Qualidade em serviços de saúde: uma contribuição à definição de um modelo paramétrico e padrão de qualidade do tempo agendado para consulta ambulatorial

This work presents a study in quality of health care, with focus on consulting appointment. The main purpose is to define a statistical model and propose a quality grade of the consulting appointment time. The time considered is that from the day the patient get the appointment done to the day the consulting is realized. It is used reliability techniques and functions that has as main characteristic the analysis of data regarding the time of occurrence certain event. It is gathered a random sample of 1743 patients in the appointment system of a University Hospital - the Hospital Universitário Onofre Lopes - of the Federal University of Rio Grande do Norte, Brazil. The sample is randomly stratified in terms on clinical specialty. The data were analyzed against the parametric methods of the reliability statistics and the adjustment of the regression model resulted in the Weibull distribution being best fit to data. The quality grade proposed is based in the PAHO criteria for a consulting appointment and result that no clinic got the PAHO quality grade. The quality grade proposed could be used to define priority for improvement and as criteria to quality control

Qualidade em serviços de saúde: uma contribuição à definição de um modelo paramétrico e padrão de qualidade do tempo agendado para consulta ambulatorial

The knowledge management has received major attention from product designers because many of the activities within this process have to be creative and, therefore, they depend basically on the knowledge of the people who are involved in the process. Moreover, Product Development Process (PDP) is one of the activities in which knowledge management manifests in the most critical form once it had the intense application of the knowledge. As a consequence, this thesis analyzes the knowledge management aiming to improve the PDP and it also proposes a theoretical model of knowledge management. This model uses five steps (creation, maintenance, dissemination, utilization and discard) through the verification of the occurrence of four types of knowledge conversion (socialization, externalization, combination and internalization) that it will improve the knowledge management in this process. The intellectual capital in Small and Medium Enterprises (SMEs) managed efficiently and with the participation of all employees has become the mechanism of the creation and transference processes of knowledge, supporting and, consequently, improving the PDP. The expected results are an effective and efficient application of the proposed model for the creation of the knowledge base within an organization (organizational memory) aiming a better performance of the PDP. In this way, it was carried out an extensive analysis of the knowledge management (instrument of qualitative and subjective evaluation) within the Design department of a Brazilian company (SEBRAE/RN). This analysis aimed to know the state-of-the-art of the Design department regarding the use of knowledge management. This step was important in order to evaluate in the level of the evolution of the department related to the practical use of knowledge management before implementing the proposed theoretical model and its methodology. At the end of this work, based on the results of the diagnosis, a knowledge management system is suggested to facilitate the knowledge sharing within the organization, in order words, the Design department

Group Sequential Communication (GSC): Especificação e Análise de Desempenho de umMecanismo de Comunicação de Tempo Real Compatível ao Padrão IEEE 802.11/11e Aplicado à Automação Industrial

This thesis proposes the specification and performance analysis of a real-time communication mechanism for IEEE 802.11/11e standard. This approach is called Group Sequential Communication (GSC). The GSC has a better performance for dealing with small data packets when compared to the HCCA mechanism by adopting a decentralized medium access control using a publish/subscribe communication scheme. The main objective of the thesis is the HCCA overhead reduction of the Polling, ACK and QoS Null frames exchanged between the Hybrid Coordinator and the polled stations. The GSC eliminates the polling scheme used by HCCA scheduling algorithm by using a Virtual Token Passing procedure among members of the real-time group to whom a high-priority and sequential access to communication medium is granted. In order to improve the reliability of the mechanism proposed into a noisy channel, it is presented an error recovery scheme called second chance algorithm. This scheme is based on block acknowledgment strategy where there is a possibility of retransmitting when missing real-time messages. Thus, the GSC mechanism maintains the real-time traffic across many IEEE 802.11/11e devices, optimized bandwidth usage and minimal delay variation for data packets in the wireless network. For validation purpose of the communication scheme, the GSC and HCCA mechanisms have been implemented in network simulation software developed in C/C++ and their performance results were compared. The experiments show the efficiency of the GSC mechanism, especially in industrial communication scenarios.

Determinação dos parâmetros do controlador preditivo generalizado com função de pesos variante no tempo através de algoritmos genéticos

The predictive control technique has gotten, on the last years, greater number of adepts in reason of the easiness of adjustment of its parameters, of the exceeding of its concepts for multi-input/multi-output (MIMO) systems, of nonlinear models of processes could be linearised around a operating point, so can clearly be used in the controller, and mainly, as being the only methodology that can take into consideration, during the project of the controller, the limitations of the control signals and output of the process. The time varying weighting generalized predictive control (TGPC), studied in this work, is one more an alternative to the several existing predictive controls, characterizing itself as an modification of the generalized predictive control (GPC), where it is used a reference model, calculated in accordance with parameters of project previously established by the designer, and the application of a new function criterion, that when minimized offers the best parameters to the controller. It is used technique of the genetic algorithms to minimize of the function criterion proposed and searches to demonstrate the robustness of the TGPC through the application of performance, stability and robustness criterions. To compare achieves results of the TGPC controller, the GCP and proportional, integral and derivative (PID) controllers are used, where whole the techniques applied to stable, unstable and of non-minimum phase plants. The simulated examples become fulfilled with the use of MATLAB tool. It is verified that, the alterations implemented in TGPC, allow the evidence of the efficiency of this algorithm

Ajuste automático e otimização do tempo de espera (Idle time) em bombeio mecânico de petróleo

The present work presents an algorithm proposal, which aims for controlling and improving idle time to be applied in oil production wells equipped with beam pump. The algorithm was totally designed based on existing papers and data acquired from two Potiguar Basin pilot wells. Oil engineering concepts such as submergence, pump off, Basic Sediments and Water (BSW), Inflow Performance Relationship (IPR), reservo ir pressure, inflow pressure, among others, were included into the algorithm through a mathematical treatment developed from a typical well and then extended to the general cases. The optimization will increase the well production potential maximum utilization having the smallest number of pumping unit cycles directly reflecting on operational cost and electricity consumption reduction

Análise teórica e experimental de superfícies seletivas de freqüência e suas aplicações em antenas planares

This work presents a theoretical and numerical analysis of structures using frequency selective surfaces applied on patch antennas. The FDTD method is used to determine the time domain reflected fields. Applications of frequency selective surfaces and patch antennas cover a wide area of telecommunications, especially mobile communications, filters and WB antennas. scattering parameters are obteained from Fourier Transformer of transmited and reflected fields in time domain. The PML are used as absorbing boundary condition, allowing the determination of the fields with a small interference of reflections from discretized limit space. Rectangular patches are considered on dielectric layer and fed by microstrip line. Frequency selective surfaces with periodic and quasi-periodic structures are analyzed on both sides of antenna. A literature review of the use of frequency selective surfaces in patch antennas are also performed. Numerical results are also compared with measured results for return loss of analyzed structures. It is also presented suggestions of continuity to this work

Multi-resolução com fóvea móvel para redução e abstração de dados em tempo real

We propose a new approach to reduction and abstraction of visual information for robotics vision applications. Basically, we propose to use a multi-resolution representation in combination with a moving fovea for reducing the amount of information from an image. We introduce the mathematical formalization of the moving fovea approach and mapping functions that help to use this model. Two indexes (resolution and cost) are proposed that can be useful to choose the proposed model variables. With this new theoretical approach, it is possible to apply several filters, to calculate disparity and to obtain motion analysis in real time (less than 33ms to process an image pair at a notebook AMD Turion Dual Core 2GHz). As the main result, most of time, the moving fovea allows the robot not to perform physical motion of its robotics devices to keep a possible region of interest visible in both images. We validate the proposed model with experimental results

Modelagem aplicada à análise de desempenho do provedor de serviços de uma rede de automação hospitalar ieee 802.3/pm-ah de tempo real

The incorporate of industrial automation in the medical are requires mechanisms to safety and efficient establishment of communication between biomedical devices. One solution to this problem is the MP-HA (Multicycles Protocol to Hospital Automation) that down a segmented network by beds coordinated by an element called Service Provider. The goal of this work is to model this Service Provider and to do performance analysis of the activities executed by in establishment and maintenance of hospital networks

Identificação em tempo real de modelo dinâmico de robô móvel com acionamento diferencial e zona morta

Several mobile robots show non-linear behavior, mainly due friction phenomena between the mechanical parts of the robot or between the robot and the ground. Linear models are efficient in some cases, but it is necessary take the robot non-linearity in consideration when precise displacement and positioning are desired. In this work a parametric model identification procedure for a mobile robot with differential drive that considers the dead-zone in the robot actuators is proposed. The method consists in dividing the system into Hammerstein systems and then uses the key-term separation principle to present the input-output relations which shows the parameters from both linear and non-linear blocks. The parameters are then simultaneously estimated through a recursive least squares algorithm. The results shows that is possible to identify the dead-zone thresholds together with the linear parameters

Estudo avaliativo de um algoritmo genético auto-organizável e multiobjetivo utilizando aprendizado de máquina para aplicações de telecomunicações

This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables

Escalabilidade Paralela de um Algoritmo de Migração Reversa no Tempo (RTM) Pré-empilhamento

The seismic method is of extreme importance in geophysics. Mainly associated with oil exploration, this line of research focuses most of all investment in this area. The acquisition, processing and interpretation of seismic data are the parts that instantiate a seismic study. Seismic processing in particular is focused on the imaging that represents the geological structures in subsurface. Seismic processing has evolved significantly in recent decades due to the demands of the oil industry, and also due to the technological advances of hardware that achieved higher storage and digital information processing capabilities, which enabled the development of more sophisticated processing algorithms such as the ones that use of parallel architectures. One of the most important steps in seismic processing is imaging. Migration of seismic data is one of the techniques used for imaging, with the goal of obtaining a seismic section image that represents the geological structures the most accurately and faithfully as possible. The result of migration is a 2D or 3D image which it is possible to identify faults and salt domes among other structures of interest, such as potential hydrocarbon reservoirs. However, a migration fulfilled with quality and accuracy may be a long time consuming process, due to the mathematical algorithm heuristics and the extensive amount of data inputs and outputs involved in this process, which may take days, weeks and even months of uninterrupted execution on the supercomputers, representing large computational and financial costs, that could derail the implementation of these methods. Aiming at performance improvement, this work conducted the core parallelization of a Reverse Time Migration (RTM) algorithm, using the parallel programming model Open Multi-Processing (OpenMP), due to the large computational effort required by this migration technique. Furthermore, analyzes such as speedup, efficiency were performed, and ultimately, the identification of the algorithmic scalability degree with respect to the technological advancement expected by future processors

Análise do efeito do tempo da moagem de alta energia no tamanho de cristalito e microdeformação da rede cristalina do WC-Co

Hard metals are the composite developed in 1923 by Karl Schröter, with wide application because high hardness, wear resistance and toughness. It is compound by a brittle phase WC and a ductile phase Co. Mechanical properties of hardmetals are strongly dependent on the microstructure of the WC Co, and additionally affected by the microstructure of WC powders before sintering. An important feature is that the toughness and the hardness increase simultaneously with the refining of WC. Therefore, development of nanostructured WC Co hardmetal has been extensively studied. There are many methods to manufacture WC-Co hard metals, including spraying conversion process, co-precipitation, displacement reaction process, mechanochemical synthesis and high energy ball milling. High energy ball milling is a simple and efficient way of manufacturing the fine powder with nanostructure. In this process, the continuous impacts on the powders promote pronounced changes and the brittle phase is refined until nanometric scale, bring into ductile matrix, and this ductile phase is deformed, re-welded and hardened. The goal of this work was investigate the effects of highenergy milling time in the micro structural changes in the WC-Co particulate composite, particularly in the refinement of the crystallite size and lattice strain. The starting powders were WC (average particle size D50 0.87 μm) supplied by Wolfram, Berglau-u. Hutten - GMBH and Co (average particle size D50 0.93 μm) supplied by H.C.Starck. Mixing 90% WC and 10% Co in planetary ball milling at 2, 10, 20, 50, 70, 100 and 150 hours, BPR 15:1, 400 rpm. The starting powders and the milled particulate composite samples were characterized by X-ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) to identify phases and morphology. The crystallite size and lattice strain were measured by Rietveld s method. This procedure allowed obtaining more precise information about the influence of each one in the microstructure. The results show that high energy milling is efficient manufacturing process of WC-Co composite, and the milling time have great influence in the microstructure of the final particles, crushing and dispersing the finely WC nanometric order in the Co particles

Influência da corrente de pulso, do tempo de pulso e diâmetro de gota sobre a estabilidade da transferência metálica no processo MIG-P

To obtain a process stability and a quality weld bead it is necessary an adequate parameters set: base current and time, pulse current and pulse time, because these influence the mode of metal transfer and the weld quality in the MIG-P, sometimes requiring special sources with synergistic modes with external control for this stability. This work aims to analyze and compare the effects of pulse parameters and droplet size in arc stability in MIG-P, four packets of pulse parameters were analysed: Ip = 160 A, tp = 5.7 ms; Ip = 300 A and tp = 2 ms, Ip = 350 A, tp = 1.2 ms and Ip = 350 A, tp = 0.8 ms. Each was analyzed with three different drop diameters: drop with the same diameter of the wire electrode; droplet diameter larger drop smaller than the diameter of the wire electrode. For purposes of comparison the same was determined relation between the average current and welding speed was determined generating a constant (Im / Vs = K) for all parameters. Welding in flat plate by simple deposition for the MIG-P with a distance beak contact number (DBCP) constant was perfomed subsequently making up welding in flat plate by simple deposition with an inclination of 10 degrees to vary the DBCP, where by assessment on how the MIG-P behaved in such a situation was possible, in addition to evaluating the MIG-P with adaptive control, in order to maintain a constant arc stability. Also high speed recording synchronized with acquiring current x voltage (oscillogram) was executed for better interpretation of the transfer mechanism and better evaluation in regard to the study of the stability of the process. It is concluded that parameters 3 and 4 exhibited greater versatility; diameters drop equal to or slightly less than the diameter of the wire exhibited better stability due to their higher frequency of detachment, and the detachment of the drop base does not harm the maintenance the height of the arc

Efeito de variáveis de processo no tempo de fermentação e na concentração das dicetonas vicinais totais

Among the main challenges in the beer industrial production is the market supply at the lowest cost and high quality, in order to ensure the expectations of customers and. consumers The beer fermentation stage represents approximately 70% of the whole time necessary to its production, having a obligatoriness of strict process controls to avoid becoming bottleneck in beer production. This stage is responsible for the formation of a series of subproducts, which are responsible for the composition of aroma/bouquet existing in beer and some of these subproducts, if produced in larger quantities, they will confer unpleasant taste and odor to the final product. Among the subproducts formed during the fermentation stage, total vicinal diketones is the main component, since it is limiting for product transfusion to the subsequent steps, besides having a low perception threshold by the consumer and giving undesirable taste and odor. Due to the instability of main raw materials quality and also process controls during fermentation, the development of alternative forms of beer production without impacting on total fermentation time and final product quality is a great challenge to breweries. In this work, a prior acidification of the pasty yeast was carried out, utilizing for that phosphoric acid, food grade, reducing yeast pH of about 5.30 to 2.20 and altering its characteristic from flocculent to pulverulent during beer fermentation. An increase of six times was observed in amount of yeast cells in suspension in the second fermentation stage regarding to fermentations by yeast with no prior acidification. With alteration on two input variables, temperature curve and cell multiplication, which goal was to minimize the maximum values for diketones detected in the fermenter tank, a reduction was obtained from peak of formed diacetyl and consequently contributed to reduction in fermentation time and total process time. Several experiments were performed with those process changes in order to verify the influence on the total fermentation time and total vicinal diketones concentration at the end of fermentation. This experiment reached as the best production result a total fermentation time of 151 hours and total vicinal diketone concentration of 0.08 ppm. The mass of yeast in suspension in the second phase of fermentation increased from 2.45 x 106 to 16.38 x 106 cells/mL of yeast, which fact is key to a greater efficiency in reducing total vicinal diketones existing in the medium, confirming that the prior yeast acidification, as well as the control of temperature and yeast cell multiplication in fermentative process enhances the performance of diketones reduction and consequently reduce the total fermentation time with diketones concentration below the expected value (Max: 0.10 ppm)

Monitoramento em tempo real de processos fermentativos por espectroscopia no infravermelho próximo (NIRS)

A chemical process optimization and control is strongly correlated with the quantity of information can be obtained from the system. In biotechnological processes, where the transforming agent is a cell, many variables can interfere in the process, leading to changes in the microorganism metabolism and affecting the quantity and quality of final product. Therefore, the continuously monitoring of the variables that interfere in the bioprocess, is crucial to be able to act on certain variables of the system, keeping it under desirable operational conditions and control. In general, during a fermentation process, the analysis of important parameters such as substrate, product and cells concentration, is done off-line, requiring sampling, pretreatment and analytical procedures. Therefore, this steps require a significant run time and the use of high purity chemical reagents to be done. In order to implement a real time monitoring system for a benchtop bioreactor, these study was conducted in two steps: (i) The development of a software that presents a communication interface between bioreactor and computer based on data acquisition and process variables data recording, that are pH, temperature, dissolved oxygen, level, foam level, agitation frequency and the input setpoints of the operational parameters of the bioreactor control unit; (ii) The development of an analytical method using near-infrared spectroscopy (NIRS) in order to enable substrate, products and cells concentration monitoring during a fermentation process for ethanol production using the yeast Saccharomyces cerevisiae. Three fermentation runs were conducted (F1, F2 and F3) that were monitored by NIRS and subsequent sampling for analytical characterization. The data obtained were used for calibration and validation, where pre-treatments combined or not with smoothing filters were applied to spectrum data. The most satisfactory results were obtained when the calibration models were constructed from real samples of culture medium removed from the fermentation assays F1, F2 and F3, showing that the analytical method based on NIRS can be used as a fast and effective method to quantify cells, substrate and products concentration what enables the implementation of insitu real time monitoring of fermentation processes