897 resultados para Analytical hierarchical process


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The present study – employing psychometric meta-analysis of 92 independent studies with sample sizes ranging from 26 to 322 leaders – examined the relationship between EI and leadership effectiveness. Overall, the results supported a linkage between leader EI and effectiveness that was moderate in nature (ρ = .25). In addition, the positive manifold of the effect sizes presented in this study, ranging from .10 to .44, indicate that emotional intelligence has meaningful relations with myriad leadership outcomes including effectiveness, transformational leadership, LMX, follower job satisfaction, and others. Furthermore, this paper examined potential process mechanisms that may account for the EI-leadership effectiveness relationship and showed that both transformational leadership and LMX partially mediate this relationship. However, while the predictive validities of EI were moderate in nature, path analysis and hierarchical regression suggests that EI contributes less than or equal to 1% of explained variance in leadership effectiveness once personality and intelligence are accounted for.

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This dissertation provides an analytical framework to study the political economy of policy reform in the Dominican Republic during the nineties. Based on a country study, I develop two theoretical models that replicate the mechanisms of policy approval in developing countries with weak democracies. The first model considers a pro-reform President who submits a tariff bill to an anti-reform Congress dominated by the opposition party. In between, two opposing lobbies try to get their favored policy approved. Lobbies act as Stackelberg leaders vis a vis a weak President. The behavior of the Congress is determined exogenously while the lobbies act strategically pursuing the approval of the reform bill and indirectly affecting the President's decision. I show that in such a setting external agents like the Press play an important role in the decision-making process of the political actors. The second model presents a similar framework. However, the President, who is a Stackelberg leader, is allowed only two choices, total reform or status-quo. I show how a lobby reacts to an increase in its rival's or its own size. These reactions depend on the President's level of commitment to the reform. Finally, I discuss the effect of variations in the size of the lobbies on the President's choice. The model suitably explains real events that took place in the Dominican Republic in the mid-nineties.

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The occurrence of hand grindstones at the Cogotas I archaeological sites is considered to be a common feature. Given that a distant-provenance raw material is frequently involved, determination of its source is a basic factor in the search for a better understanding of resource management and for any Political Economy approach. To progress in these directions an overall study should be planned, using selected grindstones with a view to covering diverse sub-zones of the Cogotas I dispersal area, especially because of its considerable distance from the granite basement source. Such a study may today includes diverse analytical procedures combining successive geographic, petrographic, mineralogical and geochemical criteria. To check the plausibility of the proposed methodology, a preliminary test has been carried out on two granite grindstones, obtained at the archaeological excavation at the Castronuño (Valladolid) Cogotian site, which is fifty km away from an inferred source area that was presumably located at Peñausende (Zamora). The result obtained validates the proposed operational process, yielding a generalizable knowledge to other similar situations.

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The present study was done in collaboration with J. Faria e Filhos company, a Madeira wine producer, and its main goal was to fully characterize three wines produced during 2014 harvest and identify possible improving points in the winemaking process. The winemaking process was followed during 4 weeks, being registered the amounts of grapes received, the fermentation temperatures, the time at which fermentation was stopped and evolution of must densities until the fortification time. The characterization of musts and wines was done in terms of density, total and volatile acidity, alcohol content, pH, total of polyphenol, organic acids composition, sugars concentration and the volatile profile. Also, it was developed and validated an analytical methodology to quantify the volatile fatty acids, namely using SPME-GC-MS. Briefly, the following key features were obtained for the latter methodology: linearity (R2=0.999) e high sensitivity (LOD =0.026-0.068 mg/L), suitable precision (repeatability and reproducibility lower than 8,5%) and good recoveries (103,11-119,46%). The results reveal that fermentation temperatures should be controlled in a more strictly manner, in order to ensure a better balance in proportion of some volatile compounds, namely the esters and higher alcohols and to minimize the concentration of some volatiles, namely hexanoic, octanoic and decanoic acids, that when above their odours threshold are not positive for the wine aroma. Also, regarding the moment to stop the fermentation, it was verified that it can be introduced changes which can also be benefit to guarantee the tipicity of Madeira wine bouquet.

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This paper proposes the joint use of the AHP (Analytic Hierarchy Process) and the ICB (IPMA Competence Baseline), as a tool for the decision-making process of selecting the most suitable managers for projects. A hierarchical structure, comprising the IPMA’s ICB 3.0 contextual, behavioural and technical competence elements, is constructed for the selection of project managers. It also describes the AHP implementation, illustrating the whole process with an example using all the 46 ICB competence elements as model criteria. This tool can be of high interest to decision-makers because it allows comparing the candidates for managing a project using a systematic and rigorous process with a rich set of proven criteria.

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This case study research reports on a small and medium-sized (SME) business-to-business (B2B) services firm implementing a novel new service development (NSD) process. It provides accounts of what occurred in practice in terms of the challenges to NSD process implementation and how the firm overcame these challenges. It also considers the implications for NSD in this and other firms’ innovation practices. This longitudinal case study (18 months) was conducted “inside” the case organization. It covered the entire innovation process from the initiation to the launch of a new service. The primary method may be viewed as participant observation. The research involved all those participating in the innovation system in the firm, including decision-makers, middle managers and employees at lower hierarchical levels and the firm’s external networks. Implications for researchers and managers focusing on structured innovation models for the services sector are also presented.

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Emergence in the sociology of Mead: Process, interaction and the conditions ofsocial life. Within sociology, and especially in the symbolic interaction genre thereof, emergence have been used in order to analyze the process between different dichotomies such as structure and agency, individual and collective, improvisation and the pre-determined as well as the relationship between a now, a past and a present. The aim of this article is to, based on mentioned dichotomies, discuss the possibilities and the limitations of emergence. In terms of possibilities emergence can be used as an analytical and theoretical tool for analyzing the process between different social phenomena. In terms of limitations, emergence could (and have been) criticized for not acknowledging the pre-conditioned aspects of social life. Hence, this article is concluded in a discussion on how to integrate pre-conditioned aspects of social life, such as power, dominance and subordination in the analysis of the emergent and dynamic social life.

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Creative ways of utilising renewable energy sources in electricity generation especially in remote areas and particularly in countries depending on imported energy, while increasing energy security and reducing cost of such isolated off-grid systems, is becoming an urgently needed necessity for the effective strategic planning of Energy Systems. The aim of this research project was to design and implement a new decision support framework for the optimal design of hybrid micro grids considering different types of different technologies, where the design objective is to minimize the total cost of the hybrid micro grid while at the same time satisfying the required electric demand. Results of a comprehensive literature review, of existing analytical, decision support tools and literature on HPS, has identified the gaps and the necessary conceptual parts of an analytical decision support framework. As a result this research proposes and reports an Iterative Analytical Design Framework (IADF) and its implementation for the optimal design of an Off-grid renewable energy based hybrid smart micro-grid (OGREH-SμG) with intra and inter-grid (μG2μG & μG2G) synchronization capabilities and a novel storage technique. The modelling design and simulations were based on simulations conducted using HOMER Energy and MatLab/SIMULINK, Energy Planning and Design software platforms. The design, experimental proof of concept, verification and simulation of a new storage concept incorporating Hydrogen Peroxide (H2O2) fuel cell is also reported. The implementation of the smart components consisting Raspberry Pi that is devised and programmed for the semi-smart energy management framework (a novel control strategy, including synchronization capabilities) of the OGREH-SμG are also detailed and reported. The hybrid μG was designed and implemented as a case study for the Bayir/Jordan area. This research has provided an alternative decision support tool to solve Renewable Energy Integration for the optimal number, type and size of components to configure the hybrid μG. In addition this research has formulated and reported a linear cost function to mathematically verify computer based simulations and fine tune the solutions in the iterative framework and concluded that such solutions converge to a correct optimal approximation when considering the properties of the problem. As a result of this investigation it has been demonstrated that, the implemented and reported OGREH-SμG design incorporates wind and sun powered generation complemented with batteries, two fuel cell units and a diesel generator is a unique approach to Utilizing indigenous renewable energy with a capability of being able to synchronize with other μ-grids is the most effective and optimal way of electrifying developing countries with fewer resources in a sustainable way, with minimum impact on the environment while also achieving reductions in GHG. The dissertation concludes with suggested extensions to this work in the future.

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Le processus de planification forestière hiérarchique présentement en place sur les terres publiques risque d’échouer à deux niveaux. Au niveau supérieur, le processus en place ne fournit pas une preuve suffisante de la durabilité du niveau de récolte actuel. À un niveau inférieur, le processus en place n’appuie pas la réalisation du plein potentiel de création de valeur de la ressource forestière, contraignant parfois inutilement la planification à court terme de la récolte. Ces échecs sont attribuables à certaines hypothèses implicites au modèle d’optimisation de la possibilité forestière, ce qui pourrait expliquer pourquoi ce problème n’est pas bien documenté dans la littérature. Nous utilisons la théorie de l’agence pour modéliser le processus de planification forestière hiérarchique sur les terres publiques. Nous développons un cadre de simulation itératif en deux étapes pour estimer l’effet à long terme de l’interaction entre l’État et le consommateur de fibre, nous permettant ainsi d’établir certaines conditions pouvant mener à des ruptures de stock. Nous proposons ensuite une formulation améliorée du modèle d’optimisation de la possibilité forestière. La formulation classique du modèle d’optimisation de la possibilité forestière (c.-à-d., maximisation du rendement soutenu en fibre) ne considère pas que le consommateur de fibre industriel souhaite maximiser son profit, mais suppose plutôt la consommation totale de l’offre de fibre à chaque période, peu importe le potentiel de création de valeur de celle-ci. Nous étendons la formulation classique du modèle d’optimisation de la possibilité forestière afin de permettre l’anticipation du comportement du consommateur de fibre, augmentant ainsi la probabilité que l’offre de fibre soit entièrement consommée, rétablissant ainsi la validité de l’hypothèse de consommation totale de l’offre de fibre implicite au modèle d’optimisation. Nous modélisons la relation principal-agent entre le gouvernement et l’industrie à l’aide d’une formulation biniveau du modèle optimisation, où le niveau supérieur représente le processus de détermination de la possibilité forestière (responsabilité du gouvernement), et le niveau inférieur représente le processus de consommation de la fibre (responsabilité de l’industrie). Nous montrons que la formulation biniveau peux atténuer le risque de ruptures de stock, améliorant ainsi la crédibilité du processus de planification forestière hiérarchique. Ensemble, le modèle biniveau d’optimisation de la possibilité forestière et la méthodologie que nous avons développée pour résoudre celui-ci à l’optimalité, représentent une alternative aux méthodes actuellement utilisées. Notre modèle biniveau et le cadre de simulation itérative représentent un pas vers l’avant en matière de technologie de planification forestière axée sur la création de valeur. L’intégration explicite d’objectifs et de contraintes industrielles au processus de planification forestière, dès la détermination de la possibilité forestière, devrait favoriser une collaboration accrue entre les instances gouvernementales et industrielles, permettant ainsi d’exploiter le plein potentiel de création de valeur de la ressource forestière.

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The present study was done in collaboration with J. Faria e Filhos company, a Madeira wine producer, and its main goal was to fully characterize three wines produced during 2014 harvest and identify possible improving points in the winemaking process. The winemaking process was followed during 4 weeks, being registered the amounts of grapes received, the fermentation temperatures, the time at which fermentation was stopped and evolution of must densities until the fortification time. The characterization of musts and wines was done in terms of density, total and volatile acidity, alcohol content, pH, total of polyphenol, organic acids composition, sugars concentration and the volatile profile. Also, it was developed and validated an analytical methodology to quantify the volatile fatty acids, namely using SPME-GC-MS. Briefly, the following key features were obtained for the latter methodology: linearity (R2=0.999) e high sensitivity (LOD =0.026-0.068 mg/L), suitable precision (repeatability and reproducibility lower than 8,5%) and good recoveries (103,11-119,46%). The results reveal that fermentation temperatures should be controlled in a more strictly manner, in order to ensure a better balance in proportion of some volatile compounds, namely the esters and higher alcohols and to minimize the concentration of some volatiles, namely hexanoic, octanoic and decanoic acids, that when above their odours threshold are not positive for the wine aroma. Also, regarding the moment to stop the fermentation, it was verified that it can be introduced changes which can also be benefit to guarantee the tipicity of Madeira wine bouquet.

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This thesis describes the development and correlation of a thermal model that forms the foundation of a thermal capacitance spacecraft propellant load estimator. Specific details of creating the thermal model for the diaphragm propellant tank used on NASA’s Magnetospheric Multiscale spacecraft using ANSYS and the correlation process implemented are presented. The thermal model was correlated to within +/- 3 Celsius of the thermal vacuum test data, and was determined sufficient to make future propellant predictions on MMS. The model was also found to be relatively sensitive to uncertainties in applied heat flux and mass knowledge of the tank. More work is needed to improve temperature predictions in the upper hemisphere of the propellant tank where predictions were found to be 2-2.5 Celsius lower than the test data. A road map for applying the model to predict propellant loads on the actual MMS spacecraft in 2017-2018 is also presented.

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A new procedure was developed in this study, based on a system equipped with a cellulose membrane and a tetraethylenepentamine hexaacetate chelator (MD-TEPHA) for in situ characterization of the lability of metal species in aquatic systems. To this end, the DM-TEPHA system was prepared by adding TEPHA chelator to cellulose bags pre-purified with 1.0 mol L-1 of HCl and NaOH solutions. After the MD-TEPHA system was sealed, it was examined in the laboratory to evaluate the influence of complexation time (0-24 h), pH (3.0, 4.0, 5.0, 6.0 and 7.0), metal ions (Cu, Cd, Fe, Mn and Ni) and concentration of organic matter (15, 30 and 60 mg L-1) on the relative lability of metal species by TEPHA chelator. The results showed that Fe and Cu metals were complexed more slowly by TEPHA chelator in the MD-TEPHA system than were Cd, Ni and Mn in all pH used. It was also found that the pH strongly influences the process of metal complexation by the MD-TEPHA system. At all the pH levels, Cd, Mn and Ni showed greater complexation with TEPHA chelator (recovery of about 95-75%) than did Cu and Fe metals. Time also affects the lability of metal species complexed by aquatic humic substances (AHS); while Cd, Ni and Mn showed a faster kinetics, reaching equilibrium after about 100 min, and Cu and Fe approached equilibrium after 400 min. Increasing the AHS concentration decreases the lability of metal species by shifting the equilibrium to AHS-metal complexes. Our results indicate that the system under study offers an interesting alternative that can be applied to in situ experiments for differentiation of labile and inert metal species in aquatic systems. (c) 2006 Elsevier B.V. All rights reserved.

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We study a reaction–diffusion mathematical model for the evolution of atherosclerosis as an inflammation process by combining analytical tools with computer-intensive numerical calculations. The computational work involved the calculation of more than sixty thousand solutions of the full reaction–diffusion system and lead to the complete characterisation of the ωω-limit for every initial condition. Qualitative properties of the solution are rigorously proved, some of them hinted at by the numerical study

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[EN] A new concept for fluid flow manipulation in microfluidic paper-based analytical devices (m-PADs) is presented by introducing ionogel materials as passive pumps. m-PADs were fabricated using a new doubleside contact stamping process and ionogels were precisely photopolymerised at the inlet of the m-PADs.The ionogels remain mainly on the surface of the paper and get absorbed in the superficial paper-fibers allowing for the liquid to flow from the ionogel into the paper easily. As a proof of concept the fluid flowand mixing behaviour of two different ionogels mPADs were compared with the non-treated mPADs.It was demonstrated that both ionogels highly affect the fluid flow by delaying the flow due to their different physical and chemical properties and water holding capacities.

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Understanding how virus strains offer protection against closely related emerging strains is vital for creating effective vaccines. For many viruses, including Foot-and-Mouth Disease Virus (FMDV) and the Influenza virus where multiple serotypes often co-circulate, in vitro testing of large numbers of vaccines can be infeasible. Therefore the development of an in silico predictor of cross-protection between strains is important to help optimise vaccine choice. Vaccines will offer cross-protection against closely related strains, but not against those that are antigenically distinct. To be able to predict cross-protection we must understand the antigenic variability within a virus serotype, distinct lineages of a virus, and identify the antigenic residues and evolutionary changes that cause the variability. In this thesis we present a family of sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution (SABRE), as well as an extended version of the method, the extended SABRE (eSABRE) method, which better takes into account the data collection process. The SABRE methods are a family of sparse Bayesian hierarchical models that use spike and slab priors to identify sites in the viral protein which are important for the neutralisation of the virus. In this thesis we demonstrate how the SABRE methods can be used to identify antigenic residues within different serotypes and show how the SABRE method outperforms established methods, mixed-effects models based on forward variable selection or l1 regularisation, on both synthetic and viral datasets. In addition we also test a number of different versions of the SABRE method, compare conjugate and semi-conjugate prior specifications and an alternative to the spike and slab prior; the binary mask model. We also propose novel proposal mechanisms for the Markov chain Monte Carlo (MCMC) simulations, which improve mixing and convergence over that of the established component-wise Gibbs sampler. The SABRE method is then applied to datasets from FMDV and the Influenza virus in order to identify a number of known antigenic residue and to provide hypotheses of other potentially antigenic residues. We also demonstrate how the SABRE methods can be used to create accurate predictions of the important evolutionary changes of the FMDV serotypes. In this thesis we provide an extended version of the SABRE method, the eSABRE method, based on a latent variable model. The eSABRE method takes further into account the structure of the datasets for FMDV and the Influenza virus through the latent variable model and gives an improvement in the modelling of the error. We show how the eSABRE method outperforms the SABRE methods in simulation studies and propose a new information criterion for selecting the random effects factors that should be included in the eSABRE method; block integrated Widely Applicable Information Criterion (biWAIC). We demonstrate how biWAIC performs equally to two other methods for selecting the random effects factors and combine it with the eSABRE method to apply it to two large Influenza datasets. Inference in these large datasets is computationally infeasible with the SABRE methods, but as a result of the improved structure of the likelihood, we are able to show how the eSABRE method offers a computational improvement, leading it to be used on these datasets. The results of the eSABRE method show that we can use the method in a fully automatic manner to identify a large number of antigenic residues on a variety of the antigenic sites of two Influenza serotypes, as well as making predictions of a number of nearby sites that may also be antigenic and are worthy of further experiment investigation.