995 resultados para Intelligent analysis of complaints
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Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação
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Superheater corrosion causes vast annual losses for the power companies. With a reliable corrosion prediction method, the plants can be designed accordingly, and knowledge of fuel selection and determination of process conditions may be utilized to minimize superheater corrosion. Growing interest to use recycled fuels creates additional demands for the prediction of corrosion potential. Models depending on corrosion theories will fail, if relations between the inputs and the output are poorly known. A prediction model based on fuzzy logic and an artificial neural network is able to improve its performance as the amount of data increases. The corrosion rate of a superheater material can most reliably be detected with a test done in a test combustor or in a commercial boiler. The steel samples can be located in a special, temperature-controlled probe, and exposed to the corrosive environment for a desired time. These tests give information about the average corrosion potential in that environment. Samples may also be cut from superheaters during shutdowns. The analysis ofsamples taken from probes or superheaters after exposure to corrosive environment is a demanding task: if the corrosive contaminants can be reliably analyzed, the corrosion chemistry can be determined, and an estimate of the material lifetime can be given. In cases where the reason for corrosion is not clear, the determination of the corrosion chemistry and the lifetime estimation is more demanding. In order to provide a laboratory tool for the analysis and prediction, a newapproach was chosen. During this study, the following tools were generated: · Amodel for the prediction of superheater fireside corrosion, based on fuzzy logic and an artificial neural network, build upon a corrosion database developed offuel and bed material analyses, and measured corrosion data. The developed model predicts superheater corrosion with high accuracy at the early stages of a project. · An adaptive corrosion analysis tool based on image analysis, constructedas an expert system. This system utilizes implementation of user-defined algorithms, which allows the development of an artificially intelligent system for thetask. According to the results of the analyses, several new rules were developed for the determination of the degree and type of corrosion. By combining these two tools, a user-friendly expert system for the prediction and analyses of superheater fireside corrosion was developed. This tool may also be used for the minimization of corrosion risks by the design of fluidized bed boilers.
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OBJECTIVE: This study aimed to analyze complaints of patients, their relatives, and friends who consulted a complaints center based (Espace Patients & Proches (EPP)) in a hospital so as to better understand the reasons that motivated them and their underlying expectations. METHODS: This study was based on the analysis of written accounts of the 253 situations that occurred during the first year of operation of the EPP. The accounts were analyzed qualitatively using an inductive, thematic analytic approach. RESULTS: We identified 372 different types of complaints and 28 main analytic themes. Five clustered themes emerged from the analysis of the interconnections among the core themes: (1) interpersonal relationship (N=160-the number of accounts including a complaint related to this general theme); (2) technical aspects of care (N=106); (3) health-care institution (N=69); (4) billing and insurance; (5) access to information (N=13). CONCLUSION: The main reason for patients, their relatives, and friends going to EPP was related to the quality of the interpersonal relationship with health-care professionals. Such complaints were markedly more frequent than those concerning technical aspects of care. PRACTICE IMPLICATIONS: These results raise important questions concerning changing patient expectations as well as how hospitals integrate complaints into the process of quality health care.
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The purpose of the current undertaking was to study the electrophysiological properties of the sleep onset period (SOP) in order to gain understanding into the persistent sleep difficulties of those who complain of insomnia following mild traumatic brain injury (MTBI). While many believe that symptoms of post concussion syndrome (PCS) following MTBI resolve within 6 to 12 months, there are a number of people who complain of persistent sleep difficulty. Two models were proposed which hypothesize alternate electrophysiological presentations of the insomnia complaints of those sustaining a MTBI: 1) Analyses of standard polysomnography (PSG) sleep parameters were conducted in order to determine if the sleep difficulties of the MTBI population were similar to that of idiopathic insomniacs (i.e. greater proportion ofREM sleep, reduced delta sleep); 2) Power spectral analysis was conducted over the SOP to determine if the sleep onset signature of those with MTBI would be similar to psychophysiological insomniacs (characterized by increased cortical arousal). Finally, exploratory analyses examined whether the sleep difficulties associated with MTBI could be explained by increases in variability of the power spectral data. Data were collected from 9 individuals who had sustained a MTBI 6 months to 5 years earlier and reported sleep difficulties that had arisen within the month subsequent to injury and persisted to the present. The control group consisted of 9 individuals who had experienced neither sleep difficulties, nor MTBI. Previous to spending 3 consecutive uninterrupted nights in the sleep lab, subjects completed questionnaires regarding sleep difficulties, adaptive functioning, and personality.
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The central motif of this work is prediction and optimization in presence of multiple interacting intelligent agents. We use the phrase `intelligent agents' to imply in some sense, a `bounded rationality', the exact meaning of which varies depending on the setting. Our agents may not be `rational' in the classical game theoretic sense, in that they don't always optimize a global objective. Rather, they rely on heuristics, as is natural for human agents or even software agents operating in the real-world. Within this broad framework we study the problem of influence maximization in social networks where behavior of agents is myopic, but complication stems from the structure of interaction networks. In this setting, we generalize two well-known models and give new algorithms and hardness results for our models. Then we move on to models where the agents reason strategically but are faced with considerable uncertainty. For such games, we give a new solution concept and analyze a real-world game using out techniques. Finally, the richest model we consider is that of Network Cournot Competition which deals with strategic resource allocation in hypergraphs, where agents reason strategically and their interaction is specified indirectly via player's utility functions. For this model, we give the first equilibrium computability results. In all of the above problems, we assume that payoffs for the agents are known. However, for real-world games, getting the payoffs can be quite challenging. To this end, we also study the inverse problem of inferring payoffs, given game history. We propose and evaluate a data analytic framework and we show that it is fast and performant.
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Unmanned air vehicles (UAVs) and micro air vehicles (MAVs) constitute unique application platforms for vibration-based energy harvesting. Generating usable electrical energy during their mission has the important practical value of providing an additional energy source to run small electronic components. Electrical energy can be harvested from aeroelastic vibrations of lifting surfaces of UAVs and MAVs as they tend to have relatively flexible wings compared to their larger counterparts. In this work, an electromechanically coupled finite element model is combined with an unsteady aerodynamic model to develop a piezoaeroelastic model for airflow excitation of cantilevered plates representing wing-like structures. The electrical power output and the displacement of the wing tip are investigated for several airflow speeds and two different electrode configurations (continuous and segmented). Cancelation of electrical output occurs for typical coupled bending-torsion aeroelastic modes of a cantilevered generator wing when continuous electrodes are used. Torsional motions of the coupled modes become relatively significant when segmented electrodes are used, improving the broadband performance and altering the flutter speed. Although the focus is placed on the electrical power that can be harvested for a given airflow speed, shunt damping effect of piezoelectric power generation is also investigated for both electrode configurations.
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This article investigates the researcher's work in the coproduction (or not) of complaint sequences in research interviews. Using a conversation analytic approach, we show how the interviewer's management of complaint sequences in a research setting is consequential for subsequent talk and thus directly affects the data generated. In the examples shown here, researchers sharing cocategorial incumbency with respondents may well provide spaces for research participants to formulate complaints. This article examines sequences of talk surrounding complaints to show how researchers generate complaints (or not) and handle unsafe complaints. Researchers are able to provoke specific types of accounts from respondents, whereas their respondents may actively resist the researchers' direction. For researchers using the interview as a method of data generation, examination of complaint sequences and how these appear in interview data provides insight into how interview talk is coproduced and managed within a socially situated setting.
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The process of resources systems selection takes an important part in Distributed/Agile/Virtual Enterprises (D/A/V Es) integration. However, the resources systems selection is still a difficult matter to solve in a D/A/VE, as it is pointed out in this paper. Globally, we can say that the selection problem has been equated from different aspects, originating different kinds of models/algorithms to solve it. In order to assist the development of a web prototype tool (broker tool), intelligent and flexible, that integrates all the selection model activities and tools, and with the capacity to adequate to each D/A/V E project or instance (this is the major goal of our final project), we intend in this paper to show: a formulation of a kind of resources selection problem and the limitations of the algorithms proposed to solve it. We formulate a particular case of the problem as an integer programming, which is solved using simplex and branch and bound algorithms, and identify their performance limitations (in terms of processing time) based on simulation results. These limitations depend on the number of processing tasks and on the number of pre-selected resources per processing tasks, defining the domain of applicability of the algorithms for the problem studied. The limitations detected open the necessity of the application of other kind of algorithms (approximate solution algorithms) outside the domain of applicability founded for the algorithms simulated. However, for a broker tool it is very important the knowledge of algorithms limitations, in order to, based on problem features, develop and select the most suitable algorithm that guarantees a good performance.
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This paper studies the impact of energy and stock markets upon electricity markets using Multidimensional Scaling (MDS). Historical values from major energy, stock and electricity markets are adopted. To analyze the data several graphs produced by MDS are presented and discussed. This method is useful to have a deeper insight into the behavior and the correlation of the markets. The results may also guide the construction models, helping electricity markets agents hedging against Market Clearing Price (MCP) volatility and, simultaneously, to achieve better financial results.
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This paper analyzes the performance of two cooperative robot manipulators. In order to capture the working performancewe formulated several performance indices that measure the manipulability, the effort reduction and the equilibrium between the two robots. In this perspective the proposed indices we determined the optimal values for the system parameters. Furthermore, it is studied the implementation of fractional-order algorithms in the position/force control of two cooperative robotic manipulators holding an object.
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This paper analyses the dynamical properties of systems with backlash and impact phenomena based on the describing function method. The dynamics is illustrated using the Nyquist and Bode plots and the results are compared with those of standard models.
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This paper studies periodic gaits of multi-legged locomotion systems based on dynamic models. The purpose is to determine the system performance during walking and the best set of locomotion variables. For that objective the prescribed motion of the robot is completely characterized in terms of several locomotion variables such as gait, duty factor, body height, step length, stroke pitch, foot clearance, legs link lengths, foot-hip offset, body and legs mass and cycle time. In this perspective, we formulate three performance measures of the walking robot namely, the mean absolute energy, the mean power dispersion and the mean power lost in the joint actuators per walking distance. A set of model-based experiments reveals the influence of the locomotion variables in the proposed indices.
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A new method for the study and optimization of manu«ipulator trajectories is developed. The novel feature resides on the modeling formulation. Standard system desciptions are based on a set of differential equations which, in general, require laborious computations and may be difficult to analyze. Moreover, the derived algorithms are suited to "deterministic" tasks, such as those appearing in a repetitivework, and are not well adapted to a "random" operation that occurs in intelligent systems interacting with a non-structured and changing environment. These facts motivate the development of alternative models based on distinct concepts. The proposed embedding of statistics and Fourier trasnform gives a new perspective towards the calculation and optimization of the robot trajectories in manipulating tasks.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics