994 resultados para Preference modelling
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Mixture of distributions, decreasing failure rate, increasing failure rate, proportional hazards model, accelerated life model, asymptotic behavior of mixture failure rate
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Dynamic model, tubular reactor, polyethylene, LDPE, discretization, simulation, sensitivity analysis, nonlinear analysis
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Nanopartikel, BaSO4, Mikroemulsion, Fällung, Modellierung
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Mo-Si-B alloys, Real microstructures, Voronoi structures, Microstructural characterization, Modelling and finite element simulations, Effective material properties, Damage and Crack growth, tensile strength, fracture toughness
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Magdeburg, Univ., Fak. für Mathematik, Diss., 2009
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Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2009
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Magdeburg, Univ., Fak. für Informatik, Diss., 2015
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At the moment there is a lack of methodological approaches to formalization of management of innovative projects relating to production systems, as well as to adaptation and practical use of the existing approaches. This article is about one potential approach to the management of innovative projects, which makes the building of innovative process models possible based on objective approach. It outlines the frameworks for the building of innovative project models, and describes the method of transition from conceptual modelling to innovative project management. In this case, the model alone and together with parameters used for evaluation of the project may be unique and depends on the special features of the project, preferences of decision-making person, and production and economic system in which it is to be implemented. Unlike existing approaches, this concept does not place any restrictions on types of models and makes it possible to take into account the specificities of economic and production systems. Principles embodied in the model allow its usage as a basis for simulation model to be used in one of specialized simulation systems, as well as for information system providing information support of decision-making process in production and economic systems both newly developed by the company (enterprise) and designed on the basis of available information systems that interact through the exchange of data. In addition, this article shows that the development of conceptual foundations of innovative project management in the economic and production systems is inseparable from the development of the theory of industrial control systems, and their comprehensive study may be reduced to a set of elements represented as certain algorithms, models and evaluations. Thus, the study of innovative process may be conducted in both directions: from general to particular, and vice versa.
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The influence of two factors, age and previous experience, on the oviposition hierarchy preference of Ceratitis capitata (Wiedemann, 1824) females was studied. Two populations were analyzed: one reared in laboratory during 17 years and the other captured in nature. In the first experiment the oviposition preference for four fruits, papaya, orange, banana and apple was tested at the beginning of oviposition period and 20 days past. The results showed that the wild females as much the laboratory ones had an oviposition preference hierarchy at the beginning of peak period of oviposition. However this hierarchic preference disappeared in a later phase of life. In the second experiment the females were previously exposed to fruits of different hierarchic positions and afterwards their choice was tested in respect to the oviposition preference for those fruits. The results showed that there was an influence of the previous experience on the posterior choice of fruits to oviposition when the females were exposed to fruits of lower hierarchic position.
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We assessed the species composition and abundance of medium and large-sized mammals in an urban forest fragment in the Brazilian Amazon, and recorded the preference of some species for particular phytophysiognomies. We placed nine transects with 20 sand plots each in three phytophysiognomies: open rainforest with a dominance of bamboos (OFB), open rainforest with palm trees (OFP), and dense rainforest (DF). We calculated species abundance as the number of records/plot.day, in a total of 2,700 plots.day. We recorded twelve mammal species; Sylvilagus brasiliensis (Linnaeus, 1758) and Dasyprocta fuliginosa (Wagler, 1831) were the most abundant. The results differed among phytophysiognomies: DF presented the highest mammal diversity, whereas the species composition of OFP was less similar than that of other phytophysiognomies. Rodents showed higher preference for OFP and Sylvilagus brasiliensis was more abundant in OFB. The study area showed high species richness, with the occurrence of mesopredators, but there was a predominance of common species adaptable to disturbed environments, which reflects the severe isolation degree of the forest fragment and the hunting pressure that is still present.
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Empirical studies on industrial location do not typically distinguish between new and relocated establishments. This paper addresses this shortcoming using data on the frequency of these events in municipalities of the same economic-administrative region. This enables us to test not only for differences in their determinants but also for interrelations between start-ups and relocations. Estimates from count regression models for cross-section and panel data show that, although partial effects differ, common patterns arise in “institutional” and “neoclassical” explanatory factors. Also, start-ups and relocations are positive but asymmetrically related. JEL classification: C25, R30, R10. Keywords: cities, count data models, industrial location
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Els bacteris són la forma dominant de vida del planeta: poden sobreviure en medis molt adversos, i en alguns casos poden generar substàncies que quan les ingerim ens són tòxiques. La seva presència en els aliments fa que la microbiologia predictiva sigui un camp imprescindible en la microbiologia dels aliments per garantir la seguretat alimentària. Un cultiu bacterià pot passar per quatre fases de creixement: latència, exponencial, estacionària i de mort. En aquest treball s’ha avançat en la comprensió dels fenòmens intrínsecs a la fase de latència, que és de gran interès en l’àmbit de la microbiologia predictiva. Aquest estudi, realitzat al llarg de quatre anys, s’ha abordat des de la metodologia Individual-based Modelling (IbM) amb el simulador INDISIM (INDividual DIScrete SIMulation), que ha estat millorat per poder fer-ho. INDISIM ha permès estudiar dues causes de la fase de latència de forma separada, i abordar l’estudi del comportament del cultiu des d’una perspectiva mesoscòpica. S’ha vist que la fase de latència ha de ser estudiada com un procés dinàmic, i no definida per un paràmetre. L’estudi de l’evolució de variables com la distribució de propietats individuals entre la població (per exemple, la distribució de masses) o la velocitat de creixement, han permès distingir dues etapes en la fase de latència, inicial i de transició, i aprofundir en la comprensió del que passa a nivell cel•lular. S’han observat experimentalment amb citometria de flux diversos resultats previstos per les simulacions. La coincidència entre simulacions i experiments no és trivial ni casual: el sistema estudiat és un sistema complex, i per tant la coincidència del comportament al llarg del temps de diversos paràmetres interrelacionats és un aval a la metodologia emprada en les simulacions. Es pot afirmar, doncs, que s’ha verificat experimentalment la bondat de la metodologia INDISIM.
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The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.