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Gu Pei-Hong - - 2010
We find an intriguing relation between neutrino and charged fermion masses, |m(ν₃)² -m(ν₁)²|:(m(ν₂)²-m(ν₁)²)::V(tb)⁴m(τ)²m(b)²/m(t)²:V(cs)⁴m(μ)²m(s)²/m(c)². We further indicate this relation can be predicted by a left-right symmetric model.
Garkani-Nejad Zahra - - 2010
A new implemented QSPR method, whose descriptors achieved from bidimensional images, was applied for predicting (13)C NMR chemical shifts of 25 mono substituted naphthalenes. The resulted descriptors were subjected to principal component analysis (PCA) and the most significant principal components (PCs) were extracted. MIA-QSPR (multivariate image analysis applied to quantitative ...
Hui Edwin Pun - - 2011
We aimed to validate the Multinational Association for Supportive Care in Cancer (MASCC) risk index, and compare it with the Talcott model and artificial neural network (ANN) in predicting the outcome of febrile neutropenia in a Chinese population. We prospectively enrolled adult cancer patients who developed febrile neutropenia after chemotherapy ...
Rughani Anand I - - 2010
OBJECT: The authors describe the artificial neural network (ANN) as an innovative and powerful modeling tool that can be increasingly applied to develop predictive models in neurosurgery. They aimed to demonstrate the utility of an ANN in predicting survival following traumatic brain injury and compare its predictive ability with that ...
Khoshayand Mohammad Reza - - 2010
Three multivariate modelling approaches including partial least squares regression (PLS), genetic algorithm-partial least squares regression (GA-PLS), and principal components-artificial neural network (PC-ANN) analysis were investigated for their application to the simultaneous determination of chlordiazepoxide and clidinium levels in pharmaceuticals. A set of synthetic mixtures of drugs in ethanol and 0.1 ...
Fatemi Mohammad H - - 2010
Quantitative structure-activity relationship (QSAR) method was used to predict the pIC(50) value of 58 derivatives of 6-methoxy benzamides in this work. The artificial neural network (ANN) and multiple linear regressions (MLR) were used to construct the non-linear and linear QSAR models, respectively. The standard errors in the prediction of pIC(50) ...
Wu Jingheng - - 2010
Based on the quantitative structure-activity relationships (QSARs) models developed by artificial neural networks (ANNs), genetic algorithm (GA) was used in the variable-selection approach with molecule descriptors and helped to improve the back-propagation training algorithm as well. The cross validation techniques of leave-one-out investigated the validity of the generated ANN model ...
Caldeira A Teresa - - 2011
The combined effect of incubation time (IT) and aspartic acid concentration (AA) on the predicted biomass concentration (BC), Bacillus sporulation (BS) and anti-fungal activity of compounds (AFA) produced by Bacillus amyloliquefaciens CCMI 1051, was studied using Artificial Neural Networks (ANNs). The values predicted by ANN were in good agreement with ...
Guo Ying - - 2010
Plackett-Burman and central composite designs were applied to optimize the medium for ethanol production by Clostridium autoethanogenum with CO as sole carbon source, and a medium containing (g/L): NaCl 1.0, KH(2)PO(4) 0.1, CaCl(2) 0.02, yeast extract 0.15, MgSO(4) 0.116, NH(4)Cl 1.694 and pH 4.74 was found optimal. The optimum ethanol ...
Perai A H - - 2010
There has been a considerable and continuous interest to develop equations for rapid and accurate prediction of the ME of meat and bone meal. In this study, an artificial neural network (ANN), a partial least squares (PLS), and a multiple linear regression (MLR) statistical method were used to predict the ...
Gauci Jason - - 2010
Looking to nature as inspiration, for at least the past 25 years, researchers in the field of neuroevolution (NE) have developed evolutionary algorithms designed specifically to evolve artificial neural networks (ANNs). Yet the ANNs evolved through NE algorithms lack the distinctive characteristics of biological brains, perhaps explaining why NE is ...
Lewis H M - - 2010
Determining processes constraining adaptation is a major challenge facing evolutionary biology, and sex allocation has proved a useful model system for exploring different constraints. We investigate the evolution of suboptimal sex allocation in a solitary parasitoid wasp system by modelling information acquisition and processing using artificial neural networks (ANNs) evolving ...
Gago Jorge - - 2010
This study employs artificial neural networks (ANNs) to create a model to identify relationships between variables affecting the in vitro rhizogenesis and acclimatization of two cultivars of Vitis vinifera L. Albariño and Mencía. The effects of three factors (inputs), the type of cultivar, concentration and exposure time to indolebutyric acid ...
Mimendia A - - 2010
A Sequential Injection Analysis (SIA) system and an 8-potentiometric all-solid-state sensor array were coupled in a simple and automated electronic tongue device. The potentiometric sensors used were planar microfabricated structures with standard PVC membranes deposited onto a gold contact. The SIA system permitted the automated operation and generation of the ...
Louis Bruno - - 2010
The machine learning methods artificial neural network (ANN) and support vector machine (SVM) techniques were used to model intrinsic solubility of 74 generic drugs. The models obtained were compared with those obtained using multiple linear regression (MLR) analysis. Cluster analysis was used to split the data into a training set ...
Dalmau Jordi - - 2010
In this study, a wrapper approach was applied to objectively select the most important variables related to two different anaerobic digestion imbalances, acidogenic states and foaming. This feature selection method, implemented in artificial neural networks (ANN), was performed using input and output data from a fully instrumented pilot plant (1 ...
Gago Jorge - - 2010
Commonly, simple mathematical models can not be used to describe exactly the biological processes due to their higher complexity. In fact, most biological interactions cannot be elucidated by a simple stepwise algorithm or a precise formula, particularly when the data are complex or noisy. ANNs allows an accurate description of ...
Goodarzi Mohammad - - 2010
Four molecular descriptors were selected from a pool of variables using genetic algorithm, and then used to built a QSAR model for a series of 1-(azacyclyl)-3-arylsulfonyl-1H-pyrrolo[2,3-b]pyridines as 5-HT(6) receptor agonists or antagonists, useful for the treatment of central nervous system disorders. Simple multiple linear regression (MLR) and a nonlinear method, ...
LeBouf Ryan F - - 2010
Identification of mold growth based on microbial volatile organic compounds (MVOCs) may be a viable alternative to current bioaerosol assessment methodologies. A feed-forward back propagation (FFBP) artificial neural network (ANN) was developed to correlate MVOCs with bioaerosol levels in built environments. A cross-validation MATLAB script was developed to train the ...
Huang Shuqiong - - 2010
Hypertension (HTN) has been proven to be associated with an increased risk of cardiovascular diseases. The purpose of the study was to examine risk factors for HTN and to develop a prediction model to estimate HTN risk for rural residents over the age of 35 years. This study was based ...
Lin Chen-Chiang - - 2010
Older patients with hip fracture have a mortality rate one year after surgery of 20-30%. The purpose of this study is to establish a predictive model to assess the outcome of surgical treatment in older patients with hip fracture. A database of information from 286 consecutive cases of surgery for ...
Lawrentschuk Nathan - - 2011
Complex statistical models utilizing multiple inputs to derive a risk assessment may benefit prostate cancer (PC) detection where focus has been on prostate-specific antigen (PSA). This study develops a polychotomous logistic regression (PR) model and an artificial neural network (ANN) for predicting biopsy results, particularly for clinically significant PC. There ...
Jiao Long - - 2010
Two quantitative structure property relationship (QSPR) models for predicting soot-water partition coefficients (K(sc)) of 25 persistent organic pollutants (POPs) were developed. One model was established with linear artificial neural network (L-ANN), the other model was developed by using back propagation artificial neural network (BP-ANN). Leave one out cross validation was ...
Balfagón A C - - 2010
Synopsis In this work, a comparative study between two methods to acquire relevant information about a cosmetic formulation has been carried out. A Design of Experiments (DOE) has been applied in two stages to a capillary cosmetic cream: first, a Plackett-Burman (PB) design has been used to reduce the number ...
Güçlü Dünyamin - - 2010
Artificial Neural Networks (ANNs), a method of artificial intelligence method, provide effective predictive models for complex processes. Three independent ANN models trained with back-propagation algorithm were developed to predict effluent chemical oxygen demand (COD), suspended solids (SS) and aeration tank mixed liquor suspended solids (MLSS) concentrations of the Ankara central ...
Pai Tzu-Yi - - 2011
A grey model (GM) and an artificial neural network (ANN) were employed to predict co-melting temperature of municipal solid waste incinerator (MSWI) fly ash and sewage sludge ash (SSA) during formation of modified slag. The results indicated that in the aspect of model prediction, the mean absolute percentage error (MAPEs) ...
Li X - - 2010
In remotely located boreal forest watersheds, monitoring nitrogen (N) export in stream discharge often is not feasible because of high costs and site inaccessibility. Therefore, modelling tools that can predict N export in unmonitored watersheds are urgently needed to support management decisions for these watersheds. The hydrological and biogeochemical processes ...
Sezer Esma - - 2012
In this study, it has been intended to analyze Electroencephalography (EEG) signals by Wavelet Transform (WT) for diagnosis of epilepsy, to employ various Artificial Neural Networks (ANNs) for the signals' automatic classification. Furthermore, carrying out a performance comparison has been aimed. Three EEG signals have been decomposed into frequency sub ...
Pozzi Luca - - 2010
The identification of the vocal repertoire of a species represents a crucial prerequisite for a correct interpretation of animal behavior. Artificial Neural Networks (ANNs) have been widely used in behavioral sciences, and today are considered a valuable classification tool for reducing the level of subjectivity and allowing replicable results across ...
O'Reilly Brian F - - 2010
To produce a reliable objective method of assessing the House-Brackmann (H-B) and regional grades of facial palsy with the results produced and presented in a time and manner suitable for a routine clinical setting. Analysis of video pixel data using artificial neural networks (ANNs). Tertiary-referral neuro-otologic center. Subjects with varying ...
Cucchetti Alessandro - - 2010
Hepatocellular carcinoma (HCC) prognosis strongly depends upon nuclear grade and the presence of microscopic vascular invasion (MVI). The aim of this study was to develop an artificial neural network (ANN) that is able to predict tumour grade and MVI on the basis of non-invasive variables. Clinical, radiological, and histological data ...
Delnavaz M - - 2010
In this study, the results of 1-year efficiency forecasting using artificial neural networks (ANN) models of a moving bed biofilm reactor (MBBR) for a toxic and hard biodegradable aniline removal were investigated. The reactor was operated in an aerobic batch and continuous condition with 50% by volume which was filled ...
Lu Hongfei - - 2010
Artificial neural networks (ANNs) with back-propagation algorithm were developed to predict the percentage loss of ascorbic acid, total phenols, flavonoid, and antioxidant activity in different segments of asparagus during water blanching at temperatures ranging from 65 to 95 degrees C as a function of blanching time and temperature. In this ...
Costas-Rodr?guez M - - 2010
Inductively coupled plasma-mass spectrometry (ICP-MS) in combination with different supervised chemometric approaches has been used to classify cultivated mussels in Galicia (Northwest of Spain) under the European Protected Designation of Origin (PDO). 158 mussel samples, collected in the five r?as on the basis of the production, along with minor and ...
Caocci Giovanni - - 2010
OBJECTIVE: There is growing interest in the development of prognostic models for predicting the occurrence of acute graft-vs-host disease (aGVHD) after unrelated donor hematopoietic stem cell transplantation. A high number of variables have been shown to play a role in aGVHD, but the search for a predictive algorithm is still ...
Xie Xiaoqiu - - 2010
ABSTRACT Objective: To construct a decision-making expert system (ES) for the orthodontic treatment of patients between 11 and 15 years old to determine whether extraction is needed by using artificial neural networks (ANN). Specifically, we will uncover the factors that affect this decision-making process. Methods: A total of 200 subjects ...
Elmolla Emad S - - 2010
The study examined the implementation of artificial neural network (ANN) for the prediction and simulation of antibiotic degradation in aqueous solution by the Fenton process. A three-layer backpropagation neural network was optimized to predict and simulate the degradation of amoxicillin, ampicillin and cloxacillin in aqueous solution in terms of COD ...
Harvey Rebecca A RA Chemical Engineering, Northeastern University, Boston, Massachusetts, - - 2010
The various components of the artificial pancreas puzzle are being put into place. Features such as communication, control, modeling, and learning are being realized presently. Steps have been set in motion to carry the conceptual design through simulation to clinical implementation. The challenging pieces still to be addressed include stress ...
Işik Hakan - - 2012
In this study, it has been intended to perform an automatic classification of Electroencephalography (EEG) signals via Artificial Neural Networks (ANN) and to investigate these signals using Wavelet Transform (WT) for diagnosing epilepsy syndrome. EEG signals have been decomposed into frequency sub-bands using WT and a set of feature vectors ...
Sov?ny T - - 2010
The subdivision of scored tablets is an important problem for the exact individual therapy of patients. The recent guidelines of the EU require verification of the equal mass of the tablet halves, but this problem has previously never been investigated in papers published on the production technological aspects. Our aim ...
Shahlaei Mohsen - - 2010
Principal component regression (PCR), principal component-artificial neural network (PC-ANN), and principal component-least squares-support vector machine (PC-LS-SVM) as regression methods were investigated for building quantitative structure-activity relationships for the prediction of inhibitory activity of some CCR1 antagonists. Nonlinear methods (PC-ANN and PC-LS-SVM) were better than the PCR method considerably in the ...
Smith Larry H - - 2010
We explore the feasibility of automatically identifying sentences in different MEDLINE abstracts that are related in meaning. We compared traditional vector space models with machine learning methods for detecting relatedness, and found that machine learning was superior. The Huber method, a variant of Support Vector Machines which minimizes the modified ...
Cartas Raul - - 2010
Simultaneous quantification of Cd(2+) and Pb(2+) in solution has been correctly targeted using the kinetic information from a single non-specific potentiometric sensor. Dual quantification was accomplished from the complex information in the transient response of an electrode used in a Sequential Injection Analysis (SIA) system and recorded after step injection ...
Zhang Yu - - 2010
Cellulase was covalently immobilized on a smart polymer, Eudragit L-100 by carbodiimide coupling. Using data of central composite design, response surface methodology (RSM) and artificial neural network (ANN) were developed to investigate the effect of pH, carbodiimide concentration, and coupling time on the activity yield of immobilized cellulase. Results showed ...
Bizios Dimitrios - - 2010
PURPOSE: To compare the performance of two machine learning classifiers (MLCs), artificial neural networks (ANNs) and support vector machines (SVMs), with input based on retinal nerve fibre layer thickness (RNFLT) measurements by optical coherence tomography (OCT), on the diagnosis of glaucoma, and to assess the effects of different input parameters. ...
Işik Hakan - - 2011
In this study, a classification to be used in physiotherapy was realized by means of Artificial Neural Network (ANN). The aim of the classification was to determine the treatment length and appropriate ultrasound value for the age of physiotherapy patients, the area on which ultrasound will be applied, the fat ...
Woolfson A David - - 2010
Dapivirine mucoadhesive gels and freeze-dried tablets were prepared using a 3x3x2 factorial design. An artificial neural network (ANN) with multi-layer perception was used to investigate the effect of hydroxypropyl-methylcellulose (HPMC): polyvinylpyrrolidone (PVP) ratio (X1), mucoadhesive concentration (X2) and delivery system (gel or freeze-dried mucoadhesive tablet, X3) on response variables; cumulative ...
Lee Eunjeong - - 2010
This study described the development and validation of an artificial neural network (ANN) for the purpose of analyzing the effects of climate change on nonpoint source (NPS) pollutant loads from agricultural small watershed. The runoff discharge was estimated using ANN algorithm. The performance of ANN modelwas examined using observed data ...
Kim Minyoung - - 2010
In the present study, a physically-based hydraulic modeling tool and a data-driven approach using artificial neural networks (ANNs) were evaluated for their ability to simulate the fate and transport of microorganisms in a water system. To produce reliable data, a pipe network was constructed and a series of experiments using ...
Moustris Kostas P - - 2010
The present study deals with the development and application of Artificial Neural Network (ANN) models as a tool for the evaluation of human thermal comfort conditions in the urban environment. ANNs are applied to forecast for three consecutive days during the hot period of the year (May-September) the human thermal ...
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