789 resultados para Relay selection
Resumo:
The aim of this research is to examine the pricing anomalies existing in the U.S. market during 1986 to 2011. The sample of stocks is divided into decile portfolios based on seven individual valuation ratios (E/P, B/P, S/P, EBIT/EV, EVITDA/EV, D/P, and CE/P) and price momentum to investigate the efficiency of individual valuation ratio and their combinations as portfolio formation criteria. This is the first time in financial literature when CE/P is employed as a constituent of composite value measure. The combinations are based on median scaled composite value measures and TOPSIS method. During the sample period value portfolios significantly outperform both the market portfolio and comparable glamour portfolios. The results show the highest return for the value portfolio that was based on the combination of S/P & CE/P ratios. The outcome of this research will increase the understanding on the suitability of different methodologies for portfolio selection. It will help managers to take advantage of the results of different methodologies in order to gain returns above the market.
Resumo:
An appropriate supplier selection and its profound effects on increasing the competitive advantage of companies has been widely discussed in supply chain management (SCM) literature. By raising environmental awareness among companies and industries they attach more importance to sustainable and green activities in selection procedures of raw material providers. The current thesis benefits from data envelopment analysis (DEA) technique to evaluate the relative efficiency of suppliers in the presence of carbon dioxide (CO2) emission for green supplier selection. We incorporate the pollution of suppliers as an undesirable output into DEA. However, to do so, two conventional DEA model problems arise: the lack of the discrimination power among decision making units (DMUs) and flexibility of the inputs and outputs weights. To overcome these limitations, we use multiple criteria DEA (MCDEA) as one alternative. By applying MCDEA the number of suppliers which are identified as efficient will be decreased and will lead to a better ranking and selection of the suppliers. Besides, in order to compare the performance of the suppliers with an ideal supplier, a “virtual” best practice supplier is introduced. The presence of the ideal virtual supplier will also increase the discrimination power of the model for a better ranking of the suppliers. Therefore, a new MCDEA model is proposed to simultaneously handle undesirable outputs and virtual DMU. The developed model is applied for green supplier selection problem. A numerical example illustrates the applicability of the proposed model.
Resumo:
Coronary artery disease (CAD) is a worldwide leading cause of death. The standard method for evaluating critical partial occlusions is coronary arteriography, a catheterization technique which is invasive, time consuming, and costly. There are noninvasive approaches for the early detection of CAD. The basis for the noninvasive diagnosis of CAD has been laid in a sequential analysis of the risk factors, and the results of the treadmill test and myocardial perfusion scintigraphy (MPS). Many investigators have demonstrated that the diagnostic applications of MPS are appropriate for patients who have an intermediate likelihood of disease. Although this information is useful, it is only partially utilized in clinical practice due to the difficulty to properly classify the patients. Since the seminal work of Lotfi Zadeh, fuzzy logic has been applied in numerous areas. In the present study, we proposed and tested a model to select patients for MPS based on fuzzy sets theory. A group of 1053 patients was used to develop the model and another group of 1045 patients was used to test it. Receiver operating characteristic curves were used to compare the performance of the fuzzy model against expert physician opinions, and showed that the performance of the fuzzy model was equal or superior to that of the physicians. Therefore, we conclude that the fuzzy model could be a useful tool to assist the general practitioner in the selection of patients for MPS.
Resumo:
The significance and impact of services in the modern global economy has become greater and there has been more demand for decades in the academic community of international business for further research into better understanding internationalisation of services. Theories based on the internationalisation of manufacturing firms have been long questioned for their applicability to services. This study aims at contributing to understanding internationalisation of services by examining how market selection decisions are made for new service products within the existing markets of a multinational financial service provider. The study focused on the factors influencing market selection and the study was conducted as a case study on a multinational financial service firm and two of its new service products. Two directors responsible for the development and internationalisation of the case service products were interviewed in guided semi-structured interviews based on themes adopted from the literature review and the outcome theoretical framework. The main empirical findings of the study suggest that the most significant factors influencing the market selection for new service products within a multinational financial service firm’s existing markets are: commitment to the new service products by both the management and the rest of the product related organisation; capability and competence by the local country organisations to adopt new services; market potential which combines market size, market structure and competitive environment; product fit to the market requirements; and enabling partnerships. Based on the empirical findings, this study suggests a framework of factors influencing market selection for new service products, and proposes further research issues and methods to test and extend the findings of this research.
Resumo:
Personalized medicine will revolutionize our capabilities to combat disease. Working toward this goal, a fundamental task is the deciphering of geneticvariants that are predictive of complex diseases. Modern studies, in the formof genome-wide association studies (GWAS) have afforded researchers with the opportunity to reveal new genotype-phenotype relationships through the extensive scanning of genetic variants. These studies typically contain over half a million genetic features for thousands of individuals. Examining this with methods other than univariate statistics is a challenging task requiring advanced algorithms that are scalable to the genome-wide level. In the future, next-generation sequencing studies (NGS) will contain an even larger number of common and rare variants. Machine learning-based feature selection algorithms have been shown to have the ability to effectively create predictive models for various genotype-phenotype relationships. This work explores the problem of selecting genetic variant subsets that are the most predictive of complex disease phenotypes through various feature selection methodologies, including filter, wrapper and embedded algorithms. The examined machine learning algorithms were demonstrated to not only be effective at predicting the disease phenotypes, but also doing so efficiently through the use of computational shortcuts. While much of the work was able to be run on high-end desktops, some work was further extended so that it could be implemented on parallel computers helping to assure that they will also scale to the NGS data sets. Further, these studies analyzed the relationships between various feature selection methods and demonstrated the need for careful testing when selecting an algorithm. It was shown that there is no universally optimal algorithm for variant selection in GWAS, but rather methodologies need to be selected based on the desired outcome, such as the number of features to be included in the prediction model. It was also demonstrated that without proper model validation, for example using nested cross-validation, the models can result in overly-optimistic prediction accuracies and decreased generalization ability. It is through the implementation and application of machine learning methods that one can extract predictive genotype–phenotype relationships and biological insights from genetic data sets.
Resumo:
Recent Storms in Nordic countries were a reason of long power outages in huge territories. After these disasters distribution networks' operators faced with a problem how to provide adequate quality of supply in such situation. The decision of utilization cable lines rather than overhead lines were made, which brings new features to distribution networks. The main idea of this work is a complex analysis of medium voltage distribution networks with long cable lines. High value of cable’s specific capacitance and length of lines determine such problems as: high values of earth fault currents, excessive amount of reactive power flow from distribution to transmission network, possibility of a high voltage level at the receiving end of cable feeders. However the core tasks was to estimate functional ability of the earth fault protection and the possibility to utilize simplified formulas for operating setting calculations in this network. In order to provide justify solution or evaluation of mentioned above problems corresponding calculations were made and in order to analyze behavior of relay protection principles PSCAD model of the examined network have been created. Evaluation of the voltage rise in the end of a cable line have educed absence of a dangerous increase in a voltage level, while excessive value of reactive power can be a reason of final penalty according to the Finish regulations. It was proved and calculated that for this networks compensation of earth fault currents should be implemented. In PSCAD models of the electrical grid with isolated neutral, central compensation and hybrid compensation were created. For the network with hybrid compensation methodology which allows to select number and rated power of distributed arc suppression coils have been offered. Based on the obtained results from experiments it was determined that in order to guarantee selective and reliable operation of the relay protection should be utilized hybrid compensation with connection of high-ohmic resistor. Directional and admittance based relay protection were tested under these conditions and advantageous of the novel protection were revealed. However, for electrical grids with extensive cabling necessity of a complex approach to the relay protection were explained and illustrated. Thus, in order to organize reliable earth fault protection is recommended to utilize both intermittent and conventional relay protection with operational settings calculated by the use of simplified formulas.
Resumo:
The lack of research of private real estate is a well-known problem. Earlier studies have mostly concentrated on the USA or the UK. Therefore, this master thesis offers more information about the performance and risk associated with private real estate investments in Nordic countries, but especially in Finland. The structure of this master thesis is divided into two independent sections based on the research questions. In first section, database analysis is performed to assess risk-return ratio of direct real estate investment for Nordic countries. Risk-return ratios are also assessed for different property sectors and economic regions. Finally, review of diversification strategies based on property sectors and economic regions is performed. However, standard deviation itself is not usually sufficient method to evaluate riskiness of private real estate. There is demand for more explicit assessment of property risk. One solution is property risk scoring. In second section risk scorecard based tool is built to make different real estate comparable in terms of risk. In order to do this, nine real estate professionals were interviewed to enhance the structure of theory-based risk scorecard and to assess weights for different risk factors.
Resumo:
Increasingly growing share of distributed generation in the whole electrical power system’s generating system is currently a worldwide tendency, driven by several factors, encircling mainly difficulties in refinement of megalopolises’ distribution networks and its maintenance; widening environmental concerns adding to both energy efficiency approaches and installation of renewable sources based generation, inherently distributed; increased power quality and reliability needs; progress in IT field, making implementable harmonization of needs and interests of different-energy-type generators and consumers. At this stage, the volume, formed by system-interconnected distributed generation facilities, have reached the level of causing broad impact toward system operation under emergency and post-emergency conditions in several EU countries, thus previously implementable approach of their preliminary tripping in case of a fault, preventing generating equipment damage and disoperation of relay protection and automation, is not applicable any more. Adding to the preceding, withstand capability and transient electromechanical stability of generating technologies, interconnecting in proximity of load nodes, enhanced significantly since the moment Low Voltage Ride-Through regulations, followed by techniques, were introduced in Grid Codes. Both aspects leads to relay protection and auto-reclosing operation in presence of distributed generation generally connected after grid planning and construction phases. This paper proposes solutions to the emerging need to ensure correct operation of the equipment in question with least possible grid refinements, distinctively for every type of distributed generation technology achieved its technical maturity to date and network’s protection. New generating technologies are equivalented from the perspective of representation in calculation of initial steady-state short-circuit current used to dimension current-sensing relay protection, and widely adopted short-circuit calculation practices, as IEC 60909 and VDE 0102. The phenomenon of unintentional islanding, influencing auto-reclosing, is addressed, and protection schemes used to eliminate an sustained island are listed and characterized by reliability and implementation related factors, whereas also forming a crucial aspect of realization of the proposed protection operation relieving measures.
Resumo:
The issue of selecting an appropriate healthcare information system is a very essential one. If implemented healthcare information system doesn’t fit particular healthcare institution, for example there are unnecessary functions; healthcare institution wastes its resources and its efficiency decreases. The purpose of this research is to develop a healthcare information system selection model to assist the decision-making process of choosing healthcare information system. Appropriate healthcare information system helps healthcare institutions to become more effective and efficient and keep up with the times. The research is based on comparison analysis of 50 healthcare information systems and 6 interviews with experts from St-Petersburg healthcare institutions that already have experience in healthcare information system utilization. 13 characteristics of healthcare information systems: 5 key and 7 additional features are identified and considered in the selection model development. Variables are used in the selection model in order to narrow the decision algorithm and to avoid duplication of brunches. The questions in the healthcare information systems selection model are designed to be easy-to-understand for common a decision-maker in healthcare institution without permanent establishment.