950 resultados para Parametric duration model
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Ethanol-gasoline fuel blends are increasingly being used in spark ignition (SI) engines due to continued growth in renewable fuels as part of a growing renewable portfolio standard (RPS). This leads to the need for a simple and accurate ethanol-gasoline blends combustion model that is applicable to one-dimensional engine simulation. A parametric combustion model has been developed, integrated into an engine simulation tool, and validated using SI engine experimental data. The parametric combustion model was built inside a user compound in GT-Power. In this model, selected burn durations were computed using correlations as functions of physically based non-dimensional groups that have been developed using the experimental engine database over a wide range of ethanol-gasoline blends, engine geometries, and operating conditions. A coefficient of variance (COV) of gross indicated mean effective pressure (IMEP) correlation was also added to the parametric combustion model. This correlation enables the cycle combustion variation modeling as a function of engine geometry and operating conditions. The computed burn durations were then used to fit single and double Wiebe functions. The single-Wiebe parametric combustion compound used the least squares method to compute the single-Wiebe parameters, while the double-Wiebe parametric combustion compound used an analytical solution to compute the double-Wiebe parameters. These compounds were then integrated into the engine model in GT-Power through the multi-Wiebe combustion template in which the values of Wiebe parameters (single-Wiebe or double-Wiebe) were sensed via RLT-dependence. The parametric combustion models were validated by overlaying the simulated pressure trace from GT-Power on to experimentally measured pressure traces. A thermodynamic engine model was also developed to study the effect of fuel blends, engine geometries and operating conditions on both the burn durations and COV of gross IMEP simulation results.
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Consecrated in 1297 as the monastery church of the four years earlier founded St. Catherine’s monastery, the Gothic Church of St. Catherine was largely destroyed in a devastating bombing raid on January 2nd 1945. To counteract the process of disintegration, the departments of geo-information and lower monument protection authority of the City of Nuremburg decided to getting done a three dimensional building model of the Church of St. Catherine’s. A heterogeneous set of data was used for preparation of a parametric architectural model. In effect the modeling of historic buildings can profit from the so called BIM method (Building Information Modeling), as the necessary structuring of the basic data renders it into very sustainable information. The resulting model is perfectly suited to deliver a vivid impression of the interior and exterior of this former mendicant orders’ church to present observers.
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Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.
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The suitability of a total-length-based, minimum capture-size and different protection regimes was investigated for the gooseneck barnacle Pollicipes pollicipes shellfishery in N Spain. For this analysis, individuals that were collected from 10 sites under different fishery protection regimes (permanently open, seasonally closed, and permanently closed) were used. First, we applied a non-parametric regression model to explore the relationship between the capitulum Rostro-Tergum (RT) size and the Total Length (TL). Important heteroskedastic disturbances were detected for this relationship, demon- strating a high variability of TL with respect to RT. This result substantiates the unsuitability of a TL-based minimum size by means of a mathematical model. Due to these disturbances, an alternative growth- based minimum capture size of 26.3 mm RT (23 mm RC) was estimated using the first derivative of a Kernel-based non-parametric regression model for the relationship between RT and dry weight. For this purpose, data from the permanently protected area were used to avoid bias due to the fishery. Second, the size-frequency distribution similarity was computed using a MDS analysis for the studied sites to evaluate the effectiveness of the protection regimes. The results of this analysis indicated a positive effect of the permanent protection, while the effect of the seasonal closure was not detected. This result needs to be interpreted with caution because the current harvesting based on a potentially unsuitable mini- mum capture size may dampen the efficacy of the seasonal protection regime.
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In the PhD thesis “Sound Texture Modeling” we deal with statistical modelling or textural sounds like water, wind, rain, etc. For synthesis and classification. Our initial model is based on a wavelet tree signal decomposition and the modeling of the resulting sequence by means of a parametric probabilistic model, that can be situated within the family of models trainable via expectation maximization (hidden Markov tree model ). Our model is able to capture key characteristics of the source textures (water, rain, fire, applause, crowd chatter ), and faithfully reproduces some of the sound classes. In terms of a more general taxonomy of natural events proposed by Graver, we worked on models for natural event classification and segmentation. While the event labels comprise physical interactions between materials that do not have textural propierties in their enterity, those segmentation models can help in identifying textural portions of an audio recording useful for analysis and resynthesis. Following our work on concatenative synthesis of musical instruments, we have developed a pattern-based synthesis system, that allows to sonically explore a database of units by means of their representation in a perceptual feature space. Concatenative syntyhesis with “molecules” built from sparse atomic representations also allows capture low-level correlations in perceptual audio features, while facilitating the manipulation of textural sounds based on their physical and perceptual properties. We have approached the problem of sound texture modelling for synthesis from different directions, namely a low-level signal-theoretic point of view through a wavelet transform, and a more high-level point of view driven by perceptual audio features in the concatenative synthesis setting. The developed framework provides unified approach to the high-quality resynthesis of natural texture sounds. Our research is embedded within the Metaverse 1 European project (2008-2011), where our models are contributting as low level building blocks within a semi-automated soundscape generation system.
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This paper studies the duration pattern of xed-term contracts and the determinantsof their conversion into permanent ones in Spain, where the share of xed-termemployment is the highest in Europe. We estimate a duration model for temporaryemployment, with competing risks of terminating into permanent employment versusalternative states, and exible duration dependence. We nd that conversion rates aregenerally below 10%. Our estimated conversion rates roughly increase with tenure,with a pronounced spike at the legal limit, when there is no legal way to retain theworker on a temporary contract. We argue that estimated di¤erences in conversionrates across categories of workers can stem from di¤erences in worker outside optionsand thus the power to credibly threat to quit temporary jobs.
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Parametric cost modeling is a technique, where cost estimating relationships are built to meet products’ parameters. Parameters are directly defined from product features, when it is possible to solve product cost exact before even a single product is manufactured and calculated with general cost accounting. The parametric model can be used in product design, sourcing and comparing product cost of similar products. The model reveals the cost origin more clear than general accounting. The purpose of this thesis was to find out parameters for modeling elevator doors and validate the parameters to meet actual costs. The other target was to simulate cost impact and changes in the cost structure. The results were compared to previous calculations and actual costs and model was tested in new product design. The results of the calculations revealed, that material consumption is the most significant issue in design effectiveness as well as the complexity of the components and structure. To develop the model more research is needed for other continents cost structure and waste calculation principles.
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Diplomityö käsittelee hisseissä erikoistapauksessa käytettävän kulmakorin suunnittelua ja tuotteistamista. Työ suoritetaan KONE Oyj:lle. Diplomityössä luotiin kulmakorille modulaarinen tuotearkkitehtuuri ja määritettiin korin toimitusprosessi. Työn tavoitteena oli saavuttaa 48,12% asiakkaiden mahdollisista vaatimuksista ja vähentää suunnitteluun kuluvaa aikaa aikaisemmasta 24 tunnista neljään tuntiin. Työn tavoite saavutettiin kokeneen tapauskohtaisten kulmakorien suunnittelijan kommenttien perusteella. 48,12% asiakasvaatimuksista sisällytettiin tuotemalliin konfigurointimahdollisuuksina. Työn alussa on esitelty tuotesuunnittelua, laadun hallintaa, parametrista mallinnusta, massakustomointia ja tuotetiedon hallintaa. Sen jälkeen on käsitelty kulmakorin tuotteistamisen kannalta kaikki tärkeimmät muuttujat. Tämän jälkeen kulmakorin tuotemalli suunnitellaan ja mallinnetaan systemaattisesti ylhäältä-alas –mallinnustapaa käyttäen ja luodaan osille ja kokoonpanoille valmistuskuvat. Päätyökaluna työssä käytettiin Pro/ENGINEER-ohjelmistoa. Tällä mallinnettiin parametrinen tuotemalli ja rakenteiden lujuustarkastelussa käytettiin ohjelmistoa Ansys. Työn tavoite saavutettiin analysoimalla massakustomoinnin perusteiden olennaisimmat osat ja seuraamalla analyyttistä ja systemaattista tuotekehitysprosessia. Laatua painottaen tuotearkkitehtuuri validoitiin suorittamalla rajoitettu tuotanto, joka sisälsi kolme tuotemallilla konfiguroitua kulmakoria. Yksi koreista testikasattiin Hyvinkään tehtaalla.
Determinantes de la deserción universitaria en la Facultad de Economía de la Universidad del Rosario
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Este trabajo analiza el problema de la deserción estudiantil en la Facultad de Economía de la Universidad del Rosario, a través del estudio de los factores individuales, académicos y socioeconómicos que implican el riesgo de desertar. Con este objetivo, se utiliza el análisis de modelos de duración. Específi camente, se estima un modelo de riesgo proporcional de tiempo discreto con y sin heterogeneidad observada (Prentice- Gloeckler, 1978 y Meyer, 1980). Los resultados muestran que los estudiantes de sexo masculino, la vinculación de los estudiantes al mercado laboral y los estudiantes provenientes de otras regiones, tienen el mayor riesgo de deserción. Además, la edad del estudiante incrementa el riesgo, sin embargo, su efecto decrece marginalmente al aumentar la edad. Palabras clave: deserción estudiantil, modelos de duración, riesgo proporcional. Clasifi cación JEL: C41, C13, I21.
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Este estudio fue conducido para evaluar la correlación entre lactato arterial y venoso central en niños con sepsis y choque séptico de una unidad de cuidado intensivo pediátrico. Se incluyeron 42 pacientes con edades comprendidas entre 1 mes y 17 años 364 días con diagnóstico de sepsis y choque séptico que ingresaron a la Unidad de Cuidado Intensivo en un hospital universitario de referencia. Se registró el valor del lactato obtenido de una muestra de sangre arterial y de sangre venosa central tomadas simultáneamente y dentro de las primeras 24 horas del ingreso a la unidad. Por medio de la prueba de Rho de Spearman se encontró una correlación de 0,872 (p<0,001) y se ajustó al uso de medicamentos, vasoactivos, edad y peso (modelo de regresión no paramétrico quantílico), manteniéndose una correlación fuerte y significativa.
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This paper attempts an empirical assessment of the incentive effects of plant variety protection regimes in the generation of crop variety innovations. A duration model of plant variety protection certificates is used to infer the private appropriability of returns from agricultural crop variety innovations in the UK over the period 1965-2000. The results suggest that plant variety protection provides only modest appropriability of returns to innovators of agricultural crop varieties. The value distribution of plant variety protection certificates is highly skewed with a large proportion of innovations providing virtually no returns to innovators. Increasing competition from newer varieties appears to have accelerated the turnover of varieties reducing appropriability further. Plant variety protection emerges as a relatively weak instrument of protection.
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This work presents a Bayesian semiparametric approach for dealing with regression models where the covariate is measured with error. Given that (1) the error normality assumption is very restrictive, and (2) assuming a specific elliptical distribution for errors (Student-t for example), may be somewhat presumptuous; there is need for more flexible methods, in terms of assuming only symmetry of errors (admitting unknown kurtosis). In this sense, the main advantage of this extended Bayesian approach is the possibility of considering generalizations of the elliptical family of models by using Dirichlet process priors in dependent and independent situations. Conditional posterior distributions are implemented, allowing the use of Markov Chain Monte Carlo (MCMC), to generate the posterior distributions. An interesting result shown is that the Dirichlet process prior is not updated in the case of the dependent elliptical model. Furthermore, an analysis of a real data set is reported to illustrate the usefulness of our approach, in dealing with outliers. Finally, semiparametric proposed models and parametric normal model are compared, graphically with the posterior distribution density of the coefficients. (C) 2009 Elsevier Inc. All rights reserved.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Bovine mastitis is considered the main disease causing great economic losses in dairy herds. It is usually treated by antimicrobial chemicals that promote drug resistance, residues in food and environmental contamination. However, consumers in different countries requires more natural foods and with higher quality. Thus, the objective was to check the activities of propolis in controlling bovine mastitis. Seventy-two Holstein cows were used. The mastitis was identified by the California Mastitis Test, somatic cell counts and microbiological examination of milk. Four treatments were held: in group EAP1 10ml of a 30% alcoholic propolis extract (EAP) were given orally for seven consecutive days; in group EAP2 the same procedure described for the first group was used, in addition EAP was used for immersion of the teats before and after milking; in group CA alcohol was used for immersion of the teats before and after milking; and in group CT animals were subjected to soaking and disinfection, procedures routinely used by the property. The results were analyzed by the non-parametric variance model for repeated measures complemented by independent groups in multiple comparisons. There was a decrease of the somatic cell count in all groups. The biological activities of propolis provide great prospects; however, under the conditions evaluated, it was not possible to observe differences between treatments. The great diversity in its chemical composition and the complexity of multiple synergistic mechanisms involved in its biological activity require additional clinical trials.