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Results 351 - 400 of 802
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Subasi Abdulhamit - - 2007
Intelligent computing tools such as artificial neural network (ANN) and fuzzy logic approaches are demonstrated to be competent when applied individually to a variety of problems. Recently, there has been a growing interest in combining both these approaches, and as a result, neuro-fuzzy computing techniques have been evolved. In this ...
Rebuffo Cecilia A - - 2006
Differentiation of the species within the genus Listeria is important for the food industry but only a few reliable methods are available so far. While a number of studies have used Fourier transform infrared (FTIR) spectroscopy to identify bacteria, the extraction of complex pattern information from the infrared spectra remains ...
Moens M - - 2006
AIMS: To evaluate the electronic nose (EN) as method for the identification of ten clinically important micro-organisms. METHODS AND RESULTS: A commercial EN system with a series of ten metal oxide sensors was used to characterize the headspace of the cultured organisms. The measurement procedure was optimized to obtain reproducible ...
Chiu Alan W L - - 2006
It has been previously shown that wavelet artificial neural networks (WANNs) are able to classify the different states of epileptiform activity and predict the onsets of seizure-like events (SLEs) by offline processing (Ann. Biomed. Eng. 33(6):798-810, 2005) of the electrical data from the in-vitro hippocampal slice model of recurrent spontaneous ...
Khayamian T - - 2006
A wavelet neural network (WNN) model is proposed for extending the dynamic range of Cu(II) determination by differential pulse adsorption cathodic stripping voltammetry (DP-AdSV) using xylenol orange (XO) as a suitable ligand. All of voltammograms data consisting of Cu(II) and Cu(II)-XO peak currents were used in WNN model. The WNN ...
Dussol Bertrand - - 2006
The pathophysiology of idiopathic calcium oxalate nephrolithiasis involves metabolic abnormalities. Previous studies gave conflicting results about the metabolic factors in stone formers. Artificial neural networks (ANN) are new methods based on computer programming that have outperformed conventional methods in prediction of outcomes in different medical applications. The aim of our ...
Bugliosi R - - 2006
Most of the forecasting models of Plasmopara viticola infections are based upon empiric correlations between meteorological/environmental data and pathogen outbreak. These models generally overestimate the risk of infections and induce to treat the vineyard even if it should be not necessary. In rare cases they underrate the risk of infection ...
Ung S T - - 2006
INTRODUCTION: The traditional fuzzy-rule-based risk assessment technique has been applied in many industries due to the capability of combining different parameters to obtain an overall risk. However, a drawback occurs as the technique is applied in circumstances where there are multiple parameters to be evaluated that are described by multiple ...
Adamson Peter A - - 2006
The M-Arch Model introduced herein expands on the utility and simplicity of the tripod concept to consider the overall length of the cartilaginous tripod arch as the major determinant of nasal tip parameters. Surgeons may exploit this powerful tool using modern grafting, suture, and cartilage-cutting techniques to predictably achieve desired ...
Garg Prabha - - 2006
This paper has two objectives: first to develop an in silico model for the prediction of blood brain barrier permeability of new chemical entities and second to find the role of active transport specific to the P-glycoprotein (P-gp) substrate probability in blood brain barrier permeability. An Artificial Neural Network (ANN) ...
Linder R - - 2006
OBJECTIVES: Accurately predicting disease progress from a set of predictive variables is an important aspect of clinical work. For binary outcomes, the classical approach is to develop prognostic logistic regression (LR) models. Alternatively, machine learning algorithms were proposed with artificial neural networks (ANN) having become popular over the last decades. ...
Mendyk Aleksander - - 2006
Artificial neural networks (ANNs) were used as modeling tools for prediction of various drugs release patterns from hydrodynamically balanced systems (HBS) composed with Metholose 90SH (hydroxypropylmethylcellulose--HPMC). The objective was to provide predictive and data-mining models of analyzed problem. It was found that ANNs are capable to accurately predict release patterns ...
Marengo Emilio - - 2006
A Portland cement process was taken into consideration and monitored for one month with respect to polluting emissions, fuel and raw material physical-chemical properties, and operative conditions. Soft models, based on linear (partial least-squares, PLS, and principal component regression, PCR) and nonlinear (artificial neural networks, ANNs) approaches, were employed to ...
Peng Yingxu - - 2006
Immediate release acetaminophen (APAP) beads with 40% drug loading were prepared using the extrusion-spheronization process. Eighteen batches of beads were prepared based on a full factorial design by varying process variables such as extruder type, extruder screw speed, spheronization speed, and spheronization time. An in vitro dissolution test was carried ...
Zeng Yong - - 2006
The weekly water quality monitor data of Liuhai lakes between April 2003 and November 2004 in Beijing City were used as an example to build an artificial neural networks (ANN) model and a multi-varieties regression model respectively for predicting the fresh water algae bloom. The different predicted abilities of the ...
Geli Patricia - - 2006
In recent decades, penicillin-resistant pneumococci (PRP) have emerged and spread rapidly between and within countries over the world. In this study we developed an iterative artificial neural network (ANN) model to describe and predict the spread of PRP in space and time as a function of antibiotic consumption and a ...
Dal Moro F - - 2006
The objective of this study was to optimally predict the spontaneous passage of ureteral stones in patients with renal colic by applying for the first time support vector machines (SVM), an instance of kernel methods, for classification. After reviewing the results found in the literature, we compared the performances obtained ...
Mueller Martina - - 2006
Approximately 30% of intubated preterm infants with respiratory distress syndrome (RDS) will fail attempted extubation, requiring reintubation and mechanical ventilation. Although ventilator technology and monitoring of premature infants have improved over time, optimal extubation remains challenging. Furthermore, extubation decisions for premature infants require complex informational processing, techniques implicitly learned through ...
Abbod M F MF Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK. - - 2006
New techniques for the prediction of tumour behaviour are needed since statistical analysis has low accuracy and is not applicable to the individual. Artificial intelligence (AI) may provide suitable methods. We have compared the predictive accuracies of neuro-fuzzy modelling (NFM), artificial neural networks (ANN) and traditional statistical methods for the ...
Polur Prasad D - - 2006
Computer speech recognition of individuals with dysarthria, such as cerebral palsy patients requires a robust technique that can handle conditions of very high variability and limited training data. In this study, application of a 10 state ergodic hidden Markov model (HMM)/artificial neural network (ANN) hybrid structure for a dysarthric speech ...
Tabaraki R - - 2006
A wavelet neural network (WNN) model in quantitative structure property relationship (QSPR) was developed for predicting solubility of 25 anthraquinone dyes in supercritical carbon dioxide over a wide range of pressures (70-770 bar) and temperatures (291-423 K). A large number of descriptors were calculated with Dragon software and a subset ...
Rizkalla N?vine - - 2005
Artificial Neural Networks (ANNs) were used to predict nanoparticle size and micropore surface area of polylactic acid nanoparticles, prepared by a double emulsion method. Different batches were prepared while varying polymer and surfactant concentration, as well as homogenization pressure. Two commercial ANNs programs were evaluated: Neuroshell Predictor, a black-box software ...
Dohnal Vlastimil - - 2005
The artificial neural networks (ANN) are very often applied in many areas of toxicology for the solving of complex problems, such as the prediction of chemical compound properties and quantitative structure-activity relationship. The aim of this contribution is to give the basic knowledge about conception of ANN, theirs division and ...
Schmid Oliver - - 2005
Surface enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF MS) has been applied in large numbers of oncological studies but the microbiological field has not been extensively explored to date. This paper describes the application of SELDI-TOF MS in concert with a multi-layer perceptron artificial neural network (ANN) with a ...
Wagner Mathias - - 2006
The 2004 Nobel Prize in Physiology or Medicine laureates, Richard Axel and Linda Buck, have made smell a less enigmatic sense to study. In clinical routine, olfactory function is assessed using defined concentrations of a single defined substance, a setting which is uncommon in daily life. The present study was ...
Hajmeer M - - 2006
Using artificial neural networks (ANNs), a highly accurate model was developed to simulate survival curves of Listeria monocytogenes in chorizos as affected by the initial water activity (a(w0)) of the sausage formulation, temperature (T), and air inflow velocity (F) where the sausages are stored. The ANN-based survival model (R(2)=0.970) outperformed ...
Dou Ying - - 2006
A method for simultaneous, nondestructive analysis of aminopyrine and phenacetin in compound aminopyrine phenacetin tablets with different concentrations has been developed by principal component artificial neural networks (PC-ANNs) on near-infrared (NIR) spectroscopy. In PC-ANN models, the spectral data were initially analyzed by principal component analysis. Then the scores of the ...
Liberda Jonathan J - - 2005
PURPOSE: To develop an artificial neural network (ANN) model of apoptotic response in gamma irradiated human lymphocytes. To assess the feasibility of training ANN radiobiological models using data collected with flow cytometry. MATERIALS AND METHODS: Irradiated isolated human lymphocytes were labelled with Annexin V-Fluorescein Isothiocyanate (FITC) and 7-Amino-Actinomycin D (7AAD) ...
Delgado Heriberto Jose - - 2005
A novel artificial neural network (SYNTHESIS-ANN) is presented, which has been designed for computationally intensive problems and applied to the optimization of antennas and microwave devices. The antenna example presented is optimized with respect to voltage standing-wave ratio, bandwidth, and frequency of operation. A simple microstrip transmission line problem is ...
Yang Lei - - 2005
Although artificial neural networks (ANNs) have been shown to exhibit superior predictive power in the study of quantitative structure-activity relationships (QSARs), they have also been labeled a "black box" because they provide little explanatory insight into the relative influence of the independent variables in the predictive process so that little ...
Coppola Emery A EA - - 2005
Artificial neural networks (ANNs) were developed to accurately predict highly time-variable specific conductance values in an unconfined coastal aquifer. Conductance values in the fresh water lens aquifer change in response to vertical displacements of the brackish zone and fresh water-salt water interface, which are caused by variable pumping and climate ...
Jalali-Heravi Mehdi - - 2005
Recently, we have developed an artificial neural network model, which was able to predict accurately the electrophoretic mobilities of relatively small peptides. To examine the robustness of this methodology, a 3-3-1 back-propagation artificial neural network (BP-ANN) model was developed using the same inputs as the previous model, which were the ...
Silva Alvaro - - 2006
OBJECTIVE: This work presents a novel approach for the prediction of mortality in intensive care units (ICUs) based on the use of adverse events, which are defined from four bedside alarms, and artificial neural networks (ANNs). This approach is compared with two logistic regression (LR) models: the prognostic model used ...
Fernández Michael - - 2006
Artificial neural networks (ANNs) were used to model both inhibition of HIV-1 protease (K(i)) and inhibition of HIV replication (IC90) for 55 cyclic urea derivatives using constitutional and 2D descriptors. As a preliminary step, linear dependences were established by multiple linear regression (MLR) approaches, selecting the relevant descriptors by genetic ...
De─čim Zelihagül - - 2005
Artificial neural network (ANN) analysis was used to predict the permeability of selected compounds through Caco-2 cell monolayers. Previously reported models, which were shown to be useful in the prediction of permeability values, use many structural parameters. More complex equations have also been proposed using both linear and non-linear relationships, ...
Poirson Emilie - - 2005
This study focuses on a particular attribute of trumpet tones, the brightness, and on the physical characteristics of the instrument thought to govern its magnitude. On the one hand, an objective study was carried out with input impedance measurements, and, on the other hand, a subjective study with hearing tests ...
Misaki Masaya - - 2006
We used an artificial neural network (ANN) to detect correlations between event sequences and fMRI (functional magnetic resonance imaging) signals. The layered feed-forward neural network, given a series of events as inputs and the fMRI signal as a supervised signal, performed a non-linear regression analysis. This type of ANN is ...
Chiu Jainn-Shiun - - 2005
BACKGROUND: Estimating total body water (TBW) is crucial in determining dry weight and dialytic dose for hemodialysis patients. Several anthropometric equations have been used to predict TBW, but a more accurate method is needed. We developed an artificial neural network (ANN) to predict TBW in hemodialysis patients. METHODS: Demographic data, ...
Jouyban A - - 2005
An artificial neural network (ANN) methodology was used to model the electrophoretic mobility of basic analytes in binary solvent electrolyte systems. The electrophoretic mobilities in pure solvent electrolytes, and the volume fractions of the solvents in mixtures were used as input. The electrophoretic mobilities in mixed solvent buffers were employed ...
Brion Gail - - 2005
A database was probed with artificial neural network (ANN) and multivariate logistic regression (MLR) models to investigate the efficacy of predicting PCR-identified human adenovirus (ADV), Norwalk-like virus (NLV), and enterovirus (EV) presence or absence in shellfish harvested from diverse countries in Europe (Spain, Sweden, Greece, and the United Kingdom). The ...
Franco Vanina G - - 2006
An experiment was developed as a simple alternative to existing analytical methods for the simultaneous quantitation of glucose (substrate) and glucuronic acid (main product) in the bioprocesses Kombucha by using FTIR spectroscopy coupled to multivariate calibration (partial least-squares, PLS-1 and artificial neural networks, ANNs). Wavelength selection through a novel ranked ...
Fatemi Mohammad H - - 2005
Quantitative structure-properties relationship (QSPR) has been applied to modeling and predicting the electrophoretic mobilities of a series of benzoic acid derivatives in different carrier electrolyte composition. Descriptors that were selected by stepwise multiple linear regression (MLR) technique are radial distribution function-lag8 (RDF-8), unweighted R-maximal autocorrelation geometry, topology and atomic weight ...
Garc?a-Gimeno R M - - 2005
The combined effect of temperature (10.5 to 24.5 degrees C), pH level (5.5 to 7.5), sodium chloride level (0.25% to 6.25%) and sodium nitrite level (0 to 200 ppm) on the predicted specific growth rate (Gr), lag-time (Lag) and maximum population density (yEnd) of Leuconostoc mesenteroides under aerobic and anaerobic ...
Di Luca Monica - - 2005
BACKGROUND: Previous studies have shown that in platelets of mild Alzheimer Disease (AD) patients there are alterations of specific APP forms, paralleled by alteration in expression level of both ADAM 10 and BACE when compared to control subjects. Due to the poor linear relation among each key-element of beta-amyloid cascade ...
Gabutti L - - 2005
BACKGROUND: Symptomatic intradialytic hypotension (IDH) associated with increased mortality in hemodialysis patients is difficult to predict and hence prevent. Artificial Neural Networks (ANNs) are promising tools to solve multidimensional non-linear problems. The aim of the study was to verify in which way mathematical models, statistics or knowledge of patients influence ...
Sahoo Goloka B - - 2005
Riverbank filtration (RBF) is a low-cost water treatment technology in which surface water contaminants are removed or degraded as the infiltrating water moves from the river/lake to the pumping wells. The removal or degradation of contaminants is a combination of physicochemical and biological processes. This paper illustrates the development and ...
Plumb A Philip - - 2005
The purpose of this study was to determine whether artificial neural network (ANN) programs implementing different backpropagation algorithms and default settings are capable of generating equivalent highly predictive models. Three ANN packages were used: INForm, CAD/Chem and MATLAB. Twenty variants of gradient descent, conjugate gradient, quasi-Newton and Bayesian regularization algorithms ...
Cortina M - - 2005
An intelligent, automatic system based on an array of non-specific-response chemical sensors was developed. As a great amount of information is required for its correct modelling, we propose a system generating it itself. The sequential injection analysis (SIA) technique was chosen as it enables the processes of training, calibration, validation ...
Abujudeh Hani - - 2005
The objective of this study was to evaluate the operation of the portable X-ray machine in relation to examinations ordered by the Emergency Department at the University of Medicine and Dentistry of New Jersey, as well as to identify any bottlenecks hindering the performance of the aforementioned system. To do ...
Güler Nihal Fatma - - 2005
In this study the performance of support vector machine (SVM)and back-propagation neural network were applied to analyze the classification of the electromyogram (EMG) signals obtained from normal, neuropathy and myopathy subjects. By using autoregressive (AR) modeling, AR coefficients were obtained from EMG signals. Moreover, the support vector machine and artificial ...
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