5 resultados para Termination

em Digital Commons - Michigan Tech


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Two volcanic debris avalanche deposits (VDADs), both attributed to sector collapse at Volcán Barú, Panama, have been identified after an investigation of deposits that covered more than a thousand square kilometers. The younger Barriles Deposit is constrained by two radiocarbon ages that are ~9 ka; the older Caisán Deposit is at or beyond the radiocarbon range, >43,500 ybp. The total runout length of the Caisán Deposit was ~50 km and it covers 1190 km2. The Barriles Deposit extended to about 45 km and covered an area of 966 km2, overlapping most of the Caisán. The VDADs are blanketed by pyroclastic deposits and contain a predominance of andesitic material likely representing volcanic dome rock which accumulated above the active vent at Barú before collapsing. Despite heavy vegetation in the field area, over 4000 individual hummocks were digitized from aerial photography. Statistical analysis of hummock locations and geometries depict flow patterns of highly- fragmented material reflecting the effects of underlying topography and also help to define the limit of Barriles’ shorter termination. Barriles and Caisán are primarily unconfined, subaerial volcanic deposits that are among the world’s most voluminous. Calculated through two different geospatial processes, thickness values from field measurements and inferences yield volumes >30 km23 for both deposits. VDADs of comparable scale come from Mount Shasta, USA; Socompa, Chile/Argentina; and Shiveluch, Russia. Currently, the modern edifice is 200-400m lower than the pre-collapse Barriles and Caisán summits and only 16-25% of the former edifice has been replaced since the last failure.

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Intraneural Ganglion Cyst is a 200 year old mystery related to nerve injury which is yet to be solved. Current treatments for the above problem are relatively simple procedures related to removal of cystic contents from the nerve. However, these treatments may result into neuropathic pain and recurrence of the cyst. The articular theory proposed by Spinner et al., (Spinner et al. 2003) takes into consideration the neurological deficit in Common Peroneal Nerve (CPN) branch of the sciatic nerve and affirms that in addition to the above treatments, ligation of articular branch results into foolproof eradication of the deficit. Mechanical Modeling of the Affected Nerve Cross Section will reinforce the articular theory (Spinner et al. 2003). As the cyst propagates, it compresses the neighboring fascicles and the nerve cross section appears like a signet ring. Hence, in order to mechanically model the affected nerve cross section; computational methods capable of modeling excessively large deformations are required. Traditional FEM produces distorted elements while modeling such deformations, resulting into inaccuracies and premature termination of the analysis. The methods described in this Master’s Thesis are effective enough to be able to simulate such deformations. The results obtained from the model adequately resemble the MRI image obtained at the same location and shows an appearance of a signet ring. This Master’s Thesis describes the neurological deficit in brief followed by detail explanation of the advanced computational methods used to simulate this problem. Finally, qualitative results show the resemblance of mechanical model to MRI images of the Nerve Cross Section at the same location validating the capability of these methods to study this neurological deficit.

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Rice (Oryza sativa L.) is an important cash crop in Honduras because of the rice lobby’s size, willingness to protest, and ability to negotiate favorable price guarantees on a year-to-year basis. Despite the availability of inexpensive irrigation in the study area in Flores, La Villa de San Antonio, Comayagua, the rice farmers do not cultivate the crop using prescribed methods such as land leveling, puddling, and water conservation structures. Soil moisture (Volumetric Water Content) was measured using a soil moisture probe after the termination of the first irrigation within the tillering/vegetative, panicle emergence/flowering, post-flowering/pre-maturation and maturation stages. Yield data was obtained by harvesting on 1 m2 plots in each soil moisture testing site. Data was analyzed to find the influence of toposequential position along transects, slope, soil moisture, and farmers on yields. The results showed that toposequential position was more important than slope and soil moisture on yields. Soil moisture was not a significant predictor of rice yields. Irrigation politics, precipitation, and land tenure were proposed as the major explanatory variables for this result.

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Fuzzy community detection is to identify fuzzy communities in a network, which are groups of vertices in the network such that the membership of a vertex in one community is in [0,1] and that the sum of memberships of vertices in all communities equals to 1. Fuzzy communities are pervasive in social networks, but only a few works have been done for fuzzy community detection. Recently, a one-step forward extension of Newman’s Modularity, the most popular quality function for disjoint community detection, results into the Generalized Modularity (GM) that demonstrates good performance in finding well-known fuzzy communities. Thus, GMis chosen as the quality function in our research. We first propose a generalized fuzzy t-norm modularity to investigate the effect of different fuzzy intersection operators on fuzzy community detection, since the introduction of a fuzzy intersection operation is made feasible by GM. The experimental results show that the Yager operator with a proper parameter value performs better than the product operator in revealing community structure. Then, we focus on how to find optimal fuzzy communities in a network by directly maximizing GM, which we call it Fuzzy Modularity Maximization (FMM) problem. The effort on FMM problem results into the major contribution of this thesis, an efficient and effective GM-based fuzzy community detection method that could automatically discover a fuzzy partition of a network when it is appropriate, which is much better than fuzzy partitions found by existing fuzzy community detection methods, and a crisp partition of a network when appropriate, which is competitive with partitions resulted from the best disjoint community detections up to now. We address FMM problem by iteratively solving a sub-problem called One-Step Modularity Maximization (OSMM). We present two approaches for solving this iterative procedure: a tree-based global optimizer called Find Best Leaf Node (FBLN) and a heuristic-based local optimizer. The OSMM problem is based on a simplified quadratic knapsack problem that can be solved in linear time; thus, a solution of OSMM can be found in linear time. Since the OSMM algorithm is called within FBLN recursively and the structure of the search tree is non-deterministic, we can see that the FMM/FBLN algorithm runs in a time complexity of at least O (n2). So, we also propose several highly efficient and very effective heuristic algorithms namely FMM/H algorithms. We compared our proposed FMM/H algorithms with two state-of-the-art community detection methods, modified MULTICUT Spectral Fuzzy c-Means (MSFCM) and Genetic Algorithm with a Local Search strategy (GALS), on 10 real-world data sets. The experimental results suggest that the H2 variant of FMM/H is the best performing version. The H2 algorithm is very competitive with GALS in producing maximum modularity partitions and performs much better than MSFCM. On all the 10 data sets, H2 is also 2-3 orders of magnitude faster than GALS. Furthermore, by adopting a simply modified version of the H2 algorithm as a mutation operator, we designed a genetic algorithm for fuzzy community detection, namely GAFCD, where elite selection and early termination are applied. The crossover operator is designed to make GAFCD converge fast and to enhance GAFCD’s ability of jumping out of local minimums. Experimental results on all the data sets show that GAFCD uncovers better community structure than GALS.

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This dissertation established a standard foam index: the absolute foam index test. This test characterized a wide range of coal fly ash by the absolute volume of air-entraining admixture (AEA) necessary to produce a 15-second metastable foam in a coal fly ash-cement slurry in a specified time. The absolute foam index test was used to characterize fly ash samples having loss on ignition (LOI) values that ranged from 0.17 to 23.3 %wt. The absolute foam index characterized the fly ash samples by absolute volume of AEA, defined as the amount of undiluted AEA solution added to obtain a 15-minute endpoint signified by 15-second metastable foam. Results were compared from several foam index test time trials that used different initial test concentrations to reach termination at selected times. Based on the coefficient of variation (CV), a 15-minute endpoint, with limits of 12 to 18 minutes was chosen. Various initial test concentrations were used to accomplish consistent contact times and concentration gradients for the 15-minute test endpoint for the fly ash samples. A set of four standard concentrations for the absolute foam index test were defined by regression analyses and a procedure simplifying the test process. The set of standard concentrations for the absolute foam index test was determined by analyzing experimental results of 80 tests on coal fly ashes with loss on ignition (LOI) values ranging from 0.39 to 23.3 wt.%. A regression analysis informed selection of four concentrations (2, 6, 10, and 15 vol.% AEA) that are expected to accommodate fly ashes with 0.39 to 23.3 wt.% LOI, depending on the AEA type. Higher concentrations should be used for high-LOI fly ash when necessary. A procedure developed using these standard concentrations is expected to require only 1-3 trials to meet specified endpoint criteria for most fly ashes. The AEA solution concentration that achieved the metastable foam in the foam index test was compared to the AEA equilibrium concentration obtained from the direct adsorption isotherm test with the same fly ash. The results showed that the AEA concentration that satisfied the absolute foam index test was much less than the equilibrium concentration. This indicated that the absolute foam index test was not at or near equilibrium. Rather, it was a dynamic test where the time of the test played an important role in the results. Even though the absolute foam index was not an equilibrium condition, a correlation was made between the absolute foam index and adsorption isotherms. Equilibrium isotherm equations obtained from direct isotherm tests were used to calculate the equilibrium concentrations and capacities of fly ash from 0.17 to 10.5% LOI. The results showed that the calculated fly ash capacity was much less than capacities obtained from isotherm tests that were conducted with higher initial concentrations. This indicated that the absolute foam index was not equilibrium. Rather, the test is dynamic where the time of the test played an important role in the results. Even though the absolute foam index was not an equilibrium condition, a correlation was made between the absolute foam index and adsorption isotherms for fly ash of 0.17 to 10.5% LOI. Several batches of mortars were mixed for the same fly ash type increasing only the AEA concentration (dosage) in each subsequent batch. Mortar air test results for each batch showed for each increase in AEA concentration, air contents increased until a point where the next increase in AEA concentration resulted in no increase in air content. This was maximum air content that could be achieved by the particular mortar system; the system reached its air capacity at the saturation limit. This concentration of AEA was compared to the critical micelle concentration (CMC) for the AEA and the absolute foam index.