Estratégia do planejamento e otimização de sistemas sem fio, considerando redes interferentes: abordagem baseada em cross-layer

Apesar do aumento significativo do uso de redes locais sem fio (WLAN) nos últimos anos, aspectos de projeto e planejamento de capacidade da rede são ainda sistematicamente negligenciados durante a implementação da rede. Tipicamente um projeto de rede local sem fio é feito e instalado por profissionais de rede. Esses profissionais são extremamente experientes com redes cabeadas, mas são ainda geralmente pouco experientes com redes sem fio. Deste modo, as instalações de redes locais sem fio são desvantajosas pela falta de um modelo de avaliação de desempenho e para determinar a localização do ponto de acesso (PA), além disso, fatores importantes do ambiente não são considerados no projeto. Esses fatores se tornam mais importante quando muitos pontos de acesso (PAs) são instalados para cobrir um único edifício, algumas vezes sem planejamento de freqüência. Falhas como essa podem causar interferência entre células geradas pelo mesmo PA. Por essa razão, a rede não obterá os padrões de qualidade de serviço (QoS) exigidos por cada serviço. O presente trabalho apresenta uma proposta para planejamento de redes sem fio levando em consideração a influência da interferência com o auxílio de inteligência computacional tais como a utilização de redes Bayesianas. Uma extensiva campanha de medição foi feita para avaliar o desempenho de dois pontos de acesso (PAs) sobre um cenário multiusuário, com e sem interferência. Os dados dessa campanha de medição foram usados como entrada das redes Bayesianas e confirmaram a influência da interferência nos parâmetros de QoS. Uma implementação de algoritmo genético foi utilizado permitindo uma abordagem híbrida para planejamento de redes sem fio. Como efeito de comparação para otimizar os parâmetros de QoS, de modo a encontrar a melhor distância do PA ao receptor garantindo as recomendações do International Telecomunication Union (ITU-T), a técnica de otimização por enxame de partículas foi aplicada.

Particle swarm optimization aplicada ao planejamento da expansão de sistemas de transmissão

Pós-graduação em Engenharia Elétrica - FEIS

Age polyethism in the swarm-founding wasp Metapolybia miltoni (Andena & Carpenter) (Hymenoptera: Vespidae; Polistinae, Epiponini)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Marimbondos: a review on the neotropical swarm-founding polistines

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Seleção de características utilizando algoritmos evolucionistas e suas aplicações em reconhecimento de padrões

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Morphology of Richards' gland in the swarm-founding wasp (Hymenoptera, Vespidae)

Richards' gland is known for the majority of Epiponini wasps, and despite few experimental evidences, the taxonomic distribution in swarm-founder species and the function of this gland remain rather unclear. This work presents a morphological description of Richards' gland in Protonectarina sylveirae. The gland is formed by a cluster of class 3 cells underneath the anterior margin of the fifth metasomal sternite, and a reservoir formed by the intersegmental membrane between the fourth and fifth metasomal sternites where the secretion can be stored. The secretory cells contain a branched end apparatus that carries the secretory products towards the duct cell. Externally, the cuticle of the sternite, where the duct cells penetrate, is characterized by modifications as scales with very numerous pores. The presence of Richards' gland according to the model proposed by Samacá et al. 2013 in Protonectarina corroborates the single origin of this gland in Epiponini. The occurrence of a Golgi apparatus and smooth endoplasmic reticulum suggests pheromone production.

Morphological caste studies in the neotropical swarm-founding polistinae wasp Angiopolybia pattern (Lepeletier) (hymenoptera: Vespidae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Epidemiological intelligence as a model of organization in health

The concept of epidemiological intelligence, as a construction of information societies, goes beyond monitoring a list of diseases and the ability to elicit rapid responses. The concept should consider the complexity of the definition of epidemiology in the identification of this object of study without being limited to a set of actions in a single government sector. The activities of epidemiological intelligence include risk assessment, strategies for prevention and protection, subsystems of information, crisis management rooms, geographical analysis, etc. This concept contributes to the understanding of policies in health, in multisectorial and geopolitical dimensions, as regards the organization of services around public health emergencies, primary healthcare, as well as disasters. The activities of epidemiological intelligence should not be restricted to scientific research, but the researchers must beware of threats to public health. Lalonde's model enabled consideration of epidemiological intelligence as a way to restructure policies and share resources by creating communities of intelligence, whose purpose is primarily to deal with public health emergencies and disasters.

Petrology and Sr-Nd characteristics of the Nova Lacerda dike swarm, SW Amazonian Craton: new insights regarding its subcontinental mantle source and Mesoproterozoic geodynamics

The NNW-trending Nova Lacerda tholeiitic dike swarm in Mato Grosso State, Central Brazil, intrudes the Nova Lacerda granite (1.46 Ga) and the Jauru granite-greenstone terrain (ca. 1.79-1.77 Ga). The swarm comprises diabases I and II and amphibolites emplaced at ca. 1.38 Ga. Geochemical data indicate that these are evolved tholeiites characterized by high LILE/HSFE and LREE/HSFE ratios. Isotopic modelling yields positive epsilon(Nd)(T) values (+0.86 to +2.65), whereas values for epsilon(Sr)(T) range from positive to negative (+1.96 to -5.56). Crustal contamination did not play a significant petrogenetic role, as indicated by a comparison of isotopic data (Sr-Nd) from both dikes and country rocks, and by the relationship between isotopic and geochemical parameters (SiO2, K2O, Rb/Sr, and La/Yb) of the dikes. We attribute the origin of these tholeiites to fractional crystallization of evolved melts derived from a heterogeneous mantle source. Comparison of the geochemical and isotopic data of the studied swarm and other tholeiitic Mesoproterozoic mafic intrusions of the SWAmazonian Craton the Serra da Providencia, Colorado, and Nova Brasilandia bimodal suites - indicates that parental melts of the Nova Lacerda swarm were derived from the most enriched mantle source. This enrichment was probably caused by the stronger influence of the EMI component on the DMM end-member. These data, coupled with trace element bulk-rock geochemistry of the country rocks, and comparisons with the Colorado Complex of similar age, suggest a continental-margin arc setting for the emplacement of the Nova Lacerda dikes.

Combining meta-learning and search techniques to select parameters for support vector machines

Support Vector Machines (SVMs) have achieved very good performance on different learning problems. However, the success of SVMs depends on the adequate choice of the values of a number of parameters (e.g., the kernel and regularization parameters). In the current work, we propose the combination of meta-learning and search algorithms to deal with the problem of SVM parameter selection. In this combination, given a new problem to be solved, meta-learning is employed to recommend SVM parameter values based on parameter configurations that have been successfully adopted in previous similar problems. The parameter values returned by meta-learning are then used as initial search points by a search technique, which will further explore the parameter space. In this proposal, we envisioned that the initial solutions provided by meta-learning are located in good regions of the search space (i.e. they are closer to optimum solutions). Hence, the search algorithm would need to evaluate a lower number of candidate solutions when looking for an adequate solution. In this work, we investigate the combination of meta-learning with two search algorithms: Particle Swarm Optimization and Tabu Search. The implemented hybrid algorithms were used to select the values of two SVM parameters in the regression domain. These combinations were compared with the use of the search algorithms without meta-learning. The experimental results on a set of 40 regression problems showed that, on average, the proposed hybrid methods obtained lower error rates when compared to their components applied in isolation.

Intelligence systems methodology: a systemic approach to the organizational intelligence function

Organizational intelligence can be seen as a function of the viable structure of an organization. With the integration of the Viable System Model and Soft Systems Methodology (systemic approaches of organizational management) focused on the role of the intelligence function, it is possible to elaborate a model of action with a structured methodology to prospect, select, treat and distribute information to the entire organization that improves the efficacy and efficiency of all processes. This combination of methodologies is called Intelligence Systems Methodology (ISM) whose assumptions and dynamics are delimited in this paper. The ISM is composed of two simultaneous activities: the Active Environmental Mapping and the Stimulated Action Cycle. The elaboration of the formal ISM description opens opportunities for applications of the methodology on real situations, offering a new path for this specific issue of systems thinking: the intelligence systems. Knowledge Management Research & Practice (2012) 10, 141-152. doi:10.1057/kmrp.2011.44

Cash balance management: A comparison between genetic algorithms and particle swarm optimization

This work aimed to apply genetic algorithms (GA) and particle swarm optimization (PSO) in cash balance management using Miller-Orr model, which consists in a stochastic model that does not define a single ideal point for cash balance, but an oscillation range between a lower bound, an ideal balance and an upper bound. Thus, this paper proposes the application of GA and PSO to minimize the Total Cost of cash maintenance, obtaining the parameter of the lower bound of the Miller-Orr model, using for this the assumptions presented in literature. Computational experiments were applied in the development and validation of the models. The results indicated that both the GA and PSO are applicable in determining the cash level from the lower limit, with best results of PSO model, which had not yet been applied in this type of problem.

Shape differences rather than size differences between castes in the Neotropical swarm-founding wasp Metapolybia docilis (Hymenoptera: Vespidae, Epiponini)

Abstract Background Swarm-founding epiponine wasps are an intriguing group of social insects in which colonies are polygynic (several queens share reproduction) and differentiation between castes is often not obvious. However, caste differences in some may be more pronounced in later phases of the colony cycle. Results Using morphometric analyses and multivariate statistics, it was found that caste differences in Metapolybia docilis are slight but more distinct in latter stages of the colony cycle. Conclusions Because differences in body parts are so slight, it is proposed that such variation may be due to differential growth rates of body parts rather than to queens being larger in size, similar to other previously observed epiponines.