Numerous techniques for 3D face reconstruction from a single image exist, making use of large facial databases. However, they commonly encounter quality issues due to the absence of information from alternate perspectives. For example, 3D reconstruction with a single front view input data has limited realism, particularly for profile views. We have observed that multiple-view 3D face reconstruction yields higher-quality models compared to single-view reconstruction. Based on this observation, we propose a novel pipeline that combines several deep-learning methods to enhance the quality of reconstruction from a single frontal view. Our method requires only a single image (front view) as input, yet it generates multiple realistic facial viewpoints using various deep-learning networks. These viewpoints are utilized to create a 3D facial model, significantly enhancing the 3D face quality. Traditional image-space editing has limitations in manipulating content and styles while preserving high quality. However, editing in the latent space, which is the space after encoding or before decoding in a neural network, offers greater capabilities for manipulating a given photo. Motivated by the ability of neural networks to generate 2D images from an extensive database and recognizing that multi-view 3D face reconstruction outperforms single-view approaches, we propose a new pipeline. This pipeline involves latent space manipulation by first finding a latent vector corresponding to a given image using the Generative Adversarial Network (GAN) inversion method. We then search for nearby latent vectors to synthesize multiple pose images from the provided input image, aiming to enhance 3D face reconstruction. The generated images are then fed into Diffusion models, another image synthesis network, to generate their respective profile views. The Diffusion model is known for producing more realistic large-angle variations of a given object than GAN models do. Subsequently, all these images (multi-view images) are fed into an Autoencoder, a neural network designed for 3D face model predictions, to derive the 3D structure of the face. Finally, the texture of the 3D face model is combined to enhance its realism, and certain areas of the 3D shape are refined to correct any unrealistic aspects. Our experimental results validate the effectiveness and efficiency of our method in reconstructing highly accurate 3D models of human faces from a single input (front view input) image. The reconstructed models retain high visual fidelity to the original image, even without the need for a 3D database.

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Yes / Reverse osmosis process is used in many industrial applications ranging from solute-solvent to solvent-solvent and gaseous separation. A number of theoretical models have been developed to describe the separation and fluxes of solvent and solute in such processes. This paper looks into the scope and limitations of two main models (the irreversible thermodynamics and the solution diffusion models) used in the past by several researchers for solute-solvent feed separation. Despite the investigation of other complex models, the simple concepts of these models accelerate the feasibility of the implementation of reverse osmosis for different types of systems and variety of industries. Briefly, an extensive review of these mathematical models is conducted by collecting more than 70 examples from literature in this study. In addition, this review has covered the improvement of such models to make them compatible with multi-component systems with consideration of concentration polarization and solvent-solute-membrane interaction.

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A rotating diffusion cell (RDC) has been used to study the kinetics of extraction of the transition metals cobalt (II), nickel (II), copper (II) and zinc (II) from sulphate solutions into either of two extractants held in n-heptane; di-(2-ethylhexyl) phosphoric acid (D2EHPA) or di-(2- ethylhexyl) dithiophosphoric acid (D2EHDTPA). The metal concentration was 10 mM and the aqueous pH was held at 4.5. The extractant concentration was varied between 0.015 to 0.4 M. In the case of cobalt extraction by D2EHPA, the metal concentration and the pH were varied Different diluents and modifiers were also studied.The rate of extraction by D2EHDTPA was found to be faster than D2EHPA. A comprehensive mathematical model, based upon established two film theory, was developed and used to describe the above experimental results. The model was also used to predict values of the important parameters. ... These values compared well with those found by other authors but using quite different experimental techniques. OS4 In the case of cobalt extraction by D2EHPA, the more polar diluents lowered the initial rate. The overall model predicts such behaviour where the rate is also dependent on the partition coefficients of the extractant. Finally, the theory of the RDC allows the prediction of the diffusion layer thicknesses, this information together with the reaction zone thickness is used to explore the influences of diffusion and chemical reaction on the overall transfer process. The diffusion processes are calculated to be the most important of the two. This is especially so for the D2EHDTPA systems.

Flexible plastic liners are sometimes installed into new and existing oil and gas pipelines to prevent corrosion of the pipe wall. A practical difficulty of this method is that the plastic liners are permeable to gases, which can collect and form an annular space between the liner and the pipe. If the operating pressure in the pipe decreases then the collected gas can cause the liner to collapse and block the pipe. One method for overcoming this problem is to insert vents at intervals along the liner to allow the gas to escape into the pipe during depressurisation. However, there is concern that this arrangement might lead to excessive corrosion beneath the vent where the pipe wall is exposed. The rate of corrosion is expected to be controlled by the vent size but this principle needs to be confirmed by experiment. The work described in this thesis is aimed at investigating this corrosion by experiment for a range of conditions typical of oil and gas production. A novel crevice corrosion cell was designed, consisting of an X100 carbon steel plate and a sheet of transparent Perspex, separated by a thin gasket. A small hole in the Perspex simulated a liner vent and allowed carbon dioxide to reach the steel surface. Tests were carried out in 3.5% NaCl solutions saturated with carbon dioxide at 1 bar partial pressure. Corrosion rates along the length of the annular space were measured using the Linear Polarisation Resistance (LPR) technique on pairs of insulated X100 electrodes set into the plate. The corrosion rates within the annular space have been shown to be small compared to those in the bulk solution and to diminish rapidly with distance from the vent. Mathematical modelling, based on the transport of carbon dioxide, is described to explain these findings and support the experimental work. The effectiveness of the LinerVentTM, installed over the vent, in a turbulence pipeline was demonstrated. The benefit of applying cathodic protection within the annular space was also demonstrated. The results are discussed in terms of the fundamental corrosion principles and their practical implications

La synchronisation des flux physiques a reçu une importante attention dans la littérature. Si le non flux physique a reçu une attention toute particulière dans des domaines tels que le SCM, le pendant financier a longtemps était délaissé. Plus inquiétant, les délais de paiement ont longtemps été perçus comme un moyen de réduction du besoin en fonds de roulement des grandes entreprises. La crise des Subprimes a eu de lourdes conséquences sur le financement des entreprises les plus modestes, mettant en danger l’existence même de ces dernières. Notre travail initial de synchronisation des flux physiques et financiers instruits dans la cadre d’un partenariat CIFRE visait à trouver des solutions à ces problématiques en proposant des modèles d’optimisation sous contraintes. Néanmoins, notre volonté de mettre en œuvre nos travaux fut vaine et notre sujet a progressivement drifté vers la découverte de l’échec du déploiement d’un système ERP. Notre enracinement au sein d’une grande entreprise du secteur de la défense française nous a permis de mettre en œuvre une recherche action canonique en trois phases distinctes et a débouché sur la production d’un modèle de diffusion de l’innovation appliqué à l’ERP. Ce modèle en 6 phases, décrits les étapes successives du déploiement, en mettant en exergue l’impact des forces politiques au sein de l’organisation. / Synchronization of physical flows received significant attention in the literature. If the non-physical flows received special attention in areas such as SCM, financial for a long time was helpless. More worryingly, payment delays have long been seen as a means of reducing the need for working capital for large firms. The subprime crisis has had a serious impact on the financing of the smaller companies, endangering the very existence of the latter. Our initial synchronization job physical and financial flows educated in the context of a CIFRE partnership aimed at finding solutions to these problems by proposing models of optimization under constraints. However, our commitment to implement our work was in vain and our subject has gradually drifted to the discovery of the failure of the deployment of an ERP system. Our roots in a large enterprise sector French defense allowed us to implement an action research canonical three distinct phases and resulted in the production of a model of diffusion of innovation applied to the ERP. This model into 6 phases, described the successive stages of deployment, highlighting the impact of political forces within the organization

The deployment of renewable energy (RE) technologies for electricity generation is a central element of the European energy and climate strategy and was laid down in binding targets on EU-level. The actual RE technology diffusion is, however, shaped by the framework conditions and support measures implemented in the individual EU Member States. This dissertation aims at contributing to a more integrated view of the influencing factors (determinants) for the deployment of RE technologies. To this end, a conceptual framework is drawn up to assess the boundary conditions for RE diffusion from the RE developer’s perspective. The framework is operationalised using a composite indicator (CI) approach and applied in a diffusion model to allow the anticipation of possible future technology deployment. The thesis concentrates on two mainstream RE technologies, namely onshore wind and non-residential PV, and focuses on European countries. Within the analysis, particular emphasis is placed on providing a holistic assessment of the impact of economic and non-economic determinants on the diffusion of RE technologies at national level. The assessment aims at understanding RE developers’ preferences and rationalities regarding the overall framework conditions for RE deployment in order to identify the drivers for and barriers to technological change and to facilitate efficient policy design and regulatory transformation. The most relevant diffusion determinants from the viewpoint of RE project developers are identified through literature research and moderated expert workshops. The relative relevance of the determinants in the diffusion process is then assessed based on an EU-wide questionnaire that resulted in the collection of >200 datasets. Building on this broad empirical basis, a composite indicator (CI) is developed for the diffusion of non-residential PV and wind onshore. The CI provides a transparent framework for the quantification of the diffusion determinants and allows an evaluation and benchmarking of national RE frameworks. In a further step, the CI is integrated in a diffusion model which enables projections of possible future market developments under different configurations of the national RE framework. This modelling approach applies and further develops established logistic models of technology diffusion. The overall approach is validated by applying it to three case study countries: Germany, Spain and the United Kingdom. Data collection in these case study countries involved, among others, semi-structured interviews with 31 RE experts. The different regulatory framework conditions in the three countries lead to 3 different CI results and projected technology diffusion. The results verify the robustness of the approach and the applicability of the concept to different national contexts. The findings of this thesis contribute to the methodological and empirical basis for understanding and modelling technology diffusion processes in general and RE technology diffusion in particular. The approach developed in this thesis further improves the scientific basis for the evaluation of RE support policies and can contribute to RE targets being achieved in an efficient and sustainable way.

The main contribution of this thesis is to derive the properties and present a closed from solution of the exotic options under some specific types of Levy processes, such as American put options, American call options, British put options, British call options and American knock-out put options under either double exponential jump-diffusion processes or one-sided exponential jump-diffusion processes. Compared to the geometric Brownian motion, exponential jump-diffusion processes can better incorporate the asymmetric leptokurtic features and the volatility smile observed from the market. Pricing the option with early exercise feature is the optimal stopping problem to determine the optimal stopping time to maximize the expected options payoff. Due to the Markovian structure of the underlying process, the optimal stopping problem is related to the free-boundary problem consisting of an integral differential equation and suitable boundary conditions. By the local time-space formula for semi-martingales, the closed form solution for the options value can be derived from the free-boundary problem and we characterize the optimal stopping boundary as the unique solution to a nonlinear integral equation arising from the early exercise premium (EEP) representation. Chapter 2 and Chapter 3 discuss American put options and American call options respectively. When pricing options with early exercise feature under the double exponential jump-diffusion processes, a non-local integral term will be found in the infinitesimal generator of the underlying process. By the local time-space formula for semi-martingales, we show that the value function and the optimal stopping boundary are the unique solution pair to the system of two integral equations. The significant contributions of these two chapters are to prove the uniqueness of the value function and the optimal stopping boundary under less restrictive assumptions compared to previous literatures. In the degenerate case with only one-sided jumps, we find that the results are in line with the geometric Brownian motion models, which extends the analytical tractability of the Black-Scholes analysis to alternative models with jumps. In Chapter 4 and Chapter 5, we examine the British payoff mechanism under one-sided exponential jump-diffusion processes, which is the first analysis of British options for process with jumps. We show that the optimal stopping boundaries of British put options with only negative jumps or British call options with only positive jumps can also be characterized as the unique solution to a nonlinear integral equation arising from the early exercise premium representation. Chapter 6 provides the study of American knock-out put options under negative exponential jump-diffusion processes. The conditional memoryless property of the exponential distribution enables us to obtain an analytical form of the arbitrage-free price for American knock-out put options, which is usually more difficult for many other jump-diffusion models.