993 resultados para variables objectives
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Microsoft Windows uses the notion of registry to store all configuration information. The registry entries have associations and dependencies. For example, the paths to executables may be relative to some home directories. The registry being designed with faster access as one of the objectives does not explicitly capture these relations. In this paper, we explore a representation that captures the dependencies more explicitly using shared and unifying variables. This representation, called mRegistry exploits the tree-structured hierarchical nature of the registry, is concept-based and obtained in multiple stages. mRegistry captures intra-block, inter-block and ancestor-children dependencies (all leaf entries of a parent key in a registry put together as an entity constitute a block thereby making the block as the only child of the parent). In addition, it learns the generalized concepts of dependencies in the form of rules. We show that mRegistry has several applications: fault diagnosis, prediction, comparison, compression etc.
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Three algorithms for reactive power optimization are proposed in this paper with three different objective functions. The objectives in the proposed algorithm are to minimize the sum of the squares of the voltage deviations of the load buses, minimization of sum of squares of voltage stability L-indices of load buses (:3L2) algorithm, and also the objective of system real power loss (Ploss) minimization. The approach adopted is an iterative scheme with successive power flow analysis using decoupled technique and solution of the linear programming problem using upper bound optimization technique. Results obtained with all these objectives are compared. The analysis of these objective functions are presented to illustrate their advantages. It is observed comparing different objective functions it is possible to identify critical On Load Tap Changers (OLTCs) that should be made manual to avoid possible voltage instability due to their operation based on voltage improvement criteria under heavy load conditions. These algorithms have been tested under simulated conditions on few test systems. The results obtained on practical systems of 24-node equivalent EHV Indian power network, and for a 205 bus EHV system are presented for illustration purposes.
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Present day power systems are growing in size and complexity of operation with inter connections to neighboring systems, introduction of large generating units, EHV 400/765 kV AC transmission systems, HVDC systems and more sophisticated control devices such as FACTS. For planning and operational studies, it requires suitable modeling of all components in the power system, as the number of HVDC systems and FACTS devices of different type are incorporated in the system. This paper presents reactive power optimization with three objectives to minimize the sum of the squares of the voltage deviations (ve) of the load buses, minimization of sum of squares of voltage stability L-indices of load buses (¿L2), and also the system real power loss (Ploss) minimization. The proposed methods have been tested on typical sample system. Results for Indian 96-bus equivalent system including HVDC terminal and UPFC under normal and contingency conditions are presented.
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Empirical research available on technology transfer initiatives is either North American or European. Literature over the last two decades shows various research objectives such as identifying the variables to be measured and statistical methods to be used in the context of studying university based technology transfer initiatives. AUTM survey data from years 1996 to 2008 provides insightful patterns about the North American technology transfer initiatives, we use this data in our paper. This paper has three sections namely, a comparison of North American Universities with (n=1129) and without Medical Schools (n=786), an analysis of the top 75th percentile of these samples and a DEA analysis of these samples. We use 20 variables. Researchers have attempted to classify university based technology transfer initiative variables into multi-stages, namely, disclosures, patents and license agreements. Using the same approach, however with minor variations, three stages are defined in this paper. The first stage is to do with inputs from R&D expenditure and outputs namely, invention disclosures. The second stage is to do with invention disclosures being the input and patents issued being the output. The third stage is to do with patents issued as an input and technology transfers as outcomes.
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Global change in climate and consequent large impacts on regional hydrologic systems have, in recent years, motivated significant research efforts in water resources modeling under climate change. In an integrated future hydrologic scenario, it is likely that water availability and demands will change significantly due to modifications in hydro-climatic variables such as rainfall, reservoir inflows, temperature, net radiation, wind speed and humidity. An integrated regional water resources management model should capture the likely impacts of climate change on water demands and water availability along with uncertainties associated with climate change impacts and with management goals and objectives under non-stationary conditions. Uncertainties in an integrated regional water resources management model, accumulating from various stages of decision making include climate model and scenario uncertainty in the hydro-climatic impact assessment, uncertainty due to conflicting interests of the water users and uncertainty due to inherent variability of the reservoir inflows. This paper presents an integrated regional water resources management modeling approach considering uncertainties at various stages of decision making by an integration of a hydro-climatic variable projection model, a water demand quantification model, a water quantity management model and a water quality control model. Modeling tools of canonical correlation analysis, stochastic dynamic programming and fuzzy optimization are used in an integrated framework, in the approach presented here. The proposed modeling approach is demonstrated with the case study of the Bhadra Reservoir system in Karnataka, India.
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This paper presents the development and application of a stochastic dynamic programming model with fuzzy state variables for irrigation of multiple crops. A fuzzy stochastic dynamic programming (FSDP) model is developed in which the reservoir storage and soil moisture of the crops are considered as fuzzy numbers, and the reservoir inflow is considered as a stochastic variable. The model is formulated with an objective of minimizing crop yield deficits, resulting in optimal water allocations to the crops by maintaining storage continuity and soil moisture balance. The standard fuzzy arithmetic method is used to solve all arithmetic equations with fuzzy numbers, and the fuzzy ranking method is used to compare two or more fuzzy numbers. The reservoir operation model is integrated with a daily-based water allocation model, which results in daily temporal variations of allocated water, soil moisture, and crop deficits. A case study of an existing Bhadra reservoir in Karnataka, India, is chosen for the model application. The FSDP is a more realistic model because it considers the uncertainty in discretization of state variables. The results obtained using the FSDP model are found to be more acceptable for the case study than those of the classical stochastic dynamic model and the standard operating model, in terms of 10-day releases from the reservoir and evapotranspiration deficit. (C) 2015 American Society of Civil Engineers.
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The cybernetic modeling framework for the growth of microorganisms provides for an elegant methodology to account for the unknown regulatory phenomena through the use of cybernetic variables for enzyme induction and activity. In this paper, we revisit the assumption of limited resources for enzyme induction (Sigma u(i) = 1) used in the cybernetic modeling framework by presenting a methodology for inferring the individual cybernetic variables u(i) from experimental data. We use this methodology to infer u(i) during the simultaneous consumption of glycerol and lactose by Escherichia coli and then model the fitness trade-offs involved in the recently discovered predictive regulation strategy of microorganisms.
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We develop an approximate analytical technique for evaluating the performance of multi-hop networks based on beaconless IEEE 802.15.4 ( the ``ZigBee'' PHY and MAC), a popular standard for wireless sensor networks. The network comprises sensor nodes, which generate measurement packets, relay nodes which only forward packets, and a data sink (base station). We consider a detailed stochastic process at each node, and analyse this process taking into account the interaction with neighbouring nodes via certain time averaged unknown variables (e.g., channel sensing rates, collision probabilities, etc.). By coupling the analyses at various nodes, we obtain fixed point equations that can be solved numerically to obtain the unknown variables, thereby yielding approximations of time average performance measures, such as packet discard probabilities and average queueing delays. The model incorporates packet generation at the sensor nodes and queues at the sensor nodes and relay nodes. We demonstrate the accuracy of our model by an extensive comparison with simulations. As an additional assessment of the accuracy of the model, we utilize it in an algorithm for sensor network design with quality-of-service (QoS) objectives, and show that designs obtained using our model actually satisfy the QoS constraints (as validated by simulating the networks), and the predictions are accurate to well within 10% as compared to the simulation results in a regime where the packet discard probability is low. (C) 2015 Elsevier B.V. All rights reserved.
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Based on the internal variable theory, a viscoelastic constitutive model of a highly deformable continuous medium is proposed. A set of second rank tensorial internal state variables corresponding to Biot's strain is introduced, and a nonlinear evolution
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La leptospirosis es considerada una de las zoonosis más difundidas en el mundo entero. El perro actúa como un potencial diseminador de esta enfermedad ya que mantiene una estrecha relación con el hombre, y al mismo tiempo con otros animales tanto domésticos como salvajes. Con el objetivo de conocer la presencia de leptospirosis canina, se realizó estudio en ocho barrios del distrito dos de la cuidad de Managua entre 8 de septiembre al 9 de diciembre 2007. Se realizó un muestreo de 76 canes, correspondiente al 5% del total de canes en los ocho barrios. Se extrajo 3ml de sangre de la vena safena externa, luego de procesarlas para separar el suero sanguíneo del plasma mediante centrifugación, fueron trasladadas al laboratorio del Centro Veterinario de Diagnóstico e Investigación CEVEDI, UNAN-León, para su análisis mediante los métodos ELISA y MAT. De acuerdo con los resultados obtenidos mediante la prueba ELISA un 93.4%, 71 canes, son negativos y un 6.6%, o bien 5 especímenes, son seropositivos a Leptospira spp. Según los resultados de la prueba de micro aglutinación MAT, el 96.1% de la población muestreada es negativa y el 3.9% es positiva a leptospirosis encontrándose los siguientes serovares canico/a, icterohemorragiae, pyrogenes.
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El presente trabajo de investigación se estableció entre los meses de Noviembre 2007-Marzo 2008, bajo sistema de riego en la estación experimental El Plantel propiedad de la Universidad Nacional Agraria (UNA), ubicada en el km 42 ½ de la carretera Tipitapa–Masaya, municipio de Tisma en las coordenadas 12 o 07’ 3.84’’ latitud norte y 86 o 05’ 26.085’’ longitud oeste a una altura de 200 msnm. Con el objetivo de comparar el crecimiento y rendimiento del cultivo maíz, variedad NB-6, se establecierondos tratamientos, con prácticas de manejo convencional y orgánico, el tamaño de la parcela experimental fué de 432m2 (16 m x 27 m) y el tamaño de cada parcela útil fue de 46.8 m2 (6 m x 7.8 m), en ambos manejos. Las variables evaluadas fueron; altura de planta, diámetro de tallo, número de hojas, área foliar, longitud de mazorca, diámetro de mazorca, número de hileras por mazorca, número de granos por hileras, número de granos por mazorca, peso de mil granos y rendimiento. Los datos fueron analizados con el programa estadístico SAS versión 9.1, año 2006; realizando comparaciones de medias para cada variable en las dos prácticas de manejo. Los resultados muestran que no hubo diferencia significativa para las variables de crecimiento, tomadas en momentos diferentes. Se encontró diferencia significativa para las variables de rendimiento; longitud de la mazorca y diámetro de la mazorca. El manejo orgánico obtuvo los mayores rendimientos con un total de 3869.78kgha-1, seguido del manejo convencional con 3060.29 kgha-1.
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Resumen: En el marco de la integración de etapas en procesos de producción industrial en serie, se identifican, clasifican y caracterizan las variables que permiten modelizar dicho proceso, como estrategia con vistas a su optimización. El estudio se aplica en el ámbito de la industria metalúrgica, a partir de los datos de un conjunto de empresas de la región centro y sur de Santa Fe. La estructura secuencial de un proceso industrial hace que cualquier falla en una etapa cause demoras o reducción de calidad en el producto final obtenido. Como herramienta integradora de análisis, se plantea la implementación de un sistema de redes neuronales artificiales.
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La importancia que el cultivo de fresa ( Fragaria spp.) tiene para los pequeños productores de El Castillito, municipio Las Sabanas del departamento de Madríz, orienta la implementación de técnicas agrícolas que incrementen sus rendimientos. Asimismo, el conocimiento de las condiciones climáticas es esencial para la producción de este rubro. En base a lo anterior se llevó a cabo el presente estudio con el objetivo de describir las características y las condiciones climáticas adecuadas para el establecimiento de este cultivo. Para el análisis se utilizó una estación experimental Kestrel 4 000 Pocket de la cual se tomaron los registros. Se obtuvieron 9 263 observaciones de 11 variables climáticas y fueron objeto de análisis univariado y multivariado. Mediante la información se determinó la evapotranspiración del sitio de estudio. Los rendimientos promedios históricos fueron analizados y contrastados con los meses en los cuales se estableció el cultivo. Las variables climáticas en los meses del año difieren de manera significativa en El Castillito, algunas características son propias de algunos meses. El grupo compuesto por los meses de diciembre a abril, se diferencian del grupo compuesto por los meses de junio a septiembre. Las condiciones de El Castillito son apropiadas para la producción de fresa, siempre y cuando ésta sea establecida durante los meses de junio a agosto. La evapotranspiración del cultivo osciló entre 2.5 a 5 mm día -1 , y mediante esto se propone utilizar láminas de riego entre uno y 1.5 litros por planta por día.