Since 1975, the extent of catching-up has been very different across Southern regions. Starting from the common arguments of growth theory, the paper wishes to show whether differences in regional income and growth can be attributed to different endowment in human capital, differences in private or public investment level, to structural imbalances, and labour force participation. The investigated panel consists of regional time series for the period 1975 to 1994 and includes NUTS II level regions of Greece, Spain, and the Italian South. Estimation of the impact of the variables on regional income is effected in a dynamic panel data model applying a GMM estimation procedure. The results indicate that the income level of Southern EU regions is largely determined by employment/educational levels and past public investment, while the impact of private investment is not significant. One may follow that EU regional policies should predominately focus on the human factor. Assistance to member countries to upgrade public infrastructures may be continued, but private investment incentives should be curbed. (author's abstract) / Series: Working Papers Series "Growth and Employment in Europe: Sustainability and Competitiveness"

Wireless Sensor Networks (WSNs) are deployed widely for various applications. A variety of useful data are generated by these deployments. Since WSNs have limited resources and unreliable communication links, traditional data management techniques are not suitable. Therefore, designing effective data management techniques for WSNs becomes important. In this dissertation, we address three key issues of data management in WSNs. For data collection, a scheme of making some nodes sleep and estimating their values according to the other active nodes’ readings has been proved energy-efficient. For the purpose of improving the precision of estimation, we propose two powerful estimation models, Data Estimation using a Physical Model (DEPM) and Data Estimation using a Statistical Model (DESM). Most of existing data processing approaches of WSNs are real-time. However, historical data of WSNs are also significant for various applications. No previous study has specifically addressed distributed historical data query processing. We propose an Index based Historical Data Query Processing scheme which stores historical data locally and processes queries energy-efficiently by using a distributed index tree. Area query processing is significant for various applications of WSNs. No previous study has specifically addressed this issue. We propose an energy-efficient in-network area query processing scheme. In our scheme, we use an intelligent method (Grid lists) to describe an area, thus reducing the communication cost and dropping useless data as early as possible. With a thorough simulation study, it is shown that our schemes are effective and energy- efficient. Based on the area query processing algorithm, an Intelligent Monitoring System is designed to detect various events and provide real-time and accurate information for escaping, rescuing, and evacuation when a dangerous event happened.

Since 1975, the extent of catching-up has been very different across Southern regions. Starting from the common arguments of growth theory, the paper wishes to show whether differences in regional income and growth can be attributed to different endowment in human capital, differences in private or public investment level, to structural imbalances, and labour force participation. The investigated panel consists of regional time series for the period 1975 to 1994 and includes NUTS II level regions of Greece, Spain, and the Italian South. Estimation of the impact of the variables on regional income is effected in a dynamic panel data model applying a GMM estimation procedure. The results indicate that the income level of Southern EU regions is largely determined by employment/educational levels and past public investment, while the impact of private investment is not significant. One may follow that EU regional policies should predominately focus on the human factor. Assistance to member countries to upgrade public infra-structures may be continued, but private investment incentives should be curbed. (author's abstract) / Series: EI Working Papers / Europainstitut

Several studies have examined the effect of remittances on economic growth,poverty, education, and governance, among other factors, in developing countrieswith inconclusive results. Using annual panel data of 99 developing countries invarious empirical models, this study aim to answer the question how remittances affect a broader aspect of development using the Human Development Index asdependent variable. The findings indicate that there is a positive relationship between remittances and the level of human development in developing countries.

La thématique abordée porte sur la métrologie virtuelle (VM) pour estimer les données manquantes durant les processus de fabrications des semi-conducteurs. L'utilisation de la métrologie virtuelle permet également de fournir les mesures logicielles (estimations) des sorties pour alimenter les régulateurs run-to-run (R2R) mis en place pour le contrôle de la qualité des produits fabriqués. Pour remédier aux problèmes liés au retard de mesures causé par l'échantillonnage statique imposé par la stratégie et les équipements mis en place, notre contribution dans cette thèse est d'introduire la notion de l'échantillonnage dynamique intelligent. Cette stratégie est basée sur un algorithme qui prend en compte la condition de voisinage permettant d'éviter la mesure réelle même si l'échantillonnage statique l'exige. Cela permet de réduire le nombre de mesures réelles, le temps du cycle et le coût de production. Cette approche est assurée par un module de métrologie virtuelle (VM) que nous avons développé et qui peut être intégré dans une boucle de régulation R2R. Les résultats obtenus ont été validés sur des exemples académiques et sur des données réelles fournies par notre partenaire STMicroelectronics de Rousset concernant un processus chemical mechanical planarization (CMP). Ces données réelles ont permis également de valider les résultats obtenus de la métrologie virtuelle pour les fournir ensuite aux régulateurs R2R (ayant besoin de l'estimation de ces données). / The addressed work is about the virtual metrology (VM) for estimating missing data during semiconductor manufacturing processes. The use of virtual metrology tool also makes it possible to provide the software measurements (estimations) of the outputs to feed the run-to-run (R2R) controllers set up for the quality control of the manufactured products.To address these issues related to the delay of measurements caused by the static sampling imposed by the strategy and the equipments put in place, our contribution in this thesis is to introduce the notion of the dynamic dynamic sampling. This strategy is based on an algorithm that considers the neighborhood condition to avoid the actual measurement even if the static sampling requires it. This reduces the number of actual measurements, the cycle time and the cost of production. This approach is provided by a virtual metrology module (VM) that we have developed and which can be integrated into an R2R control loop. The obtained results were validated on academic examples and on real data provided by our partner STMicroelectronics of Rousset from a chemical mechanical planarization (CMP) process. This real data also enabled the results obtained from the virtual metrology to be validated and then supplied to the R2R regulators (who need the estimation of these data).

Given that human development is a complex process involving multiple components and determiningfactors, multidimensional indicators are needed. On the basis of the extensive literatureon the subject, we advance two new indicators: the Matrix of Capabilities and Functioning(MCF), and the Algorithm of Human Development (HDA).The MCF is composed of vectors of capabilities and functionings, based on Sen’s idea of RefinedFunctionings. It is based in a matricial framework, both static and dynamic. The main purposeof constructing this index is to study how different sets of capabilities relate to alternativefunctionings, to produce diverse outcomes.The Human Development Algorithm (HAD) is a multidimensional index concerning the setof goods and services needed to complete a life cycle. The HDA is a socio-economic contextindicator. It is composed of the main «satisfactors» or basic goods and services needed: food,health, education, housing, social security, decent employment and retirement programs, thatmight be available to all throughout of life cycle. This indicator shows the material progressreached by each country or region as well the institutional organization, private and public, andthe degree of social cohesion and solidarity. / Dado que el desarrollo humano es un proceso complejo que tiene múltiples componentes ydeterminantes, es necesario tener indicadores multidimensionales tales como la Matriz de Capacidadesy Desempeños (MCD) y el Algoritmo del Desarrollo Humano (ADH).El MCD está compuesto de vectores de capacidades y de desempeños, basado en la idea de Sensobre desempeños refinados. Está basado en un marco conceptual matricial, tanto estático comodinámico. El propósito principal de la construcción del índice es estudiar cómo diferentes conjuntosde capacidades con desempeños pueden producir distintos resultados.El ADH es un índice multidimensional relacionado con el conjunto de bienes y servicios que senecesitan para completar un ciclo de vida. El ADH es un indicador de contexto socioeconómico.Está compuesto de los principales satisfactores o bienes y servicios básicos que se requieren: alimentos,salud, educación, vivienda, seguridad social, empleo decente y sistema de pensiones, quedeben estar disponibles durante todo el ciclo de vida. Este indicador muestra el progreso materialalcanzado por cada país o región, tanto como la organización institucional pública y privada, yel grado de cohesión social.

In this thesis, I first investigate the relation between the aggregate unemployment rate and foreign direct investment (FDI) inflows and outflows. To study this relationship, I use a panel data set that contains 45 (developed and developing) countries observed from 1987 through 2008, and I employ Arellano and Bonds generalized methods of moments (ABGMM) estimation method for dynamic panel data. My results show that FDI inflows and outflows are not determinants of the aggregate unemployment rate. In addition, in line with macroeconomic theory, the previous level of aggregate unemployment has a positive impact on the current level of aggregate unemployment. Again, as macroeconomic theory suggests, my results show that per capita real gross domestic product (RGDP) has a negative effect on the current level of aggregate unemployment. Second, I study the long-run relationship between exports and per capita gross domestic product (instrumented by total population) using a panel data set of 51 countries from 1970 through 2008. To study this relationship, I employ the dynamic ordinary least squares (DOLS) estimation method. I find that the percentage of exports in nominal gross domestic products (GDP) is sensitive to changes in the populations of host countries and, hence, to the changes in their GDP. In addition, my results show that the agreement on trade related investment measures increased the percentage of exports in the nominal GDP of developed host countries more than it did in developing host countries.

Yes / This paper uses a new measure of international trade, i.e. the international trade potential index, to measure the welfare gains from trade across countries. The measure is based on the import shares of countries in their gross domestic products. It is observed that gains from international trade are low in prosperous economies, but they are larger in poorer economies. Then, the paper investigates the impact of the index of international trade potential on renewable energy consumption in the unbalanced panel dataset of 36 Organisation for Economic Co-operation and Development member countries from 1966 to 2016. The novel evidence is that international trade potential is positively related to renewable energy consumption. It is also found that per capita income, per capita carbon dioxide emissions, and energy prices increase the demand for renewable energy. / The authors acknowledge the financial support from the Philosophy & Social Science Fund of Tianjin City, China (Award #: TJYJ20-012).

La découverte d’un nouveau bassin, Regourdou 1, offre l’occasion de discuter de l’implication fonctionnelle de la morphologie pelvienne néandertalienne. Dans un premier temps, ce spécimen est décrit, ce qui permet de vérifier son appartenance aux Néandertaliens et mettre en évidence certains traits spécifiques à cette population. Bien qu’aucun ne soit autapomorphique, la combinaison de ces caractères caractérise la ceinture pelvienne néandertalienne. Le bassin Regourdou 1 est ensuite reconstruit à l’aide d’une estimation desdonnées manquantes, par thin-plate spline à partir de Kebara 2. Les dimensions du canal pelvien de Regourdou 1sont comparées à celles de deux autres spécimens néandertaliens (Tabun C1 et Kebara 2) et d’une populationmoderne (n=151). L’analyse de la morphologie des détroits obstétricaux néandertaliens (par morphométrie géométrique), et de la relation céphalo-pelvienne, met en évidence la présence de caractéristiques associées chez l’Homme anatomiquement moderne à la naissance rotationnelle. Notre travail confirme l’existence de mécaniques obstétricales néandertaliennes de type moderne. Cette interprétation permet d’enrichir notre connaissance biologique et culturelle de cette population. / The discovery of a new Neandertal pelvis, Regourdou 1, allows discussing the functional implications of Neandertal pelvic morphology. First, the specimen is described, which offers to proveits affiliation to the Neandertal population and to highlight specific Neandertal features. Even if none of these are autapomorphic, the combinaison of these traits characterize the Neandertal pelvic belt. The pelvis Regourdou 1 is reconstructed, by an estimation of missing-data, thanks to the thin-plate splines method, applied on Kebara 2. The dimensions of Regourdou 1 birth canal are compared with those of two others Neandertal individuals (Tabun C1 and Kebara 2) as well as a modern population (n=151).The analysis of the obstetrical planes morphology (by geometric morphometrics) and the cephalo-pelvic relation highlights the presence of traits associated with rotational birth in modern Human. Our work attests the existence of modern type obstetrical mechanics, in Neandertal. This interpretation allows enriching our biological and cultural knowledge of this population.

The identification of flow characteristics and the reduction of high-dimensional simulation data have capitalized on an orthogonal basis achieved by proper orthogonal decomposition (POD), also known as principal component analysis (PCA) or the Karhunen-Loeve transform (KLT). In the realm of aerospace engineering, an orthogonal basis is versatile for diverse applications, especially associated with reduced-order modeling (ROM) as follows: a low-dimensional turbulence model, an unsteady aerodynamic model for aeroelasticity and flow control, and a steady aerodynamic model for airfoil shape design. Provided that a given data set lacks parts of its data, POD is required to adopt a least-squares formulation, leading to gappy POD, using a gappy norm that is a variant of an L2 norm dealing with only known data. Although gappy POD is originally devised to restore marred images, its application has spread to aerospace engineering for the following reason: various engineering problems can be reformulated in forms of missing data estimation to exploit gappy POD. Similar to POD, gappy POD has a broad range of applications such as optimal flow sensor placement, experimental and numerical flow data assimilation, and impaired particle image velocimetry (PIV) data restoration. Apart from POD and gappy POD, both of which are deterministic formulations, probabilistic principal component analysis (PPCA), a probabilistic generalization of PCA, has been used in the pattern recognition field for speech recognition and in the oceanography area for empirical orthogonal functions in the presence of missing data. In formulation, PPCA presumes a linear latent variable model relating an observed variable with a latent variable that is inferred only from an observed variable through a linear mapping called factor-loading. To evaluate the maximum likelihood estimates (MLEs) of PPCA parameters such as a factor-loading, PPCA can invoke an expectation-maximization (EM) algorithm, yielding an EM algorithm for PPCA (EM-PCA). By virtue of the EM algorithm, the EM-PCA is capable of not only extracting a basis but also restoring missing data through iterations whether the given data are intact or not. Therefore, the EM-PCA can potentially substitute for both POD and gappy POD inasmuch as its accuracy and efficiency are comparable to those of POD and gappy POD. In order to examine the benefits of the EM-PCA for aerospace engineering applications, this thesis attempts to qualitatively and quantitatively scrutinize the EM-PCA alongside both POD and gappy POD using high-dimensional simulation data. In pursuing qualitative investigations, the theoretical relationship between POD and PPCA is transparent such that the factor-loading MLE of PPCA, evaluated by the EM-PCA, pertains to an orthogonal basis obtained by POD. By contrast, the analytical connection between gappy POD and the EM-PCA is nebulous because they distinctively approximate missing data due to their antithetical formulation perspectives: gappy POD solves a least-squares problem whereas the EM-PCA relies on the expectation of the observation probability model. To juxtapose both gappy POD and the EM-PCA, this research proposes a unifying least-squares perspective that embraces the two disparate algorithms within a generalized least-squares framework. As a result, the unifying perspective reveals that both methods address similar least-squares problems; however, their formulations contain dissimilar bases and norms. Furthermore, this research delves into the ramifications of the different bases and norms that will eventually characterize the traits of both methods. To this end, two hybrid algorithms of gappy POD and the EM-PCA are devised and compared to the original algorithms for a qualitative illustration of the different basis and norm effects. After all, a norm reflecting a curve-fitting method is found to more significantly affect estimation error reduction than a basis for two example test data sets: one is absent of data only at a single snapshot and the other misses data across all the snapshots. From a numerical performance aspect, the EM-PCA is computationally less efficient than POD for intact data since it suffers from slow convergence inherited from the EM algorithm. For incomplete data, this thesis quantitatively found that the number of data-missing snapshots predetermines whether the EM-PCA or gappy POD outperforms the other because of the computational cost of a coefficient evaluation, resulting from a norm selection. For instance, gappy POD demands laborious computational effort in proportion to the number of data-missing snapshots as a consequence of the gappy norm. In contrast, the computational cost of the EM-PCA is invariant to the number of data-missing snapshots thanks to the L2 norm. In general, the higher the number of data-missing snapshots, the wider the gap between the computational cost of gappy POD and the EM-PCA. Based on the numerical experiments reported in this thesis, the following criterion is recommended regarding the selection between gappy POD and the EM-PCA for computational efficiency: gappy POD for an incomplete data set containing a few data-missing snapshots and the EM-PCA for an incomplete data set involving multiple data-missing snapshots. Last, the EM-PCA is applied to two aerospace applications in comparison to gappy POD as a proof of concept: one with an emphasis on basis extraction and the other with a focus on missing data reconstruction for a given incomplete data set with scattered missing data. The first application exploits the EM-PCA to efficiently construct reduced-order models of engine deck responses obtained by the numerical propulsion system simulation (NPSS), some of whose results are absent due to failed analyses caused by numerical instability. Model-prediction tests validate that engine performance metrics estimated by the reduced-order NPSS model exhibit considerably good agreement with those directly obtained by NPSS. Similarly, the second application illustrates that the EM-PCA is significantly more cost effective than gappy POD at repairing spurious PIV measurements obtained from acoustically-excited, bluff-body jet flow experiments. The EM-PCA reduces computational cost on factors 8 ~ 19 compared to gappy POD while generating the same restoration results as those evaluated by gappy POD. All in all, through comprehensive theoretical and numerical investigation, this research establishes that the EM-PCA is an efficient alternative to gappy POD for an incomplete data set containing missing data over an entire data set.