior point method (IPM) used to solve problems of linear programming that appear as sub-problems in the solution of the long-term transmission network expansion planning problem. The linear programming problem appears when the transportation model is used, and when there is the intention to solve the planning problem using a constructive heuristic algorithm (CHA), ora branch-and-bound algorithm. This paper shows the application of the IPM in a CHA. A good performance of the IPM was obtained, and then it can be used as tool inside algorithm, used to solve the planning problem. Illustrative tests are shown, using electrical systems known in the specialized literature. (C) 2005 Elsevier B.V. All rights reserved.

Transmission system expansion planning by an extended genetic algorithm

The paper presents an extended genetic algorithm for solving the optimal transmission network expansion planning problem. Two main improvements have been introduced in the genetic algorithm: (a) initial population obtained by conventional optimisation based methods; (b) mutation approach inspired in the simulated annealing technique, the proposed method is general in the sense that it does not assume any particular property of the problem being solved, such as linearity or convexity. Excellent performance is reported in the test results section of the paper for a difficult large-scale real-life problem: a substantial reduction in investment costs has been obtained with regard to previous solutions obtained via conventional optimisation methods and simulated annealing algorithms; statistical comparison procedures have been employed in benchmarking different versions of the genetic algorithm and simulated annealing methods.

A geometric interpretation for transmission real losses minimization through the optimal power flow and its influence on voltage collapse

This work presents an approach for geometric solution of an optimal power flow (OPF) problem for a two bus system (a slack and a PV busses). Additionally, the geometric relationship between the losses minimization and the increase of the reactive margin and, therefore, the maximum loading point, is shown. The algebraic equations for the calculation of the Lagrange multipliers and for the minimum losses value are obtained. These equations are used to validate the results obtained using an OPF program. (C) 2002 Elsevier B.V. B.V. All rights reserved.

Multistage and coordinated planning of the expansion of transmission systems

In this paper, an efficient genetic algorithm (GA) is presented to solve the problem of multistage and coordinated transmission expansion planning. This is a mixed integer nonlinear programming problem, difficult for systems of medium and large size and high complexity. The GA presented has a set of specialized genetic operators and an efficient form of generation of the initial population that finds high quality suboptimal topologies for large size and high complexity systems. In these systems, multistage and coordinated planning present a lower investment than static planning. Tests results are shown in one medium complexity system and one large size high complexity system.

Efficient method for AC transmission network expansion planning

A combinatorial mathematical model in tandem with a metaheuristic technique for solving transmission network expansion planning (TNEP) using an AC model associated with reactive power planning (RPP) is presented in this paper. AC-TNEP is handled through a prior DC model while additional lines as well as VAr-plants are used as reinforcements to cope with real network requirements. The solution of the reinforcement stage can be obtained by assuming all reactive demands are supplied locally to achieve a solution for AC-TNEP and by neglecting the local reactive sources, a reactive power planning (RPP) will be managed to find the minimum required reactive power sources. Binary GA as well as a real genetic algorithm (RCA) are employed as metaheuristic optimization techniques for solving this combinatorial TNEP as well as the RPP problem. High quality results related with lower investment costs through case studies on test systems show the usefulness of the proposal when working directly with the AC model in transmission network expansion planning, instead of relaxed models. (C) 2010 Elsevier B.V. All rights reserved.