5 resultados para Adaptive system theory
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
The nurses in the hemodialysis has an important role in the nursing process implementation, in the context of a theoretical referential. Among the nursing theories, highlights the Roy´s adaptations model, who considers a person as an holistic adaptive system that aims to adapt customers to different living conditions. Thus, it is believed that the Roy´s nursing process will guide nursing care to patients on dialysis. Therefore, the study aimed to analyze the nursing diagnosis present in patients with chronic kidney disease on hemodialysis based on the theoretical model of Roy and NANDA-International. Descriptive and cros-sectional study, performed at a dialysis center in a city in northeastern Brazil. Sample of 178 patients and consecutive sampling by convenience. Data collection ocurred from October/2011 until February/2012, through interview and physical examination forms. Data analysis was initiated by clinical reasoning, diagnosis judgment and similarity relation. Then, the data were entered into SPSS program, 16.0 version, generating descriptive statistics. The project was approved by the Ethics Research Committee (protocol nº 115/11) with a Presentation Certificate for Ethics Appreciation (in 0139.0.051.000-111) and was funded by the Universal edict MCT / CNPq 14/2010. The results revealed that most patients were male (52.2%), married (62.9%) and residents in the Natal´s metropolitan region (54.5%). The mean age was 46.6 years and the years of study, 8,5. Regarding nursing diagnosis obtained an average of 6.6, especially: Risk of Infection (100%), excessive fluid volume (99.4%) and hypothermia (61.8%). On the other hand the adaptive problems average was 6.4, and the most common: intracellular fluid retention (99.4%); Hyperkalemia (64.6%); Hypothermia (61.8%) and edema (53.9%). Were established 20 similarity relations between the NANDA-International nursing diagnosis and adaptive problems of Roy, namely: risk of falls / injury risk and potential for injury, impaired physical mobility and walking mobility and / or restricted coordination, dressing self-care deficit and loss of self-care ability; hypothermia and hypothermia; impaired skin integrity and impaired skin integrity; excessive fluid volume and intracellular fluid retention / Hyperkalemia / Hypocalcemia / edema; imbalanced nutrition: less than body requirements and Nutrition less than the body's needs; constipation and constipation, acute pain and acute pain, chronic pain and chronic pain, sensorial perception disturbed: visual, tactile and auditory disabilities and a primary sense: sight, hearing and tactile; sleep deprivation and insomnia, fatigue and intolerance to activities; ineffective self health and fails in the role; sexual dysfunction and sexual dysfunction; situational low self-esteem and low self-esteem, and diarrhea and diarrhea. We conclude that there is similarity between the typologies and was required a model´s analysis, because they present different ways to establish the nursing diagnosis. Moreover, the nursing process use, under the context of a theory and a classification system, subsidizes the care and contributes to the strengthening of nursing science
Resumo:
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
Resumo:
The control, automation and optimization areas help to improve the processes used by industry. They contribute to a fast production line, improving the products quality and reducing the manufacturing costs. Didatic plants are good tools for research in these areas, providing a direct contact with some industrial equipaments. Given these capabilities, the main goal of this work is to model and control a didactic plant, which is a level and flow process control system with an industrial instrumentation. With a model it is possible to build a simulator for the plant that allows studies about its behaviour, without any of the real processes operational costs, like experiments with controllers. They can be tested several times before its application in a real process. Among the several types of controllers, it was used adaptive controllers, mainly the Direct Self-Tuning Regulators (DSTR) with Integral Action and the Gain Scheduling (GS). The DSTR was based on Pole-Placement design and use the Recursive Least Square to calculate the controller parameters. The characteristics of an adaptive system was very worth to guarantee a good performance when the controller was applied to the plant
Resumo:
One way to deal with the high complexity of current software systems is through selfadaptive systems. Self-adaptive system must be able to monitor themselves and their environment, analyzing the monitored data to determine the need for adaptation, decide how the adaptation will be performed, and finally, make the necessary adjustments. One way to perform the adaptation of a system is generating, at runtime, the process that will perform the adaptation. One advantage of this approach is the possibility to take into account features that can only be evaluated at runtime, such as the emergence of new components that allow new architectural arrangements which were not foreseen at design time. In this work we have as main objective the use of a framework for dynamic generation of processes to generate architectural adaptation plans on OSGi environment. Our main interest is evaluate how this framework for dynamic generation of processes behave in new environments
Resumo:
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