Vivência do enfermeiro no cuidado humano na Unidade de Terapia Intensiva adulto

The purpose of the study was to understand the nurse s experience with human care in the Adult Intensive Care Unit (ICU). The objective was to describe the nurse s experience in caring for patients in the ICU and to analyze the nurse s perception of the care provided. The study is a descriptive inquiry of qualitative nature with a phenomenological approach. We interviewed eight nurses, 26 and 43 years of age, that provide care in the ICU of a private hospital in Natal/RN, during the manths of July and August of 2006. We analyzed the data acording to the method of Colaizzi. Four categories emerged from the data: The search for the maintenance of life, The technicalbureaucratic activities, The recognition of the patient s individuality, and the expression of the nurse s feelings.The analysis allowed us to describe the lived experience of the nurse s care the ICU and to comprehend the structural elements of this experience. The results showed that the nurse s experience presents itself as a process of the several actions and feelings that occur while the social relations between the patient and the nurse develop. Finally, we understand that although the study shows an experience based on a biological model of health, these nurses possess an initial idea on how to reach humanized care in its essence, needing, however, of an institutional policy that favors this practice, an educational formation that prepares her to recognize her field of work as a place of continuous learning and an understanding of the health model as an ally in the search of humanized care

A Acessibilidade como veículo de inclusão social: proposta de dispositivo computacional para os deficientes visuais da cidade de Natal/RN

This study aims to propose a computing device mechanism which is capable to permit a tactile communication between individuals with visual impairment (blindness or low vision) through the Internet or through a local area network (LAN - Local Network Address). The work was developed under the research projects that currently are realized in the LAI (Laboratory of Integrated Accessibility) of the Federal University of Rio Grande do Norte. This way, the research was done in order to involve a prototype capable to recognize geometries by students considered blind from the Institute of Education and Rehabilitation of Blind of Rio Grande do Norte (IERC-RN), located in Alecrim neighborhood, Natal/RN. Besides this research, another prototype was developed to test the communication via a local network and Internet. To analyze the data, a qualitative and quantitative approach was used through simple statistical techniques, such as percentages and averages, to support subjective interpretations. The results offer an analysis of the extent to which the implementation can contribute to the socialization and learning of the visually impaired. Finally, some recommendations are suggested for the development of future researches in order to facilitate the proposed mechanism.

Modelagem situada de metodologia da oficina de desenho de renda de bilros

The bobbin lace, a secular art in the process of extinction in the Village Ponta Negra in Natal, Brazil, was one of the main means of income generation for some families in town, but over time, there was growing disaffection of the younger generation to learn and practice this art, due to the high demand of time for production and insufficient and not guaranteed financial return . This project aims to promote the recovery of control over the product in the production of bobbin lace in the village of Ponta Negra, by design and implementation of a workshop for the transfer of drawing techniques in the Production Center of Craft in Village of Ponta Negra. This design was based on the methodology of Ergonomic Work Analysis and in the concepts of anthropotechnology and technology social. The ergonomic analysis, by advocating and enforcing the social and technical building, was essential for the modeling of this workshop, as allowed the construction of a social participative device , with the participation of the community groups and the external group of researchers, in a process of social construction technique. As a result, it was observed that the transfer of technical design of bobbin lace molds came to complement the learning of art office, providing solutions to promote the sustainable development of the group of tenants, in an attempt to reduce the risk of extinction eminent, and also contributed to reactivate a network of economic activities interconnected to the craft, such as the production of cushions, lace and easels

Balanced scorecard como ferramenta de gestão aplicada a unidade hospitalar privada

In this study the objective is to implant Balanced Scorecard administration for the development of a Strategic Map, for the support of the electric outlet of decisions in the administration of operations of an unit of attendance doctor-hospitalar. The present work presents a case study developed at a private hospital in the State of Rio Grande do Norte. The collection of data was developed after the analysis of the revision of the literature, and he/she had as critical judgement of evaluation used by the following Unit. The work is concluded in the proposition of a strategic map that elevates the return on investment (financial perspective), in the item profitability and growth. In the search of the customer's satisfaction (customer's perspective), that is nothing else than it already exists inside of the Unit in study, just needing to be organized and aligned with the executive picture and the other collaborators. The requirements competitiveness, information, innovation and technology (perspective of the internal processes), they were indispensable to eliminate the re-work, waste and to improve the automation. It is finally, the investment and development of innovation mechanisms, they enlarge important competitive advantage in the processes for creation of value, through the ability, attitude and knowledge (perspective of the learning and growth). As one of the results of this study a strategic map was developed, looked for in Balanced Scorecard, for support in the electric outlet of decisions of the administration of operations of an Unit Doctor- Healthcare

Gestão de organizações sem fins lucrativos: uma avaliação de desempenho através do balanced scorecard

The methodology Balanced Scorecard (BSC) focuses on the major critical issues of modern organizations, whether with or without profit. The measurement of the effective performance of the latter is by evaluating the successful implementation of organizational strategy. The aim of this paper is to present the development of a system of performance measurement strategy for a nonprofit organization, whose object of study is the Associação de Apoio as Comunidades do Campo - AACC, in the context of the BSC methodology of Kaplan and Norton. The methodology of this case study is an exploratory, descriptive and qualitative, and diagnose the coherence of the Strategy Map in an organization, based strategic planning from 2010 to 2012. Initially conducted a literature review covering the main aspects of strategy maps and performance evaluation involving the translation of the BSC and strategy evaluation. The main results of the proposed approach refers to evaluation of overall scores for each dimension of the BSC methodology, financial, customer, internal processes, learning and growth. These results are able to help the organization evaluate and revise their strategy and, in general, to adopt management methods more accurately. Data collection is centered on interviews with semi-structured questionnaire. The findings highlight on balancing and alignment of strategic objectives, low causality map, strategic communication insufficient and fragmented. For interviewees organizational culture is the biggest impediment to structuring a management model based on indicators and strategic process should be initiated by non-financial indicators gradually. The performance indicators of the AACC/RN portray more meritocracy operational procedures of social projects in the context of the Strategic Map determined in a shortterm over the long term. However, there is evidence of improved performance management and strategic taken as a basis of planning as both the strategic map structured. Therefore, the nonprofits need to adopt a form of management that enables planning, setting objectives and targets that provide the continuity of its activities, and generating instruments that can measure the financial performance and non-financial, in order to develop strategic actions for growth and sustainability

Melhoria de desempenho e ISO 9000: um estudo em empresas brasileiras do setor hoteleiro na perspectiva do Balanced Scorecard

This Thesis deals with the performance improvement on hotels that have adopted the ISO 9000 Quality Management Systems. It is researched the Brazilian hotels that have an ISO 9001 registration with an assessment form based on the Balanced Scorecard approach. The main findings are that ISO 9000 provided improvement on the performance of the hotels in general and also in all the BSC perspectives, and that are different perception on managers and directors, what suggests a need for a tool like BSC to register the performance improvements on the same basis. The Thesis contributes to provide information on the performance improvement in hotels, one of the claimed regarding the low ISO 9000 adoption rate in Brazilian hotels

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

Algoritmos inteligentes para auto-correção, auto-verificação e auto-validação de medidas em sensores

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

Dinâmica da Plasticidade Sináptica em neurônios do hipocampo durante ciclos de sono: um estudo computacional

Several research lines show that sleep favors memory consolidation and learning. It has been proposed that the cognitive role of sleep is derived from a global scaling of synaptic weights, able to homeostatically restore the ability to learn new things, erasing memories overnight. This phenomenon is typical of slow-wave sleep (SWS) and characterized by non-Hebbian mechanisms, i.e., mechanisms independent of synchronous neuronal activity. Another view holds that sleep also triggers the specific enhancement of synaptic connections, carrying out the embossing of certain mnemonic traces within a lattice of synaptic weights rescaled each night. Such an embossing is understood as the combination of Hebbian and non-Hebbian mechanisms, capable of increasing and decreasing respectively the synaptic weights in complementary circuits, leading to selective memory improvement and a restructuring of synaptic configuration (SC) that can be crucial for the generation of new behaviors ( insights ). The empirical findings indicate that initiation of Hebbian plasticity during sleep occurs in the transition of the SWS to the stage of rapid eye movement (REM), possibly due to the significant differences between the firing rates regimes of the stages and the up-regulation of factors involved in longterm synaptic plasticity. In this study the theories of homeostasis and embossing were compared using an artificial neural network (ANN) fed with action potentials recorded in the hippocampus of rats during the sleep-wake cycle. In the simulation in which the ANN did not apply the long-term plasticity mechanisms during sleep (SWS-transition REM), the synaptic weights distribution was re-scaled inexorably, for its mean value proportional to the input firing rate, erasing the synaptic weights pattern that had been established initially. In contrast, when the long-term plasticity is modeled during the transition SWSREM, an increase of synaptic weights were observed in the range of initial/low values, redistributing effectively the weights in a way to reinforce a subset of synapses over time. The results suggest that a positive regulation coming from the long-term plasticity can completely change the role of sleep: its absence leads to forgetting; its presence leads to a positive mnemonic change

Análise e síntese de antenas e superfícies seletivas de frequência utilizando computação evolucionária e inteligência de enxames

The frequency selective surfaces, or FSS (Frequency Selective Surfaces), are structures consisting of periodic arrays of conductive elements, called patches, which are usually very thin and they are printed on dielectric layers, or by openings perforated on very thin metallic surfaces, for applications in bands of microwave and millimeter waves. These structures are often used in aircraft, missiles, satellites, radomes, antennae reflector, high gain antennas and microwave ovens, for example. The use of these structures has as main objective filter frequency bands that can be broadcast or rejection, depending on the specificity of the required application. In turn, the modern communication systems such as GSM (Global System for Mobile Communications), RFID (Radio Frequency Identification), Bluetooth, Wi-Fi and WiMAX, whose services are highly demanded by society, have required the development of antennas having, as its main features, and low cost profile, and reduced dimensions and weight. In this context, the microstrip antenna is presented as an excellent choice for communications systems today, because (in addition to meeting the requirements mentioned intrinsically) planar structures are easy to manufacture and integration with other components in microwave circuits. Consequently, the analysis and synthesis of these devices mainly, due to the high possibility of shapes, size and frequency of its elements has been carried out by full-wave models, such as the finite element method, the method of moments and finite difference time domain. However, these methods require an accurate despite great computational effort. In this context, computational intelligence (CI) has been used successfully in the design and optimization of microwave planar structures, as an auxiliary tool and very appropriate, given the complexity of the geometry of the antennas and the FSS considered. The computational intelligence is inspired by natural phenomena such as learning, perception and decision, using techniques such as artificial neural networks, fuzzy logic, fractal geometry and evolutionary computation. This work makes a study of application of computational intelligence using meta-heuristics such as genetic algorithms and swarm intelligence optimization of antennas and frequency selective surfaces. Genetic algorithms are computational search methods based on the theory of natural selection proposed by Darwin and genetics used to solve complex problems, eg, problems where the search space grows with the size of the problem. The particle swarm optimization characteristics including the use of intelligence collectively being applied to optimization problems in many areas of research. The main objective of this work is the use of computational intelligence, the analysis and synthesis of antennas and FSS. We considered the structures of a microstrip planar monopole, ring type, and a cross-dipole FSS. We developed algorithms and optimization results obtained for optimized geometries of antennas and FSS considered. To validate results were designed, constructed and measured several prototypes. The measured results showed excellent agreement with the simulated. Moreover, the results obtained in this study were compared to those simulated using a commercial software has been also observed an excellent agreement. Specifically, the efficiency of techniques used were CI evidenced by simulated and measured, aiming at optimizing the bandwidth of an antenna for wideband operation or UWB (Ultra Wideband), using a genetic algorithm and optimizing the bandwidth, by specifying the length of the air gap between two frequency selective surfaces, using an optimization algorithm particle swarm

Uma contribuição ao estudo das categorias internas e de sua proliferação em redes ARTMAP

ART networks present some advantages: online learning; convergence in a few epochs of training; incremental learning, etc. Even though, some problems exist, such as: categories proliferation, sensitivity to the presentation order of training patterns, the choice of a good vigilance parameter, etc. Among the problems, the most important is the category proliferation that is probably the most critical. This problem makes the network create too many categories, consuming resources to store unnecessarily a large number of categories, impacting negatively or even making the processing time unfeasible, without contributing to the quality of the representation problem, i. e., in many cases, the excessive amount of categories generated by ART networks makes the quality of generation inferior to the one it could reach. Another factor that leads to the category proliferation of ART networks is the difficulty of approximating regions that have non-rectangular geometry, causing a generalization inferior to the one obtained by other methods of classification. From the observation of these problems, three methodologies were proposed, being two of them focused on using a most flexible geometry than the one used by traditional ART networks, which minimize the problem of categories proliferation. The third methodology minimizes the problem of the presentation order of training patterns. To validate these new approaches, many tests were performed, where these results demonstrate that these new methodologies can improve the quality of generalization for ART networks

RoboEduc: especificação de um software educacional para ensino da robótica às crianças como uma ferramenta de inclusão digital

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

Identificação não linear usando uma rede fuzzy wavelet neural network modificada

In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning ability and generalization of neural networks usually, providing more accurate models than those ones obtained by traditional networks. An extension of WNN networks is to combine the neuro-fuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) structure with wavelets, leading to generate the Fuzzy Wavelet Neural Network - FWNN structure. This network is very similar to ANFIS networks, with the difference that traditional polynomials present in consequent of this network are replaced by WNN networks. This paper proposes the identification of nonlinear dynamical systems from a network FWNN modified. In the proposed structure, functions only wavelets are used in the consequent. Thus, it is possible to obtain a simplification of the structure, reducing the number of adjustable parameters of the network. To evaluate the performance of network FWNN with this modification, an analysis of network performance is made, verifying advantages, disadvantages and cost effectiveness when compared to other existing FWNN structures in literature. The evaluations are carried out via the identification of two simulated systems traditionally found in the literature and a real nonlinear system, consisting of a nonlinear multi section tank. Finally, the network is used to infer values of temperature and humidity inside of a neonatal incubator. The execution of such analyzes is based on various criteria, like: mean squared error, number of training epochs, number of adjustable parameters, the variation of the mean square error, among others. The results found show the generalization ability of the modified structure, despite the simplification performed

Aplicação de sistemas multi-classificadores no diagnóstico de falhas em motores de indução trifásicos

Equipment maintenance is the major cost factor in industrial plants, it is very important the development of fault predict techniques. Three-phase induction motors are key electrical equipments used in industrial applications mainly because presents low cost and large robustness, however, it isn t protected from other fault types such as shorted winding and broken bars. Several acquisition ways, processing and signal analysis are applied to improve its diagnosis. More efficient techniques use current sensors and its signature analysis. In this dissertation, starting of these sensors, it is to make signal analysis through Park s vector that provides a good visualization capability. Faults data acquisition is an arduous task; in this way, it is developed a methodology for data base construction. Park s transformer is applied into stationary reference for machine modeling of the machine s differential equations solution. Faults detection needs a detailed analysis of variables and its influences that becomes the diagnosis more complex. The tasks of pattern recognition allow that systems are automatically generated, based in patterns and data concepts, in the majority cases undetectable for specialists, helping decision tasks. Classifiers algorithms with diverse learning paradigms: k-Neighborhood, Neural Networks, Decision Trees and Naïves Bayes are used to patterns recognition of machines faults. Multi-classifier systems are used to improve classification errors. It inspected the algorithms homogeneous: Bagging and Boosting and heterogeneous: Vote, Stacking and Stacking C. Results present the effectiveness of constructed model to faults modeling, such as the possibility of using multi-classifiers algorithm on faults classification

Modelos de dispositivos de microondas e ópticos através de redes neurais artificiais de alimentação direta

This dissertation contributes for the development of methodologies through feed forward artificial neural networks for microwave and optical devices modeling. A bibliographical revision on the applications of neuro-computational techniques in the areas of microwave/optical engineering was carried through. Characteristics of networks MLP, RBF and SFNN, as well as the strategies of supervised learning had been presented. Adjustment expressions of the networks free parameters above cited had been deduced from the gradient method. Conventional method EM-ANN was applied in the modeling of microwave passive devices and optical amplifiers. For this, they had been proposals modular configurations based in networks SFNN and RBF/MLP objectifying a bigger capacity of models generalization. As for the training of the used networks, the Rprop algorithm was applied. All the algorithms used in the attainment of the models of this dissertation had been implemented in Matlab