854 resultados para International Input-Output


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An approach for the analysis of uncertainty propagation in reliability-based design optimization of composite laminate structures is presented. Using the Uniform Design Method (UDM), a set of design points is generated over a domain centered on the mean reference values of the random variables. A methodology based on inverse optimal design of composite structures to achieve a specified reliability level is proposed, and the corresponding maximum load is outlined as a function of ply angle. Using the generated UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on an evolutionary learning process. Then, a Monte Carlo simulation using ANN development is performed to simulate the behavior of the critical Tsai number, structural reliability index, and their relative sensitivities as a function of the ply angle of laminates. The results are generated for uniformly distributed random variables on a domain centered on mean values. The statistical analysis of the results enables the study of the variability of the reliability index and its sensitivity relative to the ply angle. Numerical examples showing the utility of the approach for robust design of angle-ply laminates are presented.

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Cette recherche porte sur le financement public de l’enseignement supérieur au Pérou et ses impacts dans une perspective longitudinale couvant la période 1993-2003. Cette période est importante parce qu’elle a été témoin, dans ce pays, de changements majeurs aux plans du financement public et de la configuration du système d’enseignement supérieur. La recherche consiste principalement dans des analyses secondaires de données pertinentes publiées par des organismes nationaux et internationaux. Les analyses sont structurées à partir d’un schéma d’inputs et outputs. On considère comme inputs les ressources financières et les ressources humaines, lesquelles comprennent les professeurs et les étudiants, et comme outputs les taux de diplomation (efficacité interne) et la demande de diplômés par le marché du travail (efficacité externe). La théorie de la dépendance de ressources sert de cadre pour interpréter les rapports entre le financement public et ses incidences sur les réponses institutionnels et ses conséquences. Dans la période retenue, le financement du secteur public a décru de 32% en raison d’un désengagement progressif de l’État. Une conséquence majeure de la diminution du financement public a été la croissance rapide du secteur privé de l’enseignement supérieur. En effet, alors qu’en 1993 il y avait 24 institutions privées d’enseignement supérieur, il y en avait, en 2003, 46 institutions. La baisse du financement public et la croissance du secteur privé d’enseignement supérieur ont eu des incidences sur la sélectivité des étudiants, sur le statut des professeurs, sur l’implication des universités en recherche et sur les taux de diplomation. Le taux de sélectivité dans le secteur public a augmenté entre 1993 et 2003, alors que ce taux a diminué, dans la même période, dans le secteur privé. Ainsi, le secteur public répond à la diminution du financement en restreignant l’accès à l’enseignement supérieur. Le secteur privé, par contre, diminue sa sélectivité compensant ainsi l’augmentation de la sélectivité dans le secteur public et, par le fait même, augmente sa part de marché. Également, tant dans le secteur public que dans le secteur privé, les professeurs sont engagés principalement sur une base temporaire, ce qui se traduit, particulièrement dans le secteur privé, dans un moindre engagement institutionnel. Enfin, les universités publiques et privées du Pérou font peu de recherche, car elles favorisent, pour balancer leurs budgets, la consultation et les contrats au détriment de la recherche fondamentale. Paradoxalement, alors que, dans le secteur privé, les taux de sélectivité des étudiants diminuent, leurs taux de diplomation augmentent plus que dans le secteur public. Enfin, les formations avec plus d’étudiants inscrits, tant dans le secteur public que privé, sont les moins coûteuses en infrastructure et équipements. Dès lors, la pertinence de la production universitaire devient problématique. Cette recherche révèle que les organisations universitaires, face à un environnement où les ressources financières deviennent de plus en plus rares, développent des stratégies de survie qui peuvent avoir des incidences sur la qualité et la pertinence de l’enseignement supérieur.

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The telemetry data processing operation intended for a given mission are pre-defined by an onboard telemetry configuration, mission trajectory and overall telemetry methodology have stabilized lately for ISRO vehicles. The given problem on telemetry data processing is reduced through hierarchical problem reduction whereby the sequencing of operations evolves as the control task and operations on data as the function task. The function task Input, Output and execution criteria are captured into tables which are examined by the control task and then schedules when the function task when the criteria is being met.

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The rapid increase of rice imports in sub-Saharan Africa under the unstable situation in the world rice market during the 2000s has made it an important policy target for the countries in the region to increase self-sufficiency in rice in order to enhance food security. Whether domestic rice production can be competitive with imported rice is a serious question in East African countries that lie close, just across the Arabian Sea, to major rice exporting countries in South Asia. This study investigates the international competitiveness of domestic rice production in Uganda in terms of the domestic resource cost ratio. The results show that rainfed rice cultivation, which accounts for 95% of domestic rice production, does not have a comparative advantage with respect to rice imported from Pakistan, the largest supplier of imported rice to Uganda. However, the degree of non-competitiveness is not serious, and a high possibility exists for Uganda’s rainfed rice cultivation to become internationally competitive by improving yield levels by applying more modern inputs and enhancing labour productivity. Irrigated rice cultivation, though very limited in area, is competitive even under the present input-output structure when the cost of irrigation infrastructure is treated as a sunk cost. If the cost of installing irrigation infrastructure and its operation and maintenance is taken into account, the types of irrigation development that are economically feasible are not large-scale irrigation projects, but are small- and microscale projects for lowland rice cultivation and rain-water harvesting for upland rice cultivation.

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Este proyecto caracteriza la logística del sector cemento en Colombia al identificar y describir los principales actores, procesos y materiales involucrados en la cadena de suministros del sector. Este documento compila la información logística relevante para la producción de cemento en Colombia. Esta información se obtuvo sintetizando estudios y reportes acerca de las prácticas logísticas y las condiciones en las que éstas se desarrollan. Adicionalmente se realizaron visitas empresariales en diferentes plantas de producción de cemento y entrevistas semiestructuradas a expertos en logística de los diferentes eslabones. Con la información primaria y secundaria se caracteriza del producto, las materias primas e insumos necesarios para la producción de cemento. Se identifican los principales agentes que componen el sector y se describen los procesos logísticos relacionados con el cemento en cada uno de ellos. Para las cementeras y canteras se hace un análisis de entradas y salidas de los procesos principales de su cadena de valor. Adicionalmente se expone la operación de transporte como un elemento clave en el sector y se presentan las simulaciones de fletes, rutas y cubicaje. Por último, se incluye un caso de optimización de transporte aplicando teorías de investigación de operaciones.

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This paper formally derives a new path-based neural branch prediction algorithm (FPP) into blocks of size two for a lower hardware solution while maintaining similar input-output characteristic to the algorithm. The blocked solution, here referred to as B2P algorithm, is obtained using graph theory and retiming methods. Verification approaches were exercised to show that prediction performances obtained from the FPP and B2P algorithms differ within one mis-prediction per thousand instructions using a known framework for branch prediction evaluation. For a chosen FPGA device, circuits generated from the B2P algorithm showed average area savings of over 25% against circuits for the FPP algorithm with similar time performances thus making the proposed blocked predictor superior from a practical viewpoint.

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In this paper, we present an on-line estimation algorithm for an uncertain time delay in a continuous system based on the observational input-output data, subject to observational noise. The first order Pade approximation is used to approximate the time delay. At each time step, the algorithm combines the well known Kalman filter algorithm and the recursive instrumental variable least squares (RIVLS) algorithm in cascade form. The instrumental variable least squares algorithm is used in order to achieve the consistency of the delay parameter estimate, since an error-in-the-variable model is involved. An illustrative example is utilized to demonstrate the efficacy of the proposed approach.

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A new autonomous ship collision free (ASCF) trajectory navigation and control system has been introduced with a new recursive navigation algorithm based on analytic geometry and convex set theory for ship collision free guidance. The underlying assumption is that the geometric information of ship environment is available in the form of a polygon shaped free space, which may be easily generated from a 2D image or plots relating to physical hazards or other constraints such as collision avoidance regulations. The navigation command is given as a heading command sequence based on generating a way point which falls within a small neighborhood of the current position, and the sequence of the way points along the trajectory are guaranteed to lie within a bounded obstacle free region using convex set theory. A neurofuzzy network predictor which in practice uses only observed input/output data generated by on board sensors or external sensors (or a sensor fusion algorithm), based on using rudder deflection angle for the control of ship heading angle, is utilised in the simulation of an ESSO 190000 dwt tanker model to demonstrate the effectiveness of the system.

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In this article a simple and effective controller design is introduced for the Hammerstein systems that are identified based on observational input/output data. The nonlinear static function in the Hammerstein system is modelled using a B-spline neural network. The controller is composed by computing the inverse of the B-spline approximated nonlinear static function, and a linear pole assignment controller. The contribution of this article is the inverse of De Boor algorithm that computes the inverse efficiently. Mathematical analysis is provided to prove the convergence of the proposed algorithm. Numerical examples are utilised to demonstrate the efficacy of the proposed approach.

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In this paper we introduce a new Wiener system modeling approach for memory high power amplifiers in communication systems using observational input/output data. By assuming that the nonlinearity in the Wiener model is mainly dependent on the input signal amplitude, the complex valued nonlinear static function is represented by two real valued B-spline curves, one for the amplitude distortion and another for the phase shift, respectively. The Gauss-Newton algorithm is applied for the parameter estimation, which incorporates the De Boor algorithm, including both the B-spline curve and the first order derivatives recursion. An illustrative example is utilized to demonstrate the efficacy of the proposed approach.

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Two approaches are presented to calculate the weights for a Dynamic Recurrent Neural Network (DRNN) in order to identify the input-output dynamics of a class of nonlinear systems. The number of states of the identified network is constrained to be the same as the number of states of the plant.

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In this article a simple and effective algorithm is introduced for the system identification of the Wiener system using observational input/output data. The nonlinear static function in the Wiener system is modelled using a B-spline neural network. The Gauss–Newton algorithm is combined with De Boor algorithm (both curve and the first order derivatives) for the parameter estimation of the Wiener model, together with the use of a parameter initialisation scheme. Numerical examples are utilised to demonstrate the efficacy of the proposed approach.

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In this paper, a new model-based proportional–integral–derivative (PID) tuning and controller approach is introduced for Hammerstein systems that are identified on the basis of the observational input/output data. The nonlinear static function in the Hammerstein system is modelled using a B-spline neural network. The control signal is composed of a PID controller, together with a correction term. Both the parameters in the PID controller and the correction term are optimized on the basis of minimizing the multistep ahead prediction errors. In order to update the control signal, the multistep ahead predictions of the Hammerstein system based on B-spline neural networks and the associated Jacobian matrix are calculated using the de Boor algorithms, including both the functional and derivative recursions. Numerical examples are utilized to demonstrate the efficacy of the proposed approaches.

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This paper argues that offshoring indices often measure something different than what we think they are. Using data from input-output tables of 21 European countries from 1995 to 2006 we decompose an offshoring index, distinguishing between a domestic (structural change) and an international component (imported inputs ratio). Regarding offshoring of business services, a large share of the index variation is driven by the domestic component. This is even more pronounced for overall service offshoring. In the case of material offshoring, by contrast, the international component drives the main variation of the indices. Our results therefore show that, regarding (business) services, the typical calculation of offshoring indices tends to over estimate the role of the imported inputs component, neglecting the role played by structural changes in the economy.

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Existing distributed hydrologic models are complex and computationally demanding for using as a rapid-forecasting policy-decision tool, or even as a class-room educational tool. In addition, platform dependence, specific input/output data structures and non-dynamic data-interaction with pluggable software components inside the existing proprietary frameworks make these models restrictive only to the specialized user groups. RWater is a web-based hydrologic analysis and modeling framework that utilizes the commonly used R software within the HUBzero cyber infrastructure of Purdue University. RWater is designed as an integrated framework for distributed hydrologic simulation, along with subsequent parameter optimization and visualization schemes. RWater provides platform independent web-based interface, flexible data integration capacity, grid-based simulations, and user-extensibility. RWater uses RStudio to simulate hydrologic processes on raster based data obtained through conventional GIS pre-processing. The program integrates Shuffled Complex Evolution (SCE) algorithm for parameter optimization. Moreover, RWater enables users to produce different descriptive statistics and visualization of the outputs at different temporal resolutions. The applicability of RWater will be demonstrated by application on two watersheds in Indiana for multiple rainfall events.