936 resultados para Reliability in automation
Design of improved rail-to-rail low-distortion and low-stress switches in advanced CMOS technologies
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This paper describes the efficient design of an improved and dedicated switched-capacitor (SC) circuit capable of linearizing CMOS switches to allow SC circuits to reach low distortion levels. The described circuit (SC linearization control circuit, SLC) has the advantage over conventional clock-bootstrapping circuits of exhibiting low-stress, since large gate voltages are avoided. This paper presents exhaustive corner simulation results of a SC sample-and-hold (S/H) circuit which employs the proposed and optimized circuits, together with the experimental evaluation of a complete 10-bit ADC utilizing the referred S/H circuit. These results show that the SLC circuits can reduce distortion and increase dynamic linearity above 12 bits for wide input signal bandwidths.
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INTRODUCTION: Self-reported weight and height were compared with direct measurements in order to evaluate the agreement between the two sources. METHOD: Data were obtained from a cross-sectional study on health status from a probabilistic sample of 1,183 employees of a bank, in Rio de Janeiro State, Brazil. Direct measurements were made of 322 employees. Differences between the two sources were evaluated using mean differences, limits of agreement and intraclass correlation coefficient (ICC). RESULTS AND CONCLUSIONS: Men and women tended to underestimate their weight while differences between self-reported and measured height were insignificant. Body mass index (BMI) mean differences were smaller than those observed for weight. ICC was over 0.98 for weight and 0.95 for BMI, expressing close agreement. Combining a graphical method with ICC may be useful in pilot studies to detect populational groups capable of providing reliable information on weight and height, thus minimizing resources needed for field work.
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We are concerned with providing more empirical evidence on forecast failure, developing forecast models, and examining the impact of events such as audit reports. A joint consideration of classic financial ratios and relevant external indicators leads us to build a basic prediction model focused in non-financial Galician SMEs. Explanatory variables are relevant financial indicators from the viewpoint of the financial logic and financial failure theory. The paper explores three mathematical models: discriminant analysis, Logit, and linear multivariate regression. We conclude that, even though they both offer high explanatory and predictive abilities, Logit and MDA models should be used and interpreted jointly.
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Effective legislation and standards for the coordination procedures between consumers, producers and the system operator supports the advances in the technologies that lead to smart distribution systems. In short-term (ST) maintenance scheduling procedure, the energy producers in a distribution system access to the long-term (LT) outage plan that is released by the distribution system operator (DSO). The impact of this additional information on the decision-making procedure of producers in ST maintenance scheduling is studied in this paper. The final ST maintenance plan requires the approval of the DSO that has the responsibility to secure the network reliability and quality, and other players have to follow the finalized schedule. Maintenance scheduling in the producers’ layer and the coordination procedure between them and the DSO is modelled in this paper. The proposed method is applied to a 33-bus distribution system.
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In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. Grid operators and utilities are taking new initiatives, recognizing the value of demand response for grid reliability and for the enhancement of organized spot markets’ efficiency. This paper proposes a methodology for the selection of the consumers that participate in an event, which is the responsibility of the Portuguese transmission network operator. The proposed method is intended to be applied in the interruptibility service implemented in Portugal, in convergence with Spain, in the context of the Iberian electricity market. This method is based on the calculation of locational marginal prices (LMP) which are used to support the decision concerning the consumers to be schedule for participation. The proposed method has been computationally implemented and its application is illustrated in this paper using a 937 bus distribution network with more than 20,000 consumers.
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Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. In this paper, we describe a Self-Optimizing Mechanism for Scheduling System through Nature Inspired Optimization Techniques (NIT).
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The paper proposes a methodology to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The proposed methodology is based on statistical failure and repair data of distribution components and it uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A mixed integer nonlinear programming optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.
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Distribution systems are the first volunteers experiencing the benefits of smart grids. The smart grid concept impacts the internal legislation and standards in grid-connected and isolated distribution systems. Demand side management, the main feature of smart grids, acquires clear meaning in low voltage distribution systems. In these networks, various coordination procedures are required between domestic, commercial and industrial consumers, producers and the system operator. Obviously, the technical basis for bidirectional communication is the prerequisite of developing such a coordination procedure. The main coordination is required when the operator tries to dispatch the producers according to their own preferences without neglecting its inherent responsibility. Maintenance decisions are first determined by generating companies, and then the operator has to check and probably modify them for final approval. In this paper the generation scheduling from the viewpoint of a distribution system operator (DSO) is formulated. The traditional task of the DSO is securing network reliability and quality. The effectiveness of the proposed method is assessed by applying it to a 6-bus and 9-bus distribution system.
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In this paper we present VERITAS, a tool that focus time maintenance, that is one of the most important processes in the engineering of the time during the development of KBS. The verification and validation (V&V) process is part of a wider process denominated knowledge maintenance, in which an enterprise systematically gathers, organizes, shares, and analyzes knowledge to accomplish its goals and mission. The V&V process states if the software requirements specifications have been correctly and completely fulfilled. The methodologies proposed in software engineering have showed to be inadequate for Knowledge Based Systems (KBS) validation and verification, since KBS present some particular characteristics. VERITAS is an automatic tool developed for KBS verification which is able to detect a large number of knowledge anomalies. It addresses many relevant aspects considered in real applications, like the usage of rule triggering selection mechanisms and temporal reasoning.
Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems
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This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.
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This paper presents a methodology supported on the data base knowledge discovery process (KDD), in order to find out the failure probability of electrical equipments’, which belong to a real electrical high voltage network. Data Mining (DM) techniques are used to discover a set of outcome failure probability and, therefore, to extract knowledge concerning to the unavailability of the electrical equipments such us power transformers and high-voltages power lines. The framework includes several steps, following the analysis of the real data base, the pre-processing data, the application of DM algorithms, and finally, the interpretation of the discovered knowledge. To validate the proposed methodology, a case study which includes real databases is used. This data have a heavy uncertainty due to climate conditions for this reason it was used fuzzy logic to determine the set of the electrical components failure probabilities in order to reestablish the service. The results reflect an interesting potential of this approach and encourage further research on the topic.
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A replicate evaluation of increased micronucleus (MN) frequencies in peripheral lymphocytes of workers occupationally exposed to formaldehyde (FA) was undertaken to verify the observed effect and to determine scoring variability. May–Grünwald–Giemsa-stained slides were obtained from a previously performed cytokinesis-block micronucleus test (CBMNT) with 56 workers in anatomy and pathology laboratories and 85 controls. The first evaluation by one scorer (scorer 1) had led to a highly significant difference between workers and controls (3.96 vs 0.81 MN per 1000 cells). The slides were coded before re-evaluation and the code was broken after the complete re-evaluation of the study. A total of 1000 binucleated cells (BNC) were analysed per subject and the frequency of MN (in ‰) was determined. Slides were distributed equally and randomly between two scorers, so that the scorers had no knowledge of the exposure status. Scorer 2 (32 exposed, 36 controls) measured increased MN frequencies in exposed workers (9.88 vs 6.81). Statistical analysis with the two-sample Wilcoxon test indicated that this difference was not significant (p = 0.17). Scorer 3 (20 exposed, 46 controls) obtained a similar result, but slightly higher values for the comparison of exposed and controls (19.0 vs 12.89; p = 0.089). Combining the results of the two scorers (13.38 vs 10.22), a significant difference between exposed and controls (p = 0.028) was obtained when the stratified Wilcoxon test with the scorers as strata was applied. Interestingly, the re-evaluation of the slides led to clearly higher MN frequencies for exposed and controls compared with the first evaluation. Bland–Altman plots indicated that the agreement between the measurements of the different scorers was very poor, as shown by mean differences of 5.9 between scorer 1 and scorer 2 and 13.0 between scorer 1 and scorer 3. Calculation of the intra-class correlation coefficient (ICC) revealed that all scorer comparisons in this study were far from acceptable for the reliability of this assay. Possible implications for the use of the CBMNT in human biomonitoring studies are discussed.
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Background: Acute respiratory infections are usual in children under three years old occurring in upper respiratory tract, having an impact on child and caregiver’s quality of life predisposing to otitis media or bronchiolitis. There are few valid and reliable measures to determine the child’s respiratory condition and to guide the physiotherapy intervention. Aim: To assess the intra and inter rater reliability of nasal auscultation, to analyze the relation between sounds’ classification and middle ear’s pressure and compliance as well as with the Clinical Severity Score. Methods: A cross-sectional observational study was composed by 125 nursery children aged up to three years old. Tympanometry, pulmonary and nasal auscultation and application of Clinical Severity Score were performed to each child. Nasal auscultation sounds’ were recorded and sent to 3 blinded experts, that classified, as “obstructed” and “unobstructed”, with a 48 hours interval, in order to analyze inter and intra rater reliability. Results: Nasal auscultation revealed a substantial inter and intra rater reliability (=0,749 and evaluator A - K= 0,691; evaluator B - K= 0,605 and evaluator C - K= 0,724, respectively). Both ears’ pressure was significantly lower in children with an "unobstructed" nasal sound when compared with an “obstructed” nasal sound (t=-3,599, p<0,001 in left ear; t=-2,258, p=0,026 in right ear). Compliance in both ears was significantly lower in children with an "obstructed" nasal sound when compared with “unobstructed” nasal sound (t=-2,728, p=0,007 in left ear; t=-3,830, p<0,001 in right ear). There was a statistically significant association between sounds’ classification and tympanograms types in both ear’s (=11,437, p=0,003 in left ear; =13,535, p=0,001 in right ear). There was a trend to children with an "unobstructed" nasal sound that had a lower clinical severity score when compared with “obstructed” children. Conclusion: It was observed a good intra and substantial inter reliability for nasal auscultation. Nasal auscultation sounds’ classification was related to middle ears’ pressure and compliance.
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Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia
Paranoia in the General Population : a revised version of the General Paranoia Scale for adolescents
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The aim of the current study was to validate the General Paranoia Scale for Portuguese Adolescents population (GPS-A). This scale assesses the paranoid ideation in non-clinical population. Results from a confirmatory factor analysis of the scale on 1218 youths confirmed an alternative model to the one-dimensional model proposed by Fenigstein and Vanable (1992) comprising three different dimensions (Mistrust thoughts, persecutory ideas and depreciation). This alternative model presented a good fit: χ2 (162)= 727.200, p = .000; CFI = .925; RMSEA = .054, P(rmsea ≤0.05) = .000; PCFI = .788; AIC = 863.200. All items presented adequate factor loadings (λij ≥0.5) and individual reliability ((λij)2 ≥0.25). Further data analysis on the scale revealed that the GPS-A is an adequate assessment tool for adolescents, with good psychometric characteristics and high internal consistency.