953 resultados para dry method processing


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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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A UV-spectrophotometric method is described for the determination of lansoprazole (LAN). The method is based on the measurement of the absorbance of LAN solution in acetonitrile at 281 nm. The system obeyed Beer's law over the concentration range of 1.25-25.0 µg/mL. The degradation behavior of LAN was investigated under dry heat treatment, UV-degradation, acid hydrolysis, alkali hydrolysis and oxidation; and found to degrade extensively under acid hydrolysis, alkali hydrolysis and oxidation. The method was applied to the determination of LAN in capsule and the results were statistically compared with those of the reference method by applying Student's t-test and F-test.

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Some beetle species can have devastating economic impacts on forest and nursery industries. A recent example is Anophophora glabripennis, a species of beetle known in the United States as the ''Asian Longhorrned beetle'', which has damaged many American forests, and is a threat which can unintentionally reach south American countries, including Brazil. This work presents a new method based on X-ray computerized tomography (CT) and image processing for beetle injury detection in forests. Its results show a set of images with correct identification of the location of beetles in living trees as well as damage evaluation with time.

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In order to produce useful knowledge to the initiatives of protection and management of forest fragments, more specifically for tropical dry forests which suffer with frequent anthropic activities, and due to the lack of specific studies, this article aimed describe the structure and the floristic similarity among three areas of dry forest with different management histories. The study was developed in Capitão Enéas municipality, Northern Minas Gerais, Brazil, where three fragments were evaluated, being one in regeneration for 30 years, another submitted to occasional fire and the third with selective cut in small scale. The sampling was developed through the point quarter method considering all the alive phanerophyte individuals with circumference at breast height (CBH) > 15 cm. In the three fragments, 512 individuals, distributed in 60 species, 47 genera, and 23 families were sampled. The most representative families were Fabaceae (26), Anacardiaceae (4), Bignoniaceae (3) and Combretaceae (3). However, fourteen families were represented by only one species. Only eight species were common to all fragments - Myracrodruon urundeuva standed out with 26.9% of all sampled individuals - while a great number of species were exclusive of each fragment. The floristic and structural differences between the fragments are possibly related to the history and intensity of management in each area besides the topography variations and the presence or absence of limestone outcrops. These results show the importance of each fragment, indicating that the loss of anyone would cause negative impacts on the regional flora and consequently to the associated biodiversity.

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Eucalyptus stands in the setting of worldwide forestry due to its adaptability, rapid growth, production of high-quality and low cost of wood pulp fibers. The eucalyptus convetional breeding is impaired mainlly by the long life cycle making the genetic transformation systems an important tool for this purpose. However, this system requires in vitro eficient protocols for plant induction, regeneration and seletion, that allow to obtain transgenic plants from the transformed cell groups. The aim of this work was to evaluate the callus formation and to optimize the leaves and callus genetic transformation protocol by using the Agrobacterium tumefaciens system. Concerning callus formation, two different culture media were evaluated: MS medium supplemented with auxin, cytokinin (M1) and the MS medium with reduced nitrogen concentration and supplemented with auxin, cytokinin coconut water (M2). To establish the leave genetic transformation, those were exposed to agrobiolistics technique (gene gun), to tissue injury, and A. tumesfasciens EHA 105 contening the vetor pCambia 3301 (35S::GUS::NOS), for gene transference and to establish the callus transformation thoses were exposed only to A. tumefasciens. For both experiments, the influence of different infection periods was evaluated. The M2 medium provided the best values for callus sizea and fresh and dry weight. The leaves genetic transformation using the agrobiolistics technique was effective, the gus gene transient expression could be observed. No significant differences were obtained in the infection periods (4, 6 and 8 minutes). The callus genetic transformation with A. tumefaciens also promotend the gus gene transient expression on the callus co-cultiveted for 15 e 30 minutes. The transformed callus was transfered to a regeneration and selection medium and transformed plants were obtained.

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Bacteriorhodopsin (BR) is a photosensitive protein which functions as a light-driven proton pump. Due to its photoactivity, BR could be used in photosensing and information processing which has inspired researchers to study the photoelectric response and the appropriate measurement instrumentation for BR. In this thesis, the measurement instrumentation connected to a dry BR sensor was confirmed to affect the photovoltage response measured by using voltage amplifiers. Changing of the input impedance of the measurement instrumentation was shown to alter a part of the measured photovoltage response. The photocurrent measurements using transimpedance amplifier and the presented electrical equivalent circuit were used to show that the photocurrent measurements have no significant effect on the photoelectric response. The photocurrent was shown to be a derivate of the photovoltage response measured from the dry BR sensor when it was compared to the response measured with a voltage amplifier. This confirmed that another part of the photovoltage response was not affected by the measurement instrumentation. The time-variant behavior of the dry BR sensor was confirmed in both the photocurrent and the photovoltage measurements. This was caused by the fact that the capacitance of the dry BR sensor changes with the excitation light intensity.

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Knowledge of the behaviour of cellulose, hemicelluloses, and lignin during wood and pulp processing is essential for understanding and controlling the processes. Determination of monosaccharide composition gives information about the structural polysaccharide composition of wood material and helps when determining the quality of fibrous products. In addition, monitoring of the acidic degradation products gives information of the extent of degradation of lignin and polysaccharides. This work describes two capillary electrophoretic methods developed for the analysis of monosaccharides and for the determination of aliphatic carboxylic acids from alkaline oxidation solutions of lignin and wood. Capillary electrophoresis (CE), in its many variants is an alternative separation technique to chromatographic methods. In capillary zone electrophoresis (CZE) the fused silica capillary is filled with an electrolyte solution. An applied voltage generates a field across the capillary. The movement of the ions under electric field is based on the charge and hydrodynamic radius of ions. Carbohydrates contain hydroxyl groups that are ionised only in strongly alkaline conditions. After ionisation, the structures are suitable for electrophoretic analysis and identification through either indirect UV detection or electrochemical detection. The current work presents a new capillary zone electrophoretic method, relying on in-capillary reaction and direct UV detection at the wavelength of 270 nm. The method has been used for the simultaneous separation of neutral carbohydrates, including mono- and disaccharides and sugar alcohols. The in-capillary reaction produces negatively charged and UV-absorbing compounds. The optimised method was applied to real samples. The methodology is fast since no other sample preparation, except dilution, is required. A new method for aliphatic carboxylic acids in highly alkaline process liquids was developed. The goal was to develop a method for the simultaneous analysis of the dicarboxylic acids, hydroxy acids and volatile acids that are oxidation and degradation products of lignin and wood polysaccharides. The CZE method was applied to three process cases. First, the fate of lignin under alkaline oxidation conditions was monitored by determining the level of carboxylic acids from process solutions. In the second application, the degradation of spruce wood using alkaline and catalysed alkaline oxidation were compared by determining carboxylic acids from the process solutions. In addition, the effectiveness of membrane filtration and preparative liquid chromatography in the enrichment of hydroxy acids from black liquor was evaluated, by analysing the effluents with capillary electrophoresis.

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In this experiment, methods of total fecal collection (TFC) and internal markers (acid-insoluble ash - AIA, crude fiber - CF, and acid-detergent fiber - ADF) were compared for determination of the coefficients of apparent digestibility (CAD) for dry matter (DM), crude protein (CP), ether extract (EE), nitrogen-free extracts (NFE), and gross energy (GE) of commercial feline dry kibble for ocelots (Leopardus pardalis). Six adult animals, weighing 12.45±1.37 kg, gradually received experimental kibble in their usual diet until the beginning of the experiment and were submitted to an adaptation period ten days prior to the collection period. CAD obtained by TFC, AIA, CF, and ADF were, respectively, 73.7, 76.83, 62.01, and 46.03% for dry matter; 81.9, 84.8, 75.8, and 63.8% for crude protein; 85, 86.7, 78.5, and 69.1% for ether extract; 78.52, 79.55, 69.11, and 53.04% for nitrogen-free extracts; and 80.5, 82.2, 71.4, and 58.4% for gross energy. The AIA method showed to be efficient in determining coefficients of apparent digestibility and may contribute to investigations on the digestibility of diets for wild felines. In comparison to the items of ocelot's usual diet, the kibble used in this paper provided an adequate nutritional supply with reduced daily costs per animal.

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The purpose of the study is to examine and increase knowledge on customer knowledge processing in B2B context from sales perspective. Further objectives include identifying possible inhibiting and enabling factors in each phase of the process. The theoretical framework is based on customer knowledge management literature. The study is a qualitative study, in which the research method utilized is a case study. The empirical part was implemented in a case company by conducting in-depth interviews with the company’s value-selling champions located internationally. Context was maintenance business. Altogether 17 interviews were conducted. The empirical findings indicate that customer knowledge processing has not been clearly defined within the maintenance business line. Main inhibiting factors in acquiring customer knowledge are lack of time and vast amount of customer knowledge received. Enabling factors recognized are good customer relationships and sales representatives’ communication skills. Internal dissemination of knowledge is mainly inhibited by lack of time and restrictions in customer relationship management systems. Enabling factors are composition of the sales team and updated customer knowledge. Inhibiting utilization is lack of goals to utilize the customer knowledge and a low quality of the knowledge. Moreover, customer knowledge is not systematically updated nor analysed. Management of customer knowledge is based on the CRM system. As implications of the study, it is suggested for the case company to define customer knowledge processing in order to support maintenance business process.

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The usage of digital content, such as video clips and images, has increased dramatically during the last decade. Local image features have been applied increasingly in various image and video retrieval applications. This thesis evaluates local features and applies them to image and video processing tasks. The results of the study show that 1) the performance of different local feature detector and descriptor methods vary significantly in object class matching, 2) local features can be applied in image alignment with superior results against the state-of-the-art, 3) the local feature based shot boundary detection method produces promising results, and 4) the local feature based hierarchical video summarization method shows promising new new research direction. In conclusion, this thesis presents the local features as a powerful tool in many applications and the imminent future work should concentrate on improving the quality of the local features.

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We studied the community and habitat occupation of epiphytes to understand how these plants cope with a supposedly stressful habitat: i) how general epiphytes occupy tree trunks, ii) how epiphytic bromeliads, occupy their supportive trees, iii) how CAM bromeliads are spatially distributed. The study was done in the dry forest of Jacarepiá, State of Rio de Janeiro. Data collection on epiphytes, phorophytes, and trees was based on the point-center quarter method. The photosynthetic pathway of the bromeliad species was determined using isotope ratio mass spectrometry. The presence of Gesneriaceae, Araceae, and Cactaceae indicates that some humidity is present in the area allowing the presence of supposedly less-specialized epiphytes. There was no correlation between epiphyte abundance and phorophyte diameter, and phorophytes had larger sizes than trees that do not host epiphytes. There was correlation between tree diameter and bromeliad abundance, and lack of correlation between diameter and bromeliad richness. Only one species was typical of the understorey and one was typical of the canopy, while intermediate heights were occupied by different species. The only C3 bromeliad species (Vriesea procera (Mart. ex Schult.f.) Wittm.) was significantly more exposed than the other species. If CAM occurrence is related to water economy, the fact that a C3 species is subjected to more exposed conditions is remarkable. Further comments are presented on the proportion between CAM bromeliad species and abundance in dry forest. Regarding life forms, holoepiphytes, as opposed to hemiepiphytes, showed not to be restricted by the phorophyte's diameter suggesting a more successful establishment of this life form.

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The amount of biological data has grown exponentially in recent decades. Modern biotechnologies, such as microarrays and next-generation sequencing, are capable to produce massive amounts of biomedical data in a single experiment. As the amount of the data is rapidly growing there is an urgent need for reliable computational methods for analyzing and visualizing it. This thesis addresses this need by studying how to efficiently and reliably analyze and visualize high-dimensional data, especially that obtained from gene expression microarray experiments. First, we will study the ways to improve the quality of microarray data by replacing (imputing) the missing data entries with the estimated values for these entries. Missing value imputation is a method which is commonly used to make the original incomplete data complete, thus making it easier to be analyzed with statistical and computational methods. Our novel approach was to use curated external biological information as a guide for the missing value imputation. Secondly, we studied the effect of missing value imputation on the downstream data analysis methods like clustering. We compared multiple recent imputation algorithms against 8 publicly available microarray data sets. It was observed that the missing value imputation indeed is a rational way to improve the quality of biological data. The research revealed differences between the clustering results obtained with different imputation methods. On most data sets, the simple and fast k-NN imputation was good enough, but there were also needs for more advanced imputation methods, such as Bayesian Principal Component Algorithm (BPCA). Finally, we studied the visualization of biological network data. Biological interaction networks are examples of the outcome of multiple biological experiments such as using the gene microarray techniques. Such networks are typically very large and highly connected, thus there is a need for fast algorithms for producing visually pleasant layouts. A computationally efficient way to produce layouts of large biological interaction networks was developed. The algorithm uses multilevel optimization within the regular force directed graph layout algorithm.

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Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented

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The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. This method is based on the extraction and processing of spectral information from the respiratory cycle and the use of these data for user feedback and automatic recognition. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. After this procedure, the spectrogram image is processed by a two-dimensional convolution filter and a half-threshold in order to increase the contrast and isolate its highest amplitude components, respectively. Thus, in order to generate more compressed data to automatic recognition, the spectral projection from the processed spectrogram is computed and stored as an array. The higher magnitude values of the array and its respective spectral values are then located and used as inputs to a multi-layer perceptron artificial neural network, which results an automatic indication about the presence of wheezes. For validation of the methodology, lung sounds recorded from three different repositories were used. The results show that the proposed technique achieves 84.82% accuracy in the detection of wheezing for an isolated respiratory cycle and 92.86% accuracy for the detection of wheezes when detection is carried out using groups of respiratory cycles obtained from the same person. Also, the system presents the original recorded sound and the post-processed spectrogram image for the user to draw his own conclusions from the data.

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Tea has been considered a medicine and a healthy beverage since ancient times, but recently it has received a great deal of attention because of its antioxidant properties. Green tea polyphenols have demonstrated to be an effective chemopreventive agent. Recently, investigators have found that EGCG, one of the green tea catechins, could have anti-HIV effects when bound to CD4 receptor. Many factors can constitute important influences on the composition of tea, such as species, season, age of the leaf, climate, and horticultural practices (soil, water, minerals, fertilizers). This paper presents an HPLC analytical methodology development, using column RP-18 and mobile phase composed by water, acetonitrile, methanol, ethyl acetate, glacial acetic acid (89:6:1:3:1 v/v/v/v/v) for simultaneous determination and quantification of caffeine (CAF), catechin (C), epicatechin (EC) and epigallocatechin gallate (EGCG) in samples of Camellia sinensis (green tea) grown in Brazil and harvested in spring, in summer and in autumn, in comparison to Brazilian black tea, to samples of Japanese and Chinese green tea and to two standardized dry extracts of green tea. The method has been statistically evaluated and has proved to be adequate to qualitative and quantitative determination of the samples.