997 resultados para Variational Iteration Method
Resumo:
A method is proposed for the determination of the moisture content of aromatic plants. This method is based on the co-distillation of the starting material in a modified Clevenger apparatus with four organic solvents (toluene, cyclohexane, dichloromethane and carbon tetrachloride). The results were compared with those obtained by oven drying at 105 ºC and steam distillation of the essential oil. The efficiencies of the methods were shown to be equivalent. The solvent distillation method was more practical, especially with respect to operating time (2 h).
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Chromium(III) at the ng L-1 level was extracted using partially silylated MCM-41 modified by a tetraazamacrocyclic compound (TAMC) and determined by inductively coupled plasma optical emision spectrometry (ICP OES). The extraction time and efficiency, pH and flow rate, type and minimum amount of stripping acid, and break- through volume were investigated. The method's enrichment factor and detection limit are 300 and 45.5 pg mL-1, respectively. The maximum capacity of the 10 mg of modified silylated MCM-41 was found to be 400.5±4.7 µg for Cr(III). The method was applied to the determination of Cr(III) and Cr(VI) in the wastewater of the chromium electroplating industry and in environmental and biological samples (black tea, hot and black pepper).
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In image processing, segmentation algorithms constitute one of the main focuses of research. In this paper, new image segmentation algorithms based on a hard version of the information bottleneck method are presented. The objective of this method is to extract a compact representation of a variable, considered the input, with minimal loss of mutual information with respect to another variable, considered the output. First, we introduce a split-and-merge algorithm based on the definition of an information channel between a set of regions (input) of the image and the intensity histogram bins (output). From this channel, the maximization of the mutual information gain is used to optimize the image partitioning. Then, the merging process of the regions obtained in the previous phase is carried out by minimizing the loss of mutual information. From the inversion of the above channel, we also present a new histogram clustering algorithm based on the minimization of the mutual information loss, where now the input variable represents the histogram bins and the output is given by the set of regions obtained from the above split-and-merge algorithm. Finally, we introduce two new clustering algorithms which show how the information bottleneck method can be applied to the registration channel obtained when two multimodal images are correctly aligned. Different experiments on 2-D and 3-D images show the behavior of the proposed algorithms
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This thesis was produced for the Technology Marketing unit at the Nokia Research Center. Technology marketing was a new function at Nokia Research Center, and needed an established framework with the capacity to take into account multiple aspects for measuring the team performance. Technology marketing functions had existed in other parts of Nokia, yet no single method had been agreed upon for measuring their performance. The purpose of this study was to develop a performance measurement system for Nokia Research Center Technology Marketing. The target was that Nokia Research Center Technology Marketing had a framework for separate metrics; including benchmarking for starting level and target values in the future planning (numeric values were kept confidential within the company). As a result of this research, the Balanced Scorecard model of Kaplan and Norton, was chosen for the performance measurement system for Nokia Research Center Technology Marketing. This research selected the indicators, which were utilized in the chosen performance measurement system. Furthermore, performance measurement system was defined to guide the Head of Marketing in managing Nokia Research Center Technology Marketing team. During the research process the team mission, vision, strategy and critical success factors were outlined.
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Quickremovalofbiosolidsinaquaculturefacilities,andspeciallyinrecirculatingaquaculturesystems(RAS),isoneofthemostimportantstepinwastemanagement.Sedimentationdynamicsofbiosolidsinanaquaculturetankwilldeterminetheiraccumulationatthebottomofthetank.
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Identification of clouds from satellite images is now a routine task. Observation of clouds from the ground, however, is still needed to acquire a complete description of cloud conditions. Among the standard meteorologicalvariables, solar radiation is the most affected by cloud cover. In this note, a method for using global and diffuse solar radiation data to classify sky conditions into several classes is suggested. A classical maximum-likelihood method is applied for clustering data. The method is applied to a series of four years of solar radiation data and human cloud observations at a site in Catalonia, Spain. With these data, the accuracy of the solar radiation method as compared with human observations is 45% when nine classes of sky conditions are to be distinguished, and it grows significantly to almost 60% when samples are classified in only five different classes. Most errors are explained by limitations in the database; therefore, further work is under way with a more suitable database
Resumo:
The aim of our study was to assess the diagnostic usefulness of the gray level parameters to distinguish osteolytic lesions using radiological images. Materials and Methods: A retrospective study was carried out. A total of 76 skeletal radiographs of osteolytic metastases and 67 radiographs of multiple myeloma were used. The cases were classified into nonflat (MM1 and OL1) and flat bones (MM2 and OL2). These radiological images were analyzed by using a computerized method. The parameters calculated were mean, standard deviation, and coefficient of variation (MGL, SDGL, and CVGL) based on gray level histogram analysis of a region-of-interest.Diagnostic utility was quantified bymeasurement of parameters on osteolyticmetastases andmultiplemyeloma, yielding quantification of area under the receiver operating characteristic (ROC) curve (AUC). Results: Flat bone groups (MM2 and OL2) showed significant differences in mean values of MGL ( = 0.048) and SDGL ( = 0.003). Their corresponding values of AUC were 0.758 for MGL and 0.883 for SDGL in flat bones. In nonflat bones these gray level parameters do not show diagnostic ability. Conclusion: The gray level parametersMGL and SDGL show a good discriminatory diagnostic ability to distinguish between multiple myeloma and lytic metastases in flat bones.