97 resultados para Tarefas motrizes


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One of the Primary Health Care strategies for adolescent health is the growth and development follow-up and the early detection of overweight adolescents. Even though the School Health Program in Brazil proposes to evaluate the nutritional state of the school population in the corresponding community health units, not all cities have adhered to the Program and many nurses do not recognize overweight as a problem in their territory. The objective of the study was to identify the nurse´s participation in the screening of overweight adolescent students in their work territory. Cross sectional study conducted in eight state supported schools of the municipality of Natal/RN and in four Primary Health Units. The total student population was 27.277. A stratified sample was statistically calculated based on the student population of the four city geographical zones: 112 North , 74 West; 108 East; and 78 South, totalizing 372 adolescents. The students were selected by a probability process where eight schools were first selected, two per district, until the number per subsample in each district was reached. Four primary health nurses, responsible for the health units were included. Two instruments were used for data collection, a screening questionnaire and a semi-structured interview form for questioning of the nurses. The content of both instruments was validated. Anthropometric and health data were collected from the students and analyzed with descriptive and analytical statistics. Interview data were transcribed and submitted to content analysis. The nursing diagnosis of overweight was identified in 50 (13,5%) of the adolescents and its association with consumption of foods that have cardiovascular risk (canned foods, pasta and fried food). An association of the nursing diagnosis was identified with family history (diabetes, hypertension, obesity, and kidney disease). The nurses judged that care of overweight adolescents was important but noted difficulties because of the absence of this population in the health units, because of their work overload, and the lack of school articulation. The nurses do not have impacting actions with this population and delegate the responsibility to other professionals. It is concluded that overweight is a nutritional problem relevant to the adolescent school population in Natal/RN, with a 13,5% prevalence and that it is related to food consumption with cardiovascular risk and family health history. The nurses consider overweight as an important public health problem but do not envision ways to maintain linkage with adolescents and with the school to promote the needed care

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The aim of this work is the numerical simulation of the mechanical performance of concrete affected by Alkali-Aggregate Reaction or RAA, reported by Stanton in 1940. The RAA has aroused attention in the context of Civil Engineering from the early 80, when they were reported consequences of his swelling effect in concrete structures, including cracking, failure and loss of serviceability. Despite the availability of experimental results the problem formulation still lacks refinement so that your solution remains doubtful. The numerical simulation is important resource for the assessment of damages in structures caused by the reaction, and their recoveries The tasks of support of this work were performed by means of the finite element approach, about orthotropic non-linear formulation, and, thermodynamic model of deformation by RAA. The results obtained revealed that the swelling effect of RAA induced decline of the mechanical performance of concrete by decreasing the margin of safety prior to the material failure. They showed that the temperature influences, exclusively, the kinetics of the reaction, so that the failure was the more precocious the higher the temperature of the solid mass of concrete

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This dissertation presents a discussion on the level of risk awareness of students who have welding practice in the laboratories at CEFET/PI, both in Teresina and Floriano. Its main goal is to investigate risk factors involving students, teachers and employees that work in these laboratories. It s an empirical survey, held among a certain amount of students from the course in Mechanic Technology. For data analysis, the concept of risk was compared to the students direct measure of perception. The main results suggest the students must be better informed, more risk aware and more competent, in order to avoid accidents. They also point to a strong need for a more formal and effective performance to assure full consciousness about the risks involving the welding practice.

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This work discusses the environmental management thematic, on the basis of ISO 14001 standard and learning organization. This study is carried through an exploratory survey in a company of fuel transport, located in Natal/RN. The objective of this research was to investigate the practices of environmental management, carried through in the context of an implemented ISO 14001 environmental management system, in the researched organization, from the perspective of the learning organization. The methodology used in this work is supported in the quantitative method, combining the exploratory and descriptive types, and uses the technique of questionnaires, having as scope of the research, the managers, employee controlling, coordinators, supervisors and - proper and contracted - of the company. To carry through the analysis of the data of this research, it was used software Excel and Statistical version 6.0. The analysis of the data is divided in two parts: descriptive analysis and analysis of groupings (clusters). The results point, on the basis of the studied theory, as well as in the results of the research, that the implemented ISO 14001 environmental system in the searched organization presents elements that promote learning organization. From the results, it can be concluded that the company uses external information in the decision taking on environmental problems; that the employees are mobilized to generate ideas and to collect n environmental information and that the company has carried through partnerships in the activities of the environmental area with other companies. All these item cited can contribute for the generation of knowledge of the organization. It can also be concluded that the company has evaluated environmental errors occurrences in the past, as well as carried through environmental benchmarking. These practical can be considered as good ways of the company to acquire knowledge. The results also show that the employees have not found difficulties in the accomplishment of the tasks when the manager of its sector is not present. This result can demonstrate that the company has a good diffusion of knowledge

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The problem dealt with in this study concerns the analysis of bus drivers' working situation. It stemmed from the need to identify the difficulties faced by these professionals in accomplishing the results expected by the company. A case study was carried out in a public transportation company in the city of Natal. Records and observations made in the workplace, alongside perfomance indicators, such as absenteeism tax, staff turnover and traffic accidents, revealed problems in their activity. It was made clear that, in the company being studied, absenteeism was related to health problems, particularly psychiatric and musculoskeletal disorders, and that although the indicators of traffic accidents and staff turnover have declined over the years, they are still elevated. The interviews involved 50 of the 124 drivers who worked directly in the service, and contained questions covering eleven factors related to the drivers' work. They indicated a gap between the prescribed work and the work actually done, in that there were a series of embarassing or stressful situations involving traffic, itinerary length, road conditions, vehicle maintenance, physical environment (bus terminus), job post and supervision policies. On the other hand, factors such as enjoying driving, the work itself and being with workmates positively influenced the drivers' working conditions. In the propositions of the administration and human resources subsystems, some alternatives were found in order to remodel this activity

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This study evaluates the level of accessibility for people with visual impairment (blindness and low vision) hotels in the city of Natal-RN, Brazil, and provides principles, guidelines and means of projective make hotels accessible, to promote comfort, autonomy and security of these people. We used a qualitative research methodology and quantitative trait descriptive, analytical and interpretive. Was taken as a base for field studies Ergonomic Analysis of Work, beginning with a study of the demands of accessibility of hotels and analyzing the modeling activity in these establishments through the application of interactional and observational techniques, such as film, photographic records, conversational actions and observation protocols. A protocol was developed and applied to evaluate the compliance of accessibility of hotels in the face of Brazilian technical standard NBR 9050 (2004). We used methods of Cognitive Task Analysis (CTA) associated with simulated activities to identify the processes of decision making and analyzing the observables of the activities performed by people with visual impairment (POS). Interviews were conducted with people who are blind and low vision in various cities in order to meet accessibility difficulties they faced in hotels and recommendations for improvement that they indicate. The mapping results showed that of 16 hotels 4 and 5 star studied in Natal-RN, reached only 7% of the 50 items of the protocol, while none of them reached 70% of the items. About the results obtained in simulated activities and analyzed from the ATC, we saw that the hotel where it was performed this step shows a need to adequately address the guests with visual impairments

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The purpose of this paper is to identify the utilization of two models of orthotics used in the conservative treatment of rizartrose in patients/consumers that were referred by the medical clinic to the LAI (Laboratory of Integrated Accessibility). It describes this group s perception related to the functional aspects of the two models, evaluates the value of the product attributed by the patient/consumer and describes the importance attributed to each model. The research s objective consists in identifying which model this is preferred from the point of view by the patients that use either the dorsal or ventral models used in the conservative treatment of rizartrose . This work is then based on the exploratory research through the investigation of the bibliography available and in the research field. The research field used the case study methodology to investigate the phenomenon in the real context. The data were collected using a patient questionnaire during two times after the use of the dorsal orthotic and after the use of the ventral orthotic. The questionnaire was used to identify the relationship between the patients/consumers and the two different types of orthotics. A general descriptive analysis was used in order to verify the patient s abilities executing certain activities daily living using the dorsal and ventral orthotics, the product s functional aspects and its value from the patient s/consumer s point of view. The results show that the preference for the dorsal or ventral models is determined by the individual needs of each person. The results also show that other variables, such as the use of the orthotic on the dominant or non-dominant hand, play a role in the preferred model by the patient/consumer and need to be further investigated

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We propose a new paradigm for collective learning in multi-agent systems (MAS) as a solution to the problem in which several agents acting over the same environment must learn how to perform tasks, simultaneously, based on feedbacks given by each one of the other agents. We introduce the proposed paradigm in the form of a reinforcement learning algorithm, nominating it as reinforcement learning with influence values. While learning by rewards, each agent evaluates the relation between the current state and/or action executed at this state (actual believe) together with the reward obtained after all agents that are interacting perform their actions. The reward is a result of the interference of others. The agent considers the opinions of all its colleagues in order to attempt to change the values of its states and/or actions. The idea is that the system, as a whole, must reach an equilibrium, where all agents get satisfied with the obtained results. This means that the values of the state/actions pairs match the reward obtained by each agent. This dynamical way of setting the values for states and/or actions makes this new reinforcement learning paradigm the first to include, naturally, the fact that the presence of other agents in the environment turns it a dynamical model. As a direct result, we implicitly include the internal state, the actions and the rewards obtained by all the other agents in the internal state of each agent. This makes our proposal the first complete solution to the conceptual problem that rises when applying reinforcement learning in multi-agent systems, which is caused by the difference existent between the environment and agent models. With basis on the proposed model, we create the IVQ-learning algorithm that is exhaustive tested in repetitive games with two, three and four agents and in stochastic games that need cooperation and in games that need collaboration. This algorithm shows to be a good option for obtaining solutions that guarantee convergence to the Nash optimum equilibrium in cooperative problems. Experiments performed clear shows that the proposed paradigm is theoretical and experimentally superior to the traditional approaches. Yet, with the creation of this new paradigm the set of reinforcement learning applications in MAS grows up. That is, besides the possibility of applying the algorithm in traditional learning problems in MAS, as for example coordination of tasks in multi-robot systems, it is possible to apply reinforcement learning in problems that are essentially collaborative

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The goal of this work is to propose a SLAM (Simultaneous Localization and Mapping) solution based on Extended Kalman Filter (EKF) in order to make possible a robot navigates along the environment using information from odometry and pre-existing lines on the floor. Initially, a segmentation step is necessary to classify parts of the image in floor or non floor . Then the image processing identifies floor lines and the parameters of these lines are mapped to world using a homography matrix. Finally, the identified lines are used in SLAM as landmarks in order to build a feature map. In parallel, using the corrected robot pose, the uncertainty about the pose and also the part non floor of the image, it is possible to build an occupancy grid map and generate a metric map with the obstacle s description. A greater autonomy for the robot is attained by using the two types of obtained map (the metric map and the features map). Thus, it is possible to run path planning tasks in parallel with localization and mapping. Practical results are presented to validate the proposal

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Large efforts have been maden by the scientific community on tasks involving locomotion of mobile robots. To execute this kind of task, we must develop to the robot the ability of navigation through the environment in a safe way, that is, without collisions with the objects. In order to perform this, it is necessary to implement strategies that makes possible to detect obstacles. In this work, we deal with this problem by proposing a system that is able to collect sensory information and to estimate the possibility for obstacles to occur in the mobile robot path. Stereo cameras positioned in parallel to each other in a structure coupled to the robot are employed as the main sensory device, making possible the generation of a disparity map. Code optimizations and a strategy for data reduction and abstraction are applied to the images, resulting in a substantial gain in the execution time. This makes possible to the high level decision processes to execute obstacle deviation in real time. This system can be employed in situations where the robot is remotely operated, as well as in situations where it depends only on itself to generate trajectories (the autonomous case)

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In this work, we present a hardware-software architecture for controlling the autonomous mobile robot Kapeck. The hardware of the robot is composed of a set of sensors and actuators organized in a CAN bus. Two embedded computers and eigth microcontroller based boards are used in the system. One of the computers hosts the vision system, due to the significant processing needs of this kind of system. The other computer is used to coordinate and access the CAN bus and to accomplish the other activities of the robot. The microcontroller-based boards are used with the sensors and actuators. The robot has this distributed configuration in order to exhibit a good real-time behavior, where the response time and the temporal predictability of the system is important. We adopted the hybrid deliberative-reactive paradigm in the proposed architecture to conciliate the reactive behavior of the sensors-actuators net and the deliberative activities required to accomplish more complex tasks

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This work introduces a new method for environment mapping with three-dimensional information from visual information for robotic accurate navigation. Many approaches of 3D mapping using occupancy grid typically requires high computacional effort to both build and store the map. We introduce an 2.5-D occupancy-elevation grid mapping, which is a discrete mapping approach, where each cell stores the occupancy probability, the height of the terrain at current place in the environment and the variance of this height. This 2.5-dimensional representation allows that a mobile robot to know whether a place in the environment is occupied by an obstacle and the height of this obstacle, thus, it can decide if is possible to traverse the obstacle. Sensorial informations necessary to construct the map is provided by a stereo vision system, which has been modeled with a robust probabilistic approach, considering the noise present in the stereo processing. The resulting maps favors the execution of tasks like decision making in the autonomous navigation, exploration, localization and path planning. Experiments carried out with a real mobile robots demonstrates that this proposed approach yields useful maps for robot autonomous navigation

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Simulations based on cognitively rich agents can become a very intensive computing task, especially when the simulated environment represents a complex system. This situation becomes worse when time constraints are present. This kind of simulations would benefit from a mechanism that improves the way agents perceive and react to changes in these types of environments. In other worlds, an approach to improve the efficiency (performance and accuracy) in the decision process of autonomous agents in a simulation would be useful. In complex environments, and full of variables, it is possible that not every information available to the agent is necessary for its decision-making process, depending indeed, on the task being performed. Then, the agent would need to filter the coming perceptions in the same as we do with our attentions focus. By using a focus of attention, only the information that really matters to the agent running context are perceived (cognitively processed), which can improve the decision making process. The architecture proposed herein presents a structure for cognitive agents divided into two parts: 1) the main part contains the reasoning / planning process, knowledge and affective state of the agent, and 2) a set of behaviors that are triggered by planning in order to achieve the agent s goals. Each of these behaviors has a runtime dynamically adjustable focus of attention, adjusted according to the variation of the agent s affective state. The focus of each behavior is divided into a qualitative focus, which is responsible for the quality of the perceived data, and a quantitative focus, which is responsible for the quantity of the perceived data. Thus, the behavior will be able to filter the information sent by the agent sensors, and build a list of perceived elements containing only the information necessary to the agent, according to the context of the behavior that is currently running. Based on the human attention focus, the agent is also dotted of a affective state. The agent s affective state is based on theories of human emotion, mood and personality. This model serves as a basis for the mechanism of continuous adjustment of the agent s attention focus, both the qualitative and the quantative focus. With this mechanism, the agent can adjust its focus of attention during the execution of the behavior, in order to become more efficient in the face of environmental changes. The proposed architecture can be used in a very flexibly way. The focus of attention can work in a fixed way (neither the qualitative focus nor the quantitaive focus one changes), as well as using different combinations for the qualitative and quantitative foci variation. The architecture was built on a platform for BDI agents, but its design allows it to be used in any other type of agents, since the implementation is made only in the perception level layer of the agent. In order to evaluate the contribution proposed in this work, an extensive series of experiments were conducted on an agent-based simulation over a fire-growing scenario. In the simulations, the agents using the architecture proposed in this work are compared with similar agents (with the same reasoning model), but able to process all the information sent by the environment. Intuitively, it is expected that the omniscient agent would be more efficient, since they can handle all the possible option before taking a decision. However, the experiments showed that attention-focus based agents can be as efficient as the omniscient ones, with the advantage of being able to solve the same problems in a significantly reduced time. Thus, the experiments indicate the efficiency of the proposed architecture

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Because of social exclusion in Brazil and having as focus the digital inclusion, was started in Federal University of Rio Grande do Norte a project that could talk, at the same time, about concepts of collaborative learning and educational robotics , focused on children digitally excluded. In this context was created a methodology that approaches many subjects as technological elements (e. g. informatics and robotics) and school subjects (e. g. Portuguese, Mathematics, Geography, History), contextualized in everyday situations. We observed educational concepts of collaborative learning and the development of capacities from those students, as group work, logical knowledge and learning ability. This paper proposes an educational software for robotics teaching called RoboEduc, created to be used by children digitally excluded from primary school. Its introduction prioritizes a friendly interface, that makes the concepts of robotics and programming easy and fun to be taught. With this new tool, users without informatics or robotics previous knowledge are able to control a robot, previously set with Lego kits, or even program it to carry some activities out. This paper provides the implementation of the second version of the software. This version presents the control of the robot already used. After were implemented the different levels of programming linked to the many learning levels of the users and their different interfaces and functions. Nowadays, has been implemented the third version, with the improvement of each one of the mentioned stages. In order to validate, prove and test the efficience of the developed methodology to the RoboEduc, were made experiments, through practice of robotics, with children for fourth and fifth grades of primary school at the City School Professor Ascendino de Almeida, in the suburb of Natal (west zone), Rio Grande do Norte. As a preliminary result of the current technology, we verified that the use of robots associated with a well elaborated software can be spread to users that know very little about the subject, without the necessity of previous advanced technology knowledges. Therefore, they showed to be accessible and efficient tools in the process of digital inclusion

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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