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Prediction

Distribution by Scientific Domains
Life Sciences22%
Chemistry16%
Medical Sciences16%
Engineering9%
Earth and Environmental Science7%
Business, Economics, Finance and Accounting6%
Psychology4%
Polymers and Materials Science4%
Humanities and Social Sciences3%
Physics and Astronomy3%
Mathematics and Statistics2%
3 Other Domains8%
Distribution within Life Sciences
Ecology & Organismal Biology22%
Evolution9%
47 Other Subdomains69%

Kinds of Prediction

  • ab initio prediction
  • abundance prediction
  • accurate prediction
  • activity prediction
  • analytical prediction
  • ante prediction
  • bankruptcy prediction
  • basic prediction
  • behavioral prediction
  • best linear unbiased prediction
  • best prediction
  • cardiovascular risk prediction
  • cfd prediction
  • clear prediction
  • climate prediction
  • clinical prediction
  • comparative static prediction
  • comparing model prediction
  • comparing prediction
  • computational prediction
  • concentration prediction
  • correct prediction
  • crystal structure prediction
  • current prediction
  • different prediction
  • differential prediction
  • early prediction
  • economic prediction
    		•
  • empirical prediction
  • energy prediction
  • ensemble prediction
  • environmental prediction
  • equilibrium prediction
  • erosion prediction
  • ex ante prediction
  • false-positive prediction
  • fatigue life prediction
  • first prediction
  • flow prediction
  • future prediction
  • general prediction
  • good prediction
  • important prediction
  • improved prediction
  • initial prediction
  • initio prediction
  • key prediction
  • life prediction
  • lifetime prediction
  • linear unbiased prediction
  • long-term prediction
  • main prediction
  • make prediction
  • model prediction
  • mortality prediction
  • motion prediction
    		•
  • new prediction
  • novel prediction
  • numerical prediction
  • numerical weather prediction
  • out-of-sample prediction
  • outcome prediction
  • performance prediction
  • pharmacokinetic prediction
  • poor prediction
  • precise prediction
  • preoperative prediction
  • pressure prediction
  • previous prediction
  • priori prediction
  • probabilistic prediction
  • protein structure prediction
  • qualitative prediction
  • quality prediction
  • quantitative prediction
  • realistic prediction
  • reasonable prediction
  • reliability prediction
  • reliable prediction
  • response prediction
  • risk prediction
  • robust prediction
  • satisfactory prediction
  • seasonal prediction
    		•
  • second prediction
  • secondary structure prediction
  • several prediction
  • silico prediction
  • simple prediction
  • simulation prediction
  • site prediction
  • spatial prediction
  • specific prediction
  • static prediction
  • structural prediction
  • structure prediction
  • successful prediction
  • support prediction
  • support theoretical prediction
  • temperature prediction
  • test prediction
  • testable prediction
  • testing prediction
  • theoretical prediction
  • theory prediction
  • time prediction
  • unbiased prediction
  • useful prediction
  • weather prediction
  • yield prediction

    • Terms modified by Prediction

  • prediction ability
  • prediction accuracy
  • prediction algorithm
  • prediction analysis
  • prediction capability
  • prediction center
  • prediction equation
  • prediction error
    		•
  • prediction horizon
  • prediction interval
  • prediction method
  • prediction methods
  • prediction model
  • prediction models
  • prediction problem
  • prediction program
    		•
  • prediction project
  • prediction quality
  • prediction result
  • prediction rule
  • prediction score
  • prediction set
  • prediction strategy
  • prediction system
    		•
  • prediction techniques
  • prediction tool
  • prediction uncertainty
  • prediction variance

    • Selected Abstracts

    FAST AND ROBUST INCREMENTAL ACTION PREDICTION FOR INTERACTIVE AGENTS

    COMPUTATIONAL INTELLIGENCE, Issue 1 2005
    Jonathan Dinerstein
    The ability for a given agent to adapt on-line to better interact with another agent is a difficult and important problem. This problem becomes even more difficult when the agent to interact with is a human, because humans learn quickly and behave nondeterministically. In this paper, we present a novel method whereby an agent can incrementally learn to predict the actions of another agent (even a human), and thereby can learn to better interact with that agent. We take a case-based approach, where the behavior of the other agent is learned in the form of state,action pairs. We generalize these cases either through continuous k -nearest neighbor, or a modified bounded minimax search. Through our case studies, our technique is empirically shown to require little storage, learn very quickly, and be fast and robust in practice. It can accurately predict actions several steps into the future. Our case studies include interactive virtual environments involving mixtures of synthetic agents and humans, with cooperative and/or competitive relationships. [source]

    EXPERIMENTAL AND NEURAL NETWORK PREDICTION OF THE PERFORMANCE OF A SOLAR TUNNEL DRIER FOR DRYING JACKFRUIT BULBS AND LEATHER

    JOURNAL OF FOOD PROCESS ENGINEERING, Issue 6 2005
    B.K. BALA
    ABSTRACT This article presents the field performance of a solar tunnel drier for drying jackfruit bulbs and leather. The drier consists of a transparent plastic-covered flat-plate collector and a drying tunnel connected in series to supply hot air directly into the drying tunnel using two direct-current fans operated by a photovoltaic module. The drier has a loading capacity of 120,150 kg of fruits. Sixteen experimental runs were conducted for drying jackfruit bulbs and leather (eight runs each). The use of a solar tunnel drier led to a considerable reduction in drying time and dried products of better quality in comparison to products dried under the sun. A multilayered neural network approach was used to predict the performance of the solar tunnel drier. Using solar drying data of jackfruit bulbs and leather, the model has been trained using backpropagation algorithm. The prediction of the performance of the drier was found to be excellent after it was adequately trained. It can be used to predict the potential of the drier for different locations, and can also be used in a predictive optimal control algorithm. [source]

    PREDICTION OF SPRAY-DRIED PRODUCT QUALITY USING TWO SIMPLE DRYING KINETICS MODELS

    JOURNAL OF FOOD PROCESS ENGINEERING, Issue 6 2005
    KAMLESH C. PATEL
    ABSTRACT Increasing attention has been given to spray drying because of its popularity in the manufacturing of various powders with prerequisite quality. A large number of theoretical and experimental studies have been published during the last five decades to study spray-drying operations. Despite this progress, there is still lack of information on the selection of an accurate and simple drying kinetics model to characterize the droplet drying process. This article has particularly focused on the comparison of two simple and effective drying kinetics models: the characteristic drying-rate curve and reaction-engineering approach (REA) models. This article reported mathematical models that can be used to design the spray-drying operation and to predict the particle's characteristics for realistic dryer-wide situations. Both the physical and biochemical quality attributes were investigated regarding their sensitivity to the model parameters used in the two drying kinetics models. The REA model was found to deliver more realistic predictions during the modeling of the droplet drying process for all the sets of conditions tested. [source]

    GLUTEN QUALITY PREDICTION AND CORRELATION STUDIES IN SPRING WHEATS

    JOURNAL OF FOOD QUALITY, Issue 4 2007
    IMRAN PASHA
    ABSTRACT Gluten, "cohesive, viscoelastic, proteinaceous material prepared as a by-product of the starch isolation from wheat flour" and the storage and dough-forming protein of wheat flour, is the key to the unique ability of wheat to suit the production of leavened products. Wet gluten was only affected by wheat varieties, while dry gluten was affected by wheat varieties, crop years and their interaction. The wet and dry gluten ranged 8.0,43.13% and 2.58,14.55%, respectively, and were positively correlated with Zeleny value, sodium dodecyl sulfate sedimentation value and falling number. The gluten content was higher in Pavon, SA 42 and Faisalabad 85, while Zeleny value was higher in GA 02 and C 518, resulting in better gluten quality. Zeleny value was negatively correlated with crude protein content (r = ,0.1857*). The lowest amount of wet and dry gluten was detected in Triticale and durum wheats as compared to common wheats. Zeleny value and sedimentation value may be used as indicators of gluten content and quality while working on wheats. The information thus collected will be valuable for cereal chemists and wheat breeders for improvements in their future breeding programs. PRACTICAL APPLICATIONS This research work will be a breakthrough and helpful for wheat breeders, growers, millers and bakers for their intended uses as every consumer demand specific wheat quality characteristics for their end products. [source]

    PREDICTION OF APPLE FIRMNESS FROM MASS LOSS AND SHRINKAGE

    JOURNAL OF FOOD QUALITY, Issue 1 2004
    S.O. LINK
    ABSTRACT Prediction of firmness from mass loss and shrinkage was investigated in apples (Malus x domestica Borkh.) under regular atmosphere (RA) storage conditions. Apples (,Delicious' and ,Fuji') were repeatedly weighed to determine mass loss. Shrinkage was measured with a strain gauge sensor. ,Delicious' apples lost firmness (73 to 58 N) while ,Fuji' apples maintained firmness at 69 N over 57 days in storage. Apples lost mass at a constant rate with ,Delicious' losing mass slower (0.6 % per month) than ,Fuji' (1.1% per month). ,Delicious' apple shrank less (0.28 mm) than the ,Fuji' (0.70 mm) over 57 days. The relationship between firmness and mass loss, or shrinkage was dependent on apple cultivar. Firmness was significantly and linearly related to mass loss and to shrinkage in ,Delicious' apples. It is possible to predict firmness of ,Delicious' apples under RA storage conditions by tracking mass loss or shrinkage. [source]

    PREDICTION OF TEXTURE IN GREEN ASPARAGUS BY NEAR INFRARED SPECTROSCOPY (NIRS)

    JOURNAL OF FOOD QUALITY, Issue 4 2002
    D. PEREZ
    NIR spectroscopy was used to estimate three textural parameters of green asparagus: maximum cutting force, energy and toughness. An Instron 1140 Texturometer provided reference data. A total of 199 samples from two asparagus varieties (Taxara and UC-157) were used to obtain the calibration models between the reference data and the NIR spectral data. Standard errors of cross validation (SECV) and r2 were (5.73, 0.84) for maximum cutting force, (0.58, 0.66) for toughness, and (0.04, 0.85) for cutting energy. The mathematical models developed as calibration models were tested using independent validation samples (n =20); the resulting standard errors of prediction (SEP) and r2 for the same parameters were (6.73, 0.82), (0.61, 0.57) and (0.04, 0.89), respectively. For toughness, substantially improved r2 (0.85) and SEP (0.36) when four samples exhibiting large residual values were removed. The results indicated that NIRS could accurately predict texture parameters of green asparagus. [source]

    MODEL PREDICTION FOR SENSORY ATTRIBUTES OF NONGLUTEN PASTA

    JOURNAL OF FOOD QUALITY, Issue 6 2001
    JEN-CHIEH HUANG
    ABSTRACT Response surface methodology was used to predict sensory attributes of a nongluten pasta and develop response surface plots to help visualize the optimum region. Optimum regions of xanthan gum, modified starch, and locust bean gum were selected by overlapping the contour plots of sensory properties of nongluten pasta as compared with the control pasta. The formula of nongluten pasta that possessed the most desirable properties was xanthan gum at 40 g, modified starch at 35 g, locust bean gum at 40 g, tapioca starch at 113 g, potato starch at 57 g, corn flour at 250 g, and rice flour at 50 g. The quality of nongluten pasta could be improved by using different levels of nongluten starches and flours, and nonstarch polysaccharides. [source]

    EFFICACY OF SERUM PEPSINOGENS IN THE PREDICTION OF ENDOSCOPIC FEATURES OF GASTRITIS

    JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY, Issue 12 2000
    Yoshihisa Urita
    Objective The efficacy of serum pepsinogen (PG) test is widely accepted as a screening test to select persons for endoscopy in the diagnosis of gastric cancer. In this study, we would like to examine whether serum PG levels give us information on endoscopic findings of gastric mucosa. Materials and methods The serum level of PG++ and PG+, and the PG+/PG, ratio were compared with endoscopic 13C-urea breath. H.pylori status was defined as an increase in the intragastric 13CO2/12CO2 ratio of 10% over baseline. Intestinal metaplasia was made visible as the purple-stained area using a 0.05% crystal violet spraying method. PG level of less than 70,g/L and I PG+/PG, ratio of less than 3 was adopted for a (+) result, and PG level of less than 30,g/L and a PG+/PG, ratio of less than 2 for a (++) result. Results Prevalence of endoscopic features and H. pylori infection in different groups classified by serum PG tests. Conclusions Lintestinal metaplasia was identified in more than 80% of PG positive patients. The prevalence of linear reddness and raised erosion in the antrum were higher in PG (-) group than in PG(+) and (++) groups. H. pylori-positive rate was the highest in PG (+) group. [source]

    NEURAL NETWORK PREDICTION OF PERMEABILITY IN THE EL GARIA FORMATION, ASHTART OILFIELD, OFFSHORE TUNISIA

    JOURNAL OF PETROLEUM GEOLOGY, Issue 4 2001
    J.H. Ligtenberg
    The Lower Eocene El Garia Formation forms the reservoir rock at the Ashtart oilfield, offshore Tunisia. It comprises a thick package of mainly nummulitic packstones and grainstones with variable reservoir quality. Although porosity is moderate to high, permeability is often poor to fair with some high permeability streaks. The aim of this study was to establish relationships between log-derived data and core data, and to apply these relationships in a predictive sense to uncored intervals. An initial objective was to predict from measured logs and core data the limestone depositional texture (as indicated by the Dunham classification), as well as porosity and permeability. A total of nine wells with complete logging suites, multiple cored intervals with core plug measurements together with detailed core interpretations were available. We used a fully-connected Multi-Layer-Perceptron network (a type of neural network) to establish possible non-linear relationships. Detailed analyses revealed that no relationship exists between log response and limestone texture (Dunham class). The initial idea to predict Dunham class, and subsequently to use the classification results to predict permeability, could not therefore be pursued. However, further analyses revealed that it was feasible to predict permeability without using the depositional fabric, but using a combination of wireline logs and measured core porosity. Careful preparation of the training set for the neural network proved to be very important. Early experiments showed that low to fair permeability (1,35 mD) could be predicted with confidence, but that the network failed to predict the high permeability streaks. "Balancing " the data set solved this problem. Balancing is a technique in which the training set is increased by adding more examples to the under-sampled part of the data space. Examples are created by random selection from the training set and white noise is added. After balancing, the neural network's performance improved significantly. Testing the neural network on two wells indicated that this method is capable of predicting the entire range of permeability with confidence. [source]

    PREDICTION OF MECHANICAL PROPERTIES OF CUMIN SEED USING ARTIFICIAL NEURAL NETWORKS

    JOURNAL OF TEXTURE STUDIES, Issue 1 2010
    M.H. SAIEDIRAD
    ABSTRACT In this paper, two artificial neural networks (ANNs) are applied to acquire the relationship between the mechanical properties and moisture content of cumin seed, using the data of quasi-static loading test. In establishing these relationship, the moisture content, seed size, loading rate and seed orientation were taken as the inputs of both models. The force and energy required for fracturing of cumin seed, under quasi-static loading were taken as the outputs of two models. The activation function in the output layer of models obeyed a linear output, whereas the activation function in the hidden layers were in the form of a sigmoid function. Adjusting ANN parameters such as learning rate and number of neurons and hidden layers affected the accuracy of force and energy prediction. Comparison of the predicted and experimented data showed that the ANN models used to predict the relationships of mechanical properties of cumin seed have a good learning precision and good generalization, because the root mean square errors of the predicated data by ANNs were rather low (4.6 and 7.7% for the force and energy, respectively). PRACTICAL APPLICATIONS Cumin seed is generally used as a food additive in the form of powder for imparting flavor to different food preparations and for a variety of medicinal properties. Physical properties of cumin seeds are essential for the design of equipment for handling, harvesting, aeration, drying, storing, grinding and processing. For powder preparation especially the fracture behavior of the seeds are essential. These properties are affected by numerous factors such as size, form and moisture content of the grain and deformation speed. A neural network model was developed that can be used to predict the relationships of mechanical properties. Artificial neural network models are powerful empirical models approach, which can be compared with mathematical models. [source]

    INFLUENCE OF UNIAXIAL COMPRESSION RATE ON RHEOLOGICAL PARAMETERS AND SENSORY TEXTURE PREDICTION OF COOKED POTATOES

    JOURNAL OF TEXTURE STUDIES, Issue 1 2000
    ANETTE KISTRUP THYBO
    ABSTRACT The effect of uniaxial compression rate (20,1000 mm/min) on the parameters: Stress (,ftrue), strain (,fHencky) and work to fracture (Wf), modulus of deformability (Ed), maximum slope before fracture (Emax) and work during 75% compression (Wtotal) was investigated for ten potato varieties. Multivariate data analysis was used to study the correlation between and within the sensory and nonsensory measurements by Principal Component Analysis (PCA) which showed ,ftrue, Emax, Wf, and Wtotal to explain the same type of information in the data, and ,fHencky versus Ed another type of information in the data. The deformation rate had a large effect on ,fHencky. Nine sensory texture attributes covering the mechanical, geometrical and moistness attributes were evaluated. Relationships between uniaxial compression data at various deformation rates and the sensory texture attributes were studied by Partial Least Squares Regression (PLSR). A minor effect of deformation rate on the correlation with the sensory texture properties was obtained. Mechanical properties were predicted to a higher extent than the geometrical attributes and moistness. The prediction of the mechanical, geometrical and moistness attributes increased largely by using uniaxial compression supplemented by chemical measures such as dry matter and pectin methylesterase, but here no relevant effect of deformation rate was obtained. [source]

    PREDICTION OF LOCAL SCOUR AROUND BRIDGE PIERS USING ARTIFICIAL NEURAL NETWORKS,

    JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 2 2006
    Sung-Uk Choi
    ABSTRACT: This paper describes a method for predicting local scour around bridge piers using an artificial neural network (ANN). Methods for selecting input variables, calibrations of network control parameters, learning process, and verifications are also discussed. The ANN model trained by laboratory data is applied to both laboratory and field measurements. The results illustrate that the ANN model can be used to predict local scour in the laboratories and in the field better than other empirical relationships that are currently in use. A parameter study is also carried out to investigate the importance of each input variable as reflected in data. [source]

    WEPP INTERNET INTERFACES FOR FOREST EROSION PREDICTION,

    JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 2 2004
    William J. Elliot
    ABSTRACT: The Water Erosion Prediction Project (WEPP) is a physically based erosion model for applications to dryland and irrigated agriculture, rangeland, and forests. U.S. Forest Service (USFS) experience showed that WEPP was not being adapted because of the difficulty in building files describing the input conditions in the existing interfaces. To address this difficulty, a suite of Internet interfaces with a database was developed to more easily predict soil erosion for a wide range of climatic and forest conditions, including roads, fires, and timber harvest. The database included a much larger climate database than was previously available for applications in remote forest and rangeland areas. Validation results showed reasonable agreement between erosion values reported in the literature and values predicted by the interfaces to the WEPP model. [source]

    PREDICTION OF STREAM TEMPERATURE IN FORESTED WATERSHEDS,

    JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 1 2004
    V. Sridhar
    ABSTRACT: Removal of streamside vegetation changes the energy balance of a stream, and hence its temperature. A common approach to mitigating the effects of logging on stream temperature is to require establishment of buffer zones along stream corridors. A simple energy balance model is described for prediction of stream temperature in forested headwater watersheds that allows evaluation of the performance of such measures. The model is designed for application to "worst case" or maximum annual stream temperature, under low flow conditions with maximum annual solar radiation and air temperature. Low flows are estimated via a regional regression equation with independent variables readily accessible from GIS databases. Testing of the energy balance model was performed using field data for mostly forested basins on both the west and east slopes of the Cascade Mountains, and was then evaluated using the regional equations for low flow and observed maximum reach temperatures in three different east slope Cascades catchments. A series of sensitivity analyses showed that increasing the buffer width beyond 30 meters did not significantly decrease stream temperatures, and that other vegetation parameters such as leaf area index, average tree height, and to a lesser extent streamside vegetation buffer width, more strongly affected maximum stream temperatures. [source]

    II. INTERACTIONS AMONG MARITAL CONFLICT, SYMPATHETIC, AND PARASYMPATHETIC NERVOUS SYSTEMS ACTIVITY IN THE PREDICTION OF CHILDREN'S EXTERNALIZING PROBLEMS

    MONOGRAPHS OF THE SOCIETY FOR RESEARCH IN CHILD DEVELOPMENT, Issue 1 2009
    Article first published online: 18 MAR 200
    First page of article [source]

    BREAST SPECIMEN ULTRASOUND AND MAMMOGRAPHY IN THE PREDICTION OF TUMOUR-FREE MARGINS

    ANZ JOURNAL OF SURGERY, Issue 12 2006
    Kok-Yang Tan
    Background: Adequacy of margins is important for local recurrence control in breast-conserving surgery for breast cancer. This study aims to compare the accuracy of intraoperative specimen ultrasonography (IOUS) and specimen mammography in the prediction of achieving adequate histologically tumour-free margins during breast-conserving surgery. Methods: Between March 2003 and September 2004, a prospective study was carried out on 25 patients who underwent breast-conserving surgery. After wide excision, IOUS and specimen mammography were used to assess adequacy of margins. Further surgery was undertaken when either method showed an inadequate margin. The margins were assessed histologically and correlated with IOUS and mammographic findings. Results: Using IOUS alone, higher rates of histologically tumour-free margins were achieved compared with mammography alone. Combined IOUS and mammography achieved similar or slightly higher rates of histologically tumour-free margins compared with IOUS alone. If the margin measured on IOUS is twice the desired histological margin, this will result in achieving a histologically tumour-free rate of >90%. Associated ductal carcinoma in situ was the only significant factor found to decrease the rate of achieving adequate margins. Conclusion: Intraoperative specimen ultrasonography is useful in predicting histologically tumour-free margins during breast conserving surgery for cancer. [source]

    ESTIMATION, PREDICTION AND INFERENCE FOR THE LASSO RANDOM EFFECTS MODEL

    AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 1 2009
    Scott D. Foster
    Summary The least absolute shrinkage and selection operator (LASSO) can be formulated as a random effects model with an associated variance parameter that can be estimated with other components of variance. In this paper, estimation of the variance parameters is performed by means of an approximation to the marginal likelihood of the observed outcomes. The approximation is based on an alternative but equivalent formulation of the LASSO random effects model. Predictions can be made using point summaries of the predictive distribution of the random effects given the data with the parameters set to their estimated values. The standard LASSO method uses the mode of this distribution as the predictor. It is not the only choice, and a number of other possibilities are defined and empirically assessed in this article. The predictive mode is competitive with the predictive mean (best predictor), but no single predictor performs best across in all situations. Inference for the LASSO random effects is performed using predictive probability statements, which are more appropriate under the random effects formulation than tests of hypothesis. [source]

    Prediction of hyperbilirubinaemia in the healthy term newborn

    ACTA PAEDIATRICA, Issue 2 2001
    X Carbonell
    The aim is to establish the correlation between transcutaneous bilirubin (TCB) and serum bilirubin (TSB) and its predictive value for significant hyperbilirubinaemia ,290 mcmol/L (17mg/dL). We studied a total of 2004 healthy full-term newborns, weight 3.230g ± 491g; 90% received breast milk. The study was performed in two phases. In the first phase (610 newborns), the following tests were carried out: hematocrit and bilirubin in umbilical cord blood; TCB at 24 h, 48 h and between 60 h and 96 h at the forehead and over the sternum; TSB was measured along with this last test. In the second phase (1394 newborns), the predictive value of TCB and TSB was validated. The incidence of bilirubin >290 mcmol/L was 2.95% and 3.2%. The correlation between TSB and TCB is high (n= 996; r = 0.92; y = 5.916 + 0.804x; p < 0.000). There was a better correlation between TCB and TSB with sternal compared to forehead determination (< 24 h: 0.81 vs 0.77; 24,48 h: 0.887 vs 0.83; and >48 h: 0.94 vs 0.83). The study showed the scant sensitivity of umbilical cord blood bilirubin and good predictive value at 24 h of TSB > 102 mcmol/L (6mg/dL) and at 48 h of TSB > 154 mcmol/L (9mg/dL) and TCB > 13 (equivalent to 154 mcmol/L). Conclusion: There is a good correlation between TCB and TSB. In infants with TSB 102 mcmol/L at 24 h or TSB > 154 mcmol/L or transcutaneous readings > 13 h at 48 h, a TSB test must be performed after 48 h of life. [source]

    Prediction of Onset of Corrosion in Concrete Bridge Decks Using Neural Networks and Case-Based Reasoning

    COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 2 2005
    G. Morcous
    It is based on the integration of artificial neural network (ANN), case-based reasoning (CBR), mechanistic model, and Monte Carlo simulation (MCS). A probabilistic mechanistic model is used to generate the distribution of the time to corrosion initiation based on statistical models of the governing parameters obtained from field data. The proposed ANN and CBR models act as universal functional mapping tools to approximate the relationship between the input and output of the mechanistic model. These tools are integrated with the MCS technique to generate the distribution of the corrosion initiation time using the distributions of the governing parameters. The proposed methodology is applied to predict the time to corrosion initiation of the top reinforcing steel in the concrete deck of the Dickson Bridge in Montreal. This study demonstrates the feasibility, adequate reliability, and computational efficiency of the proposed integrated ANN-MCS and CBR-MCS approaches for preliminary project-level and also network-level analyses. [source]

    Prediction of gas-phase 13C nuclear magnetic shielding constants using ONIOM and optimally selected basis functions

    CONCEPTS IN MAGNETIC RESONANCE, Issue 6 2008
    M. Tafazzoli
    Abstract The wave functions for calculating gas-phase 13C nuclear magnetic shielding constants of 22 molecules have been optimally selected using factorial design as a multivariate technique. GIAO and CSGT methods were used for computation of shielding constants. Different wave functions for different types of carbons were recommended. A wave function as the best level of the theory is proposed for almost similar carbons. ONIOM approach for molecules with different types of carbons is applied. The results of GIAO method using the proposed wave function are in very good agreement with the experimental values. An additional series (21 carbons) were used as test sets and their results confirmed the validity of the approaches. © 2008 Wiley Periodicals, Inc.Concepts Magn Reson Part A 32A: 449,461, 2008. [source]

    Towards an integrated GIS-based coastal forecast workflow

    CONCURRENCY AND COMPUTATION: PRACTICE & EXPERIENCE, Issue 14 2008
    Gabrielle Allen
    Abstract The SURA Coastal Ocean Observing and Prediction (SCOOP) program is using geographical information system (GIS) technologies to visualize and integrate distributed data sources from across the United States and Canada. Hydrodynamic models are run at different sites on a developing multi-institutional computational Grid. Some of these predictive simulations of storm surge and wind waves are triggered by tropical and subtropical cyclones in the Atlantic and the Gulf of Mexico. Model predictions and observational data need to be merged and visualized in a geospatial context for a variety of analyses and applications. A data archive at LSU aggregates the model outputs from multiple sources, and a data-driven workflow triggers remotely performed conversion of a subset of model predictions to georeferenced data sets, which are then delivered to a Web Map Service located at Texas A&M University. Other nodes in the distributed system aggregate the observational data. This paper describes the use of GIS within the SCOOP program for the 2005 hurricane season, along with details of the data-driven distributed dataflow and workflow, which results in geospatial products. We also focus on future plans related to the complimentary use of GIS and Grid technologies in the SCOOP program, through which we hope to provide a wider range of tools that can enhance the tools and capabilities of earth science research and hazard planning. Copyright © 2008 John Wiley & Sons, Ltd. [source]

    Prediction of irritancy in the human skin irritancy model and occupational setting

    CONTACT DERMATITIS, Issue 2 2003
    R. A. Tupker
    It is of great importance to find ways to lower the incidence of chronic irritant contact dermatitis. In this process, it is crucial to have insight in the factors that can predict irritancy. This review offers a survey of recent findings in the field of skin irritancy testing, discussed in the context of renowned, older work. Extrinsic and intrinsic factors that may determine the outcome of irritancy testing in the human skin model are considered. In recent decades, there has been increasing interest in factors influencing the development of occupational dermatitis by means of prospective cohort studies. This promising new area of investigation is discussed separately. [source]

    Daily Patient Flow Is Not Surge: "Management Is Prediction"

    ACADEMIC EMERGENCY MEDICINE, Issue 11 2006
    Steven J. Davidson MD
    No abstract is available for this article. [source]

    Early intervention in patients at ultra high risk of psychosis: benefits and risks

    ACTA PSYCHIATRICA SCANDINAVICA, Issue 6 2009
    M. B. De Koning
    Objective:, Prediction of transition to psychosis in the prodromal phase of schizophrenia has raised interest in intervention prior to the onset of frank psychosis. The aim of this review was to examine whether interventions in the prodromal phase have a favourable benefit/risk ratio. Method:, A literature search in PubMed, EMBASE and PsycINFO was performed. Results:, Three randomized clinical trials with antipsychotic medication and/or cognitive behavioural therapy as clinical intervention suggested a positive effect at the end of treatment, but no significant differences were found at the end of follow-up periods from 1 to 4 years. Naturalistic studies present a hypothesis about a possible preventive effect of antidepressive medication. The results of eight other studies are more difficult to interpret. Side-effects of antipsychotic medication and non-adherence with medication are essential problems. Conclusion:, At the present time, the data concerning the benefits and risks do not justify prodromal intervention as standard clinical practice. [source]

    The Diagnosis and Prediction of Bank Failures in Zambia, 1990,98

    DEVELOPMENT POLICY REVIEW, Issue 3 2002
    Samuel Munzele Maimbo
    This article presents a non-econometric, yet practical approach for regulators in developing countries. With limited financial resources to determine the ,safety and soundness' of a large number of financial institutuions, regulatory authorities are appreciative of any kind of mechanism that can identify banks that are in financial difficulties. The Zambian case is interesting, in that the bank failures of 1995 and 1997/8 brought into question the ability of the central bank to diagnose the financial condition of banks. This article evaluates the Bank of Zambia's experience over the period 1990 to March 1998 and makes recommendations on how to improve diagnosis and prediction of bank failures by incorporating non-financial factors into the analysis of bank performance. [source]

    Prenatal and family risks of children born to mothers with epilepsy: effects on cognitive development

    DEVELOPMENTAL MEDICINE & CHILD NEUROLOGY, Issue 2 2008
    Karl Titze PhD
    The offspring of mothers with epilepsy are considered to be at developmental risk during pregnancy from: (1) generalized maternal seizures (hypoxia); (2) teratogenicity of antiepileptic drugs (AEDs); and (3) adverse socio-familial conditions associated with having a chronically sick mother. Sixty-seven children of mothers with epilepsy and 49 children from non-affected mothers, matched for control variables, were followed from birth to adolescence (53 males, 63 females; mean age 14y 2mo, range 10-20y). Prediction of intellectual performance of these children during adolescence was calculated from the following variables: maternal generalized seizures, prenatal exposure to AEDs, and quality of family stimulation (HOME Inventory) assessed in children at 2 years of age. Children who were prenatally exposed to AEDs achieved lower IQs than control children at adolescence. This effect was moderately significant for children who had been exposed to monotherapy (6 IQ points lower), but was considerable in those exposed to polytherapy (12 IQ points lower). Generalized seizures during pregnancy, observed in half the mothers, did not exacerbate this effect. Relative to prenatal risk status, the quality of the family environment had varied effects on intellectual development. Children with prenatal risks appeared to be more vulnerable to environmental disadvantage than control children, but they also showed longer-lasting effects of environmental support. [source]

    Prediction of mortality at age 40 in Danish males at high and low risk for alcoholism

    ACTA PSYCHIATRICA SCANDINAVICA, Issue 6 2004
    J. Knop
    Objective:, This prospective high-risk study examined the influence of father's alcoholism and other archival-generated measures on premature death. Method:, Sons of alcoholic fathers (n = 223) and sons of non-alcoholic fathers (n = 106) have been studied from birth to age 40. Archival predictors of premature death included father's alcoholism, childhood developmental data, and diagnostic information obtained from the Psychiatric Register and alcoholism clinics. Results:, By age 40, 21 of the 329 subjects had died (6.4%), a rate that is more than two times greater than expected. Sons of alcoholic fathers were not more likely to die by age 40. Premature death was associated with physical immaturity at 1-year of age and psychiatric/alcoholism treatment. No significant interactions were found between risk and archival measures. Conclusion:, Genetic vulnerability did not independently predict death at age 40. Death was associated with developmental immaturities and treatment for a psychiatric and/or substance abuse problem. [source]

    Prediction of cardiovascular and total mortality in Chinese type 2 diabetic patients by the WHO definition for the metabolic syndrome

    DIABETES OBESITY & METABOLISM, Issue 1 2006
    G. T.-C.
    Aim:, The aim of this study is to investigate the prevalence of metabolic syndrome (MES) in type 2 diabetic patients and the predictive values of the World Health Organization (WHO) and National Cholesterol Education Programme (NCEP) definitions and the individual components of the MES on total and cardiovascular mortality. Methods:, A prospective analysis of a consecutive cohort of 5202 Chinese type 2 diabetic patients recruited between July 1994 and April 2001. Results:, The prevalence of the MES was 49.2,58.1% depending on the use of various criteria. There were 189 deaths (men: 100 and women: 89) in these 5205 patients during a median (interquartile range) follow-up period of 2.1 (0.3,3.6 years). Of these, 164 (87%) were classified as cardiovascular deaths. Using the NCEP criterion, patients with MES had a death rate similar to those without (3.51 vs. 3.85%). By contrast, based on the WHO criteria, patients with MES had a higher mortality rate than those without (4.3 vs. 2.4%, p = 0.002). Compared to patients with neither NCEP- nor WHO-defined MES, only the group with MES defined by the WHO, but not NCEP, criterion had significantly higher mortality rate (2.6 vs. 6.8%, p < 0.001). Using Cox regression analysis, only age, duration of diabetes and smoking were identified as independent factors for cardiovascular or total death. Among the various components of MES, hypertension, low BMI and albuminuria were the key predictors for these adverse events. Conclusions:, In Chinese type 2 diabetic patients, the WHO criterion has a better discriminative power over the NCEP criterion for predicting death. Among the various components of the MES defined either by WHO or NCEP, hypertension, albuminuria and low BMI were the main predictors of cardiovascular and total mortality. [source]

    Current literature in diabetes

    DIABETES/METABOLISM: RESEARCH AND REVIEWS, Issue 2 2009
    Article first published online: 13 FEB 200
    In order to keep subscribers up-to-date with the latest developments in their field, John Wiley & Sons are providing a current awareness service in each issue of the journal. The bibliography contains newly published material in the field of diabetes/metabolism. Each bibliography is divided into 26 sections: 1 Reviews; 2 General; 3 Genetics; 4 Epidemiology; 5 Immunology; 6 Obesity; 7 Prediction and Prevention; 8 Intervention: a) General; b) Care; c) Drug Therapy; d)Economics; e) Gene therapy; f) Nursing; g) Nutrition; h) Surgery; i) Transplantation; 9 Pathology and Complications: a) General; b) Cardiovascular; c) Eye disease; d) Gestational and fetal; e) Neurological; f) Podiatrical; g) Renal; 10 Endocrinology & Metabolism; 11 Experimental Studies; 12 Diagnosis and Techniques. Within each section, articles are listed in alphabetical order with respect to author [source]

    Current literature in diabetes

    DIABETES/METABOLISM: RESEARCH AND REVIEWS, Issue 7 2008
    Article first published online: 29 SEP 200
    In order to keep subscribers up-to-date with the latest developments in their field, John Wiley & Sons are providing a current awareness service in each issue of the journal. The bibliography contains newly published material in the field of diabetes/metabolism. Each bibliography is divided into 26 sections: 1 Reviews; 2 General; 3 Genetics; 4 Epidemiology; 5 Immunology; 6 Obesity; 7 Prediction and Prevention; 8 Intervention: a) General; b) Care; c) Drug Therapy; d)Economics; e) Gene therapy; f) Nursing; g) Nutrition; h) Surgery; i) Transplantation; 9 Pathology and Complications: a) General; b) Cardiovascular; c) Eye disease; d) Gestational and fetal; e) Neurological; f) Podiatrical; g) Renal; 10 Endocrinology & Metabolism; 11 Experimental Studies; 12 Diagnosis and Techniques. Within each section, articles are listed in alphabetical order with respect to author [source]