1000 resultados para Erasmus networks
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The incorporation of small amount of highly anisotropic nanoparticles into liquid crystalline hydroxypropylcellulose (LC-HPC) matrix improves its response when is exposed to humidity gradients due to an anisotropic increment of order in the structure. Dispersed nanoparticles give rise to faster order/disorder transitions when exposed to moisture as it is qualitatively observed and quantified by stress-time measurements. The presence of carbon nanotubes derives in a improvement of the mechanical properties of LC-HPC thin films.
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The complexity associated with fast growing of B2B and the lack of a (complete) suite of open standards makes difficulty to maintain the underlying collaborative processes. Aligned to this challenge, this paper aims to be a contribution to an open architecture of logistics and transport processes management system. A model of an open integrated system is being defined as an open computational responsibility from the embedded systems (on-board) as well as a reference implementation (prototype) of a host system to validate the proposed open interfaces. Embedded subsystem can, natively, be prepared to cooperate with other on-board units and with IT-systems in an infrastructure commonly referred to as a center information system or back-office. In interaction with a central system the proposal is to adopt an open framework for cooperation where the embedded unit or the unit placed somewhere (land/sea) interacts in response to a set of implemented capabilities.
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Innovation is considered crucial for enterprises survival and current economic environment demands the best ways of achieving it. However, the development of complex products and services require the utilization of diverse know-how and technology, which enterprises may not hold. An effective strategy for achieving them is to rely in open innovation. Still, open innovation projects may fail for many causes, e.g. due to the dynamics of collaboration between partners. To effectively benefit from open innovation, it is recommended the utilization of adequate risk models. For achieving such models, a preliminary conceptualization of open innovation and risk is necessary, which includes modeling experiments with existing risk models, such as the FMEA.
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As the wireless cellular market reaches competitive levels never seen before, network operators need to focus on maintaining Quality of Service (QoS) a main priority if they wish to attract new subscribers while keeping existing customers satisfied. Speech Quality as perceived by the end user is one major example of a characteristic in constant need of maintenance and improvement. It is in this topic that this Master Thesis project fits in. Making use of an intrusive method of speech quality evaluation, as a means to further study and characterize the performance of speech codecs in second-generation (2G) and third-generation (3G) technologies. Trying to find further correlation between codecs with similar bit rates, along with the exploration of certain transmission parameters which may aid in the assessment of speech quality. Due to some limitations concerning the audio analyzer equipment that was to be employed, a different system for recording the test samples was sought out. Although the new designed system is not standard, after extensive testing and optimization of the system's parameters, final results were found reliable and satisfactory. Tests include a set of high and low bit rate codecs for both 2G and 3G, where values were compared and analysed, leading to the outcome that 3G speech codecs perform better, under the approximately same conditions, when compared with 2G. Reinforcing the idea that 3G is, with no doubt, the best choice if the costumer looks for the best possible listening speech quality. Regarding the transmission parameters chosen for the experiment, the Receiver Quality (RxQual) and Received Energy per Chip to the Power Density Ratio (Ec/N0), these were subject to speech quality correlation tests. Final results of RxQual were compared to those of prior studies from different researchers and, are considered to be of important relevance. Leading to the confirmation of RxQual as a reliable indicator of speech quality. As for Ec/N0, it is not possible to state it as a speech quality indicator however, it shows clear thresholds for which the MOS values decrease significantly. The studied transmission parameters show that they can be used not only for network management purposes but, at the same time, give an expected idea to the communications engineer (or technician) of the end-to-end speech quality consequences. With the conclusion of the work new ideas for future studies come to mind. Considering that the fourth-generation (4G) cellular technologies are now beginning to take an important place in the global market, as the first all-IP network structure, it seems of great relevance that 4G speech quality should be subject of evaluation. Comparing it to 3G, not only in narrowband but also adding wideband scenarios with the most recent standard objective method of speech quality assessment, POLQA. Also, new data found on Ec/N0 tests, justifies further research studies with the intention of validating the assumptions made in this work.
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The non-technical loss is not a problem with trivial solution or regional character and its minimization represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. In this paper, we show how to improve the training phase of a neural network-based classifier using a recently proposed meta-heuristic technique called Charged System Search, which is based on the interactions between electrically charged particles. The experiments were carried out in the context of non-technical loss in power distribution systems in a dataset obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others natureinspired optimization techniques for training neural networks. Thus, it is possible to improve some applications on Smart Grids.
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This paper proposes a methodology to increase the probability of delivering power to any load point through the identification of new investments. The methodology uses a fuzzy set approach to model the uncertainty of outage parameters, load and generation. A DC fuzzy multicriteria optimization model considering the Pareto front and based on mixed integer non-linear optimization programming is developed in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power to all customers in the distribution network at the minimum possible cost for the system operator, while minimizing the non supplied energy cost. To illustrate the application of the proposed methodology, the paper includes a case study which considers an 33 bus distribution network.
Resumo:
A methodology to increase the probability of delivering power to any load point through the identification of new investments in distribution network components is proposed in this paper. The method minimizes the investment cost as well as the cost of energy not supplied in the network. A DC optimization model based on mixed integer non-linear programming is developed considering the Pareto front technique in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power for any customer in the distribution system at the minimum possible cost for the system operator, while minimizing the energy not supplied cost. Thus, a multi-objective problem is formulated. To illustrate the application of the proposed methodology, the paper includes a case study which considers a 180 bus distribution network
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The high penetration of distributed energy resources (DER) in distribution networks and the competitiveenvironment of electricity markets impose the use of new approaches in several domains. The networkcost allocation, traditionally used in transmission networks, should be adapted and used in the distribu-tion networks considering the specifications of the connected resources. The main goal is to develop afairer methodology trying to distribute the distribution network use costs to all players which are usingthe network in each period. In this paper, a model considering different type of costs (fixed, losses, andcongestion costs) is proposed comprising the use of a large set of DER, namely distributed generation(DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehi-cles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). Theproposed model includes three distinct phases of operation. The first phase of the model consists in aneconomic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen’s andBialek’s tracing algorithms are used and compared to evaluate the impact of each resource in the net-work. Finally, the MW-mile method is used in the third phase of the proposed model. A distributionnetwork of 33 buses with large penetration of DER is used to illustrate the application of the proposedmodel.
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Most of distribution generation and smart grid research works are dedicated to the study of network operation parameters, reliability among others. However, many of this research works usually uses traditional test systems such as IEEE test systems. This work proposes a voltage magnitude study in presence of fault conditions considering the realistic specifications found in countries like Brazil. The methodology considers a hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzyprobabilistic models and a remedial action algorithm which is based on optimal power flow. To illustrate the application of the proposed method, the paper includes a case study that considers a real 12 bus sub-transmission network.
Resumo:
This paper presents several forecasting methodologies based on the application of Artificial Neural Networks (ANN) and Support Vector Machines (SVM), directed to the prediction of the solar radiance intensity. The methodologies differ from each other by using different information in the training of the methods, i.e, different environmental complementary fields such as the wind speed, temperature, and humidity. Additionally, different ways of considering the data series information have been considered. Sensitivity testing has been performed on all methodologies in order to achieve the best parameterizations for the proposed approaches. Results show that the SVM approach using the exponential Radial Basis Function (eRBF) is capable of achieving the best forecasting results, and in half execution time of the ANN based approaches.
Resumo:
Most of distributed generation and smart grid research works are dedicated to network operation parameters studies, reliability, etc. However, many of these works normally uses traditional test systems, for instance, IEEE test systems. This paper proposes voltage magnitude and reliability studies in presence of fault conditions, considering realistic conditions found in countries like Brazil. The methodology considers a hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models and a remedial action algorithm which is based on optimal power flow. To illustrate the application of the proposed method, the paper includes a case study that considers a real 12-bus sub-transmission network.
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Purpose: This work aims at further developing and testing the psychometric properties of the Cultural Intelligence Scale (Ang & Van Dyne, 2006) in an Erasmus Mundus Students and Alumni Population, including reliability. Design Methodology: The study included 626 participants from 109 different countries that emcompasses 6 continents. Exploratory and Confirmatory Factor Analysis procedures were carried out in order to test the scale in a multicultural scale of Erasmus Mundus Students. Reliability was assessed using Cronbach Alpha. Results: The scale presents excellent psychometric properties with alpha values that range from .84 to .90. Exploratory and Confirmatory Factor Analyses demonstrated that the original model of the scale presents an exceptionally good fit. Limitations: The present study was conducted using a convenience sample and online questionnaires that limit its conclusions when we consider the globality of the Erasmus Mundus Students. Research/Practical Implications: This study presents evidence that Ang and Van Dyne’s scale is an adequate measure instrument to assess intercultural intelligence in a multicultural setting of students and alumni. Originality/Value: Multicultural samples and studies are becoming more and more present and relevant; the study of intercultural competences and habilities is becoming increasingly important, and in this task, solid psychometric instruments are of paramount importance. This study presents evidence that Ang and Van Dyne’s (2006) scale is a fairly recent and parsimonious instrument with excellent psychometric properties properties.
Resumo:
Erasmus Mundus Masters (EMM) are programs with a strong component of interculturality. Our study aimed at understanding the level of cultural intelligence (CQ) of EMM students and alumni, as well as some of the characteristics associated with higher levels of CQ. The study included 626 EMM students and alumni from 109 different countries that encompasses 6 continents. Ang and Van Dyne’s (2006) cultural intelligence scale was used; closed and open ended questions were used to describe the sample’s sociodemographic characteristics and experiences regarding interculturality. After validating and assessing the scale’s psychometric properties, relations between different variables were explored using Pearson’s correlation, ANOVA, t Tests, and GLM procedures. We then analysed the open ended responses to gain further insight on our results. Differences among respondents are mainly equated with international experience rather than nationality or training. Respondents’ open ended replies provided us with a deeper insight on why training seems to be so ineffective in developing CQ. This is a transversal study that uses self-reporting measures; also, questionnaires were conducted in English, which was not the mother tongue of most of the respondents. This work is consistent with the CQ literature, however we argue that training mentioned by respondents systematically fails to meet some of literature’s foremost conditions for effective CQ trainings and provide clues for the implementation of more successful initiatives. With an exceptionally diverse sample, this study contributes towards the understanding of mechanisms of developing CQ among EMM and international Students. Results can be useful for selection processes, training/development of CQ and reducing dropout/turnover.
Resumo:
Based on a report for the seminar Industrial Networks, at Goethe Universität Frankfurt am Main Dozent: Prof. Dr. Blättel-Mink, Prof. Dr. António Moniz SS 2011