796 resultados para Empirical Algorithm Analysis
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This paper assesses the validity and reliability of two instruments measuring quality of service, the SERVPERF and SERVQUAL scales, replicated in a novel cultural settings, a Portuguese energy company. To provide insights and strategies for managerial intervention, a relation between customers’ satisfaction and quality of service is established. The empirical study suggests a superior convergent and predictive validity of SERVPERF scale to measure quality of service in this settings when comparing to SERVQUAL. The main differences of this study with previous ones, are that this one resorts on a confirmatory factor analysis, the validation of the instruments is performed by using the same measures suggested by their creators and extends the line of research to a novel cultural settings, a Portuguese energy company. Concerning the relationship between service quality and customers’ satisfaction, all of the quality of service attributes correlate almost equally to the satisfaction ones, with a lower weight concerning tangibles.
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Textile and tourism sectors are two important industries in the Portuguese economy. However, its high exposure to both internal and international economic volatility make the companies operating in these economic sectors particularly vulnerable to economic crises, such as the ones which have been impacting Portugal and the European Union. The objective of this paper is to evaluate and understand the impact of size and age on the financial health of textile and tourism companies, measured by economic indices. An empirical based model is proposed. Its implications are derived and tested on a sample of 4061 Portuguese companies from textile and tourism sectors, during the period 2005-2009. The findings suggest that age has a major impact on the risk of failure, rather than size. Whereas the effect of age is generally positive regarding the financial health of the company, the effect of size is less clear and ultimately depends on the age of the company.
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Textile and tourism sectors are two important industries in the Portuguese economy. However, its high exposure to both internal and international economic volatility make the companies operating in these economic sectors particularly vulnerable to economic crises, such as the ones which have been impacting Portugal and the European Union. The objective of this paper is to evaluate and understand the impact of size and age on the financial health of textile and tourism companies, measured by economic indices. An empirical based model is proposed. Its implications are derived and tested on a sample of 4061 Portuguese companies from textile and tourism sectors, during the period 2005-2009. The findings suggest that age has a major impact on the risk of failure, rather than size. Whereas the effect of age is generally positive regarding the financial health of the company, the effect of size is less clear and ultimately depends on the age of the company.
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Quantitative analysis of cine cardiac magnetic resonance (CMR) images for the assessment of global left ventricular morphology and function remains a routine task in clinical cardiology practice. To date, this process requires user interaction and therefore prolongs the examination (i.e. cost) and introduces observer variability. In this study, we sought to validate the feasibility, accuracy, and time efficiency of a novel framework for automatic quantification of left ventricular global function in a clinical setting.
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Textile and tourism sectors are two important industries in the Portuguese economy. However, its high exposure to both internal and international economic volatility make the companies operating in these economic sectors particularly vulnerable to economic crises, such as the ones which have been impacting Portugal and the European Union. The objective of this paper is to evaluate and understand the impact of size and age on the financial health of textile and tourism companies, measured by economic indices. An empirical based model is proposed. Its implications are derived and tested on a sample of 4061 Portuguese companies from textile and tourism sectors, during the period 2005-2009. The findings suggest that age has a major impact on the risk of failure, rather than size. Whereas the effect of age is generally positive regarding the financial health of the company, the effect of size is less clear and ultimately depends on the age of the company.
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Supply chain (SC) resilience and flexibility are important research topics receiving growing attention. However, the academic literature needs empirical studies on SC resilience capable of investigating the inter-organizational components of flexibility along different tiers. Therefore, this paper analyzes the main lack of flexibilities in three Brazilian automotive SCs that limit their resilience and therefore their capacity to better support and meet the demand changes in the marketplace. A multi-tier case study approach is adopted. Research findings identify lack of flexibilities in different tiers that inhibit the SC resilience as well as manufacturing and SC flexibilities that build SC resilience. The findings also highlight that the same SC may have the flexibility to be resilient for one of its products but not for another product, what sheds new lights on the academic literature. Finally, flexible SCs should be designed to increase SC resilience to cope with mishaps as significant demand changes.
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A previously developed model is used to numerically simulate real clinical cases of the surgical correction of scoliosis. This model consists of one-dimensional finite elements with spatial deformation in which (i) the column is represented by its axis; (ii) the vertebrae are assumed to be rigid; and (iii) the deformability of the column is concentrated in springs that connect the successive rigid elements. The metallic rods used for the surgical correction are modeled by beam elements with linear elastic behavior. To obtain the forces at the connections between the metallic rods and the vertebrae geometrically, non-linear finite element analyses are performed. The tightening sequence determines the magnitude of the forces applied to the patient column, and it is desirable to keep those forces as small as possible. In this study, a Genetic Algorithm optimization is applied to this model in order to determine the sequence that minimizes the corrective forces applied during the surgery. This amounts to find the optimal permutation of integers 1, ... , n, n being the number of vertebrae involved. As such, we are faced with a combinatorial optimization problem isomorph to the Traveling Salesman Problem. The fitness evaluation requires one computing intensive Finite Element Analysis per candidate solution and, thus, a parallel implementation of the Genetic Algorithm is developed.
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The current study focuses on the analysis of pressure surge damping in single pipeline systems generated by a fast change of flow, conditions. A dimensionless form of pressurised transient flow equations was developed. presenting the main advantage of being independent of the system characteristics. In lack of flow velocity profiles. the unsteady friction in turbulent regimes is analysed based on two new empirical corrective-coefficients associated with local and convective acceleration terms. A new, surge damping approach is also presented taking into account the pressure peak time variation. The observed attenuation effect in the pressure wave for high deformable pipe materials can be described by a combination of the non-elastic behaviour of the pipe-wall with steady and unsteady friction effects. Several simulations and experimental tests have been carried out. in order to analyse the dynamic response of single pipelines with different characteristics, such as pipe materials. diameters. thickness. lengths and transient conditions.
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OBJECTIVE: To test discriminant analysis as a method of turning the information of a routine customer satisfaction survey (CSS) into a more accurate decision-making tool. METHODS: A 7-question, 10-multiple choice, self-applied questionnaire was used to study a sample of patients seen in two outpatient care units in Valparaíso, Chile, one of primary care (n=100) and the other of secondary care (n=249). Two cutting points were considered in the dependent variable (final satisfaction score): satisfied versus unsatisfied, and very satisfied versus all others. Results were compared with empirical measures (proportion of satisfied individuals, proportion of unsatisfied individuals and size of the median). RESULTS: The response rate was very high, over 97.0% in both units. A new variable, medical attention, was revealed, as explaining satisfaction at the primary care unit. The proportion of the total variability explained by the model was very high (over 99.4%) in both units, when comparing satisfied with unsatisfied customers. In the analysis of very satisfied versus all other customers, significant relationship was identified only in the case of the primary care unit, which explained a small proportion of the variability (41.9%). CONCLUSIONS: Discriminant analysis identified relationships not revealed by the previous analysis. It provided information about the proportion of the variability explained by the model. It identified non-significant relationships suggested by empirical analysis (e.g. the case of the relation very satisfied versus others in the secondary care unit). It measured the contribution of each independent variable to the explanation of the variation of the dependent one.
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A methodology based on data mining techniques to support the analysis of zonal prices in real transmission networks is proposed in this paper. The mentioned methodology uses clustering algorithms to group the buses in typical classes that include a set of buses with similar LMP values. Two different clustering algorithms have been used to determine the LMP clusters: the two-step and K-means algorithms. In order to evaluate the quality of the partition as well as the best performance algorithm adequacy measurements indices are used. The paper includes a case study using a Locational Marginal Prices (LMP) data base from the California ISO (CAISO) in order to identify zonal prices.
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Mestrado em Radioterapia
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Purpose: The aim of this paper is to highlight the importance of qualitative research within the scope of management scientific studies, referring to its philosophy, nature and instruments. It also confronts it with quantitative methodology, approaching its differences as well as its complementariness and synergies, with the purpose of explaining, from a more analytic point of view, the relevance of qualitative methodology in the course of an authentic and real research despite its complexity. Design/methodology/approach: Regardless of its broad application, one may attest the scarcity literature that focuses on qualitative research applied to the management scientific area, as opposed to the large amount that refers to quantitative research. Findings: The paper shows the influence that qualitative research has on management scientific research. Originality/value:. Qualitative research assumes an important role within qualitative research by allowing for the study and analysis of certain types of phenomena that occur inside organisations, and in respect of which quantitative studies cannot provide an answer.
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Purpose: The aim of this paper is to promote qualitative methodology within the scientific community of management. The specific objective is oriented to propose an empirical research process based on case study method. This is to ensure rigor in the empirical research process, that future research may follow a similar procedure to that is proposed. Design/methodology/approach: Following a qualitative methodological approach, we propose a research process that develops according to four phases, each with several stages. This study analyses the preparatory and field work phases and their stages. Findings: The paper shows the influence that case studies have on qualitative empirical research process in management. Originality/value:. Case study method assumes an important role within qualitative research by allowing for the study and analysis of certain types of phenomena that occur inside organisations, and in respect of which quantitative studies cannot provide an answer.
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Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.
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LLF (Least Laxity First) scheduling, which assigns a higher priority to a task with a smaller laxity, has been known as an optimal preemptive scheduling algorithm on a single processor platform. However, little work has been made to illuminate its characteristics upon multiprocessor platforms. In this paper, we identify the dynamics of laxity from the system’s viewpoint and translate the dynamics into LLF multiprocessor schedulability analysis. More specifically, we first characterize laxity properties under LLF scheduling, focusing on laxity dynamics associated with a deadline miss. These laxity dynamics describe a lower bound, which leads to the deadline miss, on the number of tasks of certain laxity values at certain time instants. This lower bound is significant because it represents invariants for highly dynamic system parameters (laxity values). Since the laxity of a task is dependent of the amount of interference of higher-priority tasks, we can then derive a set of conditions to check whether a given task system can go into the laxity dynamics towards a deadline miss. This way, to the author’s best knowledge, we propose the first LLF multiprocessor schedulability test based on its own laxity properties. We also develop an improved schedulability test that exploits slack values. We mathematically prove that the proposed LLF tests dominate the state-of-the-art EDZL tests. We also present simulation results to evaluate schedulability performance of both the original and improved LLF tests in a quantitative manner.