A dança dos monstros: corpo e estética na arte e na Educação Física

The speeches about the body in interface with the technology, that fulfill the contemporary discussions, have been a stage of innumerable ethical, epistemological, aesthetic and ontological reflections. These happened bodies of the biotechnological scene also invade the dance, making several possible dialogues, making old concepts instable, opening way to revealing explorations and bringing with it implications and reflections. In this context, this research has as objective to discuss relations between body and technology in the dance; to understand the aesthetic configurations of the monster in the dance as possibility to question the body; to establish relations between the monstrous body in the dance and the conceptions of body in the Physical Education. We believe to be able to contribute for the reflection in the field of the Physical Education, since the work visualizes to extend the field of the discussions on aesthetic body and, as well as evidencing dialogues between different areas of the knowledge, as the Art and the Physical Education. From the point of view of the method, the work follows orientation of the Phenomenology for an aesthetic image appreciation of the videos in the choreographies In'perfeito and Violência of Cena 11, Dance Group that has marked new aesthetic configurations in the brazilian dance. Thus, we took for us the reflections on the "significant scenes" proposed by Bicudo (2000), to appreciate the dance of Cena 11. We emphasize that, after the identification of the Significant Scenes, it was necessary to approach these scenes from close senses, from which we detach the appearance, the space and the gesture. We evidence that, the bodies revealed by the group Cena 11, show an aesthetic that it interlaces the beauty, the ugly and the grotesque. An aesthetic of the unharmony, capable to transgress the oppositions, dialoguing with multiple antagonisms and that it amplifies the apollonian aesthetic linear rules, so predominant in the history of the dance and the Physical Education. We identify some indicatives that take us to the problematizations on an affective and anarchic body, when questioning the tyranny of the perfect corporality; the naturalization of the pain; the closed gesture in a finished and unique grammar; the standardization of feminine and masculine roles and the negation of the feeling. From these indicatives, we discuss the aesthetic of the deformed bodies of Cena 11, approaching it of the conceptions of body in the Physical Education, sometimes criticizing the rationalists and naturalistic views, sometimes dialoguing with more recent perspectives studied by researchers of this area of knowledge, which point to a reflection on the body under the optics of the sensible

Retratos, imagens, letras e numeros colados nas paredes:representaçãoes sociais de escola para ribeirinhos dos rios Môa e Azul - Acre

Remote Communities. Absence of artifacts and minimization of the exacerbated consumption of modernity. The desire which spread beyond what reality can provide. Expressions like this are present in this paper which focus in the social representations of school built by residents who live at the riversides of Môa and Azul Rivers, in Mâncio Lima, Acre State. To do so, we used the methodological contribution of the semi-structured interview, observation of the place while a natural inhabitant of the region, and also photos analyses of local reality. A key feature of the riverside homes is the glued paper on the walls of houses forming a panel set of portraits, pictures, letters and numbers for all appreciated. Regardless of whether or not read, there is admiration for the color of the images, the layout of the letters, and the things of the city awakening the desire to obtain school knowledge. The resident of this Amazon region maintains a close relationship between thinking, acting and feeling living harmonically with nature that connects them to the ideal landscape which is revisited by the graphic material that attracts wondering what exists beyond the shores of the river, beyond the horizon of green forests. It is a life entirely accomplished by the imaginary where exist a framed landscape merged and confused by the real and the supernatural, in which men and gods walk together by the forest, sailing by the rivers and seek a possible aesthetic between the real and ideal. The Theory of Social Representations spread by Serge Moscovici (2005) and Jodelet (2001) guided our gaze on the understanding what the school is and its representation to the riversides, as well to reveal the relation they practice with the knowledge that is spread by the mystification and the knowledge that is practice daily. Based in Bardin s thematic analysis (2004) we tried to raise such contents combining them in five analysis categories

Segurança do paciente no sistema de medicação: análise de enfermeiros de um hospital de ensino

This study aimed to identify and describe the factors related to Patient Safety in a medication system according to the nurses analysis in a teaching hospital from the photographic analysis method. This was a cross-sectional, descriptive study with mixed approach in a teaching hospital in Rio Grande do Norte. The population consisted of 42 nurses from inpatient units, of which 34 composed the study sample. As eligibility criteria, we defined nurses from public service and nurses who agreed to participate. Ethical determinations were observed, the study was submitted to the Ethics and Research of the University Hospital Onofre Lopes, obtaining the assent with ethical assessment certificate (CAAE 0098.0.051.294-11). For data collection, we used the photographic method (Photographic Analysis Technique) by Patricia Marck (Canada). It was developed in two phases: at first, we randomly captured photos from the medication system, resulting in 282 images; then we selected/processed the photographs, which were reduced to 10 images in Microsoft Excel 2010; in the second phase, the nurses answered the questionnaire divided into socio-professional profile and Digital Photography Scoring Tool (questions a and b ). For analysis of the question a , we used the content analysis technique, and for b , we used the Statistical Package for the Social Sciences 20.0 (temporary license). The socio-professional profile revealed the predominance of females; age group 34-43 years; professionals with specialization; 10-18 years of length of service; and nurses working exclusively in the hospital and who know the Patient Safety. The photographic analysis in relation to Patient Safety resulted in specific categories for each stage of the medication system. Regarding disposal, we identified Proper verification ; Improper verification ; Correct identification ; Disposal in single doses ; and Improper Environment , with predominance of that last category. As for storage: Proper storage ; Improper storage ; Risk of exchange/disappearance ; and Poor hygiene , with special reference to improper storage. In preparation: Risk of exchanging medication/patient ; Inappropriate physical space ; and Inadequate 9 preparation of controlled drugs , highlighting the first category. In drug administration: Lack of Personal Protective Equipment ; Use of Personal Protective Equipment ; Improper administration technique ; Proper administration technique ; Correct drug identification ; Incorrect drug identification ; and Peripheral venous access without identification . From the safety assessment of 10 photographs, by adapting the scores (1-10) to the Likert Scale, we identified three Totally Unsafe (Level 1), three Unsafe (Level 2), three Partially Safe (Level 3), one Safe (Level 4), and no photograph considered Totally Safe. This study identified the prevalence of unsafety in the medication system in the nurses opinion. We were also able to understand that, although nurses identify safety aspects, the most prevalent categories characterize an unsafe assessment. Nursing needs to reflect on its practice, identifying gaps in the medication system in order to achieve a proper and safe care

Classificação de imagens de ambientes coralinos: uma abordagem empregando uma combinação de classificadores e máquina de vetor de suporte

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

Análise e classificação de imagens de lesões da pele por atributos de cor, forma e textura utilizando máquina de vetor de suporte

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

Seleção seqüencial de descritores por análise da semântica para recuperação de imagens baseada no conteúdo

With the rapid growth of databases of various types (text, multimedia, etc..), There exist a need to propose methods for ordering, access and retrieve data in a simple and fast way. The images databases, in addition to these needs, require a representation of the images so that the semantic content characteristics are considered. Accordingly, several proposals such as the textual annotations based retrieval has been made. In the annotations approach, the recovery is based on the comparison between the textual description that a user can make of images and descriptions of the images stored in database. Among its drawbacks, it is noted that the textual description is very dependent on the observer, in addition to the computational effort required to describe all the images in database. Another approach is the content based image retrieval - CBIR, where each image is represented by low-level features such as: color, shape, texture, etc. In this sense, the results in the area of CBIR has been very promising. However, the representation of the images semantic by low-level features is an open problem. New algorithms for the extraction of features as well as new methods of indexing have been proposed in the literature. However, these algorithms become increasingly complex. So, doing an analysis, it is natural to ask whether there is a relationship between semantics and low-level features extracted in an image? and if there is a relationship, which descriptors better represent the semantic? which leads us to a new question: how to use descriptors to represent the content of the images?. The work presented in this thesis, proposes a method to analyze the relationship between low-level descriptors and semantics in an attempt to answer the questions before. Still, it was observed that there are three possibilities of indexing images: Using composed characteristic vectors, using parallel and independent index structures (for each descriptor or set of them) and using characteristic vectors sorted in sequential order. Thus, the first two forms have been widely studied and applied in literature, but there were no records of the third way has even been explored. So this thesis also proposes to index using a sequential structure of descriptors and also the order of these descriptors should be based on the relationship that exists between each descriptor and semantics of the users. Finally, the proposed index in this thesis revealed better than the traditional approachs and yet, was showed experimentally that the order in this sequence is important and there is a direct relationship between this order and the relationship of low-level descriptors with the semantics of the users

Otimizações da transmissão de imagens em redes de sensores visuais sem fio explorando a relevância de monitoramento dos nós fontes e codificação DWT

The development of wireless sensor networks for control and monitoring functions has created a vibrant investigation scenario, covering since communication aspects to issues related with energy efficiency. When source sensors are endowed with cameras for visual monitoring, a new scope of challenges is raised, as transmission and monitoring requirements are considerably changed. Particularly, visual sensors collect data following a directional sensing model, altering the meaning of concepts as vicinity and redundancy but allowing the differentiation of source nodes by their sensing relevancies for the application. In such context, we propose the combined use of two differentiation strategies as a novel QoS parameter, exploring the sensing relevancies of source nodes and DWT image coding. This innovative approach supports a new scope of optimizations to improve the performance of visual sensor networks at the cost of a small reduction on the overall monitoring quality of the application. Besides definition of a new concept of relevance and the proposition of mechanisms to support its practical exploitation, we propose five different optimizations in the way images are transmitted in wireless visual sensor networks, aiming at energy saving, transmission with low delay and error recovery. Putting all these together, the proposed innovative differentiation strategies and the related optimizations open a relevant research trend, where the application monitoring requirements are used to guide a more efficient operation of sensor networks

Seleção de features guiada por atenção visual em imagens com fóvea

Visual attention is a very important task in autonomous robotics, but, because of its complexity, the processing time required is significant. We propose an architecture for feature selection using foveated images that is guided by visual attention tasks and that reduces the processing time required to perform these tasks. Our system can be applied in bottom-up or top-down visual attention. The foveated model determines which scales are to be used on the feature extraction algorithm. The system is able to discard features that are not extremely necessary for the tasks, thus, reducing the processing time. If the fovea is correctly placed, then it is possible to reduce the processing time without compromising the quality of the tasks outputs. The distance of the fovea from the object is also analyzed. If the visual system loses the tracking in top-down attention, basic strategies of fovea placement can be applied. Experiments have shown that it is possible to reduce up to 60% the processing time with this approach. To validate the method, we tested it with the feature algorithm known as Speeded Up Robust Features (SURF), one of the most efficient approaches for feature extraction. With the proposed architecture, we can accomplish real time requirements of robotics vision, mainly to be applied in autonomous robotics

Identificação de nematóides através de técnicas de processamento inteligentes de imagens

abstract

Algoritmo SOM com estrutura hierárquica e dinâmica aplicado a compressão de imagens

ln this work the implementation of the SOM (Self Organizing Maps) algorithm or Kohonen neural network is presented in the form of hierarchical structures, applied to the compression of images. The main objective of this approach is to develop an Hierarchical SOM algorithm with static structure and another one with dynamic structure to generate codebooks (books of codes) in the process of the image Vector Quantization (VQ), reducing the time of processing and obtaining a good rate of compression of images with a minimum degradation of the quality in relation to the original image. Both self-organizing neural networks developed here, were denominated HSOM, for static case, and DHSOM, for the dynamic case. ln the first form, the hierarchical structure is previously defined and in the later this structure grows in an automatic way in agreement with heuristic rules that explore the data of the training group without use of external parameters. For the network, the heuristic mIes determine the dynamics of growth, the pruning of ramifications criteria, the flexibility and the size of children maps. The LBO (Linde-Buzo-Oray) algorithm or K-means, one ofthe more used algorithms to develop codebook for Vector Quantization, was used together with the algorithm of Kohonen in its basic form, that is, not hierarchical, as a reference to compare the performance of the algorithms here proposed. A performance analysis between the two hierarchical structures is also accomplished in this work. The efficiency of the proposed processing is verified by the reduction in the complexity computational compared to the traditional algorithms, as well as, through the quantitative analysis of the images reconstructed in function of the parameters: (PSNR) peak signal-to-noise ratio and (MSE) medium squared error

Correspondência estéreo usando imagens em multiresolução com profundidade variável

We propose a multi-resolution, coarse-to-fine approach for stereo matching, where the first matching happens at a different depth for each pixel. The proposed technique has the potential of attenuating several problems faced by the constant depth algorithm, making it possible to reduce the number of errors or the number of comparations needed to get equivalent results. Several experiments were performed to demonstrate the method efficiency, including comparison with the traditional plain correlation technique, where the multi-resolution matching with variable depth, proposed here, generated better results with a smaller processing time

Técnicas de computação natural para segmentação de imagens médicas

Image segmentation is one of the image processing problems that deserves special attention from the scientific community. This work studies unsupervised methods to clustering and pattern recognition applicable to medical image segmentation. Natural Computing based methods have shown very attractive in such tasks and are studied here as a way to verify it's applicability in medical image segmentation. This work treats to implement the following methods: GKA (Genetic K-means Algorithm), GFCMA (Genetic FCM Algorithm), PSOKA (PSO and K-means based Clustering Algorithm) and PSOFCM (PSO and FCM based Clustering Algorithm). Besides, as a way to evaluate the results given by the algorithms, clustering validity indexes are used as quantitative measure. Visual and qualitative evaluations are realized also, mainly using data given by the BrainWeb brain simulator as ground truth

Uma proposição para o cálculo de mapas de disparidade de imagens estéreo usando um interpolador neural baseado em funções de base radial

This study aims to seek a more viable alternative for the calculation of differences in images of stereo vision, using a factor that reduces heel the amount of points that are considered on the captured image, and a network neural-based radial basis functions to interpolate the results. The objective to be achieved is to produce an approximate picture of disparities using algorithms with low computational cost, unlike the classical algorithms

Posicionamento e movimentação de um robô humanóide utilizando imagens de uma câmera móvel externa

This work proposes a method to localize a simple humanoid robot, without embedded sensors, using images taken from an extern camera and image processing techniques. Once the robot is localized relative to the camera, supposing we know the position of the camera relative to the world, we can compute the position of the robot relative to the world. To make the camera move in the work space, we will use another mobile robot with wheels, which has a precise locating system, and will place the camera on it. Once the humanoid is localized in the work space, we can take the necessary actions to move it. Simultaneously, we will move the camera robot, so it will take good images of the humanoid. The mainly contributions of this work are: the idea of using another mobile robot to aid the navigation of a humanoid robot without and advanced embedded electronics; chosing of the intrinsic and extrinsic calibration methods appropriated to the task, especially in the real time part; and the collaborative algorithm of simultaneous navigation of the robots

Compressão auto-adaptativa de imagens coloridas

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