996 resultados para Multicommodity flow algorithms
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Buffered crossbar switches have recently attracted considerable attention as the next generation of high speed interconnects. They are a special type of crossbar switches with an exclusive buffer at each crosspoint of the crossbar. They demonstrate unique advantages over traditional unbuffered crossbar switches, such as high throughput, low latency, and asynchronous packet scheduling. However, since crosspoint buffers are expensive on-chip memories, it is desired that each crosspoint has only a small buffer. This dissertation proposes a series of practical algorithms and techniques for efficient packet scheduling for buffered crossbar switches. To reduce the hardware cost of such switches and make them scalable, we considered partially buffered crossbars, whose crosspoint buffers can be of an arbitrarily small size. Firstly, we introduced a hybrid scheme called Packet-mode Asynchronous Scheduling Algorithm (PASA) to schedule best effort traffic. PASA combines the features of both distributed and centralized scheduling algorithms and can directly handle variable length packets without Segmentation And Reassembly (SAR). We showed by theoretical analysis that it achieves 100% throughput for any admissible traffic in a crossbar with a speedup of two. Moreover, outputs in PASA have a large probability to avoid the more time-consuming centralized scheduling process, and thus make fast scheduling decisions. Secondly, we proposed the Fair Asynchronous Segment Scheduling (FASS) algorithm to handle guaranteed performance traffic with explicit flow rates. FASS reduces the crosspoint buffer size by dividing packets into shorter segments before transmission. It also provides tight constant performance guarantees by emulating the ideal Generalized Processor Sharing (GPS) model. Furthermore, FASS requires no speedup for the crossbar, lowering the hardware cost and improving the switch capacity. Thirdly, we presented a bandwidth allocation scheme called Queue Length Proportional (QLP) to apply FASS to best effort traffic. QLP dynamically obtains a feasible bandwidth allocation matrix based on the queue length information, and thus assists the crossbar switch to be more work-conserving. The feasibility and stability of QLP were proved, no matter whether the traffic distribution is uniform or non-uniform. Hence, based on bandwidth allocation of QLP, FASS can also achieve 100% throughput for best effort traffic in a crossbar without speedup.
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Flow Cytometry analyzers have become trusted companions due to their ability to perform fast and accurate analyses of human blood. The aim of these analyses is to determine the possible existence of abnormalities in the blood that have been correlated with serious disease states, such as infectious mononucleosis, leukemia, and various cancers. Though these analyzers provide important feedback, it is always desired to improve the accuracy of the results. This is evidenced by the occurrences of misclassifications reported by some users of these devices. It is advantageous to provide a pattern interpretation framework that is able to provide better classification ability than is currently available. Toward this end, the purpose of this dissertation was to establish a feature extraction and pattern classification framework capable of providing improved accuracy for detecting specific hematological abnormalities in flow cytometric blood data. ^ This involved extracting a unique and powerful set of shift-invariant statistical features from the multi-dimensional flow cytometry data and then using these features as inputs to a pattern classification engine composed of an artificial neural network (ANN). The contribution of this method consisted of developing a descriptor matrix that can be used to reliably assess if a donor’s blood pattern exhibits a clinically abnormal level of variant lymphocytes, which are blood cells that are potentially indicative of disorders such as leukemia and infectious mononucleosis. ^ This study showed that the set of shift-and-rotation-invariant statistical features extracted from the eigensystem of the flow cytometric data pattern performs better than other commonly-used features in this type of disease detection, exhibiting an accuracy of 80.7%, a sensitivity of 72.3%, and a specificity of 89.2%. This performance represents a major improvement for this type of hematological classifier, which has historically been plagued by poor performance, with accuracies as low as 60% in some cases. This research ultimately shows that an improved feature space was developed that can deliver improved performance for the detection of variant lymphocytes in human blood, thus providing significant utility in the realm of suspect flagging algorithms for the detection of blood-related diseases.^
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General-purpose parallel processing for solving day-to-day industrial problems has been slow to develop, partly because of the lack of suitable hardware from well-established, mainstream computer manufacturers and suitably parallelized application software. The parallelization of a CFD-(computational fluid dynamics) flow solution code is known as ESAUNA. This code is part of SAUNA, a large CFD suite aimed at computing the flow around very complex aircraft configurations including complete aircraft. A novel feature of the SAUNA suite is that it is designed to use either block-structured hexahedral grids, unstructured tetrahedral grids, or a hybrid combination of both grid types. ESAUNA is designed to solve the Euler equations or the Navier-Stokes equations, the latter in conjunction with various turbulence models. Two fundamental parallelization concepts are used—namely, grid partitioning and encapsulation of communications. Grid partitioning is applied to both block-structured grid modules and unstructured grid modules. ESAUNA can also be coupled with other simulation codes for multidisciplinary computations such as flow simulations around an aircraft coupled with flutter prediction for transient flight simulations.
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Recently, there has been considerable interest in solving viscoelastic problems in 3D particularly with the improvement in modern computing power. In many applications the emphasis has been on economical algorithms which can cope with the extra complexity that the third dimension brings. Storage and computer time are of the essence. The advantage of the finite volume formulation is that a large amount of memory space is not required. Iterative methods rather than direct methods can be used to solve the resulting linear systems efficiently.
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This thesis presents approximation algorithms for some NP-Hard combinatorial optimization problems on graphs and networks; in particular, we study problems related to Network Design. Under the widely-believed complexity-theoretic assumption that P is not equal to NP, there are no efficient (i.e., polynomial-time) algorithms that solve these problems exactly. Hence, if one desires efficient algorithms for such problems, it is necessary to consider approximate solutions: An approximation algorithm for an NP-Hard problem is a polynomial time algorithm which, for any instance of the problem, finds a solution whose value is guaranteed to be within a multiplicative factor of the value of an optimal solution to that instance. We attempt to design algorithms for which this factor, referred to as the approximation ratio of the algorithm, is as small as possible. The field of Network Design comprises a large class of problems that deal with constructing networks of low cost and/or high capacity, routing data through existing networks, and many related issues. In this thesis, we focus chiefly on designing fault-tolerant networks. Two vertices u,v in a network are said to be k-edge-connected if deleting any set of k − 1 edges leaves u and v connected; similarly, they are k-vertex connected if deleting any set of k − 1 other vertices or edges leaves u and v connected. We focus on building networks that are highly connected, meaning that even if a small number of edges and nodes fail, the remaining nodes will still be able to communicate. A brief description of some of our results is given below. We study the problem of building 2-vertex-connected networks that are large and have low cost. Given an n-node graph with costs on its edges and any integer k, we give an O(log n log k) approximation for the problem of finding a minimum-cost 2-vertex-connected subgraph containing at least k nodes. We also give an algorithm of similar approximation ratio for maximizing the number of nodes in a 2-vertex-connected subgraph subject to a budget constraint on the total cost of its edges. Our algorithms are based on a pruning process that, given a 2-vertex-connected graph, finds a 2-vertex-connected subgraph of any desired size and of density comparable to the input graph, where the density of a graph is the ratio of its cost to the number of vertices it contains. This pruning algorithm is simple and efficient, and is likely to find additional applications. Recent breakthroughs on vertex-connectivity have made use of algorithms for element-connectivity problems. We develop an algorithm that, given a graph with some vertices marked as terminals, significantly simplifies the graph while preserving the pairwise element-connectivity of all terminals; in fact, the resulting graph is bipartite. We believe that our simplification/reduction algorithm will be a useful tool in many settings. We illustrate its applicability by giving algorithms to find many trees that each span a given terminal set, while being disjoint on edges and non-terminal vertices; such problems have applications in VLSI design and other areas. We also use this reduction algorithm to analyze simple algorithms for single-sink network design problems with high vertex-connectivity requirements; we give an O(k log n)-approximation for the problem of k-connecting a given set of terminals to a common sink. We study similar problems in which different types of links, of varying capacities and costs, can be used to connect nodes; assuming there are economies of scale, we give algorithms to construct low-cost networks with sufficient capacity or bandwidth to simultaneously support flow from each terminal to the common sink along many vertex-disjoint paths. We further investigate capacitated network design, where edges may have arbitrary costs and capacities. Given a connectivity requirement R_uv for each pair of vertices u,v, the goal is to find a low-cost network which, for each uv, can support a flow of R_uv units of traffic between u and v. We study several special cases of this problem, giving both algorithmic and hardness results. In addition to Network Design, we consider certain Traveling Salesperson-like problems, where the goal is to find short walks that visit many distinct vertices. We give a (2 + epsilon)-approximation for Orienteering in undirected graphs, achieving the best known approximation ratio, and the first approximation algorithm for Orienteering in directed graphs. We also give improved algorithms for Orienteering with time windows, in which vertices must be visited between specified release times and deadlines, and other related problems. These problems are motivated by applications in the fields of vehicle routing, delivery and transportation of goods, and robot path planning.
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Rapidity-odd directed flow (v1) measurements for charged pions, protons, and antiprotons near midrapidity (y=0) are reported in sNN=7.7, 11.5, 19.6, 27, 39, 62.4, and 200 GeV Au+Au collisions as recorded by the STAR detector at the Relativistic Heavy Ion Collider. At intermediate impact parameters, the proton and net-proton slope parameter dv1/dy|y=0 shows a minimum between 11.5 and 19.6 GeV. In addition, the net-proton dv1/dy|y=0 changes sign twice between 7.7 and 39 GeV. The proton and net-proton results qualitatively resemble predictions of a hydrodynamic model with a first-order phase transition from hadronic matter to deconfined matter, and differ from hadronic transport calculations.
Biased Random-key Genetic Algorithms For The Winner Determination Problem In Combinatorial Auctions.
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Abstract In this paper, we address the problem of picking a subset of bids in a general combinatorial auction so as to maximize the overall profit using the first-price model. This winner determination problem assumes that a single bidding round is held to determine both the winners and prices to be paid. We introduce six variants of biased random-key genetic algorithms for this problem. Three of them use a novel initialization technique that makes use of solutions of intermediate linear programming relaxations of an exact mixed integer-linear programming model as initial chromosomes of the population. An experimental evaluation compares the effectiveness of the proposed algorithms with the standard mixed linear integer programming formulation, a specialized exact algorithm, and the best-performing heuristics proposed for this problem. The proposed algorithms are competitive and offer strong results, mainly for large-scale auctions.
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Response surface methodology based on Box-Behnken (BBD) design was successfully applied to the optimization in the operating conditions of the electrochemical oxidation of sanitary landfill leachate aimed for making this method feasible for scale up. Landfill leachate was treated in continuous batch-recirculation system, where a dimensional stable anode (DSA(©)) coated with Ti/TiO2 and RuO2 film oxide were used. The effects of three variables, current density (milliampere per square centimeter), time of treatment (minutes), and supporting electrolyte dosage (moles per liter) upon the total organic carbon removal were evaluated. Optimized conditions were obtained for the highest desirability at 244.11 mA/cm(2), 41.78 min, and 0.07 mol/L of NaCl and 242.84 mA/cm(2), 37.07 min, and 0.07 mol/L of Na2SO4. Under the optimal conditions, 54.99 % of chemical oxygen demand (COD) and 71.07 ammonia nitrogen (NH3-N) removal was achieved with NaCl and 45.50 of COD and 62.13 NH3-N with Na2SO4. A new kinetic model predicted obtained from the relation between BBD and the kinetic model was suggested.
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We reported here for the first time that triboelectric charges on PET sheets can be used to seal and control the flow rate in paper-based devices. The proposed method exhibits simplicity and low cost, provides reversible sealing and minimizes the effect of sample evaporation.
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The aim of this present study was to investigate on the effects of concurrent training with blood flow restriction (BFR-CT) and concurrent training (CT) on the aerobic fitness, muscle mass and muscle strength in a cohort of older individuals. 25 healthy older adults (64.7±4.1 years; 69.33±10.8 kg; 1.6±0.1 m) were randomly assigned to experimental groups: CT (n=8, endurance training (ET), 2 days/week for 30-40 min, 50-80% VO2peak and RT, 2 days/week, leg press with 4 sets of 10 reps at 70-80% of 1-RM with 60 s rest), BFR-CT (n=10, ET, similar to CT, but resistance training with blood flow restriction: 2 days/week, leg press with 1 set of 30 and 3 sets of 15 reps at 20-30% 1-RM with 60 s rest) or control group (n=7). Quadriceps cross-sectional area (CSAq), 1-RM and VO2peak were assessed pre- and post-examination (12 wk). The CT and BFR-CT showed similar increases in CSAq post-test (7.3%, P<0.001; 7.6%, P<0.0001, respectively), 1-RM (38.1%, P<0.001; 35.4%, P=0.001, respectively) and VO2peak (9.5%, P=0.04; 10.3%, P=0.02, respectively). The BFR-CT promotes similar neuromuscular and cardiorespiratory adaptations as CT.
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Nitric oxide (NO)-mediated vasodilation plays a key role in gastric mucosal defense, and NO-donor drugs may protect against diseases associated with gastric mucosal blood flow (GMBF) deficiencies. In this study, we used the ex vivo gastric chamber method and Laser Doppler Flowmetry to characterize the effects of luminal aqueous NO-donor drug S-nitroso-N-acetylcysteine (SNAC) solution administration compared to aqueous NaNO2 and NaNO3 solutions (pH 7.4) on GMBF in Sprague-Dawley rats. SNAC solutions (600 μM and 12 mM) led to a rapid threefold increase in GMBF, which was maintained during the incubation of the solutions with the gastric mucosa, while NaNO2 or NaNO3 solutions (12 mM) did not affect GMBF. SNAC solutions (600 μM and 12 mM) spontaneously released NO at 37 °C at a constant rate of 0.3 or 14 nmol·mL-1·min-1, respectively, while NaNO2 (12 mM) released NO at a rate of 0.06 nmol·mL-1·min-1 and NaNO3 (12 mM) did not release NO. These results suggest that the SNAC-induced GMBF increase is due to their higher rates of spontaneous NO release compared to equimolar NaNO2 solutions. Taken together, our data indicate that oral SNAC administration is a potential approach for gastric acid-peptic disorder prevention and treatment.
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A flow injection method for the quantitative analysis of ketoconazole in tablets, based on the reaction with iron (III) ions, is presented. Ketoconazole forms a red complex with iron ions in an acid medium, with maximum absorbance at 495 nm. The detection limit was estimated to be 1×10--4 mol L-1; the quantitation limit is about 3×10--4 mol L-1 and approximately 30 determinations can be performed in an hour. The results were compared with those obtained with a reference HPLC method. Statistical comparisons were done using the Student's t procedure and the F test. Complete agreement was found at the 0.95 significance level between the proposed flow injection and the HPLC procedures. The two methods present similar precision, i.e., for HPLC the mean relative standard deviation was ca. 1.2% and for FIA ca. 1.6%.
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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FUNDAMENTOS: O tratamento da hanseníase é definido pela classificação de pacientes em paucibacilares (PB) e multibacilares (MB). A OMS (Organização Mundial de Saúde) classifica os doentes de acordo com o número de lesões, mas Ridley-Jopling (R&J) utiliza também exames complementares, porém é de difícil utilização fora dos serviços de referência. Em 2003 foi desenvolvido um teste denominado ML-Flow, uma alternativa à sorologia por ELISA para auxiliar na classificação de pacientes em PB e MB e auxiliar na decisão terapêutica. OBJETIVOS: Observar a concordância entre o teste de ML-Flow e baciloscopia de linfa, exame já consagrado para detecção de MB. Analisar a utilidade do teste de ML-Flow em campo. MATERIAL E MÉTODOS: Estudo retrospectivo avaliando prontuário de 55 pacientes virgens de tratamento, diagnosticados como PB ou MB por R&J. Submetidos à baciloscopia e ao teste de ML-Flow. RESULTADOS: Nos MB, a baciloscopia foi positiva em 80% dos casos, o ML-flow foi positivo em 82,5%. Entre os PB, o ML-Flow foi positivo em 37,5% e a baciloscopia do esfregaço foi negativa em 100% dos casos. A concordância entre os resultados da baciloscopia do esfregaço e ML-Flow foi de 87,5%, kappa=0,59, p<0,001. CONCLUSÃO: Nenhum teste laboratorial é 100% sensível e específico para a correta classificação de todas as formas de hanseníase. O ML-Flow é um teste rápido, de fácil manuseio em campo, menos invasivo que a baciloscopia podendo ser útil para auxiliar na decisão terapêutica em locais de difícil acesso a serviços de referência.