28 resultados para Vetor Auto-Regressivo Multivariado
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
The current study presents the characteristics of self-efficacy of students of Administration course, who work and do not work. The study was conducted through a field research, descriptive, addressed quantitatively using statistical procedures. Was studied a population composed of 394 students distributed in three Higher Education Institutions, in the metropolitan region of Belém, in the State of Pará. The sampling was not probabilistic by accessibility, with a sample of 254 subjects. The instrument for data collection was a questionnaire composed of a set of questions divided into three sections: the first related to sociodemographic data, the second section was built to identify the work situation of the respondent and the third section was built with issues related to General Perceived Self-Efficacy Scale proposed by Schwarzer and Jerusalem (1999). Sociodemographic data were processed using methods of descriptive statistics. This procedure allowed characterizing the subjects of the sample. To identify the work situation, the analysis of frequency and percentage was used, which allowed to classify in percentage, the respondents who worked and those that did not work, and the data related to the scale of self-efficacy were processed quantitatively by the method of multivariate statistics using the software of program Statistical Package for Social Sciences for Windows - SPSS, version 17 from the process of Exploratory Factor Analysis. This procedure allowed characterizing the students who worked and the students who did not worked. The results were discussed based on Social Cognitive Theory from the construct of self-efficacy of Albert Bandura (1977). The study results showed a young sample, composed the majority of single women with work experience, and indicated that the characteristics of self-efficacy of students who work and students who do not work are different. The self-efficacy beliefs of students who do not work are based on psychological expectations, whereas the students who work demonstrated that their efficacy beliefs are sustained by previous experiences. A student who does not work proved to be reliant in their abilities to achieve a successful performance in their activities, believing it to be easy to achieve your goals and to face difficult situations at work, simply by invest a necessary effort and trust in their abilities. One who has experience working proved to be reliant in their abilities to conduct courses of action, although know that it is not easy to achieve your goals, and in unexpected situations showed its ability to solve difficult problems
Resumo:
The present work analyzes the fast evolution of gated communities in Natal-RN´s urban space. Characterized by the occupation of large areas, providing private security and utilities, this kind of real estate use arises a long list of questions and issues from society and scholars, due to privatization of urban space, bending of law constraints and the lack of an integrated planning of the cities where they are built. The reasons for its fast growth in Brazil s urban areas are analyzed, considering the impact on formal urban planning and municipal services and on the identification of urbanistic, architectural pattern and constraints, as well as legal, social and economic issues. This study is based on the detailed analysis of the first three units of gated communities built in the urban space in Natal, between 1995 and 2003, including their evolution throughout time and the specific social and economic reasons for its present widespread adoption in Brazilian real estate market and, particulary, in our city. The main objective of this piece of work is to answer the why s and how s these phenomena evolved, setting a basis for the definition of adequate public policies and regulation of this kind of urban land use
Resumo:
A self-flotator vibrational prototype electromechanical drive for treatment of oil and water emulsion or like emulsion is presented and evaluated. Oil production and refining to obtain derivatives is carried out under arrangements technically referred to as on-shore and off-shore, ie, on the continent and in the sea. In Brazil 80 % of the petroleum production is taken at sea and area of deployment and it cost scale are worrisome. It is associated, oily water production on a large scale, carrier 95% of the potential pollutant of activity whose final destination is the environment medium, terrestrial or maritime. Although diversified set of techniques and water treatment systems are in use or research, we propose an innovative system that operates in a sustainable way without chemical additives, for the good of the ecosystem. Labyrinth adsor-bent is used in metal spirals, and laboratory scale flow. Equipment and process patents are claimed. Treatments were performed at different flow rates and bands often monitored with control systems, some built, other bought for this purpose. Measurements of the levels of oil and grease (OGC) of efluents treaty remained within the range of legal framework under test conditions. Adsorbents were weighed before and after treatment for obtaining oil impregna-tion, the performance goal of vibratory action and treatment as a whole. Treatment technolo-gies in course are referenced, to compare performance, qualitatively and quantitatively. The vibration energy consumption is faced with and without conventional flotation and self-flotation. There are good prospects for the proposed, especially in reducing the residence time, by capillary action system. The impregnation dimensionless parameter was created and confronted with consecrated dimensionless parameters, on the vibrational version, such as Weber number and Froude number in quadratic form, referred to as vibrational criticality. Re-sults suggest limits to the vibration intensity
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Resumo:
Gene therapy is based on the transfer of exogenous genetic material into cells or tissues in order to correct, supplement or silencing a particular gene. To achieve this goal, efficient vehicles, viral or non-viral, should be developed. The aim of this work was to produce and evaluate a nanoemulsion system as a possible carrier for no-viral gene therapy able to load a plasmid model (pIRES2-EGFP). The nanoemulsion was produced by the sonication method, after been choose in a pseudo-ternary phase diagram build with 5 % of Captex 355®, 1.2 % of Tween 80®, 0.8 % of Span 80®, 0.16% of stearylamine and water (to 100 %). Measurements of droplet size, polydispersity index (PI), zeta potential, pH and conductivity, were performed to characterize the system. Results showed droplets smaller than 200 nm (PI < 0.2) and zeta potential > 30 mV. The formulation pH was near to 7.0 and conductivity was that expected to oil in water systems (70 to 90 μS/s) A scale up study, the stability of the system and the best sterilization method were also evaluated. We found that the system may be scaled up considering the time of sonication according to the volume produced, filtration was the best sterilization process and nanoemulsions were stable by 180 days at 4 ºC. Once developed, the complexation efficiency of the plasmid (pDNA) by the system was tested by agarose gel electrophoresis retardation assay.. The complexation efficiency increases when stearylamine was incorporated into aqueous phase (from 46 to 115 ng/μL); regarding a contact period (nanoemulsion / pDNA) of at least 2 hours in an ice bath, for complete lipoplex formation. The nanoemulsion showed low toxicity in MRC-5 cells at the usual transfection concentration, 81.49 % of survival was found. So, it can be concluded that a nanoemulsion in which a plasmid model was loaded was achieved. However, further studies concerning transfectation efficiency should be performed to confirm the system as non-viral gene carrier
Resumo:
The object of study of this thesis is the use of (self)training workshops as a fundamental process for the constitution of the teaching subject in mathematics education. The central purposes of the study were to describe and analyze a learning process of mathematics teachers supported by the training-research methodology, which procedures have been affected with the practice of (self)training workshops as a way of collaborating to the constitution of the teaching subject in Mathematics Education. The survey was conducted with a group of teachers in the city of Nova Cruz, Rio Grande do Norte through a process of continued education realized in the training workshops having as main goal the realization of the group s (self)training sessions in order to lead participants to the extent of their autonomy in their personal and professional transformations. The results obtained in the formative processes have shown the need to develop activities of mathematics teaching as a contribution to overcome the conceptual difficulties of the teachers, apart from their (self)reflections about themselves and the educational processes in which they belong. The results raised some propositions about (self)training workshops that may be incurred in practices to be included in the curriculum frameworks or materialize as a strategy of pedagogical work in training courses for teachers of mathematics. Also, they can constitute an administrative and educational activity to be instituted in the public schools of Basic Education
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Resumo:
The use of the maps obtained from remote sensing orbital images submitted to digital processing became fundamental to optimize conservation and monitoring actions of the coral reefs. However, the accuracy reached in the mapping of submerged areas is limited by variation of the water column that degrades the signal received by the orbital sensor and introduces errors in the final result of the classification. The limited capacity of the traditional methods based on conventional statistical techniques to solve the problems related to the inter-classes took the search of alternative strategies in the area of the Computational Intelligence. In this work an ensemble classifiers was built based on the combination of Support Vector Machines and Minimum Distance Classifier with the objective of classifying remotely sensed images of coral reefs ecosystem. The system is composed by three stages, through which the progressive refinement of the classification process happens. The patterns that received an ambiguous classification in a certain stage of the process were revalued in the subsequent stage. The prediction non ambiguous for all the data happened through the reduction or elimination of the false positive. The images were classified into five bottom-types: deep water; under-water corals; inter-tidal corals; algal and sandy bottom. The highest overall accuracy (89%) was obtained from SVM with polynomial kernel. The accuracy of the classified image was compared through the use of error matrix to the results obtained by the application of other classification methods based on a single classifier (neural network and the k-means algorithm). In the final, the comparison of results achieved demonstrated the potential of the ensemble classifiers as a tool of classification of images from submerged areas subject to the noise caused by atmospheric effects and the water column
Resumo:
The skin cancer is the most common of all cancers and the increase of its incidence must, in part, caused by the behavior of the people in relation to the exposition to the sun. In Brazil, the non-melanoma skin cancer is the most incident in the majority of the regions. The dermatoscopy and videodermatoscopy are the main types of examinations for the diagnosis of dermatological illnesses of the skin. The field that involves the use of computational tools to help or follow medical diagnosis in dermatological injuries is seen as very recent. Some methods had been proposed for automatic classification of pathology of the skin using images. The present work has the objective to present a new intelligent methodology for analysis and classification of skin cancer images, based on the techniques of digital processing of images for extraction of color characteristics, forms and texture, using Wavelet Packet Transform (WPT) and learning techniques called Support Vector Machine (SVM). The Wavelet Packet Transform is applied for extraction of texture characteristics in the images. The WPT consists of a set of base functions that represents the image in different bands of frequency, each one with distinct resolutions corresponding to each scale. Moreover, the characteristics of color of the injury are also computed that are dependants of a visual context, influenced for the existing colors in its surround, and the attributes of form through the Fourier describers. The Support Vector Machine is used for the classification task, which is based on the minimization principles of the structural risk, coming from the statistical learning theory. The SVM has the objective to construct optimum hyperplanes that represent the separation between classes. The generated hyperplane is determined by a subset of the classes, called support vectors. For the used database in this work, the results had revealed a good performance getting a global rightness of 92,73% for melanoma, and 86% for non-melanoma and benign injuries. The extracted describers and the SVM classifier became a method capable to recognize and to classify the analyzed skin injuries
Resumo:
The human voice is an important communication tool and any disorder of the voice can have profound implications for social and professional life of an individual. Techniques of digital signal processing have been used by acoustic analysis of vocal disorders caused by pathologies in the larynx, due to its simplicity and noninvasive nature. This work deals with the acoustic analysis of voice signals affected by pathologies in the larynx, specifically, edema, and nodules on the vocal folds. The purpose of this work is to develop a classification system of voices to help pre-diagnosis of pathologies in the larynx, as well as monitoring pharmacological treatments and after surgery. Linear Prediction Coefficients (LPC), Mel Frequency cepstral coefficients (MFCC) and the coefficients obtained through the Wavelet Packet Transform (WPT) are applied to extract relevant characteristics of the voice signal. For the classification task is used the Support Vector Machine (SVM), which aims to build optimal hyperplanes that maximize the margin of separation between the classes involved. The hyperplane generated is determined by the support vectors, which are subsets of points in these classes. According to the database used in this work, the results showed a good performance, with a hit rate of 98.46% for classification of normal and pathological voices in general, and 98.75% in the classification of diseases together: edema and nodules
Resumo:
We propose a multi-resolution approach for surface reconstruction from clouds of unorganized points representing an object surface in 3D space. The proposed method uses a set of mesh operators and simple rules for selective mesh refinement, with a strategy based on Kohonen s self-organizing map. Basically, a self-adaptive scheme is used for iteratively moving vertices of an initial simple mesh in the direction of the set of points, ideally the object boundary. Successive refinement and motion of vertices are applied leading to a more detailed surface, in a multi-resolution, iterative scheme. Reconstruction was experimented with several point sets, induding different shapes and sizes. Results show generated meshes very dose to object final shapes. We include measures of performance and discuss robustness.
Resumo:
This work presents a set of intelligent algorithms with the purpose of correcting calibration errors in sensors and reducting the periodicity of their calibrations. Such algorithms were designed using Artificial Neural Networks due to its great capacity of learning, adaptation and function approximation. Two approaches willbe shown, the firstone uses Multilayer Perceptron Networks to approximate the many shapes of the calibration curve of a sensor which discalibrates in different time points. This approach requires the knowledge of the sensor s functioning time, but this information is not always available. To overcome this need, another approach using Recurrent Neural Networks was proposed. The Recurrent Neural Networks have a great capacity of learning the dynamics of a system to which it was trained, so they can learn the dynamics of a sensor s discalibration. Knowingthe sensor s functioning time or its discalibration dynamics, it is possible to determine how much a sensor is discalibrated and correct its measured value, providing then, a more exact measurement. The algorithms proposed in this work can be implemented in a Foundation Fieldbus industrial network environment, which has a good capacity of device programming through its function blocks, making it possible to have them applied to the measurement process
Resumo:
Ceramic substrates have been investigated by researchers around the world and has achieved a high interest in the scientific community, because they had high dielectric constants and excellent performance in the structures employed. Such ceramics result in miniaturized structures with dimensions well reduced and high radiation efficiency. In this work, we have used a new ceramic material called lead zinc titanate in the form of Zn0,8Pb0,2TiO3, capable of being used as a dielectric substrate in the construction of various structures of antennas. The method used in constructing the ceramic combustion synthesis was Self- Sustained High Temperature (SHS - "Self-Propagating High-Temperature Synthesis") which is defined as a process that uses highly exothermic reactions to produce various materials. Once initiated the reaction area in the reaction mixture, the heat generated is sufficient to become self-sustaining combustion in the form of a wave that propagates converting the reaction mixture into the product of interest. Were analyzed aspects of the formation of the composite Zn0,8Pb0,2TiO3 by SHS powders and characterized. The analysis consisted of determining the parameters of the reaction for the formation of the composite, as the ignition temperature and reaction mechanisms. The production of composite Zn0,8Pb0,2TiO3 by SHS performed in the laboratory, was the result of a total control of combustion temperature and after obtaining the powder began the development of ceramics. The product was obtained in the form of regular, alternating layers of porous ceramics and was obtained by uniaxial pressing. 10 The product was characterized by analysis of dilatometry, X-ray diffraction analysis and scanning electron microscopy. One of the contributions typically defined in this work is the development of a new dielectric material, nevertheless presented previously in the literature. Therefore, the structures of the antennas presented in this work consisted of new dielectric ceramics based Zn0,8Pb0,2TiO3 usually used as dielectric substrate. The materials produced were characterized in the microwave range. These are dielectrics with high relative permittivity and low loss tangent. The Ansoft HFSS, commercial program employee, using the finite element method, and was used for analysis of antennas studied in this work
Resumo:
Image compress consists in represent by small amount of data, without loss a visual quality. Data compression is important when large images are used, for example satellite image. Full color digital images typically use 24 bits to specify the color of each pixel of the Images with 8 bits for each of the primary components, red, green and blue (RGB). Compress an image with three or more bands (multispectral) is fundamental to reduce the transmission time, process time and record time. Because many applications need images, that compression image data is important: medical image, satellite image, sensor etc. In this work a new compression color images method is proposed. This method is based in measure of information of each band. This technique is called by Self-Adaptive Compression (S.A.C.) and each band of image is compressed with a different threshold, for preserve information with better result. SAC do a large compression in large redundancy bands, that is, lower information and soft compression to bands with bigger amount of information. Two image transforms are used in this technique: Discrete Cosine Transform (DCT) and Principal Component Analysis (PCA). Primary step is convert data to new bands without relationship, with PCA. Later Apply DCT in each band. Data Loss is doing when a threshold discarding any coefficients. This threshold is calculated with two elements: PCA result and a parameter user. Parameters user define a compression tax. The system produce three different thresholds, one to each band of image, that is proportional of amount information. For image reconstruction is realized DCT and PCA inverse. SAC was compared with JPEG (Joint Photographic Experts Group) standard and YIQ compression and better results are obtain, in MSE (Mean Square Root). Tests shown that SAC has better quality in hard compressions. With two advantages: (a) like is adaptive is sensible to image type, that is, presents good results to divers images kinds (synthetic, landscapes, people etc., and, (b) it need only one parameters user, that is, just letter human intervention is required