997 resultados para Trust modeling
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics
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Dissertation presented to obtain the Ph.D degree in Biology
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Dissertação para obtenção do Grau de Doutor em Engenharia Informática
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In this thesis, a predictive analytical and numerical modeling approach for the orthogonal cutting process is proposed to calculate temperature distributions and subsequently, forces and stress distributions. The models proposed include a constitutive model for the material being cut based on the work of Weber, a model for the shear plane based on Merchants model, a model describing the contribution of friction based on Zorev’s approach, a model for the effect of wear on the tool based on the work of Waldorf, and a thermal model based on the works of Komanduri and Hou, with a fraction heat partition for a non-uniform distribution of the heat in the interfaces, but extended to encompass a set of contributions to the global temperature rise of chip, tool and work piece. The models proposed in this work, try to avoid from experimental based values or expressions, and simplifying assumptions or suppositions, as much as possible. On a thermo-physical point of view, the results were affected not only by the mechanical or cutting parameters chosen, but also by their coupling effects, instead of the simplifying way of modeling which is to contemplate only the direct effect of the variation of a parameter. The implementation of these models was performed using the MATLAB environment. Since it was possible to find in the literature all the parameters for AISI 1045 and AISI O2, these materials were used to run the simulations in order to avoid arbitrary assumption.
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The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.
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This paper offers a new approach to estimating time-varying covariance matrices in the framework of the diagonal-vech version of the multivariate GARCH(1,1) model. Our method is numerically feasible for large-scale problems, produces positive semidefinite conditional covariance matrices, and does not impose unrealistic a priori restrictions. We provide an empirical application in the context of international stock markets, comparing the nev^ estimator with a number of existing ones.
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In the fields of marketing and general management, many are the contributions of literature relating trust and e‐commerce. Trust is perceived as an issue that concerns the consumers’ intention to purchase. As so, in this research, a path model is empirically tested in order to develop solutions for Internet vendors on how to deal with consumers and increase their trust. The path model measures how the dimensions of trust, named as competence, integrity and benevolence positively influence the overall trust of the consumers and at the same time how the sources of trust – consumer characteristics, firm characteristics, website infrastructure and interactions influence those dimensions. The data used to test the model was collected in Portugal, through 365 valid cases. Findings revealed that consumers, which have high level of overall trust, are more likely to intent to purchase online.
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A potentially renewable and sustainable source of energy is the chemical energy associated with solvation of salts. Mixing of two aqueous streams with different saline concentrations is spontaneous and releases energy. The global theoretically obtainable power from salinity gradient energy due to World’s rivers discharge into the oceans has been estimated to be within the range of 1.4-2.6 TW. Reverse electrodialysis (RED) is one of the emerging, membrane-based, technologies for harvesting the salinity gradient energy. A common RED stack is composed by alternately-arranged cation- and anion-exchange membranes, stacked between two electrodes. The compartments between the membranes are alternately fed with concentrated (e.g., sea water) and dilute (e.g., river water) saline solutions. Migration of the respective counter-ions through the membranes leads to ionic current between the electrodes, where an appropriate redox pair converts the chemical salinity gradient energy into electrical energy. Given the importance of the need for new sources of energy for power generation, the present study aims at better understanding and solving current challenges, associated with the RED stack design, fluid dynamics, ionic mass transfer and long-term RED stack performance with natural saline solutions as feedwaters. Chronopotentiometry was used to determinate diffusion boundary layer (DBL) thickness from diffusion relaxation data and the flow entrance effects on mass transfer were found to avail a power generation increase in RED stacks. Increasing the linear flow velocity also leads to a decrease of DBL thickness but on the cost of a higher pressure drop. Pressure drop inside RED stacks was successfully simulated by the developed mathematical model, in which contribution of several pressure drops, that until now have not been considered, was included. The effect of each pressure drop on the RED stack performance was identified and rationalized and guidelines for planning and/or optimization of RED stacks were derived. The design of new profiled membranes, with a chevron corrugation structure, was proposed using computational fluid dynamics (CFD) modeling. The performance of the suggested corrugation geometry was compared with the already existing ones, as well as with the use of conductive and non-conductive spacers. According to the estimations, use of chevron structures grants the highest net power density values, at the best compromise between the mass transfer coefficient and the pressure drop values. Finally, long-term experiments with natural waters were performed, during which fouling was experienced. For the first time, 2D fluorescence spectroscopy was used to monitor RED stack performance, with a dedicated focus on following fouling on ion-exchange membrane surfaces. To extract relevant information from fluorescence spectra, parallel factor analysis (PARAFAC) was performed. Moreover, the information obtained was then used to predict net power density, stack electric resistance and pressure drop by multivariate statistical models based on projection to latent structures (PLS) modeling. The use in such models of 2D fluorescence data, containing hidden, but extractable by PARAFAC, information about fouling on membrane surfaces, considerably improved the models fitting to the experimental data.
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The aim of this work project is to find a model that is able to accurately forecast the daily Value-at-Risk for PSI-20 Index, independently of the market conditions, in order to expand empirical literature for the Portuguese stock market. Hence, two subsamples, representing more and less volatile periods, were modeled through unconditional and conditional volatility models (because it is what drives returns). All models were evaluated through Kupiec’s and Christoffersen’s tests, by comparing forecasts with actual results. Using an out-of-sample of 204 observations, it was found that a GARCH(1,1) is an accurate model for our purposes.
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Strategic alliances represent a key driver for internationalization and growth, being the purpose of this work project to better understand the intertwined relationship between trust and the existence of an alliance management position. Previous research supports the positive impact of such position in stock market returns. However, little attention has been given to the impact of such position on the level of trust in the collaborative arrangement, which is deemed to be a key driver for alliance success. A qualitative comparative case-study of three Portuguese SMEs is used to draw conclusions from the literature to real life business cases and it demonstrates the positive impact of an alliance management position on trust.
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RESUMO - Introdução: Os critérios de adequação (Appropriate Use Criteria - AUC) em Ecocardiografia Transtorácica (ETT) foram publicados com o intuito de permitir o uso racional da ecocardiografia, de influenciar decisões clinicas, prestar cuidados de saúde de elevada qualidade e melhorar o outcome dos pacientes. A relação entre a adequação destes e o seu impacto clinico ainda não se encontra largamente estudada. Objectivo: Neste estudo pretendeu-se avaliar o grau de adesão aos AUC em ETT, em diferentes contextos de atendimento e de acordo com diferentes especialidades, bem como o impacto clínico do exame no outcome do paciente, num hospital público terciário no Reino Unido. Metodologia: 859 ETTs realizados consecutivamente no mês de Janeiro de 2014, foram revistos por forma a avaliar a sua adequação e foram classificados como adequados, incertos ou inadequados de acordo com as guidelines de 2011. De seguida os registos dos pacientes foram revistos com o intuito de avaliar o impacto clinico dos ETTs e foram classificados de acordo com uma das 3 seguintes categorias: (1) alteração ativa dos cuidados – por continuação ou descontinuação dos cuidados como resultado do ETT, (2) continuação dos cuidados – sem continuação ou descontinuação dos cuidados, mas comunicação ao paciente dos resultados do ETT, (3) sem alteração dos cuidados – os cuidados ao paciente já estavam a ser aplicados previamente ao resultado do ETT, causa de sintomas já estabelecida no momento da requisição para exame, exame prévio explicativo dos sintomas e sem indicação aguda para novo ETT, terapêutica não alterada ou inexistência de documentação relativa aos achados ecocardiográficos. Pacientes cujos registos não se encontravam disponíveis foram excluídos (259). Todas as classificações foram avaliadas por uma cardiologista independente, sem relação direta com o estudo. Resultados: A nossa amostra apresentou uma média de idades de 63 ± 17 anos, com uma equilíbrio de géneros. A maioria dos exames foi solicitada em contexto de ambulatório (81,4%), pela Cardiologia (50,3%) e pela Medicina Geral e Familiar (13,4%). Relativamente aos achados ecocardiográficos dos exames, 7,6% demonstraram disfunção sistólica do ventrículo esquerdo moderada a grave, 4,0% revelaram doença valvular grave e 5,1% hipertensão pulmonar significativa. Em relação à adequação dos pedidos para ETTs, 76,5% foram adequados, 7,1% inadequados e 12,6% incertos. Relativamente ao impacto clínico dos ETTs, 42,7% dos exames revelaram uma alteração ativa nos cuidados, 15,6% mostraram uma continuação dos cuidados e 11,5% demonstraram não haver alteração nos cuidados. A idade (P=0,05), o contexto de atendimento (P<0,01) e o pedido realizado pela especialidade medicina geral e familiar (MGF) (P=0,02) foram os preditores mais importantes de uma alteração ativa nos cuidados. Numa perspectiva de prestação de cuidados a uma população mais idosa, o contexto de atendimento, a presença de achados ecocardiográficos significativos e a não alteração dos cuidados apresentam uma relação significativa com a idade. Conclusões: Os dados demonstram que quase 8 em cada 10 ETTs foram considerados adequados e que 4 em cada 10 exames não apresentaram alteração ativa dos cuidados.
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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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This paper presents a proposal for a management model based on reliability requirements concerning Cloud Computing (CC). The proposal was based on a literature review focused on the problems, challenges and underway studies related to the safety and reliability of Information Systems (IS) in this technological environment. This literature review examined the existing obstacles and challenges from the point of view of respected authors on the subject. The main issues are addressed and structured as a model, called "Trust Model for Cloud Computing environment". This is a proactive proposal that purposes to organize and discuss management solutions for the CC environment, aiming improved reliability of the IS applications operation, for both providers and their customers. On the other hand and central to trust, one of the CC challenges is the development of models for mutual audit management agreements, so that a formal relationship can be established involving the relevant legal responsibilities. To establish and control the appropriate contractual requirements, it is necessary to adopt technologies that can collect the data needed to inform risk decisions, such as access usage, security controls, location and other references related to the use of the service. In this process, the cloud service providers and consumers themselves must have metrics and controls to support cloud-use management in compliance with the SLAs agreed between the parties. The organization of these studies and its dissemination in the market as a conceptual model that is able to establish parameters to regulate a reliable relation between provider and user of IT services in CC environment is an interesting instrument to guide providers, developers and users in order to provide services and secure and reliable applications.
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Dissertação de mestrado em Construção e Reabilitação Sustentáveis
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PhD Thesis in Bioengineering