996 resultados para Differential forms.


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"UIUL-ENG 78 1730."

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Miscibility and phase separation in the blends of phenolphthalein poly(aryl ether ketone) (PPAEK) and poly(ethylene oxide) (PEO) were investigated by means of differential scanning calorimetry (DSC). The PPAEK/PEO blends prepared by solution casting from N,N-dimethylformamide (DMF) displayed single composition-dependent glass transition temperatures (T-g), intermediate between those of the pure components, suggesting that the blend system is miscible in the amorphous state at all compositions. All the blends underwent phase separation at higher temperatures and the system exhibited a lower critical solution temperature (LCST) behavior. A step-heating thermal analysis was designed to determine the phase boundaries with DSC. The significant changes in the thermal properties of blends were utilized to judge the mixing status for the blends and the phase diagram was thus established. (C) 2004 Elsevier B.V. All rights reserved.

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A lab-scale sequencing batch reactor was operated with alternating anoxic/aerobic conditions for nitrogen removal. Flocs and granules co-existed in the same reactor, with distinct aggregate structure and size, for over 180 days of reactor operation' Process data showed complete nitrogen removal, with temporary nitrite accumulation before full depletion of ammonia in the aerobic phase. Microbial quantification of the biomass by fluorescence in situ hybridisation showed that granules contained most of the nitrite-oxidising bacteria (NOB) whereas the ammonium-oxidising bacteria (AOB) seemed to be more abundant in the flocs. This was supported by microsensor measurements, which showed a higher potential of NO2- uptake than NH4 uptake in the granules. The segregation is possibly linked to the different growth rates of the two types of nitrifiers and the reactor operational conditions, which produced different sludge retention time for flocs and granules. The apparent physical separation of AOB and NOB in two growth forms could potentially affect mass transfer of NO2- from AOB to NOB, but the data presented here shows that it did not impact negatively on the overall nitrogen removal. (c) 2006 Elsevier Inc. All rights reserved.

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Hemispheric differences in the learning and generalization of pattern categories were explored in two experiments involving sixteen patients with unilateral posterior, cerebral lesions in the left (LH) or right (RH) hemisphere. In each experiment participants were first trained to criterion in a supervised learning paradigm to categorize a set of patterns that either consisted of simple geometric forms (Experiment 1) or unfamiliar grey-level images (Experiment 2). They were then tested for their ability to generalize acquired categorical knowledge to contrast-reversed versions of the learning patterns. The results showed that RH lesions impeded category learning of unfamiliar grey-level images more severely than LH lesions, whereas this relationship appeared reversed for categories defined by simple geometric forms. With regard to generalization to contrast reversal, categorization performance of LH and RH patients was unaffected in the case of simple geometric forms. However, generalization to of contrast-reversed grey-level images distinctly deteriorated for patients with LH lesions relative to those with RH lesions, with the latter (but not the former) being consistently unable to identify the pattern manipulation. These findings suggest a differential use of contrast information in the representation of pattern categories in the two hemispheres. Such specialization appears in line with previous distinctions between a predominantly lefthemispheric, abstract-analytical and a righthemispheric, specific-holistic representation of object categories, and their prediction of a mandatory representation of contrast polarity in the RH. Some implications for the well-established dissociation of visual disorders for the recognition of faces and letters are discussed.

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Differential evolution is an optimisation technique that has been successfully employed in various applications. In this paper, we apply differential evolution to the problem of extracting the optimal colours of a colour map for quantised images. The choice of entries in the colour map is crucial for the resulting image quality as it forms a look-up table that is used for all pixels in the image. We show that differential evolution can be effectively employed as a method for deriving the entries in the map. In order to optimise the image quality, our differential evolution approach is combined with a local search method that is guaranteed to find the local optimal colour map. This hybrid approach is shown to outperform various commonly used colour quantisation algorithms on a set of standard images. Copyright © 2010 Inderscience Enterprises Ltd.

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Urban growth models have been used for decades to forecast urban development in metropolitan areas. Since the 1990s cellular automata, with simple computational rules and an explicitly spatial architecture, have been heavily utilized in this endeavor. One such cellular-automata-based model, SLEUTH, has been successfully applied around the world to better understand and forecast not only urban growth but also other forms of land-use and land-cover change, but like other models must be fed important information about which particular lands in the modeled area are available for development. Some of these lands are in categories for the purpose of excluding urban growth that are difficult to quantify since their function is dictated by policy. One such category includes voluntary differential assessment programs, whereby farmers agree not to develop their lands in exchange for significant tax breaks. Since they are voluntary, today’s excluded lands may be available for development at some point in the future. Mapping the shifting mosaic of parcels that are enrolled in such programs allows this information to be used in modeling and forecasting. In this study, we added information about California’s Williamson Act into SLEUTH’s excluded layer for Tulare County. Assumptions about the voluntary differential assessments were used to create a sophisticated excluded layer that was fed into SLEUTH’s urban growth forecasting routine. The results demonstrate not only a successful execution of this method but also yielded high goodness-of-fit metrics for both the calibration of enrollment termination as well as the urban growth modeling itself.