811 resultados para Hand recognition


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Social insects use cuticular lipids for nestmate recognition. These lipids are chiefly hydrocarbons that can be endogenously produced or acquired from the environment. Although these compounds are already described as coming from different sources for different groups of social insects, nothing is known about the source of cuticular hydrocarbons in stingless bees. We used behavioural recognition tests and cuticle chemical investigation to elucidate the role of endogenous and environmentally based cues for nestmate recognition in the stingless bee Frieseomelitta varia. We found that although newly emerged workers present specific cuticle patterns according to their nest origin, these compounds are not used for nestmate recognition, since newly emerged workers are broadly accepted in different colonies. The cerumen used in nest construction played an important role in recognition behaviour. Twenty minutes of contact with foreign cerumen was sufficient to increase the rejection rates of nestmates and separate the groups of workers according to their chemical profile. On the other hand, tests of feeding on a common diet showed no effect on chemical cuticle pattern or recognition behaviour. (C) 2010 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

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The application of information technologies (specially the Internet, Web 2.0 and social tools) make informal learning more visible. This kind of learning is not linked to an institution or a period of time, but it is important enough to be taken into account. On the one hand, learners should be able to communicate to the institutions they are related to, what skills they possess, whether they were achieved in a formal or informal way. On the other hand the companies and educational institutions need to have a deeper knowledge about the competencies of their staff. The TRAILER project provides a methodology supported by a technological framework to facilitate communication about informal learning between businesses, employees and learners. The paper presents the project and some of the work carried out, an exploratory analysis about how informal learning is considered and the technological framework proposed. Whilst challenges remain in terms of establishing the meaningfulness of technological engagement for employees and businesses, the continuing transformation of the social, technological and educational environment is likely to lead to greater emphasis for the effective exploitation of informal learning.

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Dissertation presented to obtain the Ph.D degree in Chemistry

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Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

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Vision-based hand gesture recognition is an area of active current research in computer vision and machine learning. Being a natural way of human interaction, it is an area where many researchers are working on, with the goal of making human computer interaction (HCI) easier and natural, without the need for any extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them, for example, to convey information. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Hand gestures are a powerful human communication modality with lots of potential applications and in this context we have sign language recognition, the communication method of deaf people. Sign lan- guages are not standard and universal and the grammars differ from country to coun- try. In this paper, a real-time system able to interpret the Portuguese Sign Language is presented and described. Experiments showed that the system was able to reliably recognize the vowels in real-time, with an accuracy of 99.4% with one dataset of fea- tures and an accuracy of 99.6% with a second dataset of features. Although the im- plemented solution was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.

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Macrophages and muscle cells are the main targets for invasion of Trypanosoma cruzi. Ultrastructural studies of this phenomenon in vitro showed that invasion occurs by endocytosis, with attachment and internalization being mediated by different components capable of recognizing epi-or trypomastigotes (TRY). A parasitophorus vacuole was formed in both cell types, thereafter fusing with lysosomes. Then, the mechanism of T. cruzi invasion of host cells (HC) is essentially similar (during a primary infection in the abscence of a specific immune response), regardless of wether the target cell is a professional or a non-professional phagocytic cell. Using sugars, lectins, glycosidases, proteinases and proteinase inhibitors, we observed that the relative balance between exposed sialic acid and galactose/N-acetyl galactosamine (GAL) residues on the TRY surface, determines the parasite's capacity to invade HC, and that lectin-mediated phagocytosis with GAL specificity is important for internalization of T. cruzi into macrophages. On the other hand, GAL on the surface to heart muscle cells participate on TRY adhesion. TRY need to process proteolytically both the HC and their own surface, to expose the necessary ligands and receptors that allow binding to, and internalization in the host cell. The diverse range of molecular mechanisms which the parasite could use to invade the host cell may correspond to differences in the available "receptors"on the surface of each specific cell type. Acute phase components, with lectin or proteinase inhibitory activities (a-macroglobulins), may also be involved in T. cruzi-host cell interaction.

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This study proposes a theoretical model describing the electrostatically driven step of the alpha 1 b-adrenergic receptor (AR)-G protein recognition. The comparative analysis of the structural-dynamics features of functionally different receptor forms, i.e., the wild type (ground state) and its constitutively active mutants D142A and A293E, was instrumental to gain insight on the receptor-G protein electrostatic and steric complementarity. Rigid body docking simulations between the different forms of the alpha 1 b-AR and the heterotrimeric G alpha q, G alpha s, G alpha i1, and G alpha t suggest that the cytosolic crevice shared by the active receptor and including the second and the third intracellular loops as well as the cytosolic extension of helices 5 and 6, represents the receptor surface with docking complementarity with the G protein. On the other hand, the G protein solvent-exposed portions that recognize the intracellular loops of the activated receptors are the N-terminal portion of alpha 3, alpha G, the alpha G/alpha 4 loop, alpha 4, the alpha 4/beta 6 loop, alpha 5, and the C-terminus. Docking simulations suggest that the two constitutively active mutants D142A and A293E recognize different G proteins with similar selectivity orders, i.e., G alpha q approximately equal to G alpha s > G alpha i > G alpha t. The theoretical models herein proposed might provide useful suggestions for new experiments aiming at exploring the receptor-G protein interface.

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Social identity is a double-edged sword. On the one hand, identifying with a social group is a prerequisite for the sharing of common norms and values, solidarity, and collective action. On the other hand, in-group identification often goes together with prejudice and discrimination. Today, these two sides of social identification underlie contradictory trends in the way European nations and European nationals relate to immigrants and immigration. Most European countries are becoming increasingly multicultural, and anti-discrimination laws have been adopted throughout the European Union, demonstrating a normative shift towards more social inclusion and tolerance. At the same time, racist and xenophobic attitudes still shape social relations, individual as well as collective behaviour (both informal and institutional), and political positions throughout Europe. The starting point for this chapter is Sanchez-Mazas' (2004) interactionist approach to the study of racism and xenophobia, which in turn builds on Axel Honneth's (1996) philosophical theory of recognition. In this view, the origin of attitudes towards immigrants cannot be located in one or the other group, but in a dynamic of mutual influence. Sanchez-Mazas' approach is used as a general framework into which we integrate social psychological approaches of prejudice and recent empirical findings examining minority-majority relations. We particularly focus on the role of national and European identities as antecedents of anti-immigrant attitudes held by national majorities. Minorities' reactions to denials of recognition are also examined. We conclude by delineating possible social and political responses to prejudice towards immigrants.

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The case of a professional tennis player presenting exercise-induced hand pain with late appearance of digital blanching is reported. A bilateral hypothenar hammer syndrome and stenosis of the common palmar digital arteries close to the head of the metacarpals where the racket handle exerts its maximal force was observed with arteriography. As the patient decided to stop tennis practice, the condition improved without any medication. Six months after stopping tennis he was symptom free. Three conclusions can be drawn from this case report: 1) arteries of both hands can be injured by intense tennis practice, 2) pain in the dominant hand during tennis practice can be due to arterial insufficiency even in the absence of digital blanching which is a sign of severity, 3) hypothenar hammer syndrome is the main cause but stenosis of the common palmar digital arteries can possibly contribute to the ischemic phenomenon. Early recognition is important to avoid ineffective treatment and permanent symptoms. Therefore, we recommend an arterial examination in tennis players suffering from exercise-induced hand pain even in the absence of digital blanching which can be only a late manifestation.

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The visualization of tools and manipulable objects activates motor-related areas in the cortex, facilitating possible actions toward them. This pattern of activity may underlie the phenomenon of object affordance. Some cortical motor neurons are also covertly activated during the recognition of body parts such as hands. One hypothesis is that different subpopulations of motor neurons in the frontal cortex are activated in each motor program; for example, canonical neurons in the premotor cortex are responsible for the affordance of visual objects, while mirror neurons support motor imagery triggered during handedness recognition. However, the question remains whether these subpopulations work independently. This hypothesis can be tested with a manual reaction time (MRT) task with a priming paradigm to evaluate whether the view of a manipulable object interferes with the motor imagery of the subject's hand. The MRT provides a measure of the course of information processing in the brain and allows indirect evaluation of cognitive processes. Our results suggest that canonical and mirror neurons work together to create a motor plan involving hand movements to facilitate successful object manipulation.

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Convolutional Neural Networks (CNN) have become the state-of-the-art methods on many large scale visual recognition tasks. For a lot of practical applications, CNN architectures have a restrictive requirement: A huge amount of labeled data are needed for training. The idea of generative pretraining is to obtain initial weights of the network by training the network in a completely unsupervised way and then fine-tune the weights for the task at hand using supervised learning. In this thesis, a general introduction to Deep Neural Networks and algorithms are given and these methods are applied to classification tasks of handwritten digits and natural images for developing unsupervised feature learning. The goal of this thesis is to find out if the effect of pretraining is damped by recent practical advances in optimization and regularization of CNN. The experimental results show that pretraining is still a substantial regularizer, however, not a necessary step in training Convolutional Neural Networks with rectified activations. On handwritten digits, the proposed pretraining model achieved a classification accuracy comparable to the state-of-the-art methods.

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Handwritten character recognition is always a frontier area of research in the field of pattern recognition and image processing and there is a large demand for OCR on hand written documents. Even though, sufficient studies have performed in foreign scripts like Chinese, Japanese and Arabic characters, only a very few work can be traced for handwritten character recognition of Indian scripts especially for the South Indian scripts. This paper provides an overview of offline handwritten character recognition in South Indian Scripts, namely Malayalam, Tamil, Kannada and Telungu

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The objective of the study is to develop a hand written character recognition system that could recognisze all the characters in the mordern script of malayalam language at a high recognition rate

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In the present study, to shed light on a role of positional error correction mechanism and prediction mechanism in the proactive control discovered earlier, we carried out a visual tracking experiment, in which the region where target was shown, was regulated in a circular orbit. Main results found in this research were following. Recognition of a time step, obtained from the environmental stimuli, is required for the predictive function. The period of the rhythm in the brain obtained from environmental stimuli is shortened about 10%, when the visual information is cut-off. The shortening of the period of the rhythm in the brain accelerates the motion as soon as the visual information is cut-off, and lets the hand motion precedes the target motion. Although the precedence of the hand in the blind region is reset by the environmental information when the target enters the visible region, the hand precedes in average the target when the predictive mechanism dominates the error-corrective mechanism.