31 resultados para real-world

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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Os sistemas biológicos são surpreendentemente flexíveis pra processar informação proveniente do mundo real. Alguns organismos biológicos possuem uma unidade central de processamento denominada de cérebro. O cérebro humano consiste de 10(11) neurônios e realiza processamento inteligente de forma exata e subjetiva. A Inteligência Artificial (IA) tenta trazer para o mundo da computação digital a heurística dos sistemas biológicos de várias maneiras, mas, ainda resta muito para que isso seja concretizado. No entanto, algumas técnicas como Redes neurais artificiais e lógica fuzzy tem mostrado efetivas para resolver problemas complexos usando a heurística dos sistemas biológicos. Recentemente o numero de aplicação dos métodos da IA em sistemas zootécnicos tem aumentado significativamente. O objetivo deste artigo é explicar os princípios básicos da resolução de problemas usando heurística e demonstrar como a IA pode ser aplicada para construir um sistema especialista para resolver problemas na área de zootecnia.

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The conventional approach to simple quantum chemistry models is contrasted with that known as momentum representation, where the wavefunctions are momentum dependent. Since the physical interactions are the same, state energies should not change, and whence the energy differences correlating with the real world as spectral lines or bands. We emphasize that one representation is not more fundamental than the other, and the choice is a matter of mathematical convenience. As spatial localization is rooted in our brains, to think in terms of the momentum present us a great mental challenge that can lead to complementary perspectives of a model.

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A network can be analyzed at different topological scales, ranging from single nodes to motifs, communities, up to the complete structure. We propose a novel approach which extends from single nodes to the whole network level by considering non-overlapping subgraphs (i.e. connected components) and their interrelationships and distribution through the network. Though such subgraphs can be completely general, our methodology focuses on the cases in which the nodes of these subgraphs share some special feature, such as being critical for the proper operation of the network. The methodology of subgraph characterization involves two main aspects: (i) the generation of histograms of subgraph sizes and distances between subgraphs and (ii) a merging algorithm, developed to assess the relevance of nodes outside subgraphs by progressively merging subgraphs until the whole network is covered. The latter procedure complements the histograms by taking into account the nodes lying between subgraphs, as well as the relevance of these nodes to the overall subgraph interconnectivity. Experiments were carried out using four types of network models and five instances of real-world networks, in order to illustrate how subgraph characterization can help complementing complex network-based studies.

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This article focuses on the identification of the number of paths with different lengths between pairs of nodes in complex networks and how these paths can be used for characterization of topological properties of theoretical and real-world complex networks. This analysis revealed that the number of paths can provide a better discrimination of network models than traditional network measurements. In addition, the analysis of real-world networks suggests that the long-range connectivity tends to be limited in these networks and may be strongly related to network growth and organization.

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A great part of the interest in complex networks has been motivated by the presence of structured, frequently nonuniform, connectivity. Because diverse connectivity patterns tend to result in distinct network dynamics, and also because they provide the means to identify and classify several types of complex network, it becomes important to obtain meaningful measurements of the local network topology. In addition to traditional features such as the node degree, clustering coefficient, and shortest path, motifs have been introduced in the literature in order to provide complementary descriptions of the network connectivity. The current work proposes a different type of motif, namely, chains of nodes, that is, sequences of connected nodes with degree 2. These chains have been subdivided into cords, tails, rings, and handles, depending on the type of their extremities (e.g., open or connected). A theoretical analysis of the density of such motifs in random and scale-free networks is described, and an algorithm for identifying these motifs in general networks is presented. The potential of considering chains for network characterization has been illustrated with respect to five categories of real-world networks including 16 cases. Several interesting findings were obtained, including the fact that several chains were observed in real-world networks, especially the world wide web, books, and the power grid. The possibility of chains resulting from incompletely sampled networks is also investigated.

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Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.

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One important issue implied by the finite nature of real-world networks regards the identification of their more external (border) and internal nodes. The present work proposes a formal and objective definition of these properties, founded on the recently introduced concept of node diversity. It is shown that this feature does not exhibit any relevant correlation with several well-established complex networks measurements. A methodology for the identification of the borders of complex networks is described and illustrated with respect to theoretical (geographical and knitted networks) as well as real-world networks (urban and word association networks), yielding interesting results and insights in both cases.

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Cooling towers are widely used in many industrial and utility plants as a cooling medium, whose thermal performance is of vital importance. Despite the wide interest in cooling tower design, rating and its importance in energy conservation, there are few investigations concerning the integrated analysis of cooling systems. This work presents an approach for the systemic performance analysis of a cooling water system. The approach combines experimental design with mathematical modeling. An experimental investigation was carried out to characterize the mass transfer in the packing of the cooling tower as a function of the liquid and gas flow rates, whose results were within the range of the measurement accuracy. Then, an integrated model was developed that relies on the mass and heat transfer of the cooling tower, as well as on the hydraulic and thermal interactions with a heat exchanger network. The integrated model for the cooling water system was simulated and the temperature results agree with the experimental data of the real operation of the pilot plant. A case study illustrates the interaction in the system and the need for a systemic analysis of cooling water system. The proposed mathematical and experimental analysis should be useful for performance analysis of real-world cooling water systems. (C) 2009 Elsevier Ltd. All rights reserved.

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Using the network random generation models from Gustedt (2009)[23], we simulate and analyze several characteristics (such as the number of components, the degree distribution and the clustering coefficient) of the generated networks. This is done for a variety of distributions (fixed value, Bernoulli, Poisson, binomial) that are used to control the parameters of the generation process. These parameters are in particular the size of newly appearing sets of objects, the number of contexts in which new elements appear initially, the number of objects that are shared with `parent` contexts, and, the time period inside which a context may serve as a parent context (aging). The results show that these models allow to fine-tune the generation process such that the graphs adopt properties as can be found in real world graphs. (C) 2011 Elsevier B.V. All rights reserved.

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The traditional theory of price index numbers is based on the law of one price. But in the real world, we frequently observe the existence of an equilibrium price dispersion instead of one price of equilibrium. This article discusses the effects of price dispersion on two price indexes: the cost of living index and the consumer price index. With price dispersion and consumer searching for the lowest price, these indexes cannot be interpreted as deterministic indicators, but as stochastic indicators, and they can be biased if price dispersion is not taken into account. A measure for the bias of the consumer price index is proposed and the article ends with an estimation of the bias based on data obtained from the consumer price index calculated for the city of Sao Paulo, Brazil, from January 1988 through December 2004. The period analysed is very interesting, because it exhibits different inflationary environments: high levels and high volatility of the rates of inflation with great price dispersion until July 1994 and low and relatively stable rates of inflation with prices less dispersed after August 1994.

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In [Haiyin Gao, Ke Wang, Fengying Wei, Xiaohua Ding, Massera-type theorem and asymptotically periodic Logistic equations, Nonlinear Analysis: Real World Applications 7 (2006) 1268-1283, Lemma 2.1] it is established that a scalar S-asymptotically to-periodic function (that is, a continuous and bounded function f : [0, infinity) -> R such that lim(t ->infinity)(f (t + omega) - f (t)) = 0) is asymptotically omega-periodic. In this note we give two examples to show that this assertion is false. (C) 2008 Elsevier Ltd. Ail rights reserved.

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Objectives: We compared 12-month outcomes, regarding ischemic events, repeat intervention, and ST, between diabetic and nondiabetic patients treated with the Genous (TM) EPC capturing R stent (TM) during routine nonurgent percutaneous coronary intervention (PCI) using data from the multicenter, prospective worldwide e-HEALING registry. Background: Diabetic patients have an increased risk for restenosis and stent thrombosis (ST). Methods: In the 4,996 patient e-HEALING registry, 273 were insulin requiring diabetics (IRD), 963 were non-IRD (NIRD), and 3,703 were nondiabetics. The 12-month primary outcome was target vessel failure (TVF), defined as target vessel-related cardiac death or myocardial infarction (MI) and target vessel revascularization. Secondary outcomes were the composite of cardiac death, MI or target lesion revascularization (TLR), and individual outcomes including ST. Cumulative event rates were estimated with the Kaplan-Meier method and compared with a log-rank test. Results: TVF rates were respectively 13.4% in IRD, 9.0% in NIRD, and 7.9% in nondiabetics (P < 0.01). This was mainly driven by a higher mortality hazard in IRD (P < 0.001) and NIRD (P = 0.07), compared with nondiabetics. TLR rates were comparable in NIRD and nondiabetics, but significantly higher in IRD (P = 0.04). No difference was observed in ST. Conclusion: The 1-year results of the Genous stent in a real-world population of diabetics show higher TVF rates in diabetics compared with nondiabetics, mainly driven by a higher mortality hazard. IRD is associated with a significant higher TLR hazard. Definite or probable ST in all diabetic patients was comparable with nondiabetics. (J Interven Cardiol 2011;24:285-294)

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Objectives: We tested two novel drug-eluting stents (DES), covered with a biodegradable-polymer carrier and releasing paclitaxel or sirolimus, which were compared against a bare metal stent (primary objective). The DES differed by the drug, but were identical otherwise, allowing to compare the anti-restenosis effects of sirolimus versus paclitaxel (secondary objective). Background: The efficacy of novel DES with biodegradable polymers should be tested in the context of randomized trials, even when using drugs known to be effective, such as sirolimus and paclitaxel. Methods: Overall, 274 patients with de novo coronary lesions in native vessels scheduled for stent implantation were randomly assigned (2:21 ratio) for the paclitaxel (n = 111), sirolimus (n = 106), or bare metal stent (n = 57) groups. Angiographic follow-up was obtained at 9 months and major cardiac adverse events up to 12 months. Results: Both paclitaxel and sirolimus stents reduced the 9-month in-stent late loss (0.54-0.44 mm, 0.32-0.43 mm, vs. 0.90-0.45 mm respectively), and 1-year risk of target vessel revascularization and combined major adverse cardiac events (P < 0.05 for both, in all comparisons), compared with controls. Sirolimus stents had lower late loss than paclitaxel stents (P < 0.01), but similar 1-year clinical outcomes. There were no differences in the risk of death, infarction, or stent thrombosis among the study groups. Conclusion: Both novel DES were effective in reducing neointimal hyperplasia and 1-year re-intervention, compared to bare metal stents. Our findings also suggest that sirolimus is more effective than paclitaxel in reducing angiographic neointima, although this effect was not associated with better clinical outcomes. (C) 2009 Wiley-Liss, Inc.

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Objective: To evaluate the validity and applicability of the Mini International Neuropsychiatric Interview (MINI) used by family medicine residents in primary health care (PHC) in Brazil. Methods: Training for administrating the MINI was given as part of a broad psychiatry education program. Interviews were held with 120 PHC patients who were at least 15 years old. MINI was administered by 25 resident physicians, while the Structured Clinical Interview for Diagnosis (SCID) was administered by a psychiatrist blind to patients` results on the MINI, and the diagnoses on both interviews were compared. The resident physicians answered questions on the applicability of the MINI. Results: Concordance levels for any mental disorder, the broader current diagnostic categories and the most common specific diagnoses were analyzed. Kappa coefficients ranged between 0.65 and 0.85; sensitivity, between 0.75 and 0.92; specificity, between 0.90 and 0.99; positive predictive values (PPV), between 0.60 and 0.86; negative predictive values (NPV), between 0.92 and 0.99; and accuracy, between 0.88 and 0.98. The resident physicians considered MINI comprehensibility and clinical relevance satisfactory. Conclusions: These good psychometric results in a real-world setting may be related to a special training program, which is more frequent, intensive and diversified. In these conditions, the MINI is a useful tool for general practitioners. (c) 2008 Elsevier Inc. All rights reserved.

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Searching in a dataset for elements that are similar to a given query element is a core problem in applications that manage complex data, and has been aided by metric access methods (MAMs). A growing number of applications require indices that must be built faster and repeatedly, also providing faster response for similarity queries. The increase in the main memory capacity and its lowering costs also motivate using memory-based MAMs. In this paper. we propose the Onion-tree, a new and robust dynamic memory-based MAM that slices the metric space into disjoint subspaces to provide quick indexing of complex data. It introduces three major characteristics: (i) a partitioning method that controls the number of disjoint subspaces generated at each node; (ii) a replacement technique that can change the leaf node pivots in insertion operations; and (iii) range and k-NN extended query algorithms to support the new partitioning method, including a new visit order of the subspaces in k-NN queries. Performance tests with both real-world and synthetic datasets showed that the Onion-tree is very compact. Comparisons of the Onion-tree with the MM-tree and a memory-based version of the Slim-tree showed that the Onion-tree was always faster to build the index. The experiments also showed that the Onion-tree significantly improved range and k-NN query processing performance and was the most efficient MAM, followed by the MM-tree, which in turn outperformed the Slim-tree in almost all the tests. (C) 2010 Elsevier B.V. All rights reserved.