52 resultados para Weighted shift
Resumo:
The data represents a shift in process variable presented in a control chart due to the sudden change in the machine setting.
Resumo:
Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R 2 and lower corrected Akaike information criterion (AICC). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R 2 and lower AICC. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.
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The ordered weighted averaging (OWA) determination method with stress function was proposed by Yager, and it makes the OWA operator elements scatter in the shape of the stress function. In this paper, we extend the OWA determination with the stress function method using an optimization model. The proposed method transforms the OWA optimal solution elements into the interpolation points of the stress function. The proposed method extends the basic form of the stress function method with both scale and vertical shift transformations.We also explore a number of properties of this optimization-based stress function method. The OWA operator optimal solution elements can distribute as the shape of the given stress function in a parameterized way, in which case, the solution always possesses the arithmetic average operator as a special case.
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Since the introduction of the ordered weighted averaging operator [18], the OWA has received great attention with applications in fields including decision making, recommender systems [8, 21], classification [10] and data mining [16] among others. The most important step in the calculation of the OWA is the permutation of the input vector according to the size of its arguments. In some applications, it makes sense that the inputs be reordered by values different to those used in calculation. For instance, if we have a number of mobile sensor readings, we may wish to allocate more importance to the reading taken from the sensor closest to us at a given point in time, rather than the largest reading.
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This paper proposes a ramp dual-pulse actuation-voltage waveform that reduces actuation-voltage shift in capacitive microelectromechanical system (MEMS) switches. The proposed waveform as well as two reported waveforms (dual pulse, and novel dual-pulse) are analyzed using equivalent-circuit and equation models. Based on the analysis outcome, the paper provides a clear understanding of trapped charge density in the dielectric. The results show that the proposed actuation-voltage waveform successfully reduces trapped charge and increases lifetime due to lowering of actuation-voltage shift. Using the proposed actuation-voltage waveform, the membrane reaches a steady state on the electrode faster.
Resumo:
Objective. To develop a version of the Melbourne Low-Vision ADL Index that measures the personal impact of disability in activities of daily living (ADL's). Also, to determine the relationship between clinical measures of vision impairment and disability impact.
Methods. The Melbourne Low-Vision ADL Index (MLVAI) is a desk-based clinical assessment of disability in ADL's. Ability to perform each item is rated on a five-level descriptive scale from zero to four. In this study, the original version of the MLVAI was modified to measure disability impact. The simple modification involved weighting each item by the importance of that item to the person being tested. Importance was also rated on a five-level scale from zero to four. The validity and reliability of the Weighted Melbourne Low-Vision ADL Index (MLVAIW) was determined for 97 vision-impaired subjects in a cross-sectional study.
Results. Cronbach's alpha coefficient indicated an internal reliability of 0.94, and an intraclass correlation coefficient indicated an overall reliability of 0.88. The standard error of measurement was 24.7 points (out of a possible score of 400). There was a statistically significant difference in test scores between normal subjects and vision-impaired subjects. All vision measures had a high, statistically significant correlation with MLVAIW score. Near-word acuity had the strongest correlation (rs = 0.78, p < 0.001), followed by Melbourne Edge Test contrast sensitivity (rs = -0.72, p < 0.001). Visual field had the weakest correlation (rs = -0.52, p < 0.001). The best predictive model of MLVAIW score incorporated the variables age, near-word acuity, and visual field. Together, these variables accounted for 65.1% of the variance in MLVAIW score.
Conclusions. The MLVAI is highly valid and reliable when weighted by a scale that reflects the personal importance of ADL's. The MLVAIW can provide information over and above that obtained with the usual clinical vision measures and may be used to assess low-vision patients and to measure low-vision rehabilitation outcomes. It is suggested that the assessment of disability using the original MLVAI and the assessment of the impact of disability using the MLVAIW should be kept separate to facilitate the clear interpretation of the outcomes of low-vision rehabilitation.
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Taking the uncertainty existing in edge weights of networks into consideration, finding shortest path in such fuzzy weighted networks has been widely studied in various practical applications. In this paper, an amoeboid algorithm is proposed, combing fuzzy sets theory with a path finding model inspired by an amoeboid organism, Physarum polycephalum. With the help of fuzzy numbers, uncertainty is well represented and handled in our algorithm. What's more, biological intelligence of Physarum polycephalum has been incorporate into the algorithm. A numerical example on a transportation network is demonstrated to show the efficiency and flexibility of our proposed amoeboid algorithm.
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Identification of the most central node within a network is one of the primary problems in network analysis. Among various centrality measures for weighted networks, most are based on the assumption that information only spreads through the shortest paths. Then, a mathematical model of an amoeboid organism has been used by Physarum centrality to relax the assumption. However, its computational complexity is relatively high by finding competing paths between all pairs of nodes in networks. In this paper, with the idea of a ground node, an improved Physarum centrality is proposed by maintaining the feature of original measure with the performance is greatly enhanced. Examples and applications are given to show the efficiency and effectiveness of our proposed measure in weighted networks.
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In a replicated whole-lake experiment, we (a) tested for the existence of a flexible habitat shift in response to predator presence in age-0 rainbow trout (Oncorhynchus mykiss) at risk of cannibalism and (b) evaluated the population-level consequences of habitat shifts in terms of growth and survival over their first growing season. Daphnid food and adult trout predators were substantially more abundant in pelagic than in littoral habitats. Age-0 trout used all habitats in populations without adult trout predators, whereas age-0 trout were observed only in the less profitable littoral habitat in populations with adult trout. Consequently, mean fall mass of age-0 trout in the presence of predators was almost half that observed in populations without adult trout. Despite the shift in habitat use, age-0 trout experienced 90% mortality when adult trout predators were present, in comparison to only 36% mortality when absent. We conclude that the commonly observed habitat shifts by fish at risk of predation, observed at smaller scales, do in fact occur at the whole-system scale over long time intervals. These results suggest that fish are able to perceive risk at large spatial scales and thus take advantage of profitable (but normally risky) habitats when predators are absent, or move to less profitable refuge habitats when predators are present.