795 resultados para Fuzzy Measure


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n this paper, a multistage evolutionary scheme is proposed for clustering in a large data base, like speech data. This is achieved by clustering a small subset of the entire sample set in each stage and treating the cluster centroids so obtained as samples, together with another subset of samples not considered previously, as input data to the next stage. This is continued till the whole sample set is exhausted. The clustering is accomplished by constructing a fuzzy similarity matrix and using the fuzzy techniques proposed here. The technique is illustrated by an efficient scheme for voiced-unvoiced-silence classification of speech.

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The fatty acid composition of ground nuts (Arachis hypogaea L.) commonly known as peanuts, is an important consideration when a new variety is being released. The composition impacts on nutrition and, importantly, self-life of peanut products. To select for suitable breeding material, it was necessary to develop a rapid, non-derstructive and cost-efficient method. Near infrared spectroscopy was chosen as that methodology. Calibrations were developed for two major fatty-acid components, oleic and linoleic acids and two minor components, palmitic and stearic acids, as well as total oil content. Partial least squares models indicated a high level of precision with a squared multiple correlation coefficient of greater than 0.90 for each constitutent. Standard errors for prediction for oleic, linoleic, palmitic, stearic acids and total oil content were 6.4%, 4.5%, 0.8%, 0.9% and 1.3% respectively. The results demonstrated that reasonable calibrations could be developed to predict oil composition and content of peanuts for a breeding programme.

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Volatile chemical compounds responsible for the aroma of wine are derived from a number of different biochemical and chemical pathways. These chemical compounds are formed during grape berry metabolism, crushing of the berries, fermentation processes (i.e. yeast and malolactic bacteria) and also from the ageing and storage of wine. Not surprisingly, there are a large number of chemical classes of compounds found in wine which are present at varying concentrations (ng L-1 to mg L-1), exhibit differing potencies, and have a broad range of volatilities and boiling points. The aim of this work was to investigate the potential use of near infrared (NIR) spectroscopy combined with chemometrics as a rapid and low-cost technique to measure volatile compounds in Riesling wines. Samples of commercial Riesling wine were analyzed using an NIR instrument and volatile compounds by gas chromatography (GC) coupled with selected ion monitoring mass spectrometry. Correlation between the NIR and GC data were developed using partial least-squares (PLS) regression with full cross validation (leave one out). Coefficients of determination in cross validation (R 2) and the standard error in cross validation (SECV) were 0.74 (SECV: 313.6 μg L−1) for esters, 0.90 (SECV: 20.9 μg L−1) for monoterpenes and 0.80 (SECV: 1658 ?g L-1) for short-chain fatty acids. This study has shown that volatile chemical compounds present in wine can be measured by NIR spectroscopy. Further development with larger data sets will be required to test the predictive ability of the NIR calibration models developed.

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The research in software science has so far been concentrated on three measures of program complexity: (a) software effort; (b) cyclomatic complexity; and (c) program knots. In this paper we propose a measure of the logical complexity of programs in terms of the variable dependency of sequence of computations, inductive effort in writing loops and complexity of data structures. The proposed complexity mensure is described with the aid of a graph which exhibits diagrammatically the dependence of a computation at a node upon the computation of other (earlier) nodes. Complexity measures of several example programs have been computed and the related issues have been discussed. The paper also describes the role played by data structures in deciding the program complexity.

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A fuzzy logic based centralized control algorithm for irrigation canals is presented. Purpose of the algorithm is to control downstream discharge and water level of pools in the canal, by adjusting discharge release from the upstream end and gates settings. The algorithm is based on the dynamic wave model (Saint-Venant equations) inversion in space, wherein the momentum equation is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. The fuzzy rule based model is developed on fuzzification of a new mathematical model for wave velocity, the derivational details of which are given. The advantages of the fuzzy control algorithm, over other conventional control algorithms, are described. It is transparent and intuitive, and no linearizations of the governing equations are involved. Timing of the algorithm and method of computation are explained. It is shown that the tuning is easy and the computations are straightforward. The algorithm provides stable, realistic and robust outputs. The disadvantage of the algorithm is reduced precision in its outputs due to the approximation inherent in the fuzzy logic. Feed back control logic is adopted to eliminate error caused by the system disturbances as well as error caused by the reduced precision in the outputs. The algorithm is tested by applying it to water level control problem in a fictitious canal with a single pool and also in a real canal with a series of pools. It is found that results obtained from the algorithm are comparable to those obtained from conventional control algorithms.

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A fuzzy dynamic flood routing model (FDFRM) for natural channels is presented, wherein the flood wave can be approximated to a monoclinal wave. This study is based on modification of an earlier published work by the same authors, where the nature of the wave was of gravity type. Momentum equation of the dynamic wave model is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. Hence, the FDFRM gets rid of the assumptions associated with the momentum equation. Also, it overcomes the necessity of calculating friction slope (S-f) in flood routing and hence the associated uncertainties are eliminated. The fuzzy rule based model is developed on an equation for wave velocity, which is obtained in terms of discontinuities in the gradient of flow parameters. The channel reach is divided into a number of approximately uniform sub-reaches. Training set required for development of the fuzzy rule based model for each sub-reach is obtained from discharge-area relationship at its mean section. For highly heterogeneous sub-reaches, optimized fuzzy rule based models are obtained by means of a neuro-fuzzy algorithm. For demonstration, the FDFRM is applied to flood routing problems in a fictitious channel with single uniform reach, in a fictitious channel with two uniform sub-reaches and also in a natural channel with a number of approximately uniform sub-reaches. It is observed that in cases of the fictitious channels, the FDFRM outputs match well with those of an implicit numerical model (INM), which solves the dynamic wave equations using an implicit numerical scheme. For the natural channel, the FDFRM Outputs are comparable to those of the HEC-RAS model.

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Sorghum ergot, caused by Claviceps africana, has remained a major disease problem in Australia since it was first recorded in 1996, and is the focus of a range of biological and integrated management research. Artificial inoculation using conidial suspensions is an important tool in this research. Ergot infection is greatly influenced by environmental factors, so it is important to reduce controllable sources of variation such as inoculum concentration. The use of optical density was tested as a method of quantifying conidial suspensions of C. africana, as an alternative to haemocytometer counts. This method was found to be accurate and time efficient, with possible applications in other disease systems.

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Aim Psychotic-like experiences (PLEs) are common in young people and are associated with both distress and adverse outcomes. The Community Assessment of Psychic Experiences-Positive Scale (CAPE-P) provides a 20-item measure of lifetime PLEs. A 15-item revision of this scale was recently published (CAPE-P15). Although the CAPE-P has been used to assess PLEs in the last 12 months, there is no version of the CAPE for assessing more recent PLEs (e.g. 3 months). This study aimed to determine the reliability and validity of the current CAPE-P15 and assess its relationship with current distress. Method A cross-sectional online survey of 489 university students (17–25 years) assessed lifetime and current substance use, current distress, and lifetime and 3-month PLEs on the CAPE-P15. Results Confirmatory factor analysis indicated that the current CAPE-P15 retained the same three-factor structure as the lifetime version consisting of persecutory ideation, bizarre experiences and perceptual abnormalities. The total score of the current version was lower than the lifetime version, but the two were strongly correlated (r = .64). The current version was highly predictive of generalized distress (r = .52) and indices that combined symptom frequency with associated distress did not confer greater predictive power than frequency alone. Conclusion This study provided preliminary data that the current CAPE-P15 provides a valid and reliable measure of current PLEs. The current CAPE-P15 is likely to have substantial practical utility if it is later shown to be sensitive to change, especially in prevention and early intervention for mental disorders in young people.

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A fuzzy logic system (FLS) with a new sliding window defuzzifier is proposed for structural damage detection using modal curvatures. Changes in the modal curvatures due to damage are fuzzified using Gaussian fuzzy sets and mapped to damage location and size using the FLS. The first four modal vectors obtained from finite element simulations of a cantilever beam are used for identifying the location and size of damage. Parametric studies show that modal curvatures can be used to accurately locate the damage; however, quantifying the size of damage is difficult. Tests with noisy simulated data show that the method detects damage very accurately at different noise levels and when some modal data are missing.

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A series of metabolism experiments investigated the recovery of continuous-, intravenously infused chromium complexed with ethylenediamine tetra-acetic acid (CrEDTA) and lithium sulphate in the urine of cattle with a view to using the markers to estimate urine and metabolite output in grazing cattle. The recovery of Cr in urine from these infusions was similar (90%) in metabolism trials when cattle consumed three very contrasting diets: high-grain formulated pellet, lucerne hay (Medicago sativa) or low-quality native grass hay (predominantly Heteropogon contortus). By contrast, Li recovery in urine averaged 46.3 +/- 0.40% and 72.6 +/- 0.43% for native pasture and lucerne hays, respectively, but was not constant across days. There was negligible transfer of Cr from CrEDTA in blood serum to the rumen or faeces, whereas appreciable quantities of infused Li were found in both. The ratio of urine volume estimated by spot samples and marker dilution of Cr, to urine volume measured gravimetrically, was 1.05. In grazing studies using rumen-fistulated (RF) steers grazing seven different tropical and temperate grass and legume pastures, the ratio of concentrations of purine derivatives (PD) to Cr in spot samples of urine was shown to vary diurnally in the range of 49% to 157% of the average 24 h value. This finding indicated the need for regular sampling of urine to achieve an accurate average value for the PD: Cr ratio in urine for use in estimating urinary PD excretion and hence microbial protein production in the rumen. It was concluded that continuous, intravenous infusion of CrEDTA resulted in a constant recovery of Cr in the urine of cattle across diets and, provided an intensive sampling regime was followed to account for diurnal variation, it would be suitable as a marker to estimate urine volume and urinary output of PD in grazing cattle.

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Based on the conclusions drawn in the bijective transformation between possibility and probability, a method is proposed to estimate the fuzzy membership function for pattern recognition purposes. A rational function approximation to the probability density function is obtained from the histogram of a finite (and sometimes very small) number of samples. This function is normalized such that the highest ordinate is one. The parameters representing the rational function are used for classifying the pattern samples based on a max-min decision rule. The method is illustrated with examples.

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Combating the spread of invasive fish is problematic, with eradication rarely possible and control options varying enormously in their effectiveness. In two small impoundments in north-eastern Australia, an electrofishing removal program was conducted to control an invasive tilapia population. We hypothesised that electrofishing would reduce the population density of Oreochromis mossambicus (Mozambique tilapia), to limit the risk of downstream spread into areas of high conservation value. We sampled by electrofishing monthly for 33 months. Over this period, there was an 87% decline in catch per unit effort (CPUE) of mature fish, coupled with a corresponding increase of 366% in the number of juveniles, suggesting a density-dependent response in the stock-recruitment relationship for the population. Temperature was inversely related to CPUE (r=0.43, lag=10 days), implying greater electrofishing efficiency in cooler months. The reduction in breeding stock is likely to reduce the risk of spread and render the population vulnerable to other control measures such as netting and/or biological control. Importantly, the current study suggests routine electrofishing may be a useful control tool for invasive fish in small impoundments when the use of more destructive techniques, such as piscicides, is untenable.

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This study addresses three important issues in tree bucking optimization in the context of cut-to-length harvesting. (1) Would the fit between the log demand and log output distributions be better if the price and/or demand matrices controlling the bucking decisions on modern cut-to-length harvesters were adjusted to the unique conditions of each individual stand? (2) In what ways can we generate stand and product specific price and demand matrices? (3) What alternatives do we have to measure the fit between the log demand and log output distributions, and what would be an ideal goodness-of-fit measure? Three iterative search systems were developed for seeking stand-specific price and demand matrix sets: (1) A fuzzy logic control system for calibrating the price matrix of one log product for one stand at a time (the stand-level one-product approach); (2) a genetic algorithm system for adjusting the price matrices of one log product in parallel for several stands (the forest-level one-product approach); and (3) a genetic algorithm system for dividing the overall demand matrix of each of the several log products into stand-specific sub-demands simultaneously for several stands and products (the forest-level multi-product approach). The stem material used for testing the performance of the stand-specific price and demand matrices against that of the reference matrices was comprised of 9 155 Norway spruce (Picea abies (L.) Karst.) sawlog stems gathered by harvesters from 15 mature spruce-dominated stands in southern Finland. The reference price and demand matrices were either direct copies or slightly modified versions of those used by two Finnish sawmilling companies. Two types of stand-specific bucking matrices were compiled for each log product. One was from the harvester-collected stem profiles and the other was from the pre-harvest inventory data. Four goodness-of-fit measures were analyzed for their appropriateness in determining the similarity between the log demand and log output distributions: (1) the apportionment degree (index), (2) the chi-square statistic, (3) Laspeyres quantity index, and (4) the price-weighted apportionment degree. The study confirmed that any improvement in the fit between the log demand and log output distributions can only be realized at the expense of log volumes produced. Stand-level pre-control of price matrices was found to be advantageous, provided the control is done with perfect stem data. Forest-level pre-control of price matrices resulted in no improvement in the cumulative apportionment degree. Cutting stands under the control of stand-specific demand matrices yielded a better total fit between the demand and output matrices at the forest level than was obtained by cutting each stand with non-stand-specific reference matrices. The theoretical and experimental analyses suggest that none of the three alternative goodness-of-fit measures clearly outperforms the traditional apportionment degree measure. Keywords: harvesting, tree bucking optimization, simulation, fuzzy control, genetic algorithms, goodness-of-fit

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Background Data describing the Australian allied health workforce is inadequate and so insufficient for workforce planning. National health policy reform requires that health-care models take into account future workforce requirements, the distribution and work contexts of existing practitioners, training needs, workforce roles and scope of practice. Good information on this workforce is essential for managing services as demands increase, accountability of practitioners, measurement of outcomes and benchmarking against other jurisdictions. A comprehensive data set is essential to underpin policy and planning to meet future health workforce needs. Discussion Some data on allied health professions is managed by the Australian Health Practitioner Regulation Agency; however, there is limited information regarding several core allied health professions. A global registration and accreditation scheme recognizing all allied health professions might provide safeguards and credibility for professionals and their clients. Summary Arguments are presented about inconsistencies and voids in the available information about allied health services. Remedying these information deficits is essential to underpin policy and planning for future health workforce needs. We make the case for a comprehensive national data set based on a broad and inclusive sampling process across the allied health population.

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Background Sedentary behaviour is associated with several deleterious health consequences. Although device-based measures of sedentary time are available, they are costly and do not provide a measure of domain specific sedentary time. High quality self-report measures are necessary to accurately capture domain specific sedentary time, and to provide an alternative to devices when cost is an issue. In this study, the Past-day Adults’ Sedentary Time (PAST) questionnaire, previously shown to have acceptable validity and reliability in a sample of breast cancer survivors, was modified for a university sample and validity of the modified questionnaire was examined compared with activPAL. Methods Participants (n = 58, age = 18–55 years, 48% female, 66% students) were recruited from the University of Queensland (students and staff). They answered the PAST questionnaire, which asked about time spent sitting or lying down for work, study, travel, television viewing, leisure-time computer use, reading, eating, socialising and other purposes, during the previous day. Time reported for these questions was summed to provide a measure of total sedentary time. Participants also wore an activPAL device for the full day prior to completing the questionnaire and recorded their wake and sleep times in an activity log. Total waking sedentary time derived from the activPAL was used as the criterion measure. Correlation (Pearson's r) and agreement (Bland–Altman plots) between PAST and activPAL sedentary time were examined. Results Participants were sedentary (activPAL-determined) for approximately 66% of waking hours. The correlation between PAST and activPAL sedentary time for the whole sample was r = 0.50 [95% confidence interval (CI) = 0.28–0.67]; and higher for non-students (r = 0.63, 95% CI = 0.26–0.84) than students (r = 0.46, 95% CI = 0.16–0.68). Bland–Altman plots revealed that the mean difference between the two measures was 19 min although limits of agreement were wide (95% limits of agreement −4.1 to 4.7 h). Discussion The PAST questionnaire provides an acceptable measure of sedentary time in this population, which included students and adults with high workplace sitting. These findings support earlier research that questionnaires employing past-day recall of sedentary time provide a viable alternative to existing sedentary behaviour questionnaires.