945 resultados para hydropower system model
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Dissertação para obtenção do Grau de Mestre em Biotecnologia
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The four studies in this article introduce a questionnaire to measure Strength of the HRM System (HRMSQ), a multidimensional construct, theoretically developed by Bowen and Ostroff (2004). Strength of the HRM System is a set of process characteristics that lead to effectiveness in conveying signals to employees that allow them to create a shared meaning of desired and appropriate work behaviours. Nine characteristics are suggested, grouped in three features: Distinctiveness, Consistency and Consensus. Study 1 developed and tested a questionnaire in a sample of workers from five different sectors. Study 2 cross-validated the measure in a sample of civil servants in a municipality. These two studies used performance appraisal as the reference HRM practice and led to a short version of the HRMSQ. Study 3 and Study 4 extend the HRMSQ to several common HRM practices. The HRMSQ is tested in two samples, of call center and several private and public organizations‟ workers (study 3). In study 4 the questionnaire is refined and tested with a sample from a hotel chain and finally cross-validated with two other samples, in the insurance and batteries sectors, leading to a longer version of the HRMSQ. Content analysis of several interviews with human resource managers and the Rasch model (1960, 1961, 1980), were used to define and select the indicators of the questionnaire. Convergent, discriminant and predictive validity of the measure are tested. The results of the four studies highlight the complexity of the relationships between the proposed characteristics and support the validity of a parsimonious measure of Strength of the HRM System.
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There is a family of models with Physical, Human capital and R&D for which convergence properties have been discussed (Arnold, 2000a; Gómez, 2005). However, spillovers in R&D have been ignored in this context. We introduce spillovers in this model and derive its steady-state and stability properties. This new feature implies that the model is characterized by a system of four differential equations. A unique Balanced Growth Path along with a two dimensional stable manifold are obtained under simple and reasonable conditions. Transition is oscillatory toward the steady-state for plausible values of parameters.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
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The convergence features of an Endogenous Growth model with Physical capital, Human Capital and R&D have been studied. We add an erosion effect (supported by empirical evidence) to this model, and fully characterize its convergence properties. The dynamics is described by a fourth-order system of differential equations. We show that the model converges along a one-dimensional stable manifold and that its equilibrium is saddle-path stable. We also argue that one of the implications of considering this “erosion effect” is the increase in the adherence of the model to data.
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The reported productivity gains while using models and model transformations to develop entire systems, after almost a decade of experience applying model-driven approaches for system development, are already undeniable benefits of this approach. However, the slowness of higher-level, rule based model transformation languages hinders the applicability of this approach to industrial scales. Lower-level, and efficient, languages can be used but productivity and easy maintenance seize to exist. The abstraction penalty problem is not new, it also exists for high-level, object oriented languages but everyone is using them now. Why is not everyone using rule based model transformation languages then? In this thesis, we propose a framework, comprised of a language and its respective environment, designed to tackle the most performance critical operation of high-level model transformation languages: the pattern matching. This framework shows that it is possible to mitigate the performance penalty while still using high-level model transformation languages.
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Nowadays, several sensors and mechanisms are available to estimate a mobile robot trajectory and location with respect to its surroundings. Usually absolute positioning mechanisms are the most accurate, but they also are the most expensive ones, and require pre installed equipment in the environment. Therefore, a system capable of measuring its motion and location within the environment (relative positioning) has been a research goal since the beginning of autonomous vehicles. With the increasing of the computational performance, computer vision has become faster and, therefore, became possible to incorporate it in a mobile robot. In visual odometry feature based approaches, the model estimation requires absence of feature association outliers for an accurate motion. Outliers rejection is a delicate process considering there is always a trade-off between speed and reliability of the system. This dissertation proposes an indoor 2D position system using Visual Odometry. The mobile robot has a camera pointed to the ceiling, for image analysis. As requirements, the ceiling and the oor (where the robot moves) must be planes. In the literature, RANSAC is a widely used method for outlier rejection. However, it might be slow in critical circumstances. Therefore, it is proposed a new algorithm that accelerates RANSAC, maintaining its reliability. The algorithm, called FMBF, consists on comparing image texture patterns between pictures, preserving the most similar ones. There are several types of comparisons, with different computational cost and reliability. FMBF manages those comparisons in order to optimize the trade-off between speed and reliability.
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The processes of mobilization of land for infrastructures of public and private domain are developed according to proper legal frameworks and systematically confronted with the impoverished national situation as regards the cadastral identification and regularization, which leads to big inefficiencies, sometimes with very negative impact to the overall effectiveness. This project report describes Ferbritas Cadastre Information System (FBSIC) project and tools, which in conjunction with other applications, allow managing the entire life-cycle of Land Acquisition and Cadastre, including support to field activities with the integration of information collected in the field, the development of multi-criteria analysis information, monitoring all information in the exploration stage, and the automated generation of outputs. The benefits are evident at the level of operational efficiency, including tools that enable process integration and standardization of procedures, facilitate analysis and quality control and maximize performance in the acquisition, maintenance and management of registration information and expropriation (expropriation projects). Therefore, the implemented system achieves levels of robustness, comprehensiveness, openness, scalability and reliability suitable for a structural platform. The resultant solution, FBSIC, is a fit-for-purpose cadastre information system rooted in the field of railway infrastructures. FBSIC integrating nature of allows: to accomplish present needs and scale to meet future services; to collect, maintain, manage and share all information in one common platform, and transform it into knowledge; to relate with other platforms; to increase accuracy and productivity of business processes related with land property management.
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Research on Parkinson’s disease (PD) has mainly focused on the degeneration of the dopaminergic neurons of nigro-striatal (NS) pathway; also, post-mortem studies have demonstrated that the noradrenergic and the serotonergic transmitter systems are also affected (Jellinger, 1999). Degeneration of these neuronal cell bodies is generally thought to start prior to the loss of dopaminergic neurons in the NS pathway and precedes the appearance of the motor symptoms that are the “hallmark” of PD. Gastrointestinal (GI) motility is often disturbed in PD, manifesting chiefly as impaired gastric emptying and constipation. These GI dysfunction symptoms may be the result of a loss in noradrenergic and serotonergic innervation. GI deficits were evaluated using an organ bath technique. Groups treated with different combinations of neurotoxins (6-OHDA alone, 6-OHDA + pCA or 6-OHDA + DSP-4) presented significant differences in gut contractility compared to control groups. Since a substantial body of literature suggests the presence of an inflammatory process in parkinsonian state (Whitton, 2007), changes in pro-inflammatory cytokines in the gut were assessed using a cytokine microarray. It has been found in this work that groups with a combined dopaminergic and noradrenergic lesion have a significant increase in both expressions of IL-13 and VEGF. IL-6 also shows a decrease in treatment groups; however this decrease did not reach statistical significance. The therapeutic value of Exendin-4 (EX-4) was evaluated. It has been previously demonstrated that EX-4, a glucagon-like peptide-1 receptor (GLP-1R) agonist, is neuroprotective in rodent models of PD (Harkavyi et al., 2008). In this thesis it has been found that EX-4 was able to reverse a decrease in gut contractility obtained through intracerebral bilateral 6-OHDA injection. Although more studies are required, EX-4 could be used as a possible therapy for the GI symptoms prominent in the early stages of PD.
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In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.
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The purpose of this paper is to conduct a methodical drawback analysis of a financial supplier risk management approach which is currently implemented in the automotive industry. Based on identified methodical flaws, the risk assessment model is further developed by introducing a malus system which incorporates hidden risks into the model and by revising the derivation of the most central risk measure in the current model. Both methodical changes lead to significant enhancements in terms of risk assessment accuracy, supplier identification and workload efficiency.
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RESUMO: Em 2011, a Associação Psiquiátrica Mundial lançou um programa de bolsas de investigação para psiquiatras em início de carreira a partir de países de renda baixa ou média-baixa, no âmbito deste programa, o autor foi selecionado para uma bolsa de pesquisa no Centre for Youth Mental Health/Orygen Youth Health Research Centre da Universidade de Melbourne. Orygen, é a principal organização de pesquisa e tradução do conhecimento do mundo com foco em problemas de saúde mental em pessoas jovens. O estágio foi baseado em Prevenção e Intervenção Precoce Psychosis Centre (EPPIC), que faz parte do Orygen. EPPIC fornece programa de tratamento abrangente e integrada, baseada na comunidade para o primeiro episódio de psicose. Esta dissertação descreve o modelo EPPIC, e seus componentes essenciais e fatores que são necessários para uma implementação de serviço direito. Além disso, uma proposta de criação de um programa-piloto de intervenção psicose precoce é discutido. Este programa inclui um programa de extensão inovadora que combina princípios comerciais sólidos, com metas sociais, a fim de combater especificamente a maior barreira para o tratamento da psicose precoce na Bolívia: o estigma da doença mental. Ao utilizar uma equipe de tratamento móvel, multidisciplinar, que enfatiza os papéis dos gerentes do caso treinados focada em fornecer indivíduo intensiva e apoio familiar no lar, este programa irá prestar cuidados culturalmente apropriados que irá alavancar contribuições de um suprimento limitado de psiquiatras e mudar longe da dependência um sistema médico fragmentado. ---------------------------- ABSTRACT: In 2011, the World Psychiatric Association launched a programme of research fellowships for early-career psychiatrists from low- or lower-middle income countries, within this programme, the author was selected to a research fellowship at the Centre for Youth Mental Health/Orygen Youth Health Research Centre at University of Melbourne. Orygen, is the world’s leading research and knowledge translation organization focusing on mental ill-health in young people. The traineeship was based on Early Psychosis Prevention and Intervention Centre (EPPIC), which is part of Orygen. EPPIC provides comprehensive, integrated, community-based treatment program for first-episode psychosis. This dissertation describes the EPPIC model, and its core components and factors which are necessary to a right service implementation. Additionally, a proposal to establish a pilot early psychosis intervention programme is discussed. This programme includes an innovative outreach programme that combines sound business principals with social goals in order to specifically target the largest barrier to early psychosis treatment in Bolivia: the stigma of mental illness. By utilizing a mobile, multidisciplinary treatment team that emphasizes the roles of trained case managers focused on providing intensive individual and family support in the home, this programme will provide culturally appropriate care that will leverage contributions from a limited supply of psychiatrists and shift dependence away from a fragmented medical system.
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Fado was listed as UNESCO Intangible Cultural Heritage in 2011. This dissertation describes a theoretical model, as well as an automatic system, able to generate instrumental music based on the musics and vocal sounds typically associated with fado’s practice. A description of the phenomenon of fado, its musics and vocal sounds, based on ethnographic, historical sources and empirical data is presented. The data includes the creation of a digital corpus, of musical transcriptions, identified as fado, and statistical analysis via music information retrieval techniques. The second part consists in the formulation of a theory and the coding of a symbolic model, as a proof of concept, for the automatic generation of instrumental music based on the one in the corpus.
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Nowadays manufacturing companies are facing a more challenging environment due to the unpredictability of the markets in order to survive. Enterprises need to keep innovating and deliver products with new internal or external characteristics. There are strategies and solutions, to different organisational level from strategic to operational, when technology is growing faster in operational level, more specifically in manufacturing system. This means that companies have to deal with the changes of the emergent manufacturing systems while it can be expensive and not easy to be implement. An agile manufacturing system can help to cope with the markets changeability. Evolvable Production Systems (EPS) is an emergent paradigm which aims to bring new solutions to deal with changeability. The proposed paradigm is characterised by modularity and intends to introduce high flexibility and dynamism at shop floor level through the use of the evolution of new computational devices and technology. This new approach brings to enterprises the ability to plug and unplug new devices and allowing fast reformulation of the production line without reprogramming. There is no doubt about the advantages and benefits of this emerging technology but the feasibility and applicability is still under questioned. Most researches in this area are focused on technical side, explaining the advantages of those systems while there are no sufficient works discussing the implementation risks from different perspective, including business owner. The main objective of this work is to propose a methodology and model to identify, classify and measure potential risk associated with an implementation of this emergent paradigm. To quantify the proposed comprehensive risk model, an Intelligent Decision system is developed employing Fuzzy Inference System to deal with the knowledge of experts, as there are no historical data and sufficient research on this area. The result can be the vulnerability assessment of implementing EPS technology in manufacturing companies when the focus is more on SMEs. The present dissertation used the experts’ knowledge and experiences, who were involved in FP7 project IDEAS, which is one of the leading projects in this area.
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This work aimed to contribute to drug discovery and development (DDD) for tauopathies, while expanding our knowledge on this group of neurodegenerative disorders, including Alzheimer’s disease (AD). Using yeast, a recognized model for neurodegeneration studies, useful models were produced for the study of tau interaction with beta-amyloid (Aβ), both AD hallmark proteins. The characterization of these models suggests that these proteins co-localize and that Aβ1-42, which is toxic to yeast, is involved in tau40 phosphorylation (Ser396/404) via the GSK-3β yeast orthologue, whereas tau seems to facilitate Aβ1-42 oligomerization. The mapping of tau’s interactome in yeast, achieved with a tau toxicity enhancer screen using the yeast deletion collection, provided a novel framework, composed of 31 genes, to identify new mechanisms associated with tau pathology, as well as to identify new drug targets or biomarkers. This genomic screen also allowed to select the yeast strain mir1Δ-tau40 for development of a new GPSD2TM drug discovery screening system. A library of unique 138 marine bacteria extracts, obtained from the Mid-Atlantic Ridge hydrothermal vents, was screened with mir1Δ-tau40. Three extracts were identified as suppressors of tau toxicity and constitute good starting points for DDD programs. mir1Δ strain was sensitive to tau toxicity, relating tau pathology with mitochondrial function. SLC25A3, the human homologue of MIR1, codes for the mitochondrial phosphate carrier protein (PiC). Resorting to iRNA, SLC25A3 expression was silenced in human neuroglioma cells, as a first step towards the engineering of a neural model for replicating the results obtained in yeast. This model is essential to understand the mechanisms of tau toxicity at the mitochondrial level and to validate PiC as a relevant drug target. The set of DDD tools here presented will foster the development of innovative and efficacious therapies, urgently needed to cope with tau-related disorders of high human and social-economic impact.