954 resultados para Search strategy
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The Rural Postman Problem (RPP) is a particular Arc Routing Problem (ARP) which consists of determining a minimum cost circuit on a graph so that a given subset of required edges is traversed. The RPP is an NP-hard problem with significant real-life applications. This paper introduces an original approach based on Memetic Algorithms - the MARP algorithm - to solve the RPP and, also deals with an interesting Industrial Application, which focuses on the path optimization for component cutting operations. Memetic Algorithms are a class of Metaheuristics which may be seen as a population strategy that involves cooperation and competition processes between population elements and integrates “social knowledge”, using a local search procedure. The MARP algorithm is tested with different groups of instances and the results are compared with those gathered from other publications. MARP is also used in the context of various real-life applications.
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Cloud data centers have been progressively adopted in different scenarios, as reflected in the execution of heterogeneous applications with diverse workloads and diverse quality of service (QoS) requirements. Virtual machine (VM) technology eases resource management in physical servers and helps cloud providers achieve goals such as optimization of energy consumption. However, the performance of an application running inside a VM is not guaranteed due to the interference among co-hosted workloads sharing the same physical resources. Moreover, the different types of co-hosted applications with diverse QoS requirements as well as the dynamic behavior of the cloud makes efficient provisioning of resources even more difficult and a challenging problem in cloud data centers. In this paper, we address the problem of resource allocation within a data center that runs different types of application workloads, particularly CPU- and network-intensive applications. To address these challenges, we propose an interference- and power-aware management mechanism that combines a performance deviation estimator and a scheduling algorithm to guide the resource allocation in virtualized environments. We conduct simulations by injecting synthetic workloads whose characteristics follow the last version of the Google Cloud tracelogs. The results indicate that our performance-enforcing strategy is able to fulfill contracted SLAs of real-world environments while reducing energy costs by as much as 21%.
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A new iterative algorithm based on the inexact-restoration (IR) approach combined with the filter strategy to solve nonlinear constrained optimization problems is presented. The high level algorithm is suggested by Gonzaga et al. (SIAM J. Optim. 14:646–669, 2003) but not yet implement—the internal algorithms are not proposed. The filter, a new concept introduced by Fletcher and Leyffer (Math. Program. Ser. A 91:239–269, 2002), replaces the merit function avoiding the penalty parameter estimation and the difficulties related to the nondifferentiability. In the IR approach two independent phases are performed in each iteration, the feasibility and the optimality phases. The line search filter is combined with the first one phase to generate a “more feasible” point, and then it is used in the optimality phase to reach an “optimal” point. Numerical experiences with a collection of AMPL problems and a performance comparison with IPOPT are provided.
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Innovation is recognized by academics and practitioners as an essential competitive enabler for any company to survive, to remain competitive and to grow. Investments in tasks of R&D have not always brought the expected results. But that doesn't mean that the outcomes would not be useful to other companies of the same business area or even from another area. Thus, there is much knowledge already available in the market that can be helpful to some and profitable to others. So, the ideas and expertise can be found outside a company's boundaries and also exported from within. Information, knowledge, experience, wisdom is already available in the millions of the human beings of this planet, the challenge is to use them through a network to produce new ideas and tips that can be useful to a company with less costs. This was the reason for the emergence of the area of crowdsourcing innovation. Crowdsourcing innovation is a way of using the Web 2.0 tools to generate new ideas through the heterogeneous knowledge available in the global network of individuals highly qualified and with easy access to information and technology. So, a crowdsourcing innovation broker is an organization that mediates the communication and relationship between the seekers - companies that aspire to solve some problem or to take advantage of any business opportunity - with a crowd that is prone to give ideas based on their knowledge, experience and wisdom. This paper makes a literature review on models of open innovation, crowdsourcing innovation, and technology and knowledge intermediaries, and discusses this new phenomenon as a way to leverage the innovation capacity of enterprises. Finally, the paper outlines a research design agendafor explaining crowdsourcing innovation brokering phenomenon, exploiting its players, main functions, value creation process, and knowledge creation in order to define a knowledge metamodel of such intermediaries.
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In this work we propose a mathematical approach to estimate the dengue force of infection, the average age of dengue first infection, the optimum age to vaccinate children against dengue in a routine fashion and the optimum age interval to introduce the dengue vaccine in a mass vaccination campaign. The model is based on previously published models for vaccination against other childhood infections, which resulted in actual vaccination programmes in Brazil. The model was applied for three areas of distinct levels of endemicity of the city of Recife in Northeastern State of Pernambuco, Brazil. Our results point to an optimal age to introduce the dengue vaccine in the routine immunization programme at two years of age and an age interval to introduce a mass vaccination between three and 14 years of age.
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Leprosy is a disease caused by Mycobacterium leprae that carries a high risk of disability, making early diagnosis mandatory. This study aimed to determine the applicability of anti-PGL-1 IgM antibody detection, using the ML FLOW technique, as an assistant tool for the detection of leprosy infection in asymptomatic household contacts (AHHC) of multibacillary leprosy index cases from Midwest Brazil. Serological changes induced by the prophylaxis of these household contacts with Bacillus Calmette-Guérin (BCG) were also verified. A total of 91 AHHC were assessed, among which, 18.68% (n = 17) presented both positive bacilloscopy and positive anti-PGL-1 IgM serology. Positivity concordance between these two laboratorial exams (Kappa Index = 1; p < 0.001) was indicated, however, one case did not demonstrate concordance between the semiquantitative assessment of anti-PGL-1 IgM and the bacilloscopy index (Kappa Index = 0.96; p < 0.001). Among the 17 AHHC with positive bacilloscopy, eight were reassessed after prophylaxis with BCG and two of them presented negative anti-PGL-1 IgM serology, being these patients who had presented a bacilloscopy index of < 2[+] in the initial assessment. This study shows that anti-PGL-1 IgM detection may be used as a tool to determine the bacillary load in AHHC and to detect immune changes related to prophylaxis by nonspecific vaccination.
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This dissertation is presented to obtain a Master degree in Structural and Functional Biochemistry
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Master’s Degree Dissertation
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Dissertação para obtenção do Grau de Mestre em Biotecnologia
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics