886 resultados para LC Classification System
Resumo:
Bauhinia forficata is used in folk medicine for its hypoglycemiant effect. In the south of Brazil, the subspecies pruinosa is found in a region with the characteristic flora, pampa biome. This species has been consumed by the local population as a tea for diabetes treatment. We studied the chemical composition of hydroethanolic extracts using LC/ESI-MS. The leaf extracts were prepared by percolation with 50% (v/v) ethanol. The chromatographic analyses were performed using a reverse-phase system, gradient elution with acetonitrile:phosphoric acid 0.05%, and ESI-MS in the positive ion mode. The chemical profile of the flavonoids was suggested to involve four quercetin and kaempferol glycosides.
Resumo:
Quetiapine is an atypical antipsychotic used to treat schizophrenia. However, despite great interest for its chronic therapeutic use, quetiapine has some important side effects such as weight gain induction. The development of a quetiapine nanocarrier can potentially target the drug into central nervous system, resulting in a reduction of systemic side effects and improved patient treatment. In the present work, a simple liquid chromatography/ultraviolet detection (LC/UV) analytical method was developed and validated for quantification of total quetiapine content in lipid core nanocapsules as well as for determination of incorporation efficiency. An algorithm proposed by Oliveira et al. (2012) was applied to characterize the distribution of quetiapine in the pseudo-phases of the nanocarrier, leading to a better understanding of the quetiapine nanoparticles produced. The analytical methodology developed was specific, linear in the range of 0.5 to 100 µg mL−1 (r2 > 0,99), and accurate and precise (R.S.D < ±5%). The absolute recovery of quetiapine from the nanoparticles was approximately 98% with an incorporation efficiency of approximately 96%. The results indicated that quetiapine was present in a type III distribution according to the algorithm, and was mainly located in the core of the nanoparticle because of its logD in the formulation pH (6.86 ± 0.4).
Resumo:
In recent years, the network vulnerability to natural hazards has been noticed. Moreover, operating on the limits of the network transmission capabilities have resulted in major outages during the past decade. One of the reasons for operating on these limits is that the network has become outdated. Therefore, new technical solutions are studied that could provide more reliable and more energy efficient power distributionand also a better profitability for the network owner. It is the development and price of power electronics that have made the DC distribution an attractive alternative again. In this doctoral thesis, one type of a low-voltage DC distribution system is investigated. Morespecifically, it is studied which current technological solutions, used at the customer-end, could provide better power quality for the customer when compared with the current system. To study the effect of a DC network on the customer-end power quality, a bipolar DC network model is derived. The model can also be used to identify the supply parameters when the V/kW ratio is approximately known. Although the model provides knowledge of the average behavior, it is shown that the instantaneous DC voltage ripple should be limited. The guidelines to choose an appropriate capacitance value for the capacitor located at the input DC terminals of the customer-end are given. Also the structure of the customer-end is considered. A comparison between the most common solutions is made based on their cost, energy efficiency, and reliability. In the comparison, special attention is paid to the passive filtering solutions since the filter is considered a crucial element when the lifetime expenses are determined. It is found out that the filter topology most commonly used today, namely the LC filter, does not provide economical advantage over the hybrid filter structure. Finally, some of the typical control system solutions are introduced and their shortcomings are presented. As a solution to the customer-end voltage regulation problem, an observer-based control scheme is proposed. It is shown how different control system structures affect the performance. The performance meeting the requirements is achieved by using only one output measurement, when operating in a rigid network. Similar performance can be achieved in a weak grid by DC voltage measurement. An additional improvement can be achieved when an adaptive gain scheduling-based control is introduced. As a conclusion, the final power quality is determined by a sum of various factors, and the thesis provides the guidelines for designing the system that improves the power quality experienced by the customer.
Resumo:
This study aimed at quantifying total organic carbon stocks and its pools in Acrisol under agroforestry systems with six (AFS6) and thirteen years old (AFS13), slash-and-burn agriculture (SBA) and savanna native forest (SNF) in northeastern Brazil. Soil samples were collected at 0-0.05 m, 0.05-0.10 m, 0.10-0.20 m and 0.20-0.40 m depths in the dry and rainy seasons to evaluate total organic carbon (TOC) stocks and labile carbon (LC), fulvic acid fraction (C-FAF), humic acid fraction (C-HAF), humin (C-HF) and microbial biomass carbon (Cmic) contents. Additionally, carbon management index (CMI) was determined. Higher TOC stocks (97.7 and 81.8 Mg ha-1 for the 0-0.40 m depth in the dry and rainy seasons, respectively) and LC, humic substances and Cmic contents were observed in the AFS13 in all the depths. CMI also was higher in the AFS13 (0-0. 05 m: 158 and 86; 0.05-0.10 m: 171 and 67, respectively for the dry and rainy seasons) especially when compared to the SBA (0-0.05 m: 5.6 and 5.4; 0.05-0.10 m: 5.3 and 5.8, respectively for dry and rainy seasons). The agroforestry systems increased soil quality through the conservation of organic matter and can be considered an excellent strategy to assurance sustainability in tropical soil of Northeastern Brazil
Resumo:
This study compares the precision of three image classification methods, two of remote sensing and one of geostatistics applied to areas cultivated with citrus. The 5,296.52ha area of study is located in the city of Araraquara - central region of the state of São Paulo (SP), Brazil. The multispectral image from the CCD/CBERS-2B satellite was acquired in 2009 and processed through the Geographic Information System (GIS) SPRING. Three classification methods were used, one unsupervised (Cluster), and two supervised (Indicator Kriging/IK and Maximum Likelihood/Maxver), in addition to the screen classification taken as field checking.. Reliability of classifications was evaluated by Kappa index. In accordance with the Kappa index, the Indicator kriging method obtained the highest degree of reliability for bands 2 and 4. Moreover the Cluster method applied to band 2 (green) was the best quality classification between all the methods. Indicator Kriging was the classifier that presented the citrus total area closest to the field check estimated by -3.01%, whereas Maxver overestimated the total citrus area by 42.94%.
Resumo:
Abstract: Fifty-five bursa of Fabricius (BF) were evaluated by optical microscopy for three different avian histopathologists (H1, H3 and H4) to determine the degree of lymphoid depletion. One histologist evaluated the same slides at two different times (H1 and H2) with four-months interval between the observations. The same BFs were evaluated using the system of Digital Lymphocyte Depletion Evaluation (ADDL), being performed by three differents operators of the system, not histopathologists. The results showed was a significant difference between the histopathologists and between the scores established by the same expert (H1 and H2). However, there were not significant differences between the scores with the ADDL system, obtained using ADDL. The results make clear the fragility of the subjective lymphocyte depletion score classification by the traditional histologic method, while the ADDL system proves to be more appropriated for the assessment of the lymphoid loss in the BF.
Resumo:
Abstract: Bull breeding soundness evaluation (BBSE) is a method applied to reduce the risk of using subfertile bulls in herds. There are currently two BBSE systems, those of the Society for Theriogenology (SFT) and the Western Canadian Association of Bovine Practitioners (WCABP). Scrotal circumference (SC), sperm motility (SM) and normal sperm (NS) of 454 bulls aged between 12 and 15 months of a Spanish beef breed were used to compare both systems, and since there is no agreement on that BBSE system must be applied in Spain, a single one was proposed for its consideration. SC was adjusted to 15 months (SC15) and the mean of the BBSE traits was: SC15 (34.2±2.4cm), SM (76.6±14.6%) and NS (76.8±12.3%). In the PROPOSED system, the SM and NS thresholds were those defined by the WCABP system, while the SC15 thresholds were set by combining the SFT threshold and SC15±1SD in order to establish four classification categories, the three proposed by the WCABP system: unsatisfactory, questionable and satisfactory, and other category, called superior, for bulls with SM≥60%, NS≥70% and SC15≥Mean+1SD. The PROPOSED system scored fewer bulls as unsatisfactory than the SFT and the WCABP systems (8.6%, 23.6% and 22.5%, respectively; P<0.01), while the percentage of bulls from worst to best in the other three categories under the PROPOSED system was: 26.0%, 54.2% and 11.2%, respectively. In conclusion, the PROPOSED system gives more emphasis to SC, sets differences between bulls classified as satisfactory by the other systems and can be considered a good system for Spain and for other countries that have no defined their own system.
Resumo:
This study will concentrate on Product Data Management (PDM) systems, and sheet metal design features and classification. In this thesis, PDM is seen as an individual system which handles all product-related data and information. The meaning of relevant data is to take the manufacturing process further with fewer errors. The features of sheet metals are giving more information and value to the designed models. The possibility of implementing PDM and sheet metal features recognition are the core of this study. Their integration should make the design process faster and manufacturing-friendly products easier to design. The triangulation method is the basis for this research. The sections of this triangle are: scientific literature review, interview using the Delphi method and the author’s experience and observations. The main key findings of this study are: (1) the area of focus in triangle (the triangle of three different point of views: business, information exchange and technical) depends on the person’s background and their role in the company, (2) the classification in the PDM system (and also in the CAD system) should be done using the materials, tools and machines that are in use in the company and (3) the design process has to be more effective because of the increase of industrial production, sheet metal blank production and the designer’s time spent on actual design and (4) because Design For Manufacture (DFM) integration can be done with CAD-programs, DFM integration with the PDM system should also be possible.
Resumo:
Since the times preceding the Second World War the subject of aircraft tracking has been a core interest to both military and non-military aviation. During subsequent years both technology and configuration of the radars allowed the users to deploy it in numerous fields, such as over-the-horizon radar, ballistic missile early warning systems or forward scatter fences. The latter one was arranged in a bistatic configuration. The bistatic radar has continuously re-emerged over the last eighty years for its intriguing capabilities and challenging configuration and formulation. The bistatic radar arrangement is used as the basis of all the analyzes presented in this work. The aircraft tracking method of VHF Doppler-only information, developed in the first part of this study, is solely based on Doppler frequency readings in relation to time instances of their appearance. The corresponding inverse problem is solved by utilising a multistatic radar scenario with two receivers and one transmitter and using their frequency readings as a base for aircraft trajectory estimation. The quality of the resulting trajectory is then compared with ground-truth information based on ADS-B data. The second part of the study deals with the developement of a method for instantaneous Doppler curve extraction from within a VHF time-frequency representation of the transmitted signal, with a three receivers and one transmitter configuration, based on a priori knowledge of the probability density function of the first order derivative of the Doppler shift, and on a system of blocks for identifying, classifying and predicting the Doppler signal. The extraction capabilities of this set-up are tested with a recorded TV signal and simulated synthetic spectrograms. Further analyzes are devoted to more comprehensive testing of the capabilities of the extraction method. Besides testing the method, the classification of aircraft is performed on the extracted Bistatic Radar Cross Section profiles and the correlation between them for different types of aircraft. In order to properly estimate the profiles, the ADS-B aircraft location information is adjusted based on extracted Doppler frequency and then used for Bistatic Radar Cross Section estimation. The classification is based on seven types of aircraft grouped by their size into three classes.
Resumo:
Wind is one of the most compelling forms of indirect solar energy. Available now, the conversion of wind power into electricity is and will continue to be an important element of energy self-sufficiency planning. This paper is one in a series intended to report on the development of a new type of generator for wind energy; a compact, high-power, direct-drive permanent magnet synchronous generator (DD-PMSG) that uses direct liquid cooling (LC) of the stator windings to manage Joule heating losses. The main param-eters of the subject LC DD-PMSG are 8 MW, 3.3 kV, and 11 Hz. The stator winding is cooled directly by deionized water, which flows through the continuous hollow conductor of each stator tooth-coil winding. The design of the machine is to a large degree subordinate to the use of these solid-copper tooth-coils. Both steady-state and timedependent temperature distributions for LC DD-PMSG were examined with calculations based on a lumpedparameter thermal model, which makes it possible to account for uneven heat loss distribution in the stator conductors and the conductor cooling system. Transient calculations reveal the copper winding temperature distribution for an example duty cycle during variable-speed wind turbine operation. The cooling performance of the liquid cooled tooth-coil design was predicted via finite element analysis. An instrumented cooling loop featuring a pair of LC tooth-coils embedded in a lamination stack was built and laboratory tested to verify the analytical model. Predicted and measured results were in agreement, confirming the predicted satisfactory operation of the LC DD-PMSG cooling technology approach as a whole.
Resumo:
Genetic Programming (GP) is a widely used methodology for solving various computational problems. GP's problem solving ability is usually hindered by its long execution times. In this thesis, GP is applied toward real-time computer vision. In particular, object classification and tracking using a parallel GP system is discussed. First, a study of suitable GP languages for object classification is presented. Two main GP approaches for visual pattern classification, namely the block-classifiers and the pixel-classifiers, were studied. Results showed that the pixel-classifiers generally performed better. Using these results, a suitable language was selected for the real-time implementation. Synthetic video data was used in the experiments. The goal of the experiments was to evolve a unique classifier for each texture pattern that existed in the video. The experiments revealed that the system was capable of correctly tracking the textures in the video. The performance of the system was on-par with real-time requirements.
Resumo:
The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and deterministic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel metaheuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS metaheuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.
Resumo:
The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and determinis- tic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel meta–heuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS meta–heuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.
Resumo:
This paper develops a model of short-range ballistic missile defense and uses it to study the performance of Israel’s Iron Dome system. The deterministic base model allows for inaccurate missiles, unsuccessful interceptions, and civil defense. Model enhancements consider the trade-offs in attacking the interception system, the difficulties faced by militants in assembling large salvos, and the effects of imperfect missile classification by the defender. A stochastic model is also developed. Analysis shows that system performance can be highly sensitive to the missile salvo size, and that systems with higher interception rates are more “fragile” when overloaded. The model is calibrated using publically available data about Iron Dome’s use during Operation Pillar of Defense in November 2012. If the systems performed as claimed, they saved Israel an estimated 1778 casualties and $80 million in property damage, and thereby made preemptive strikes on Gaza about 8 times less valuable to Israel. Gaza militants could have inflicted far more damage by grouping their rockets into large salvos, but this may have been difficult given Israel’s suppression efforts. Counter-battery fire by the militants is unlikely to be worthwhile unless they can obtain much more accurate missiles.
Resumo:
Cette thèse traite de la classification analytique du déploiement de systèmes différentiels linéaires ayant une singularité irrégulière. Elle est composée de deux articles sur le sujet: le premier présente des résultats obtenus lors de l'étude de la confluence de l'équation hypergéométrique et peut être considéré comme un cas particulier du second; le deuxième contient les théorèmes et résultats principaux. Dans les deux articles, nous considérons la confluence de deux points singuliers réguliers en un point singulier irrégulier et nous étudions les conséquences de la divergence des solutions au point singulier irrégulier sur le comportement des solutions du système déployé. Pour ce faire, nous recouvrons un voisinage de l'origine (de manière ramifiée) dans l'espace du paramètre de déploiement $\epsilon$. La monodromie d'une base de solutions bien choisie est directement reliée aux matrices de Stokes déployées. Ces dernières donnent une interprétation géométrique aux matrices de Stokes, incluant le lien (existant au moins pour les cas génériques) entre la divergence des solutions à $\epsilon=0$ et la présence de solutions logarithmiques autour des points singuliers réguliers lors de la résonance. La monodromie d'intégrales premières de systèmes de Riccati correspondants est aussi interprétée en fonction des éléments des matrices de Stokes déployées. De plus, dans le second article, nous donnons le système complet d'invariants analytiques pour le déploiement de systèmes différentiels linéaires $x^2y'=A(x)y$ ayant une singularité irrégulière de rang de Poincaré $1$ à l'origine au-dessus d'un voisinage fixé $\mathbb{D}_r$ dans la variable $x$. Ce système est constitué d'une partie formelle, donnée par des polynômes, et d'une partie analytique, donnée par une classe d'équivalence de matrices de Stokes déployées. Pour chaque valeur du paramètre $\epsilon$ dans un secteur pointé à l'origine d'ouverture plus grande que $2\pi$, nous recouvrons l'espace de la variable, $\mathbb{D}_r$, avec deux secteurs et, au-dessus de chacun, nous choisissons une base de solutions du système déployé. Cette base sert à définir les matrices de Stokes déployées. Finalement, nous prouvons un théorème de réalisation des invariants qui satisfont une condition nécessaire et suffisante, identifiant ainsi l'ensemble des modules.