61 resultados para Mathematical Programs


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A pseudo 2-D mathematical model has been developed to simulate a cupola with one row and two rows of tuyere. The simulation results predicted higher spout temperature and combustion ratio for cupola with two rows of tuyere compared to that with one row. Further, the model has been used to study the effect of the distance of separation between the two rows of tuyere on cupola performance. The computed results shows that the spout temperature increases with tuyere level separation and attains the maximum at an optimum distance of separation between two rows of tuyere. Above the optimum, the spout temperature starts decreasing. The exit gas temperature and combustion ratio increases monotonously with the increase in tuyere level separation. These results agree well with the reported experimental observations. The mechanism behind the improved cupola performance with two rows of tuyere has been deduced from the computed temperature and composition profiles inside the cupola.

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A three-dimensional mathematical model has been developed to simulate the gas flow, composition, and temperature profiles inside a cupola. Comparison of the model with the reported experimental data shows the presence of a zone with low combustion rate at the tuyere level. For a 24 in (610 mm) cupola with four rows of tuyeres, the combustion zones from each tuyere overlap each other, forming an overall combustion zone of cylindrical shape of height similar to 0.2 m. Using the model, it is found that the spout temperature initially increases with increasing blast velocity and attains a maximum. Further increase in blast velocity does not change the spout temperature. This suggests that smaller size tuyeres and higher permeability of the bed can give superior cupola performance. (C) 1997 The Institute of Materials.

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A dynamic model of the COREX melter gasifier is developed to study the transient behavior of the furnace. The effect of pulse disturbance and step disturbance on the process performance has been studied. This study shows that the effect of pulse disturbance decays asymptotically. The step change brings the system to a new steady state after a delay of about 5 hours. The dynamic behavior of the melter gasifier with respect to a shutdown/blow-on condition and the effect of tapping are also studied. The results show that the time response of the melter gasifier is much less than that of a blast furnace.

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The COREX melter gasifier is a countercurrent reactor to produce liquid iron. Directly reduced iron (DRI), noncoking coal, and other additives are charged to the melter gasifier at their respective temperatures, and O-2 is blown through the tuyeres. Functionally, a melter gasifier is divided into three zones: a moving bed, fluidized bed, and free board. A model has been developed for the moving bed, where the tuyere region is two-dimensional (2-D) and the rest is one-dimensional (1-D). It is based on multiphase conservation of mass, momentum, and heat. The fluidized bed has been treated as 1-D. Partial equilibrium is calculated for the free board. The calculated temperature of the hot metal, the top gas, and the chemistry of the top gas agree with the reported plant data. The model has been used to study the effects of bed height, injection of impure O-2, coal chemistry, and reactivity on the process performance.

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MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.

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Fusion of multiple intrusion detection systems results in a more reliable and accurate detection for a wider class of intrusions. The paper presented here introduces the mathematical basis for sensor fusion and provides enough support for the acceptability of sensor fusion in performance enhancement of intrusion detection systems. The sensor fusion system is characterized and modeled with no knowledge of the intrusion detection systems and the intrusion detection data. The theoretical analysis is supported with an experimental illustration with three of the available intrusion detection systems using the DARPA 1999 evaluation data set.

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Advertisements(Ads) are the main revenue earner for Television (TV) broadcasters. As TV reaches a large audience, it acts as the best media for advertisements of products and services. With the emergence of digital TV, it is important for the broadcasters to provide an intelligent service according to the various dimensions like program features, ad features, viewers’ interest and sponsors’ preference. We present an automatic ad recommendation algorithm that selects a set of ads by considering these dimensions and semantically match them with programs. Features of the ad video are captured interms of annotations and they are grouped into number of predefined semantic categories by using a categorization technique. Fuzzy categorical data clustering technique is applied on categorized data for selecting better suited ads for a particular program. Since the same ad can be recommended for more than one program depending upon multiple parameters, fuzzy clustering acts as the best suited method for ad recommendation. The relative fuzzy score called “degree of membership” calculated for each ad indicates the membership of a particular ad to different program clusters. Subjective evaluation of the algorithm is done by 10 different people and rated with a high success score.

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Cardiac arrhythmias such as ventricular tachycardia (VT) or ventricular fibrillation (VF) are the leading cause of death in the industrialised world. There is a growing consensus that these arrhythmias arise because of the formation of spiral waves of electrical activation in cardiac tissue; unbroken spiral waves are associated with VT and broken ones with VF. Several experimental studies have been carried out to determine the effects of inhomogeneities in cardiac tissue on such arrhythmias. We give a brief overview of such experiments, and then an introduction to partial-differential-equation models for ventricular tissue. We show how different types of inhomogeneities can be included in such models, and then discuss various numerical studies, including our own, of the effects of these inhomogeneities on spiral-wave dynamics. The most remarkable qualitative conclusion of our studies is that the spiral-wave dynamics in such systems depends very sensitively on the positions of these inhomogeneities.

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Innate immunity recognizes and resists various pathogens; however, the mechanisms regulating pathogen versus non-pathogen discrimination are still imprecisely understood. Here, we demonstrate that pathogen-specific activation of TLR2 upon infection with Mycobacterium bovis BCG, in comparison with other pathogenic microbes, including Salmonella typhimurium and Staphylococcus aureus, programs macrophages for robust up-regulation of signaling cohorts of Wnt-beta-catenin signaling. Signaling perturbations or genetic approaches suggest that infection-mediated stimulation of Wnt-beta-catenin is vital for activation of Notch1 signaling. Interestingly, inducible NOS (iNOS) activity is pivotal for TLR2-mediated activation of Wnt-beta-catenin signaling as iNOS(-/-) mice demonstrated compromised ability to trigger activation of Wnt-beta-catenin signaling as well as Notch1-mediated cellular responses. Intriguingly, TLR2-driven integration of iNOS/NO, Wnt-beta-catenin, and Notch1 signaling contributes to its capacity to regulate the battery of genes associated with T(Reg) cell lineage commitment. These findings reveal a role for differential stimulation of TLR2 in deciding the strength of Wnt-beta-catenin signaling, which together with signals from Notch1 contributes toward the modulation of a defined set of effector functions in macrophages and thus establishes a conceptual framework for the development of novel therapeutics.

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Mathematical models have provided key insights into the pathogenesis of hepatitis C virus (HCV) in vivo, suggested predominant mechanism(s) of drug action, explained confounding patterns of viral load changes in HCV infected patients undergoing therapy, and presented a framework for therapy optimization. In this article, I present an overview of the major advances in the mathematical modeling of HCV dynamics.

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Interaction between the hepatitis C virus (HCV) envelope protein E2 and the host receptor CD81 is essential for HCV entry into target cells. The number of E2-CD81 complexes necessary for HCV entry has remained difficult to estimate experimentally. Using the recently developed cell culture systems that allow persistent HCV infection in vitro, the dependence of HCV entry and kinetics on CD81 expression has been measured. We reasoned that analysis of the latter experiments using a mathematical model of viral kinetics may yield estimates of the number of E2-CD81 complexes necessary for HCV entry. Here, we constructed a mathematical model of HCV viral kinetics in vitro, in which we accounted explicitly for the dependence of HCV entry on CD81 expression. Model predictions of viral kinetics are in quantitative agreement with experimental observations. Specifically, our model predicts triphasic viral kinetics in vitro, where the first phase is characterized by cell proliferation, the second by the infection of susceptible cells and the third by the growth of cells refractory to infection. By fitting model predictions to the above data, we were able to estimate the threshold number of E2-CD81 complexes necessary for HCV entry into human hepatoma-derived cells. We found that depending on the E2-CD81 binding affinity, between 1 and 13 E2-CD81 complexes are necessary for HCV entry. With this estimate, our model captured data from independent experiments that employed different HCV clones and cells with distinct CD81 expression levels, indicating that the estimate is robust. Our study thus quantifies the molecular requirements of HCV entry and suggests guidelines for intervention strategies that target the E2-CD81 interaction. Further, our model presents a framework for quantitative analyses of cell culture studies now extensively employed to investigate HCV infection.

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We present a comprehensive numerical study of spiral-and scroll-wave dynamics in a state-of-the-art mathematical model for human ventricular tissue with fiber rotation, transmural heterogeneity, myocytes, and fibroblasts. Our mathematical model introduces fibroblasts randomly, to mimic diffuse fibrosis, in the ten Tusscher-Noble-Noble-Panfilov (TNNP) model for human ventricular tissue; the passive fibroblasts in our model do not exhibit an action potential in the absence of coupling with myocytes; and we allow for a coupling between nearby myocytes and fibroblasts. Our study of a single myocyte-fibroblast (MF) composite, with a single myocyte coupled to N-f fibroblasts via a gap-junctional conductance G(gap), reveals five qualitatively different responses for this composite. Our investigations of two-dimensional domains with a random distribution of fibroblasts in a myocyte background reveal that, as the percentage P-f of fibroblasts increases, the conduction velocity of a plane wave decreases until there is conduction failure. If we consider spiral-wave dynamics in such a medium we find, in two dimensions, a variety of nonequilibrium states, temporally periodic, quasiperiodic, chaotic, and quiescent, and an intricate sequence of transitions between them; we also study the analogous sequence of transitions for three-dimensional scroll waves in a three-dimensional version of our mathematical model that includes both fiber rotation and transmural heterogeneity. We thus elucidate random-fibrosis-induced nonequilibrium transitions, which lead to conduction block for spiral waves in two dimensions and scroll waves in three dimensions. We explore possible experimental implications of our mathematical and numerical studies for plane-, spiral-, and scroll-wave dynamics in cardiac tissue with fibrosis.

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Dynamic Voltage and Frequency Scaling (DVFS) is a very effective tool for designing trade-offs between energy and performance. In this paper, we use a formal Petri net based program performance model that directly captures both the application and system properties, to find energy efficient DVFS settings for CMP systems, that satisfy a given performance constraint, for SPMD multithreaded programs. Experimental evaluation shows that we achieve significant energy savings, while meeting the performance constraints.

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Dynamic Voltage and Frequency Scaling (DVFS) offers a huge potential for designing trade-offs involving energy, power, temperature and performance of computing systems. In this paper, we evaluate three different DVFS schemes - our enhancement of a Petri net performance model based DVFS method for sequential programs to stream programs, a simple profile based Linear Scaling method, and an existing hardware based DVFS method for multithreaded applications - using multithreaded stream applications, in a full system Chip Multiprocessor (CMP) simulator. From our evaluation, we find that the software based methods achieve significant Energy/Throughput2(ET−2) improvements. The hardware based scheme degrades performance heavily and suffers ET−2 loss. Our results indicate that the simple profile based scheme achieves the benefits of the complex Petri net based scheme for stream programs, and present a strong case for the need for independent voltage/frequency control for different cores of CMPs, which is lacking in most of the state-of-the-art CMPs. This is in contrast to the conclusions of a recent evaluation of per-core DVFS schemes for multithreaded applications for CMPs.