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At least 973 records · Page 54Linked to original sources
PubMed2003

Cokriging optimization of monitoring network configuration based on fuzzy and non-fuzzy variogram evaluation.

A number of optimization approaches regarding monitoring network design and sampling optimization procedures have been reported in the literature. Cokriging Estimation Variance (CEV) is a useful optimization tool to determine the influence of the spatial configuration of monitoring networks on parameter estimations. It was used in order to derive a reduced configuration of a nitrate concentration monitoring well network. The reliability of the reduced monitoring configuration suffers from the uncertainties caused by the variographer's choices and several inherent assumptions. These uncertainties can be described considering the variogram parameters as fuzzy numbers and the uncertainties by means of membership functions. Fuzzy and non-fuzzy approaches were used to evaluate differences among well network configurations. Both approaches permitted estimates of acceptable levels of information loss for nitrate concentrations in the monitoring network of the aquifer of the Plain of Modena, Northern Italy. The fuzzy approach was found to require considerably more computational time and numbers of wells at comparable level of information loss.

Data Collection↗
PubMed1999

Fuzzy segmentation spatiotemporal patterns of cognitive potential into microstates.

Fuzzy c-mean algorithm was applied to segment spatiotemporal patterns of brainwave into microstates and memberships. The optimal clustering number was estimated with both the trends of objective function and the eigenvalue number of microstates. Comparable spatial patterns may occur at different temporal moments in consideration of fuzzy index that is beyond the limit of serial processing. Those techniques were illustrated with multichannel event-related potentials recorded from 9 subjects during Stroop test. Statistical parametric map of F value suggested that significant task (color decision and word decision) effect involve widespread cortical regions after stimulus onset 280 ms and this result supports the hypothesis that Stroop interference derives from response competition during post-perception stage. As significant stimulus (congruent stimulus and incongruent stimulus) effect only involves several separate visual regions within 100 ms after stimulus presentation, it may reflect top-down attentional regulation.

Algorithms↗
PubMed2003

Neurofuzzy classification of the effect of diabetes mellitus on carotid artery.

Here, we present a new clasification system for the effects of diabetes mellitus (DM) on carotid artery by using neurofuzzy system. Blood flow hemodynamics were obtained from 118 carotid arteries of 59 patients with DM by using 7.5 MHz transducer and Doppler-M unit. Vmax = peak systole, Vmin = end diastole, resistive index (RI), and pulsatile index (PI) were measured with the use of Doppler sonography. These values were applied to neurofuzzy system using NEFCLASS model. With the increase of epoch from 200 to 500 and pruning of fuzzy rules, our classification system was found to be successful in 85% of the cases. In 100 of 118 patients the classificitaion system was found to be correct. Our findings suggest that with the application of Doppler signal parameters from carotid arteries to neurofuzzy system may produce a new and reliable classification system for diagnosing diameter stenosis.

Algorithms↗
PubMed2004

Intelligent self-tuning of PID control for the robotic testing system for human musculoskeletal joints test.

In this paper, an intelligent proportional-integral-derivative (PID) control method is introduced to the robotic testing system for the biomechanical study of human musculoskeletal joints. For the testing system, the robot is a highly nonlinear and heavily coupled complicated system, and the human spinal specimen also demonstrates nonlinear property when undergoing testing. Although the conventional PID control approach is extensively used in most industrial control systems, it will break down for nonlinear systems, particularly for complicated systems that have no precise mathematical models. To overcome those difficulties, an intelligent fuzzy PID controller is proposed replacing the widely used conventional PID controllers. The fuzzy PID algorithm is outlined using the fuzzy set theory. The design techniques are developed based on the linguistic phase plane approach. The heuristic rules of syntheses are summarized into a rule-based expert system. Experiments are carried out and the results demonstrate the good performance of the robotic testing system using the proposed control method.

Algorithms↗
PubMed2004

A recipe for unconventional evenness measures.

The degree to which abundances are evenly divided among the species of a given community is a basic property of any biological community. Several evenness indices have thus far been proposed in ecological literature. However, despite their vast potential applicability in ecological research, none seems to be generally preferred. In this paper, I first summarize the basic requirements that evenness measures should meet to adequately behave in ecological studies. Then, I discuss the major drawbacks of these requirements and propose an alternative family of measures that are based on the notion of specificity used in fuzzy set theory for measuring the uncertainty associated with a fuzzy set.

Fuzzy Logic↗
PubMed2004

Automated medical diagnosis with fuzzy stochastic models: monitoring chronic diseases.

As the world population ages, the patients per physician ratio keeps on increasing. This is even more important in the domain of chronic pathologies where people are usually monitored for years and need regular consultations. To address this problem, we propose an automated system to monitor a patient population, detecting anomalies in instantaneous data and in their temporal evolution, so that it could alert physicians. By handling the population of healthy patients autonomously and by drawing the physicians' attention to the patients-at-risk, the system allows physicians to spend comparatively more time with patients who need their services. In such a system, the interaction between the patients, the diagnosis module, and the physicians is very important. We have based this system on a combination of stochastic models, fuzzy filters, and strong medical semantics. We particularly focused on a particular tele-medicine application: the Diatelic Project. Its objective is to monitor chronic kidney-insufficient patients and to detect hydration troubles. During two years, physicians from the ALTIR have conducted a prospective randomized study of the system. This experiment clearly shows that the proposed system is really beneficial to the patients' health.

Aged↗
PubMed2004

Spatiotemporal analysis of ERP during chinese idiom comprehension.

The objective of the present study was to elucidate the neural underpinning of Chinese idiom comprehension with spatiotemporal patterns of ERP. Thirteen subjects were required to decide whether the last character of each viewed Chinese four-character idiom was correct or not. Fuzzy c-means algorithm based on shape similarity was applied to segmenting spatiotemporal patterns of ERP. Statistical parametric map of t-statistic (SPM(t)) was performed after realignment according to the referential frame provided by fuzzy clustering in order to overcome temporal mismatch. Within 540 ms post-stimulus onset, the spatiotemporal patterns of ERP under both conditions could be segmented into 7 stages optimally and both share the first four microstates with variant membership functions and durations. SPM(t) presented significant differences in multiple regions in 3 stages: (1) during 120-150 ms, the early right hemispheric negativities (ERHN) inboth frontal and temporoparietal areas were likely to reflect both initial syntactic processing and visual word-form mismatch; (2) during 320-380 ms (the N400 stage), negative deflections in left frontal, left anterior temporal, centrofrontal regions might coordinate and integrate both syntactic and semantic analysis in extensive right hemisphere; (3) during 480-540 ms (the P600 stage), positive deflections in left temporoparietal and occipital regions seemed to reflect the reanalysis and the integration of word meanings to obtain the over all meaning of idioms. Our study has implicated the brain mechanism of language comprehension common to alphabetic language as well as that specialized in logographic language.

Adult↗
PubMed2004

Optimal expansion of water quality monitoring network by fuzzy optimization approach.

River reaches are frequently classified with respect to various mode of water utilization depending on the quantity and quality of water resources available at different location. Monitoring of water quality in a river system must collect both temporal and spatial information for comparison with respect to the preferred situation of a water body based on different scenarios. Designing a technically sound monitoring network, however, needs to identify a suite of significant planning objectives and consider a series of inherent limitations simultaneously. It would rely on applying an advanced systems analysis technique via an integrated simulation-optimization approach to meet the ultimate goal. This article presents an optimal expansion strategy of water quality monitoring stations for fulfilling a long-term monitoring mission under an uncertain environment. The planning objectives considered in this analysis are to increase the protection degree in the proximity of the river system with higher population density, to enhance the detection capability for lower compliance areas, to promote the detection sensitivity by better deployment and installation of monitoring stations, to reflect the levels of utilization potential of water body at different locations, and to monitor the essential water quality in the upper stream areas of all water intakes. The constraint set contains the limitations of budget, equity implication, and the detection sensitivity in the water environment. A fuzzy multi-objective evaluation framework that reflects the uncertainty embedded in decision making is designed for postulating and analyzing the underlying principles of optimal expansion strategy of monitoring network. The case study being organized in South Taiwan demonstrates a set of more robust and flexible expansion alternatives in terms of spatial priority. Such an approach uniquely indicates the preference order of each candidate site to be expanded step-wise whenever the budget limitation is sensitive in the government agencies.

Environmental Monitoring↗
PubMed2004

The examination of the effects of obesity on a number of arteries and body mass index by using expert systems.

In this study, the areas affected from obesity were examined by classifying divergent arteries and body mass index (BMI) of 30 healthy persons and 52 obese persons by using expert systems, and the classifying performances of NEFCLASS and CANFIS, which are expert systems were compared. As a result of this comparison, it is observed that the classifying performance of NEFCLASS is better than that of CANFIS, and the causes of this are examined. Furthermore, it is observed that after these classifications, obesity affects the BMI rather than divergent arteries.

Arteries↗
PubMed2004

A neurofuzzy classification system for the effects of diabetes mellitus on ophtalmic artery.

Here, we present a classification system for the effects of diabetes mellitus (DM) on blood flow hemodynamics of the ophthalmic arteries by using neurofuzzy system. Blood flow hemodynamics were obtained from 80 ophthalmic arteries of 20 healthy persons and 20 patients with DM by using 7.5 MHz transducer and Doppler-M unit. Peak systole, peak diastole, resistive index (RI), pulsatile index (PI), and systole/diastole rate (SDR) were measured with the use of Doppler sonography. These values were applied to neurofuzzy system using NEFCLASS model. The performance of this classification system was examined with the application of the data obtained from Doppler analyses of the right and left ophthalmic arteries to the neurofuzzy system. After learning and testing processes, 85% success rates were reached from the data of right ophthalmic arteries, and 87.5% success rates were reached from the data of left ophthalmic arteries. Our findings suggest that neurofuzzy system may provide a successful classification system for the effects of DM on either right or left ophthalmic arteries with the application of Doppler signal parameters from carotid arteries to neurofuzzy system may produce a new and reliable classification system for diagnosing diameter stenosis.

Blood Flow Velocity↗
PubMed2004

Classification of mitral insufficiency and stenosis using MLP neural network and neuro-fuzzy system.

Cardiac Doppler signals recorded from mitral valve of 60 patients were transferred to a personal computer by using a 16-bit sound card. The power spectral density (PSD) was applied to the recorded signal from each patient. In order to do a good interpretation and rapid diagnosis, PSD values classified using multilayer perceptron (MLP) and neuro-fuzzy system. Our findings demonstrated that 93.33% classification success rate was obtained from MLP, 90% classification success rate was obtained from neuro-fuzzy system. The classification results show that MLP offers best results in the case of diagnosis.

Diagnosis, Computer-Assisted↗
PubMed2004

Application of FFT-analyzed umbilical artery doppler signals to fuzzy algorithm.

Doppler signals, recorded from the umbilical artery of 60 women with pregnancy, were transferred to personal computer via a 16-bit sound card. The fast Fourier transform (FFT) method was applied to the recorded signal from each patient. Because FFT method inherently cannot offer a good spectral resolution at highly turbulent blood flows, it sometimes causes wrong interpretation of Doppler signals. In order to avoid this problem, umbilical artery Doppler blood flow velocity parameters were introduced to a fuzzy algorithm. It is observed that the fuzzy algorithm gives true results for interpretation of umbilical artery blood flow velocity parameters. Forty-five blood flow velocity parameters of 60 women with pregnancy and 15 parameters in training data have been used in a fuzzy system as testing data. The overall success ratio in training data and the testing data were 95.55 and 93.35% respectively.

Algorithms↗
PubMed2004

Application of fuzzy functions for visual presentation of medical data.

While interpretation of medical data is very often an ambiguous process, computers usually display results of recommendations, provided by both human experts and computer algorithms, as concrete data. This study proposes a visual presentation of relative degrees of uncertainty along with "standard" concrete medical data. A medical parameter (mean arterial pressure) is dynamically evaluated during surgery for being too low or too high. Fuzzy membership functions are utilized to display degrees of deviation in the form of a clear and concise pie chart. Thus, in the Operating Room the anesthesiologist can be provided with an easy statistical assessment of uncertainty of existing recommendations.

Algorithms↗
PubMed2004

Fuzzy simulation of pharmacokinetic models: case study of whole body physiologically based model of diazepam.

The aim of the present study is to develop and implement a methodology that accounts for parameter variability and uncertainty in the presence of qualitative and semi-quantitative information (fuzzy simulations) as well as when some parameters are better quantitatively defined than others (fuzzy-probabilistic approach). The fuzzy simulations method consists of (i) representing parameter uncertainty and variability by fuzzy numbers and (ii) simulating predictions by solving the pharmacokinetic model. The fuzzy-probabilistic approach includes an additional transformation between fuzzy numbers and probability density functions. To illustrate the proposed method a diazepam WBPBPK model was used where the information for hepatic intrinsic clearance determined by in vitro-in vivo scaling was semi-quantitative. The predicted concentration time profiles were compared with those resulting from a Monte Carlo simulation. Fuzzy simulations can be used as an alternative to Monte Carlo simulation.

Animals↗
PubMed1993

Memory independence and memory interference in cognitive development.

Recent experiments have established the surprising fact that age improvements in reasoning are often dissociated from improvements in memory for determinative informational inputs. Fuzzy-trace theory explains this memory-independence effect on the grounds that reasoning operations do not directly access verbatim traces of critical background information but, rather, process gist that was retrieved and edited in parallel with the encoding of such information. This explanation also envisions 2 ways in which children's memory and reasoning might be mutually interfering: (a) memory-to-reasoning interference, a tendency to process verbatim traces of background inputs on both memory probes and reasoning problems that simultaneously improves memory performance and impairs reasoning, and (b) reasoning-to-memory interference, a tendency for reasoning activities that produce problem solutions to erase or reduce the distinctiveness of verbatim traces of background inputs. Both forms of interference were detected in studies of children's story inferences.

Attention↗
PubMed1997

Application of fuzzy reasoning in an expert system for ultrasonography.

OBJECTIVES: To apply fuzzy reasoning in a computer-assisted diagnostic system for ultrasonography and to evaluate its clinical utility as a diagnostic aid for the unskilled clinician. METHODS: A computer-assisted diagnostic system for ultrasonography was constructed to differentiate metastatic from inflammatory lymph nodes. The pattern of a skilled clinician's considerations was simulated with the fuzzy expert system. Three fuzzy production rules were set up according to the diagnostic criteria for lymphadenopathy. Each rule was transformed into a membership function. The max-min composition method was used for inference and the centroid method for defuzzification. The system was tested with 20 clinicians who were one to three years after graduation and inexperienced in ultrasonography. Accuracy, sensitivity and specificity were evaluated. RESULTS: The average increase in accuracy was 8.5%, and the sensitivity and specificity 10.7% and 6.4% respectively. These scores were significant for accuracy (P = 0.005), sensitivity (P = 0.02) and specificity (P = 0.036). CONCLUSIONS: Application of fuzzy reasoning in an expert system for ultrasonography improves the diagnostic performance of inexperienced clinicians.

Clinical Competence↗
PubMed1999

How optimal are computer-calculated optimal diets?

OBJECTIVE: This paper aims at clarifying the meaning of 'optimal diets'. DESIGN: Two different optimization approaches are considered. Both depart from people's actual diets which in general do not meet all their nutrient requirements. In the first case (non fuzzy approach) the actual diets are modified such that all nutrient intake recommendations are met and the resulting changes in the persons' food habits are as little as possible. In the second case (fuzzy approach) the actual diets are modified such that the persons' food habits undergo little change and the nutrient intake recommendations are met as well as possible. Both approaches are evaluated using data on the actual diets of three randomly chosen participants of the Bavarian Food Intake Survey. RESULTS: With both approaches feasible solutions can be found. The optimal diets computed with the non fuzzy approach satisfy all the persons' nutrient requirements, but make it necessary to change the persons' food habits considerably. When compared to the subjects' actual diets, the optimal diets computed with the fuzzy approach yield improvements for the intake of many nutrients, but in some cases deteriorations also occur (for example, concerning folate, calcium and iodine). So, the process and the results of the fuzzy approach are not 'Pareto efficient'. But it has the advantage that the corresponding optimal diets deviate from the actual diets by no more than about 3-5 kitchen units per day. CONCLUSIONS: The term 'optimal' does not have a general meaning. An 'optimal diet' does not necessarily meet all the nutrient requirements of a person. Optimality only depends on the respective conditions any optimization is based on.

Adult↗
PubMed2003

Total luminescence spectroscopy with pattern recognition for classification of edible oils.

Total luminescence spectroscopy combined with pattern recognition has been used to discriminate between four different types of edible oils, extra virgin olive (EVO), non-virgin olive (NVO), sunflower (SF) and rapeseed (RS) oils. Simplified fuzzy adaptive resonance theory mapping (SFAM), traditional back propagation (BP) and radial basis function (RBF) neural networks provided 100% classification for 120 samples, SFAM was found to be the most efficient. The investigation was extended to the adulteration of percentage v/v SF or RS in EVO at levels from 5% to 90% creating a total of 480 samples. SFAM was found to be more accurate than RBF and BP for classification of adulterant level. All misclassifications for SFAM occurred at the 5% v/v level resulting in a total of 99.375% correctly classified oil samples. The percentage of adulteration may be described by either RBF network (2.435% RMSE) or a simple Euclidean distance relationship of the principal component analysis (PCA) scores (2.977% RMSE) for v/v RS in EVO adulteration.

Computational Biology↗