Fire Effects, Education, and Expert Systems

Science.gov (United States)

Robert E. Martin

1987-01-01

Predicting the effects of fires in the year 2000 and beyond will be enhanced by the use of expert systems. Although our predictions may have broad confidence limits, expert systems should help us to improve the predictions and to focus on the areas where improved knowledge is most needed. The knowledge of experts can be incorporated into previously existing knowledge...

Year-ahead prediction of US landfalling hurricane numbers: intense hurricanes

OpenAIRE

Khare, Shree; Jewson, Stephen

2005-01-01

We continue with our program to derive simple practical methods that can be used to predict the number of US landfalling hurricanes a year in advance. We repeat an earlier study, but for a slightly different definition landfalling hurricanes, and for intense hurricanes only. We find that the averaging lengths needed for optimal predictions of numbers of intense hurricanes are longer than those needed for optimal predictions of numbers of hurricanes of all strengths.

Neural processing of emotional-intensity predicts emotion regulation choice.

Science.gov (United States)

Shafir, Roni; Thiruchselvam, Ravi; Suri, Gaurav; Gross, James J; Sheppes, Gal

2016-12-01

Emotional-intensity is a core characteristic of affective events that strongly determines how individuals choose to regulate their emotions. Our conceptual framework suggests that in high emotional-intensity situations, individuals prefer to disengage attention using distraction, which can more effectively block highly potent emotional information, as compared with engagement reappraisal, which is preferred in low emotional-intensity. However, existing supporting evidence remains indirect because prior intensity categorization of emotional stimuli was based on subjective measures that are potentially biased and only represent the endpoint of emotional-intensity processing. Accordingly, this study provides the first direct evidence for the role of online emotional-intensity processing in predicting behavioral regulatory-choices. Utilizing the high temporal resolution of event-related potentials, we evaluated online neural processing of stimuli's emotional-intensity (late positive potential, LPP) prior to regulatory-choices between distraction and reappraisal. Results showed that enhanced neural processing of intensity (enhanced LPP amplitudes) uniquely predicted (above subjective measures of intensity) increased tendency to subsequently choose distraction over reappraisal. Additionally, regulatory-choices led to adaptive consequences, demonstrated in finding that actual implementation of distraction relative to reappraisal-choice resulted in stronger attenuation of LPPs and self-reported arousal. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Prediction of absolute infrared intensities for the fundamental vibrations of H2O2

Science.gov (United States)

Rogers, J. D.; Hillman, J. J.

1981-01-01

Absolute infrared intensities are predicted for the vibrational bands of gas-phase H2O2 by the use of a hydrogen atomic polar tensor transferred from the hydroxyl hydrogen atom of CH3OH. These predicted intensities are compared with intensities predicted by the use of a hydrogen atomic polar tensor transferred from H2O. The predicted relative intensities agree well with published spectra of gas-phase H2O2, and the predicted absolute intensities are expected to be accurate to within at least a factor of two. Among the vibrational degrees of freedom, the antisymmetric O-H bending mode nu(6) is found to be the strongest with a calculated intensity of 60.5 km/mole. The torsional band, a consequence of hindered rotation, is found to be the most intense fundamental with a predicted intensity of 120 km/mole. These results are compared with the recent absolute intensity determinations for the nu(6) band.

EKORISK project - an information system for prediction and expert evaluation of environmental impact

International Nuclear Information System (INIS)

Zaimov, V.; Antonov, A.

1993-01-01

The aim of this project is to create an expert system for prediction, evaluation and decision making support in case of accidents. The system consists of the following modules: 1) A data base containing information about the situation - geographical and demographical data for the region of the accident as well as data about the contaminants. The data about geographic objects (boundaries, rivers, roads, towns, soils, etc.) is managed and visualized by a geographic information system (GIS), which produces multi-layer geographical maps, showing different viewpoints of the region of interest. Information about the pollutants, their use and storage, as well as data about the available resources for action in case of accidents, are stored in relational data bases which guarantee easy access, search, sorting and proper visualisation. 2) Predicting the propagation of contamination by using actual meteorological information and applying mathematical models for propagation of the spilled substances in the air, water and ground. They calculate the concentration of the substance as a function of time and distance from the initial spill location. The choice of the proper model is made by applying expert knowledge for evaluation of situation and comparing the model characteristics. 3) Suggesting actions for minimising the accident's impact. Expert knowledge is used for recommendations concerning deactivating of the region as well as actions for reducing the absorbed radiation doses of population. The modern technologies for knowledge processing and the object-oriented approach ensure flexibility and integration of all subsystems. (author)

Deep nets vs expert designed features in medical physics: An IMRT QA case study.

Science.gov (United States)

Interian, Yannet; Rideout, Vincent; Kearney, Vasant P; Gennatas, Efstathios; Morin, Olivier; Cheung, Joey; Solberg, Timothy; Valdes, Gilmer

2018-03-30

The purpose of this study was to compare the performance of Deep Neural Networks against a technique designed by domain experts in the prediction of gamma passing rates for Intensity Modulated Radiation Therapy Quality Assurance (IMRT QA). A total of 498 IMRT plans across all treatment sites were planned in Eclipse version 11 and delivered using a dynamic sliding window technique on Clinac iX or TrueBeam Linacs. Measurements were performed using a commercial 2D diode array, and passing rates for 3%/3 mm local dose/distance-to-agreement (DTA) were recorded. Separately, fluence maps calculated for each plan were used as inputs to a convolution neural network (CNN). The CNNs were trained to predict IMRT QA gamma passing rates using TensorFlow and Keras. A set of model architectures, inspired by the convolutional blocks of the VGG-16 ImageNet model, were constructed and implemented. Synthetic data, created by rotating and translating the fluence maps during training, was created to boost the performance of the CNNs. Dropout, batch normalization, and data augmentation were utilized to help train the model. The performance of the CNNs was compared to a generalized Poisson regression model, previously developed for this application, which used 78 expert designed features. Deep Neural Networks without domain knowledge achieved comparable performance to a baseline system designed by domain experts in the prediction of 3%/3 mm Local gamma passing rates. An ensemble of neural nets resulted in a mean absolute error (MAE) of 0.70 ± 0.05 and the domain expert model resulted in a 0.74 ± 0.06. Convolutional neural networks (CNNs) with transfer learning can predict IMRT QA passing rates by automatically designing features from the fluence maps without human expert supervision. Predictions from CNNs are comparable to a system carefully designed by physicist experts. © 2018 American Association of Physicists in Medicine.

Expert status and performance.

Directory of Open Access Journals (Sweden)

Mark A Burgman

Full Text Available Expert judgements are essential when time and resources are stretched or we face novel dilemmas requiring fast solutions. Good advice can save lives and large sums of money. Typically, experts are defined by their qualifications, track record and experience. The social expectation hypothesis argues that more highly regarded and more experienced experts will give better advice. We asked experts to predict how they will perform, and how their peers will perform, on sets of questions. The results indicate that the way experts regard each other is consistent, but unfortunately, ranks are a poor guide to actual performance. Expert advice will be more accurate if technical decisions routinely use broadly-defined expert groups, structured question protocols and feedback.

Computer Based Expert Systems.

Science.gov (United States)

Parry, James D.; Ferrara, Joseph M.

1985-01-01

Claims knowledge-based expert computer systems can meet needs of rural schools for affordable expert advice and support and will play an important role in the future of rural education. Describes potential applications in prediction, interpretation, diagnosis, remediation, planning, monitoring, and instruction. (NEC)

SeTES, a Self-Teaching Expert System for the analysis, design and prediction of gas production from shales and a prototype for a new generation of Expert Systems in the Earth Sciences

Science.gov (United States)

Kuzma, H. A.; Boyle, K.; Pullman, S.; Reagan, M. T.; Moridis, G. J.; Blasingame, T. A.; Rector, J. W.; Nikolaou, M.

2010-12-01

A Self Teaching Expert System (SeTES) is being developed for the analysis, design and prediction of gas production from shales. An Expert System is a computer program designed to answer questions or clarify uncertainties that its designers did not necessarily envision which would otherwise have to be addressed by consultation with one or more human experts. Modern developments in computer learning, data mining, database management, web integration and cheap computing power are bringing the promise of expert systems to fruition. SeTES is a partial successor to Prospector, a system to aid in the identification and evaluation of mineral deposits developed by Stanford University and the USGS in the late 1970s, and one of the most famous early expert systems. Instead of the text dialogue used in early systems, the web user interface of SeTES helps a non-expert user to articulate, clarify and reason about a problem by navigating through a series of interactive wizards. The wizards identify potential solutions to queries by retrieving and combining together relevant records from a database. Inferences, decisions and predictions are made from incomplete and noisy inputs using a series of probabilistic models (Bayesian Networks) which incorporate records from the database, physical laws and empirical knowledge in the form of prior probability distributions. The database is mainly populated with empirical measurements, however an automatic algorithm supplements sparse data with synthetic data obtained through physical modeling. This constitutes the mechanism for how SeTES self-teaches. SeTES’ predictive power is expected to grow as users contribute more data into the system. Samples are appropriately weighted to favor high quality empirical data over low quality or synthetic data. Finally, a set of data visualization tools digests the output measurements into graphical outputs.

Phenobarbital in intensive care unit pediatric population: predictive performances of population pharmacokinetic model.

Science.gov (United States)

Marsot, Amélie; Michel, Fabrice; Chasseloup, Estelle; Paut, Olivier; Guilhaumou, Romain; Blin, Olivier

2017-10-01

An external evaluation of phenobarbital population pharmacokinetic model described by Marsot et al. was performed in pediatric intensive care unit. Model evaluation is an important issue for dose adjustment. This external evaluation should allow confirming the proposed dosage adaptation and extending these recommendations to the entire intensive care pediatric population. External evaluation of phenobarbital published population pharmacokinetic model of Marsot et al. was realized in a new retrospective dataset of 35 patients hospitalized in a pediatric intensive care unit. The published population pharmacokinetic model was implemented in nonmem 7.3. Predictive performance was assessed by quantifying bias and inaccuracy of model prediction. Normalized prediction distribution errors (NPDE) and visual predictive check (VPC) were also evaluated. A total of 35 infants were studied with a mean age of 33.5 weeks (range: 12 days-16 years) and a mean weight of 12.6 kg (range: 2.7-70.0 kg). The model predicted the observed phenobarbital concentrations with a reasonable bias and inaccuracy. The median prediction error was 3.03% (95% CI: -8.52 to 58.12%), and the median absolute prediction error was 26.20% (95% CI: 13.07-75.59%). No trends in NPDE and VPC were observed. The model previously proposed by Marsot et al. in neonates hospitalized in intensive care unit was externally validated for IV infusion administration. The model-based dosing regimen was extended in all pediatric intensive care unit to optimize treatment. Due to inter- and intravariability in pharmacokinetic model, this dosing regimen should be combined with therapeutic drug monitoring. © 2017 Société Française de Pharmacologie et de Thérapeutique.

The use of a sweetener substitution method to predict dietary exposures for the intense sweetener rebaudioside A.

Science.gov (United States)

Renwick, A G

2008-07-01

There are more published dietary exposure data for intense sweeteners than for any other group of food additives. Data are available for countries with different patterns of sweetener approvals and also for population groups with high potential intakes, such as children and diabetic subjects. These data provide a secure basis for predicting the potential intakes of a novel intense sweetener by adjustment of the reported intakes of different sweeteners in mg/kg body weight by their relative sweetness intensities. This approach allows the possibility that a novel sweetener attains the same pattern and extent of use as the existing sweeteners. The intakes by high consumers of other sweeteners allows for possible brand loyalty to the novel sweetener. Using this method, the estimated dietary exposures for rebaudioside A in average and high consumers are predicted to be 1.3 and 3.4mg/kg body weight per day for the general population, 2.1 and 5.0mg/kg body weight per day for children and 3.4 and 4.5mg/kg body weight per day for children with diabetes. The temporary ADI defined by the JECFA for steviol glycosides [JECFA, 2005. Steviol glycosides. In: 63rd Meeting of the Joint FAO/WHO Expert Committee on Food Additives. World Health Organization (WHO), Geneva, Switzerland, WHO Technical Report Series 928, pp. 34-39] was set at 0-2mg/kg body weight (expressed as steviol equivalents); after correction for the difference in molecular weights, these estimated intakes of rebaudioside A are equivalent to daily steviol intakes of less than 2mg/kg. In consequence, this analysis shows that the intakes of rebaudioside A would not exceed the JECFA temporary ADI set for steviol glycosides.

Football experts versus sports economists: Whose forecasts are better?

Science.gov (United States)

Frick, Bernd; Wicker, Pamela

2016-08-01

Given the uncertainty of outcome in sport, predicting the outcome of sporting contests is a major topic in sport sciences. This study examines the accuracy of expert predictions in the German Bundesliga and compares their predictions to those of sports economists. Prior to the start of each season, a set of distinguished experts (head coaches and players) express their subjective evaluations of the teams in school grades. While experts may be driven by irrational sentiments and may therefore systematically over- or underestimate specific teams, sports economists use observable characteristics to predict season outcomes. The latter typically use team wage bills given the positive pay-performance relationship as well as other factors (average team age, tenure, appearances on national team, and attendance). Using data from 15 consecutive Bundesliga seasons, the predictive accuracy of expert evaluations and sports economists is analysed. The results of separate estimations show that relative grade and relative wage bill significantly affect relative points, while age, tenure, appearances, and attendance are insignificant. In a joint model, relative grade and relative wage bill are still statistically significant, suggesting that the two types of predictions are complements rather than substitutes. Consequently, football experts and sports economists seem to rely on completely different sources of information when making their predictions.

Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

Science.gov (United States)

Ibrahim, Wael Refaat Anis

The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an

Predictability of bone density at posterior mandibular implant sites using cone-beam computed tomography intensity values.

Science.gov (United States)

Alkhader, Mustafa; Hudieb, Malik; Khader, Yousef

2017-01-01

The aim of this study was to investigate the predictability of bone density at posterior mandibular implant sites using cone-beam computed tomography (CBCT) intensity values. CBCT cross-sectional images for 436 posterior mandibular implant sites were selected for the study. Using Invivo software (Anatomage, San Jose, California, USA), two observers classified the bone density into three categories: low, intermediate, and high, and CBCT intensity values were generated. Based on the consensus of the two observers, 15.6% of sites were of low bone density, 47.9% were of intermediate density, and 36.5% were of high density. Receiver-operating characteristic analysis showed that CBCT intensity values had a high predictive power for predicting high density sites (area under the curve [AUC] =0.94, P < 0.005) and intermediate density sites (AUC = 0.81, P < 0.005). The best cut-off value for intensity to predict intermediate density sites was 218 (sensitivity = 0.77 and specificity = 0.76) and the best cut-off value for intensity to predict high density sites was 403 (sensitivity = 0.93 and specificity = 0.77). CBCT intensity values are considered useful for predicting bone density at posterior mandibular implant sites.

Contextual Factors for Finding Similar Experts

DEFF Research Database (Denmark)

Hofmann, Katja; Balog, Krisztian; Bogers, Toine

2010-01-01

-seeking models, are rarely taken into account. In this article, we extend content-based expert-finding approaches with contextual factors that have been found to influence human expert finding. We focus on a task of science communicators in a knowledge-intensive environment, the task of finding similar experts......, given an example expert. Our approach combines expertise-seeking and retrieval research. First, we conduct a user study to identify contextual factors that may play a role in the studied task and environment. Then, we design expert retrieval models to capture these factors. We combine these with content......-based retrieval models and evaluate them in a retrieval experiment. Our main finding is that while content-based features are the most important, human participants also take contextual factors into account, such as media experience and organizational structure. We develop two principled ways of modeling...

Does expert perceptual anticipation transfer to a dissimilar domain?

Science.gov (United States)

Müller, Sean; McLaren, Michelle; Appleby, Brendyn; Rosalie, Simon M

2015-06-01

The purpose of this experiment was to extend theoretical understanding of transfer of learning by investigating whether expert perceptual anticipation skill transfers to a dissimilar domain. The capability of expert and near-expert rugby players as well as novices to anticipate skill type within rugby (learning sport) was first examined using a temporal occlusion paradigm. Participants watched video footage of an opponent performing rugby skill types that were temporally occluded at different points in the opponent's action and then made a written prediction. Thereafter, the capability of participants to transfer their anticipation skill to predict pitch type in baseball (transfer sport) was examined. Participants watched video footage of a pitcher throwing different pitch types that were temporally occluded and made a written prediction. Results indicated that expert and near-expert rugby players anticipated significantly better than novices across all occlusion conditions. However, none of the skill groups were able to transfer anticipation skill to predict pitch type in baseball. The findings of this paper, along with existing literature, support the theoretical prediction that transfer of perceptual anticipation is expertise dependent and restricted to similar domains. (c) 2015 APA, all rights reserved).

Geometrical theory to predict eccentric photorefraction intensity profiles in the human eye

Science.gov (United States)

Roorda, Austin; Campbell, Melanie C. W.; Bobier, W. R.

1995-08-01

In eccentric photorefraction, light returning from the retina of the eye is photographed by a camera focused on the eye's pupil. We use a geometrical model of eccentric photorefraction to generate intensity profiles across the pupil image. The intensity profiles for three different monochromatic aberration functions induced in a single eye are predicted and show good agreement with the measured eccentric photorefraction intensity profiles. A directional reflection from the retina is incorporated into the calculation. Intensity profiles for symmetric and asymmetric aberrations are generated and measured. The latter profile shows a dependency on the source position and the meridian. The magnitude of the effect of thresholding on measured pattern extents is predicted. Monochromatic aberrations in human eyes will cause deviations in the eccentric photorefraction measurements from traditional crescents caused by defocus and may cause misdiagnoses of ametropia or anisometropia. Our results suggest that measuring refraction along the vertical meridian is preferred for screening studies with the eccentric photorefractor.

Ask-the-expert: Active Learning Based Knowledge Discovery Using the Expert

Science.gov (United States)

Das, Kamalika; Avrekh, Ilya; Matthews, Bryan; Sharma, Manali; Oza, Nikunj

2017-01-01

Often the manual review of large data sets, either for purposes of labeling unlabeled instances or for classifying meaningful results from uninteresting (but statistically significant) ones is extremely resource intensive, especially in terms of subject matter expert (SME) time. Use of active learning has been shown to diminish this review time significantly. However, since active learning is an iterative process of learning a classifier based on a small number of SME-provided labels at each iteration, the lack of an enabling tool can hinder the process of adoption of these technologies in real-life, in spite of their labor-saving potential. In this demo we present ASK-the-Expert, an interactive tool that allows SMEs to review instances from a data set and provide labels within a single framework. ASK-the-Expert is powered by an active learning algorithm for training a classifier in the backend. We demonstrate this system in the context of an aviation safety application, but the tool can be adopted to work as a simple review and labeling tool as well, without the use of active learning.

Efficacy beliefs predict collaborative practice among intensive care unit nurses

NARCIS (Netherlands)

Le Blanc, Pascale M.; Schaufeli, Wilmar B.; Salanova, Marisa; Llorens, Susana; Nap, Raoul E.

P>Aim. This paper is a report of an investigation of whether intensive care nurses' efficacy beliefs predict future collaborative practice, and to test the potential mediating role of team commitment in this relationship. Background. Recent empirical studies in the field of work and organizational

Prediction of maximum earthquake intensities for the San Francisco Bay region

Science.gov (United States)

Borcherdt, Roger D.; Gibbs, James F.

1975-01-01

The intensity data for the California earthquake of April 18, 1906, are strongly dependent on distance from the zone of surface faulting and the geological character of the ground. Considering only those sites (approximately one square city block in size) for which there is good evidence for the degree of ascribed intensity, the empirical relation derived between 1906 intensities and distance perpendicular to the fault for 917 sites underlain by rocks of the Franciscan Formation is: Intensity = 2.69 - 1.90 log (Distance) (km). For sites on other geologic units intensity increments, derived with respect to this empirical relation, correlate strongly with the Average Horizontal Spectral Amplifications (AHSA) determined from 99 three-component recordings of ground motion generated by nuclear explosions in Nevada. The resulting empirical relation is: Intensity Increment = 0.27 +2.70 log (AHSA), and average intensity increments for the various geologic units are -0.29 for granite, 0.19 for Franciscan Formation, 0.64 for the Great Valley Sequence, 0.82 for Santa Clara Formation, 1.34 for alluvium, 2.43 for bay mud. The maximum intensity map predicted from these empirical relations delineates areas in the San Francisco Bay region of potentially high intensity from future earthquakes on either the San Andreas fault or the Hazard fault.

Prediction of maximum earthquake intensities for the San Francisco Bay region

Energy Technology Data Exchange (ETDEWEB)

Borcherdt, R.D.; Gibbs, J.F.

1975-01-01

The intensity data for the California earthquake of Apr 18, 1906, are strongly dependent on distance from the zone of surface faulting and the geological character of the ground. Considering only those sites (approximately one square city block in size) for which there is good evidence for the degree of ascribed intensity, the empirical relation derived between 1906 intensities and distance perpendicular to the fault for 917 sites underlain by rocks of the Franciscan formation is intensity = 2.69 - 1.90 log (distance) (km). For sites on other geologic units, intensity increments, derived with respect to this empirical relation, correlate strongly with the average horizontal spectral amplifications (AHSA) determined from 99 three-component recordings of ground motion generated by nuclear explosions in Nevada. The resulting empirical relation is intensity increment = 0.27 + 2.70 log (AHSA), and average intensity increments for the various geologic units are -0.29 for granite, 0.19 for Franciscan formation, 0.64 for the Great Valley sequence, 0.82 for Santa Clara formation, 1.34 for alluvium, and 2.43 for bay mud. The maximum intensity map predicted from these empirical relations delineates areas in the San Francisco Bay region of potentially high intensity from future earthquakes on either the San Andreas fault or the Hayward fault.

Adaptability of expert visual anticipation in baseball batting.

Science.gov (United States)

Müller, Sean; Fadde, Peter J; Harbaugh, Allen G

2017-09-01

By manipulating stimulus variation in terms of opponent pitcher actions, this study investigated the capability of expert (n = 30) and near-expert (n = 95) professional baseball batters to adapt anticipation skill when using the video simulation temporal occlusion paradigm. Participants watched in-game footage of two pitchers, one after the other, that was temporally occluded at ball release and various points during ball flight. They were required to make a written prediction of pitch types and locations. Per cent accuracy was calculated for pitch type, for pitch location, and for type and location combined. Results indicated that experts and near-experts could adapt their anticipation to predict above guessing level across both pitchers, but adaptation to the left-handed pitcher was poorer than the right-handed pitcher. Small-to-moderate effect sizes were found in terms of superior adaptation by experts over near-experts at the ball release and early ball flight occlusion conditions. The findings of this study extend theoretical and applied knowledge of expertise in striking sports. Practical application of the instruments and findings are discussed in terms of applied researchers, practitioners and high-performance staff in professional sporting organisations.

Expectations and drivers of future greenhouse gas emissions from Canada's oil sands: An expert elicitation

International Nuclear Information System (INIS)

McKellar, Jennifer M.; Sleep, Sylvia; Bergerson, Joule A.; MacLean, Heather L.

2017-01-01

The greenhouse gas (GHG) emissions intensity of oil sands operations has declined over time but has not offset absolute emissions growth due to rapidly increasing production. Policy making, decisions about research and development, and stakeholder discourse should be informed by an assessment of future emissions intensity trends, however informed projections are not easily generated. This study investigates expected trends in oil sands GHG emissions using expert elicitation. Thirteen experts participated in a survey, providing quantitative estimates of expected GHG emissions intensity changes and qualitative identifications of drivers. Experts generally agree that emissions intensity reductions are expected at commercially operating projects by 2033, with the greatest reductions expected through the use of technology in the in situ area of oil sands activity (40% mean reduction at multiple projects, averaged across experts). Incremental process changes are expected to contribute less to reducing GHG emissions intensity, however their potentially lower risk and cost may result in larger cumulative reductions. Both technology availability and more stringent GHG mitigation policies are required to realize these emissions intensity reductions. This paper demonstrates a method to increase rigour in emissions forecasting activities and the results can inform policy making, research and development and modelling and forecasting studies. - Highlights: • Expert elicitation used to investigate expected trends in oil sands GHG emissions. • Overall, emissions intensity reductions are expected at commercial projects by 2033. • Reductions are expected due to both technology changes and process improvements. • Technology availability and more stringent GHG policies are needed for reductions. • Method used increases rigour in emissions forecasting, and results inform policy.

Beyond intensity: Spectral features effectively predict music-induced subjective arousal.

Science.gov (United States)

Gingras, Bruno; Marin, Manuela M; Fitch, W Tecumseh

2014-01-01

Emotions in music are conveyed by a variety of acoustic cues. Notably, the positive association between sound intensity and arousal has particular biological relevance. However, although amplitude normalization is a common procedure used to control for intensity in music psychology research, direct comparisons between emotional ratings of original and amplitude-normalized musical excerpts are lacking. In this study, 30 nonmusicians retrospectively rated the subjective arousal and pleasantness induced by 84 six-second classical music excerpts, and an additional 30 nonmusicians rated the same excerpts normalized for amplitude. Following the cue-redundancy and Brunswik lens models of acoustic communication, we hypothesized that arousal and pleasantness ratings would be similar for both versions of the excerpts, and that arousal could be predicted effectively by other acoustic cues besides intensity. Although the difference in mean arousal and pleasantness ratings between original and amplitude-normalized excerpts correlated significantly with the amplitude adjustment, ratings for both sets of excerpts were highly correlated and shared a similar range of values, thus validating the use of amplitude normalization in music emotion research. Two acoustic parameters, spectral flux and spectral entropy, accounted for 65% of the variance in arousal ratings for both sets, indicating that spectral features can effectively predict arousal. Additionally, we confirmed that amplitude-normalized excerpts were adequately matched for loudness. Overall, the results corroborate our hypotheses and support the cue-redundancy and Brunswik lens models.

Expert system based radionuclide identification

International Nuclear Information System (INIS)

Aarnio, P.A.; Ala-Heikkil, J.J.; Hakulinen, T.T.; Nikkinen, M.T.

1998-01-01

An expert system coupled with the gamma spectrum analysis system SAMPO has been developed for automating the qualitative identification of radionuclides as well as for determining the quantitative parameters of the spectrum components. The program is written in C-language and runs in various environments ranging from PCs to UNIX workstations. The expert system utilizes a complete gamma library with over 2600 nuclides and 80,000 lines, and a rule base of about fifty criteria including energies, relative peak intensities, genesis modes, half lives, parent-daughter relationships, etc. The rule base is furthermore extensible by the user. This is not an original contribution but a somewhat updated version of papers and reports previously published elsewhere. (author)

Sherlock Holmes: an expert's view of expertise.

Science.gov (United States)

André, Didierjean; Fernand, Gobet

2008-02-01

In recent years, there has been an intense research effort to understand the cognitive processes and structures underlying expert behaviour. Work in different fields, including scientific domains, sports, games and mnemonics, has shown that there are vast differences in perceptual abilities between experts and novices, and that these differences may underpin other cognitive differences in learning, memory and problem solving. In this article, we evaluate the progress made in the last years through the eyes of an outstanding, albeit fictional, expert: Sherlock Holmes. We first use the Sherlock Holmes character to illustrate expert processes as described by current research and theories. In particular, the role of perception, as well as the nature and influence of expert knowledge, are all present in the description of Conan Doyle's hero. In the second part of the article, we discuss a number of issues that current research on expertise has barely addressed. These gaps include, for example, several forms of reasoning, the influence of emotions on cognition, and the effect of age on experts' knowledge and cognitive processes. Thus, although nearly 120-year-old, Conan Doyle's books show remarkable illustrations of expert behaviour, including the coverage of themes that have mostly been overlooked by current research.

Processes in construction of failure management expert systems from device design information

Science.gov (United States)

Malin, Jane T.; Lance, Nick

1987-01-01

This paper analyzes the tasks and problem solving methods used by an engineer in constructing a failure management expert system from design information about the device to te diagnosed. An expert test engineer developed a trouble-shooting expert system based on device design information and experience with similar devices, rather than on specific expert knowledge gained from operating the device or troubleshooting its failures. The construction of the expert system was intensively observed and analyzed. This paper characterizes the knowledge, tasks, methods, and design decisions involved in constructing this type of expert system, and makes recommendations concerning tools for aiding and automating construction of such systems.

A Reliable and Valid Survey to Predict a Patient’s Gagging Intensity

Directory of Open Access Journals (Sweden)

Casey M. Hearing

2014-07-01

Full Text Available Objectives: The aim of this study was to devise a reliable and valid survey to predict the intensity of someone’s gag reflex. Material and Methods: A 10-question Predictive Gagging Survey was created, refined, and tested on 59 undergraduate participants. The questions focused on risk factors and experiences that would indicate the presence and strength of someone’s gag reflex. Reliability was assessed by administering the survey to a group of 17 participants twice, with 3 weeks separating the two administrations. Finally, the survey was given to 25 dental patients. In these cases, patients completed an informed consent form, filled out the survey, and then had a maxillary impression taken while their gagging response was quantified from 1 to 5 on the Fiske and Dickinson Gagging Intensity Index. Results: There was a moderate positive correlation between the Predictive Gagging Survey and Fiske and Dickinson’s Gagging Severity Index, r = +0.64, demonstrating the survey’s validity. Furthermore, the test-retest reliability was r = +0.96, demonstrating the survey’s reliability. Conclusions: The Predictive Gagging Survey is a 10-question survey about gag-related experiences and behaviours. We established that it is a reliable and valid method to assess the strength of someone’s gag reflex.

Expert Systems: What Is an Expert System?

Science.gov (United States)

Duval, Beverly K.; Main, Linda

1994-01-01

Describes expert systems and discusses their use in libraries. Highlights include parts of an expert system; expert system shells; an example of how to build an expert system; a bibliography of 34 sources of information on expert systems in libraries; and a list of 10 expert system shells used in libraries. (Contains five references.) (LRW)

ECG Rhythm Analysis with Expert and Learner-Generated Schemas in Novice Learners

Science.gov (United States)

Blissett, Sarah; Cavalcanti, Rodrigo; Sibbald, Matthew

2015-01-01

Although instruction using expert-generated schemas is associated with higher diagnostic performance, implementation is resource intensive. Learner-generated schemas are an alternative, but may be limited by increases in cognitive load. We compared expert- and learner-generated schemas for learning ECG rhythm interpretation on diagnostic accuracy,…

Ensemble Prediction Model with Expert Selection for Electricity Price Forecasting

Directory of Open Access Journals (Sweden)

Bijay Neupane

2017-01-01

Full Text Available Forecasting of electricity prices is important in deregulated electricity markets for all of the stakeholders: energy wholesalers, traders, retailers and consumers. Electricity price forecasting is an inherently difficult problem due to its special characteristic of dynamicity and non-stationarity. In this paper, we present a robust price forecasting mechanism that shows resilience towards the aggregate demand response effect and provides highly accurate forecasted electricity prices to the stakeholders in a dynamic environment. We employ an ensemble prediction model in which a group of different algorithms participates in forecasting 1-h ahead the price for each hour of a day. We propose two different strategies, namely, the Fixed Weight Method (FWM and the Varying Weight Method (VWM, for selecting each hour’s expert algorithm from the set of participating algorithms. In addition, we utilize a carefully engineered set of features selected from a pool of features extracted from the past electricity price data, weather data and calendar data. The proposed ensemble model offers better results than the Autoregressive Integrated Moving Average (ARIMA method, the Pattern Sequence-based Forecasting (PSF method and our previous work using Artificial Neural Networks (ANN alone on the datasets for New York, Australian and Spanish electricity markets.

The recourse to experts. Political reasons and uses

International Nuclear Information System (INIS)

Dumoulin, L.; La Branche, St.; Robert, C.; Warin, Ph.

2005-01-01

The need of reliable knowledge is necessary to draw adequate public policies. The role of experts is more and more important in any field, the expert brings his own specialized knowledge to the political world, he can define looming threads, can predict catastrophes, can highlight the long-term responsibility of particular choices but he can also contribute to the drawing of adequate solutions. The limit of expert's power lays in his ability to make a synthesis of plural knowledge. This book presents the role and weight of experts in our society from justice to economics via natural risks. A lot of examples of public policies based on expert valuation is given, in particular the recourse to experts of the European Union when it was to deal with the upgrading of nuclear safety standard in eastern countries. (A.C.)

Using expert opinion to evaluate a habitat effectiveness model for elk in western Oregon and Washington.

Science.gov (United States)

Richard S. Holthausen; Michael J. Wisdom; John Pierce; Daniel K. Edwards; Mary M. Rowland

1994-01-01

We used expert opinion to evaluate the predictive reliability of a habitat effectiveness model for elk in western Oregon and Washington. Twenty-five experts in elk ecology were asked to rate habitat quality for 16 example landscapes. Rankings and ratings of 21 experts were significantly correlated with model output. Expert opinion and model predictions differed for 4...

GOTRES: an expert system for fault detection and analysis

International Nuclear Information System (INIS)

Chung, D.T.; Modarres, M.

1989-01-01

This paper describes a deep-knowledge expert system shell for diagnosing faults in process operations. The expert program shell is called GOTRES (GOal TRee Expert System) and uses a goal tree-success tree deep-knowledge structure to model its knowledge-base. To demonstrate GOTRES, we have built an on-line fault diagnosis expert system for an experimental nuclear reactor facility using this shell. The expert system is capable of diagnosing fault conditions using system goal tree as well as utilizing accumulated operating knowledge to predict plant causal and temporal behaviours. The GOTRES shell has also been used for root-cause detection and analysis in a nuclear plant. (author)

Environmental policy. 2000 environmental expert opinion of the Council of Experimental Experts

International Nuclear Information System (INIS)

2000-05-01

The reorientation of energy policy is a key issue. The Council of Environmental Experts considers the further use of atomic energy to be irresponsible and recommends a new orientation. Recommendations are made on ecology-centered taxation. Critical comments are made in the context of conservation of nature, where many species of plants and animals still continue to be endangered. The conservation programme of the Federal government, which also comprises a system of large, interconnected biotopes on 10% of Germany's total surface, is approved, and the potential contribution of sustainable agricultural and forestry policy is discussed in a separate chapter. Further subjects discussed are recycling and waste management, protection of water and soil, air pollution abatement, health protection and genetic engineering. The environmental aspects of Eastern European states becoming EC members are gone into in particular. The network of Europen Environmental Councils, for which the German Council of Environmental Experts currently acts as a coordinator, makes intensive efforts to improve environmental counselling in these states [de

Using Expert Systems To Build Cognitive Simulations.

Science.gov (United States)

Jonassen, David H.; Wang, Sherwood

2003-01-01

Cognitive simulations are runnable computer programs for modeling human cognitive activities. A case study is reported where expert systems were used as a formalism for modeling metacognitive processes in a seminar. Building cognitive simulations engages intensive introspection, ownership and meaning making in learners who build them. (Author/AEF)

Management of neutropenic patients in the intensive care unit (NEWBORNS EXCLUDED) recommendations from an expert panel from the French Intensive Care Society (SRLF) with the French Group for Pediatric Intensive Care Emergencies (GFRUP), the French Society of Anesthesia and Intensive Care (SFAR), the French Society of Hematology (SFH), the French Society for Hospital Hygiene (SF2H), and the French Infectious Diseases Society (SPILF).

Science.gov (United States)

Schnell, David; Azoulay, Elie; Benoit, Dominique; Clouzeau, Benjamin; Demaret, Pierre; Ducassou, Stéphane; Frange, Pierre; Lafaurie, Matthieu; Legrand, Matthieu; Meert, Anne-Pascale; Mokart, Djamel; Naudin, Jérôme; Pene, Frédéric; Rabbat, Antoine; Raffoux, Emmanuel; Ribaud, Patricia; Richard, Jean-Christophe; Vincent, François; Zahar, Jean-Ralph; Darmon, Michael

2016-12-01

Neutropenia is defined by either an absolute or functional defect (acute myeloid leukemia or myelodysplastic syndrome) of polymorphonuclear neutrophils and is associated with high risk of specific complications that may require intensive care unit (ICU) admission. Specificities in the management of critically ill neutropenic patients prompted the establishment of guidelines dedicated to intensivists. These recommendations were drawn up by a panel of experts brought together by the French Intensive Care Society in collaboration with the French Group for Pediatric Intensive Care Emergencies, the French Society of Anesthesia and Intensive Care, the French Society of Hematology, the French Society for Hospital Hygiene, and the French Infectious Diseases Society. Literature review and formulation of recommendations were performed using the Grading of Recommendations Assessment, Development and Evaluation system. Each recommendation was then evaluated and rated by each expert using a methodology derived from the RAND/UCLA Appropriateness Method. Six fields are covered by the provided recommendations: (1) ICU admission and prognosis, (2) protective isolation and prophylaxis, (3) management of acute respiratory failure, (4) organ failure and organ support, (5) antibiotic management and source control, and (6) hematological management. Most of the provided recommendations are obtained from low levels of evidence, however, suggesting a need for additional studies. Seven recommendations were, however, associated with high level of evidences and are related to protective isolation, diagnostic workup of acute respiratory failure, medical management, and timing surgery in patients with typhlitis.

Early hospital mortality prediction of intensive care unit patients using an ensemble learning approach.

Science.gov (United States)

Awad, Aya; Bader-El-Den, Mohamed; McNicholas, James; Briggs, Jim

2017-12-01

Mortality prediction of hospitalized patients is an important problem. Over the past few decades, several severity scoring systems and machine learning mortality prediction models have been developed for predicting hospital mortality. By contrast, early mortality prediction for intensive care unit patients remains an open challenge. Most research has focused on severity of illness scoring systems or data mining (DM) models designed for risk estimation at least 24 or 48h after ICU admission. This study highlights the main data challenges in early mortality prediction in ICU patients and introduces a new machine learning based framework for Early Mortality Prediction for Intensive Care Unit patients (EMPICU). The proposed method is evaluated on the Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II) database. Mortality prediction models are developed for patients at the age of 16 or above in Medical ICU (MICU), Surgical ICU (SICU) or Cardiac Surgery Recovery Unit (CSRU). We employ the ensemble learning Random Forest (RF), the predictive Decision Trees (DT), the probabilistic Naive Bayes (NB) and the rule-based Projective Adaptive Resonance Theory (PART) models. The primary outcome was hospital mortality. The explanatory variables included demographic, physiological, vital signs and laboratory test variables. Performance measures were calculated using cross-validated area under the receiver operating characteristic curve (AUROC) to minimize bias. 11,722 patients with single ICU stays are considered. Only patients at the age of 16 years old and above in Medical ICU (MICU), Surgical ICU (SICU) or Cardiac Surgery Recovery Unit (CSRU) are considered in this study. The proposed EMPICU framework outperformed standard scoring systems (SOFA, SAPS-I, APACHE-II, NEWS and qSOFA) in terms of AUROC and time (i.e. at 6h compared to 48h or more after admission). The results show that although there are many values missing in the first few hour of ICU admission

An expert system based software sizing tool, phase 2

Science.gov (United States)

Friedlander, David

1990-01-01

A software tool was developed for predicting the size of a future computer program at an early stage in its development. The system is intended to enable a user who is not expert in Software Engineering to estimate software size in lines of source code with an accuracy similar to that of an expert, based on the program's functional specifications. The project was planned as a knowledge based system with a field prototype as the goal of Phase 2 and a commercial system planned for Phase 3. The researchers used techniques from Artificial Intelligence and knowledge from human experts and existing software from NASA's COSMIC database. They devised a classification scheme for the software specifications, and a small set of generic software components that represent complexity and apply to large classes of programs. The specifications are converted to generic components by a set of rules and the generic components are input to a nonlinear sizing function which makes the final prediction. The system developed for this project predicted code sizes from the database with a bias factor of 1.06 and a fluctuation factor of 1.77, an accuracy similar to that of human experts but without their significant optimistic bias.

Estimating Production Potentials: Expert Bias in Applied Decision Making

International Nuclear Information System (INIS)

Matthews, L.J.; Burggraf, L.K.; Reece, W.J.

1998-01-01

A study was conducted to evaluate how workers predict manufacturing production potentials given positively and negatively framed information. Findings indicate the existence of a bias toward positive information and suggest that this bias may be reduced with experience but is never the less maintained. Experts err in the same way non experts do in differentially processing negative and positive information. Additionally, both experts and non experts tend to overestimate production potentials in a positive direction. The authors propose that these biases should be addressed with further research including cross domain analyses and consideration in training, workplace design, and human performance modeling

An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU.

Science.gov (United States)

Nemati, Shamim; Holder, Andre; Razmi, Fereshteh; Stanley, Matthew D; Clifford, Gari D; Buchman, Timothy G

2018-04-01

Sepsis is among the leading causes of morbidity, mortality, and cost overruns in critically ill patients. Early intervention with antibiotics improves survival in septic patients. However, no clinically validated system exists for real-time prediction of sepsis onset. We aimed to develop and validate an Artificial Intelligence Sepsis Expert algorithm for early prediction of sepsis. Observational cohort study. Academic medical center from January 2013 to December 2015. Over 31,000 admissions to the ICUs at two Emory University hospitals (development cohort), in addition to over 52,000 ICU patients from the publicly available Medical Information Mart for Intensive Care-III ICU database (validation cohort). Patients who met the Third International Consensus Definitions for Sepsis (Sepsis-3) prior to or within 4 hours of their ICU admission were excluded, resulting in roughly 27,000 and 42,000 patients within our development and validation cohorts, respectively. None. High-resolution vital signs time series and electronic medical record data were extracted. A set of 65 features (variables) were calculated on hourly basis and passed to the Artificial Intelligence Sepsis Expert algorithm to predict onset of sepsis in the proceeding T hours (where T = 12, 8, 6, or 4). Artificial Intelligence Sepsis Expert was used to predict onset of sepsis in the proceeding T hours and to produce a list of the most significant contributing factors. For the 12-, 8-, 6-, and 4-hour ahead prediction of sepsis, Artificial Intelligence Sepsis Expert achieved area under the receiver operating characteristic in the range of 0.83-0.85. Performance of the Artificial Intelligence Sepsis Expert on the development and validation cohorts was indistinguishable. Using data available in the ICU in real-time, Artificial Intelligence Sepsis Expert can accurately predict the onset of sepsis in an ICU patient 4-12 hours prior to clinical recognition. A prospective study is necessary to determine the

Application of Intelligent Dynamic Bayesian Network with Wavelet Analysis for Probabilistic Prediction of Storm Track Intensity Index

Directory of Open Access Journals (Sweden)

Ming Li

2018-06-01

Full Text Available The effective prediction of storm track (ST is greatly beneficial for analyzing the development and anomalies of mid-latitude weather systems. For the non-stationarity, nonlinearity, and uncertainty of ST intensity index (STII, a new probabilistic prediction model was proposed based on dynamic Bayesian network (DBN and wavelet analysis (WA. We introduced probability theory and graph theory for the first time to quantitatively describe the nonlinear relationship and uncertain interaction of the ST system. Then a casual prediction network (i.e., DBN was constructed through wavelet decomposition, structural learning, parameter learning, and probabilistic inference, which was used for expression of relation among predictors and probabilistic prediction of STII. The intensity prediction of the North Pacific ST with data from 1961–2010 showed that the new model was able to give more comprehensive prediction information and higher prediction accuracy and had strong generalization ability and good stability.

Predicting the effects of organ motion on the dose delivered by dynamic intensity modulation

International Nuclear Information System (INIS)

Yu, C.X.; Jaffray, David; Martinez, A.A.; Wong, J.W.

1997-01-01

Purpose: Computer-optimized treatment plans, aimed to enhance tumor control and reduce normal tissue complication, generally require non-uniform beam intensities. One of the techniques for delivering intensity-modulated beams is the use of dynamic multileaf collimation, where the beam aperture and field shape change during irradiation. When intensity-modulated beams are delivered with dynamic collimation, intra-treatment organ motion may not only cause geometric misses at the field boundaries but also create hot and cold spots in the target. The mechanism for producing such effects has not been well understood. This study analyzes the dosimetric effects of intra-treatment organ motion on dynamic intensity modulation. A numerical method is developed for predicting the intensity distributions in a moving target before dose is delivered with dynamic intensity modulation. Material and Methods: In the numerical algorithm, the change in position and shape of the beam aperture with time were modeled as a three-dimensional 'tunnel', with the shape of the field aperture described in the x-y plane and its temporal position shown in the z-dimension. A point in the target had to be in the tunnel in order to receive irradiation and the dose to the point was proportional to the amount of time that this point stayed in the tunnel. Since each point in the target were analyzed separately, non-rigid body variations could easily be handled. The dependency of the dose variations on all parameters involved, including the speed of collimator motion, the frequency and amplitude of the target motion, and the size of the field segments, was analyzed. The algorithm was verified by irradiating moving phantoms with beams of dynamically modulated intensities. Predictions were also made for a treatment of a thoracic tumor using a dynamic wedge. The changes of target position with time were based on the MRI images of the chest region acquired using fast MRI scans in a cine fashion for a duration

Prediction of chronic critical illness in a general intensive care unit

Directory of Open Access Journals (Sweden)

Sérgio H. Loss

2013-06-01

Full Text Available OBJECTIVE: To assess the incidence, costs, and mortality associated with chronic critical illness (CCI, and to identify clinical predictors of CCI in a general intensive care unit. METHODS: This was a prospective observational cohort study. All patients receiving supportive treatment for over 20 days were considered chronically critically ill and eligible for the study. After applying the exclusion criteria, 453 patients were analyzed. RESULTS: There was an 11% incidence of CCI. Total length of hospital stay, costs, and mortality were significantly higher among patients with CCI. Mechanical ventilation, sepsis, Glasgow score < 15, inadequate calorie intake, and higher body mass index were independent predictors for cci in the multivariate logistic regression model. CONCLUSIONS: CCI affects a distinctive population in intensive care units with higher mortality, costs, and prolonged hospitalization. Factors identifiable at the time of admission or during the first week in the intensive care unit can be used to predict CCI.

Predicting intensity of white-tailed deer herbivory in the Central Appalachian Mountains

Science.gov (United States)

Kniowski, Andrew B.; Ford, W. Mark

2018-01-01

In eastern North America, white-tailed deer (Odocoileus virginianus) can have profound influences on forest biodiversity and forest successional processes. Moderate to high deer populations in the central Appalachians have resulted in lower forest biodiversity. Legacy effects in some areas persist even following deer population reductions or declines. This has prompted managers to consider deer population management goals in light of policies designed to support conservation of biodiversity and forest regeneration while continuing to support ample recreational hunting opportunities. However, despite known relationships between herbivory intensity and biodiversity impact, little information exists on the predictability of herbivory intensity across the varied and spatially diverse habitat conditions of the central Appalachians. We examined the predictability of browsing rates across central Appalachian landscapes at four environmental scales: vegetative community characteristics, physical environment, habitat configuration, and local human and deer population demographics. In an information-theoretic approach, we found that a model fitting the number of stems browsed relative to local vegetation characteristics received most (62%) of the overall support of all tested models assessing herbivory impact. Our data suggest that deer herbivory responded most predictably to differences in vegetation quantity and type. No other spatial factors or demographic factors consistently affected browsing intensity. Because herbivory, vegetation communities, and productivity vary spatially, we suggest that effective broad-scale herbivory impact assessment should include spatially-balanced vegetation monitoring that accounts for regional differences in deer forage preference. Effective monitoring is necessary to avoid biodiversity impacts and deleterious changes in vegetation community composition that are difficult to reverse and/or may not be detected using traditional deer

Expert Judgement Assessment & SCENT Ontological Analysis

Directory of Open Access Journals (Sweden)

NICHERSU Iulian

2018-05-01

Full Text Available This study aims to provide insights in the starting point of the Horizon 2020 ECfunded project SCENT (Smart Toolbox for Εngaging Citizens into a People-Centric Observation Web Citizen Observatory (CO in terms of existing infrastructure, existing monitoring systems and some discussion on the existing legal and administrative framework that relate to flood monitoring and management in the area of Danube Delta. The methodology used in this approach is based on expert judgement and ontological analysis, using the information collected from the identified end-users of the SCENT toolbox. In this type of analysis the stages of flood monitoring and management that the experts are involved in are detailed. This is done through an Expert Judgement Assessment analysis. The latter is complemented by a set of Key Performance Indicators that the stakeholders have assessed and/or proposed for the evaluation of the SCENT demonstrations, for the impact of the project and finally for SCENT toolbox performance and usefulness. The second part of the study presents an analysis that attempts to map the interactions between different organizations and components of the existing monitoring systems in the Danube Delta case study. Expert Judgement (EJ allows to gain information from specialists in a specific field through a consultation process with one or more experts that have experience in similar and complementary topics. Expert judgment, expert estimates, or expert opinion are all terms that refer to the contents of the problem; estimates, outcomes, predictions, uncertainties, and their corresponding assumptions and conditions are all examples of expert judgment. Expert Judgement is affected by the process used to gather it. On the other hand, the ontological analysis comes to complete this study, by organizing and presenting the connections behind the flood management and land use systems in the three phases of the flood event.

Computer-assisted expert case definition in electronic health records.

Science.gov (United States)

Walker, Alexander M; Zhou, Xiaofeng; Ananthakrishnan, Ashwin N; Weiss, Lisa S; Shen, Rongjun; Sobel, Rachel E; Bate, Andrew; Reynolds, Robert F

2016-02-01

To describe how computer-assisted presentation of case data can lead experts to infer machine-implementable rules for case definition in electronic health records. As an illustration the technique has been applied to obtain a definition of acute liver dysfunction (ALD) in persons with inflammatory bowel disease (IBD). The technique consists of repeatedly sampling new batches of case candidates from an enriched pool of persons meeting presumed minimal inclusion criteria, classifying the candidates by a machine-implementable candidate rule and by a human expert, and then updating the rule so that it captures new distinctions introduced by the expert. Iteration continues until an update results in an acceptably small number of changes to form a final case definition. The technique was applied to structured data and terms derived by natural language processing from text records in 29,336 adults with IBD. Over three rounds the technique led to rules with increasing predictive value, as the experts identified exceptions, and increasing sensitivity, as the experts identified missing inclusion criteria. In the final rule inclusion and exclusion terms were often keyed to an ALD onset date. When compared against clinical review in an independent test round, the derived final case definition had a sensitivity of 92% and a positive predictive value of 79%. An iterative technique of machine-supported expert review can yield a case definition that accommodates available data, incorporates pre-existing medical knowledge, is transparent and is open to continuous improvement. The expert updates to rules may be informative in themselves. In this limited setting, the final case definition for ALD performed better than previous, published attempts using expert definitions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

[Main principles of rapid diagnosis and intensive care in emergency states: their realization in expert systems].

Science.gov (United States)

Zislin, B D; Bazhenov, A M; Belkin, A A; Bazylev, S V; Badaev, F I; Trifonov, Iu O

1997-01-01

A retrospective analysis of 543 case histories over 1980-1990 in the town of Yekaterinburg and analysis of published data permitted the authors to single out the signs characterizing the most frequent syndromes requiring urgent intensive care. By either diagnostic value, these signs are distributed into main, accessory, and ruling out. An expert system has been created, making use of the productive-Freimont's approach to representing information on the basis of blurred multiplicities and ambiguous logics. The diagnosis was made by stages: first the main signs were analyzed, determining the severity of patient's status, then (after first aid was rendered) accessory and ruling out signs, which help make the diagnosis more precise. The system was tried in 231 patients, 102 of these with acute respiratory failure, 63 with acute hemodynamic insufficiency, and 66 with acute cerebral insufficiency. Primary diagnosis of the underlying syndrome was correct in 87-89% of cases, of the concomitant syndrome in 92-97%. Repeated evaluations (in 1-3 and 24 h) taking account of the time course of the symptoms and of the results of unsophisticated instrumental examinations increased the share of correct diagnoses to 92-96%.

On the performance of social network and likelihood-based expert weighting schemes

International Nuclear Information System (INIS)

Cooke, Roger M.; ElSaadany, Susie; Huang Xinzheng

2008-01-01

Using expert judgment data from the TU Delft's expert judgment database, we compare the performance of different weighting schemes, namely equal weighting, performance-based weighting from the classical model [Cooke RM. Experts in uncertainty. Oxford: Oxford University Press; 1991.], social network (SN) weighting and likelihood weighting. The picture that emerges with regard to SN weights is rather mixed. SN theory does not provide an alternative to performance-based combination of expert judgments, since the statistical accuracy of the SN decision maker is sometimes unacceptably low. On the other hand, it does outperform equal weighting in the majority of cases. The results here, though not overwhelmingly positive, do nonetheless motivate further research into social interaction methods for nominating and weighting experts. Indeed, a full expert judgment study with performance measurement requires an investment in time and effort, with a view to securing external validation. If high confidence in a comparable level of validation can be obtained by less intensive methods, this would be very welcome, and would facilitate the application of structured expert judgment in situations where the resources for a full study are not available. Likelihood weights are just as resource intensive as performance-based weights, and the evidence presented here suggests that they are inferior to performance-based weights with regard to those scoring variables which are optimized in performance weights (calibration and information). Perhaps surprisingly, they are also inferior with regard to likelihood. Their use is further discouraged by the fact that they constitute a strongly improper scoring rule

From expert witness to defendant: abolition of expert witness protection and its implications.

Science.gov (United States)

Mendelson, Danuta

2012-12-01

In Jones v Kaney [2011] 2 AC 398, the United Kingdom Supreme Court held that in England and Wales (but not in Scotland), clients can sue expert witnesses in negligence and/or contract for work performed under their retainer, whether in civil or criminal trials. The duties of expert witnesses in England are regulated by the Civil Procedure Rules and Protocols; the former also regulate the conduct of cases involving expert opinions. The legal context that led to the litigation is examined in the light of these rules, in particular, the nature of the allegations against Dr Kaney, a psychologist retained to provide psychiatric opinion. Jones v Kaney, as a decision of the United Kingdom Supreme Court, is not a binding precedent in Australia. However, unlike statutory enactments, common law judgments are retrospective in their operation, which means that health care practitioners who follow a generally accepted practice today may still be sued for damages by their patients or clients in the future. By definition, the future, including the refusal by the Australian High Court to follow Kaney's abolition of expert witnesses' immunity from suit for breach of duty to their clients, cannot be predicted with certainty. Consequently, health care practitioners in Australia and other countries should be aware of the case, its jurisprudential and practical ramifications.

Prediction of SEP Peak Proton Intensity Based on CME Speed, Direction and Observations of Associated Solar Phenomena

Science.gov (United States)

Richardson, I. G.; Mays, M. L.; Thompson, B. J.; Kwon, R.; Frechette, B. P.

2017-12-01

We assess whether a formula obtained by Richardson et al. (Solar Phys., 289, 3059, 2014; DOI 10.1007/s11207-014-0524-8) relating the intensity of 14-24 MeV protons in a solar energetic particle event at 1 AU to the solar event location and the speed of the associated coronal mass ejection (CME), may be used to "predict" the intensity of a solar energetic particle event. Starting with a subset of several hundred CMEs in the CCMC/SWRC DONKI real-time database (http://kauai.ccmc.gsfc.nasa.gov/DONKI/) selected without consideration of whether they were associated with SEP events, we first use the CME speed and direction to predict the proton intensity at Earth or the STEREO spacecraft using this formula. Since most of these CMEs were not in fact associated with SEP events, many "false alarms" result. We then examine whether considering other phenomena which may accompany the CMEs, such as the X-ray flare intensity and the properties of type II and type III radio emissions, may help to reduce the false alarm rate. We also use CME parameters calculated from an ellipsoidal shell fit to multi-spacecraft CME shock observations for a smaller number of events to predict the SEP intensity. We calculate skill scores for each case and assess whether the Richardson et al. (2014) formula, using additional observations to reduce the false alarm rate, has any potential as a SEP prediction tool, assuming that the required observations could be acquired sufficiently rapidly following the onset of the related solar event/CME.

A computerized expert system for mammography

International Nuclear Information System (INIS)

Jackson, V.P.; Dines, K.A.; Bassett, L.W.

1988-01-01

The authors have developed a computer-based expert system to aid in the interpretation of mammograms, breast sonograms, and clinical findings. The radiologist enters clinical and image data into the artificial intelligence system and receives a prediction of the etiology of lesions seen on breast imaging studies. This prototype interactive system has undergone preliminary clinical testing and evaluation. Ultimately, a more refined and complex system will be of value in mammography education, for general radiologists without ready access to mammography experts, for paramedical personnel, and for all mammographers in need of a breast imaging database and reporting systems

Price competition between an expert and a non-expert

OpenAIRE

Bouckaert, J.M.C.; Degryse, H.A.

1998-01-01

This paper characterizes price competition between an expert and a non-expert. In contrast with the expert, the non-expert’s repair technology is not always successful. Consumers visit the expert after experiencing an unsuccessful match at the non-expert. This re-entry affects the behaviour of both sellers. For low enough probability of successful repair at the non-expert, all consumers first visit the non-expert, and a ‘timid-pricing’ equilibrium results. If the non-expert’s repair technolog...

An expert system for spare parts inventory control

International Nuclear Information System (INIS)

Kim, K.Y.; Chen, P.Y.C.; Okrent, D.

1987-01-01

This paper describes an expert system which can handle spare part requirements not only in corrective maintenance (CM) or preventive maintenance (PM), but also when failure rates of components or parts are updated by new data or by predictive maintenance (PDM), and which can also decide optimum stocking level of each spare part. This expert system provides a maintenance (or inventory) manager with an improved basis for decision making in the maintenance related to spare parts. The definitions of PM and PDM from NUREG-1212 (USNRC 1986) are used herein. This expert system used Intellignece/Compiler (Intelligence Ware, 1986) as a language/tool in the IBM-PC

Expert Game experiment predicts emergence of trust in professional communication networks.

Science.gov (United States)

Bendtsen, Kristian Moss; Uekermann, Florian; Haerter, Jan O

2016-10-25

Strong social capital is increasingly recognized as an organizational advantage. Better knowledge sharing and reduced transaction costs increase work efficiency. To mimic the formation of the associated communication network, we propose the Expert Game, where each individual must find a specific expert and receive her help. Participants act in an impersonal environment and under time constraints that provide short-term incentives for noncooperative behavior. Despite these constraints, we observe cooperation between individuals and the self-organization of a sustained trust network, which facilitates efficient communication channels with increased information flow. We build a behavioral model that explains the experimental dynamics. Analysis of the model reveals an exploitation protection mechanism and measurable social capital, which quantitatively describe the economic utility of trust.

Consumer versus expert hazard identification

DEFF Research Database (Denmark)

Hagemann, Kit S.; Scholderer, Joachim

2007-01-01

Novel foods have been the object of intense public debate in recent years. Despite efforts to communicate the outcomes of risk assessments to consumers, public confidence in the management of potential risks has been low. Various reasons behind this have been identified, chiefly a disagreement...... between technical experts and consumers over the nature of the hazards on which risk assessments should focus, and perceptions of insufficient openness about uncertainties in risk assessment. Whilst previous research has almost exclusively focused on genetically modified foods, the present paper...

Complex data modeling and computationally intensive methods for estimation and prediction

CERN Document Server

Secchi, Piercesare; Advances in Complex Data Modeling and Computational Methods in Statistics

2015-01-01

The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held...

Development of a CME-associated geomagnetic storm intensity prediction tool

Science.gov (United States)

Wu, C. C.; DeHart, J. M.

2015-12-01

From 1995 to 2012, the Wind spacecraft recorded 168 magnetic cloud (MC) events. Among those events, 79 were found to have upstream shock waves and their source locations on the Sun were identified. Using a recipe of interplanetary magnetic field (IMF) Bz initial turning direction after shock (Wu et al., 1996, GRL), it is found that the north-south polarity of 66 (83.5%) out of the 79 events were accurately predicted. These events were tested and further analyzed, reaffirming that the Bz intial turning direction was accurate. The results also indicate that 37 of the 79 MCs originate from the north (of the Sun) averaged a Dst_min of -119 nT, whereas 42 of the MCs originating from the south (of the Sun) averaged -89 nT. In an effort to provide this research to others, a website was built that incorporated various tools and pictures to predict the intensity of the geomagnetic storms. The tool is capable of predicting geomagnetic storms with different ranges of Dst_min (from no-storm to gigantic storms). This work was supported by Naval Research Lab HBCU/MI Internship program and Chief of Naval Research.

NESSUS/EXPERT - An expert system for probabilistic structural analysis methods

Science.gov (United States)

Millwater, H.; Palmer, K.; Fink, P.

1988-01-01

An expert system (NESSUS/EXPERT) is presented which provides assistance in using probabilistic structural analysis methods. NESSUS/EXPERT is an interactive menu-driven expert system that provides information to assist in the use of the probabilistic finite element code NESSUS/FEM and the fast probability integrator. NESSUS/EXPERT was developed with a combination of FORTRAN and CLIPS, a C language expert system tool, to exploit the strengths of each language.

Hybrid expert system implementation to determine core reload patterns

International Nuclear Information System (INIS)

Greek, K.J.; Robinson, A.H.

1989-01-01

Determining reactor reload fuel patterns is a computationally intensive problem solving process for which automation can be of significant benefit. Often much effort is expended in the search for an optimal loading. While any modern programming language could be used to automate solution, the specialized tools of artificial intelligence (AI) are the most efficient means of introducing the fuel management expert's knowledge into the search for an optimum reload pattern. Prior research in pressurized water reactor refueling strategies developed FORTRAN programs that automated an expert's basic knowledge to direct a search for an acceptable minimum peak power loading. The dissatisfaction with maintenance of compiled knowledge in FORTRAN programs has served as the motivation for the development of the SHUFFLE expert system. SHUFFLE is written in Smalltalk, an object-oriented programming language, and evaluates loadings as it generates them using a two-group, two-dimensional nodal power calculation compiled in a personal computer-based FORTRAN. This paper reviews the object-oriented representation developed to solve the core reload problem with an expert system tool and its operating prototype, SHUFFLE

Information encryption in the expert management of strategic uncertainty

OpenAIRE

Frey, Seth; Williams, Paul L.; Albino, Dominic K.

2016-01-01

Strategic agents in incomplete-information environments have a conflicted relationship with uncertainty: it can keep them unpredictable to their opponents, but it must also be overcome to predict the actions of those opponents. We use a multivariate generalization of information theory to characterize the information processing behavior of strategic reasoning experts. We compare expert and novice poker players --- "sharks" and "fish" --- over 1.75 million hands of online two-player No-Limit T...

Tools and technologies for expert systems: A human factors perspective

Science.gov (United States)

Rajaram, Navaratna S.

1987-01-01

It is widely recognized that technologies based on artificial intelligence (AI), especially expert systems, can make significant contributions to the productivity and effectiveness of operations of information and knowledge intensive organizations such as NASA. At the same time, these being relatively new technologies, there is the problem of transfering technology to key personnel of such organizations. The problems of examining the potential of expert systems and of technology transfer is addressed in the context of human factors applications. One of the topics of interest was the investigation of the potential use of expert system building tools, particularly NEXPERT as a technology transfer medium. Two basic conclusions were reached in this regard. First, NEXPERT is an excellent tool for rapid prototyping of experimental expert systems, but not ideal as a delivery vehicle. Therefore, it is not a substitute for general purpose system implementation languages such a LISP or C. This assertion probably holds for nearly all such tools on the market today. Second, an effective technology transfer mechanism is to formulate and implement expert systems for problems which members of the organization in question can relate to. For this purpose, the LIghting EnGineering Expert (LIEGE) was implemented using NEXPERT as the tool for technology transfer and to illustrate the value of expert systems to the activities of the Man-System Division.

Expert systems

International Nuclear Information System (INIS)

Haldy, P.A.

1988-01-01

The definitions of the terms 'artificial intelligence' and 'expert systems', the methodology, areas of employment and limits of expert systems are discussed. The operation of an expert system is described, especially the presentation and organization of knowledge as well as interference and control. Methods and tools for expert system development are presented and their application in nuclear energy are briefly addressed. 7 figs., 2 tabs., 6 refs

Expert System Diagnosis of Cataract Eyes Using Fuzzy Mamdani Method

Science.gov (United States)

Santosa, I.; Romla, L.; Herawati, S.

2018-01-01

Cataracts are eye diseases characterized by cloudy or opacity of the lens of the eye by changing the colour of black into grey-white which slowly continues to grow and develop without feeling pain and pain that can cause blindness in human vision. Therefore, researchers make an expert system of cataract eye disease diagnosis by using Fuzzy Mamdani and how to care. The fuzzy method can convert the crisp value to linguistic value by fuzzification and includes in the rule. So this system produces an application program that can help the public in knowing cataract eye disease and how to care based on the symptoms suffered. From the results of the design implementation and testing of expert system applications to diagnose eye disease cataracts, it can be concluded that from a trial of 50 cases of data, obtained test results accuracy between system predictions with expert predictions obtained a value of 78% truth.

Intensive Intervention Practice Guide: School-Based Functional Analysis

Science.gov (United States)

Pennington, Brittany; Pokorski, Elizabeth A.; Kumm, Skip; Sterrett, Brittany I.

2017-01-01

The National Center for Leadership in Intensive Intervention (NCLII), a consortium funded by the Office of Special Education Programs (OSEP), prepares special education leaders to become experts in research on intensive intervention for students with disabilities who have persistent and severe academic (e.g., reading and math) and behavioral…

A Comparative Study of Spectral Auroral Intensity Predictions From Multiple Electron Transport Models

Science.gov (United States)

Grubbs, Guy; Michell, Robert; Samara, Marilia; Hampton, Donald; Hecht, James; Solomon, Stanley; Jahn, Jorg-Micha

2018-01-01

It is important to routinely examine and update models used to predict auroral emissions resulting from precipitating electrons in Earth's magnetotail. These models are commonly used to invert spectral auroral ground-based images to infer characteristics about incident electron populations when in situ measurements are unavailable. In this work, we examine and compare auroral emission intensities predicted by three commonly used electron transport models using varying electron population characteristics. We then compare model predictions to same-volume in situ electron measurements and ground-based imaging to qualitatively examine modeling prediction error. Initial comparisons showed differences in predictions by the GLobal airglOW (GLOW) model and the other transport models examined. Chemical reaction rates and radiative rates in GLOW were updated using recent publications, and predictions showed better agreement with the other models and the same-volume data, stressing that these rates are important to consider when modeling auroral processes. Predictions by each model exhibit similar behavior for varying atmospheric constants, energies, and energy fluxes. Same-volume electron data and images are highly correlated with predictions by each model, showing that these models can be used to accurately derive electron characteristics and ionospheric parameters based solely on multispectral optical imaging data.

An Accurate and Impartial Expert Assignment Method for Scientific Project Review

Directory of Open Access Journals (Sweden)

Mingliang Yue

2017-12-01

Full Text Available Purpose: This paper proposes an expert assignment method for scientific project review that considers both accuracy and impartiality. As impartial and accurate peer review is extremely important to ensure the quality and feasibility of scientific projects, enhanced methods for managing the process are needed. Design/methodology/approach: To ensure both accuracy and impartiality, we design four criteria, the reviewers’ fitness degree, research intensity, academic association, and potential conflict of interest, to express the characteristics of an appropriate peer review expert. We first formalize the expert assignment problem as an optimization problem based on the designed criteria, and then propose a randomized algorithm to solve the expert assignment problem of identifying reviewer adequacy. Findings: Simulation results show that the proposed method is quite accurate and impartial during expert assignment. Research limitations: Although the criteria used in this paper can properly show the characteristics of a good and appropriate peer review expert, more criteria/conditions can be included in the proposed scheme to further enhance accuracy and impartiality of the expert assignment. Practical implications: The proposed method can help project funding agencies (e.g. the National Natural Science Foundation of China find better experts for project peer review. Originality/value: To the authors’ knowledge, this is the first publication that proposes an algorithm that applies an impartial approach to the project review expert assignment process. The simulation results show the effectiveness of the proposed method.

Expert Systems

OpenAIRE

Lucas, P.J.F.

2005-01-01

Expert systems mimic the problem-solving activity of human experts in specialized domains by capturing and representing expert knowledge. Expert systems include a knowledge base, an inference engine that derives conclusions from the knowledge, and a user interface. Knowledge may be stored as if-then rules, orusing other formalisms such as frames and predicate logic. Uncertain knowledge may be represented using certainty factors, Bayesian networks, Dempster-Shafer belief functions, or fuzzy se...

Neural network-based expert system for severe accident management

International Nuclear Information System (INIS)

Klopp, G.T.; Silverman, E.B.

1992-01-01

This paper presents the results of the second phase of a three-phase Severe Accident Management expert system program underway at Commonwealth Edison Company (CECo). Phase I successfully demonstrated the feasibility of Artificial Neural Networks to support several of the objectives of severe accident management. Simulated accident scenarios were generated by the Modular Accident Analysis Program (MAAP) code currently in use by CECo as part of their Individual Plant Evaluations (IPE)/Accident Management Program. The primary objectives of the second phase were to develop and demonstrate four capabilities of neural networks with respect to nuclear power plant severe accident monitoring and prediction. The results of this work would form the foundation of a demonstration system which included expert system performance features. These capabilities included the ability to: (1) Predict the time available prior to support plate (and reactor vessel) failure; (2) Calculate the time remaining until recovery actions were too late to prevent core damage; (3) Predict future parameter values of each of the MAAP parameter variables; and (4) Detect simulated sensor failure and provide best-value estimates for further processing in the presence of a sensor failure. A variety of accident scenarios for the Zion and Dresden plants were used to train and test the neural network expert system. These included large and small break LOCAs as well as a range of transient events. 3 refs., 1 fig., 1 tab

Climate Prediction Center - Expert Assessments Index

Science.gov (United States)

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > Monitoring and Data > Global Climate Data & Maps > ; Global Regional Climate Maps Regional Climate Maps Banner The Monthly regional analyses products are

Predictability of bone density at posterior mandibular implant sites using cone-beam computed tomography intensity values

OpenAIRE

Alkhader, Mustafa; Hudieb, Malik; Khader, Yousef

2017-01-01

Objective: The aim of this study was to investigate the predictability of bone density at posterior mandibular implant sites using cone-beam computed tomography (CBCT) intensity values. Materials and Methods: CBCT cross-sectional images for 436 posterior mandibular implant sites were selected for the study. Using Invivo software (Anatomage, San Jose, California, USA), two observers classified the bone density into three categories: low, intermediate, and high, and CBCT intensity values were g...

A deep learning approach for predicting the quality of online health expert question-answering services.

Science.gov (United States)

Hu, Ze; Zhang, Zhan; Yang, Haiqin; Chen, Qing; Zuo, Decheng

2017-07-01

Recently, online health expert question-answering (HQA) services (systems) have attracted more and more health consumers to ask health-related questions everywhere at any time due to the convenience and effectiveness. However, the quality of answers in existing HQA systems varies in different situations. It is significant to provide effective tools to automatically determine the quality of the answers. Two main characteristics in HQA systems raise the difficulties of classification: (1) physicians' answers in an HQA system are usually written in short text, which yields the data sparsity issue; (2) HQA systems apply the quality control mechanism, which refrains the wisdom of crowd. The important information, such as the best answer and the number of users' votes, is missing. To tackle these issues, we prepare the first HQA research data set labeled by three medical experts in 90days and formulate the problem of predicting the quality of answers in the system as a classification task. We not only incorporate the standard textual feature of answers, but also introduce a set of unique non-textual features, i.e., the popular used surface linguistic features and the novel social features, from other modalities. A multimodal deep belief network (DBN)-based learning framework is then proposed to learn the high-level hidden semantic representations of answers from both textual features and non-textual features while the learned joint representation is fed into popular classifiers to determine the quality of answers. Finally, we conduct extensive experiments to demonstrate the effectiveness of including the non-textual features and the proposed multimodal deep learning framework. Copyright © 2017 Elsevier Inc. All rights reserved.

Expert systems applied to two problems in nuclear power plants

International Nuclear Information System (INIS)

Kim, K.Y.

1988-01-01

This dissertation describes two prototype expert systems applied to two problems in nuclear power plants. One problem is spare parts inventory control, and the other one is radionuclide release from containment during severe accident. The expert system for spare parts inventory control can handle spare parts requirements not only in corrective, preventive, or predictive maintenance, but also when failure rates of components or parts are updated by new data. Costs and benefits of spare parts inventory acquisition are evaluated with qualitative attributes such as spare part availability to provide the inventory manager with an improved basis for decision making. The expert system is implemented with Intelligence/Compiler on an IBM-AT. The other expert system for radionuclide release from containment can estimate magnitude, type, location, and time of release of radioactive materials from containment during a severe accident nearly on line, based on the actual measured physical parameters such as temperature and pressure inside the containment. The expert system has a function to check the validation of sensor data. The expert system is implemented with KEE on a Symbolics LISP machine

Expert - Non-expert differences in visual behaviour during alpine slalom skiing.

Science.gov (United States)

Decroix, Marjolein; Wazir, Mohd Rozilee Wazir Norjali; Zeuwts, Linus; Deconinck, Frederik F J A; Lenoir, Matthieu; Vansteenkiste, Pieter

2017-10-01

The aim of this study was to investigate visual behaviour of expert and non-expert ski athletes during an alpine slalom. Fourteen non-experts and five expert slalom skiers completed an alpine slalom course in an indoor ski slope while wearing a head-mounted eye tracking device. Experts completed the slalom clearly faster than non-experts, but no significant difference was found in timing and position of the turn initiation. Although both groups already looked at future obstacles approximately 0,5s before passing the upcoming pole, the higher speed of experts implied that they shifted gaze spatially earlier in the bend than non-experts. Furthermore, experts focussed more on the second next pole while non-expert slalom skiers looked more to the snow surface immediately in front of their body. No difference was found in the fixation frequency, average fixation duration, and quiet eye duration between both groups. These results suggest that experts focus on the timing of their actions while non-experts still need to pay attention to the execution of these actions. These results also might suggest that ski trainers should instruct non-experts and experts to focus on the next pole and, shift their gaze to the second next pole shortly before reaching it. Based on the current study it seems unadvisable to instruct slalom skiers to look several poles ahead during the actual slalom. However, future research should test if these results still hold on a real outdoor slope, including multiple vertical gates. Copyright © 2017 Elsevier B.V. All rights reserved.

Adaptation and validation of the REGEN expert system for the Central Appalachians

Science.gov (United States)

Lance A. Vickers; Thomas R. Fox; David L. Loftis; David A. Boucugnani

2011-01-01

REGEN is an expert system that predicts future species composition at the onset of stem exclusion using preharvest stand conditions. To extend coverage into hardwood stands of the Central Appalachians, we developed REGEN knowledge bases for four site qualities (xeric, subxeric, submesic, mesic) based on relevant literature and expert opinion. Data were collected from...

Network approaches for expert decisions in sports.

Science.gov (United States)

Glöckner, Andreas; Heinen, Thomas; Johnson, Joseph G; Raab, Markus

2012-04-01

This paper focuses on a model comparison to explain choices based on gaze behavior via simulation procedures. We tested two classes of models, a parallel constraint satisfaction (PCS) artificial neuronal network model and an accumulator model in a handball decision-making task from a lab experiment. Both models predict action in an option-generation task in which options can be chosen from the perspective of a playmaker in handball (i.e., passing to another player or shooting at the goal). Model simulations are based on a dataset of generated options together with gaze behavior measurements from 74 expert handball players for 22 pieces of video footage. We implemented both classes of models as deterministic vs. probabilistic models including and excluding fitted parameters. Results indicated that both classes of models can fit and predict participants' initially generated options based on gaze behavior data, and that overall, the classes of models performed about equally well. Early fixations were thereby particularly predictive for choices. We conclude that the analyses of complex environments via network approaches can be successfully applied to the field of experts' decision making in sports and provide perspectives for further theoretical developments. Copyright © 2011 Elsevier B.V. All rights reserved.

Geospatial Analytics in Retail Site Selection and Sales Prediction.

Science.gov (United States)

Ting, Choo-Yee; Ho, Chiung Ching; Yee, Hui Jia; Matsah, Wan Razali

2018-03-01

Studies have shown that certain features from geography, demography, trade area, and environment can play a vital role in retail site selection, largely due to the impact they asserted on retail performance. Although the relevant features could be elicited by domain experts, determining the optimal feature set can be intractable and labor-intensive exercise. The challenges center around (1) how to determine features that are important to a particular retail business and (2) how to estimate retail sales performance given a new location? The challenges become apparent when the features vary across time. In this light, this study proposed a nonintervening approach by employing feature selection algorithms and subsequently sales prediction through similarity-based methods. The results of prediction were validated by domain experts. In this study, data sets from different sources were transformed and aggregated before an analytics data set that is ready for analysis purpose could be obtained. The data sets included data about feature location, population count, property type, education status, and monthly sales from 96 branches of a telecommunication company in Malaysia. The finding suggested that (1) optimal retail performance can only be achieved through fulfillment of specific location features together with the surrounding trade area characteristics and (2) similarity-based method can provide solution to retail sales prediction.

Bitterness intensity prediction of berberine hydrochloride using an electronic tongue and a GA-BP neural network.

Science.gov (United States)

Liu, Ruixin; Zhang, Xiaodong; Zhang, Lu; Gao, Xiaojie; Li, Huiling; Shi, Junhan; Li, Xuelin

2014-06-01

The aim of this study was to predict the bitterness intensity of a drug using an electronic tongue (e-tongue). The model drug of berberine hydrochloride was used to establish a bitterness prediction model (BPM), based on the taste evaluation of bitterness intensity by a taste panel, the data provided by the e-tongue and a genetic algorithm-back-propagation neural network (GA-BP) modeling method. The modeling characteristics of the GA-BP were compared with those of multiple linear regression, partial least square regression and BP methods. The determination coefficient of the BPM was 0.99965±0.00004, the root mean square error of cross-validation was 0.1398±0.0488 and the correlation coefficient of the cross-validation between the true and predicted values was 0.9959±0.0027. The model is superior to the other three models based on these indicators. In conclusion, the model established in this study has a high fitting degree and may be used for the bitterness prediction modeling of berberine hydrochloride of different concentrations. The model also provides a reference for the generation of BPMs of other drugs. Additionally, the algorithm of the study is able to conduct a rapid and accurate quantitative analysis of the data provided by the e-tongue.

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

Science.gov (United States)

Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

1988-01-01

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

Does exercise motivation predict engagement in objectively assessed bouts of moderate-intensity exercise? A self-determination theory perspective.

Science.gov (United States)

Standage, Martyn; Sebire, Simon J; Loney, Tom

2008-08-01

This study examined the utility of motivation as advanced by self-determination theory (Deci & Ryan, 2000) in predicting objectively assessed bouts of moderate intensity exercise behavior. Participants provided data pertaining to their exercise motivation. One week later, participants wore a combined accelerometer and heart rate monitor (Actiheart; Cambridge Neurotechnology Ltd) and 24-hr energy expenditure was estimated for 7 days. After controlling for gender and a combined marker of BMI and waist circumference, results showed autonomous motivation to positively predict moderate-intensity exercise bouts of >or=10 min, or=20 min, and an accumulation needed to meet public health recommendations for moderate intensity activity (i.e., ACSM/AHA guidelines). The present findings add bouts of objectively assessed exercise behavior to the growing body of literature that documents the adaptive consequences of engaging in exercise for autonomous reasons. Implications for practice and future work are discussed.

Expert systems for structure elucidation of organic molecules by spectral methods

International Nuclear Information System (INIS)

Elyashberg, Mikhail E

1999-01-01

The state-of-the-art of the investigations aimed at creating expert systems for establishing the structure of organic molecules from IR, 1 H and 13 C NMR spectra is analysed. Computer methods used for identification of molecular fragments, generation of their structure and spectra prediction are considered. Principles of the creation of modern expert systems and general strategy of solving structural problems are discussed. The bibliography includes 174 references.

Macroseismic intensity attenuation in Iran

Science.gov (United States)

Yaghmaei-Sabegh, Saman

2018-01-01

Macroseismic intensity data plays an important role in the process of seismic hazard analysis as well in developing of reliable earthquake loss models. This paper presents a physical-based model to predict macroseismic intensity attenuation based on 560 intensity data obtained in Iran in the time period 1975-2013. The geometric spreading and energy absorption of seismic waves have been considered in the proposed model. The proposed easy to implement relation describes the intensity simply as a function of moment magnitude, source to site distance and focal depth. The prediction capability of the proposed model is assessed by means of residuals analysis. Prediction results have been compared with those of other intensity prediction models for Italy, Turkey, Iran and central Asia. The results indicate the higher attenuation rate for the study area in distances less than 70km.

The Role of Parental Perceptions of Tic Frequency and Intensity in Predicting Tic-Related Functional Impairment in Youth with Chronic Tic Disorders

Science.gov (United States)

Espil, Flint M.; Capriotti, Matthew R.; Conelea, Christine A.; Woods, Douglas W.

2014-01-01

Tic severity is composed of several dimensions. Tic frequency and intensity are two such dimensions, but little empirical data exist regarding their relative contributions to functional impairment in those with Chronic Tic Disorders (CTD). The present study examined the relative contributions of these dimensions in predicting tic-related impairment across several psychosocial domains. Using data collected from parents of youth with CTD, multivariate regression analyses revealed that both tic frequency and intensity predicted tic-related impairment in several areas; including family and peer relationships, school interference, and social endeavors, even when controlling for the presence of comorbid anxiety symptoms and Attention Deficit Hyperactivity Disorder diagnostic status. Results showed that tic intensity predicted more variance across more domains than tic frequency. PMID:24395287

The role of parental perceptions of tic frequency and intensity in predicting tic-related functional impairment in youth with chronic tic disorders.

Science.gov (United States)

Espil, Flint M; Capriotti, Matthew R; Conelea, Christine A; Woods, Douglas W

2014-12-01

Tic severity is composed of several dimensions. Tic frequency and intensity are two such dimensions, but little empirical data exist regarding their relative contributions to functional impairment in those with chronic tic disorders (CTD). The present study examined the relative contributions of these dimensions in predicting tic-related impairment across several psychosocial domains. Using data collected from parents of youth with CTD, multivariate regression analyses revealed that both tic frequency and intensity predicted tic-related impairment in several areas; including family and peer relationships, school interference, and social endeavors, even when controlling for the presence of comorbid anxiety symptoms and Attention Deficit Hyperactivity Disorder diagnostic status. Results showed that tic intensity predicted more variance across more domains than tic frequency.

Expert ease

Energy Technology Data Exchange (ETDEWEB)

1984-04-01

Expert-ease allows the most inexperienced of computer users to build an expert system in a matter of hours. It is nothing more or less than a computer based problem-solving system. It allows the expert to preserve his or her knowledge in the form of rules, which can be applied to problems put to the system by the non-expert. The crucial piece of software at the heart of Expert-Ease extracts rules from data, and is called the analogue concept learning system. It was developed by Intelligent Terminals Ltd. and supplied to Export Software International to be incorporated into a commercially attractive package for business users. The resulting product runs on the Act Sirius and the IBM PC and compatibles. It is a well conceived and polished product with a popular appeal that should ensure widespread acceptance even at a cost of >1500 plus vat.

Expert System

DEFF Research Database (Denmark)

Hildebrandt, Thomas Troels; Cattani, Gian Luca

2016-01-01

An expert system is a computer system for inferring knowledge from a knowledge base, typically by using a set of inference rules. When the concept of expert systems was introduced at Stanford University in the early 1970s, the knowledge base was an unstructured set of facts. Today the knowledge b...... for the application of expert systems, but also raises issues regarding privacy and legal liability....

Component aging evaluation with expert systems

International Nuclear Information System (INIS)

Wiesemann, J.S.; Maguire, H.T. Jr.

1988-01-01

The age degradation of components involves a complex relationship between a variety of variables. These relationships are typically modeled using probabilistic and deterministic analyses. These methods depend upon a formal understanding of the underlying degradation mechanisms and a database of experience which allows statistical analyses to extract numerical trends. At present, not all age degradation mechanisms are adequately modeled and available data for age degradation is in most cases insufficient. In addition, these methods tend to focus upon answers to isolated questions (e.g., What is the component failure rate?) rather than the more pertinent questions concerning operations and maintenance (e.g., should the component be replaced at the next outage). Fortunately, knowledge in the form of personal experience does exist which allows plant personnel to make decisions concerning operations and maintenance. This knowledge can be modeled using expert systems. This paper discusses CAGES (Component Aging Expert System). It combines expert rules (heuristics), probabilistic models, and deterministic models to make evaluations of component aging; predict the implications for component life extension, operational readiness, maintenance effectiveness, and safety, and make recommendations for maintenance and operation

Expert system verification and validation for nuclear power industry applications

International Nuclear Information System (INIS)

Naser, J.A.

1990-01-01

The potential for the use of expert systems in the nuclear power industry is widely recognized. The benefits of such systems include consistency of reasoning during off-normal situations when humans are under great stress, the reduction of times required to perform certain functions, the prevention of equipment failures through predictive diagnostics, and the retention of human expertise in performing specialized functions. The increased use of expert systems brings with it concerns about their reliability. Difficulties arising from software problems can affect plant safety, reliability, and availability. A joint project between EPRI and the US Nuclear Regulatory Commission is being initiated to develop a methodology for verification and validation of expert systems for nuclear power applications. This methodology will be tested on existing and developing expert systems. This effort will explore the applicability of conventional verification and validation methodologies to expert systems. The major area of concern will be certification of the knowledge base. This is expected to require new types of verification and validation techniques. A methodology for developing validation scenarios will also be studied

Design of groundwater pollution expert system: forward chaining and interfacing

International Nuclear Information System (INIS)

Mongkon Ta-oun; Mohamed Daud; Mohd Zohadie Bardaie; Shamshuddin Jusop

2000-01-01

The groundwater pollution expert system (GWPES was developed by C Language Integrate Production System (CLEPS). The control techniques of this system consider some conclusion and then attempts to prove it by searching for supportive information from the database. The inference process goes in forward chaining of this system such as predicting groundwater pollution vulnerability, predicting the effect of nitrogen fertiliser, agricultural impact and project development on groundwater pollution potential. In GWPES, forward chaining system begins with a matching of inputs with the existing database of groundwater environment and activities impact of the project development. While, interaction between an expert system and user is conducted in simple English language. The interaction is highly interactive. A basis design with simple Graphic User Interface (GUI) to input data and by asking simple questions. (author)

Rational consensus under uncertainty: Expert judgment in the EC-USNRC uncertainty study

International Nuclear Information System (INIS)

Cooke, R.; Kraan, B.; Goossens, L.

1999-01-01

Governmental bodies are confronted with the problem of achieving rational consensus in the face of substantial uncertainties. The area of accident consequence management for nuclear power plants affords a good example. Decisions with regard to evacuation, decontamination, and food bans must be taken on the basis of predictions of environmental transport of radioactive material, contamination through the food chain, cancer induction, and the like. These predictions use mathematical models containing scores of uncertain parameters. Decision makers want to take, and want to be perceived to take, these decisions in a rational manner. The question is, how can this be accomplished in the face of large uncertainties? Indeed, the very presence of uncertainty poses a threat to rational consensus. Decision makers will necessarily base their actions on the judgments of experts. The experts, however, will not agree among themselves, as otherwise we would not speak of large uncertainties. Any given expert's viewpoint will be favorable to the interests of some stakeholders, and hostile to the interests of others. If a decision maker bases his/her actions on the views of one single expert, then (s)he is invariably open to charges of partiality toward the interests favored by this viewpoint. An appeal to 'impartial' or 'disinterested' experts will fail for two reasons. First, experts have interests; they have jobs, mortgages and professional reputations. Second, even if expert interests could somehow be quarantined, even then the experts would disagree. Expert disagreement is not explained by diverging interests, and consensus cannot be reached by shielding the decision process from expert interests. If rational consensus requires expert agreement, then rational consensus is simply not possible in the face of uncertainty. If rational consensus under uncertainty is to be achieved, then evidently the views of a diverse set of experts must be taken into account. The question is how

Radiological social risk perception: something more than experts/ public discrepancies

International Nuclear Information System (INIS)

Prades Lopez, Ana; Gonzalez Reyes, Felisa

1998-01-01

One of the most important concerns of the postindustrial societies lies on the specification and quantification of risk, the Risk Assesment. However, the efforts and resources devoted to such goal have not avoided a growing worry about both the environmental conditions and the situations that potentially threaten it, generating an intense social debate about risks. In this framework, discrepancies between experts and public evaluations risks leaded to the study of social Risk perception. Several theoretical scopes have tried to characterize the phenomenon. A worthy conclusion of the empirical studies carried out on this issue is that all of them, experts and public, are influence by some factors which, in turns, affect their risk perception,. Specially striking is the fact that perception of risk among experts is also modulated by qualitative, personal and social factors. Social Risk Perception, through the process of Communication and Social Participation, has been configurated as a critical tool for both risk prevention and management

Fuzzy Expert System for Heart Attack Diagnosis

Science.gov (United States)

Hassan, Norlida; Arbaiy, Nureize; Shah, Noor Aziyan Ahmad; Afizah Afif@Afip, Zehan

2017-08-01

Heart attack is one of the serious illnesses and reported as the main killer disease. Early prevention is significant to reduce the risk of having the disease. The prevention efforts can be strengthen through awareness and education about risk factor and healthy lifestyle. Therefore the knowledge dissemination is needed to play role in order to distribute and educate public in health care management and disease prevention. Since the knowledge dissemination in medical is important, there is a need to develop a knowledge based system that can emulate human intelligence to assist decision making process. Thereby, this study utilized hybrid artificial intelligence (AI) techniques to develop a Fuzzy Expert System for Diagnosing Heart Attack Disease (HAD). This system integrates fuzzy logic with expert system, which helps the medical practitioner and people to predict the risk and as well as diagnosing heart attack based on given symptom. The development of HAD is expected not only providing expert knowledge but potentially become one of learning resources to help citizens to develop awareness about heart-healthy lifestyle.

EXPERT SYSTEMS

OpenAIRE

Georgiana Marin; Mihai Catalin Andrei

2011-01-01

In recent decades IT and computer systems have evolved rapidly in economic informatics field. The goal is to create user friendly information systems that respond promptly and accurately to requests. Informatics systems evolved into decision assisted systems, and such systems are converted, based on gained experience, in expert systems for creative problem solving that an organization is facing. Expert systems are aimed at rebuilding human reasoning on the expertise obtained from experts, sto...

An expert elicitation process to project the frequency and magnitude of Florida manatee mortality events caused by red tide (Karenia brevis)

Science.gov (United States)

Martin, Julien; Runge, Michael C.; Flewelling, Leanne J.; Deutsch, Charles J.; Landsberg, Jan H.

2017-11-20

the Southwest region was 0.35 (80-percent confidence interval [CI]: 0.21−0.52), whereas the forecast probability was 0.48 (80-percent CI: 0.30−0.64) over a 40-year projected time horizon. Moderate and intense RTMM events are expected to continue to be most frequent in the Southwest region, to increase in mean frequency in the Northwest region (historical frequency of moderate and intense RTMM events [combined] in the Northwest region was 0, whereas the forecast probability was 0.12 [80-percent CI: 0.02−0.39] over a 40-year projected time horizon) and in the Atlantic region (historical frequency of moderate and intense RTMM events [combined] in the Atlantic region was 0.05 [80-percent CI: 0.005–0.18], whereas the forecast probability was 0.11 [80-percent CI: 0.03−0.25] over a 40-year projected time horizon), and to remain absent from the Upper St. Johns River region. The impact of red-tide blooms on manatee mortality has been measured for the Southwest region but not for the Northwest and Atlantic regions, where such events have been rare. The expert panel predicted that the median magnitude of RTMM events in the Atlantic and Northwest regions will be much smaller than that in the Southwest; given the large uncertainties, however, they acknowledged the possibility that these events could be larger in their mortality impacts than in the Southwest region. By its nature, forecasting requires expert judgment because it is impossible to have empirical evidence about the future. The large uncertainties in parameter estimates over a 100-year timeframe are to be expected and may also indicate that the training provided to panelists successfully minimized one common pitfall of expert judgment, that of overconfidence. This study has provided useful and needed inputs to the Florida manatee population viability analysis associated with an important and recurrent source of mortality from harmful algal blooms.

Application of fuzzy expert system on LILW performance assessment

International Nuclear Information System (INIS)

Lemos, F.L. de; Sullivan, T.

2002-01-01

A complete LILW repository performance assessment requires the involvement between several experts in many fields of science. Many sources of uncertainties arise due to complexity of interaction of environmental parameters, lack of data and ignorance, this makes predictive analysis and interpretation difficult. This difficulty in understanding the impact of the ambiguities is even higher when it comes to public and decision makers involvement. Traditional methods of data analysis, while having strong mathematical basis, many times are not adequate to deal with ambiguous data. These ambiguities can be an obstacle to make the results easier to understand and defensible. A methodology of decision making, based on fuzzy logic, can help the interaction between experts, decision makers and the public. This method is the basis of an expert system which can help the analysis of very complex and ambiguous processes. (author)

Predicting dynamic range and intensity discrimination for electrical pulse-train stimuli using a stochastic auditory nerve model: the effects of stimulus noise.

Science.gov (United States)

Xu, Yifang; Collins, Leslie M

2005-06-01

This work investigates dynamic range and intensity discrimination for electrical pulse-train stimuli that are modulated by noise using a stochastic auditory nerve model. Based on a hypothesized monotonic relationship between loudness and the number of spikes elicited by a stimulus, theoretical prediction of the uncomfortable level has previously been determined by comparing spike counts to a fixed threshold, Nucl. However, no specific rule for determining Nucl has been suggested. Our work determines the uncomfortable level based on the excitation pattern of the neural response in a normal ear. The number of fibers corresponding to the portion of the basilar membrane driven by a stimulus at an uncomfortable level in a normal ear is related to Nucl at an uncomfortable level of the electrical stimulus. Intensity discrimination limens are predicted using signal detection theory via the probability mass function of the neural response and via experimental simulations. The results show that the uncomfortable level for pulse-train stimuli increases slightly as noise level increases. Combining this with our previous threshold predictions, we hypothesize that the dynamic range for noise-modulated pulse-train stimuli should increase with additive noise. However, since our predictions indicate that intensity discrimination under noise degrades, overall intensity coding performance may not improve significantly.

Artificial Intelligence and Expert Systems in Medicine and Their Ability to Prediction as Therapy Planning Systems by CADIAG-2 Algorithm

OpenAIRE

Mohammad Madadpour Inallou; Zeinab Ajurlou; Bahman Mehri

2012-01-01

Expert Systems in Medicine is a collection, storage, retrieval, communication and processing of medical data for the purposes of interpretation, inference, decision-support, research and so other purposes in medicine. Expert System is an interactive computer-based decision tool that uses both facts and heuristics to solve difficult decision problems based on knowledge acquired from an expert. Expert systems provide expert advice and guidance in a wide variety of activities, from computer diag...

Combining Lead Exposure Measurements and Experts' Judgment Through a Bayesian Framework.

Science.gov (United States)

Koh, Dong-Hee; Park, Ju-Hyun; Lee, Sang-Gil; Kim, Hwan-Cheol; Choi, Sangjun; Jung, Hyejung; Park, Dong-Uk

2017-11-10

CARcinogen EXposure (CAREX) is a carcinogen-surveillance system employed in many countries. To develop Korean CAREX, the intensity of exposure to lead, as an example, was estimated across industries. Airborne-lead measurement records were extracted from the work-environment measurement database (WEMD), which is a nationwide workplace-monitoring database. Lead measurements were log-transformed; then, the log-transformed geometric means (LGMs) and log-transformed geometric standard deviations (LGSDs) were calculated for each industry. However, the data of many industries was limited. To address this shortcoming, experts' judgments of the lead exposure levels across industries were elicited. Experts provided their estimates of lead exposure levels as the boundary of the 5th and 95th percentiles, and it is assumed that these estimates are based on the log-normal distributions of exposure levels. Estimates of LGM and LGSD were extracted from each expert's response and then combined to quantify the experts' prior distribution. Then, the experts' prior distributions for each industry were updated with the corresponding LGMs and LGSDs calculated from the WEMD data through a Bayesian framework, yielding posterior distributions of the LGM and LGSD. The WEMD contains 83035 airborne-lead measurements that were collected between 2002 and 2007. A total of 17 occupational-hygiene professionals with >20 years of experience provided lead exposure estimates. In industries where measurement data were abundant, the measurement data dominated the posterior exposure estimates. For example, for one industry, 'Manufacture of Accumulator, Primary Cells, and Primary Batteries,' 1152 lead measurements [with a geometric mean (GM) of 14.42 µg m-3 and a geometric standard deviation (GSD) of 3.31] were available and 15 experts' responses (with a GM of 7.06 µg m-3 and a GSD of 4.15) were collected, resulting in a posterior exposure estimate of 14.41µg m-3 as the GM with a GSD of 3.31. For

What defines an Expert? - Uncertainty in the interpretation of seismic data

Science.gov (United States)

Bond, C. E.

2008-12-01

Studies focusing on the elicitation of information from experts are concentrated primarily in economics and world markets, medical practice and expert witness testimonies. Expert elicitation theory has been applied in the natural sciences, most notably in the prediction of fluid flow in hydrological studies. In the geological sciences expert elicitation has been limited to theoretical analysis with studies focusing on the elicitation element, gaining expert opinion rather than necessarily understanding the basis behind the expert view. In these cases experts are defined in a traditional sense, based for example on: standing in the field, no. of years of experience, no. of peer reviewed publications, the experts position in a company hierarchy or academia. Here traditional indicators of expertise have been compared for significance on affective seismic interpretation. Polytomous regression analysis has been used to assess the relative significance of length and type of experience on the outcome of a seismic interpretation exercise. Following the initial analysis the techniques used by participants to interpret the seismic image were added as additional variables to the analysis. Specific technical skills and techniques were found to be more important for the affective geological interpretation of seismic data than the traditional indicators of expertise. The results of a seismic interpretation exercise, the techniques used to interpret the seismic and the participant's prior experience have been combined and analysed to answer the question - who is and what defines an expert?

Evaluation of the predictive indices for candidemia in an adult intensive care unit

Directory of Open Access Journals (Sweden)

Gilberto Gambero Gaspar

2015-02-01

Full Text Available INTRODUCTION: To evaluate predictive indices for candidemia in an adult intensive care unit (ICU and to propose a new index. METHODS: A prospective cohort study was conducted between January 2011 and December 2012. This study was performed in an ICU in a tertiary care hospital at a public university and included 114 patients staying in the adult ICU for at least 48 hours. The association of patient variables with candidemia was analyzed. RESULTS: There were 18 (15.8% proven cases of candidemia and 96 (84.2% cases without candidemia. Univariate analysis revealed the following risk factors: parenteral nutrition, severe sepsis, surgical procedure, dialysis, pancreatitis, acute renal failure, and an APACHE II score higher than 20. For the Candida score index, the odds ratio was 8.50 (95% CI, 2.57 to 28.09; the sensitivity, specificity, positive predictive value, and negative predictive value were 0.78, 0.71, 0.33, and 0.94, respectively. With respect to the clinical predictor index, the odds ratio was 9.45 (95%CI, 2.06 to 43.39; the sensitivity, specificity, positive predictive value, and negative predictive value were 0.89, 0.54, 0.27, and 0.96, respectively. The proposed candidemia index cutoff was 8.5; the sensitivity, specificity, positive predictive value, and negative predictive value were 0.77, 0.70, 0.33, and 0.94, respectively. CONCLUSIONS: The Candida score and clinical predictor index excluded candidemia satisfactorily. The effectiveness of the candidemia index was comparable to that of the Candida score.

Brain mechanisms of persuasion: how 'expert power' modulates memory and attitudes.

Science.gov (United States)

Klucharev, Vasily; Smidts, Ale; Fernández, Guillén

2008-12-01

Human behaviour is affected by various forms of persuasion. The general persuasive effect of high expertise of the communicator, often referred to as 'expert power', is well documented. We found that a single exposure to a combination of an expert and an object leads to a long-lasting positive effect on memory for and attitude towards the object. Using functional magnetic resonance imaging, we probed the neural processes predicting these behavioural effects. Expert context was associated with distributed left-lateralized brain activity in prefrontal and temporal cortices related to active semantic elaboration. Furthermore, experts enhanced subsequent memory effects in the medial temporal lobe (i.e. in hippocampus and parahippocampal gyrus) involved in memory formation. Experts also affected subsequent attitude effects in the caudate nucleus involved in trustful behaviour, reward processing and learning. These results may suggest that the persuasive effect of experts is mediated by modulation of caudate activity resulting in a re-evaluation of the object in terms of its perceived value. Results extend our view of the functional role of the dorsal striatum in social interaction and enable us to make the first steps toward a neuroscientific model of persuasion.

Topography and geology site effects from the intensity prediction model (ShakeMap) for Austria

Science.gov (United States)

del Puy Papí Isaba, María; Jia, Yan; Weginger, Stefan

2017-04-01

The seismicity in Austria can be categorized as moderated. Despite the fact that the hazard seems to be rather low, earthquakes can cause great damage and losses, specially in densely populated and industrialized areas. It is well known, that equations which predict intensity as a function of magnitude and distance, among other parameters, are useful tool for hazard and risk assessment. Therefore, this study aims to determine an empirical model of the ground shaking intensities (ShakeMap) of a series of earthquakes occurred in Austria between 1000 and 2014. Furthermore, the obtained empirical model will lead to further interpretation of both, contemporary and historical earthquakes. A total of 285 events, which epicenters were located in Austria, and a sum of 22.739 reported macreoseismic data points from Austria and adjoining countries, were used. These events are enclosed in the period 1000-2014 and characterized by having a local magnitude greater than 3. In the first state of the model development, the data was careful selected, e.g. solely intensities equal or greater than III were used. In a second state the data was adjusted to the selected empirical model. Finally, geology and topography corrections were obtained by means of the model residuals in order to derive intensity-based site amplification effects.

Use of Occupancy Models to Evaluate Expert Knowledge-based Species-Habitat Relationships

Directory of Open Access Journals (Sweden)

Monica N. Iglecia

2012-12-01

Full Text Available Expert knowledge-based species-habitat relationships are used extensively to guide conservation planning, particularly when data are scarce. Purported relationships describe the initial state of knowledge, but are rarely tested. We assessed support in the data for suitability rankings of vegetation types based on expert knowledge for three terrestrial avian species in the South Atlantic Coastal Plain of the United States. Experts used published studies, natural history, survey data, and field experience to rank vegetation types as optimal, suitable, and marginal. We used single-season occupancy models, coupled with land cover and Breeding Bird Survey data, to examine the hypothesis that patterns of occupancy conformed to species-habitat suitability rankings purported by experts. Purported habitat suitability was validated for two of three species. As predicted for the Eastern Wood-Pewee (Contopus virens and Brown-headed Nuthatch (Sitta pusilla, occupancy was strongly influenced by vegetation types classified as "optimal habitat" by the species suitability rankings for nuthatches and wood-pewees. Contrary to predictions, Red-headed Woodpecker (Melanerpes erythrocephalus models that included vegetation types as covariates received similar support by the data as models without vegetation types. For all three species, occupancy was also related to sampling latitude. Our results suggest that covariates representing other habitat requirements might be necessary to model occurrence of generalist species like the woodpecker. The modeling approach described herein provides a means to test expert knowledge-based species-habitat relationships, and hence, help guide conservation planning.

SLC beam line error analysis using a model-based expert system

International Nuclear Information System (INIS)

Lee, M.; Kleban, S.

1988-02-01

Commissioning particle beam line is usually a very time-consuming and labor-intensive task for accelerator physicists. To aid in commissioning, we developed a model-based expert system that identifies error-free regions, as well as localizing beam line errors. This paper will give examples of the use of our system for the SLC commissioning. 8 refs., 5 figs

Plutonium - the ultrapoison? An expert's opinion about an expert opinion

International Nuclear Information System (INIS)

Stoll, W.; Becker, K.

1989-01-01

In an expert opinion written by Professor H. Kuni, Marburg, for the North Rhine-Westphalian state government, plutonium is called by far the most dangerous element in the Periodic Table. The Marburg medical expert holds that even improved legal instruments are unable to warrant effective protection of the workers handling this material, in the light of the present standards of industrial safety, because of radiological conditions and measuring problems with plutonium isotopes. In this article by an internationally renowned expert in the field, the ideas expressed in the expert opinion about the toxicity of plutonium, the cause-and-effect relationship in radiation damage by plutonium, and recent findings about the toxicity are subjected to a critical review. On the basis of results of radiation protection and of case studies, the statements in the expert opinion are contrasted with facts which make them appear in a very different light. (orig./RB) [de

Prediction of the intensity and diversity of day-to-day activities among people with schizophrenia using parameters obtained during acute hospitalization.

Science.gov (United States)

Lipskaya-Velikovsky, Lena; Jarus, Tal; Kotler, Moshe

2017-06-01

Participation in day-to-day activities of people with schizophrenia is restricted, causing concern to them, their families, service providers and the communities at large. Participation is a significant component of health and recovery; however, factors predicting participation are still not well established. This study examines whether the parameters obtained during acute hospitalization can predict the intensity and diversity of participation in day-to-day activities six months after discharge. In-patients with chronic schizophrenia (N = 104) were enrolled into the study and assessed for cognitive functioning, functional capacity in instrumental activities of daily living (IADL), and symptoms. Six months after discharge, the intensity and diversity of participation in day-to-day activities were evaluated (N = 70). Multiple correlations were found between parameters obtained during hospitalization and participation diversity, but not participation intensity. The model that is better suited to the prediction of participation diversity contains cognitive ability of construction, negative symptoms and number of previous hospitalizations. The total explained variance is 37.8% (F 3,66  =   14.99, p process for the prediction of participation diversity in day-to-day activities six months after discharge. Participation diversity is best predicted through a set of factors reflecting personal and environmental indicators. Implications for rehabilitation Results of in-patient evaluations can predict the diversity of participation in day-to-day activities six months after discharge. Higher prediction of participation diversity is obtained using a holistic evaluation model that includes assessments for cognitive abilities, negative symptoms severity and number of hospitalizations.

An Investigation of Marketing via Mobile Devices - Attitudes of Croatian Marketing Experts

OpenAIRE

Dobrinić, Damir; Dvorski, Stjepan; Bosilj, Neven

2008-01-01

Marketing activities supported by mobile devices offer great opportunities for direct communication with consumers without the barriers of time, place, location and other. This article explores opinions and expectations Croatian marketing experts have towards use of m-advertising and other available advertising media, where we take the perspective of marketing experts to predict the future of m-marketing and m-advertising in Croatia. The paper also discusses the relevance of m-advertising and...

Extending Theory-Based Quantitative Predictions to New Health Behaviors.

Science.gov (United States)

Brick, Leslie Ann D; Velicer, Wayne F; Redding, Colleen A; Rossi, Joseph S; Prochaska, James O

2016-04-01

Traditional null hypothesis significance testing suffers many limitations and is poorly adapted to theory testing. A proposed alternative approach, called Testing Theory-based Quantitative Predictions, uses effect size estimates and confidence intervals to directly test predictions based on theory. This paper replicates findings from previous smoking studies and extends the approach to diet and sun protection behaviors using baseline data from a Transtheoretical Model behavioral intervention (N = 5407). Effect size predictions were developed using two methods: (1) applying refined effect size estimates from previous smoking research or (2) using predictions developed by an expert panel. Thirteen of 15 predictions were confirmed for smoking. For diet, 7 of 14 predictions were confirmed using smoking predictions and 6 of 16 using expert panel predictions. For sun protection, 3 of 11 predictions were confirmed using smoking predictions and 5 of 19 using expert panel predictions. Expert panel predictions and smoking-based predictions poorly predicted effect sizes for diet and sun protection constructs. Future studies should aim to use previous empirical data to generate predictions whenever possible. The best results occur when there have been several iterations of predictions for a behavior, such as with smoking, demonstrating that expected values begin to converge on the population effect size. Overall, the study supports necessity in strengthening and revising theory with empirical data.

Medical Expert Systems Survey

OpenAIRE

Abu-Nasser, Bassem S.

2017-01-01

International audience; There is an increased interest in the area of Artificial Intelligence in general and expert systems in particular. Expert systems are rapidly growing technology. Expert systems are a branch of Artificial Intelligence which is having a great impact on many fields of human life. Expert systems use human expert knowledge to solve complex problems in many fields such as Health, science, engineering, business, and weather forecasting. Organizations employing the technology ...

Inter-expert and intra-expert reliability in sleep spindle scoring

DEFF Research Database (Denmark)

Wendt, Sabrina Lyngbye; Welinder, Peter; Sørensen, Helge Bjarup Dissing

2015-01-01

Objectives To measure the inter-expert and intra-expert agreement in sleep spindle scoring, and to quantify how many experts are needed to build a reliable dataset of sleep spindle scorings. Methods The EEG dataset was comprised of 400 randomly selected 115 s segments of stage 2 sleep from 110...... with higher reliability than the estimation of spindle duration. Reliability of sleep spindle scoring can be improved by using qualitative confidence scores, rather than a dichotomous yes/no scoring system. Conclusions We estimate that 2–3 experts are needed to build a spindle scoring dataset...... with ‘substantial’ reliability (κ: 0.61–0.8), and 4 or more experts are needed to build a dataset with ‘almost perfect’ reliability (κ: 0.81–1). Significance Spindle scoring is a critical part of sleep staging, and spindles are believed to play an important role in development, aging, and diseases of the nervous...

Predictive factors for the admission of a newborn in an intensive care unit

Directory of Open Access Journals (Sweden)

Carla Danielle Ribeiro Lages

2014-04-01

Full Text Available Analytical documentary and retrospective study aiming at determining association between predictive factors for admission of a newborn in a public Intensive Care Unit and maternal features. The study sample had 376 neonates admitted in 2009. Results showed: mothers aged between 19 and 25 years (43.4%, primary education (52.4%, living with a partner (66.2%. Prenatal care was done by 84.8% of them, and 62% presented gestational pathologies. Out of all neonates, 55.1% were male, 85.4% preterm, 83% underweight, 57.2% presented respiratory problems. The bivariate analysis showed a significant association between birth weight and growth (p = 0.04 between maternal age and Apgar in the 1st minute (p = 0.04 and maternal age and Apgar score in the 5th minute (p = 0.01. Maternal age and number of prenatal appointments influence on the admission of the neonates to the Intensive Care Unit because they are related to birth weight and Apgar scores.

Application of expert elicitation techniques in human reliability, assessment

International Nuclear Information System (INIS)

Sanyasi Rao, V.V.S.; Saraf, R.K.; Ghosh, A.K.; Kushwaha, H.S.

2006-01-01

Expert elicitation techniques are being used, in the area of technological forecasting, in estimating data needed for analysis when it is either difficult to arrive at the data by experimental means or when it is quite involved to plan and conduct the experiment. In this study, expert elicitation techniques are applied to the evaluation of the frequencies of the various accident sequences that can result from the initiating event (IE) 'High Pressure Process Water (HPPW) system failure' in typical Indian Pressurised Heavy Water Reactor (IPHWR) of the older generation. The Operating Procedure under Emergency Conditions (OPEC) for this IE involves human actions according to a pre-defined procedure. The Human Error Probabilities for all these human actions are obtained using expert elicitation techniques. These techniques aim at eliciting the opinion of the experts in the area of interest with regard to the issue in question. The uncertainty is analysed by employing the measure of dissonance and the most probable range of human error probabilities are arrived at by maximizing this measure. These values are combined using the same procedures mentioned above to yield a distribution representing the uncertainty associated with the predictions. (author)

explICU: A web-based visualization and predictive modeling toolkit for mortality in intensive care patients.

Science.gov (United States)

Chen, Robert; Kumar, Vikas; Fitch, Natalie; Jagadish, Jitesh; Lifan Zhang; Dunn, William; Duen Horng Chau

2015-01-01

Preventing mortality in intensive care units (ICUs) has been a top priority in American hospitals. Predictive modeling has been shown to be effective in prediction of mortality based upon data from patients' past medical histories from electronic health records (EHRs). Furthermore, visualization of timeline events is imperative in the ICU setting in order to quickly identify trends in patient histories that may lead to mortality. With the increasing adoption of EHRs, a wealth of medical data is becoming increasingly available for secondary uses such as data exploration and predictive modeling. While data exploration and predictive modeling are useful for finding risk factors in ICU patients, the process is time consuming and requires a high level of computer programming ability. We propose explICU, a web service that hosts EHR data, displays timelines of patient events based upon user-specified preferences, performs predictive modeling in the back end, and displays results to the user via intuitive, interactive visualizations.

Common problems in the elicitation and analysis of expert opinion affecting probabilistic safety assessments

Energy Technology Data Exchange (ETDEWEB)

Meyer, M.A.; Booker, J.M.

1990-01-01

Expert opinion is frequently used in probabilistic safety assessment (PSA), particularly in estimating low probability events. In this paper, we discuss some of the common problems encountered in eliciting and analyzing expert opinion data and offer solutions or recommendations. The problems are: that experts are not naturally Bayesian. People fail to update their existing information to account for new information as it becomes available, as would be predicted by the Bayesian philosophy; that experts cannot be fully calibrated. To calibrate experts, the feedback from the known quantities must be immediate, frequent, and specific to the task; that experts are limited in the number of things that they can mentally juggle at a time to 7 {plus minus} 2; that data gatherers and analysts can introduce bias by unintentionally causing an altering of the expert's thinking or answers; that the level of detail the data, or granularity, can affect the analyses; and the conditioning effect poses difficulties in gathering and analyzing of the expert data. The data that the expert gives can be conditioned on a variety of factors that can affect the analysis and the interpretation of the results. 31 refs.

Real time expert systems

International Nuclear Information System (INIS)

Asami, Tohru; Hashimoto, Kazuo; Yamamoto, Seiichi

1992-01-01

Recently, aiming at the application to the plant control for nuclear reactors and traffic and communication control, the research and the practical use of the expert system suitable to real time processing have become conspicuous. In this report, the condition for the required function to control the object that dynamically changes within a limited time is presented, and the technical difference between the real time expert system developed so as to satisfy it and the expert system of conventional type is explained with the actual examples and from theoretical aspect. The expert system of conventional type has the technical base in the problem-solving equipment originating in STRIPS. The real time expert system is applied to the fields accompanied by surveillance and control, to which conventional expert system is hard to be applied. The requirement for the real time expert system, the example of the real time expert system, and as the techniques of realizing real time processing, the realization of interruption processing, dispersion processing, and the mechanism of maintaining the consistency of knowledge are explained. (K.I.)

Tapping into past design experiences : Knowledge sharing and creation during novice-expert design consultations

NARCIS (Netherlands)

Deken, F.; Kleinsmann, M.S.; Aurisicchio, M.; Lauche, K.; Bracewell, R.

2011-01-01

Designing is a knowledge-intensive activity. For novice design engineers, an important means of acquiring knowledge is to consult experienced colleagues. We observed novice–expert consultations as part of three engineering projects in a large aerospace company. Seven meetings were analysed in detail

Risk taking in adversarial situations: Civilization differences in chess experts.

Science.gov (United States)

Chassy, Philippe; Gobet, Fernand

2015-08-01

The projections of experts in politics predict that a new world order will emerge within two decades. Being multipolar, this world will inevitably lead to frictions where civilizations and states will have to decide whether to risk conflict. Very often these decisions are informed if not taken by experts. To estimate risk-taking across civilizations, we examined strategies used in 667,599 chess games played over eleven years by chess experts from 11 different civilizations. We show that some civilizations are more inclined to settle for peace. Similarly, we show that once engaged in the battle, the level of risk taking varies significantly across civilizations, the boldest civilization using the riskiest strategy about 35% more than the most conservative civilization. We discuss which psychological factors might underpin these civilizational differences. Copyright © 2015. Published by Elsevier B.V.

Situational motivation and perceived intensity: their interaction in predicting changes in positive affect from physical activity.

Science.gov (United States)

Guérin, Eva; Fortier, Michelle S

2012-01-01

There is evidence that affective experiences surrounding physical activity can contribute to the proper self-regulation of an active lifestyle. Motivation toward physical activity, as portrayed by self-determination theory, has been linked to positive affect, as has the intensity of physical activity, especially of a preferred nature. The purpose of this experimental study was to examine the interaction between situational motivation and intensity [i.e., ratings of perceived exertion (RPE)] in predicting changes in positive affect following an acute bout of preferred physical activity, namely, running. Fourty-one female runners engaged in a 30-minute self-paced treadmill run in a laboratory context. Situational motivation for running, pre- and post-running positive affect, and RPE were assessed via validated self-report questionnaires. Hierarchical regression analyses revealed a significant interaction effect between RPE and introjection (P positive affect was considerable, with higher RPE ratings being associated with greater increases in positive affect. The implications of the findings in light of SDT principles as well as the potential contingencies between the regulations and RPE in predicting positive affect among women are discussed.

Brain mechanisms of persuasion: how ‘expert power’ modulates memory and attitudes

Science.gov (United States)

Smidts, Ale; Fernández, Guillén

2008-01-01

Human behaviour is affected by various forms of persuasion. The general persuasive effect of high expertise of the communicator, often referred to as ’expert power’, is well documented. We found that a single exposure to a combination of an expert and an object leads to a long-lasting positive effect on memory for and attitude towards the object. Using functional magnetic resonance imaging, we probed the neural processes predicting these behavioural effects. Expert context was associated with distributed left-lateralized brain activity in prefrontal and temporal cortices related to active semantic elaboration. Furthermore, experts enhanced subsequent memory effects in the medial temporal lobe (i.e. in hippocampus and parahippocampal gyrus) involved in memory formation. Experts also affected subsequent attitude effects in the caudate nucleus involved in trustful behaviour, reward processing and learning. These results may suggest that the persuasive effect of experts is mediated by modulation of caudate activity resulting in a re-evaluation of the object in terms of its perceived value. Results extend our view of the functional role of the dorsal striatum in social interaction and enable us to make the first steps toward a neuroscientific model of persuasion. PMID:19015077

Toxicity management of angiogenesis inhibitors: resolution of expert panel

Directory of Open Access Journals (Sweden)

Pavel O. Rumiantsev

2017-12-01

Full Text Available On 22 June 2017 in St. Petersburg the expert panel was held on the topic “Management of toxicity of angiogenesis inhibitors”, which discussed current issues of systemic therapy of advanced differentiated thyroid cancer resistant to radioactive iodine therapy, advanced kidney cancer and questions of efficacy and safety of new target drugs in the treatment of these diseases. The reports and discussions of experts raised the following questions: 1. Own experience of using lenvatinib in patients with differentiated thyroid cancer refractory to therapy with radioactive iodine and kidney cancer. 2. Profile of efficacy and safety of modern targeted therapy with multikinase inhibitors. 3. Prophylaxis and management of predictable toxicity.

Comparison of climate envelope models developed using expert-selected variables versus statistical selection

Science.gov (United States)

Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

2017-01-01

Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable

Online-Expert: An Expert System for Online Database Selection.

Science.gov (United States)

Zahir, Sajjad; Chang, Chew Lik

1992-01-01

Describes the design and development of a prototype expert system called ONLINE-EXPERT that helps users select online databases and vendors that meet users' needs. Search strategies are discussed; knowledge acquisition and knowledge bases are described; and the Analytic Hierarchy Process (AHP), a decision analysis technique that ranks databases,…

Being an expert

International Nuclear Information System (INIS)

Brechet, Y.; Musseau, O.; Bruna, G.; Sperandio, M.; Roulleaux-Dugage, M.; Andrieux, S.; Metteau, L.

2014-01-01

This series of short articles are dedicated to the role of the expert in the enterprise. There is an important difference between a scientific counsellor and an expert, the expert, recognized by his peers, can speak publicly in his field of expertise but has a duty of transparency while the job of a scientific counsellor requires confidentiality. The making and the use of an expert in an enterprise requires a dedicated organization. The organization of the expertise in 5 enterprises in nuclear industry are considered: CEA (French Alternative Energies and Atomic Energy Commission), IRSN (Institute of Radioprotection and Nuclear Safety), AREVA, ANDRA (National Radioactive Waste Management Agency) and EDF (Electricity of France)

Implementation of an expert system for xenon spatial control in pressurized-water reactors

International Nuclear Information System (INIS)

Chung, S.K.

1988-01-01

Control of the axial xenon oscillations is a knowledge- and experience-intensive activity for reactor operators. To aid reactor operators in the control of axial xenon oscillations, an advisory expert system was developed. A rule-based expert system shell, INSIGHT2+, was used to build the expert system which was interfaced with a microcomputer-based core control model of a pressurized-water reactor, graphic engine, and data base. A core control model described by one-group diffusion theory with moderator temperature and xenon feedbacks was used to develop heuristic control rules and to test the system. Full- and part-length control rods, boron concentration, and coolant inlet temperature were considered as control variables of the core control model. This expert system consists of a search space: the set of possible power level and power shape patterns. The search space was made by combining the following core state variables: the sign of relative power and axial offset (AO) error, sign of the rate of change of power level and AO, and magnitude of relative power and AO error

Determination of intensity functions for predicting subsidence from coal mining, potash mining, and groundwater withdrawal using the influence function technique

Energy Technology Data Exchange (ETDEWEB)

Triplett, T; Yurchak, D [Twin Cities Research Center, Bureau of Mines, US Dept. of the Interior, Minneapolis, MN (United States)

1997-12-31

This paper presents research, conducted by the Bureau of Mines, on modifying the influence function method to predict subsidence. According to theory, this technique must incorporate an intensity function to represent the relative significance of the causes of subsidence. This paper shows that the inclusion of a reasonable intensity function increases the accuracy of the technique, then presents the required functions for case studies of longwall coal mining subsidence in Illinois, USA, potash mining subsidence in new Mexico, USA, and subsidence produced by ground water withdrawal in California, USA. Finally, the paper discusses a method to predict the resultant strain from a simply measured site constant and ground curvatures calculated by the technique. (orig.)

Determination of intensity functions for predicting subsidence from coal mining, potash mining, and groundwater withdrawal using the influence function technique

Energy Technology Data Exchange (ETDEWEB)

Triplett, T.; Yurchak, D. [Twin Cities Research Center, Bureau of Mines, US Dept. of the Interior, Minneapolis, MN (United States)

1996-12-31

This paper presents research, conducted by the Bureau of Mines, on modifying the influence function method to predict subsidence. According to theory, this technique must incorporate an intensity function to represent the relative significance of the causes of subsidence. This paper shows that the inclusion of a reasonable intensity function increases the accuracy of the technique, then presents the required functions for case studies of longwall coal mining subsidence in Illinois, USA, potash mining subsidence in new Mexico, USA, and subsidence produced by ground water withdrawal in California, USA. Finally, the paper discusses a method to predict the resultant strain from a simply measured site constant and ground curvatures calculated by the technique. (orig.)

Prediction of thermal coagulation from the instantaneous strain distribution induced by high-intensity focused ultrasound

Science.gov (United States)

Iwasaki, Ryosuke; Takagi, Ryo; Tomiyasu, Kentaro; Yoshizawa, Shin; Umemura, Shin-ichiro

2017-07-01

The targeting of the ultrasound beam and the prediction of thermal lesion formation in advance are the requirements for monitoring high-intensity focused ultrasound (HIFU) treatment with safety and reproducibility. To visualize the HIFU focal zone, we utilized an acoustic radiation force impulse (ARFI) imaging-based method. After inducing displacements inside tissues with pulsed HIFU called the push pulse exposure, the distribution of axial displacements started expanding and moving. To acquire RF data immediately after and during the HIFU push pulse exposure to improve prediction accuracy, we attempted methods using extrapolation estimation and applying HIFU noise elimination. The distributions going back in the time domain from the end of push pulse exposure are in good agreement with tissue coagulation at the center. The results suggest that the proposed focal zone visualization employing pulsed HIFU entailing the high-speed ARFI imaging method is useful for the prediction of thermal coagulation in advance.

Diagnosing battery behavior with an expert system in Prolog

International Nuclear Information System (INIS)

Kirkwood, N.; Weeks, D.J.

1986-01-01

Power for the Hubble Space Telescope comes from a system of 20 solar panel assemblies (SPAs) and six nickel-cadmium batteries. The HST battery system is simulated by the HST Electrical Power System (EPS) testbed at Marshall Space Flight Center. The Nickel Cadmium Battery Expert System (NICBES) is being used to diagnose faults of the testbed system, evaluate battery status and provide decision support for the engineer. Extensive telemetry of system operating conditions is relayed through a DEC LSI-11, and sent on to an IBM PC-AT. A BASIC program running on the PC monitors the flow of data, figures cell divergence and recharge ratio and stores these values, along with other selected data, for use by the expert system. The expert system is implemented in the logic programming language Prolog. It has three modes of operation: fault diagnosis, status and advice, and decision support. An alert or failure of the system will trigger a diagnosis by the system to assist the operator. The operator can also request battery status information as well as a number of plots and histograms of recent battery behavior. Trends in EOC and EOD voltage, recharge ratio and divergence are used by the expert system in its analysis of battery status. A future enhancement to the system includes the statistical prediction of battery life. Incorporating learning into the expert system is another possible enhancement; This is a difficult task, but one which could promise great rewards in improved battery performance

System Experts and Decision Making Experts in Transdisciplinary Projects

Science.gov (United States)

Mieg, Harald A.

2006-01-01

Purpose: This paper aims at a better understanding of expert roles in transdisciplinary projects. Thus, the main purpose is the analysis of the roles of experts in transdisciplinary projects. Design/methodology/approach: The analysis of the ETH-UNS case studies from the point of view of the psychology of expertise and the sociology of professions…

Expert auditors’ services classification

OpenAIRE

Jolanta Wisniewska

2013-01-01

The profession of an expert auditor is a public trust occupation with a distinctive feature of taking responsibility for actions in the public interest. The main responsibility of expert auditors is performing financial auditing; however, expert auditors are prepared to carry out different tasks which encompass a wide plethora of financial and auditing services for different kinds of institutions and companies. The aim of the article is first of all the description of expert auditors’ service...

Regional regression models of percentile flows for the contiguous United States: Expert versus data-driven independent variable selection

Directory of Open Access Journals (Sweden)

Geoffrey Fouad

2018-06-01

New hydrological insights for the region: A set of three variables selected based on an expert assessment of factors that influence percentile flows performed similarly to larger sets of variables selected using a data-driven method. Expert assessment variables included mean annual precipitation, potential evapotranspiration, and baseflow index. Larger sets of up to 37 variables contributed little, if any, additional predictive information. Variables used to describe the distribution of basin data (e.g. standard deviation were not useful, and average values were sufficient to characterize physical and climatic basin conditions. Effectiveness of the expert assessment variables may be due to the high degree of multicollinearity (i.e. cross-correlation among additional variables. A tool is provided in the Supplementary material to predict percentile flows based on the three expert assessment variables. Future work should develop new variables with a strong understanding of the processes related to percentile flows.

An expert system for PWR core operation management

Energy Technology Data Exchange (ETDEWEB)

Ida, Toshio; Masuda, Masahiro; Nishioka, Hiromasa

1988-01-01

Planning for restartup after planned or unplanned reactor shutdown and load-follow operations is an important task in the core operation management of pressurized water reactors (PWRs). These planning problems have been solved by planning experts using their expertise and the computational prediction of core behavior. Therefore, the quality of the plan and the time consumed in the planning depend heavily on the skillfulness of the planning experts. A knowledge engineering approach has been recently considered as a promising means to solve such complicated planning problems. Many knowledge-based systems have been developed so far, and some of them have already been applied because of their effectiveness. The expert system REPLEX has been developed to aid core management engineers in making a successful plan for the restartup or the load-follow operation of PWRs within a shorter time. It can maintain planning tasks at a high-quality level independent of the skillfulness of core management engineers and enhance the efficiency of management. REPLEX has an explanation function that helps user understanding of plans. It could be a useful took, therefore, for the training of core management engineers.

An expert system for PWR core operation management

International Nuclear Information System (INIS)

Ida, Toshio; Masuda, Masahiro; Nishioka, Hiromasa.

1988-01-01

Planning for restartup after planned or unplanned reactor shutdown and load-follow operations is an important task in the core operation management of pressurized water reactors (PWRs). These planning problems have been solved by planning experts using their expertise and the computational prediction of core behavior. Therefore, the quality of the plan and the time consumed in the planning depend heavily on the skillfulness of the planning experts. A knowledge engineering approach has been recently considered as a promising means to solve such complicated planning problems. Many knowledge-based systems have been developed so far, and some of them have already been applied because of their effectiveness. The expert system REPLEX has been developed to aid core management engineers in making a successful plan for the restartup or the load-follow operation of PWRs within a shorter time. It can maintain planning tasks at a high-quality level independent of the skillfulness of core management engineers and enhance the efficiency of management. REPLEX has an explanation function that helps user understanding of plans. It could be a useful took, therefore, for the training of core management engineers

Targeted temperature management in the ICU: guidelines from a French expert panel.

Science.gov (United States)

Cariou, Alain; Payen, Jean-François; Asehnoune, Karim; Audibert, Gerard; Botte, Astrid; Brissaud, Olivier; Debaty, Guillaume; Deltour, Sandrine; Deye, Nicolas; Engrand, Nicolas; Francony, Gilles; Legriel, Stéphane; Levy, Bruno; Meyer, Philippe; Orban, Jean-Christophe; Renolleau, Sylvain; Vigue, Bernard; De Saint Blanquat, Laure; Mathien, Cyrille; Velly, Lionel

2017-12-01

Over the recent period, the use of induced hypothermia has gained an increasing interest for critically ill patients, in particular in brain-injured patients. The term "targeted temperature management" (TTM) has now emerged as the most appropriate when referring to interventions used to reach and maintain a specific level temperature for each individual. TTM may be used to prevent fever, to maintain normothermia, or to lower core temperature. This treatment is widely used in intensive care units, mostly as a primary neuroprotective method. Indications are, however, associated with variable levels of evidence based on inhomogeneous or even contradictory literature. Our aim was to conduct a systematic analysis of the published data in order to provide guidelines. We present herein recommendations for the use of TTM in adult and paediatric critically ill patients developed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) method. These guidelines were conducted by a group of experts from the French Intensive Care Society (Société de Réanimation de Langue Française [SRLF]) and the French Society of Anesthesia and Intensive Care Medicine (Société Francaise d'Anesthésie Réanimation [SFAR]) with the participation of the French Emergency Medicine Association (Société Française de Médecine d'Urgence [SFMU]), the French Group for Pediatric Intensive Care and Emergencies (Groupe Francophone de Réanimation et Urgences Pédiatriques [GFRUP]), the French National Association of Neuro-Anesthesiology and Critical Care (Association Nationale de Neuro-Anesthésie Réanimation Française [ANARLF]), and the French Neurovascular Society (Société Française Neurovasculaire [SFNV]). Fifteen experts and two coordinators agreed to consider questions concerning TTM and its practical implementation in five clinical situations: cardiac arrest, traumatic brain injury, stroke, other brain injuries, and shock. This resulted in 30 recommendations

Prediction of modified Mercalli intensity from PGA, PGV, moment magnitude, and epicentral distance using several nonlinear statistical algorithms

Science.gov (United States)

Alvarez, Diego A.; Hurtado, Jorge E.; Bedoya-Ruíz, Daniel Alveiro

2012-07-01

Despite technological advances in seismic instrumentation, the assessment of the intensity of an earthquake using an observational scale as given, for example, by the modified Mercalli intensity scale is highly useful for practical purposes. In order to link the qualitative numbers extracted from the acceleration record of an earthquake and other instrumental data such as peak ground velocity, epicentral distance, and moment magnitude on the one hand and the modified Mercalli intensity scale on the other, simple statistical regression has been generally employed. In this paper, we will employ three methods of nonlinear regression, namely support vector regression, multilayer perceptrons, and genetic programming in order to find a functional dependence between the instrumental records and the modified Mercalli intensity scale. The proposed methods predict the intensity of an earthquake while dealing with nonlinearity and the noise inherent to the data. The nonlinear regressions with good estimation results have been performed using the "Did You Feel It?" database of the US Geological Survey and the database of the Center for Engineering Strong Motion Data for the California region.

Performance of the FV3-powered Next Generation Global Prediction System for Harvey and Irma, and a vision for a "beyond weather timescale" prediction system for long-range hurricane track and intensity predictions

Science.gov (United States)

Lin, S. J.; Bender, M.; Harris, L.; Hazelton, A.

2017-12-01

The performance of a GFDL developed FV3-based Next Generation Global Prediction System (NGGPS) for Harvey and Irma will be reported. We will report on aspects of track and intensity errors (vs operational models), heavy precipitation (Harvey), rapid intensification, and simulated structure (in comparison with ground based radar), and point to a need of a future long-range (from day-5 up to 30 days) physically based ensemble hurricane prediction system for providing useful information to the forecasters, beyond the usual weather timescale.

High intensity region segmentation in MR imaging of multiple sclerosis

International Nuclear Information System (INIS)

Rodrigo, F; Filipuzzi, M; Graffigna, J P; Isoardi, R; Noceti, M

2013-01-01

Numerous pathologies are often manifest in Magnetic Resonance Imaging (MRI) as hyperintense or bright regions as compared to normal tissue. It is of particular interest to develop an algorithm to detect, identify and define those Regions of Interest (ROI) when analyzing MRI studies, particularly for lesions of Multiple Sclerosis (MS). The objective of this study is to analyze those parameters which optimize segmentation of the areas of interest. To establish which areas should be considered as hyperintense regions, we developed a database (DB), with studies of patients diagnosed with MS. This disease causes axonal demyelination and it is expressed as bright regions in PD, T2 and FLAIR MRI sequences. Thus, with more than 4300 hyperintense regions validated by an expert physician, an algorithm was developed to detect such spots, approximating the results the expert obtained. Alongside these hyperintense lesion regions, it also detected bone regions with high intensity levels, similar to the intensity of the lesions, but with other features that allow a good differentiation.The algorithm will then detect ROIs with similar intensity levels and performs classification through data mining techniques

Quality versus Quantity Debate in Swimming: Perceptions and Training Practices of Expert Swimming Coaches.

Science.gov (United States)

Nugent, Frank J; Comyns, Thomas M; Warrington, Giles D

2017-06-01

The debate over low-volume, high-intensity training versus high-volume, low-intensity training, commonly known as Quality versus Quantity, respectively, is a frequent topic of discussion among swimming coaches and academics. The aim of this study was to explore expert coaches' perceptions of quality and quantity coaching philosophies in competitive swimming and to investigate their current training practices. A purposeful sample of 11 expert swimming coaches was recruited for this study. The study was a mixed methods design and involved each coach participating in 1 semi-structured interview and completing 1 closed-ended questionnaire. The main findings of this study were that coaches felt quality training programmes would lead to short term results for youth swimmers, but were in many cases more appropriate for senior swimmers. The coaches suggested that quantity training programmes built an aerobic base for youth swimmers, promoted technical development through a focus on slower swimming and helped to enhance recovery from training or competition. However, the coaches continuously suggested that quantity training programmes must be performed with good technique and they felt this was a misunderstood element. This study was a critical step towards gaining a richer and broader understanding on the debate over Quality versus Quantity training from an expert swimming coaches' perspective which was not currently available in the research literature.

Quality Versus Quantity Debate in Swimming: Perceptions and Training Practices of Expert Swimming Coaches

Directory of Open Access Journals (Sweden)

Nugent Frank J.

2017-06-01

Full Text Available The debate over low-volume, high-intensity training versus high-volume, low-intensity training, commonly known as Quality versus Quantity, respectively, is a frequent topic of discussion among swimming coaches and academics. The aim of this study was to explore expert coaches’ perceptions of quality and quantity coaching philosophies in competitive swimming and to investigate their current training practices. A purposeful sample of 11 expert swimming coaches was recruited for this study. The study was a mixed methods design and involved each coach participating in 1 semi-structured interview and completing 1 closed-ended questionnaire. The main findings of this study were that coaches felt quality training programmes would lead to short term results for youth swimmers, but were in many cases more appropriate for senior swimmers. The coaches suggested that quantity training programmes built an aerobic base for youth swimmers, promoted technical development through a focus on slower swimming and helped to enhance recovery from training or competition. However, the coaches continuously suggested that quantity training programmes must be performed with good technique and they felt this was a misunderstood element. This study was a critical step towards gaining a richer and broader understanding on the debate over Quality versus Quantity training from an expert swimming coaches’ perspective which was not currently available in the research literature.

RISK REDUCTION WITH A FUZZY EXPERT EXPLORATION TOOL

Energy Technology Data Exchange (ETDEWEB)

William W. Weiss

2000-06-30

found to correlate regional attributes with individual well production. On a local scale, given open-hole log information, a neural network was trained to predict the product of porosity and oil saturation as reported in whole core analysis. Thus a direct indicator of an oil show is available from log information. This is important in the thin-bedded Delaware sand reservoirs. Fuzzy ranking was used to prioritize 3D seismic attributes that were then correlated to formation depth with a neural network. The results were superior to those obtained using linear interpolation or low order polynomial interpolation as time-to-depth conversion tools. A radial basis function neural network was developed and used as a log evaluation tool. This new technology gives an additional tool to the more commonly used multilayer perceptron (MLP) neural network. An interactive web based MLP, PredictOnline, was coded in Java and made available to consortium members for beta testing. PredictOnline demonstrates the power of Java programming language for web-based applications. A draft design of the Fuzzy Expert Exploration (FEE) Tool system based on readily available software was completed. The recent development of a Java Expert System Shell, JESS, facilitates expert rule development.

Can Energy Cost During Low-Intensity Resistance Exercise be Predicted by the OMNI-RES Scale?

Science.gov (United States)

Vianna, Jefferson M.; Reis, Victor M.; Saavedra, Francisco; Damasceno, Vinicius; Silva, Sérgio G.; Goss, Fredric

2011-01-01

The aim of the present study was to assess the precision of the OMNI-RES scale to predict energy cost (EC) at low intensity in four resistance exercises (RE). 17 male recreational body builders (age = 26.6 ± 4.9 years; height = 177.7 ± 0.1 cm; body weight = 79.0 ± 11.1 kg and percent body fat = 10.5 ± 4.6%) served as subjects. Initially tests to determine 1RM for four resistance exercises (bench press, half squat, lat pull down and triceps extension) were administered. Subjects also performed resistance exercise at 12, 16, 20, and 24% of 1RM at a rate of 40 bpm until volitional exhaustion. Oxygen uptake (VO2) and rate of perceived exertion (RPE) using the OMNI-RES were obtained during and after all RE. EC was calculated using VO2 and the caloric values of VO2 for non-protein RER. Regression analyses were performed for every RE, using EC as the dependent and RPE as the predictor variable. The triceps extension, lat pull down and bench press, RPE correlated strongly with EC (R > 0.97) and predicted EC with a error of less than 0.2 kcal.min−1. In conclusion, RPE using the OMNI-RES scale can be considered as an accurate indicator of EC in the bench press, lat pull down and triceps extension performed by recreational bodybuilders, provided lower intensities are used (up to 24% of 1-RM) and provided each set of exercise is performed for the maximal sustainable duration. It would be interesting in future studies to consider having the subjects exercise at low intensities for longer durations than those in the present study. PMID:23486188

Learning from the Experts: Gaining Insights into Best Practice during the Acquisition of Three Novel Motor Skills

Science.gov (United States)

Hodges, Nicola J.; Edwards, Christopher; Luttin, Shaun; Bowcock, Alison

2011-01-01

The amount and quality of practice predicts expertise, yet optimal conditions of practice have primarily been explored with novice learners. Ten expert musicians and ten novices practiced disc-throwing skills under self-regulated conditions. A third novice group practiced with the same schedule as the music experts (yoked). The groups did not…

Artificial neural networks application for solid fuel slagging intensity predictions

Directory of Open Access Journals (Sweden)

Kakietek Sławomir

2017-01-01

Full Text Available Slagging issues present in pulverized steam boilers very often lead to heat transfer problems, corrosion and not planned outages of boilers which increase the cost of energy production and decrease the efficiency of energy production. Slagging especially occurs in regions with reductive atmospheres which nowadays are very common due to very strict limitations in NOx emissions. Moreover alternative fuels like biomass which are also used in combustion systems from two decades in order to decrease CO2 emissions also usually increase the risk of slagging. Thus the prediction of slagging properties of fuels is not the minor issue which can be neglected before purchasing or mixing of fuels. This however is rather difficult to estimate and even commonly known standard laboratory methods like fusion temperature determination or special indexers calculated on the basis of proximate and ultimate analyses, very often have no reasonable correlation to real boiler fuel behaviour. In this paper the method of determination of slagging properties of solid fuels based on laboratory investigation and artificial neural networks were presented. A fuel data base with over 40 fuels was created. Neural networks simulations were carried out in order to predict the beginning temperature and intensity of slagging. Reasonable results were obtained for some of tested neural networks, especially for hybrid feedforward networks with PCA technique. Consequently neural network model will be used in Common Intelligent Boiler Operation Platform (CIBOP being elaborated within CERUBIS research project for two BP-1150 and BB-1150 steam boilers. The model among others enables proper fuel selection in order to minimize slagging risk.

Intensive physical activity and alexithymia: results from swimmers' discourse analysis.

Science.gov (United States)

Allegre, Benjamin; Noel-Jorand, Marie-Christine; Souville, Marc; Pellegrin, Liliane; Therme, Pierre

2007-06-01

The aim of this study was to describe and understand the relationship of swimmers' practice intensity and alexithymia features in discourse. This study investigated psychological processes in two groups of male swimmers training at different intensities. The first group was composed of 10 Expert amateurs (M age = 19.5 yr., SD = 1.9), who were competing at the national or international level and trained 22 hours per week. The second group was composed of 10 Amateur swimmers (M age = 20.5 yr., SD = 1.4), who competed at the regional level and trained 6 hours per week. The discourse of swimmers was analysed using the ALCESTE (Analyse de Lexèmes Coocurents dans les Enoncés Simples d'un Texte) method of discourse analysis. Discourse analysis was performed on speech samples produced by swimmers. All the swimmers showed alexithymic verbal behaviour as regards both the means of expression used and the feelings and emotions expressed. This lack of articulateness was more pronounced in the Expert than in the Amateur group. The difference of alexithymic features in correlation with the intensity of sport practice raises the question of the health benefits of intense sports practice and the need for psychological assessment of athletes.

Expert forecasts and the emergence of water scarcity on public agendas

Science.gov (United States)

Graffy, E.A.

2006-01-01

Expert forecasts of worldwide water scarcity depict conditions that call for proactive, preventive, coordinated water governance, but they have not been matched by public agendas of commensurate scope and urgency in the United States. This disconnect can not be adequately explained without some attention to attributes of forecasts themselves. I propose that the institutional fragmentation of water expertise and prevailing patterns of communication about water scarcity militate against the formulation of a common public definition of the problem and encourage reliance on unambiguous crises to stimulate social and policy agenda setting. I do not argue that expert forecasts should drive public agendas deterministically, but if their purpose is to help prevent water crises (not just predict them), then a greater effort is needed to overcome the barriers to meaningful public scrutiny of expert claims and evaluation of water strategies presently in place. Copyright ?? 2006 Taylor & Francis Group, LLC.

Delegating Decisions to Experts

Science.gov (United States)

Li, Hao; Suen, Wing

2004-01-01

We present a model of delegation with self-interested and privately informed experts. A team of experts with extreme but opposite biases is acceptable to a wide range of decision makers with diverse preferences, but the value of expertise from such a team is low. A decision maker wants to appoint experts who are less partisan than he is in order…

Situational Motivation and Perceived Intensity: Their Interaction in Predicting Changes in Positive Affect from Physical Activity

Directory of Open Access Journals (Sweden)

Eva Guérin

2012-01-01

Full Text Available There is evidence that affective experiences surrounding physical activity can contribute to the proper self-regulation of an active lifestyle. Motivation toward physical activity, as portrayed by self-determination theory, has been linked to positive affect, as has the intensity of physical activity, especially of a preferred nature. The purpose of this experimental study was to examine the interaction between situational motivation and intensity [i.e., ratings of perceived exertion (RPE] in predicting changes in positive affect following an acute bout of preferred physical activity, namely, running. Fourty-one female runners engaged in a 30-minute self-paced treadmill run in a laboratory context. Situational motivation for running, pre- and post-running positive affect, and RPE were assessed via validated self-report questionnaires. Hierarchical regression analyses revealed a significant interaction effect between RPE and introjection (P<.05 but not between RPE and identified regulation or intrinsic motivation. At low levels of introjection, the influence of RPE on the change in positive affect was considerable, with higher RPE ratings being associated with greater increases in positive affect. The implications of the findings in light of SDT principles as well as the potential contingencies between the regulations and RPE in predicting positive affect among women are discussed.

Application of expert systems

Energy Technology Data Exchange (ETDEWEB)

Basden, A

1983-11-01

This article seeks to bring together a number of issues relevant to the application of expert systems by discussing their advantages and limitations, their roles and benefits, and the influence that real-life applications might have on the design of expert systems software. Part of the expert systems strategy of one major chemical company is outlined. Because it was in constructing one particular expert system that many of these issues became important this system is described briefly at the start of the paper and used to illustrate much of the later discussion. It is of the plausible-inference type and has application in the field of materials engineering. 22 references.

Counselor Expert System | Debretsion | Zede Journal

African Journals Online (AJOL)

An expert system plays an important role on alleviating primarily shortage of experts in a specific area of interest. With the help of an expert system, personnel with little expertise can solve problems that require expert knowledge. In this paper all major aspects of an expert system development have been presented.

Opportune maintenance and predictive maintenance decision support

OpenAIRE

Thomas , Edouard; Levrat , Eric; Iung , Benoît; Cocheteux , Pierre

2009-01-01

International audience; Conventional maintenance strategies on a single component are being phased out in favour of more predictive maintenance actions. These new kinds of actions are performed in order to control the global performances of the whole industrial system. They are anticipative in nature, which allows a maintenance expert to consider non-already-planned maintenance actions. Two questions naturally emerge: when to perform a predictive maintenance action; how a maintenance expert c...

[Study on expert system of infrared spectral characteristic of combustible smoke agent].

Science.gov (United States)

Song, Dong-ming; Guan, Hua; Hou, Wei; Pan, Gong-pei

2009-05-01

The present paper studied the application of expert system in prediction of infrared spectral characteristic of combustible anti-infrared smoke agent. The construction of the expert system was founded, based on the theory of minimum free energy and infrared spectral addition. After the direction of smoke agent was input, the expert system could figure out the final combustion products. Then infrared spectrogram of smoke could also be simulated by adding the spectra of all of the combustion products. Meanwhile, the screening index of smoke was provided in the wave bands of 3-5 im and 8-14 microm. FTIR spectroscope was used to investigate the performance of one kind of HC smoke. The combustion products calculated by the expert system were coincident with the actual data, and the simulant infrared spectrum was also similar to the real one of the smoke. The screening index given by the system was consistent with the known facts. It was showed that a new approach was offered for the fast discrimination of varieties of directions of smoke agent.

Expert Panel Elicitation

Energy Technology Data Exchange (ETDEWEB)

Jensen, M. [Swedish Radiation Protection Authority, Stockholm (Sweden). Dept. of Waste Management and Environmental Protection; Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States)

2005-09-15

Scientists are now frequently in a situation where data cannot be easily assessed, since they may have conflicting or uncertain sources. While expert judgment reflects private choices, it is possible both reduce the personal aspect as well as in crease confidence in the judgments by using formal protocols for choice and elicitation of experts. A full-scale elicitation made on seismicity following glaciation, now in its late phase and presented here in a preliminary form, illustrates the value of the technique and some essential issues in connection with the decision to launch such a project. The results show an unusual low variation between the experts.

Appropriate Combination of Artificial Intelligence and Algorithms for Increasing Predictive Accuracy Management

Directory of Open Access Journals (Sweden)

Shahram Gilani Nia

2010-03-01

Full Text Available In this paper a simple and effective expert system to predict random data fluctuation in short-term period is established. Evaluation process includes introducing Fourier series, Markov chain model prediction and comparison (Gray combined with the model prediction Gray- Fourier- Markov that the mixed results, to create an expert system predicted with artificial intelligence, made this model to predict the effectiveness of random fluctuation in most data management programs to increase. The outcome of this study introduced artificial intelligence algorithms that help detect that the computer environment to create a system that experts predict the short-term and unstable situation happens correctly and accurately predict. To test the effectiveness of the algorithm presented studies (Chen Tzay len,2008, and predicted data of tourism demand for Iran model is used. Results for the two countries show output model has high accuracy.

[Quality assurance concepts in intensive care medicine].

Science.gov (United States)

Brinkmann, A; Braun, J P; Riessen, R; Dubb, R; Kaltwasser, A; Bingold, T M

2015-11-01

Intensive care medicine (ICM) is characterized by a high degree of complexity and requires intense communication and collaboration on interdisciplinary and multiprofessional levels. In order to achieve good quality of care in this environment and to prevent errors, a proactive quality and error management as well as a structured quality assurance system are essential. Since the early 1990s, German intensive care societies have developed concepts for quality management and assurance in ICM. In 2006, intensive care networks were founded in different states to support the implementation of evidence-based knowledge into clinical routine and to improve medical outcome, efficacy, and efficiency in ICM. Current instruments and concepts of quality assurance in German ICM include core intensive care data from the data registry DIVI REVERSI, quality indicators, peer review in intensive care, IQM peer review, and various certification processes. The first version of German ICM quality indicators was published in 2010 by an interdisciplinary and interprofessional expert commission. Key figures, indicators, and national benchmarks are intended to describe the quality of structures, processes, and outcomes in intensive care. Many of the quality assurance tools have proved to be useful in clinical practice, but nationwide implementation still can be improved.

Sleep-spindle detection: crowdsourcing and evaluating performance of experts, non-experts and automated methods

DEFF Research Database (Denmark)

Warby, Simon C.; Wendt, Sabrina Lyngbye; Welinder, Peter

2014-01-01

to crowdsource spindle identification by human experts and non-experts, and we compared their performance with that of automated detection algorithms in data from middle- to older-aged subjects from the general population. We also refined methods for forming group consensus and evaluating the performance...... of event detectors in physiological data such as electroencephalographic recordings from polysomnography. Compared to the expert group consensus gold standard, the highest performance was by individual experts and the non-expert group consensus, followed by automated spindle detectors. This analysis showed...... that crowdsourcing the scoring of sleep data is an efficient method to collect large data sets, even for difficult tasks such as spindle identification. Further refinements to spindle detection algorithms are needed for middle- to older-aged subjects....

Surgical experts: born or made?

Science.gov (United States)

Sadideen, Hazim; Alvand, Abtin; Saadeddin, Munir; Kneebone, Roger

2013-01-01

The concept of surgical expertise and the processes involved in its development are topical, and there is a constant drive to identify reliable measures of expert performance in surgery. This review explores the notion of whether surgical experts are "born" or "made", with reference to educational theory and pertinent literature. Peer-reviewed publications, books, and online resources on surgical education, expertise and training were reviewed. Important themes and aspects of expertise acquisition were identified in order to better understand the concept of a surgical expert. The definition of surgical expertise and several important aspects of its development are highlighted. Innate talent plays an important role, but is insufficient on its own to produce a surgical expert. Multiple theories that explore motor skill acquisition and memory are relevant, and Ericsson's theory of the development of competence followed by deliberate self-practice has been especially influential. Psychomotor and non-technical skills are necessary for progression in the current climate in light of our training curricula; surgical experts are adaptive experts who excel in these. The literature suggests that surgical expertise is reached through practice; surgical experts are made, not born. A deeper understanding of the nature of expert performance and its development will ensure that surgical education training programmes are of the highest possible quality. Surgical educators should aim to develop an expertise-based approach, with expert performance as the benchmark. Copyright © 2013 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.

Law for nuclear experts only

Energy Technology Data Exchange (ETDEWEB)

Wagner, H [Kernforschungszentrum Karlsruhe G.m.b.H. (Germany, F.R.)

1980-02-01

The Federal Ministry of the Interior is preparing an ordinance on expert consultants under the Atomic Energy Act which, among other topics, is to include legal norms for the criteria to be met by experts in terms of non-partisanship, training, capabilities, technical equipment and cooperation in expert organizations of members of various scientific and technical disciplines. A summary of general criteria relating to the qualification, selection and status of experts called in by the legislative and executive branches and by courts of law, which could be organized as a series of guidelines without any original qualities of legal norms, could be recommended in view of the increasing quantitative and qualitative importance of experts. However, passing an ordinance merely fixing and putting into concrete terms the image of an 'expert under the Atomic Energy Act' is intolerable, because the status of scientific and technical experts by far extends beyond the field of nuclear law in our industrial society characterized by a far reaching division of labor. Weak points in the organization of expert services are not confined to technology or nuclear power. Separate rules establishing legal norms are not convincing also for reasons of technology policy and legal policy as well as for those of social psychology and practice.

Expert Systems for the Analytical Laboratory.

Science.gov (United States)

de Monchy, Allan R.; And Others

1988-01-01

Discusses two computer problem solving programs: rule-based expert systems and decision analysis expert systems. Explores the application of expert systems to automated chemical analyses. Presents six factors to consider before using expert systems. (MVL)

Shaping beliefs in experimental markets for expert services: Guilt aversion and the impact of promises and money-burning options☆☆☆

Science.gov (United States)

Beck, Adrian; Kerschbamer, Rudolf; Qiu, Jianying; Sutter, Matthias

2013-01-01

In a credence goods game with an expert and a consumer, we study experimentally the impact of two devices that are predicted to induce consumer-friendly behavior if the expert has a propensity to feel guilty when he believes that he violates the consumerʼs payoff expectations: (i) an opportunity for the expert to make a non-binding promise; and (ii) an opportunity for the consumer to burn money. In belief-based guilt aversion theory the first opportunity shapes an expertʼs behavior if an appropriate promise is made and if it is expected to be believed by the consumer; by contrast, the second opportunity might change behavior even though this option is never used along the predicted path. Experimental results confirm the behavioral relevance of (i) but fail to confirm (ii). PMID:24003266

Expert and novice categorization of introductory physics problems

Science.gov (United States)

Wolf, Steven Frederick

sets that discriminate experts from novices in a measurable way? We are describing a method to characterize problems along several dimensions, and then study the effectiveness of differently composed problem sets in differentiating experts from novices, using our analysis method. Both components of our study are based on an extensive experiment using a large problem set, which known physics experts and novices categorized according to the original experimental protocol. Both the size of the card set and the size of the sorter pool were larger than in comparable experiments. Based on our analysis method, we find that most of the variation in sorting outcome is not due to the sorter being an expert versus a novice, but rather due to an independent characteristic that we named "stacker" versus "spreader." The fact that the expert-novice distinction only accounts for a smaller amount of the variation may partly explain the frequent null-results when conducting these experiments. In order to study how the outcome depends on the original problem set, our problem set needed to be large so that we could determine how well experts and novices could be discriminated by considering both small subsets using a Monte Carlo approach and larger subsets using Simulated Annealing. This computationally intense study relied on our objective analysis method, as the large combinatorics did not allow for manual analysis of the outcomes from the subsets. We found that the number of questions required to accurately classify experts and novices could be surprisingly small so long as the problem set was carefully crafted to be composed of problems with particular pedagogical and contextual features. In order to discriminate experts from novices in a categorization task, it is important that the problem sets carefully consider three problem properties: The chapters that problems are in (the problems need to be from a wide spectrum of chapters to allow for the original "deep structure

Expert system application for prioritizing preventive actions for shift work: shift expert.

Science.gov (United States)

Esen, Hatice; Hatipoğlu, Tuğçen; Cihan, Ahmet; Fiğlali, Nilgün

2017-09-19

Shift patterns, work hours, work arrangements and worker motivations have increasingly become key factors for job performance. The main objective of this article is to design an expert system that identifies the negative effects of shift work and prioritizes mitigation efforts according to their importance in preventing these negative effects. The proposed expert system will be referred to as the shift expert. A thorough literature review is conducted to determine the effects of shift work on workers. Our work indicates that shift work is linked to demographic variables, sleepiness and fatigue, health and well-being, and social and domestic conditions. These parameters constitute the sections of a questionnaire designed to focus on 26 important issues related to shift work. The shift expert is then constructed to provide prevention advice at the individual and organizational levels, and it prioritizes this advice using a fuzzy analytic hierarchy process model, which considers comparison matrices provided by users during the prioritization process. An empirical study of 61 workers working on three rotating shifts is performed. After administering the questionnaires, the collected data are analyzed statistically, and then the shift expert produces individual and organizational recommendations for these workers.

Developments in REDES: The Rocket Engine Design Expert System

Science.gov (United States)

Davidian, Kenneth O.

1990-01-01

The Rocket Engine Design Expert System (REDES) was developed at NASA-Lewis to collect, automate, and perpetuate the existing expertise of performing a comprehensive rocket engine analysis and design. Currently, REDES uses the rigorous JANNAF methodology to analyze the performance of the thrust chamber and perform computational studies of liquid rocket engine problems. The following computer codes were included in REDES: a gas properties program named GASP; a nozzle design program named RAO; a regenerative cooling channel performance evaluation code named RTE; and the JANNAF standard liquid rocket engine performance prediction code TDK (including performance evaluation modules ODE, ODK, TDE, TDK, and BLM). Computational analyses are being conducted by REDES to provide solutions to liquid rocket engine thrust chamber problems. REDES was built in the Knowledge Engineering Environment (KEE) expert system shell and runs on a Sun 4/110 computer.

Automatic single questionnaire intensity (SQI, EMS98 scale) estimation using ranking models built on the existing BCSF database

Science.gov (United States)

Schlupp, A.; Sira, C.; Schmitt, K.; Schaming, M.

2013-12-01

In charge of intensity estimations in France, BCSF has collected and manually analyzed more than 47000 online individual macroseismic questionnaires since 2000 up to intensity VI. These macroseismic data allow us to estimate one SQI value (Single Questionnaire Intensity) for each form following the EMS98 scale. The reliability of the automatic intensity estimation is important as they are today used for automatic shakemaps communications and crisis management. Today, the automatic intensity estimation at BCSF is based on the direct use of thumbnails selected on a menu by the witnesses. Each thumbnail corresponds to an EMS-98 intensity value, allowing us to quickly issue an intensity map of the communal intensity by averaging the SQIs at each city. Afterwards an expert, to determine a definitive SQI, manually analyzes each form. This work is time consuming and not anymore suitable considering the increasing number of testimonies at BCSF. Nevertheless, it can take into account incoherent answers. We tested several automatic methods (USGS algorithm, Correlation coefficient, Thumbnails) (Sira et al. 2013, IASPEI) and compared them with 'expert' SQIs. These methods gave us medium score (between 50 to 60% of well SQI determined and 35 to 40% with plus one or minus one intensity degree). The best fit was observed with the thumbnails. Here, we present new approaches based on 3 statistical ranking methods as 1) Multinomial logistic regression model, 2) Discriminant analysis DISQUAL and 3) Support vector machines (SVMs). The two first methods are standard methods, while the third one is more recent. Theses methods could be applied because the BCSF has already in his database more then 47000 forms and because their questions and answers are well adapted for a statistical analysis. The ranking models could then be used as automatic method constrained on expert analysis. The performance of the automatic methods and the reliability of the estimated SQI can be evaluated thanks to

Earthquake Magnitude and Shaking Intensity Dependent Fragility Functions for Rapid Risk Assessment of Buildings

Directory of Open Access Journals (Sweden)

Marie-José Nollet

2018-01-01

Full Text Available An integrated web application, referred to as ER2 for rapid risk evaluator, is under development for a user-friendly seismic risk assessment by the non-expert public safety community. The assessment of likely negative consequences is based on pre-populated databases of seismic, building inventory and vulnerability parameters. To further accelerate the computation for near real-time analyses, implicit building fragility curves were developed as functions of the magnitude and the intensity of the seismic shaking defined with a single intensity measure, input spectral acceleration at 1.0 s implicitly considering the epicentral distance and local soil conditions. Damage probabilities were compared with those obtained with the standard fragility functions explicitly considering epicentral distances and local site classes in addition to the earthquake magnitudes and respective intensity of the seismic shaking. Different seismic scenarios were considered first for 53 building classes common in Eastern Canada, and then a reduced number of 24 combined building classes was proposed. Comparison of results indicate that the damage predictions with implicit fragility functions for short (M ≤ 5.5 and medium strong motion duration (5.5 < M ≤ 7.5 show low variation with distance and soil class, with average error of less than 3.6%.

How is intensive care reimbursed?

DEFF Research Database (Denmark)

Bittner, Martin-Immanuel; Donnelly, Maria; van Zanten, Arthur Rh

2013-01-01

Reimbursement schemes in intensive care are more complex than in other areas of healthcare, due to special procedures and high care needs. Knowledge regarding the principles of functioning in other countries can lead to increased understanding and awareness of potential for improvement. This can...... be achieved through mutual exchange of solutions found in other countries. In this review, experts from eight European countries explain their respective intensive care unit reimbursement schemes. Important conclusions include the apparent differences in the countries' reimbursement schemes---despite all...... of them originating from a DRG system, the high degree of complexity found, and the difficulties faced in several countries when collecting the data for this collaborative work. This review has been designed to help the intensivist clinician and researcher to understanding neighbouring countries...

Real-time expert systems and deep knowledge models

International Nuclear Information System (INIS)

Felkel, L.

1990-01-01

To guide operators in normal and disturbed plant conditions expert systems are feasible. These, however, must be on-line and real-time systems. The knowledge contained in such a system cannot be represented in a 'classical' role-based manner. The paper describes problems and solutions with regard to process reference models as these are important in order to provide so-called deep-knowledge for the operators. The system described is being implemented and is meant to support both diagnosis and prediction

Intensive Intervention Practice Guide: Explicit Instruction in Reading Comprehension for Students with Autism Spectrum Disorder

Science.gov (United States)

Braun, Gina; Austin, Christy; Ledbetter-Cho, Katherine

2017-01-01

The National Center for Leadership in Intensive Intervention (NCLII), a consortium funded by the Office of Special Education Programs (OSEP), prepares special education leaders to become experts in research on intensive intervention for students with disabilities who have persistent and severe academic (e.g., reading and math) and behavioral…

Upper arm elevation and repetitive shoulder movements: a general population job exposure matrix based on expert ratings and technical measurements.

Science.gov (United States)

Dalbøge, Annett; Hansson, Gert-Åke; Frost, Poul; Andersen, Johan Hviid; Heilskov-Hansen, Thomas; Svendsen, Susanne Wulff

2016-08-01

We recently constructed a general population job exposure matrix (JEM), The Shoulder JEM, based on expert ratings. The overall aim of this study was to convert expert-rated job exposures for upper arm elevation and repetitive shoulder movements to measurement scales. The Shoulder JEM covers all Danish occupational titles, divided into 172 job groups. For 36 of these job groups, we obtained technical measurements (inclinometry) of upper arm elevation and repetitive shoulder movements. To validate the expert-rated job exposures against the measured job exposures, we used Spearman rank correlations and the explained variance[Formula: see text] according to linear regression analyses (36 job groups). We used the linear regression equations to convert the expert-rated job exposures for all 172 job groups into predicted measured job exposures. Bland-Altman analyses were used to assess the agreement between the predicted and measured job exposures. The Spearman rank correlations were 0.63 for upper arm elevation and 0.64 for repetitive shoulder movements. The expert-rated job exposures explained 64% and 41% of the variance of the measured job exposures, respectively. The corresponding calibration equations were y=0.5%time+0.16×expert rating and y=27°/s+0.47×expert rating. The mean differences between predicted and measured job exposures were zero due to calibration; the 95% limits of agreement were ±2.9% time for upper arm elevation >90° and ±33°/s for repetitive shoulder movements. The updated Shoulder JEM can be used to present exposure-response relationships on measurement scales. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Classification of Word Levels with Usage Frequency, Expert Opinions and Machine Learning

Science.gov (United States)

Sohsah, Gihad N.; Ünal, Muhammed Esad; Güzey, Onur

2015-01-01

Educational applications for language teaching can utilize the language levels of words to target proficiency levels of students. This paper and the accompanying data provide a methodology for making educational standard-aligned language-level predictions for all English words. The methodology involves expert opinions on language levels and…

On the use of the analytic hierarchy process in the aggregation of expert judgments

International Nuclear Information System (INIS)

Zio, E.

1996-01-01

Expert judgments are involved in many aspects of scientific research, either formally or informally. In order to combine the different opinions elicited, simple aggregation methods have often been used with the result that expert biases, interexpert dependencies and other factors which might affect the judgments of the experts are often ignored. A more comprehensive approach, based on the analytic hierarchy process, is proposed in this paper to account for the large variety of factors influencing the experts. A structured hierarchy is constructed to decompose the overall problem in the elementary factors that can influence the expert's judgements. The importance of the different elements of the hierarchy is then assessed by pairwise comparison. The overall approach is simple, presents a systematic character and offers a good degree of flexibility. The approach provides the decision maker with a tool to quantitatively measure the significance of the judgments provided by the different experts involved in the elicitation. The resulting values can be used as weights in an aggregation scheme such as, for example, the simple weighted averaging scheme. Two applications of the approach are presented with reference to case studies of formal expert judgment elicitation previously analyzed in literature: the elicitation of the pressure increment in the containment building of the Sequoyah nuclear power plant following reactor vessel breach, and the prediction of the future changes in precipitation in the vicinity of Yucca Mountain

Investigation of Perceptual-Motor Behavior Across the Expert Athlete to Disabled Patient Skill Continuum can Advance Theory and Practical Application.

Science.gov (United States)

Müller, Sean; Vallence, Ann-Maree; Winstein, Carolee

2017-12-14

A framework is presented of how theoretical predictions can be tested across the expert athlete to disabled patient skill continuum. Common-coding theory is used as the exemplar to discuss sensory and motor system contributions to perceptual-motor behavior. Behavioral and neural studies investigating expert athletes and patients recovering from cerebral stroke are reviewed. They provide evidence of bi-directional contributions of visual and motor systems to perceptual-motor behavior. Majority of this research is focused on perceptual-motor performance or learning, with less on transfer. The field is ripe for research designed to test theoretical predictions across the expert athlete to disabled patient skill continuum. Our view has implications for theory and practice in sports science, physical education, and rehabilitation.

Experts in science and society

CERN Document Server

Gigerenzer, Gerd

2004-01-01

In today's complex world, we have come to rely increasingly on those who have expertise in specific areas and can bring their knowledge to bear on crucial social, political and scientific questions. Taking the viewpoint that experts are consulted when there is something important at stake for an individual, a group, or society at large, Experts in Science and Society explores expertise as a relational concept. How do experts balance their commitment to science with that to society? How does a society actually determine that a person has expertise? What personal traits are valued in an expert? From where does the expert derive authority? What makes new forms of expertise emerge? These and related questions are addressed from a wide range of areas in order to be inclusive, as well as to demonstrate similarities across areas. Likewise, in order to be culturally comparative, this volume includes examples and discussions of experts in different countries and even in different time periods. The topics include the r...

Expert system in PNC, 5

International Nuclear Information System (INIS)

Tobita, Yoshimasa; Yamaguchi, Takashi; Matsumoto, Mitsuo; Ono, Kiyoshi.

1990-01-01

The computer code system which can evaluate the mass balance and cycle cost in nuclear fuel cycle has been developing a PNC using an artificial intelligence technique. This system is composed of the expert system, data base and analysis codes. The expert system is the most important one in the system and the content of the expert system is explained in this paper. The expert system has the three functions. The first is the function of understanding the meaning of user's questions by natural language, the second is the function of selecting the best way to solve the problem given by the user using the knowledge which is already installed in the system, and the last is the function of answering the questions. The knowledge of the experts installed in the expert system is represented by the frame-type rules. Therefore, the knowledge will be simply added to the system, and consequently the system will be easily extended. (author)

How would peak rainfall intensity affect runoff predictions using conceptual water balance models?

Directory of Open Access Journals (Sweden)

B. Yu

2015-06-01

Full Text Available Most hydrological models use continuous daily precipitation and potential evapotranspiration for streamflow estimation. With the projected increase in mean surface temperature, hydrological processes are set to intensify irrespective of the underlying changes to the mean precipitation. The effect of an increase in rainfall intensity on the long-term water balance is, however, not adequately accounted for in the commonly used hydrological models. This study follows from a previous comparative analysis of a non-stationary daily series of stream flow of a forested watershed (River Rimbaud in the French Alps (area = 1.478 km2 (1966–2006. Non-stationarity in the recorded stream flow occurred as a result of a severe wild fire in 1990. Two daily models (AWBM and SimHyd were initially calibrated for each of three distinct phases in relation to the well documented land disturbance. At the daily and monthly time scales, both models performed satisfactorily with the Nash–Sutcliffe coefficient of efficiency (NSE varying from 0.77 to 0.92. When aggregated to the annual time scale, both models underestimated the flow by about 22% with a reduced NSE at about 0.71. Exploratory data analysis was undertaken to relate daily peak hourly rainfall intensity to the discrepancy between the observed and modelled daily runoff amount. Preliminary results show that the effect of peak hourly rainfall intensity on runoff prediction is insignificant, and model performance is unlikely to improve when peak daily precipitation is included. Trend analysis indicated that the large decrease of precipitation when daily precipitation amount exceeded 10–20 mm may have contributed greatly to the decrease in stream flow of this forested watershed.

An effort to improve track and intensity prediction of tropical cyclones through vortex initialization in NCUM-global model

Science.gov (United States)

Singh, Vivek; Routray, A.; Mallick, Swapan; George, John P.; Rajagopal, E. N.

2016-05-01

Tropical cyclones (TCs) have strong impact on socio-economic conditions of the countries like India, Bangladesh and Myanmar owing to its awful devastating power. This brings in the need of precise forecasting system to predict the tracks and intensities of TCs accurately well in advance. However, it has been a great challenge for major operational meteorological centers over the years. Genesis of TCs over data sparse warm Tropical Ocean adds more difficulty to this. Weak and misplaced vortices at initial time are one of the prime sources of track and intensity errors in the Numerical Weather Prediction (NWP) models. Many previous studies have reported the forecast skill of track and intensity of TC improved due to the assimilation of satellite data along with vortex initialization (VI). Keeping this in mind, an attempt has been made to investigate the impact of vortex initialization for simulation of TC using UK-Met office global model, operational at NCMRWF (NCUM). This assessment is carried out by taking the case of a extremely severe cyclonic storm "Chapala" that occurred over Arabian Sea (AS) from 28th October to 3rd November 2015. Two numerical experiments viz. Vort-GTS (Assimilation of GTS observations with VI) and Vort-RAD (Same as Vort-GTS with assimilation of satellite data) are carried out. This vortex initialization study in NCUM model is first of its type over North Indian Ocean (NIO). The model simulation of TC is carried out with five different initial conditions through 24 hour cycles for both the experiments. The results indicate that the vortex initialization with assimilation of satellite data has a positive impact on the track and intensity forecast, landfall time and position error of the TCs.

An abnormal event advisory expert system prototype for reactor operators

International Nuclear Information System (INIS)

Hance, D.C.

1989-01-01

Nuclear plant operators must respond correctly during abnormal conditions in the presence of dynamic and potentially overwhelming volumes of information. For this reason, considerable effort has been directed toward the development of nuclear plant operator aids using artificial intelligence techniques. The objective of such systems is to diagnose abnormal conditions within the plant, possibly predict consequences, and advise the operators of corrective actions in a timely manner. The objective of the work is the development of a prototype expert system to diagnose abnormal events at a nuclear power plant and advise plant operators of the event and applicable procedures in an on-line mode. The major difference between this effort and previous work is the use of plant operating procedures as a knowledge source and as an integral part of the advice provided by the expert system. The acceptance by utilities of expert systems as operator aids requires that such systems be compatible with the regulatory environment and provide economic benefits. For this reason, commercially viable operator aid systems developed in the near future must complement existing plant procedures rather than reach beyond them in a revolutionary manner. A knowledge source is the resource providing facts and relationships that are coded into the expert system program. In this case, the primary source of knowledge is a set of selected abnormal operating procedures for a modern Westinghouse pressurized water reactor

Experts on public trial

DEFF Research Database (Denmark)

Blok, Anders

2007-01-01

a case study of the May 2003 Danish consensus conference on environmental economics as a policy tool, the article reflects on the politics of expert authority permeating practices of public participation. Adopting concepts from the sociology of scientific knowledge (SSK), the conference is seen......-than-successful defense in the citizen perspective. Further, consensus conferences are viewed alternatively as "expert dissent conferences," serving to disclose a multiplicity of expert commitments. From this perspective, some challenges for democratizing expertise through future exercises in public participation...

The development of a quality prediction system for aluminum laser welding to measure plasma intensity using photodiodes

Energy Technology Data Exchange (ETDEWEB)

Yu, Ji Young [Technical Research Center, Hyundai Steel Company, Dangjin (Korea, Republic of); Sohn, Yong Ho [Dept. of Materials Science and Engineering, University of Central Florida, Orlando (United States); Park, Young Whan; Kwak, Jae Seob [Dept. of Mechanical Engineering, Pukyong National University, Busan (Korea, Republic of)

2016-10-15

Lightweight metals have been used to manufacture the body panels of cars to reduce the weight of car bodies. Typically, aluminum sheets are welded together, with a focus on weld quality assurance. A weld quality prediction system for the laser welding of aluminum was developed in this research to maximize welding production. The behavior of the plasma was also analyzed, dependent on various welding conditions. The light intensity of the plasma was altered with heat input and wire feed rate conditions, and the strength of the weld and sensor signals correlated closely for this heat input condition. Using these characteristics, a new algorithm and program were developed to evaluate the weld quality. The design involves a combinatory algorithm using a neural network model for the prediction of tensile strength from measured signals and a fuzzy multi-feature pattern recognition algorithm for the weld quality classification to improve predictability of the system.

The development of a quality prediction system for aluminum laser welding to measure plasma intensity using photodiodes

International Nuclear Information System (INIS)

Yu, Ji Young; Sohn, Yong Ho; Park, Young Whan; Kwak, Jae Seob

2016-01-01

Lightweight metals have been used to manufacture the body panels of cars to reduce the weight of car bodies. Typically, aluminum sheets are welded together, with a focus on weld quality assurance. A weld quality prediction system for the laser welding of aluminum was developed in this research to maximize welding production. The behavior of the plasma was also analyzed, dependent on various welding conditions. The light intensity of the plasma was altered with heat input and wire feed rate conditions, and the strength of the weld and sensor signals correlated closely for this heat input condition. Using these characteristics, a new algorithm and program were developed to evaluate the weld quality. The design involves a combinatory algorithm using a neural network model for the prediction of tensile strength from measured signals and a fuzzy multi-feature pattern recognition algorithm for the weld quality classification to improve predictability of the system

Reflection group on 'Expert Culture'

International Nuclear Information System (INIS)

Eggermont, G.

2000-01-01

As part of SCK-CEN's social sciences and humanities programme, a reflection group on 'Expert Culture' was established. The objectives of the reflection group are: (1) to clarify the role of SCK-CEN experts; (2) to clarify the new role of expertise in the evolving context of risk society; (3) to confront external views and internal SCK-CEN experiences on expert culture; (4) to improve trust building of experts and credibility of SCK-CEN as a nuclear actor in society; (5) to develop a draft for a deontological code; (6) to integrate the approach in training on assertivity and communication; (7) to create an output for a topical day on the subject of expert culture. The programme, achievements and perspectives of the refection group are summarised

PSG-EXPERT. An expert system for the diagnosis of sleep disorders.

Science.gov (United States)

Fred, A; Filipe, J; Partinen, M; Paiva, T

2000-01-01

This paper describes PSG-EXPERT, an expert system in the domain of sleep disorders exploring polysomnographic data. The developed software tool is addressed from two points of view: (1)--as an integrated environment for the development of diagnosis-oriented expert systems; (2)--as an auxiliary diagnosis tool in the particular domain of sleep disorders. Developed over a Windows platform, this software tool extends one of the most popular shells--CLIPS (C Language Integrated Production System) with the following features: backward chaining engine; graph-based explanation facilities; knowledge editor including a fuzzy fact editor and a rules editor, with facts-rules integrity checking; belief revision mechanism; built-in case generator and validation module. It therefore provides graphical support for knowledge acquisition, edition, explanation and validation. From an application domain point of view, PSG-Expert is an auxiliary diagnosis system for sleep disorders based on polysomnographic data, that aims at assisting the medical expert in his diagnosis task by providing automatic analysis of polysomnographic data, summarising the results of this analysis in terms of a report of major findings and possible diagnosis consistent with the polysomnographic data. Sleep disorders classification follows the International Classification of Sleep Disorders. Major features of the system include: browsing on patients data records; structured navigation on Sleep Disorders descriptions according to ASDA definitions; internet links to related pages; diagnosis consistent with polysomnographic data; graphical user-interface including graph-based explanatory facilities; uncertainty modelling and belief revision; production of reports; connection to remote databases.

Expert Systems: An Overview for Teacher-Librarians.

Science.gov (United States)

Orwig, Gary; Barron, Ann

1992-01-01

Provides an overview of expert systems for teacher librarians. Highlights include artificial intelligence and expert systems; the development of the MYCIN medical expert system; rule-based expert systems; the use of expert system shells to develop a specific system; and how to select an appropriate application for an expert system. (11 references)…

Accuracy and interobserver agreement between MR-non-expert radiologists and MR-experts in reading MRI for suspected appendicitis

Energy Technology Data Exchange (ETDEWEB)

Leeuwenburgh, Marjolein M.N., E-mail: m.m.leeuwenburgh@amc.uva.nl [Department of Surgery, Academic Medical Center, University of Amsterdam (Netherlands); Department of Radiology, Academic Medical Center, University of Amsterdam (Netherlands); Wiarda, Bart M. [Department of Radiology, Alkmaar Medical Center, Alkmaar (Netherlands); Jensch, Sebastiaan [Department of Radiology, Sint Lucas Andreas Hospital, Amsterdam (Netherlands); Wouter van Es, H. [Department of Radiology, Sint Antonius Hospital, Nieuwegein (Netherlands); Stockmann, Hein B.A.C. [Department of Surgery, Kennemer Gasthuis, Haarlem (Netherlands); Gratama, Jan Willem C. [Department of Radiology, Gelre Hospitals, Apeldoorn (Netherlands); Cobben, Lodewijk P.J. [Department of Radiology, Haaglanden Medical Center, Leidschendam (Netherlands); Bossuyt, Patrick M.M. [Department of Clinical Epidemiology, Academic Medical Center, University of Amsterdam (Netherlands); Boermeester, Marja A. [Department of Surgery, Academic Medical Center, University of Amsterdam (Netherlands); Stoker, Jaap [Department of Radiology, Academic Medical Center, University of Amsterdam (Netherlands)

2014-01-15

Objective: To compare accuracy and interobserver agreement between radiologists with limited experience in the evaluation of abdominal MRI (non-experts), and radiologists with longer MR reading experience (experts), in reading MRI in patients with suspected appendicitis. Methods: MR imaging was performed in 223 adult patients with suspected appendicitis and read independently by two members of a team of eight MR-inexperienced radiologists, who were trained with 100 MR examinations previous to this study (non-expert reading). Expert reading was performed by two radiologists with a larger abdominal MR experience (>500 examinations) in consensus. A final diagnosis was assigned after three months based on all available information, except MRI findings. We estimated MRI sensitivity and specificity for appendicitis and for all urgent diagnoses separately. Interobserver agreement was evaluated using kappa statistics. Results: Urgent diagnoses were assigned to 147 of 223 patients; 117 had appendicitis. Sensitivity for appendicitis was 0.89 by MR-non-expert radiologists and 0.97 in MR-expert reading (p = 0.01). Specificity was 0.83 for MR-non-experts versus 0.93 for MR-expert reading (p = 0.002). MR-experts and MR-non-experts agreed on appendicitis in 89% of cases (kappa 0.78). Accuracy in detecting urgent diagnoses was significantly lower in MR-non-experts compared to MR-expert reading: sensitivity 0.84 versus 0.95 (p < 0.001) and specificity 0.71 versus 0.82 (p = 0.03), respectively. Agreement on urgent diagnoses was 83% (kappa 0.63). Conclusion: MR-non-experts have sufficient sensitivity in reading MRI in patients with suspected appendicitis, with good agreement with MR-expert reading, but accuracy of MR-expert reading was higher.

Accuracy and interobserver agreement between MR-non-expert radiologists and MR-experts in reading MRI for suspected appendicitis

International Nuclear Information System (INIS)

Leeuwenburgh, Marjolein M.N.; Wiarda, Bart M.; Jensch, Sebastiaan; Wouter van Es, H.; Stockmann, Hein B.A.C.; Gratama, Jan Willem C.; Cobben, Lodewijk P.J.; Bossuyt, Patrick M.M.; Boermeester, Marja A.; Stoker, Jaap

2014-01-01

Objective: To compare accuracy and interobserver agreement between radiologists with limited experience in the evaluation of abdominal MRI (non-experts), and radiologists with longer MR reading experience (experts), in reading MRI in patients with suspected appendicitis. Methods: MR imaging was performed in 223 adult patients with suspected appendicitis and read independently by two members of a team of eight MR-inexperienced radiologists, who were trained with 100 MR examinations previous to this study (non-expert reading). Expert reading was performed by two radiologists with a larger abdominal MR experience (>500 examinations) in consensus. A final diagnosis was assigned after three months based on all available information, except MRI findings. We estimated MRI sensitivity and specificity for appendicitis and for all urgent diagnoses separately. Interobserver agreement was evaluated using kappa statistics. Results: Urgent diagnoses were assigned to 147 of 223 patients; 117 had appendicitis. Sensitivity for appendicitis was 0.89 by MR-non-expert radiologists and 0.97 in MR-expert reading (p = 0.01). Specificity was 0.83 for MR-non-experts versus 0.93 for MR-expert reading (p = 0.002). MR-experts and MR-non-experts agreed on appendicitis in 89% of cases (kappa 0.78). Accuracy in detecting urgent diagnoses was significantly lower in MR-non-experts compared to MR-expert reading: sensitivity 0.84 versus 0.95 (p < 0.001) and specificity 0.71 versus 0.82 (p = 0.03), respectively. Agreement on urgent diagnoses was 83% (kappa 0.63). Conclusion: MR-non-experts have sufficient sensitivity in reading MRI in patients with suspected appendicitis, with good agreement with MR-expert reading, but accuracy of MR-expert reading was higher

Holistic processing of musical notation: Dissociating failures of selective attention in experts and novices.

Science.gov (United States)

Wong, Yetta Kwailing; Gauthier, Isabel

2010-12-01

Holistic processing (i.e., the tendency to process objects as wholes) is associated with face perception and also with expertise individuating novel objects. Surprisingly, recent work also reveals holistic effects in novice observers. It is unclear whether the same mechanisms support holistic effects in experts and in novices. In the present study, we measured holistic processing of music sequences using a selective attention task in participants who vary in music-reading expertise. We found that holistic effects were strategic in novices but were relatively automatic in experts. Correlational analyses revealed that individual holistic effects were predicted by both individual music-reading ability and neural responses for musical notation in the right fusiform face area (rFFA), but in opposite directions for experts and novices, suggesting that holistic effects in the two groups may be of different natures. To characterize expert perception, it is important not only to measure the tendency to process objects as wholes, but also to test whether this effect is dependent on task constraints.

Expert system for assisting the repair operations on the control racks of the control rods assembly in a 900 MW PWR type reactor

International Nuclear Information System (INIS)

Monnier, B.; Doutre, J.L.; Franco, A.

1990-01-01

The expert system presented was developed for assisting the repair operations on the control equipment of the control rod assembly in a PWR type reactor. The expert system allows the representation of expert knowledge and diagnostic reasoning. The objective of the expert system is to achieve the most precise diagnostic and localizing of the breakdown elements, by processing the data acquired during breakdown. The development steps, the structure and the applications of the expert system are summarized. The expert system operates in an IBM PC equipped with a AMAIA 8 Mo card. A time schedule of 18 months is predicted [fr

Functional MRI reveals expert-novice differences during sport-related anticipation.

Science.gov (United States)

Wright, Michael J; Bishop, Daniel T; Jackson, Robin C; Abernethy, Bruce

2010-01-27

We examined the effect of expertise on cortical activation during sports anticipation using functional MRI. In experiment 1, recreational players predicted badminton stroke direction and the pattern of active clusters was consistent with a proposed perception-of-action network. This pattern was not replicated in a stimulus-matched, action-unrelated control task. In experiment 2, players of three different skill levels anticipated stroke direction from clips occluded either 160 ms before or 80 ms after racquet-shuttle contact. Early-occluded sequences produced more activation than late-occluded sequences overall, in most cortical regions of interest, but experts showed an additional enhancement in medial, dorsolateral and ventrolateral frontal cortex. Anticipation in open-skill sports engages cortical areas integral to observing and understanding others' actions; such activity is enhanced in experts.

IAEA Expert Team Returns from Iran

International Nuclear Information System (INIS)

2012-01-01

Full text: A senior IAEA expert team is returning from Iran after two days of discussions with Iranian officials held on 20 and 21 February 2012. The meeting followed previous discussions held on 29 to 31 January 2012. During both the first and second round of discussions, the Agency team requested access to the military site at Parchin. Iran did not grant permission for this visit to take place. Intensive efforts were made to reach agreement on a document facilitating the clarification of unresolved issues in connection with Iran's nuclear programme, particularly those relating to possible military dimensions. Unfortunately, agreement was not reached on this document. 'It is disappointing that Iran did not accept our request to visit Parchin during the first or second meetings', IAEA Director General Yukiya Amano said. 'We engaged in a constructive spirit, but no agreement was reached'. (IAEA)

Intelligent programs-expert systems

Energy Technology Data Exchange (ETDEWEB)

Gledhill, V X

1982-01-01

In recent years, computer scientists have developed what are called expert systems. These programs have three fundamental components: a knowledge base, which changes with experience; an inference engine which enables the program to make decisions; and an interface that allows the program to communicate with the person using the system. Expert systems have been developed successfully in areas such as medical diagnosis, geology, and computer maintenance. This paper describes the evolution and basic principles of expert systems and give some examples of their use.

Experts correctly describe demography associated with historical decline of the endangered Indiana bat, but not recent period of stationarity

Science.gov (United States)

Thogmartin, Wayne E.; Sanders-Reed, Carol A.; Szymanski, Jennifer; Pruitt, Lori; Runge, Michael C.

2017-01-01

Demographic characteristics of bats are often insufficiently described for modeling populations. In data poor situations, experts are often relied upon for characterizing ecological systems. In concert with the development of a matrix model describing Indiana bat (Myotis sodalis) demography, we elicited estimates for parameterizing this model from 12 experts. We conducted this elicitation in two stages, requesting expert values for 12 demographic rates. These rates were adult and juvenile seasonal (winter, summer, fall) survival rates, pup survival in fall, and propensity and success at breeding. Experts were most in agreement about adult fall survival (3% Coefficient of Variation) and least in agreement about propensity of juveniles to breed (37% CV). The experts showed greater concordance for adult ( mean CV, adult = 6.2%) than for juvenile parameters ( mean CV, juvenile = 16.4%), and slightly more agreement for survival (mean CV, survival = 9.8%) compared to reproductive rates ( mean CV, reproduction = 15.1%). However, survival and reproduction were negatively and positively biased, respectively, relative to a stationary dynamic. Despite the species exhibiting near stationary dynamics for two decades prior to the onset of a potential extinction-causing agent, white-nose syndrome, expert estimates indicated a population decline of -11% per year (95% CI = -2%, -20%); quasi-extinction was predicted within a century ( mean = 61 years to QE, range = 32, 97) by 10 of the 12 experts. Were we to use these expert estimates in our modeling efforts, we would have errantly trained our models to a rapidly declining demography asymptomatic of recent demographic behavior. While experts are sometimes the only source of information, a clear understanding of the temporal and spatial context of the information being elicited is necessary to guard against wayward predictions.

Loading Intensity Prediction by Velocity and the OMNI-RES 0-10 Scale in Bench Press.

Science.gov (United States)

Naclerio, Fernando; Larumbe-Zabala, Eneko

2017-02-01

Naclerio, F and Larumbe-Zabala, E. Loading intensity prediction by velocity and the OMNI-RES 0-10 scale in bench press. J Strength Cond Res 32(1): 323-329, 2017-This study examined the possibility of using movement velocity and the perceived exertion as indicators of relative load in the bench press (BP) exercise. A total of 308 young, healthy, resistance trained athletes (242 men and 66 women) performed a progressive strength test up to the one repetition maximum for the individual determination of the full load-velocity and load-exertion relationships. Longitudinal regression models were used to predict the relative load from the average velocity (AV) and the OMNI-Resistance Exercise Scales (OMNI-RES 0-10 scale), considering sets as the time-related variable. Load associated with the AV and the OMNI-RES 0-10 scale value expressed after performing a set of 1-3 repetitions were used to construct 2 adjusted predictive equations: Relative load = 107.75 - 62.97 × average velocity; and Relative load = 29.03 + 7.26 × OMNI-RES 0-10 scale value. The 2 models were capable of estimating the relative load with an accuracy of 84 and 93%, respectively. These findings confirm the ability of the 2 calculated regression models, using load-velocity and load-exertion from the OMNI-RES 0-10 scale, to accurately predict strength performance in BP.

A demonstration of expert systems applications in transportation engineering : volume I, transportation engineers and expert systems.

Science.gov (United States)

1987-01-01

Expert systems, a branch of artificial-intelligence studies, is introduced with a view to its relevance in transportation engineering. Knowledge engineering, the process of building expert systems or transferring knowledge from human experts to compu...

Everyday food is safe! Consumer versus expert hazard identification of two novel foods

DEFF Research Database (Denmark)

Hagemann, Kit

Novel foods have been the object of intense public debate in recent years. Despite efforts to communicate the outcomes of risk assessments to consumers, public confidence in the management of potential risks associated has been low. Various reasons behind this has identified, chiefly a disagreement...... in terms of detailed chains of cause-effect relationships, but consumers used abstract concepts when they reasoned about biological processes. Outcome uncertainty played an enormous role in consumers' perception of risk, which was in contrast to experts, who often declined to elaborate on consequences...... between technical experts and consumers e.g. over the nature of the hazards on which risk assessments should focus and perceptions of insufficient openness about uncertainties in risk assessment. The consumers part of the EU-project, NOFORISK, investigate the disagreement by comparing laypeople...

TU Delft expert judgment data base

International Nuclear Information System (INIS)

Cooke, Roger M.; Goossens, Louis L.H.J.

2008-01-01

We review the applications of structured expert judgment uncertainty quantification using the 'classical model' developed at the Delft University of Technology over the last 17 years [Cooke RM. Experts in uncertainty. Oxford: Oxford University Press; 1991; Expert judgment study on atmospheric dispersion and deposition. Report Faculty of Technical Mathematics and Informatics No.01-81, Delft University of Technology; 1991]. These involve 45 expert panels, performed under contract with problem owners who reviewed and approved the results. With a few exceptions, all these applications involved the use of seed variables; that is, variables from the experts' area of expertise for which the true values are available post hoc. Seed variables are used to (1) measure expert performance, (2) enable performance-based weighted combination of experts' distributions, and (3) evaluate and hopefully validate the resulting combination or 'decision maker'. This article reviews the classical model for structured expert judgment and the performance measures, reviews applications, comparing performance-based decision makers with 'equal weight' decision makers, and collects some lessons learned

Expert system technology for the military

International Nuclear Information System (INIS)

Franklin, J.E.; Carmody, C.L.; Buteau, B.L.; Keller, K.; Levitt, T.S.

1988-01-01

This paper is concerned with the applications of expert systems to complex military problems. A brief description of needs for expert systems in the military arena is given. A short tutorial on some of the elements of an expert system is found in Appendix I. An important aspect of expert systems concerns using uncertain information and ill-defined procedures. Many of the general techniques of dealing with uncertainty are described in Appendix II. These techniques include Bayesian certainty factors, Dempster-Shafer theory of uncertainty, and Zadeh's fuzzy set theory. The major portion of the paper addresses specific expert system examples such as resource allocation, identification of radar images, maintenance and troubleshooting of electronic equipment, and the interpretation and understanding of radar images. Extensions of expert systems to incorporate learning are examined in the context of military intelligence to determine the disposition, location, and intention of the adversary. The final application involves the use of distributed communicating cooperating expert systems for battle management. Finally, the future of expert systems and their evolving capabilities are discussed

A revised ground-motion and intensity interpolation scheme for shakemap

Science.gov (United States)

Worden, C.B.; Wald, D.J.; Allen, T.I.; Lin, K.; Garcia, D.; Cua, G.

2010-01-01

We describe a weighted-average approach for incorporating various types of data (observed peak ground motions and intensities and estimates from groundmotion prediction equations) into the ShakeMap ground motion and intensity mapping framework. This approach represents a fundamental revision of our existing ShakeMap methodology. In addition, the increased availability of near-real-time macroseismic intensity data, the development of newrelationships between intensity and peak ground motions, and new relationships to directly predict intensity from earthquake source information have facilitated the inclusion of intensity measurements directly into ShakeMap computations. Our approach allows for the combination of (1) direct observations (ground-motion measurements or reported intensities), (2) observations converted from intensity to ground motion (or vice versa), and (3) estimated ground motions and intensities from prediction equations or numerical models. Critically, each of the aforementioned data types must include an estimate of its uncertainties, including those caused by scaling the influence of observations to surrounding grid points and those associated with estimates given an unknown fault geometry. The ShakeMap ground-motion and intensity estimates are an uncertainty-weighted combination of these various data and estimates. A natural by-product of this interpolation process is an estimate of total uncertainty at each point on the map, which can be vital for comprehensive inventory loss calculations. We perform a number of tests to validate this new methodology and find that it produces a substantial improvement in the accuracy of ground-motion predictions over empirical prediction equations alone.

Expert systems: A 5-year perspective

International Nuclear Information System (INIS)

MacAllister, D.J.; Day, R.; McCormack, M.D.

1996-01-01

This paper gives an overview of a major integrated oil company's experience with artificial intelligence (AI) over the last 5 years, with an emphasis on expert systems. The authors chronicle the development of an AI group, including details on development tool selection, project selection strategies, potential pitfalls, and descriptions of several completed expert systems. Small expert systems produced by teams of petroleum technology experts and experienced expert system developers that are focused in well-defined technical areas have produced substantial benefits and accelerated petroleum technology transfer

Design of an expert system for the development and formulation of push-pull osmotic pump tablets containing poorly water-soluble drugs.

Science.gov (United States)

Zhang, Zhi-hong; Dong, Hong-ye; Peng, Bo; Liu, Hong-fei; Li, Chun-lei; Liang, Min; Pan, Wei-san

2011-05-30

The purpose of this article was to build an expert system for the development and formulation of push-pull osmotic pump tablets (PPOP). Hundreds of PPOP formulations were studied according to different poorly water-soluble drugs and pharmaceutical acceptable excipients. The knowledge base including database and rule base was built based on the reported results of hundreds of PPOP formulations containing different poorly water-soluble drugs and pharmaceutical excipients and the experiences available from other researchers. The prediction model of release behavior was built using back propagation (BP) neural network, which is good at nonlinear mapping and learning function. Formulation design model was established based on the prediction model of release behavior, which was the nucleus of the inference engine. Finally, the expert system program was constructed by VB.NET associating with SQL Server. Expert system is one of the most popular aspects in artificial intelligence. To date there is no expert system available for the formulation of controlled release dosage forms yet. Moreover, osmotic pump technology (OPT) is gradually getting consummate all over the world. It is meaningful to apply expert system on OPT. Famotidine, a water insoluble drug was chosen as the model drug to validate the applicability of the developed expert system. Copyright © 2011 Elsevier B.V. All rights reserved.

[Deontology of the medical expert].

Science.gov (United States)

Raszeja, S

1995-09-01

The authority of prosecuting organ to choose the expert, set his task and verify the following opinion is defined. The qualities of the medical expert and his duties are described, referring to: -his expertise; -his morality; -his ability to issue an independent (objective) opinion. Detailed rules, which can be ascribed to a specific medical expert's deontological code, are listed and explained.

Testing the Limits of Skill Transfer for Scrabble Experts in Behaviour and Brain

Directory of Open Access Journals (Sweden)

Sophia Van Hees

2016-11-01

Full Text Available We investigated transfer of the skills developed by competitive Scrabble players. Previous studies reported superior performance for Scrabble experts on the lexical decision task (LDT, suggesting near transfer of Scrabble skills. Here we investigated the potential for far transfer to a symbol decision task (SDT; in particular, transfer of enhanced long-term working memory for vertically presented stimuli. Our behavioural results showed no evidence for far transfer. Despite years of intensive practice, Scrabble experts were no faster and no more accurate than controls in the SDT. However, our fMRI and EEG data from the SDT suggest that the neural repertoire that Scrabble experts develop supports task performance even outside of the practised domain, in a non-linguistic context. The regions engaged during the SDT were different across groups: controls engaged temporal-frontal regions, whereas Scrabble experts engaged posterior visual and temporal-parietal regions. In Scrabble experts, activity related to Scrabble skill (anagramming scores included regions associated with visual-spatial processing and long-term working memory, and overlapped with regions previously shown to be associated with Scrabble expertise in the near transfer task (LDT. Analysis of source waveforms within these regions showed that participants with higher anagramming scores had larger P300 amplitudes, potentially reflecting greater working memory capacity, or less variability in the participants who perform the task more efficiently. Thus, the neuroimaging results provide evidence of brain transfer in the absence of behavioural transfer, providing new clues about the consequences of long-term training associated with competitive Scrabble expertise.

Expert systems: An overview

International Nuclear Information System (INIS)

Verdejo, F.

1985-01-01

The purpose of this article is to introduce readers to the basic principles of rule-based expert systems. Four topics are discussed in subsequent sections: (1) Definition; (2) Structure of an expert system; (3) State of the art and (4) Impact and future research. (orig.)

Validity and validation of expert (Q)SAR systems.

Science.gov (United States)

Hulzebos, E; Sijm, D; Traas, T; Posthumus, R; Maslankiewicz, L

2005-08-01

At a recent workshop in Setubal (Portugal) principles were drafted to assess the suitability of (quantitative) structure-activity relationships ((Q)SARs) for assessing the hazards and risks of chemicals. In the present study we applied some of the Setubal principles to test the validity of three (Q)SAR expert systems and validate the results. These principles include a mechanistic basis, the availability of a training set and validation. ECOSAR, BIOWIN and DEREK for Windows have a mechanistic or empirical basis. ECOSAR has a training set for each QSAR. For half of the structural fragments the number of chemicals in the training set is >4. Based on structural fragments and log Kow, ECOSAR uses linear regression to predict ecotoxicity. Validating ECOSAR for three 'valid' classes results in predictivity of > or = 64%. BIOWIN uses (non-)linear regressions to predict the probability of biodegradability based on fragments and molecular weight. It has a large training set and predicts non-ready biodegradability well. DEREK for Windows predictions are supported by a mechanistic rationale and literature references. The structural alerts in this program have been developed with a training set of positive and negative toxicity data. However, to support the prediction only a limited number of chemicals in the training set is presented to the user. DEREK for Windows predicts effects by 'if-then' reasoning. The program predicts best for mutagenicity and carcinogenicity. Each structural fragment in ECOSAR and DEREK for Windows needs to be evaluated and validated separately.

Expert opinion on landslide susceptibility elicted by probabilistic inversion from scenario rankings

Science.gov (United States)

Lee, Katy; Dashwood, Claire; Lark, Murray

2016-04-01

For many natural hazards the opinion of experts, with experience in assessing susceptibility under different circumstances, is a valuable source of information on which to base risk assessments. This is particularly important where incomplete process understanding, and limited data, limit the scope to predict susceptibility by mechanistic or statistical modelling. The expert has a tacit model of a system, based on their understanding of processes and their field experience. This model may vary in quality, depending on the experience of the expert. There is considerable interest in how one may elicit expert understanding by a process which is transparent and robust, to provide a basis for decision support. One approach is to provide experts with a set of scenarios, and then to ask them to rank small overlapping subsets of these with respect to susceptibility. Methods of probabilistic inversion have been used to compute susceptibility scores for each scenario, implicit in the expert ranking. It is also possible to model these scores as functions of measurable properties of the scenarios. This approach has been used to assess susceptibility of animal populations to invasive diseases, to assess risk to vulnerable marine environments and to assess the risk in hypothetical novel technologies for food production. We will present the results of a study in which a group of geologists with varying degrees of expertise in assessing landslide hazards were asked to rank sets of hypothetical simplified scenarios with respect to land slide susceptibility. We examine the consistency of their rankings and the importance of different properties of the scenarios in the tacit susceptibility model that their rankings implied. Our results suggest that this is a promising approach to the problem of how experts can communicate their tacit model of uncertain systems to those who want to make use of their expertise.

Preserving experience through expert systems

International Nuclear Information System (INIS)

Jelinek, J.B.; Weidman, S.H.

1989-01-01

Expert systems technology, one of the branches in the field of computerized artificial intelligence, has existed for >30 yr but only recently has been made available on commercially standard hardware and software platforms. An expert system can be defined as any method of encoding knowledge by representing that knowledge as a collection of facts or objects. Decisions are made by the expert program by obtaining data about the problem or situation and correlating encoded facts (knowledge) to the data until a conclusion can be reached. Such conclusions can be relayed to the end user as expert advice. Realizing the potential of this technology, General Electric (GE) Nuclear Energy (GENE) has initiated a development program in expert systems applications; this technology offers the potential for packaging, distributing, and preserving nuclear experience in a software form. The paper discusses application fields, effective applications, and knowledge acquisition and knowledge verification

Operational expert system applications in Canada

CERN Document Server

Suen, Ching Y

1992-01-01

This book is part of a new series on operational expert systems worldwide. Expert systems are now widely used in different parts of the world for various applications. The past four years have witnessed a steady growth in the development and deployment of expert systems in Canada. Research in this field has also gained considerable momentum during the past few years. However, the field of expert systems is still young in Canada. This book contains 13 chapters contributed by 31 experts from both universities and industries across Canada covering a wide range of applications related to electric

Planning intensive care unit design using computer simulation modeling: optimizing integration of clinical, operational, and architectural requirements.

Science.gov (United States)

OʼHara, Susan

2014-01-01

Nurses have increasingly been regarded as critical members of the planning team as architects recognize their knowledge and value. But the nurses' role as knowledge experts can be expanded to leading efforts to integrate the clinical, operational, and architectural expertise through simulation modeling. Simulation modeling allows for the optimal merge of multifactorial data to understand the current state of the intensive care unit and predict future states. Nurses can champion the simulation modeling process and reap the benefits of a cost-effective way to test new designs, processes, staffing models, and future programming trends prior to implementation. Simulation modeling is an evidence-based planning approach, a standard, for integrating the sciences with real client data, to offer solutions for improving patient care.

Expert Systems as Tools for Technical Communicators.

Science.gov (United States)

Grider, Daryl A.

1994-01-01

Discusses expertise, what an expert system is, what an expert system shell is, what expert systems can and cannot do, knowledge engineering and technical communicators, and planning and managing expert system projects. (SR)

The feasibility of using expert systems to cope with the complexity and extent of the indoor radon problem

International Nuclear Information System (INIS)

Raes, F.; Poffijn, A.; Eggermont, G.

1988-01-01

The main problems in predicting the average radon concentration in a single house are: (1) to obtain specific high resolution information about the house, and (2) to handle qualitative but relevant information. We introduce the idea of using an expert system to obtain high resolution data by interrogating the inhabitants about their house, as well as to interpret the qualitative information obtained in this way. To study the feasibility of this approach, a prototype expert system has been written which was given the obvious name Radon Expert System (RAES). RAES derives a radon index starting from information obtained from geological maps and other data bases. It subsequently refines this information and focusses on a single house by asking for information from the inhabitants. With the help of RAES, we interrogated the inhabitants of a number of houses where radon measurements had previously been performed. The correspondence between prediction and measurement is encouraging. (author)

An expert system for uranium exploration

International Nuclear Information System (INIS)

Chhipa, V.K.; Sengupta, M.

1989-01-01

Artificial intelligence is an emerging technology in the field of computer application. Expert systems have been developed to imitate human intelligence and reasoning process. Expert systems have much scope of application in the decision making process in mineral exploration as such decisions are highly subjective and expert opinions are very helpful. This paper presents a small expert system to analyze the reasoning process in exploring for uranium deposits in sandstone

Expert software for accident identification

International Nuclear Information System (INIS)

Dobnikar, M.; Nemec, T.; Muehleisen, A.

2003-01-01

Each type of an accident in a Nuclear Power Plant (NPP) causes immediately after the start of the accident variations of physical parameters that are typical for that type of the accident thus enabling its identification. Examples of these parameter are: decrease of reactor coolant system pressure, increase of radiation level in the containment, increase of pressure in the containment. An expert software enabling a fast preliminary identification of the type of the accident in Krsko NPP has been developed. As input data selected typical parameters from Emergency Response Data System (ERDS) of the Krsko NPP are used. Based on these parameters the expert software identifies the type of the accident and also provides the user with appropriate references (past analyses and other documentation of such an accident). The expert software is to be used as a support tool by an expert team that forms in case of an emergency at Slovenian Nuclear Safety Administration (SNSA) with the task to determine the cause of the accident, its most probable scenario and the source term. The expert software should provide initial identification of the event, while the final one is still to be made after appropriate assessment of the event by the expert group considering possibility of non-typical events, multiple causes, initial conditions, influences of operators' actions etc. The expert software can be also used as an educational/training tool and even as a simple database of available accident analyses. (author)

BWR recirculation pump diagnostic expert system

International Nuclear Information System (INIS)

Chiang, S.C.; Morimoto, C.N.; Torres, M.R.

2004-01-01

At General Electric (GE), an on-line expert system to support maintenance decisions for BWR recirculation pumps for nuclear power plants has been developed. This diagnostic expert system is an interactive on-line system that furnishes diagnostic information concerning BWR recirculation pump operational problems. It effectively provides the recirculation pump diagnostic expertise in the plant control room continuously 24 hours a day. The expert system is interfaced to an on-line monitoring system, which uses existing plant sensors to acquire non-safety related data in real time. The expert system correlates and evaluates process data and vibration data by applying expert rules to determine the condition of a BWR recirculation pump system by applying knowledge based rules. Any diagnosis will be automatically displayed, indicating which pump may have a problem, the category of the problem, and the degree of concern expressed by the validity index and color hierarchy. The rules incorporate the expert knowledge from various technical sources such as plant experience, engineering principles, and published reports. These rules are installed in IF-THEN formats and the resulting truth values are also expressed in fuzzy terms and a certainty factor called a validity index. This GE Recirculation Pump Expert System uses industry-standard software, hardware, and network access to provide flexible interfaces with other possible data acquisition systems. Gensym G2 Real-Time Expert System is used for the expert shell and provides the graphical user interface, knowledge base, and inference engine capabilities. (author)

Low intensity pulsed ultrasound (LIPUS) for bone healing: A clinical practice guideline

NARCIS (Netherlands)

R.W. Poolman (Rudolf); Agoritsas, T. (Thomas); Siemieniuk, R.A.C. (Reed A C); I. Harris (Ian); I.B. Schipper (Inger); Mollon, B. (Brent); Smith, M. (Maureen); Albin, A. (Alexandra); Nador, S. (Sally); Sasges, W. (Will); S. Schandelmaier; Lytvyn, L. (Lyubov); T. Kuijpers (Ton); Van Beers, L.W.A.H. (Loes W A H); M.H.J. Verhofstad (Michiel); P.O. Vandvik (Per)

2017-01-01

textabstractDoes low intensity pulsed ultrasound (LIPUS) accelerate recovery in adults and children who have experienced bone fractures or osteotomy (cutting of a bone)? An expert panel rapidly produced these recommendations based on a linked systematic review triggered by a large multi-centre

Trendwatch combining expert opinion

NARCIS (Netherlands)

Hendrix, E.M.T.; Kornelis, M.; Pegge, S.M.; Galen, van M.A.

2006-01-01

In this study, focus is on a systematic way to detect future changes in trends that may effect the dynamics in the agro-food sector, and on the combination of opinions of experts. For the combination of expert opinions, the usefulness of multilevel models is investigated. Bayesian data analysis is

Mapping on complex neutrosophic soft expert sets

Science.gov (United States)

Al-Quran, Ashraf; Hassan, Nasruddin

2018-04-01

We introduce the mapping on complex neutrosophic soft expert sets. Further, we investigated the basic operations and other related properties of complex neutrosophic soft expert image and complex neutrosophic soft expert inverse image of complex neutrosophic soft expert sets.

An expert system for microbiologically influenced corrosion

International Nuclear Information System (INIS)

Carney, C.E.; Licina, G.J.

1991-01-01

Microbiologically Influenced Corrosion (MIC) is a damage mechanism that can cause serious degradation of service water system components. MIC can be particularly insidious since damage can occur very quickly, even in environments otherwise resistant to corrosion. Plant operations or maintenance personnel or system engineers typically do not have sufficient expertise to predict when and where MIC may occur or what methods of treatment are effective. An expert system (MICPro) has been devised which provides a tool for utilities to predict where MIC will occur, which systems or components are most susceptible, how operating parameters may affect vulnerability, and how to implement corrective and preventative measures. The system is designed to be simple to use: required inputs are common system parameters and results are presented as numbers from 1 to 10 indicating the likelihood of damage due to the given input. In this paper the structure and operation of the system is described, and future refinements are discussed

An Investigation of Marketing via Mobile Devices - Attitudes of Croatian Marketing Experts

Directory of Open Access Journals (Sweden)

Damir Dobrinić

2008-06-01

Full Text Available Marketing activities supported by mobile devices offer great opportunities for direct communication with consumers without the barriers of time, place, location and other. This article explores opinions and expectations Croatian marketing experts have towards use of m-advertising and other available advertising media, where we take the perspective of marketing experts to predict the future of m-marketing and m-advertising in Croatia. The paper also discusses the relevance of m-advertising and investigates the future of m-marketing and m-advertising in Croatia. This research focuses mainly on understanding the potential and effectiveness of the use of mobile phones as a promotional medium, but we also try to recognize the level of concern of marketing experts associated with spam, relating to privacy intrusion and ethics components in m-advertising. Privacy and ethics concerns could create resistance to the adoption of m-advertising. Media selection becomes the most critical factor for the success of a promotional and advertising marketing campaign. Croatian experts still consider TV or newspapers the best way to reach a large number of potential consumers, but what are their expectations towards mobile advertising? To answer this question, we built a model that links attitudes towards advertising via classical media to the intention to use m-advertising.

Vulnerability of bridges to scour: insights from an international expert elicitation workshop

Science.gov (United States)

Lamb, Rob; Aspinall, Willy; Odbert, Henry; Wagener, Thorsten

2017-08-01

Scour (localised erosion) during flood events is one of the most significant threats to bridges over rivers and estuaries, and has been the cause of numerous bridge failures, with damaging consequences. Mitigation of the risk of bridges being damaged by scour is therefore important to many infrastructure owners, and is supported by industry guidance. Even after mitigation, some residual risk remains, though its extent is difficult to quantify because of the uncertainties inherent in the prediction of scour and the assessment of the scour risk. This paper summarises findings from an international expert workshop on bridge scour risk assessment that explores uncertainties about the vulnerability of bridges to scour. Two specialised structured elicitation methods were applied to explore the factors that experts in the field consider important when assessing scour risk and to derive pooled expert judgements of bridge failure probabilities that are conditional on a range of assumed scenarios describing flood event severity, bridge and watercourse types and risk mitigation protocols. The experts' judgements broadly align with industry good practice, but indicate significant uncertainty about quantitative estimates of bridge failure probabilities, reflecting the difficulty in assessing the residual risk of failure. The data and findings presented here could provide a useful context for the development of generic scour fragility models and their associated uncertainties.

Air-sea heat flux control on the Yellow Sea Cold Water Mass intensity and implications for its prediction

Science.gov (United States)

Zhu, Junying; Shi, Jie; Guo, Xinyu; Gao, Huiwang; Yao, Xiaohong

2018-01-01

The Yellow Sea Cold Water Mass (YSCWM), which occurs during summer in the central Yellow Sea, plays an important role in the hydrodynamic field, nutrient cycle and biological species. Based on water temperature observations during the summer from 1978 to 1998 in the western Yellow Sea, five specific YSCWM years were identified, including two strong years (1984 and 1985), two weak years (1989 and 1995) and one normal year (1992). Using a three-dimensional hydrodynamic model, the YSCWM formation processes in these five years were simulated and compared with observations. In general, the YSCWM began forming in spring, matured in summer and gradually disappeared in autumn of every year. The 8 °C isotherm was used to indicate the YSCWM boundary. The modelled YSCWM areas in the two strong years were approximately two times larger than those in the two weak years. Based on the simulations in the weak year of 1995, ten numerical experiments were performed to quantify the key factors influencing the YSCWM intensity by changing the initial water condition in the previous autumn, air-sea heat flux, wind, evaporation, precipitation and sea level pressure to those in the strong year of 1984, respectively. The results showed that the air-sea heat flux was the dominant factor influencing the YSCWM intensity, which contributed about 80% of the differences of the YSCWM average water temperature at a depth of 50 m. In addition, the air-sea heat flux in the previous winter had a determining effect, contributing more than 50% of the differences between the strong and weak YSCWM years. Finally, a simple formula for predicting the YSCWM intensity was established by using the key influencing factors, i.e., the sea surface temperature before the cooling season and the air-sea heat flux during the cooling season from the previous December to the current February. With this formula, instead of a complicated numerical model, we were able to roughly predict the YSCWM intensity for the

A condition metric for Eucalyptus woodland derived from expert evaluations.

Science.gov (United States)

Sinclair, Steve J; Bruce, Matthew J; Griffioen, Peter; Dodd, Amanda; White, Matthew D

2018-02-01

The evaluation of ecosystem quality is important for land-management and land-use planning. Evaluation is unavoidably subjective, and robust metrics must be based on consensus and the structured use of observations. We devised a transparent and repeatable process for building and testing ecosystem metrics based on expert data. We gathered quantitative evaluation data on the quality of hypothetical grassy woodland sites from experts. We used these data to train a model (an ensemble of 30 bagged regression trees) capable of predicting the perceived quality of similar hypothetical woodlands based on a set of 13 site variables as inputs (e.g., cover of shrubs, richness of native forbs). These variables can be measured at any site and the model implemented in a spreadsheet as a metric of woodland quality. We also investigated the number of experts required to produce an opinion data set sufficient for the construction of a metric. The model produced evaluations similar to those provided by experts, as shown by assessing the model's quality scores of expert-evaluated test sites not used to train the model. We applied the metric to 13 woodland conservation reserves and asked managers of these sites to independently evaluate their quality. To assess metric performance, we compared the model's evaluation of site quality with the managers' evaluations through multidimensional scaling. The metric performed relatively well, plotting close to the center of the space defined by the evaluators. Given the method provides data-driven consensus and repeatability, which no single human evaluator can provide, we suggest it is a valuable tool for evaluating ecosystem quality in real-world contexts. We believe our approach is applicable to any ecosystem. © 2017 State of Victoria.

Predictive models for pressure ulcers from intensive care unit electronic health records using Bayesian networks.

Science.gov (United States)

Kaewprag, Pacharmon; Newton, Cheryl; Vermillion, Brenda; Hyun, Sookyung; Huang, Kun; Machiraju, Raghu

2017-07-05

We develop predictive models enabling clinicians to better understand and explore patient clinical data along with risk factors for pressure ulcers in intensive care unit patients from electronic health record data. Identifying accurate risk factors of pressure ulcers is essential to determining appropriate prevention strategies; in this work we examine medication, diagnosis, and traditional Braden pressure ulcer assessment scale measurements as patient features. In order to predict pressure ulcer incidence and better understand the structure of related risk factors, we construct Bayesian networks from patient features. Bayesian network nodes (features) and edges (conditional dependencies) are simplified with statistical network techniques. Upon reviewing a network visualization of our model, our clinician collaborators were able to identify strong relationships between risk factors widely recognized as associated with pressure ulcers. We present a three-stage framework for predictive analysis of patient clinical data: 1) Developing electronic health record feature extraction functions with assistance of clinicians, 2) simplifying features, and 3) building Bayesian network predictive models. We evaluate all combinations of Bayesian network models from different search algorithms, scoring functions, prior structure initializations, and sets of features. From the EHRs of 7,717 ICU patients, we construct Bayesian network predictive models from 86 medication, diagnosis, and Braden scale features. Our model not only identifies known and suspected high PU risk factors, but also substantially increases sensitivity of the prediction - nearly three times higher comparing to logistical regression models - without sacrificing the overall accuracy. We visualize a representative model with which our clinician collaborators identify strong relationships between risk factors widely recognized as associated with pressure ulcers. Given the strong adverse effect of pressure ulcers

A law for nuclear experts only

International Nuclear Information System (INIS)

Wagner, H.

1980-01-01

The Federal Ministry of the Interior is preparing an ordinance on expert consultants under the Atomic Energy Act which, among other topics, is to include legal norms for the criteria to be met by experts in terms of non-partisanship, training, capabilities, technical equipment and cooperation in expert organizations of members of various scientific and technical disciplines. A summary of general criteria relating to the qualification, selection and status of experts called in by the legislative and executive branches and by courts of law, which could be organized as a series of guidelines without any original qualities of legal norms, could be recommended in view of the increasing quantitative and qualitative importance of experts. However, passing an ordinance merely fixing and putting into concrete terms the image of an 'expert under the Atomic Energy Act' is intolerable, because the status of scientific and technical experts by far extends beyond the field of nuclear law in our industrial society characterized by a far reaching division of labor. Weak points in the organization of expert services are not confined to technology or nuclear power. Separate rules establishing legal norms are not convincing also for reasons of technology policy and legal policy as well as for those of social psychology and practice. (orig.) 891 HP/orig. 892 MKO [de

PREVAIL: Predicting Recovery through Estimation and Visualization of Active and Incident Lesions.

Science.gov (United States)

Dworkin, Jordan D; Sweeney, Elizabeth M; Schindler, Matthew K; Chahin, Salim; Reich, Daniel S; Shinohara, Russell T

2016-01-01

The goal of this study was to develop a model that integrates imaging and clinical information observed at lesion incidence for predicting the recovery of white matter lesions in multiple sclerosis (MS) patients. Demographic, clinical, and magnetic resonance imaging (MRI) data were obtained from 60 subjects with MS as part of a natural history study at the National Institute of Neurological Disorders and Stroke. A total of 401 lesions met the inclusion criteria and were used in the study. Imaging features were extracted from the intensity-normalized T1-weighted (T1w) and T2-weighted sequences as well as magnetization transfer ratio (MTR) sequence acquired at lesion incidence. T1w and MTR signatures were also extracted from images acquired one-year post-incidence. Imaging features were integrated with clinical and demographic data observed at lesion incidence to create statistical prediction models for long-term damage within the lesion. The performance of the T1w and MTR predictions was assessed in two ways: first, the predictive accuracy was measured quantitatively using leave-one-lesion-out cross-validated (CV) mean-squared predictive error. Then, to assess the prediction performance from the perspective of expert clinicians, three board-certified MS clinicians were asked to individually score how similar the CV model-predicted one-year appearance was to the true one-year appearance for a random sample of 100 lesions. The cross-validated root-mean-square predictive error was 0.95 for normalized T1w and 0.064 for MTR, compared to the estimated measurement errors of 0.48 and 0.078 respectively. The three expert raters agreed that T1w and MTR predictions closely resembled the true one-year follow-up appearance of the lesions in both degree and pattern of recovery within lesions. This study demonstrates that by using only information from a single visit at incidence, we can predict how a new lesion will recover using relatively simple statistical techniques. The

Operational expert system applications in Europe

CERN Document Server

Zarri, Gian Piero

1992-01-01

Operational Expert System Applications in Europe describes the representative case studies of the operational expert systems (ESs) that are used in Europe.This compilation provides examples of operational ES that are realized in 10 different European countries, including countries not usually examined in the standard reviews of the field.This book discusses the decision support system using several artificial intelligence tools; expert systems for fault diagnosis on computerized numerical control (CNC) machines; and expert consultation system for personal portfolio management. The failure prob

An infrastructure for data-intensive seismology using ADMIRE: laying the bricks for a new data highway

Science.gov (United States)

Trani, L.; Spinuso, A.; Galea, M.; Atkinson, M.; Van Eck, T.; Vilotte, J.

2011-12-01

The data bonanza generated by today's digital revolution is forcing scientists to rethink their methodologies and working practices. Traditional approaches to knowledge discovery are pushed to their limit and struggle to keep apace with the data flows produced by modern systems. This work shows how the ADMIRE data-intensive architecture supports seismologists by enabling them to focus on their scientific goals and questions, abstracting away the underlying technology platform that enacts their data integration and analysis tasks. ADMIRE accomplishes this partly by recognizing 3 different types of experts that require clearly defined interfaces between their interaction: the domain expert who is the application specialist, the data-analysis expert who is a specialist in extracting information from data, and the data-intensive engineer who develops the infrastructure for data-intensive computation. In order to provide a context in which each category of expert may flourish, ADMIRE uses a 3-level architecture: the upper - tool - level supports the work of both domain and data-analysis experts, housing an extensive and evolving set of portals, tools and development environments; the lower - enactment - level houses a large and dynamic community of providers delivering data and data-intensive enactment environments as an evolving infrastructure that supports all of the work underway in the upper layer. Most data-intensive engineers work here; the crucial innovation lies in the middle level, a gateway that is a tightly defined and stable interface through which the two diverse and dynamic upper and lower layers communicate. This is a minimal and simple protocol and language (DISPEL), ultimately to be controlled by standards, so that the upper and lower communities may invest, secure in the knowledge that changes in this interface will be carefully managed. We implemented a well-established procedure for processing seismic ambient noise on the prototype architecture. The

Branch technical position on the use of expert elicitation in the high-level radioactive waste program

International Nuclear Information System (INIS)

Kotra, J.P.; Lee, M.P.; Eisenberg, N.A.; DeWispelare, A.R.

1996-11-01

Should the site be found suitable, DOE will apply to the US Nuclear Regulatory Commission for permission to construct and then operate a proposed geologic repository for the disposal of spent nuclear fuel and other high-level radioactive waste at Yucca Mountain. In deciding whether to grant or deny DOE's license application for a geologic repository, NRC will closely examine the facts and expert judgment set forth in any potential DOE license application. NRC expects that subjective judgments of individual experts and, in some cases, groups of experts, will be used by DOE to interpret data obtained during site characterization and to address the many technical issues and inherent uncertainties associated with predicting the performance of a repository system for thousands of years. NRC has traditionally accepted, for review, expert judgment to evaluate and interpret the factual bases of license applications and is expected to give appropriate consideration to the judgments of DOE's experts regarding the geologic repository. Such consideration, however, envisions DOE using expert judgments to complement and supplement other sources of scientific and technical information, such as data collection, analyses, and experimentation. In this document, the NRC staff has set forth technical positions that: (1) provide general guidelines on those circumstances that may warrant the use of a formal process for obtaining the judgments of more than one expert (i.e., expert elicitation); and (2) describe acceptable procedures for conducting expert elicitation when formally elicited judgments are used to support a demonstration of compliance with NRC's geologic disposal regulation, currently set forth in 10 CFR Part 60. 76 refs

An inter-observer agreement study of autofluorescence endoscopy in Barrett's esophagus among expert and non-expert endoscopists.

Science.gov (United States)

Mannath, J; Subramanian, V; Telakis, E; Lau, K; Ramappa, V; Wireko, M; Kaye, P V; Ragunath, K

2013-02-01

Autofluorescence imaging (AFI), which is a "red flag" technique during Barrett's surveillance, is associated with significant false positive results. The aim of this study was to assess the inter-observer agreement (IOA) in identifying AFI-positive lesions and to assess the overall accuracy of AFI. Anonymized AFI and high resolution white light (HRE) images were prospectively collected. The AFI images were presented in random order, followed by corresponding AFI + HRE images. Three AFI experts and 3 AFI non-experts scored images after a training presentation. The IOA was calculated using kappa and accuracy was calculated with histology as gold standard. Seventy-four sets of images were prospectively collected from 63 patients (48 males, mean age 69 years). The IOA for number of AF positive lesions was fair when AFI images were presented. This improved to moderate with corresponding AFI and HRE images [experts 0.57 (0.44-0.70), non-experts 0.47 (0.35-0.62)]. The IOA for the site of AF lesion was moderate for experts and fair for non-experts using AF images, which improved to substantial for experts [κ = 0.62 (0.50-0.72)] but remained at fair for non-experts [κ = 0.28 (0.18-0.37)] with AFI + HRE. Among experts, the accuracy of identifying dysplasia was 0.76 (0.7-0.81) using AFI images and 0.85 (0.79-0.89) using AFI + HRE images. The accuracy was 0.69 (0.62-0.74) with AFI images alone and 0.75 (0.70-0.80) using AFI + HRE among non-experts. The IOA for AF positive lesions is fair to moderate using AFI images which improved with addition of HRE. The overall accuracy of identifying dysplasia was modest, and was better when AFI and HRE images were combined.

Expert system application education project

Science.gov (United States)

Gonzelez, Avelino J.; Ragusa, James M.

1988-01-01

Artificial intelligence (AI) technology, and in particular expert systems, has shown potential applicability in many areas of operation at the Kennedy Space Center (KSC). In an era of limited resources, the early identification of good expert system applications, and their segregation from inappropriate ones can result in a more efficient use of available NASA resources. On the other hand, the education of students in a highly technical area such as AI requires an extensive hands-on effort. The nature of expert systems is such that proper sample applications for the educational process are difficult to find. A pilot project between NASA-KSC and the University of Central Florida which was designed to simultaneously address the needs of both institutions at a minimum cost. This project, referred to as Expert Systems Prototype Training Project (ESPTP), provided NASA with relatively inexpensive development of initial prototype versions of certain applications. University students likewise benefit by having expertise on a non-trivial problem accessible to them at no cost. Such expertise is indispensible in a hands-on training approach to developing expert systems.

Neuro-fuzzy modeling in bankruptcy prediction

Directory of Open Access Journals (Sweden)

Vlachos D.

2003-01-01

Full Text Available For the past 30 years the problem of bankruptcy prediction had been thoroughly studied. From the paper of Altman in 1968 to the recent papers in the '90s, the progress of prediction accuracy was not satisfactory. This paper investigates an alternative modeling of the system (firm, combining neural networks and fuzzy controllers, i.e. using neuro-fuzzy models. Classical modeling is based on mathematical models that describe the behavior of the firm under consideration. The main idea of fuzzy control, on the other hand, is to build a model of a human control expert who is capable of controlling the process without thinking in a mathematical model. This control expert specifies his control action in the form of linguistic rules. These control rules are translated into the framework of fuzzy set theory providing a calculus, which can stimulate the behavior of the control expert and enhance its performance. The accuracy of the model is studied using datasets from previous research papers.

Long Range Dependence Prognostics for Bearing Vibration Intensity Chaotic Time Series

Directory of Open Access Journals (Sweden)

Qing Li

2016-01-01

Full Text Available According to the chaotic features and typical fractional order characteristics of the bearing vibration intensity time series, a forecasting approach based on long range dependence (LRD is proposed. In order to reveal the internal chaotic properties, vibration intensity time series are reconstructed based on chaos theory in phase-space, the delay time is computed with C-C method and the optimal embedding dimension and saturated correlation dimension are calculated via the Grassberger–Procaccia (G-P method, respectively, so that the chaotic characteristics of vibration intensity time series can be jointly determined by the largest Lyapunov exponent and phase plane trajectory of vibration intensity time series, meanwhile, the largest Lyapunov exponent is calculated by the Wolf method and phase plane trajectory is illustrated using Duffing-Holmes Oscillator (DHO. The Hurst exponent and long range dependence prediction method are proposed to verify the typical fractional order features and improve the prediction accuracy of bearing vibration intensity time series, respectively. Experience shows that the vibration intensity time series have chaotic properties and the LRD prediction method is better than the other prediction methods (largest Lyapunov, auto regressive moving average (ARMA and BP neural network (BPNN model in prediction accuracy and prediction performance, which provides a new approach for running tendency predictions for rotating machinery and provide some guidance value to the engineering practice.

Prediction of galactic cosmic ray intensity variation for a few (up to 10-12 years ahead on the basis of convection-diffusion and drift model

Directory of Open Access Journals (Sweden)

L. I. Dorman

2005-11-01

Full Text Available We determine the dimension of the Heliosphere (modulation region, radial diffusion coefficient and other parameters of convection-diffusion and drift mechanisms of cosmic ray (CR long-term variation, depending on particle energy, the level of solar activity (SA and general solar magnetic field. This important information we obtain on the basis of CR and SA data in the past, taking into account the theory of convection-diffusion and drift global modulation of galactic CR in the Heliosphere. By using these results and the predictions which are regularly published elsewhere of expected SA variation in the near future and prediction of next future SA cycle, we may make a prediction of the expected in the near future long-term cosmic ray intensity variation. We show that by this method we may make a prediction of the expected in the near future (up to 10-12 years, and may be more, in dependence for what period can be made definite prediction of SA galactic cosmic ray intensity variation in the interplanetary space on different distances from the Sun, in the Earth's magnetosphere, and in the atmosphere at different altitudes and latitudes.

The First Expert CAI System

Science.gov (United States)

Feurzeig, Wallace

1984-01-01

The first expert instructional system, the Socratic System, was developed in 1964. One of the earliest applications of this system was in the area of differential diagnosis in clinical medicine. The power of the underlying instructional paradigm was demonstrated and the potential of the approach for valuably supplementing medical instruction was recognized. Twenty years later, despite further educationally significant advances in expert systems technology and enormous reductions in the cost of computers, expert instructional methods have found very little application in medical schools.

Combining Crowd and Expert Labels using Decision Theoretic Active Learning

Science.gov (United States)

2015-10-11

including those la- beled by a classifier trained on using the labels acquired so far). For example, a simple loss function would just be the number...model is used to predict the probability that each crowd la- beled item is correct. This estimate is in turn used to weight the corresponding...costs) for each state using Algorithm 1 as a subroutine. We consider taking the possible action for each item not yet la- beled by the expert. Thus each

SU-F-T-342: Dosimetric Constraint Prediction Guided Automatic Mulit-Objective Optimization for Intensity Modulated Radiotherapy

International Nuclear Information System (INIS)

Song, T; Zhou, L; Li, Y

2016-01-01

Purpose: For intensity modulated radiotherapy, the plan optimization is time consuming with difficulties of selecting objectives and constraints, and their relative weights. A fast and automatic multi-objective optimization algorithm with abilities to predict optimal constraints and manager their trade-offs can help to solve this problem. Our purpose is to develop such a framework and algorithm for a general inverse planning. Methods: There are three main components contained in this proposed multi-objective optimization framework: prediction of initial dosimetric constraints, further adjustment of constraints and plan optimization. We firstly use our previously developed in-house geometry-dosimetry correlation model to predict the optimal patient-specific dosimetric endpoints, and treat them as initial dosimetric constraints. Secondly, we build an endpoint(organ) priority list and a constraint adjustment rule to repeatedly tune these constraints from their initial values, until every single endpoint has no room for further improvement. Lastly, we implement a voxel-independent based FMO algorithm for optimization. During the optimization, a model for tuning these voxel weighting factors respecting to constraints is created. For framework and algorithm evaluation, we randomly selected 20 IMRT prostate cases from the clinic and compared them with our automatic generated plans, in both the efficiency and plan quality. Results: For each evaluated plan, the proposed multi-objective framework could run fluently and automatically. The voxel weighting factor iteration time varied from 10 to 30 under an updated constraint, and the constraint tuning time varied from 20 to 30 for every case until no more stricter constraint is allowed. The average total costing time for the whole optimization procedure is ∼30mins. By comparing the DVHs, better OAR dose sparing could be observed in automatic generated plan, for 13 out of the 20 cases, while others are with competitive

SU-F-T-342: Dosimetric Constraint Prediction Guided Automatic Mulit-Objective Optimization for Intensity Modulated Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Song, T; Zhou, L [Southern Medical University, Guangzhou, Guangdong (China); Li, Y [Beihang University, Beijing, Beijing (China)

2016-06-15

Purpose: For intensity modulated radiotherapy, the plan optimization is time consuming with difficulties of selecting objectives and constraints, and their relative weights. A fast and automatic multi-objective optimization algorithm with abilities to predict optimal constraints and manager their trade-offs can help to solve this problem. Our purpose is to develop such a framework and algorithm for a general inverse planning. Methods: There are three main components contained in this proposed multi-objective optimization framework: prediction of initial dosimetric constraints, further adjustment of constraints and plan optimization. We firstly use our previously developed in-house geometry-dosimetry correlation model to predict the optimal patient-specific dosimetric endpoints, and treat them as initial dosimetric constraints. Secondly, we build an endpoint(organ) priority list and a constraint adjustment rule to repeatedly tune these constraints from their initial values, until every single endpoint has no room for further improvement. Lastly, we implement a voxel-independent based FMO algorithm for optimization. During the optimization, a model for tuning these voxel weighting factors respecting to constraints is created. For framework and algorithm evaluation, we randomly selected 20 IMRT prostate cases from the clinic and compared them with our automatic generated plans, in both the efficiency and plan quality. Results: For each evaluated plan, the proposed multi-objective framework could run fluently and automatically. The voxel weighting factor iteration time varied from 10 to 30 under an updated constraint, and the constraint tuning time varied from 20 to 30 for every case until no more stricter constraint is allowed. The average total costing time for the whole optimization procedure is ∼30mins. By comparing the DVHs, better OAR dose sparing could be observed in automatic generated plan, for 13 out of the 20 cases, while others are with competitive

Expert robots in nuclear plants

International Nuclear Information System (INIS)

Byrd, J.S.; Fisher, J.J.; DeVries, K.R.; Martin, T.P.

1987-01-01

Expert robots enhance a safety and operations in nuclear plants. E.I. du Pont de Nemours and Company, Savannah River Laboratory, is developing expert mobile robots for deployment in nuclear applications at the Savannah River Plant. Knowledge-based expert systems are being evaluated to simplify operator control, to assist in navigation and manipulation functions, and to analyze sensory information. Development work using two research vehicles is underway to demonstrate semiautonomous, intelligence, expert robot system operation in process areas. A description of the mechanical equipment, control systems, and operating modes is presented, including the integration of onboard sensors. A control hierarchy that uses modest computational methods is being used to allow mobile robots to autonomously navigate and perform tasks in known environments without the need for large computer systems

Expert robots in nuclear plants

International Nuclear Information System (INIS)

Byrd, J.S.; Fisher, J.J.; DeVries, K.R.; Martin, T.P.

1987-01-01

Expert robots will enhance safety and operations in nuclear plants. E. I. du Pont de Nemours and Company, Savannah River Laboratory, is developing expert mobile robots for deployment in nuclear applications at the Savannah River Plant. Knowledge-based expert systems are being evaluated to simplify operator control, to assist in navigation and manipulation functions, and to analyze sensory information. Development work using two research vehicles is underway to demonstrate semiautonomous, intelligent, expert robot system operation in process areas. A description of the mechanical equipment, control systems, and operating modes is presented, including the integration of onboard sensors. A control hierarchy that uses modest computational methods is being used to allow mobile robots to autonomously navigate and perform tasks in known environments without the need for large computer systems

Expert database system for quality control

Science.gov (United States)

Wang, Anne J.; Li, Zhi-Cheng

1993-09-01

There are more competitors today. Markets are not homogeneous they are fragmented into increasingly focused niches requiring greater flexibility in the product mix shorter manufacturing production runs and above allhigher quality. In this paper the author identified a real-time expert system as a way to improve plantwide quality management. The quality control expert database system (QCEDS) by integrating knowledge of experts in operations quality management and computer systems use all information relevant to quality managementfacts as well as rulesto determine if a product meets quality standards. Keywords: expert system quality control data base

Expert systems in process control systems

International Nuclear Information System (INIS)

Wittig, T.

1987-01-01

To illustrate where the fundamental difference between expert systems in classical diagnosis and in industrial control lie, the work of process control instrumentation is used as an example for the job of expert systems. Starting from the general process of problem-solving, two classes of expert systems can be defined accordingly. (orig.) [de

Progress in Ultrafast Intense Laser Science

CERN Document Server

Yamanouchi, Kaoru; Li, Ruxin; Chin, See Leang

2009-01-01

The PUILS series presents Progress in Ultrafast Intense Laser Science, a newly emerging interdisciplinary research field spanning atomic and molecular physics, molecular science, and optical science. PUILS has been stimulated by the recent development of ultrafast laser technologies. Each volume contains approximately 15 chapters, authored by researchers at the forefront. Each chapter opens with an overview of the topics to be discussed, so that researchers, who are not experts in the specific topics, as well as graduate students can grasp the importance and attractions of this sub-field of research, and these are followed by reports of cutting-edge discoveries. This fourth volume covers a broad range of topics from this interdisciplinary research field, focusing on strong field ionization of atoms; excitation, ionization and fragmentation of molecules; nonlinear intense optical phenomena and attosecond pulses; and laser - solid interactions and photoemission.

Underwater Munitions Expert System to Predict Mobility and Burial

Science.gov (United States)

2017-11-14

for predicting the location and possible burial of underwater munitions is required to advise site managers as they plan...that region above the given UXO relative density, which is defined as the UXO density divided by the sand grain density, ( nominally 2650 g...0.0 + 2.5*dsed ; % nominal bed roughness if no burial % (Potentially in future version, ripple height

Use of expert judgement in NUREG-1150

International Nuclear Information System (INIS)

Ortiz, N.R.; Wheeler, T.A.; Breeding, R.J.; Hora, S.; Meyer, M.A.; Kenney, R.L.

1991-01-01

The explicit expert judgment process used in NUREG-1150, 'Severe Accident Risks: An Assessment for Five US Nuclear Plants', is discussed in this paper. The main steps of the process are described, including selection of issues and experts, elicitation training, presentation of issues to the experts, preparation of issue analyses by the experts, discussion of issue analyses and elicitation, and recomposition and aggregation of results. To demonstrate the application of the expert judgment process to NUREG-1150, two issues are summarized: one from the accident frequency analysis, and one from the accident progression analysis. Recommendations and insights are provided to improve the use of explicit expert judgment in complex technical issues. (orig.)

Expert Evidence and International Criminal Justice

DEFF Research Database (Denmark)

Appazov, Artur

The book is a comprehensive narration of the use of expertise in international criminal trials offering reflection on standards concerning the quality and presentation of expert evidence. It analyzes and critiques the rules governing expert evidence in international criminal trials...... and the strategies employed by counsel and courts relying upon expert evidence and challenges that courts face determining its reliability. In particular, the author considers how the procedural and evidentiary architecture of international criminal courts and tribunals influences the courts' ability to meaningfully...... incorporate expert evidence into the rational fact-finding process. The book provides analysis of the unique properties of expert evidence as compared with other forms of evidence and the challenges that these properties present for fact-finding in international criminal trials. It draws conclusions about...

SMART-COP: a tool for predicting the need for intensive respiratory or vasopressor support in community-acquired pneumonia.

Science.gov (United States)

Charles, Patrick G P; Wolfe, Rory; Whitby, Michael; Fine, Michael J; Fuller, Andrew J; Stirling, Robert; Wright, Alistair A; Ramirez, Julio A; Christiansen, Keryn J; Waterer, Grant W; Pierce, Robert J; Armstrong, John G; Korman, Tony M; Holmes, Peter; Obrosky, D Scott; Peyrani, Paula; Johnson, Barbara; Hooy, Michelle; Grayson, M Lindsay

2008-08-01

Existing severity assessment tools, such as the pneumonia severity index (PSI) and CURB-65 (tool based on confusion, urea level, respiratory rate, blood pressure, and age >or=65 years), predict 30-day mortality in community-acquired pneumonia (CAP) and have limited ability to predict which patients will require intensive respiratory or vasopressor support (IRVS). The Australian CAP Study (ACAPS) was a prospective study of 882 episodes in which each patient had a detailed assessment of severity features, etiology, and treatment outcomes. Multivariate logistic regression was performed to identify features at initial assessment that were associated with receipt of IRVS. These results were converted into a simple points-based severity tool that was validated in 5 external databases, totaling 7464 patients. In ACAPS, 10.3% of patients received IRVS, and the 30-day mortality rate was 5.7%. The features statistically significantly associated with receipt of IRVS were low systolic blood pressure (2 points), multilobar chest radiography involvement (1 point), low albumin level (1 point), high respiratory rate (1 point), tachycardia (1 point), confusion (1 point), poor oxygenation (2 points), and low arterial pH (2 points): SMART-COP. A SMART-COP score of >or=3 points identified 92% of patients who received IRVS, including 84% of patients who did not need immediate admission to the intensive care unit. Accuracy was also high in the 5 validation databases. Sensitivities of PSI and CURB-65 for identifying the need for IRVS were 74% and 39%, respectively. SMART-COP is a simple, practical clinical tool for accurately predicting the need for IRVS that is likely to assist clinicians in determining CAP severity.

Complex method to calculate objective assessments of information systems protection to improve expert assessments reliability

Science.gov (United States)

Abdenov, A. Zh; Trushin, V. A.; Abdenova, G. A.

2018-01-01

The paper considers the questions of filling the relevant SIEM nodes based on calculations of objective assessments in order to improve the reliability of subjective expert assessments. The proposed methodology is necessary for the most accurate security risk assessment of information systems. This technique is also intended for the purpose of establishing real-time operational information protection in the enterprise information systems. Risk calculations are based on objective estimates of the adverse events implementation probabilities, predictions of the damage magnitude from information security violations. Calculations of objective assessments are necessary to increase the reliability of the proposed expert assessments.

Predicting Calcium Values for Gastrointestinal Bleeding Patients in Intensive Care Unit Using Clinical Variables and Fuzzy Modeling

Directory of Open Access Journals (Sweden)

G Khalili-Zadeh-Mahani

2016-07-01

Full Text Available Introduction: Reducing unnecessary laboratory tests is an essential issue in the Intensive Care Unit. One solution for this issue is to predict the value of a laboratory test to specify the necessity of ordering the tests. The aim of this paper was to propose a clinical decision support system for predicting laboratory tests values. Calcium laboratory tests of three categories of patients, including upper and lower gastrointestinal bleeding, and unspecified hemorrhage of gastrointestinal tract, have been selected as the case studies for this research. Method: In this research, the data have been collected from MIMIC-II database. For predicting calcium laboratory values, a Fuzzy Takagi-Sugeno model is used and the input variables of the model are heart rate and previous value of calcium laboratory test. Results: The results showed that the values of calcium laboratory test for the understudy patients were predictable with an acceptable accuracy. In average, the mean absolute errors of the system for the three categories of the patients are 0.27, 0.29, and 0.28, respectively. Conclusion: In this research, using fuzzy modeling and two variables of heart rate and previous calcium laboratory values, a clinical decision support system was proposed for predicting laboratory values of three categories of patients with gastrointestinal bleeding. Using these two clinical values as input variables, the obtained results were acceptable and showed the capability of the proposed system in predicting calcium laboratory values. For achieving better results, the impact of more input variables should be studied. Since, the proposed system predicts the laboratory values instead of just predicting the necessity of the laboratory tests; it was more generalized than previous studies. So, the proposed method let the specialists make the decision depending on the condition of each patient.

Inductive acquisition of expert knowledge

Energy Technology Data Exchange (ETDEWEB)

Muggleton, S.H.

1986-01-01

Expert systems divide neatly into two categories: those in which (1) the expert decisions result in changes to some external environment (control systems), and (2) the expert decisions merely seek to describe the environment (classification systems). Both the explanation of computer-based reasoning and the bottleneck (Feigenbaum, 1979) of knowledge acquisition are major issues in expert-systems research. The author contributed to these areas of research in two ways: 1. He implemented an expert-system shell, the Mugol environment, which facilitates knowledge acquisition by inductive inference and provides automatic explanation of run-time reasoning on demand. RuleMaster, a commercial version of this environment, was used to advantage industrially in the construction and testing of two large classification systems. 2. He investigated a new techniques called 'sequence induction' that can be used in construction of control systems. Sequence induction is based on theoretical work in grammatical learning. He improved existing grammatical learning algorithms as well as suggesting and theoretically characterizing new ones. These algorithms were successfully applied to acquisition of knowledge for a diverse set of control systems, including inductive construction of robot plans and chess end-gam strategies.

ALICE Expert System

CERN Document Server

Ionita, C

2014-01-01

The ALICE experiment at CERN employs a number of human operators (shifters), who have to make sure that the experiment is always in a state compatible with taking Physics data. Given the complexity of the system and the myriad of errors that can arise, this is not always a trivial task. The aim of this paper is to describe an expert system that is capable of assisting human shifters in the ALICE control room. The system diagnoses potential issues and attempts to make smart recommendations for troubleshooting. At its core, a Prolog engine infers whether a Physics or a technical run can be started based on the current state of the underlying sub-systems. A separate C++ component queries certain SMI objects and stores their state as facts in a Prolog knowledge base. By mining the data stored in dierent system logs, the expert system can also diagnose errors arising during a run. Currently the system is used by the on-call experts for faster response times, but we expect it to be adopted as a standard tool by reg...

Development of an expert system for tsunami warning: a unit source approach

International Nuclear Information System (INIS)

Roshan, A.D.; Pisharady, Ajai S.; Bishnoi, L.R.; Shah, Meet

2015-01-01

Coastal region of India has been experiencing tsunamis since historical times. Many nuclear facilities including nuclear power plants (NPPs), located along the coast are thus exposed to the hazards of tsunami. For the safety of these facilities as well as the safety of the citizens it is necessary to predict the possibility of occurrence of tsunamis for a recorded earthquake event and evaluate the tsunami hazard posed by the earthquake. To address these concerns, this work aims to design an expert system for Tsunami Warning for the Indian Coast with emphasis on evaluation of tsunami heights and arrival times at various nuclear facility sites. The expert system identifies possibility or otherwise of a tsunamigenic event based on earthquake data inputs. Rupture parameters are worked out for the event and unit tsunami source estimations which are available as precomputed database are combined appropriately to estimate the wave heights and time of arrivals at desired locations along the coast. The system also predicts tsunami wave heights at some pre-defined locations such as Nuclear Power Plant (NPP) and other nuclear facility sites. Time of arrivals of first wave along Indian coast is also evaluated

Tropical Cyclone Intensity Estimation Using Deep Convolutional Neural Networks

Science.gov (United States)

Maskey, Manil; Cecil, Dan; Ramachandran, Rahul; Miller, Jeffrey J.

2018-01-01

Estimating tropical cyclone intensity by just using satellite image is a challenging problem. With successful application of the Dvorak technique for more than 30 years along with some modifications and improvements, it is still used worldwide for tropical cyclone intensity estimation. A number of semi-automated techniques have been derived using the original Dvorak technique. However, these techniques suffer from subjective bias as evident from the most recent estimations on October 10, 2017 at 1500 UTC for Tropical Storm Ophelia: The Dvorak intensity estimates ranged from T2.3/33 kt (Tropical Cyclone Number 2.3/33 knots) from UW-CIMSS (University of Wisconsin-Madison - Cooperative Institute for Meteorological Satellite Studies) to T3.0/45 kt from TAFB (the National Hurricane Center's Tropical Analysis and Forecast Branch) to T4.0/65 kt from SAB (NOAA/NESDIS Satellite Analysis Branch). In this particular case, two human experts at TAFB and SAB differed by 20 knots in their Dvorak analyses, and the automated version at the University of Wisconsin was 12 knots lower than either of them. The National Hurricane Center (NHC) estimates about 10-20 percent uncertainty in its post analysis when only satellite based estimates are available. The success of the Dvorak technique proves that spatial patterns in infrared (IR) imagery strongly relate to tropical cyclone intensity. This study aims to utilize deep learning, the current state of the art in pattern recognition and image recognition, to address the need for an automated and objective tropical cyclone intensity estimation. Deep learning is a multi-layer neural network consisting of several layers of simple computational units. It learns discriminative features without relying on a human expert to identify which features are important. Our study mainly focuses on convolutional neural network (CNN), a deep learning algorithm, to develop an objective tropical cyclone intensity estimation. CNN is a supervised learning

Expert system in PNC, 6

International Nuclear Information System (INIS)

Tsubota, Koji

1990-01-01

The application of Artificial Intelligence (AI) as a tool for mineral exploration started only a decade ago. The systems that have been reported are in the most cases the expert systems that can simulate the decision of the experts or help numerical calculation for more reasonable and/or fast decision making. PNC started the development of the expert system for uranium exploration in 1983. Since then, KOGITO, a expert system to find the favorability of the target area, has been developed. Two years ago, the second generation development, Intelligent Research Environment and Support System, IRESS was initiated aiming at the establishment of a total support system for a project evaluation. We will review our effort for development of our system and introduce the application of the Data directed Numerical method as a new tool to Ahnemland area in Australia. (author)

Uncertain but able: Entrepreneurial self-efficacy and novices׳ use of expert decision-logic under uncertainty

NARCIS (Netherlands)

Engel, Y.; Dimitrova, N.G.; Khapova, S.N.; Elfring, T.

2014-01-01

Entrepreneurs' initial strategy choices are made in the face of inherently uncertain and fundamentally unpredictable futures. Yet, unlike experts, novice entrepreneurs still tend to rely on predictions and forecasts as they move their ideas through t h e venture creation process. This study examines

Use of an expert system data analysis manager for space shuttle main engine test evaluation

Science.gov (United States)

Abernethy, Ken

1988-01-01

The ability to articulate, collect, and automate the application of the expertise needed for the analysis of space shuttle main engine (SSME) test data would be of great benefit to NASA liquid rocket engine experts. This paper describes a project whose goal is to build a rule-based expert system which incorporates such expertise. Experiential expertise, collected directly from the experts currently involved in SSME data analysis, is used to build a rule base to identify engine anomalies similar to those analyzed previously. Additionally, an alternate method of expertise capture is being explored. This method would generate rules inductively based on calculations made using a theoretical model of the SSME's operation. The latter rules would be capable of diagnosing anomalies which may not have appeared before, but whose effects can be predicted by the theoretical model.

Charlson comorbidity index derived from chart review or administrative data: agreement and prediction of mortality in intensive care patients

Directory of Open Access Journals (Sweden)

Stavem K

2017-06-01

Full Text Available Knut Stavem,1–3 Henrik Hoel,4 Stein Arve Skjaker,5 Rolf Haagensen6 1Institute of Clinical Medicine, University of Oslo, Oslo, 2Department of Pulmonary Medicine, Medical Division, 3Health Services Research Unit, Akershus University Hospital, Lørenskog, 4Department of Surgery, Sykehuset Innlandet Kongsvinger, Kongsvinger, 5Section of Orthopaedic Emergency, Department of Orthopaedic Surgery, Oslo University Hospital, Oslo, 6Department of Anaesthesiology, Surgical Division, Akershus University Hospital, Lørenskog, Norway Purpose: This study compared the Charlson comorbidity index (CCI information derived from chart review and administrative systems to assess the completeness and agreement between scores, evaluate the capacity to predict 30-day and 1-year mortality in intensive care unit (ICU patients, and compare the predictive capacity with that of the Simplified Acute Physiology Score (SAPS II model.Patients and methods: Using data from 959 patients admitted to a general ICU in a Norwegian university hospital from 2007 to 2009, we compared the CCI score derived from chart review and administrative systems. Agreement was assessed using % agreement, kappa, and weighted kappa. The capacity to predict 30-day and 1-year mortality was assessed using logistic regression, model discrimination with the c-statistic, and calibration with a goodness-of-fit statistic.Results: The CCI was complete (n=959 when calculated from chart than from administrative data (n=839. Agreement was good, with a weighted kappa of 0.667 (95% confidence interval: 0.596–0.714. The c-statistics for categorized CCI scores from charts and administrative data were similar in the model that included age, sex, and type of admission: 0.755 and 0.743 for 30-day mortality, respectively, and 0.783 and 0.775, respectively, for 1-year mortality. Goodness-of-fit statistics supported the model fit.Conclusion: The CCI scores from chart review and administrative data showed good agreement

The relative abundance of predicted genes associated with ammonia-oxidation, nitrate reduction, and biomass decomposition in mineral soil are altered by intensive timber harvest.

Science.gov (United States)

Mushinski, R. M.; Zhou, Y.; Gentry, T. J.; Boutton, T. W.

2017-12-01

Forest ecosystems in the southern United States are substantially altered by anthropogenic disturbances such as timber harvest and land conversion, with effects being observed in carbon and nutrient pools as well as biogeochemical processes. Furthermore, the desire to develop renewable energy sources in the form of biomass extraction from logging residues may result in alterations in soil community structure and function. While the impact of forest management on soil physicochemical properties of the region has been studied, its' long-term effect on soil bacterial community composition and metagenomic potential is relatively unknown, especially at deeper soil depths. This study investigates how intensive organic matter removal intensities associated with timber harvest influence decadal-scale alterations in bacterial community structure and functional potential in the upper 1-m of the soil profile, 18 years post-harvest in a Pinus taeda L. forest of eastern Texas. Amplicon sequencing of the 16S rRNA gene was used in conjunction with soil chemical analyses to evaluate treatment-induced differences in community composition and potential environmental drivers of associated change. Furthermore, functional potential was assessed by using amplicon data to make metagenomic predictions. Results indicate that increasing organic matter removal intensity leads to altered community composition and the relative abundance of dominant OTUs annotated to Burkholderia and Aciditerrimonas. The relative abundance of predicted genes associated with dissimilatory nitrate reduction and denitrification were highest in the most intensively harvested treatment while genes involved in nitrification were significantly lower in the most intensively harvested treatment. Furthermore, genes associated with glycosyltransferases were significantly reduced with increasing harvest intensity while polysaccharide lyases increased. These results imply that intensive organic matter removal may create

Partners for development: Expert assistant in Malaysia

International Nuclear Information System (INIS)

Daud, A.H.

1996-01-01

This report reviews the expert assignments received by Malaysia under the TC programme over the 1980-95 time period. It provides data about the type of assignments and expert services, the institutions receiving the experts, and duration of the assignment. Also reviewed is the process of requesting and implementing an expert assignment in Malaysia, as well as the country's related objectives and plans

Expert system technology for nondestructive waste assay

International Nuclear Information System (INIS)

Becker, G.K.; Determan, J.C.

1998-01-01

Nondestructive assay waste characterization data generated for use in the National TRU Program must be of known and demonstrable quality. Each measurement is required to receive an independent technical review by a qualified expert. An expert system prototype has been developed to automate waste NDA data review of a passive/active neutron drum counter system. The expert system is designed to yield a confidence rating regarding measurement validity. Expert system rules are derived from data in a process involving data clustering, fuzzy logic, and genetic algorithms. Expert system performance is assessed against confidence assignments elicited from waste NDA domain experts. Performance levels varied for the active, passive shielded, and passive system assay modes of the drum counter system, ranging from 78% to 94% correct classifications

Intensity dependence of focused ultrasound lesion position

Science.gov (United States)

Meaney, Paul M.; Cahill, Mark D.; ter Haar, Gail R.

1998-04-01

Knowledge of the spatial distribution of intensity loss from an ultrasonic beam is critical to predicting lesion formation in focused ultrasound surgery. To date most models have used linear propagation models to predict the intensity profiles needed to compute the temporally varying temperature distributions. These can be used to compute thermal dose contours that can in turn be used to predict the extent of thermal damage. However, these simulations fail to adequately describe the abnormal lesion formation behavior observed for in vitro experiments in cases where the transducer drive levels are varied over a wide range. For these experiments, the extent of thermal damage has been observed to move significantly closer to the transducer with increasing transducer drive levels than would be predicted using linear propagation models. The simulations described herein, utilize the KZK (Khokhlov-Zabolotskaya-Kuznetsov) nonlinear propagation model with the parabolic approximation for highly focused ultrasound waves, to demonstrate that the positions of the peak intensity and the lesion do indeed move closer to the transducer. This illustrates that for accurate modeling of heating during FUS, nonlinear effects must be considered.

A prototype expert system 'SMART' for water chemistry control in reactor water circuits

International Nuclear Information System (INIS)

Rangarajan, S.; Narasimhan, S.V.

1998-01-01

The operational safety of a power plant depends mainly on the material compatibility of the system materials with the environment. However, for an operating plant, the material is almost fixed and hence one can improve the safety by controlling the surrounding environment. From the economy point of view, the plant availability factor as well as plant life extension (PLEX) are important considerations and these necessitate a systematic approach for continuous parametric monitoring, rapid data analysis and diagnosis for controlling the water chemistry regime. A prototype expert system 'SMART' was developed in BASIC language. The expert system consists of four modules. The DATA HANDLER module controls all the data handling functions and graphical display of the data parameters. It also generates weekly and monthly reports of the water chemistry data. The DATA INTERPRETER module compares the experimental data with the theoretically calculated values and predicts the presence of impurity ingress in the system. The CHEMISTRY EXPERT contains the knowledge base about the various sub-systems. All the water chemistry specifications are translated in the form of IF... THEN.. rules and are stored in this module. The expert system inferences with the forward chain reasoning mechanism to identify the diagnostic parameters by consulting the knowledge base and applying the appropriate rules. The ACTION EXPERT module collects all the diagnostic parameters and suggests the operator, the remedial actions/counter measures that should be taken immediately. This rule based system can be expanded to accommodate different water chemistry regimes. (author)

Vulnerability of bridges to scour: insights from an international expert elicitation workshop

Directory of Open Access Journals (Sweden)

R. Lamb

2017-08-01

Full Text Available Scour (localised erosion during flood events is one of the most significant threats to bridges over rivers and estuaries, and has been the cause of numerous bridge failures, with damaging consequences. Mitigation of the risk of bridges being damaged by scour is therefore important to many infrastructure owners, and is supported by industry guidance. Even after mitigation, some residual risk remains, though its extent is difficult to quantify because of the uncertainties inherent in the prediction of scour and the assessment of the scour risk. This paper summarises findings from an international expert workshop on bridge scour risk assessment that explores uncertainties about the vulnerability of bridges to scour. Two specialised structured elicitation methods were applied to explore the factors that experts in the field consider important when assessing scour risk and to derive pooled expert judgements of bridge failure probabilities that are conditional on a range of assumed scenarios describing flood event severity, bridge and watercourse types and risk mitigation protocols. The experts' judgements broadly align with industry good practice, but indicate significant uncertainty about quantitative estimates of bridge failure probabilities, reflecting the difficulty in assessing the residual risk of failure. The data and findings presented here could provide a useful context for the development of generic scour fragility models and their associated uncertainties.

Closed-loop control for cardiopulmonary management and intensive care unit sedation using digital imaging

Science.gov (United States)

Gholami, Behnood

This dissertation introduces a new problem in the delivery of healthcare, which could result in lower cost and a higher quality of medical care as compared to the current healthcare practice. In particular, a framework is developed for sedation and cardiopulmonary management for patients in the intensive care unit. A method is introduced to automatically detect pain and agitation in nonverbal patients, specifically in sedated patients in the intensive care unit, using their facial expressions. Furthermore, deterministic as well as probabilistic expert systems are developed to suggest the appropriate drug dose based on patient sedation level. Patients in the intensive care unit who require mechanical ventilation due to acute respiratory failure also frequently require the administration of sedative agents. The need for sedation arises both from patient anxiety due to the loss of personal control and the unfamiliar and intrusive environment of the intensive care unit, and also due to pain or other variants of noxious stimuli. In this dissertation, we develop a rule-based expert system for cardiopulmonary management and intensive care unit sedation. Furthermore, we use probability theory to quantify uncertainty and to extend the proposed rule-based expert system to deal with more realistic situations. Pain assessment in patients who are unable to verbally communicate is a challenging problem. The fundamental limitations in pain assessment stem from subjective assessment criteria, rather than quantifiable, measurable data. The relevance vector machine (RVM) classification technique is a Bayesian extension of the support vector machine (SVM) algorithm which achieves comparable performance to SVM while providing posterior probabilities for class memberships and a sparser model. In this dissertation, we use the RVM classification technique to distinguish pain from non-pain as well as assess pain intensity levels. We also correlate our results with the pain intensity

Expert system aids transport regulation users

International Nuclear Information System (INIS)

Cheshire, R.D.; Straw, R.J.

1990-01-01

During late 1984 the IAEA Regulations were identified as an area of application for an expert system adviser which could offer many advantages. Over the following year some simple tests were carried out to examine its feasibility, but TRANAID did not get underway until 1986 when British Nuclear Fuels (BNFL) Corporate Management services were engaged on the product. By this time a greater choice of suitable software, in the form of expert system shells, had become available. After a number of trial systems the shell Leonardo was finally adopted for the final system. In order for TRANAID to emulate the expert it was necessary to spend time extracting and documenting the expert knowledge. This was a matter of investigating how the regulations are used and was achieved by a series of meetings including opportunity for the computer specialists to interview the regulations experts. There are several benefits in having an expert system advisor in this area. It is useful to both experienced and inexperienced users of regulations. For those who are learning to use the regulations it is an excellent training aid. For those who know the regulations but use them infrequently it can save time and provide a valuable reassurance. The adviser has enabled the expert user's know how to be captured and to be made widely available to those with less experience. (author)

Cooperative expert system reasoning for waste remediations

International Nuclear Information System (INIS)

Bohn, S.J.; Pennock, K.A.; Franklin, A.L.

1991-12-01

The United States Department of Energy (DOE) is facing a large task in completing Remedial Investigations and Feasibility Studies (RI/FS) for hazardous waste sites across the nation. One of the primary objectives of an RI/FS is the specification of viable sequences of technology treatment trains which can provide implementable site solutions. We present a methodology which integrates expert system technology within an object-oriented framework to create a cooperative reasoning system designed to provide a comprehensive list of these implementable solutions. The system accomplishes its goal of specifying technology trains by utilizing a ''team'' of expert system objects. The system distributes the problem solving among the individual expert objects, and then coordinates the combination of individual decisions into a joint solution. Each expert object possesses the knowledge of an expert in a particular technology. An expert object can examine the parameters and characteristics of the waste site, seek information and support from other expert objects, and then make decisions concerning its own applicability. This methodology has at least two primary benefits. First, the creation of multiple expert objects provides a more direct mapping from the actual process to a software system, making the system easier to build. Second, the distribution of the inferencing among a number of loosely connected expert objects allows for a more robust and maintainable final product

A new risk prediction model for critical care: the Intensive Care National Audit & Research Centre (ICNARC) model.

Science.gov (United States)

Harrison, David A; Parry, Gareth J; Carpenter, James R; Short, Alasdair; Rowan, Kathy

2007-04-01

To develop a new model to improve risk prediction for admissions to adult critical care units in the UK. Prospective cohort study. The setting was 163 adult, general critical care units in England, Wales, and Northern Ireland, December 1995 to August 2003. Patients were 216,626 critical care admissions. None. The performance of different approaches to modeling physiologic measurements was evaluated, and the best methods were selected to produce a new physiology score. This physiology score was combined with other information relating to the critical care admission-age, diagnostic category, source of admission, and cardiopulmonary resuscitation before admission-to develop a risk prediction model. Modeling interactions between diagnostic category and physiology score enabled the inclusion of groups of admissions that are frequently excluded from risk prediction models. The new model showed good discrimination (mean c index 0.870) and fit (mean Shapiro's R 0.665, mean Brier's score 0.132) in 200 repeated validation samples and performed well when compared with recalibrated versions of existing published risk prediction models in the cohort of patients eligible for all models. The hypothesis of perfect fit was rejected for all models, including the Intensive Care National Audit & Research Centre (ICNARC) model, as is to be expected in such a large cohort. The ICNARC model demonstrated better discrimination and overall fit than existing risk prediction models, even following recalibration of these models. We recommend it be used to replace previously published models for risk adjustment in the UK.

Hierarchical Model of Assessing and Selecting Experts

OpenAIRE

Chernysheva, Tatiana Yurievna; Korchuganova, Mariya Anatolievna; Borisov, V. V.; Minkov, S. L.

2016-01-01

Revealing experts' competences is a multi-objective issue. Authors of the paper deal with competence assessing methods of experts seen as objects, and criteria of qualities. An analytic hierarchy process of assessing and ranking experts is offered, which is based on paired comparison matrices and scores, quality parameters are taken into account as well. Calculation and assessment of experts is given as an example.

Heterogeneous postsurgical data analytics for predictive modeling of mortality risks in intensive care units.

Science.gov (United States)

Yun Chen; Hui Yang

2014-01-01

The rapid advancements of biomedical instrumentation and healthcare technology have resulted in data-rich environments in hospitals. However, the meaningful information extracted from rich datasets is limited. There is a dire need to go beyond current medical practices, and develop data-driven methods and tools that will enable and help (i) the handling of big data, (ii) the extraction of data-driven knowledge, (iii) the exploitation of acquired knowledge for optimizing clinical decisions. This present study focuses on the prediction of mortality rates in Intensive Care Units (ICU) using patient-specific healthcare recordings. It is worth mentioning that postsurgical monitoring in ICU leads to massive datasets with unique properties, e.g., variable heterogeneity, patient heterogeneity, and time asyncronization. To cope with the challenges in ICU datasets, we developed the postsurgical decision support system with a series of analytical tools, including data categorization, data pre-processing, feature extraction, feature selection, and predictive modeling. Experimental results show that the proposed data-driven methodology outperforms traditional approaches and yields better results based on the evaluation of real-world ICU data from 4000 subjects in the database. This research shows great potentials for the use of data-driven analytics to improve the quality of healthcare services.

Experts' perceptions on the entrepreneurial framework conditions

Science.gov (United States)

Correia, Aldina; e Silva, Eliana Costa; Lopes, I. Cristina; Braga, Alexandra; Braga, Vitor

2017-11-01

The Global Entrepreneurship Monitor is a large scale database for internationally comparative entrepreneurship. This database includes information of more than 100 countries concerning several aspects of entrepreneurship activities, perceptions, conditions, national and regional policy, among others, in two main sources of primary data: the Adult Population Survey and the National Expert Survey. In the present work the National Expert Survey datasets for 2011, 2012 and 2013 are analyzed with the purpose of studying the effects of different type of entrepreneurship expert specialization on the perceptions about the Entrepreneurial Framework Conditions (EFCs). The results of the multivariate analysis of variance for the 2013 data show significant differences of the entrepreneurship experts when compared the 2011 and 2012 surveys. For the 2013 data entrepreneur experts are less favorable then most of the other experts to the EFCs.

Robust Trust in Expert Testimony

Directory of Open Access Journals (Sweden)

Christian Dahlman

2015-05-01

Full Text Available The standard of proof in criminal trials should require that the evidence presented by the prosecution is robust. This requirement of robustness says that it must be unlikely that additional information would change the probability that the defendant is guilty. Robustness is difficult for a judge to estimate, as it requires the judge to assess the possible effect of information that the he or she does not have. This article is concerned with expert witnesses and proposes a method for reviewing the robustness of expert testimony. According to the proposed method, the robustness of expert testimony is estimated with regard to competence, motivation, external strength, internal strength and relevance. The danger of trusting non-robust expert testimony is illustrated with an analysis of the Thomas Quick Case, a Swedish legal scandal where a patient at a mental institution was wrongfully convicted for eight murders.

Expert systems in clinical microbiology.

Science.gov (United States)

Winstanley, Trevor; Courvalin, Patrice

2011-07-01

This review aims to discuss expert systems in general and how they may be used in medicine as a whole and clinical microbiology in particular (with the aid of interpretive reading). It considers rule-based systems, pattern-based systems, and data mining and introduces neural nets. A variety of noncommercial systems is described, and the central role played by the EUCAST is stressed. The need for expert rules in the environment of reset EUCAST breakpoints is also questioned. Commercial automated systems with on-board expert systems are considered, with emphasis being placed on the "big three": Vitek 2, BD Phoenix, and MicroScan. By necessity and in places, the review becomes a general review of automated system performances for the detection of specific resistance mechanisms rather than focusing solely on expert systems. Published performance evaluations of each system are drawn together and commented on critically.

Expert opinion vs. empirical evidence

Science.gov (United States)

Herman, Rod A; Raybould, Alan

2014-01-01

Expert opinion is often sought by government regulatory agencies when there is insufficient empirical evidence to judge the safety implications of a course of action. However, it can be reckless to continue following expert opinion when a preponderance of evidence is amassed that conflicts with this opinion. Factual evidence should always trump opinion in prioritizing the information that is used to guide regulatory policy. Evidence-based medicine has seen a dramatic upturn in recent years spurred by examples where evidence indicated that certain treatments recommended by expert opinions increased death rates. We suggest that scientific evidence should also take priority over expert opinion in the regulation of genetically modified crops (GM). Examples of regulatory data requirements that are not justified based on the mass of evidence are described, and it is suggested that expertise in risk assessment should guide evidence-based regulation of GM crops. PMID:24637724

Critical thinking traits of top-tier experts and implications for computer science education

Science.gov (United States)

Bushey, Dean E.

A documented shortage of technical leadership and top-tier performers in computer science jeopardizes the technological edge, security, and economic well-being of the nation. The 2005 President's Information and Technology Advisory Committee (PITAC) Report on competitiveness in computational sciences highlights the major impact of science, technology, and innovation in keeping America competitive in the global marketplace. It stresses the fact that the supply of science, technology, and engineering experts is at the core of America's technological edge, national competitiveness and security. However, recent data shows that both undergraduate and postgraduate production of computer scientists is falling. The decline is "a quiet crisis building in the United States," a crisis that, if allowed to continue unchecked, could endanger America's well-being and preeminence among the world's nations. Past research on expert performance has shown that the cognitive traits of critical thinking, creativity, and problem solving possessed by top-tier performers can be identified, observed and measured. The studies show that the identified attributes are applicable across many domains and disciplines. Companies have begun to realize that cognitive skills are important for high-level performance and are reevaluating the traditional academic standards they have used to predict success for their top-tier performers in computer science. Previous research in the computer science field has focused either on programming skills of its experts or has attempted to predict the academic success of students at the undergraduate level. This study, on the other hand, examines the critical-thinking skills found among experts in the computer science field in order to explore the questions, "What cognitive skills do outstanding performers possess that make them successful?" and "How do currently used measures of academic performance correlate to critical-thinking skills among students?" The results

A user perspective on the gap between science and decision-making. Local administrators’ views on expert knowledge in urban planning

NARCIS (Netherlands)

Stigt, van Rien; Driessen, P.J.; Spit, Tejo

2015-01-01

The role of expert knowledge of the environment in decision-making about urban development has been intensively debated. Most contributions to this debate have studied the use of knowledge in the decision-making process from the knowledge providers’ point of view. In this paper, we reverse the

An expert system for automated robotic grasping

International Nuclear Information System (INIS)

Stansfield, S.A.

1990-01-01

Many US Department of Energy sites and facilities will be environmentally remediated during the next several decades. A number of the restoration activities (e.g., decontamination and decommissioning of inactive nuclear facilities) can only be carried out by remote means and will be manipulation-intensive tasks. Experience has shown that manipulation tasks are especially slow and fatiguing for the human operator of a remote manipulator. In this paper, the authors present a rule-based expert system for automated, dextrous robotic grasping. This system interprets the features of an object to generate hand shaping and wrist orientation for a robot hand and arm. The system can be used in several different ways to lessen the demands on the human operator of a remote manipulation system - either as a fully autonomous grasping system or one that generates grasping options for a human operator and then automatically carries out the selected option

Expert system and process optimization techniques for real-time monitoring and control of plasma processes

Science.gov (United States)

Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

1991-03-01

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

Expert systems in clinical practice

International Nuclear Information System (INIS)

Renaud-Salis, J.L.

1987-01-01

The first expert systems prototypes intended for advising physicians on diagnosis or therapy selection have been designed more than ten years ago. However, a few of them are already in use in clinical practice after years of research and development efforts. The capabilities of these systems to reason symbolically and to mimic the hypothetico-deductive processes used by physicians distinguishes them from conventional computer programs. Their power comes from their knowledge-base which embeds a large quantity of high-level, specialized knowledge captured from medical experts. Common methods for knowledge representation include production rules and frames. These methods also provide a mean for organizing and structuring the knowledge according to hierarchical or causal links. The best expert-systems perform at the level of the experts. They are easy to learn and use, and can communicate with the user in pseudo-natural language. Moreover they are able to explain their line of reasoning. These capabilities make them potentially useful, usable and acceptable by physicians. However if the problems related to difficulties and costs in building expert-systems are on the way to be solved within the next few years, forensic and ethical issues should have to be addressed before one can envisage their routine use in clinical practice [fr

Human Influence on Tropical Cyclone Intensity

Science.gov (United States)

Sobel, Adam H.; Camargo, Suzana J.; Hall, Timothy M.; Lee, Chia-Ying; Tippett, Michael K.; Wing, Allison A.

2016-01-01

Recent assessments agree that tropical cyclone intensity should increase as the climate warms. Less agreement exists on the detection of recent historical trends in tropical cyclone intensity.We interpret future and recent historical trends by using the theory of potential intensity, which predicts the maximum intensity achievable by a tropical cyclone in a given local environment. Although greenhouse gas-driven warming increases potential intensity, climate model simulations suggest that aerosol cooling has largely canceled that effect over the historical record. Large natural variability complicates analysis of trends, as do poleward shifts in the latitude of maximum intensity. In the absence of strong reductions in greenhouse gas emissions, future greenhouse gas forcing of potential intensity will increasingly dominate over aerosol forcing, leading to substantially larger increases in tropical cyclone intensities.

Expert Witness

African Journals Online (AJOL)

Adele

formal rules of evidence apply) to help it understand the issues of a case and ... statements on medical expert witness by professional representative bodies in .... determining the size of the financial settlement that may have to be made to the.

Expert system for estimating LWR plutonium production

International Nuclear Information System (INIS)

Sandquist, G.M.

1988-01-01

An Artificial Intelligence-Expert System called APES (Analysis of Proliferation by Expert System) has been developed and tested to permit a non proliferation expert to evaluate the capability and capacity of a specified LWR reactor and PUREX reprocessing system for producing and separating plutonium even when system information may be limited and uncertain. APES employs an expert system coded in LISP and based upon an HP-RL (Hewlett Packard-Representational Language) Expert System Shell. The user I/O interface communicates with a blackboard and the knowledge base which contains the quantitative models required to describe the reactor, selected fission product production and radioactive decay processes, Purex reprocessing and ancillary knowledge

Development and assessment of an Al expert system for the monitoring and diagnosis of nuclear power plants

International Nuclear Information System (INIS)

Takeuchi, K.; Gagnon, A.; Cheung, A.C.; Meyer, P.E.

1988-01-01

Due to the rapid progress in microcomputer and software development, artificial intelligence (AI) expert systems of practical value can be built into microcomputers. An expert system for nuclear plant surveillance, diagnostics, and prognostics was developed using the Texas Instruments AI shell, Personal Consultant Plus (PC-plus) on an IBM PCAT. This expert system runs in a surveillance mode to find an abnormal operating condition. Once an abnormal behavior is found,it switches to a diagnostics mode to identify the cause of difficult, such as steam generator tube rupture (SGTR) and leak. Then, the prognostics mode can be activated to predict the consequences. For this purpose, the knowledge of experts at Westinghouse for nuclear safety has been collected and processed to construct parameters and rules within the framework of a logic tree. The expert system may be used in an on-line mode via a connection to the plant computer, safety parameter display system, or a plant simulator. In addition to evaluating the diagnosis of an event and providing appropriate information required to generate an event report, this tool can also be used to review the normal recorded plant data daily to assure that no abnormal events have occurred. A limited assessment of the expert system was performed and is presented

Expert Systems in Reference Services.

Science.gov (United States)

Roysdon, Christine, Ed.; White, Howard D., Ed.

1989-01-01

Eleven articles introduce expert systems applications in library and information science, and present design and implementation issues of system development for reference services. Topics covered include knowledge based systems, prototype development, the use of artificial intelligence to remedy current system inadequacies, and an expert system to…

ISOE EG-SAM interim report - Report on behalf of the Sub expert Group

International Nuclear Information System (INIS)

Harris, Willie; Miller, David W.; Djeffal, Salah; Anderson, Ellen; Couasnon, Olivier; Hagemeyer, Derek; Sovijarvi, Jukka; Amaral, Marcos A.; Tarzia, J.P.; Schmidt, Claudia; Fritioff, Karin; Kaulard, Joerg; Lance, Benoit; Fritioff, Karin; Schieber, Caroline; Hayashida, Yoshihisa; Doty, Rick

2014-01-01

During its November 2012 meeting, the expert group decided to develop an interim (preliminary) report before the end of 2013 (with a general perspective and discussion of specific severe accident management worker dose issues), and to finalize the report by organizing the international workshop of 2014 to address national experiences, which will be incorporated to the report. The work of the EG-SAM focuses on radiation protection management and organization, radiation protection training and exercises related to severe accident management, facility configuration and readiness, worker protection, radioactive materials, contamination controls and logistics and key lessons learned especially from the TMI, Chernobyl and Fukushima Dai-ichi accidents. This interim report was completed through intensive work of all Group members nominated by the ISOE, and was accomplished during EG-SAM meetings through 2012-2013. This document gathers the different presentations given by the sub expert groups in charge of each chapter of the report

Development of an expert system for signal validation: Topical report

International Nuclear Information System (INIS)

Qualls, A.L.; Uhrig, R.E.; Upadhyaya, B.R.

1988-07-01

A signal validation and sensor information expert system is developed and applied to nuclear power plant subsystems. The expert system interactively provides the user with a list of sensors used to monitor a subsystem of a power plant and answers the user's questions about the characteristics of those sensors. The expert system performs an evaluation of the present output characteristics of an instrument channel. The evaluation is fully automated and is designed to mimic an operator's approach to signal validation. The evaluation is designed to detect three types of possible sensor anomalies: (1) incorrect average output, (2) improper noise level,and (3) incorrect response to a system perturbation. There are two tests used to detect each possible anomalous condition. One test is a comparison of the specified sensor characteristic against the same characteristic of its redundant sensors. The second test is a prediction of the sensor's expected behavior and comparison with its observed behavior. The evaluation was tested using operational data from twelve sensors used to monitor level, pressure, primary and secondary coolant flow rates, and hot and cold leg temperatures of a steam generator in a commercial nuclear power plant. The results of the testing demonstrated successfully that the evaluation detected the three possible anomalies, and was able to handle conflicting information using the comparison among redundant sensors and the system specific test used to detect the anomalies

Quantitative and qualitative analysis of the expert and non-expert opinion in fire risk in buildings

International Nuclear Information System (INIS)

Hanea, D.M.; Jagtman, H.M.; Alphen, L.L.M.M. van; Ale, B.J.M.

2010-01-01

Expert judgment procedure is a method very often used in the area of risk assessments of complex systems or processes to fill in quantitative data. Although it has been proved to be a very reliable source of information when no other data are available, the choice of experts is always questioned. When the available data are limited, the seed questions cover only partially the domains of expertise, which may cause problems. Expertise is assessed not covering the full object of study but only those topics for which seed questions can be formulated. The commonly used quantitative analysis of an expert judgment exercise is combined with a qualitative analysis. The latter adds more insights to the relation between the assessor's field and statistical knowledge and their performance in an expert judgment. In addition the qualitative analysis identifies different types of seed questions. Three groups of assessors with different levels of statistical and domain knowledge are studied. The quantitative analysis shows no differences between field experts and non-experts and no differences between having advanced statistical knowledge or not. The qualitative analysis supports these findings. In addition it is found that especially technical questions are answered with larger intervals. Precaution is required when using seed questions for which the real value can be calculated, which was the case for one of the seed questions.

20 CFR 405.10 - Medical and Vocational Expert System.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Medical and Vocational Expert System. 405.10... Vocational Expert System. (a) General. The Medical and Vocational Expert System is comprised of the Medical... Vocational Expert System. (3) Experts who provide evidence at your request. Experts whom you ask to provide...

ALICE Expert System

International Nuclear Information System (INIS)

Ionita, C; Carena, F

2014-01-01

The ALICE experiment at CERN employs a number of human operators (shifters), who have to make sure that the experiment is always in a state compatible with taking Physics data. Given the complexity of the system and the myriad of errors that can arise, this is not always a trivial task. The aim of this paper is to describe an expert system that is capable of assisting human shifters in the ALICE control room. The system diagnoses potential issues and attempts to make smart recommendations for troubleshooting. At its core, a Prolog engine infers whether a Physics or a technical run can be started based on the current state of the underlying sub-systems. A separate C++ component queries certain SMI objects and stores their state as facts in a Prolog knowledge base. By mining the data stored in different system logs, the expert system can also diagnose errors arising during a run. Currently the system is used by the on-call experts for faster response times, but we expect it to be adopted as a standard tool by regular shifters during the next data taking period

Poor Agreement Among Expert Witnesses in Bile Duct Injury Malpractice Litigation An Expert Panel Survey

NARCIS (Netherlands)

de Reuver, Philip R.; Dijkgraaf, Marcel G. W.; Gevers, Sjef K. M.; Gouma, Dirk J.

2008-01-01

Objective: To determine the inter-rater agreement of expert witness testimonies in bile duct injury malpractice litigation. Background Data: Malpractice litigation is an increasing concern in modem surgical practice. As most of the lawyers are not educated in medicine, expert witnesses are asked to

Poor agreement among expert witnesses in bile duct injury malpractice litigation: an expert panel survey.

NARCIS (Netherlands)

Reuver, P.R. de; Dijkgraaf, M.G.; Gevers, S.K.; Gouma, D.J.; Bleichrodt, R.P.; Cuesta, M.A.; Erp, W.F. van; Gerritsen, J.; Hesselink, E.J.; Laarhoven, C.J.H.M. van; Lange, J. de; Obertop, H.; Stassen, L.P.; Terpstra, O.T.; Tilanus, H.W.; Vroonhoven, T.J.; Wit, L. de

2008-01-01

OBJECTIVE: To determine the inter-rater agreement of expert witness testimonies in bile duct injury malpractice litigation. BACKGROUND DATA: Malpractice litigation is an increasing concern in modern surgical practice. As most of the lawyers are not educated in medicine, expert witnesses are asked to

An expert system for turbogenerator diagnostics

International Nuclear Information System (INIS)

Bessenyei, Z.; Tomcsanyi, T.; Toth, Z.; Laczay, I.

1992-01-01

In 1990, an expert system for turbo-generator diagnostics (EST-D) was installed at the 3rd and 4th units of the Paks NPP (Hungary). The expert system is strongly integrated to the ARGUS II vibration monitoring and diagnostics system. The system works on IBM PC AT. The VEIKI's and the NPP's human experts were interviewed to fill up the knowledgebase. The system is able to identify 13 different faults of the parts of a turbogenerator. The knowledgebase consists of ca 200 rules. The rules were built in and the system was verified and validated using a model of the turbines and using the experiences gathered with ARGUS II during the last 3 years. The maintenance personnel is authorized to modify and/or extend the knowledgebase. The input data for evaluation come from measured vibration patterns produced by the ARGUS II system, database of events, and maintenance data input by the maintenance personnel. The expert system is based on the modified GENESYS 2.1 shell (developed by SZAMALK, Hungary). Some limitations from PC application were eliminated, and a new, independent explanation module and man-machine interface were developed. Using this man-machine interface, one of the basic goals of the expert system developments was achieved: the human experts contribution is not necessary for diagnoses. The operator of the diagnostics system is able to produce the reports of diagnoses. Of course the interface allows the human experts to see the diagnoses through. It should be mentioned, at the beginning of 1991, we installed a similar expert system at the 1st 1000 MW WWER type unit of the Kalinin NPP (Soviet Union). In this paper, the operation of the EST-D, the man-machine interface and the operational experiences of the first 4 months work are explained. 2 refs., 14 figs

Complexity factors and prediction of performance

International Nuclear Information System (INIS)

Braarud, Per Oeyvind

1998-03-01

Understanding of what makes a control room situation difficult to handle is important when studying operator performance, both with respect to prediction as well as improvement of the human performance. A factor analytic approach identified eight factors from operators' answers to an 39 item questionnaire about complexity of the operator's task in the control room. A Complexity Profiling Questionnaire was developed, based on the factor analytic results from the operators' conception of complexity. The validity of the identified complexity factors was studied by prediction of crew performance and prediction of plant performance from ratings of the complexity of scenarios. The scenarios were rated by both process experts and the operators participating in the scenarios, using the Complexity Profiling Questionnaire. The process experts' complexity ratings predicted both crew performance and plant performance, while the operators' rating predicted plant performance only. The results reported are from initial studies of complexity, and imply a promising potential for further studies of the concept. The approach used in the study as well as the reported results are discussed. A chapter about the structure of the conception of complexity, and a chapter about further research conclude the report. (author)

SU-E-T-802: Verification of Implanted Cardiac Pacemaker Doses in Intensity-Modulated Radiation Therapy: Dose Prediction Accuracy and Reduction Effect of a Lead Sheet

Energy Technology Data Exchange (ETDEWEB)

Lee, J [Dept. of Radiation Oncology, Konkuk University Medical Center, Seoul (Korea, Republic of); Chung, J [Dept. of Radiation Oncology, Seoul National University Bundang Hospital, Seongnam (Korea, Republic of)

2015-06-15

Purpose: To verify delivered doses on the implanted cardiac pacemaker, predicted doses with and without dose reduction method were verified using the MOSFET detectors in terms of beam delivery and dose calculation techniques in intensity-modulated radiation therapy (IMRT). Methods: The pacemaker doses for a patient with a tongue cancer were predicted according to the beam delivery methods [step-and-shoot (SS) and sliding window (SW)], intensity levels for dose optimization, and dose calculation algorithms. Dosimetric effects on the pacemaker were calculated three dose engines: pencil-beam convolution (PBC), analytical anisotropic algorithm (AAA), and Acuros-XB. A lead shield of 2 mm thickness was designed for minimizing irradiated doses to the pacemaker. Dose variations affected by the heterogeneous material properties of the pacemaker and effectiveness of the lead shield were predicted by the Acuros-XB. Dose prediction accuracy and the feasibility of the dose reduction strategy were verified based on the measured skin doses right above the pacemaker using mosfet detectors during the radiation treatment. Results: The Acuros-XB showed underestimated skin doses and overestimated doses by the lead-shield effect, even though the lower dose disagreement was observed. It led to improved dose prediction with higher intensity level of dose optimization in IMRT. The dedicated tertiary lead sheet effectively achieved reduction of pacemaker dose up to 60%. Conclusion: The current SS technique could deliver lower scattered doses than recommendation criteria, however, use of the lead sheet contributed to reduce scattered doses.Thin lead plate can be a useful tertiary shielder and it could not acuse malfunction or electrical damage of the implanted pacemaker in IMRT. It is required to estimate more accurate scattered doses of the patient with medical device to design proper dose reduction strategy.

SU-E-T-802: Verification of Implanted Cardiac Pacemaker Doses in Intensity-Modulated Radiation Therapy: Dose Prediction Accuracy and Reduction Effect of a Lead Sheet

International Nuclear Information System (INIS)

Lee, J; Chung, J

2015-01-01

Purpose: To verify delivered doses on the implanted cardiac pacemaker, predicted doses with and without dose reduction method were verified using the MOSFET detectors in terms of beam delivery and dose calculation techniques in intensity-modulated radiation therapy (IMRT). Methods: The pacemaker doses for a patient with a tongue cancer were predicted according to the beam delivery methods [step-and-shoot (SS) and sliding window (SW)], intensity levels for dose optimization, and dose calculation algorithms. Dosimetric effects on the pacemaker were calculated three dose engines: pencil-beam convolution (PBC), analytical anisotropic algorithm (AAA), and Acuros-XB. A lead shield of 2 mm thickness was designed for minimizing irradiated doses to the pacemaker. Dose variations affected by the heterogeneous material properties of the pacemaker and effectiveness of the lead shield were predicted by the Acuros-XB. Dose prediction accuracy and the feasibility of the dose reduction strategy were verified based on the measured skin doses right above the pacemaker using mosfet detectors during the radiation treatment. Results: The Acuros-XB showed underestimated skin doses and overestimated doses by the lead-shield effect, even though the lower dose disagreement was observed. It led to improved dose prediction with higher intensity level of dose optimization in IMRT. The dedicated tertiary lead sheet effectively achieved reduction of pacemaker dose up to 60%. Conclusion: The current SS technique could deliver lower scattered doses than recommendation criteria, however, use of the lead sheet contributed to reduce scattered doses.Thin lead plate can be a useful tertiary shielder and it could not acuse malfunction or electrical damage of the implanted pacemaker in IMRT. It is required to estimate more accurate scattered doses of the patient with medical device to design proper dose reduction strategy

Artificial Intelligence: The Expert Way.

Science.gov (United States)

Bitter, Gary G.

1989-01-01

Discussion of artificial intelligence (AI) and expert systems focuses on their use in education. Characteristics of good expert systems are explained; computer software programs that contain applications of AI are described, highlighting one used to help educators identify learning-disabled students; and the future of AI is discussed. (LRW)

Mind the Gaps: Expert and Non-Expert Differences in Conceptualising the Geological Subsurface.

Science.gov (United States)

Gibson, H.; Stewart, I. S.; Stokes, A.; Pahl, S.

2017-12-01

In communicating geoscience topics, emphasis is often given to approaches such as the use of narrative to make a message engaging and reducing the use of jargon to ensure that it is understood by as wide a group of people as possible. Whilst these are undeniably important techniques to promote effective communication, an aspect of geoscience communication that is often overlooked is the publics' conceptual frameworks about core geoscience concepts. The consideration of different conceptual frameworks fits with the need to ensure that the framing is appropriate for the message, but it extends beyond simple framing into more complicated issues of addressing and incorporating pre- and mis-conceptions in geoscience. In a study examining expert and non-expert cognitive (mental) models of the geological subsurface in south-west England, several gaps were found between the fundamental ways that experts and non-experts conceptualise this invisible realm. Of these, three gaps were considered to be particularly important and common to many participants: the use of spatial reasoning; the application of surface experiences to subsurface processes; and the connection between the surface and subsurface. This paper will examine the evidence for these three important conceptual gaps between specialists and non-specialists and will address how this type of cognitive study can help improve effective geoscience communication.

Key attributes of expert NRL referees.

Science.gov (United States)

Morris, Gavin; O'Connor, Donna

2017-05-01

Experiential knowledge of elite National Rugby League (NRL) referees was investigated to determine the key attributes contributing to expert officiating performance. Fourteen current first-grade NRL referees were asked to identify the key attributes they believed contributed to their expert refereeing performance. The modified Delphi method involved a 3-round process of an initial semi-structured interview followed by 2 questionnaires to reach consensus of opinion. The data revealed 25 attributes that were rated as most important that underpin expert NRL refereeing performance. Results illustrate the significance of the cognitive category, with the top 6 ranked attributes all cognitive skills. Of these, the referees ranked decision-making accuracy as the most important attribute, followed by reading the game, communication, game understanding, game management and knowledge of the rules. Player rapport, positioning and teamwork were the top ranked game skill attributes underpinning performance excellence. Expert referees also highlighted a number of psychological attributes (e.g., concentration, composure and mental toughness) that were significant to performance. There were only 2 physiological attributes (fitness, aerobic endurance) that were identified as significant to elite officiating performance. In summary, expert consensus was attained which successfully provided a hierarchy of the most significant attributes of expert NRL refereeing performance.

Psychological scaling of expert estimates of human error probabilities: application to nuclear power plant operation

International Nuclear Information System (INIS)

Comer, K.; Gaddy, C.D.; Seaver, D.A.; Stillwell, W.G.

1985-01-01

The US Nuclear Regulatory Commission and Sandia National Laboratories sponsored a project to evaluate psychological scaling techniques for use in generating estimates of human error probabilities. The project evaluated two techniques: direct numerical estimation and paired comparisons. Expert estimates were found to be consistent across and within judges. Convergent validity was good, in comparison to estimates in a handbook of human reliability. Predictive validity could not be established because of the lack of actual relative frequencies of error (which will be a difficulty inherent in validation of any procedure used to estimate HEPs). Application of expert estimates in probabilistic risk assessment and in human factors is discussed

Intensity attenuation for active crustal regions

Science.gov (United States)

Allen, Trevor I.; Wald, David J.; Worden, C. Bruce

2012-07-01

We develop globally applicable macroseismic intensity prediction equations (IPEs) for earthquakes of moment magnitude M W 5.0-7.9 and intensities of degree II and greater for distances less than 300 km for active crustal regions. The IPEs are developed for two distance metrics: closest distance to rupture ( R rup) and hypocentral distance ( R hyp). The key objective for developing the model based on hypocentral distance—in addition to more rigorous and standard measure R rup—is to provide an IPE which can be used in near real-time earthquake response systems for earthquakes anywhere in the world, where information regarding the rupture dimensions of a fault may not be known in the immediate aftermath of the event. We observe that our models, particularly the model for the R rup distance metric, generally have low median residuals with magnitude and distance. In particular, we address whether the direct use of IPEs leads to a reduction in overall uncertainties when compared with methods which use a combination of ground-motion prediction equations and ground motion to intensity conversion equations. Finally, using topographic gradient as a proxy and median model predictions, we derive intensity-based site amplification factors. These factors lead to a small reduction of residuals at shallow gradients at strong shaking levels. However, the overall effect on total median residuals is relatively small. This is in part due to the observation that the median site condition for intensity observations used to develop these IPEs is approximately near the National Earthquake Hazard Reduction Program CD site-class boundary.

Prospective demonstration of brain plasticity after intensive abacus-based mental calculation training: An fMRI study

International Nuclear Information System (INIS)

Chen, C.L.; Wu, T.H.; Cheng, M.C.; Huang, Y.H.; Sheu, C.Y.; Hsieh, J.C.; Lee, J.S.

2006-01-01

Abacus-based mental calculation is a unique Chinese culture. The abacus experts can perform complex computations mentally with exceptionally fast speed and high accuracy. However, the neural bases of computation processing are not yet clearly known. This study used a BOLD contrast 3T fMRI system to explore the brain activation differences between abacus experts and non-expert subjects. All the acquired data were analyzed using SPM99 software. From the results, different ways of performing calculations between the two groups were seen. The experts tended to adopt efficient visuospatial/visuomotor strategy (bilateral parietal/frontal network) to process and retrieve all the intermediate and final results on the virtual abacus during calculation. By contrast, coordination of several networks (verbal, visuospatial processing and executive function) was required in the normal group to carry out arithmetic operations. Furthermore, more involvement of the visuomotor imagery processing (right dorsal premotor area) for imagining bead manipulation and low level use of the executive function (frontal-subcortical area) for launching the relatively time-consuming sequentially organized process was noted in the abacus expert group than in the non-expert group. We suggest that these findings may explain why abacus experts can reveal the exceptional computational skills compared to non-experts after intensive training

Prospective demonstration of brain plasticity after intensive abacus-based mental calculation training: An fMRI study

Science.gov (United States)

Chen, C. L.; Wu, T. H.; Cheng, M. C.; Huang, Y. H.; Sheu, C. Y.; Hsieh, J. C.; Lee, J. S.

2006-12-01

Abacus-based mental calculation is a unique Chinese culture. The abacus experts can perform complex computations mentally with exceptionally fast speed and high accuracy. However, the neural bases of computation processing are not yet clearly known. This study used a BOLD contrast 3T fMRI system to explore the brain activation differences between abacus experts and non-expert subjects. All the acquired data were analyzed using SPM99 software. From the results, different ways of performing calculations between the two groups were seen. The experts tended to adopt efficient visuospatial/visuomotor strategy (bilateral parietal/frontal network) to process and retrieve all the intermediate and final results on the virtual abacus during calculation. By contrast, coordination of several networks (verbal, visuospatial processing and executive function) was required in the normal group to carry out arithmetic operations. Furthermore, more involvement of the visuomotor imagery processing (right dorsal premotor area) for imagining bead manipulation and low level use of the executive function (frontal-subcortical area) for launching the relatively time-consuming sequentially organized process was noted in the abacus expert group than in the non-expert group. We suggest that these findings may explain why abacus experts can reveal the exceptional computational skills compared to non-experts after intensive training.

The impact of leadership, management and power in an international knowledge-intensive organization

Directory of Open Access Journals (Sweden)

Senni Kirjavainen

Full Text Available The shift to knowledge economies and the boom of knowledge-intensive organizations with their expert employees pose new challenges for leadership and management of development work. What is the appropriate amount and form of managerial control that is needed in knowledge-intensive development work? This paper focuses on illuminating the kind of leadership and management efforts that either support or hinder advancing development projects. The results highlight the paradoxical role of power and control, and reveal that employees need freedom and yet strong guidance and managerial commitment to develop work in order to stay motivated. Implications for leading knowledge-intensive development are discussed.

Expert judgement models in quantitative risk assessment

Energy Technology Data Exchange (ETDEWEB)

Rosqvist, T. [VTT Automation, Helsinki (Finland); Tuominen, R. [VTT Automation, Tampere (Finland)

1999-12-01

Expert judgement is a valuable source of information in risk management. Especially, risk-based decision making relies significantly on quantitative risk assessment, which requires numerical data describing the initiator event frequencies and conditional probabilities in the risk model. This data is seldom found in databases and has to be elicited from qualified experts. In this report, we discuss some modelling approaches to expert judgement in risk modelling. A classical and a Bayesian expert model is presented and applied to real case expert judgement data. The cornerstone in the models is the log-normal distribution, which is argued to be a satisfactory choice for modelling degree-of-belief type probability distributions with respect to the unknown parameters in a risk model. Expert judgements are qualified according to bias, dispersion, and dependency, which are treated differently in the classical and Bayesian approaches. The differences are pointed out and related to the application task. Differences in the results obtained from the different approaches, as applied to real case expert judgement data, are discussed. Also, the role of a degree-of-belief type probability in risk decision making is discussed.

Expert judgement models in quantitative risk assessment

International Nuclear Information System (INIS)

Rosqvist, T.; Tuominen, R.

1999-01-01

Expert judgement is a valuable source of information in risk management. Especially, risk-based decision making relies significantly on quantitative risk assessment, which requires numerical data describing the initiator event frequencies and conditional probabilities in the risk model. This data is seldom found in databases and has to be elicited from qualified experts. In this report, we discuss some modelling approaches to expert judgement in risk modelling. A classical and a Bayesian expert model is presented and applied to real case expert judgement data. The cornerstone in the models is the log-normal distribution, which is argued to be a satisfactory choice for modelling degree-of-belief type probability distributions with respect to the unknown parameters in a risk model. Expert judgements are qualified according to bias, dispersion, and dependency, which are treated differently in the classical and Bayesian approaches. The differences are pointed out and related to the application task. Differences in the results obtained from the different approaches, as applied to real case expert judgement data, are discussed. Also, the role of a degree-of-belief type probability in risk decision making is discussed

Predictive value of T2 relative signal intensity for response to somatostatin analogs in newly diagnosed acromegaly

Energy Technology Data Exchange (ETDEWEB)

Shen, Ming; Zhang, Qilin [Fudan University, Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Shanghai (China); Shanghai Pituitary Tumor Center, Shanghai (China); Liu, Wenjuan; Li, Yiming; Zhang, Zhaoyun; Ye, Hongying; He, Min; Lu, Bin; Yang, Yeping [Shanghai Pituitary Tumor Center, Shanghai (China); Fudan University, Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Shanghai (China); Wang, Meng [Fudan University, Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Shanghai (China); Soochow University, Division of Endocrinology, the Second Affiliated Hospital, Suzhou (China); Zhu, Jingjing [Shanghai Pituitary Tumor Center, Shanghai (China); Fudan University, Department of Neuropathology, Huashan Hospital, Shanghai Medical College, Shanghai (China); Ma, Zengyi; He, Wenqiang; Li, Shiqi; Shou, Xuefei; Qiao, Nidan; Ye, Zhao; Zhang, Yichao; Zhao, Yao; Wang, Yongfei [Fudan University, Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Shanghai (China); Shanghai Pituitary Tumor Center, Shanghai (China); Yao, Zhenwei [Shanghai Pituitary Tumor Center, Shanghai (China); Fudan University, Department of Radiology, Huashan Hospital, Shanghai Medical College, Shanghai (China); Lu, Yun [Fudan University, Department of Nuclear Medicine, Huashan Hospital, Shanghai Medical College, Shanghai (China)

2016-11-15

The difficulty of predicting the efficacy of somatostatin analogs (SSA) is not fully resolved. Here, we quantitatively evaluated the predictive value of relative signal intensity (rSI) on T1- and T2-weighted magnetic resonance imaging (MRI) for the short-term efficacy (3 months) of SSA therapy in patients with active acromegaly and assessed the correlation between MRI rSI and expression of somatostatin receptors (SSTR). This was a retrospective review of prospectively recorded data. Ninety-two newly diagnosed patients (37 males and 55 females) with active acromegaly were recruited. All patients were treated with pre-surgical SSA, followed by reassessment and transspenoidal surgery. rSI values were generated by calculating the ratio of SI in the tumor to the SI of normal frontal white matter. The Youden indices were calculated to determine the optimal cutoff of rSI to determine the efficacy of SSA. The correlation between rSI and expression of SSTR2/5 was analyzed by the Spearman rank correlation coefficient. T2 rSI was strongly correlated with biochemical sensitivity to SSA. The cutoff value of T2 rSI to distinguish biochemical sensitivity was 1.205, with a positive predictive value (PPV) of 81.5 % and a negative predictive value (NPV) of 77.3 %. No correlation was found between MRI and tumor size sensitivity. Moreover, T2 rSI was negatively correlated with the expression of SSTR5. T2 rSI correlates with the expression of SSTR5 and quantitatively predicts the biochemical efficacy of SSA in acromegaly. (orig.)

Predictive value of T2 relative signal intensity for response to somatostatin analogs in newly diagnosed acromegaly

International Nuclear Information System (INIS)

Shen, Ming; Zhang, Qilin; Liu, Wenjuan; Li, Yiming; Zhang, Zhaoyun; Ye, Hongying; He, Min; Lu, Bin; Yang, Yeping; Wang, Meng; Zhu, Jingjing; Ma, Zengyi; He, Wenqiang; Li, Shiqi; Shou, Xuefei; Qiao, Nidan; Ye, Zhao; Zhang, Yichao; Zhao, Yao; Wang, Yongfei; Yao, Zhenwei; Lu, Yun

2016-01-01

The difficulty of predicting the efficacy of somatostatin analogs (SSA) is not fully resolved. Here, we quantitatively evaluated the predictive value of relative signal intensity (rSI) on T1- and T2-weighted magnetic resonance imaging (MRI) for the short-term efficacy (3 months) of SSA therapy in patients with active acromegaly and assessed the correlation between MRI rSI and expression of somatostatin receptors (SSTR). This was a retrospective review of prospectively recorded data. Ninety-two newly diagnosed patients (37 males and 55 females) with active acromegaly were recruited. All patients were treated with pre-surgical SSA, followed by reassessment and transspenoidal surgery. rSI values were generated by calculating the ratio of SI in the tumor to the SI of normal frontal white matter. The Youden indices were calculated to determine the optimal cutoff of rSI to determine the efficacy of SSA. The correlation between rSI and expression of SSTR2/5 was analyzed by the Spearman rank correlation coefficient. T2 rSI was strongly correlated with biochemical sensitivity to SSA. The cutoff value of T2 rSI to distinguish biochemical sensitivity was 1.205, with a positive predictive value (PPV) of 81.5 % and a negative predictive value (NPV) of 77.3 %. No correlation was found between MRI and tumor size sensitivity. Moreover, T2 rSI was negatively correlated with the expression of SSTR5. T2 rSI correlates with the expression of SSTR5 and quantitatively predicts the biochemical efficacy of SSA in acromegaly. (orig.)

Predictive value of T2 relative signal intensity for response to somatostatin analogs in newly diagnosed acromegaly.

Science.gov (United States)

Shen, Ming; Zhang, Qilin; Liu, Wenjuan; Wang, Meng; Zhu, Jingjing; Ma, Zengyi; He, Wenqiang; Li, Shiqi; Shou, Xuefei; Li, Yiming; Zhang, Zhaoyun; Ye, Hongying; He, Min; Lu, Bin; Yao, Zhenwei; Lu, Yun; Qiao, Nidan; Ye, Zhao; Zhang, Yichao; Yang, Yeping; Zhao, Yao; Wang, Yongfei

2016-11-01

The difficulty of predicting the efficacy of somatostatin analogs (SSA) is not fully resolved. Here, we quantitatively evaluated the predictive value of relative signal intensity (rSI) on T1- and T2-weighted magnetic resonance imaging (MRI) for the short-term efficacy (3 months) of SSA therapy in patients with active acromegaly and assessed the correlation between MRI rSI and expression of somatostatin receptors (SSTR). This was a retrospective review of prospectively recorded data. Ninety-two newly diagnosed patients (37 males and 55 females) with active acromegaly were recruited. All patients were treated with pre-surgical SSA, followed by reassessment and transspenoidal surgery. rSI values were generated by calculating the ratio of SI in the tumor to the SI of normal frontal white matter. The Youden indices were calculated to determine the optimal cutoff of rSI to determine the efficacy of SSA. The correlation between rSI and expression of SSTR2/5 was analyzed by the Spearman rank correlation coefficient. T2 rSI was strongly correlated with biochemical sensitivity to SSA. The cutoff value of T2 rSI to distinguish biochemical sensitivity was 1.205, with a positive predictive value (PPV) of 81.5 % and a negative predictive value (NPV) of 77.3 %. No correlation was found between MRI and tumor size sensitivity. Moreover, T2 rSI was negatively correlated with the expression of SSTR5. T2 rSI correlates with the expression of SSTR5 and quantitatively predicts the biochemical efficacy of SSA in acromegaly.

Expert systems and nuclear safety

International Nuclear Information System (INIS)

Beltracchi, L.

1990-01-01

The US Nuclear Regulatory Commission (NRC) and the Electric Power Research Institute have initiated a broad-based exploration of means to evaluate the potential applications of expert systems in the nuclear industry. This exploratory effort will assess the use of expert systems to augment the diagnostic and decision-making capabilities of personnel with the goal of enhancing productivity, reliability, and performance. The initial research effort is the development and documentation of guidelines for verifying and validating (V and V) expert systems. An initial application of expert systems in the nuclear industry is to aid operations and maintenance personnel in decision-making tasks. The scope of the decision aiding covers all types of cognitive behavior consisting of skill, rule, and knowledge-based behavior. For example, procedure trackers were designed and tested to support rule-based behavior. Further, these systems automate many of the tedious, error-prone human monitoring tasks, thereby reducing the potential for human error. The paper version of the procedure contains the knowledge base and the rules and thus serves as the basis of the design verification of the procedure tracker. Person-in-the-loop tests serve as the basis for the validation of a procedure tracker. When conducting validation tests, it is important to ascertain that the human retains the locus of control in the use of the expert system

Expert systems: an alternative paradigm

Energy Technology Data Exchange (ETDEWEB)

Coombs, M.; Alty, J.

1984-01-01

There has recently been a significant effort by the AI community to interest industry in the potential of expert systems. However, this has resulted in far fewer substantial applications projects than might be expected. This article argues that this is because human experts are rarely required to perform the role that computer-based experts are programmed to adopt. Instead of being called in to answer well-defined problems, they are more often asked to assist other experts to extend and refine their understanding of a problem area at the junction of their two domains of knowledge. This more properly involves educational rather than problem-solving skills. An alternative approach to expert system design is proposed based upon guided discovery learning. The user is provided with a supportive environment for a particular class of problem, the system predominantly acting as an adviser rather than directing the interaction. The environment includes a database of domain knowledge, a set of procedures for its application to a concrete problem, and an intelligent machine-based adviser to judge the user's effectiveness and advise on strategy. The procedures focus upon the use of user generated explanations both to promote the application of domain knowledge and to expose understanding difficulties. Simple database PROLOG is being used as the subject material for the prototype system which is known as MINDPAD. 30 references.

Paradigms and building tools for real-time expert systems

International Nuclear Information System (INIS)

Behrens, U.; Flasinski, M.; Hagge, L.; Ohrenberg, K.

1994-01-01

An expert system is a software which can simulate the problem solving behavior of a human expert. The rule-based paradigm is chosen to describe the different aspects involved in expert system development. Differences between expert systems and common procedural or object-oriented programs are investigated. Expert system shells are introduced as a building tool for expert systems, together with some guidelines on the evaluation of such shells. A discussion of special needs for real-time expert system development concludes the paper

Balance, Sensorimotor, and Cognitive Performance in Long-Year Expert Senior Ballroom Dancers

Directory of Open Access Journals (Sweden)

Jan-Christoph Kattenstroth

2011-01-01

Full Text Available Physical fitness is considered a major factor contributing to the maintenance of independent living and everyday competence. In line with this notion, it has been shown that several years of amateur dancing experience can exert beneficial effects not only on balance and posture but also on tactile, motor, and cognitive functions in older people. This raises the question of whether an even more extensive schedule of dancing, including competitive tournaments, would further enhance these positive effects. We therefore assessed posture, balance, and reaction times, as well as motor, tactile, and cognitive performance in older expert ballroom dancers with several years of competitive experience. We found substantially better performance in the expert group than in the controls in terms of expertise-related domains like posture, balance, and reaction times. However, there was no generalization of positive effects to those domains that were found to be improved in amateur dancers, such as tactile and cognitive performance, suggesting that there might be an optimal range of intervention intensity to maintain health and independence throughout the human lifespan.

Transvaginal ultrasound assessment of myometrial and cervical stroma invasion in women with endometrial cancer -interobserver reproducibility among ultrasound experts and gynaecologists

DEFF Research Database (Denmark)

Eriksson, LS; Lindqvist, PG; Flöter Rådestad, A

2014-01-01

OBJECTIVES: To assess interobserver reproducibility among ultrasound experts and gynaecologists in the prediction of deep myometrial- and cervical stroma invasion by transvaginal ultrasound in women with endometrial cancer. METHODS: Video-clips of the corpus- and cervix uteri of 53 women...... with endometrial cancer, examined preoperatively by the same ultrasound expert, were integrated in a digitalized survey. Nine ultrasound experts and 9 gynaecologists evaluated presence or absence of deep myometrial- and cervical stroma invasion. Histopathology from hysterectomy specimen was used as gold standard.......001). CONCLUSION: Preoperative ultrasound assessment of deep myometrial- and cervical stroma invasion in endometrial cancer is best performed by ultrasound experts, as they show a higher degree of agreement to histopathology and higher interobserver reproducibility in the assessment of cervical stromal invasion....

Forensic comparison and matching of fingerprints: using quantitative image measures for estimating error rates through understanding and predicting difficulty.

Directory of Open Access Journals (Sweden)

Philip J Kellman

Full Text Available Latent fingerprint examination is a complex task that, despite advances in image processing, still fundamentally depends on the visual judgments of highly trained human examiners. Fingerprints collected from crime scenes typically contain less information than fingerprints collected under controlled conditions. Specifically, they are often noisy and distorted and may contain only a portion of the total fingerprint area. Expertise in fingerprint comparison, like other forms of perceptual expertise, such as face recognition or aircraft identification, depends on perceptual learning processes that lead to the discovery of features and relations that matter in comparing prints. Relatively little is known about the perceptual processes involved in making comparisons, and even less is known about what characteristics of fingerprint pairs make particular comparisons easy or difficult. We measured expert examiner performance and judgments of difficulty and confidence on a new fingerprint database. We developed a number of quantitative measures of image characteristics and used multiple regression techniques to discover objective predictors of error as well as perceived difficulty and confidence. A number of useful predictors emerged, and these included variables related to image quality metrics, such as intensity and contrast information, as well as measures of information quantity, such as the total fingerprint area. Also included were configural features that fingerprint experts have noted, such as the presence and clarity of global features and fingerprint ridges. Within the constraints of the overall low error rates of experts, a regression model incorporating the derived predictors demonstrated reasonable success in predicting objective difficulty for print pairs, as shown both in goodness of fit measures to the original data set and in a cross validation test. The results indicate the plausibility of using objective image metrics to predict expert

Forensic comparison and matching of fingerprints: using quantitative image measures for estimating error rates through understanding and predicting difficulty.

Science.gov (United States)

Kellman, Philip J; Mnookin, Jennifer L; Erlikhman, Gennady; Garrigan, Patrick; Ghose, Tandra; Mettler, Everett; Charlton, David; Dror, Itiel E

2014-01-01

Latent fingerprint examination is a complex task that, despite advances in image processing, still fundamentally depends on the visual judgments of highly trained human examiners. Fingerprints collected from crime scenes typically contain less information than fingerprints collected under controlled conditions. Specifically, they are often noisy and distorted and may contain only a portion of the total fingerprint area. Expertise in fingerprint comparison, like other forms of perceptual expertise, such as face recognition or aircraft identification, depends on perceptual learning processes that lead to the discovery of features and relations that matter in comparing prints. Relatively little is known about the perceptual processes involved in making comparisons, and even less is known about what characteristics of fingerprint pairs make particular comparisons easy or difficult. We measured expert examiner performance and judgments of difficulty and confidence on a new fingerprint database. We developed a number of quantitative measures of image characteristics and used multiple regression techniques to discover objective predictors of error as well as perceived difficulty and confidence. A number of useful predictors emerged, and these included variables related to image quality metrics, such as intensity and contrast information, as well as measures of information quantity, such as the total fingerprint area. Also included were configural features that fingerprint experts have noted, such as the presence and clarity of global features and fingerprint ridges. Within the constraints of the overall low error rates of experts, a regression model incorporating the derived predictors demonstrated reasonable success in predicting objective difficulty for print pairs, as shown both in goodness of fit measures to the original data set and in a cross validation test. The results indicate the plausibility of using objective image metrics to predict expert performance and

Computerized prediction of intensive care unit discharge after cardiac surgery: development and validation of a Gaussian processes model

Directory of Open Access Journals (Sweden)

Meyfroidt Geert

2011-10-01

Full Text Available Abstract Background The intensive care unit (ICU length of stay (LOS of patients undergoing cardiac surgery may vary considerably, and is often difficult to predict within the first hours after admission. The early clinical evolution of a cardiac surgery patient might be predictive for his LOS. The purpose of the present study was to develop a predictive model for ICU discharge after non-emergency cardiac surgery, by analyzing the first 4 hours of data in the computerized medical record of these patients with Gaussian processes (GP, a machine learning technique. Methods Non-interventional study. Predictive modeling, separate development (n = 461 and validation (n = 499 cohort. GP models were developed to predict the probability of ICU discharge the day after surgery (classification task, and to predict the day of ICU discharge as a discrete variable (regression task. GP predictions were compared with predictions by EuroSCORE, nurses and physicians. The classification task was evaluated using aROC for discrimination, and Brier Score, Brier Score Scaled, and Hosmer-Lemeshow test for calibration. The regression task was evaluated by comparing median actual and predicted discharge, loss penalty function (LPF ((actual-predicted/actual and calculating root mean squared relative errors (RMSRE. Results Median (P25-P75 ICU length of stay was 3 (2-5 days. For classification, the GP model showed an aROC of 0.758 which was significantly higher than the predictions by nurses, but not better than EuroSCORE and physicians. The GP had the best calibration, with a Brier Score of 0.179 and Hosmer-Lemeshow p-value of 0.382. For regression, GP had the highest proportion of patients with a correctly predicted day of discharge (40%, which was significantly better than the EuroSCORE (p Conclusions A GP model that uses PDMS data of the first 4 hours after admission in the ICU of scheduled adult cardiac surgery patients was able to predict discharge from the ICU as a

Necessity for training of experts on energy efficiency and energy management

International Nuclear Information System (INIS)

Gramatikov, Plamen

2015-01-01

The energy intensity of the Bulgarian GDP is the highest one in comparison with other EU countries. This fact leads to low competitiveness of Bulgarian goods at the international markets. The country lacks a sufficient number of well trained experts on energy efficiency and energy management which requires development of such educational programs in Bachelor and Master's curricula of the universities. The Master's program on Energy Management and Sustainable Energy Development developed in the Physics Department is shortly presented in this paper. This curriculum must be introduced in all technical areas of SWU if it likes to be adequate to current needs of the country and society.

ART-Ada: An Ada-based expert system tool

Science.gov (United States)

Lee, S. Daniel; Allen, Bradley P.

1991-01-01

The Department of Defense mandate to standardize on Ada as the language for software systems development has resulted in increased interest in making expert systems technology readily available in Ada environments. NASA's Space Station Freedom is an example of the large Ada software development projects that will require expert systems in the 1990's. Another large scale application that can benefit from Ada based expert system tool technology is the Pilot's Associate (PA) expert system project for military combat aircraft. Automated Reasoning Tool (ART) Ada, an Ada Expert system tool is described. ART-Ada allow applications of a C-based expert system tool called ART-IM to be deployed in various Ada environments. ART-Ada is being used to implement several prototype expert systems for NASA's Space Station Freedom Program and the U.S. Air Force.

Methodology toward second generation expert systems

International Nuclear Information System (INIS)

Dormoy, J.L.

1989-01-01

So-called First Generation Expert Systems were aimed at capturing the expert's know-how. Though providing remarkable achievements, this first wave did not give the expected outcome. A new generation is getting out from the laboratories. Instead of remaining at a shallow level of knowledge - that is the unmotivated reasoning processes expressed by an expert when he is forced to tell them - one attempts to re-build this level of knowledge from the first principles which constitute the basis of an expert's knowledge. These systems are called deep knowledge-based, or second generation expert systems. Discussion in the three first parts rests on two examples: A first generation and a half system for process control in nuclear powers plants, than the system EXTRA for alarm processing in nuclear plants, wherein fonctional knowledge is explicitely represented. We show how deep knowledge can be implemented, and the advantages that can be expected from this methodology. Qualitative Physics is discussed in the next part. Future research developments as well as potential payoffs are mentioned [fr

False confessions, expert testimony, and admissibility.

Science.gov (United States)

Watson, Clarence; Weiss, Kenneth J; Pouncey, Claire

2010-01-01

The confession of a criminal defendant serves as a prosecutor's most compelling piece of evidence during trial. Courts must preserve a defendant's constitutional right to a fair trial while upholding the judicial interests of presenting competent and reliable evidence to the jury. When a defendant seeks to challenge the validity of that confession through expert testimony, the prosecution often contests the admissibility of the expert's opinion. Depending on the content and methodology of the expert's opinion, testimony addressing the phenomenon of false confessions may or may not be admissible. This article outlines the scientific and epistemological bases of expert testimony on false confession, notes the obstacles facing its admissibility, and provides guidance to the expert in formulating opinions that will reach the judge or jury. We review the 2006 New Jersey Superior Court decision in State of New Jersey v. George King to illustrate what is involved in the admissibility of false-confession testimony and use the case as a starting point in developing a best-practice approach to working in this area.

Progress in Ultrafast Intense Laser Science II

CERN Document Server

Yamanouchi, Kaoru; Agostini, Pierre; Ferrante, Gaetano

2007-01-01

This book series addresses a newly emerging interdisciplinary research field, Ultrafast Intense Laser Science, spanning atomic and molecular physics, molecular science, and optical science. Its progress is being stimulated by the recent development of ultrafast laser technologies. Highlights of this second volume include Coulomb explosion and fragmentation of molecules, control of chemical dynamics, high-order harmonic generation, propagation and filamentation, and laser-plasma interaction. All chapters are authored by foremost experts in their fields and the texts are written at a level accessible to newcomers and graduate students, each chapter beginning with an introductory overview.

Enhanced presurgical pain temporal summation response predicts post-thoracotomy pain intensity during the acute postoperative phase.

Science.gov (United States)

Weissman-Fogel, Irit; Granovsky, Yelena; Crispel, Yonathan; Ben-Nun, Alon; Best, Lael Anson; Yarnitsky, David; Granot, Michal

2009-06-01

Recent evidence points to an association between experimental pain measures obtained preoperatively and acute postoperative pain (POP). We hypothesized that pain temporal summation (TS) might be an additional predictor for POP insofar as it represents the neuroplastic changes that occur in the central nervous system following surgery. Therefore, a wide range of psychophysical tests (TS to heat and mechanical repetitive stimuli, pain threshold, and suprathreshold pain estimation) and personality tests (pain catastrophizing and anxiety levels) were administered prior to thoracotomy in 84 patients. POP ratings were evaluated on the 2nd and 5th days after surgery at rest (spontaneous pain) and in response to activity (provoked pain). Linear regression models revealed that among all assessed variables, enhanced TS and higher pain scores for mechanical stimulation were significantly associated with greater provoked POP intensity (overall r2 = 0.225, P = .008). Patients who did not demonstrate TS to both modalities reported lower scores of provoked POP as compared with patients who demonstrated TS in response to at least 1 modality (F = 4.59 P = .013). Despite the moderate association between pain catastrophizing and rest POP, none of the variables predicted the spontaneous POP intensity. These findings suggest that individual susceptibility toward a greater summation response may characterize patients who are potentially vulnerable to augmented POP. This study proposed the role of pain temporal summation assessed preoperatively as a significant psychophysical predictor for acute postoperative pain intensity. The individual profile of enhanced pain summation is associated with the greater likelihood of higher postoperative pain scores.

Expert PLSQL Practices

CERN Document Server

Beresniewicz, John

2011-01-01

Expert PL/SQL Practices is a book of collected wisdom on PL/SQL programming from some of the best and the brightest in the field. Each chapter is a deep-dive into a specific problem, technology, or feature set that you'll face as a PL/SQL programmer. Each author has chosen their topic out of the strong belief that what they share can make a positive difference in the quality and scalability of code that you write. The path to mastery begins with syntax and the mechanics of writing statements to make things happen. If you've reached that point with PL/SQL, then let the authors of Expert PL/SQL

Expert systems for superalloy studies

Science.gov (United States)

Workman, Gary L.; Kaukler, William F.

1990-01-01

There are many areas in science and engineering which require knowledge of an extremely complex foundation of experimental results in order to design methodologies for developing new materials or products. Superalloys are an area which fit well into this discussion in the sense that they are complex combinations of elements which exhibit certain characteristics. Obviously the use of superalloys in high performance, high temperature systems such as the Space Shuttle Main Engine is of interest to NASA. The superalloy manufacturing process is complex and the implementation of an expert system within the design process requires some thought as to how and where it should be implemented. A major motivation is to develop a methodology to assist metallurgists in the design of superalloy materials using current expert systems technology. Hydrogen embrittlement is disasterous to rocket engines and the heuristics can be very complex. Attacking this problem as one module in the overall design process represents a significant step forward. In order to describe the objectives of the first phase implementation, the expert system was designated Hydrogen Environment Embrittlement Expert System (HEEES).

T2-weighted signal intensity-selected volumetry for prediction of pathological complete response after preoperative chemoradiotherapy in locally advanced rectal cancer.

Science.gov (United States)

Kim, Sungwon; Han, Kyunghwa; Seo, Nieun; Kim, Hye Jin; Kim, Myeong-Jin; Koom, Woong Sub; Ahn, Joong Bae; Lim, Joon Seok

2018-06-01

To evaluate the diagnostic value of signal intensity (SI)-selected volumetry findings in T2-weighted magnetic resonance imaging (MRI) as a potential biomarker for predicting pathological complete response (pCR) to preoperative chemoradiotherapy (CRT) in patients with rectal cancer. Forty consecutive patients with pCR after preoperative CRT were compared with 80 age- and sex-matched non-pCR patients in a case-control study. SI-selected tumor volume was measured on post-CRT T2-weighted MRI, which included voxels of the treated tumor exceeding the SI (obturator internus muscle SI + [ischiorectal fossa fat SI - obturator internus muscle SI] × 0.2). Three blinded readers independently rated five-point pCR confidence scores and compared the diagnostic outcome with SI-selected volumetry findings. The SI-selected volumetry protocol was validated in 30 additional rectal cancer patients. The area under the receiver-operating characteristic curve (AUC) of SI-selected volumetry for pCR prediction was 0.831, with an optimal cutoff value of 649.6 mm 3 (sensitivity 0.850, specificity 0.725). The AUC of the SI-selected tumor volume was significantly greater than the pooled AUC of readers (0.707, p volumetry in post-CRT T2-weighted MRI can help predict pCR after preoperative CRT in patients with rectal cancer. • Fibrosis and viable tumor MRI signal intensities (SIs) are difficult to distinguish. • T2 SI-selected volumetry yields high diagnostic performance for assessing pathological complete response. • T2 SI-selected volumetry is significantly more accurate than readers and non-SI-selected volumetry. • Post-chemoradiation therapy T2-weighted MRI SI-selected volumetry facilitates prediction of pathological complete response.

Expert systems as decision tools

International Nuclear Information System (INIS)

Scott, C.K.

1989-01-01

The feasibility of using expert systems as an aid in regulatory compliance functions has been investigated. A literature review was carried out to identify applications of expert systems to regulatory affairs. A bibliography of the small literature on such applications was prepared. A prototype system, ARIES, was developed to demonstrate the use of an expert system as an aid to a Project Officer in assuring compliance with licence requirements. The system runs on a personal computer with a graphical interface. Extensive use is made of hypertext to link interrelated rules and requirements as well as to provide an explanation facility. Based on the performance of ARIES the development of a field version is recommended

Expert system for fast reactor diagnostic

International Nuclear Information System (INIS)

Parcy, J.P.

1982-09-01

A general description of expert systems is given. The operation of a fast reactor is reviewed. The expert system to the diagnosis of breakdowns limited to the reactor core. The structure of the system is described: specification of the diagnostics; structure of the data bank and evaluation of the rules; specification of the prediagnostics and evaluation; explanation of the diagnostics; time evolution of the system; comparison with other expert systems. Applications to some cases of faults are finally presented [fr

Contrast-enhanced transrectal ultrasound for prediction of prostate cancer aggressiveness: The role of normal peripheral zone time-intensity curves.

Science.gov (United States)

Huang, Hui; Zhu, Zheng-Qiu; Zhou, Zheng-Guo; Chen, Ling-Shan; Zhao, Ming; Zhang, Yang; Li, Hong-Bo; Yin, Li-Ping

2016-12-08

To assess the role of time-intensity curves (TICs) of the normal peripheral zone (PZ) in the identification of biopsy-proven prostate nodules using contrast-enhanced transrectal ultrasound (CETRUS). This study included 132 patients with 134 prostate PZ nodules. Arrival time (AT), peak intensity (PI), mean transit time (MTT), area under the curve (AUC), time from peak to one half (TPH), wash in slope (WIS) and time to peak (TTP) were analyzed using multivariate linear logistic regression and receiver operating characteristic (ROC) curves to assess whether combining nodule TICs with normal PZ TICs improved the prediction of prostate cancer (PCa) aggressiveness. The PI, AUC (p < 0.001 for both), MTT and TPH (p = 0.011 and 0.040 respectively) values of the malignant nodules were significantly higher than those of the benign nodules. Incorporating the PI and AUC values (both, p < 0.001) of the normal PZ TIC, but not the MTT and TPH values (p = 0.076 and 0.159 respectively), significantly improved the AUC for prediction of malignancy (PI: 0.784-0.923; AUC: 0.758-0.891) and assessment of cancer aggressiveness (p < 0.001). Thus, all these findings indicate that incorporating normal PZ TICs with nodule TICs in CETRUS readings can improve the diagnostic accuracy for PCa and cancer aggressiveness assessment.

Applications of geographic information system and expert system for urban runoff and water quality management

Energy Technology Data Exchange (ETDEWEB)

Lee, Beum-Hee [Pai Chai University, Taejeon(Korea)

2001-06-30

It is very important to select appropriate methods of collecting, predicting, and analyzing information for the development of urban water resources and the prevention of disasters. Thus, in this study an accurate data generation method is developed using Geographic Information System (GIS) and Remote Sensing (RS). The methods of development and application of an expert system are suggested to solve more efficiently the problems of water resources and quality induced by the rapid urbanization. The time-varying data in a large region, the An-Yang Cheon watershed, were reasonably obtained by the application of the GIS using ARC/INFO and RS data. The ESPE (Expert System for Parameter Estimation), an expert system is developed using the CLIPS 6.0. The simulated results showed agreement with the measured data globally. These methods are expected to efficiently simulate the runoff and water quality in the rapidly varying urban area. (author). 10 refs., 4 tabs., 10 figs.

21 CFR 516.141 - Qualified expert panels.

Science.gov (United States)

2010-04-01

... choose members for the qualified expert panel in accordance with selection criteria listed in paragraph... whether the proposed qualified expert panel meets the selection criteria prior to the panel beginning its... Committee Act, as amended, 5 U.S.C. App. (b) Criteria for the selection of a qualified expert panel. (1) A...

Differentiating Experts' Anticipatory Skills in Beach Volleyball

Science.gov (United States)

Canal-Bruland, Rouwen; Mooren, Merel; Savelsbergh, Geert J. P.

2011-01-01

In this study, we examined how perceptual-motor expertise and watching experience contribute to anticipating the outcome of opponents' attacking actions in beach volleyball. To this end, we invited 8 expert beach volleyball players, 8 expert coaches, 8 expert referees, and 8 control participants with no beach volleyball experience to watch videos…

Measuring the Effectiveness of Gamesourcing Expert Oil Painting Annotations

NARCIS (Netherlands)

M.C. Traub (Myriam); J.R. van Ossenbruggen (Jacco); J. He (Jiyin); L. Hardman (Lynda); M. de Rijke (Maarten); T Kentner; A.P. de Vries (Arjen); F.M.G. de Jong (Franciska); C. Zhai (ChengXiang ); K. Hofmann (Katja); K. Radinsky

2014-01-01

htmlabstractTasks that require users to have expert knowledge are diffi- cult to crowdsource. They are mostly too complex to be carried out by non-experts and the available experts in the crowd are difficult to target. Adapting an expert task into a non-expert user task, thereby enabling the

STEMing the tide: using ingroup experts to inoculate women's self-concept in science, technology, engineering, and mathematics (STEM).

Science.gov (United States)

Stout, Jane G; Dasgupta, Nilanjana; Hunsinger, Matthew; McManus, Melissa A

2011-02-01

Three studies tested a stereotype inoculation model, which proposed that contact with same-sex experts (advanced peers, professionals, professors) in academic environments involving science, technology, engineering, and mathematics (STEM) enhances women's self-concept in STEM, attitudes toward STEM, and motivation to pursue STEM careers. Two cross-sectional controlled experiments and 1 longitudinal naturalistic study in a calculus class revealed that exposure to female STEM experts promoted positive implicit attitudes and stronger implicit identification with STEM (Studies 1-3), greater self-efficacy in STEM (Study 3), and more effort on STEM tests (Study 1). Studies 2 and 3 suggested that the benefit of seeing same-sex experts is driven by greater subjective identification and connectedness with these individuals, which in turn predicts enhanced self-efficacy, domain identification, and commitment to pursue STEM careers. Importantly, women's own self-concept benefited from contact with female experts even though negative stereotypes about their gender and STEM remained active. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

[Telemedicine correlation in retinopathy of prematurity between experts and non-expert observers].

Science.gov (United States)

Ossandón, D; Zanolli, M; López, J P; Stevenson, R; Agurto, R; Cartes, C

2015-01-01

To study the correlation between expert and non-expert observers in the reporting images for the diagnosis of retinopathy of prematurity (ROP) in a telemedicine setting. A cross-sectional, multicenter study, consisting of 25 sets of images of patients screened for ROP. They were evaluated by two experts in ROP and 1 non-expert and classified according to telemedicine classification, zone, stage, plus disease and Ells referral criteria. The telemedicine classification was: no ROP, mild ROP, type 2 ROP, or ROP that requires treatment. Ells referral criteria is defined as the presence at least one of the following: ROP in zone I, Stage 3 in zone I or II, or plus+ For statistical analysis, SPSS 16.0 was used. For correlation, Kappa value was performed. There was a high correlation between observers for the assessment of ROP stage (0.75; 0.54-0.88) plus disease (0.85; 0.71-0.92), and Ells criteria (0.89; 0.83-1.0). However, inter-observer values were low for zone (0.41; 0.27-0.54) and telemedicine classification (0.43; 0.33-0.6). When evaluating telemedicine images by examiners with different levels of expertise in ROP, the Ells criteria gave the best correlation. In addition, stage of disease and plus disease have good correlation among observers. In contrast, the correlation between observers was low for zone and telemedicine classification. Copyright © 2014 Sociedad Española de Oftalmología. Published by Elsevier España, S.L.U. All rights reserved.

Expert system for liquid low-level waste management

International Nuclear Information System (INIS)

Ferrada, J.J.

1992-01-01

An expert system prototype has been developed to support system analysis activities at the Oak Ridge National Laboratory (ORNL) for waste management tasks. This expert system will aid in prioritizing radioactive waste streams for treatment and disposal by evaluating the severity and treatability of the problem as well as the final waste form. The objectives of the expert system development included: (1) collecting information on process treatment technologies for liquid low-level waste (LLLW) that can be incorporated in the knowledge base of the expert system, and (2) producing a prototype that suggests processes and disposal technologies for the ORNL LLLW system. The concept under which the expert system has been designed is integration of knowledge. There are many sources of knowledge (data bases, text files, simulation programs, etc.) that an expert would regularly consult in order to solve a problem of liquid waste management. The expert would normally know how to extract the information from these different sources of knowledge. The general scope of this project would be to include as much pertinent information as possible within the boundaries of the expert system. As a result, the user, who may not be an expert in every aspect of liquid waste management, may be able to apply the content of the information to a specific waste problem. This paper gives the methodological steps to develop the expert system under this general framework

Reflection group on 'Expert Culture'

Energy Technology Data Exchange (ETDEWEB)

Eggermont, G

2000-07-01

As part of SCK-CEN's social sciences and humanities programme, a reflection group on 'Expert Culture' was established. The objectives of the reflection group are: (1) to clarify the role of SCK-CEN experts; (2) to clarify the new role of expertise in the evolving context of risk society; (3) to confront external views and internal SCK-CEN experiences on expert culture; (4) to improve trust building of experts and credibility of SCK-CEN as a nuclear actor in society; (5) to develop a draft for a deontological code; (6) to integrate the approach in training on assertivity and communication; (7) to create an output for a topical day on the subject of expert culture. The programme, achievements and perspectives of the refection group are summarised.

Expert Systems for auditing management information systems

Directory of Open Access Journals (Sweden)

Gheroghe Popescu

2007-05-01

Full Text Available Expert systems are built with the help of: specialised programming languages or expert system generators (shell. But this structure was reached after tens of years of work and research, because expert systems are nothing but pragmatic capitalisation of the results of research carried out in artificial intelligence and theory of knowledge.

Expert and Novice Approaches to Using Graphs: Evidence from Eye-Track Experiments

Science.gov (United States)

Wirth, K. R.; Lindgren, J. M.

2015-12-01

Professionals and students in geology use an array of graphs to study the earth, but relatively little detail is known about how users interact with these graphs. Comprehension of graphical information in the earth sciences is further complicated by the common use of non-traditional formats (e.g., inverted axes, logarithmic scales, normalized plots, ternary diagrams). Many educators consider graph-reading skills an important outcome of general education science curricula, so it is critical that we understand both the development of graph-reading skills and the instructional practices that are most efficacious. Eye-tracking instruments provide quantitative information about eye movements and offer important insights into the development of expertise in graph use. We measured the graph reading skills and eye movements of novices (students with a variety of majors and educational attainment) and experts (faculty and staff from a variety of disciplines) while observing traditional and non-traditional graph formats. Individuals in the expert group consistently demonstrated significantly greater accuracy in responding to questions (e.g., retrieval, interpretation, prediction) about graphs. Among novices, only the number of college math and science courses correlated with response accuracy. Interestingly, novices and experts exhibited similar eye-tracks when they first encountered a new graph; they typically scanned through the title, x and y-axes, and data regions in the first 5-15 seconds. However, experts are readily distinguished from novices by a greater number of eye movements (20-35%) between the data and other graph elements (e.g., title, x-axis, y-axis) both during and after the initial orientation phase. We attribute the greater eye movements between the different graph elements an outcome of the generally better-developed self-regulation skills (goal-setting, monitoring, self-evaluation) that likely characterize individuals in our expert group.

Comparison of tree types of models for the prediction of final academic achievement

Directory of Open Access Journals (Sweden)

Silvana Gasar

2002-12-01

Full Text Available For efficient prevention of inappropriate secondary school choices and by that academic failure, school counselors need a tool for the prediction of individual pupil's final academic achievements. Using data mining techniques on pupils' data base and expert modeling, we developed several models for the prediction of final academic achievement in an individual high school educational program. For data mining, we used statistical analyses, clustering and two machine learning methods: developing classification decision trees and hierarchical decision models. Using an expert system shell DEX, an expert system, based on a hierarchical multi-attribute decision model, was developed manually. All the models were validated and evaluated from the viewpoint of their applicability. The predictive accuracy of DEX models and decision trees was equal and very satisfying, as it reached the predictive accuracy of an experienced counselor. With respect on the efficiency and difficulties in developing models, and relatively rapid changing of our education system, we propose that decision trees are used in further development of predictive models.

Expert judgment based multi-criteria decision model to address uncertainties in risk assessment of nanotechnology-enabled food products

International Nuclear Information System (INIS)

Flari, Villie; Chaudhry, Qasim; Neslo, Rabin; Cooke, Roger

2011-01-01

Currently, risk assessment of nanotechnology-enabled food products is considered difficult due to the large number of uncertainties involved. We developed an approach which could address some of the main uncertainties through the use of expert judgment. Our approach employs a multi-criteria decision model, based on probabilistic inversion that enables capturing experts’ preferences in regard to safety of nanotechnology-enabled food products, and identifying their opinions in regard to the significance of key criteria that are important in determining the safety of such products. An advantage of these sample-based techniques is that they provide out-of-sample validation and therefore a robust scientific basis. This validation in turn adds predictive power to the model developed. We achieved out-of-sample validation in two ways: (1) a portion of the expert preference data was excluded from the model’s fitting and was then predicted by the model fitted on the remaining rankings and (2) a (partially) different set of experts generated new scenarios, using the same criteria employed in the model, and ranked them; their ranks were compared with ranks predicted by the model. The degree of validation in each method was less than perfect but reasonably substantial. The validated model we applied captured and modelled experts’ preferences regarding safety of hypothetical nanotechnology-enabled food products. It appears therefore that such an approach can provide a promising route to explore further for assessing the risk of nanotechnology-enabled food products.

Rapid improvements in emotion regulation predict intensive treatment outcome for patients with bulimia nervosa and purging disorder.

Science.gov (United States)

MacDonald, Danielle E; Trottier, Kathryn; Olmsted, Marion P

2017-10-01

Rapid and substantial behavior change (RSBC) early in cognitive behavior therapy (CBT) for eating disorders is the strongest known predictor of treatment outcome. Rapid change in other clinically relevant variables may also be important. This study examined whether rapid change in emotion regulation predicted treatment outcomes, beyond the effects of RSBC. Participants were diagnosed with bulimia nervosa or purging disorder (N = 104) and completed ≥6 weeks of CBT-based intensive treatment. Hierarchical regression models were used to test whether rapid change in emotion regulation variables predicted posttreatment outcomes, defined in three ways: (a) binge/purge abstinence; (b) cognitive eating disorder psychopathology; and (c) depression symptoms. Baseline psychopathology and emotion regulation difficulties and RSBC were controlled for. After controlling for baseline variables and RSBC, rapid improvement in access to emotion regulation strategies made significant unique contributions to the prediction of posttreatment binge/purge abstinence, cognitive psychopathology of eating disorders, and depression symptoms. Individuals with eating disorders who rapidly improve their belief that they can effectively modulate negative emotions are more likely to achieve a variety of good treatment outcomes. This supports the formal inclusion of emotion regulation skills early in CBT, and encouraging patient beliefs that these strategies are helpful. © 2017 Wiley Periodicals, Inc.

Climate Prediction Center

Science.gov (United States)

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Organization Enter Search Term(s): Search Search the CPC Go NCEP Quarterly Newsletter Climate Highlights U.S Climate-Weather El Niño/La Niña MJO Blocking AAO, AO, NAO, PNA Climatology Global Monsoons Expert

GIS Supported Landslide Susceptibility Modeling at Regional Scale: An Expert-Based Fuzzy Weighting Method

Directory of Open Access Journals (Sweden)

Christos Chalkias

2014-04-01

Full Text Available The main aim of this paper is landslide susceptibility assessment using fuzzy expert-based modeling. Factors that influence landslide occurrence, such as elevation, slope, aspect, lithology, land cover, precipitation and seismicity were considered. Expert-based fuzzy weighting (EFW approach was used to combine these factors for landslide susceptibility mapping (Peloponnese, Greece. This method produced a landslide susceptibility map of the investigated area. The landslides under investigation have more or less same characteristics: lateral based and downslope shallow movement of soils or rocks. The validation of the model reveals, that predicted susceptibility levels are found to be in good agreement with the past landslide occurrences. Hence, the obtained landslide susceptibility map could be acceptable, for landslide hazard prevention and mitigation at regional scale.

Combination and Selection of Traffic Safety Expert Judgments for the Prevention of Driving Risks

Directory of Open Access Journals (Sweden)

Andrés Redchuk

2012-11-01

Full Text Available In this paper, we describe a new framework to combine experts’ judgments for the prevention of driving risks in a cabin truck. In addition, the methodology shows how to choose among the experts the one whose predictions fit best the environmental conditions. The methodology is applied over data sets obtained from a high immersive cabin truck simulator in natural driving conditions. A nonparametric model, based in Nearest Neighbors combined with Restricted Least Squared methods is developed. Three experts were asked to evaluate the driving risk using a Visual Analog Scale (VAS, in order to measure the driving risk in a truck simulator where the vehicle dynamics factors were stored. Numerical results show that the methodology is suitable for embedding in real time systems.

Expert Cold Structure Development

Science.gov (United States)

Atkins, T.; Demuysere, P.

2011-05-01

The EXPERT Program is funded by ESA. The objective of the EXPERT mission is to perform a sub-orbital flight during which measurements of critical aero- thermodynamic phenomena will be obtained by using state-of-the-art instrumentation. As part of the EXPERT Flight Segment, the responsibility of the Cold Structure Development Design, Manufacturing and Validation was committed to the Belgian industrial team SONACA/SABCA. The EXPERT Cold Structure includes the Launcher Adapter, the Bottom Panel, the Upper Panel, two Cross Panels and the Parachute Bay. An additional Launcher Adapter was manufactured for the separation tests. The selected assembly definition and manufacturing technologies ( machined parts and sandwich panels) were dictated classically by the mass and stiffness, but also by the CoG location and the sensitive separation interface. Used as support for the various on-board equipment, the Cold Structure is fixed to but thermally uncoupled from the PM 1000 thermal shield. It is protect on its bottom panel by a thermal blanket. As it is a protoflight, analysis was the main tool for the verification. Low level stiffness and modal analysis tests have also been performed on the Cold Structure equipped with its ballast. It allowed to complete its qualification and to prepare SONACA/SABCA support for the system dynamic tests foreseen in 2011. The structure was finally coated with a thermal control black painting and delivered on time to Thales Alenia Space-Italy end of March 201.

Development of Lightning Observation Network in the Western Pacific Region for the Intensity Prediction of Severe Weather

Science.gov (United States)

Sato, M.; Takahashi, Y.; Yamashita, K.; Kubota, H.; Hamada, J. I.; Momota, E.; Marciano, J. J.

2017-12-01

Lightning activity represents the thunderstorm activity, that is, the precipitation and/or updraft intensity and area. Thunderstorm activity is also an important parameter in terms of the energy inputs from the ocean to the atmosphere inside tropical cyclone, which is one of severe weather events. Recent studies suggest that it is possible to predict the maximum wind velocity and minimum pressure near the center of the tropical cyclone by one or two days before if we monitor the lightning activities in the tropical cyclone. Many countries in the western Pacific region suffer from the attack of tropical cyclone (typhoon) and have a strong demand to predict the intensity development of typhoons. Thus, we started developing a new lightning observation system and installing the observation system at Guam, Palau, and Manila in the Philippines from this summer. The lightning observation system consists of a VLF sensor detecting lightning-excited electromagnetic waves in the frequency range of 1-5 kHz, an automatic data-processing unit, solar panels, and batteries. Lightning-excited pulse signals detected by the VLF sensor are automatically analyzed by the data-processing unit, and only the extracted information of the trigger time and pulse amplitude is transmitted to a data server via the 3G data communications. In addition, we are now developing an upgraded lightning and weather observation system, which will be installed at 50 automated weather stations in Metro Manila and 10 radar sites in the Philippines under the 5-year project (SATREPS) scheme. At the presentation, we will show the initial results derived from the lightning observation system in detail and will show the detailed future plan of the SATREPS project.

Artificial intelligence/expert (AI/EX) systems for steelworks pollution control

Energy Technology Data Exchange (ETDEWEB)

Schofield, N.; Le Louer, P.; Mirabile, D.; Hubner, R. [Corus UK Ltd., Rotherham (United Kingdom)

2002-07-01

The objectives of this project have been to develop and apply artificial intelligence and expert system (AI/EX) methods to improve the control and operational performance of steelworks' pollution control equipment and to assess the viability and benefits of using such systems in dynamic process plant applications. Four distinct sub-projects were carried out: an expert system incorporating knowledge-based rules and neural network simulations has been developed by Corus which provides plant personnel with a real-time condition monitoring tool for the plant. Abnormalities with plant operation are now instantly recognised and alarmed, allowing prioritised maintenance to increase plant availability. The LECES project focused on studies concerning three different sites in order to evaluate predictive emission monitoring systems using neural networks to replace conventional instrumental and controls in steelworks' combustion systems. VAI developed a software template for pollution control expert systems to demonstrate the transferability of AI/EX technology. This has been done through the development of a validated process database containing data from the Corus sub-project and the subsequent integration of this data with dynamic emission models to produce rules for input to an evaluation database. CSM developed a fuzzy logic controlled process management system applied to the biological treatment of coke-oven waste water. A pilot plant has been installed and results on simulations performed using the fuzzy logic system linked to a neural network simulator show that it is possible to obtain great advantages in the biological pilot plant performance.

Expert judgment for nuclear energy

International Nuclear Information System (INIS)

Choi, Young Sung; Lee, Sun Ho; Lee, Byong Whi

2000-01-01

Public perception on nuclear energy is much influenced by subjective impressions mostly formed through sensational and dramatic news of mass media or anti-nuclear groups. However, nuclear experts, those who have more relevant knowledge and information about nuclear energy, may have reasonable opinion based on scientific facts or inferences. Thus their opinion and consensus should be examined and taken into account during the process of nuclear energy policy formulation. For the purpose of eliciting experts' opinion, the web-based on-line survey system (eBOSS) was developed. Using the survey system, experts' views on nuclear energy were tallied, analyzed and compared with the public's. Based on the survey results, the paper suggests some recommendations about the future direction of the public information program in Korea

Stimulated Raman backscattering at high laser intensities

Energy Technology Data Exchange (ETDEWEB)

Skoric, M M [Vinca Inst. of Nuclear Sciences, Belgrade (Yugoslavia); Tajima, Toshiki; Sasaki, Akira; Maluckov, A; Jovanovic, M

1998-03-01

Signatures of Stimulated Raman backscattering of a short-pulse high-intensity laser interacting with an underdense plasma are discussed. We introduce a nonlinear three-wave interaction model that accounts for laser pump depletion and relativistic detuning. A mechanism is revealed based on a generic route to chaos, that predicts a progressive increase of the backscatter complexity with a growing laser intensity. Importance of kinetic effects is outlined and demonstrated in fluid-hybrid and particle simulations. As an application, we show that spectral anomalies of the backscatter, predicted by the above model, are consistent with recent sub-picosecond, high-intensity laser gas-target measurements at Livermore and elsewhere. Finally, a recently proposed scheme for generation of ultra-short, low-prepulse laser pulses by Raman backscattering in a thin foil target, is shown. (author)

Waste disposal experts meet

Energy Technology Data Exchange (ETDEWEB)

NONE

1959-01-15

Problems connected with the disposal into the sea of radioactive wastes from peaceful uses of atomic energy are being examined by a panel of experts, convened by the International Atomic Energy Agency. These experts from eight different countries held a first meeting at IAEA headquarters in Vienna from 4-9 December 1958, under the chairmanship of Dr. Harry Brynielsson, Director General of the Swedish Atomic Energy Company. The countries represented are: Canada, Czechoslovakia, France, Japan, Netherlands, United Kingdom and United States. The group will meet again in 1959. (author)

Bathyphotometer bioluminescence potential measurements: A framework for characterizing flow agitators and predicting flow-stimulated bioluminescence intensity

Science.gov (United States)

Latz, Michael I.; Rohr, Jim

2013-07-01

BBP. This correlation, when further scaled by pipe diameter, effectively predicted bioluminescence intensity in fully developed turbulent flow in a 0.83-cm i.d. pipe. Determining similar correlations between other bathyphotometer flow agitators and flow fields will allow bioluminescence potential measurements to become a more powerful tool for the oceanographic community.

Expert system for fault diagnosis in process control valves using fuzzy-logic

Energy Technology Data Exchange (ETDEWEB)

Carneiro, Alvaro L.G., E-mail: carneiro@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Porto Junior, Almir C.S., E-mail: almir@ctmsp.mar.mil.br [Centro Tecnologico da Marinha em Sao Paulo (CIANA/CTMSP), Ipero, SP (Brazil). Centro de Instrucao e Adestramento Nuclear de ARAMAR

2013-07-01

The models of asset maintenance of a process plant basically are classified in corrective maintenance, preventive, predictive and proactive (online). The corrective maintenance is the elementary and most obvious way of the maintenance models. The preventive maintenance consists in a fault prevention work, based on statistical studies that can lead to low efficiency or even an unexpected shutdown of the plant. Predictive maintenance aims to prevent equipment or systems failures through monitoring and tracking of parameters, allowing continuous operation as long as possible. The proactive maintenance usually includes predictive maintenance, emphasizing the root cause analysis of the failure. The maintenance predictive/proactive planning frequently uses software that integrates data from different systems, which facilitates a quick and effective decision- making. In nuclear plants this model has an important role regarding the reliability of equipment and systems. The main focus of this work is to study the development of a model of non-intrusive monitoring and diagnosis applied to process control valves using artificial intelligence by fuzzy logic technique, contributing in the development of predictive methodologies identifying faults in incipient state. The control valve analyzed belongs to a steam plant which simulates the secondary circuit of a PWR nuclear reactor - Pressurized Water Reactor. This study makes use of MATLAB language through the fuzzy logic toolbox which uses the method of inference Mamdani, acting by fuzzy conjunction, through Triangular Norms (t-norm) and Triangular Conorms (t-conorm). As input variables are used air pressure and displacement of the valve stem. Input data coming into the fuzzy system by graph of the automation system Delta V ® available in the plant, which receives a signal of electric current from an 'intelligent' positioned installed on the valve. The output variable is the 'status' of the valve. Through a

Expert system for fault diagnosis in process control valves using fuzzy-logic

International Nuclear Information System (INIS)

Carneiro, Alvaro L.G.; Porto Junior, Almir C.S.

2013-01-01

The models of asset maintenance of a process plant basically are classified in corrective maintenance, preventive, predictive and proactive (online). The corrective maintenance is the elementary and most obvious way of the maintenance models. The preventive maintenance consists in a fault prevention work, based on statistical studies that can lead to low efficiency or even an unexpected shutdown of the plant. Predictive maintenance aims to prevent equipment or systems failures through monitoring and tracking of parameters, allowing continuous operation as long as possible. The proactive maintenance usually includes predictive maintenance, emphasizing the root cause analysis of the failure. The maintenance predictive/proactive planning frequently uses software that integrates data from different systems, which facilitates a quick and effective decision- making. In nuclear plants this model has an important role regarding the reliability of equipment and systems. The main focus of this work is to study the development of a model of non-intrusive monitoring and diagnosis applied to process control valves using artificial intelligence by fuzzy logic technique, contributing in the development of predictive methodologies identifying faults in incipient state. The control valve analyzed belongs to a steam plant which simulates the secondary circuit of a PWR nuclear reactor - Pressurized Water Reactor. This study makes use of MATLAB language through the fuzzy logic toolbox which uses the method of inference Mamdani, acting by fuzzy conjunction, through Triangular Norms (t-norm) and Triangular Conorms (t-conorm). As input variables are used air pressure and displacement of the valve stem. Input data coming into the fuzzy system by graph of the automation system Delta V ® available in the plant, which receives a signal of electric current from an 'intelligent' positioned installed on the valve. The output variable is the 'status' of the valve. Through a rule base

External Validation of Risk Prediction Scores for Invasive Candidiasis in a Medical/Surgical Intensive Care Unit: An Observational Study

Science.gov (United States)

Ahmed, Armin; Baronia, Arvind Kumar; Azim, Afzal; Marak, Rungmei S. K.; Yadav, Reema; Sharma, Preeti; Gurjar, Mohan; Poddar, Banani; Singh, Ratender Kumar

2017-01-01

Background: The aim of this study was to conduct external validation of risk prediction scores for invasive candidiasis. Methods: We conducted a prospective observational study in a 12-bedded adult medical/surgical Intensive Care Unit (ICU) to evaluate Candida score >3, colonization index (CI) >0.5, corrected CI >0.4 (CCI), and Ostrosky's clinical prediction rule (CPR). Patients' characteristics and risk factors for invasive candidiasis were noted. Patients were divided into two groups; invasive candidiasis and no-invasive candidiasis. Results: Of 198 patients, 17 developed invasive candidiasis. Discriminatory power (area under receiver operator curve [AUROC]) for Candida score, CI, CCI, and CPR were 0.66, 0.67, 0.63, and 0.62, respectively. A large number of patients in the no-invasive candidiasis group (114 out of 181) were exposed to antifungal agents during their stay in ICU. Subgroup analysis was carried out after excluding such patients from no-invasive candidiasis group. AUROC of Candida score, CI, CCI, and CPR were 0.7, 0.7, 0.65, and 0.72, respectively, and positive predictive values (PPVs) were in the range of 25%–47%, along with negative predictive values (NPVs) in the range of 84%–96% in the subgroup analysis. Conclusion: Currently available risk prediction scores have good NPV but poor PPV. They are useful for selecting patients who are not likely to benefit from antifungal therapy. PMID:28904481

[Medical expert consensus in AH on the clinical use of triple fixed-dose antihypertensive therapy in Spain].

Science.gov (United States)

Mazón, P; Galve, E; Gómez, J; Gorostidi, M; Górriz, J L; Mediavilla, J D

The opinion of experts (different specialties) on the triple fixed-dose antihypertensive therapy in clinical practice may differ. Online questionnaire with controversial aspects of the triple therapy answered by panel of experts in hypertension (HT) using two-round modified Delphi method. The questionnaire was completed by 158 experts: Internal Medicine (49), Nephrology (26), Cardiology (83). Consensus was reached (agreement) on 27/45 items (60%); 7 items showed differences statistically significant. Consensus was reached regarding: Predictive factors in the need for combination therapy and its efficacy vs. increasing the dose of a pretreatment, and advantage of triple therapy (prescription/adherence/cost/pressure control) vs. free combination. This consensus provides an overview of the clinical use of triple therapy in moderate-severe and resistant/difficult to control HT. Copyright © 2016 SEH-LELHA. Publicado por Elsevier España, S.L.U. All rights reserved.

Enhancing Transparency in Multidisciplinary Expert Communication

International Nuclear Information System (INIS)

Hukki, Kristiina; Pulkkinen, Urho

2003-01-01

Faced with problems of public acceptance most nuclear waste management organisations now acknowledge the importance of transparency in their pursuit of solutions for high-level nuclear waste disposal. To make progress the implementing organizations need the trust of other stakeholders in the decision-making process. For such trust these outside stakeholders need knowledge on the grounds for the judgments and decisions made in different scientific and technical disciplines. Transparency is, however, at least as important for the multidisciplinary expert communication itself. As a matter of fact, the transparency of the internal expert interaction processes is a prerequisite for the true transparency of the communication between the implementer and the external stakeholder groups. The introduced conceptual framework has been developed for the identification of the requirements of safety-informed communication in multidisciplinary expert work in nuclear waste management. The framework offers a common thinking model and common concepts which can be utilized in the development of the communication practices. The basis of the framework is on the possibility to understand the safety-critical significance of one's work. The transparency of communication is, for its part, based on making explicit the relevant knowledge necessary for gaining the understanding. This supplementary knowledge, which is related to the substance issues but is not scientific-technical by nature, enhances the experts' awareness of the context of their own contribution and of the background of the other experts' contributions. The common conceptualization and modelling of the knowledge-related dependencies between the tasks make it possible to realize the significance of the supplementary knowledge for transparent communication in actual situations. They also facilitate the recognition of the need for different types of supplementary knowledge in the interfaces between the tasks. By enhancing mutual

Progress in Ultrafast Intense Laser Science III

CERN Document Server

Yamanouchi, Kaoru; Agostini, Pierre; Ferrante, Gaetano

2008-01-01

The PUILS series presents Progress in Ultrafast Intense Laser Science, a newly emerging interdisciplinary research field spanning atomic and molecular physics, molecular science, and optical science. PUILS has been stimulated by the recent development of ultrafast laser technologies. Each volume contains approximately 15 chapters, authored by researchers at the forefront. Each chapter opens with an overview of the topics to be discussed, so that researchers, who are not experts in the specific topics, as well as graduate students can grasp the importance and attractions of this sub-field of research, and these are followed by reports of cutting-edge discoveries. This third volume covers a diverse range of disciplines, focusing on such topics as strong field ionization of atoms, ionization and fragmentation of molecules and clusters, generation of high-order harmonics and attosecond pulses, filamentation and laser plasma interaction, and the development of ultrashort and ultrahigh-intensity light sources.

Classification of health webpages as expert and non expert with a reduced set of cross-language features.

Science.gov (United States)

Grabar, Natalia; Krivine, Sonia; Jaulent, Marie-Christine

2007-10-11

Making the distinction between expert and non expert health documents can help users to select the information which is more suitable for them, according to whether they are familiar or not with medical terminology. This issue is particularly important for the information retrieval area. In our work we address this purpose through stylistic corpus analysis and the application of machine learning algorithms. Our hypothesis is that this distinction can be performed on the basis of a small number of features and that such features can be language and domain independent. The used features were acquired in source corpus (Russian language, diabetes topic) and then tested on target (French language, pneumology topic) and source corpora. These cross-language features show 90% precision and 93% recall with non expert documents in source language; and 85% precision and 74% recall with expert documents in target language.

Earthquakes and Tectonics Expert Judgment Elicitation Project

International Nuclear Information System (INIS)

Coppersmith, K.J.; Perman, R.C.; Youngs, R.R.

1993-02-01

This report summarizes the results of the Earthquakes and Tectonics Expert Judgement Excitation Project sponsored by the Electric Power Research Institute (EPRI). The objectives of this study were two-fold: (1) to demonstrate methods for the excitation of expert judgement, and (2) to quantify the uncertainties associated with earthquake and tectonics issues for use in the EPRI-HLW performance assessment. Specifically, the technical issue considered is the probability of differential fault displacement through the proposed repository at Yucca Mountain, Nevada. For this study, a strategy for quantifying uncertainties was developed that relies on the judgements of multiple experts. A panel of seven geologists and seismologists was assembled to quantify the uncertainties associated with earthquake and tectonics issues for the performance assessment model. A series of technical workshops focusing on these issues were conducted. Finally, each expert was individually interviewed in order to elicit his judgement regarding the technical issues and to provide the technical basis for his assessment. This report summarizes the methodologies used to elicit the judgements of the earthquakes and tectonics experts (termed ''specialists''), and summarizes the technical assessments made by the expert panel

Expert judgement in performance assessment

International Nuclear Information System (INIS)

Wilmot, R.D.; Galson, D.A.

2000-01-01

This report is a pilot study that systematically describes the various types of expert judgement that are made throughout the development of a PA, and summarizes existing tools and practices for dealing with expert judgements. The report also includes recommendations for further work in the area of expert judgement. Expert judgements can be classified in a number of ways, including classification according to why the judgements are made and according to how the judgements are made. In terms of why judgements are made, there is a broad distinction between: Judgements concerning data that are made because alternatives are not feasible; and Judgements about the conduct of a PA that are made because there are no alternative approaches for making the decision. In the case of how judgements are made, the report distinguishes between non-elicited judgements made by individuals, non-elicited judgements made by groups, and elicited judgements made by individuals or groups. These types of judgement can generally be distinguished by the extent of the associated documentation, and hence their traceability. Tools for assessing judgements vary depending on the type of judgements being examined. Key tools are peer review, an appropriate QA regime, documentation, and elicitation. Dialogue with stake holders is also identified as important in establishing whether judgements are justified in the context in which they are used. The PA process comprises a number of stages, from establishing the assessment context, through site selection and repository design, to scenario and model development and parametrisation. The report discusses how judgements are used in each of these stages, and identifies which of the tools and procedures for assessing judgements are most appropriate at each stage. Recommendations for further work include the conduct of a trial expert elicitation to gain experience in the advantages and disadvantages of this technique, the development of guidance for peer

Expert judgement in performance assessment

Energy Technology Data Exchange (ETDEWEB)

Wilmot, R.D.; Galson, D.A. [Galson Sciences Ltd, Oakham (United Kingdom)

2000-01-01

This report is a pilot study that systematically describes the various types of expert judgement that are made throughout the development of a PA, and summarizes existing tools and practices for dealing with expert judgements. The report also includes recommendations for further work in the area of expert judgement. Expert judgements can be classified in a number of ways, including classification according to why the judgements are made and according to how the judgements are made. In terms of why judgements are made, there is a broad distinction between: Judgements concerning data that are made because alternatives are not feasible; and Judgements about the conduct of a PA that are made because there are no alternative approaches for making the decision. In the case of how judgements are made, the report distinguishes between non-elicited judgements made by individuals, non-elicited judgements made by groups, and elicited judgements made by individuals or groups. These types of judgement can generally be distinguished by the extent of the associated documentation, and hence their traceability. Tools for assessing judgements vary depending on the type of judgements being examined. Key tools are peer review, an appropriate QA regime, documentation, and elicitation. Dialogue with stake holders is also identified as important in establishing whether judgements are justified in the context in which they are used. The PA process comprises a number of stages, from establishing the assessment context, through site selection and repository design, to scenario and model development and parametrisation. The report discusses how judgements are used in each of these stages, and identifies which of the tools and procedures for assessing judgements are most appropriate at each stage. Recommendations for further work include the conduct of a trial expert elicitation to gain experience in the advantages and disadvantages of this technique, the development of guidance for peer

Wine Expertise Predicts Taste Phenotype.

Science.gov (United States)

Hayes, John E; Pickering, Gary J

2012-03-01

Taste phenotypes have long been studied in relation to alcohol intake, dependence, and family history, with contradictory findings. However, on balance - with appropriate caveats about populations tested, outcomes measured and psychophysical methods used - an association between variation in taste responsiveness and some alcohol behaviors is supported. Recent work suggests super-tasting (operationalized via propylthiouracil (PROP) bitterness) not only associates with heightened response but also with more acute discrimination between stimuli. Here, we explore relationships between food and beverage adventurousness and taste phenotype. A convenience sample of wine drinkers (n=330) were recruited in Ontario and phenotyped for PROP bitterness via filter paper disk. They also filled out a short questionnaire regarding willingness to try new foods, alcoholic beverages and wines as well as level of wine involvement, which was used to classify them as a wine expert (n=110) or wine consumer (n=220). In univariate logisitic models, food adventurousness predicted trying new wines and beverages but not expertise. Likewise, wine expertise predicted willingness to try new wines and beverages but not foods. In separate multivariate logistic models, willingness to try new wines and beverages was predicted by expertise and food adventurousness but not PROP. However, mean PROP bitterness was higher among wine experts than wine consumers, and the conditional distribution functions differed between experts and consumers. In contrast, PROP means and distributions did not differ with food adventurousness. These data suggest individuals may self-select for specific professions based on sensory ability (i.e., an active gene-environment correlation) but phenotype does not explain willingness to try new stimuli.

Liquid low level waste management expert system

International Nuclear Information System (INIS)

Ferrada, J.J.; Abraham, T.J.; Jackson, J.R.

1991-01-01

An expert system has been developed as part of a new initiative for the Oak Ridge National Laboratory (ORNL) systems analysis program. This expert system will aid in prioritizing radioactive waste streams for treatment and disposal by evaluating the severity and treatability of the problem, as well as the final waste form. The objectives of the expert system development included: (1) collecting information on process treatment technologies for liquid low-level waste (LLLW) that can be incorporated in the knowledge base of the expert system, and (2) producing a prototype that suggests processes and disposal technologies for the ORNL LLLW system. 4 refs., 9 figs

40 CFR 194.26 - Expert judgment.

Science.gov (United States)

2010-07-01

... CFR PART 191 DISPOSAL REGULATIONS Compliance Certification and Re-certification General Requirements... experts (by name and employer) involved in any expert judgment elicitation processes used to support the... judgment elicitation processes and the reasoning behind those results. Documentation of interviews used to...

A method for using expert judgement in PSA

International Nuclear Information System (INIS)

Pulkkinen, U.; Holmberg, J.

1997-03-01

The report discusses an expert judgement methodology development for applications at all levels of probabilistic safety assessment (PSA). The main applications are expected to be at PSA-levels 1 and 2. The method consists of several phases, including the selection and training of the experts, elicitation of experts' judgements, probabilistic modeling and combination of experts' judgements and documentation of the judgement process. The expert training and elicitation process is rather similar to that applied in the NUREG-1150 study. The combination of experts judgements is based on a Bayesian framework utilizing hierarchic models. The posterior distributions of the variables under analysis can be interpreted as a Bayesian counterpart of the combined or aggregated (consensus) distributions, and they are determined by applying Markov chain Monte-Carlo methods. The properties of the method are illustrated by some simple examples. The method is tested in a case study belonging to the benchmark exercise on the use of expert judgement in level 2 PSA, organized as a concerted action of European Commission Fourth Framework Programme on Nuclear Fission Safety. (14 refs.)

Expert system characteristics and potential applications in safeguards

International Nuclear Information System (INIS)

Chapman, L.D.

1986-01-01

The general growth of expert, knowledge-based (KB) or rule based systems will significantly increase in the next three to five years. Improvements in computer hardware (speed, reduced size, power) and software (rule based, data based, user interfaces) in recent years are providing the foundations for the growth of expert systems. A byproduct of this growth will undoubtedly be the application of expert systems to various safeguards problems. Characteristics of these expert systems will involve 1) multiple rules governing an outcome, 2) confidence factors on individual variables and rule sets, 3) priority, cost, and risk based rule sets, and 4) the reasoning behind the advice or decision given by the expert system. This paper presents characteristics, structures, and examples of simple rule based systems. Potential application areas for these expert systems may include training, operations, management, designs, evaluations, and specific hardware operation

A Phenomenology of Expert Musicianship

DEFF Research Database (Denmark)

Høffding, Simon

This dissertation develops a phenomenology of expert musicianship through an interdisciplinary approach that integrates qualitative interviews with the Danish String Quartet with philosophical analyses drawing on ideas and theses found in phenomenology, philosophy of mind, cognitive science...... and psychology of music. The dissertation is structured through the asking, analyzing and answering of three primary questions, namely: 1) What is it like to be an expert? 2) What is the general phenomenology of expert musicianship? 3) What happens to the self in deep musical absorption? The first question...... targets a central debate in philosophy and psychology on whether reflection is conducive for, or detrimental to, skillful performance. My analyses show that the concepts assumed in the literature on this question are poorly defined and gloss over more important features of expertise. The second question...

EPRI expert system activities for nuclear utility industry application

International Nuclear Information System (INIS)

Naser, J.A.

1990-01-01

This paper reports on expert systems which have reached a level of maturity where they offer considerable benefits for the nuclear utility industry. The ability of expert systems to enhance expertise makes them an important tool for the nuclear utility industry in the areas of engineering, operations and maintenance. Benefits of expert system applications include comprehensive and consistent reasoning, reduction of time required for activities, retention of human expertise and ability to utilize multiple experts knowledge for an activity. The Electric Power Research Institute (EPRI) has been performing four basic activities to help the nuclear industry take advantage of this expert system technology. The first is the development of expert system building tools which are tailored to nuclear utility industry applications. The second is the development of expert system applications. The third is work in developing a methodology for verification and validation of expert systems. The last is technology transfer activities to help the nuclear utility industry benefit from expert systems. The purpose of this paper is to describe the EPRI activities

Hierarchical Model of Assessing and Selecting Experts

Science.gov (United States)

Chernysheva, T. Y.; Korchuganova, M. A.; Borisov, V. V.; Min'kov, S. L.

2016-04-01

Revealing experts’ competences is a multi-objective issue. Authors of the paper deal with competence assessing methods of experts seen as objects, and criteria of qualities. An analytic hierarchy process of assessing and ranking experts is offered, which is based on paired comparison matrices and scores, quality parameters are taken into account as well. Calculation and assessment of experts is given as an example.

Counseling, Artificial Intelligence, and Expert Systems.

Science.gov (United States)

Illovsky, Michael E.

1994-01-01

Considers the use of artificial intelligence and expert systems in counseling. Limitations are explored; candidates for counseling versus those for expert systems are discussed; programming considerations are reviewed; and techniques for dealing with rational, nonrational, and irrational thoughts and feelings are described. (Contains 46…

Medical Physics expert and competence in radiation protection

International Nuclear Information System (INIS)

Vano, E.; Lamn, I. N.; Guerra, A. del; Van Kleffens, H. J.

2003-01-01

The Council Directive 97/43/EURATOM on health protection of individuals against the dangers of ionizing radiation in relation to medical exposure, defines the Medical Physical Expert as an expert in radiation physics or radiation technology applied to exposure, within the scope of the Directive, whose training and competence to act is recognized by the competent authorities; and who, as appropriate, acts or gives advice on patient dosimetry, on the development and use of complex techniques and equipment, on optimization, on quality assurance, including quality control, and on other matters relating to radiation protection, concerning exposure within the scope of this Directive. As a consequence, it might be implied that his competence in radiation protection should also cover the staff and the public. In fact, the training programmes of medical physics experts include all the aspects concerning these topics. Some confusion could arise in the medical area when the Qualified Expert defined in the Council Directive 96/29/Euratom laying down basic safety standards for the protection of the health of workers and the general public against the dangers arising from ionizing radiation is considered. The Qualified Expert is defined as a person having the knowledge and training needed to carry out physical, technical or radiochemical tests enabling doses to be assessed, and to give advice in order to ensure effective protection of individuals and the correct operation of protective equipment, whose capacity to act a qualified expert is recognized by the competent authorities. A qualified expert may be assigned the technical responsibility for the tasks of radiation protection of workers and members of the public. In Europe, the Qualified Expert is acting at present in the Medical Area in countries where there are not enough Medical Physics Experts or in countries where this role was established before the publication of the Council Directive 97/43/EURATOM. Now, the coherent

Nickel Hydrogen Battery Expert System

Science.gov (United States)

Johnson, Yvette B.; Mccall, Kurt E.

1992-01-01

The Nickel Cadmium Battery Expert System-2, or 'NICBES-2', which was used by the NASA HST six-battery testbed, was subsequently converted into the Nickel Hydrogen Battery Expert System, or 'NICHES'. Accounts are presently given of this conversion process and future uses being contemplated for NICHES. NICHES will calculate orbital summary data at the end of each orbit, and store these files for trend analyses and rules-generation.

Development of an expert system for analysis of Shuttle atmospheric revitalization and pressure control subsystem anomalies

Science.gov (United States)

Lafuse, Sharon A.

1991-01-01

The paper describes the Shuttle Leak Management Expert System (SLMES), a preprototype expert system developed to enable the ECLSS subsystem manager to analyze subsystem anomalies and to formulate flight procedures based on flight data. The SLMES combines the rule-based expert system technology with the traditional FORTRAN-based software into an integrated system. SLMES analyzes the data using rules, and, when it detects a problem that requires simulation, it sets up the input for the FORTRAN-based simulation program ARPCS2AT2, which predicts the cabin total pressure and composition as a function of time. The program simulates the pressure control system, the crew oxygen masks, the airlock repress/depress valves, and the leakage. When the simulation has completed, other SLMES rules are triggered to examine the results of simulation contrary to flight data and to suggest methods for correcting the problem. Results are then presented in form of graphs and tables.

Safety Tips from the Expert Witness.

Science.gov (United States)

Gray, Gary R.

1995-01-01

Many physical educators and coaches use the potential for liability to guide their decisions about conducting activities. By understanding expert witnesses' roles in negligence actions, surer planning, teaching, and coaching are possible. The paper describes issues that expert witnesses examine in negligence actions against physical educators,…

Photon-photon scattering at the high-intensity frontier

Science.gov (United States)

Gies, Holger; Karbstein, Felix; Kohlfürst, Christian; Seegert, Nico

2018-04-01

The tremendous progress in high-intensity laser technology and the establishment of dedicated high-field laboratories in recent years have paved the way towards a first observation of quantum vacuum nonlinearities at the high-intensity frontier. We advocate a particularly prospective scenario, where three synchronized high-intensity laser pulses are brought into collision, giving rise to signal photons, whose frequency and propagation direction differ from the driving laser pulses, thus providing various means to achieve an excellent signal to background separation. Based on the theoretical concept of vacuum emission, we employ an efficient numerical algorithm which allows us to model the collision of focused high-intensity laser pulses in unprecedented detail. We provide accurate predictions for the numbers of signal photons accessible in experiment. Our study is the first to predict the precise angular spread of the signal photons, and paves the way for a first verification of quantum vacuum nonlinearity in a well-controlled laboratory experiment at one of the many high-intensity laser facilities currently coming online.

Experimental reduction in interaction intensity strongly affects biotic selection.

Science.gov (United States)

Sletvold, Nina; Ågren, Jon

2016-11-01

The link between biotic interaction intensity and strength of selection is of fundamental interest for understanding biotically driven diversification and predicting the consequences of environmental change. The strength of selection resulting from biotic interactions is determined by the strength of the interaction and by the covariance between fitness and the trait under selection. When the relationship between trait and absolute fitness is constant, selection strength should be a direct function of mean population interaction intensity. To test this prediction, we excluded pollinators for intervals of different length to induce five levels of pollination intensity within a single plant population. Pollen limitation (PL) increased from 0 to 0.77 across treatments, accompanied by a fivefold increase in the opportunity for selection. Trait-fitness covariance declined with PL for number of flowers, but varied little for other traits. Pollinator-mediated selection on plant height, corolla size, and spur length increased by 91%, 34%, and 330%, respectively, in the most severely pollen-limited treatment compared to open-pollinated plants. The results indicate that realized biotic selection can be predicted from mean population interaction intensity when variation in trait-fitness covariance is limited, and that declines in pollination intensity will strongly increase selection on traits involved in the interaction. © 2016 by the Ecological Society of America.

Accurate Predictions of Mean Geomagnetic Dipole Excursion and Reversal Frequencies, Mean Paleomagnetic Field Intensity, and the Radius of Earth's Core Using McLeod's Rule

Science.gov (United States)

Voorhies, Coerte V.; Conrad, Joy

1996-01-01

The geomagnetic spatial power spectrum R(sub n)(r) is the mean square magnetic induction represented by degree n spherical harmonic coefficients of the internal scalar potential averaged over the geocentric sphere of radius r. McLeod's Rule for the magnetic field generated by Earth's core geodynamo says that the expected core surface power spectrum (R(sub nc)(c)) is inversely proportional to (2n + 1) for 1 less than n less than or equal to N(sub E). McLeod's Rule is verified by locating Earth's core with main field models of Magsat data; the estimated core radius of 3485 kn is close to the seismologic value for c of 3480 km. McLeod's Rule and similar forms are then calibrated with the model values of R(sub n) for 3 less than or = n less than or = 12. Extrapolation to the degree 1 dipole predicts the expectation value of Earth's dipole moment to be about 5.89 x 10(exp 22) Am(exp 2)rms (74.5% of the 1980 value) and the expected geomagnetic intensity to be about 35.6 (mu)T rms at Earth's surface. Archeo- and paleomagnetic field intensity data show these and related predictions to be reasonably accurate. The probability distribution chi(exp 2) with 2n+1 degrees of freedom is assigned to (2n + 1)R(sub nc)/(R(sub nc). Extending this to the dipole implies that an exceptionally weak absolute dipole moment (less than or = 20% of the 1980 value) will exist during 2.5% of geologic time. The mean duration for such major geomagnetic dipole power excursions, one quarter of which feature durable axial dipole reversal, is estimated from the modern dipole power time-scale and the statistical model of excursions. The resulting mean excursion duration of 2767 years forces us to predict an average of 9.04 excursions per million years, 2.26 axial dipole reversals per million years, and a mean reversal duration of 5533 years. Paleomagnetic data show these predictions to be quite accurate. McLeod's Rule led to accurate predictions of Earth's core radius, mean paleomagnetic field

Expert clinical reasoning and pain assessment in mechanically ventilated patients: A descriptive study.

Science.gov (United States)

Gerber, Anne; Thevoz, Anne-Laure; Ramelet, Anne-Sylvie

2015-02-01

Pain assessment in mechanically ventilated patients is challenging, because nurses need to decode pain behaviour, interpret pain scores, and make appropriate decisions. This clinical reasoning process is inherent to advanced nursing practice, but is poorly understood. A better understanding of this process could contribute to improved pain assessment and management. This study aimed to describe the indicators that influence expert nurses' clinical reasoning when assessing pain in critically ill nonverbal patients. This descriptive observational study was conducted in the adult intensive care unit (ICU) of a tertiary referral hospital in Western Switzerland. A purposive sample of expert nurses, caring for nonverbal ventilated patients who received sedation and analgesia, were invited to participate in the study. Data were collected in "real life" using recorded think-aloud combined with direct non-participant observation and brief interviews. Data were analysed using deductive and inductive content analyses using a theoretical framework related to clinical reasoning and pain. Seven expert nurses with an average of 7.85 (±3.1) years of critical care experience participated in the study. The patients had respiratory distress (n=2), cardiac arrest (n=2), sub-arachnoid bleeding (n=1), and multi-trauma (n=2). A total of 1344 quotes in five categories were identified. Patients' physiological stability was the principal indicator for making decision in relation to pain management. Results also showed that it is a permanent challenge for nurses to discriminate situations requiring sedation from situations requiring analgesia. Expert nurses mainly used working knowledge and patterns to anticipate and prevent pain. Patient's clinical condition is important for making decision about pain in critically ill nonverbal patients. The concept of pain cannot be assessed in isolation and its assessment should take the patient's clinical stability and sedation into account. Further

Influence of Professional Affiliation on Expert's View on Welfare Measures

DEFF Research Database (Denmark)

Dam Otten, Nina; Rousing, Tine; Forkman, Björn

2017-01-01

are not balanced in numbers of experts. At two time points (2012 and 2016), dairy cattle and swine experts from four different stakeholder groups, namely researchers (RES), production advisors (CONS), practicing veterinarians (VET) and animal welfare control officers (AWC) were asked to weigh eight different...... between expert groups among swine experts. Inter-expert differences were more pronounced for both species. The results highlight the challenges of using expert weightings in aggregated welfare assessment models, as the choice of expert affiliation may play a confounding role in the final aggregation due...

A Quality Function Deployment-Based Expert System for Cotton Fibre Selection

Science.gov (United States)

Chakraborty, Shankar; Prasad, Kanika

2018-06-01

The textile industries have seen resurgence in customers' demand for quality products during the preceding few years. This product range is extremely varied, with hand-spun and hand-woven products at one end of the spectrum, while products manufactured from the capital intensive sophisticated machineries at the other end. Since, cotton fibres are predominantly employed as the raw material for manufacturing these products, their proper selection is crucial for sustainable development of the textile/spinning industries. However, availability of numerous cotton fibre alternatives with various physical properties makes this selection process unwieldy and time consuming. Thus, there is need for a structured approach that can incorporate customers' demand into the selection process. This paper demonstrates the application of a structured and logical procedure of selecting the best cotton fibre type to fulfill a set of specified end product requirements through design and development of a quality function deployment (QFD)-based expert system. The QFD technique is employed here to provide due importance to the customers' spoken and unspoken needs, and subsequently calculate the priority weights of the considered cotton fibre properties. Two real time illustrative examples are presented to explicate the applicability and potentiality of the developed expert system to resolve cotton fibre selection problems.

A Quality Function Deployment-Based Expert System for Cotton Fibre Selection

Science.gov (United States)

Chakraborty, Shankar; Prasad, Kanika

2018-01-01

The textile industries have seen resurgence in customers' demand for quality products during the preceding few years. This product range is extremely varied, with hand-spun and hand-woven products at one end of the spectrum, while products manufactured from the capital intensive sophisticated machineries at the other end. Since, cotton fibres are predominantly employed as the raw material for manufacturing these products, their proper selection is crucial for sustainable development of the textile/spinning industries. However, availability of numerous cotton fibre alternatives with various physical properties makes this selection process unwieldy and time consuming. Thus, there is need for a structured approach that can incorporate customers' demand into the selection process. This paper demonstrates the application of a structured and logical procedure of selecting the best cotton fibre type to fulfill a set of specified end product requirements through design and development of a quality function deployment (QFD)-based expert system. The QFD technique is employed here to provide due importance to the customers' spoken and unspoken needs, and subsequently calculate the priority weights of the considered cotton fibre properties. Two real time illustrative examples are presented to explicate the applicability and potentiality of the developed expert system to resolve cotton fibre selection problems.

Expert tool use

DEFF Research Database (Denmark)

Thorndahl, Kathrine Liedtke; Ravn, Susanne

2017-01-01

on a case study of elite rope skipping, we argue that the phenomenological concept of incorporation does not suffice to adequately describe how expert tool users feel when interacting with their tools. By analyzing a combination of insights gained from participant observation of 11 elite rope skippers......According to some phenomenologists, a tool can be experienced as incorporated when, as a result of habitual use or deliberate practice, someone is able to manipulate it without conscious effort. In this article, we specifically focus on the experience of expertise tool use in elite sport. Based...... and autoethnographic material from one former elite skipper, we take some initial steps toward the development of a more nuanced understanding of the concept of incorporation; one that is able to accommodate the experiences of expert tool users. In sum, our analyses indicate that the possibility for experiencing...

Using the Delphi expert consensus method in mental health research.

Science.gov (United States)

Jorm, Anthony F

2015-10-01

The article gives an introductory overview of the use of the Delphi expert consensus method in mental health research. It explains the rationale for using the method, examines the range of uses to which it has been put in mental health research, and describes the stages of carrying out a Delphi study using examples from the literature. To ascertain the range of uses, a systematic search was carried out in PubMed. The article also examines the implications of 'wisdom of crowds' research for how to conduct Delphi studies. The Delphi method is a systematic way of determining expert consensus that is useful for answering questions that are not amenable to experimental and epidemiological methods. The validity of the approach is supported by 'wisdom of crowds' research showing that groups can make good judgements under certain conditions. In mental health research, the Delphi method has been used for making estimations where there is incomplete evidence (e.g. What is the global prevalence of dementia?), making predictions (e.g. What types of interactions with a person who is suicidal will reduce their chance of suicide?), determining collective values (e.g. What areas of research should be given greatest priority?) and defining foundational concepts (e.g. How should we define 'relapse'?). A range of experts have been used in Delphi research, including clinicians, researchers, consumers and caregivers. The Delphi method has a wide range of potential uses in mental health research. © The Royal Australian and New Zealand College of Psychiatrists 2015.

Information Retrieval Diary of an Expert Technical Translator.

Science.gov (United States)

Cremmins, Edward T.

1984-01-01

Recommends use of entries from the information retrieval diary of Ted Crump, expert technical translator at the National Institute of Health, in the construction of computer models showing how expert translators solve problems of ambiguity in language. Expert and inexpert translation systems, eponyms, abbreviations, and alphabetic solutions are…

Earlier visual N1 latencies in expert video-game players: a temporal basis of enhanced visuospatial performance?

Science.gov (United States)

Latham, Andrew J; Patston, Lucy L M; Westermann, Christine; Kirk, Ian J; Tippett, Lynette J

2013-01-01

Increasing behavioural evidence suggests that expert video game players (VGPs) show enhanced visual attention and visuospatial abilities, but what underlies these enhancements remains unclear. We administered the Poffenberger paradigm with concurrent electroencephalogram (EEG) recording to assess occipital N1 latencies and interhemispheric transfer time (IHTT) in expert VGPs. Participants comprised 15 right-handed male expert VGPs and 16 non-VGP controls matched for age, handedness, IQ and years of education. Expert VGPs began playing before age 10, had a minimum 8 years experience, and maintained playtime of at least 20 hours per week over the last 6 months. Non-VGPs had little-to-no game play experience (maximum 1.5 years). Participants responded to checkerboard stimuli presented to the left and right visual fields while 128-channel EEG was recorded. Expert VGPs responded significantly more quickly than non-VGPs. Expert VGPs also had significantly earlier occipital N1s in direct visual pathways (the hemisphere contralateral to the visual field in which the stimulus was presented). IHTT was calculated by comparing the latencies of occipital N1 components between hemispheres. No significant between-group differences in electrophysiological estimates of IHTT were found. Shorter N1 latencies may enable expert VGPs to discriminate attended visual stimuli significantly earlier than non-VGPs and contribute to faster responding in visual tasks. As successful video-game play requires precise, time pressured, bimanual motor movements in response to complex visual stimuli, which in this sample began during early childhood, these differences may reflect the experience and training involved during the development of video-game expertise, but training studies are needed to test this prediction.

Earlier visual N1 latencies in expert video-game players: a temporal basis of enhanced visuospatial performance?

Directory of Open Access Journals (Sweden)

Andrew J Latham

Full Text Available Increasing behavioural evidence suggests that expert video game players (VGPs show enhanced visual attention and visuospatial abilities, but what underlies these enhancements remains unclear. We administered the Poffenberger paradigm with concurrent electroencephalogram (EEG recording to assess occipital N1 latencies and interhemispheric transfer time (IHTT in expert VGPs. Participants comprised 15 right-handed male expert VGPs and 16 non-VGP controls matched for age, handedness, IQ and years of education. Expert VGPs began playing before age 10, had a minimum 8 years experience, and maintained playtime of at least 20 hours per week over the last 6 months. Non-VGPs had little-to-no game play experience (maximum 1.5 years. Participants responded to checkerboard stimuli presented to the left and right visual fields while 128-channel EEG was recorded. Expert VGPs responded significantly more quickly than non-VGPs. Expert VGPs also had significantly earlier occipital N1s in direct visual pathways (the hemisphere contralateral to the visual field in which the stimulus was presented. IHTT was calculated by comparing the latencies of occipital N1 components between hemispheres. No significant between-group differences in electrophysiological estimates of IHTT were found. Shorter N1 latencies may enable expert VGPs to discriminate attended visual stimuli significantly earlier than non-VGPs and contribute to faster responding in visual tasks. As successful video-game play requires precise, time pressured, bimanual motor movements in response to complex visual stimuli, which in this sample began during early childhood, these differences may reflect the experience and training involved during the development of video-game expertise, but training studies are needed to test this prediction.

A demonstration of expert systems applications in transportation engineering : volume III, evaluation of the prototype expert system TRANZ.

Science.gov (United States)

1990-01-01

The validation and evaluation of an expert system for traffic control in highway work zones (TRANZ) is described. The stages in the evaluation process consisted of the following: revisit the experts, selectively distribute copies of TRANZ with docume...

The 2014 updated version of the Confusion Assessment Method for the Intensive Care Unit compared to the 5th version of the Diagnostic and Statistical Manual of Mental Disorders and other current methods used by intensivists.

Science.gov (United States)

Chanques, Gérald; Ely, E Wesley; Garnier, Océane; Perrigault, Fanny; Eloi, Anaïs; Carr, Julie; Rowan, Christine M; Prades, Albert; de Jong, Audrey; Moritz-Gasser, Sylvie; Molinari, Nicolas; Jaber, Samir

2018-03-01

One third of patients admitted to an intensive care unit (ICU) will develop delirium. However, delirium is under-recognized by bedside clinicians without the use of delirium screening tools, such as the Intensive Care Delirium Screening Checklist (ICDSC) or the Confusion Assessment Method for the ICU (CAM-ICU). The CAM-ICU was updated in 2014 to improve its use by clinicians throughout the world. It has never been validated compared to the new reference standard, the Diagnostic and Statistical Manual of Mental Disorders 5th version (DSM-5). We made a prospective psychometric study in a 16-bed medical-surgical ICU of a French academic hospital, to measure the diagnostic performance of the 2014 updated CAM-ICU compared to the DSM-5 as the reference standard. We included consecutive adult patients with a Richmond Agitation Sedation Scale (RASS) ≥ -3, without preexisting cognitive disorders, psychosis or cerebral injury. Delirium was independently assessed by neuropsychological experts using an operationalized approach to DSM-5, by investigators using the CAM-ICU and the ICDSC, by bedside clinicians and by ICU patients. The sensitivity, specificity, positive and negative predictive values were calculated considering neuropsychologist DSM-5 assessments as the reference standard (primary endpoint). CAM-ICU inter-observer agreement, as well as that between delirium diagnosis methods and the reference standard, was summarized using κ coefficients, which were subsequently compared using the Z-test. Delirium was diagnosed by experts in 38% of the 108 patients included for analysis. The CAM-ICU had a sensitivity of 83%, a specificity of 100%, a positive predictive value of 100% and a negative predictive value of 91%. Compared to the reference standard, the CAM-ICU had a significantly (p DSM-5 criteria and reliable regarding inter-observer agreement in a research setting. Delirium remains under-recognized by bedside clinicians.

A brief history and technical review of the expert system research

Science.gov (United States)

Tan, Haocheng

2017-09-01

The expert system is a computer system that emulates the decision-making ability of a human expert, which aims to solve complex problems by reasoning knowledge. It is an important branch of artificial intelligence. In this paper, firstly, we briefly introduce the development and basic structure of the expert system. Then, from the perspective of the enabling technology, we classify the current expert systems and elaborate four expert systems: The Rule-Based Expert System, the Framework-Based Expert System, the Fuzzy Logic-Based Expert System and the Expert System Based on Neural Network.

Expert opinion vs. empirical evidence

OpenAIRE

Herman, Rod A; Raybould, Alan

2014-01-01

Expert opinion is often sought by government regulatory agencies when there is insufficient empirical evidence to judge the safety implications of a course of action. However, it can be reckless to continue following expert opinion when a preponderance of evidence is amassed that conflicts with this opinion. Factual evidence should always trump opinion in prioritizing the information that is used to guide regulatory policy. Evidence-based medicine has seen a dramatic upturn in recent years sp...

[Interest of psychiatric guidelines in managing agitation in intensive care].

Science.gov (United States)

Lazignac, Coralie; Ricou, Bara; Dan, Liviu; Virgillito, Salvatore; Adam, Eric; Seyedi, Majid; Cicotti, Andrei; Azi, Amine; Damsa, Cristian

2007-02-14

This paper discusses the importance of psychiatric guidelines and the position of the psychiatrist in the management of agitation in the intensive care unit. The use of psychiatric validated scales to assess agitation seems to ameliorate the quality of care in psychiatry, but also in intensive care. Psychiatric experts' recommendations for managing agitation are given, which is useful to create an open discussion with the intensivists. The use of sedative medication to protect the patient, staff and to prevent an escalation of violence remains a personal choice for each practitioner, depending on individual patient needs and context. In the treatment of agitated patients, an equilibrium needs to be found between the subjective dimension and the available data from evidence based medicine.

System and method for creating expert systems

Science.gov (United States)

Hughes, Peter M. (Inventor); Luczak, Edward C. (Inventor)

1998-01-01

A system and method provides for the creation of a highly graphical expert system without the need for programming in code. An expert system is created by initially building a data interface, defining appropriate Mission, User-Defined, Inferred, and externally-generated GenSAA (EGG) data variables whose data values will be updated and input into the expert system. Next, rules of the expert system are created by building appropriate conditions of the rules which must be satisfied and then by building appropriate actions of rules which are to be executed upon corresponding conditions being satisfied. Finally, an appropriate user interface is built which can be highly graphical in nature and which can include appropriate message display and/or modification of display characteristics of a graphical display object, to visually alert a user of the expert system of varying data values, upon conditions of a created rule being satisfied. The data interface building, rule building, and user interface building are done in an efficient manner and can be created without the need for programming in code.

Expert systems for plant operations training and assistance

International Nuclear Information System (INIS)

Pack, R.W.; Lazar, P.M.; Schmidt, R.V.; Gaddy, C.D.

1988-01-01

The project described in this paper explored the use of expert systems for plant operations training and assistance. Three computer technologies were reviewed: computer-aided instruction, expert systems, and expert training systems (ETS). The technology of CAI has been developed since the early 1960s, and a wide range of applications are available commercially today. Expert systems have been developed primarily as job performance aids, and the number of commercial applications is increasing. A fully developed ETS has models of the trainer and trainee, in addition to a knowledge base

Handbook of VLSI chip design and expert systems

CERN Document Server

Schwarz, A F

1993-01-01

Handbook of VLSI Chip Design and Expert Systems provides information pertinent to the fundamental aspects of expert systems, which provides a knowledge-based approach to problem solving. This book discusses the use of expert systems in every possible subtask of VLSI chip design as well as in the interrelations between the subtasks.Organized into nine chapters, this book begins with an overview of design automation, which can be identified as Computer-Aided Design of Circuits and Systems (CADCAS). This text then presents the progress in artificial intelligence, with emphasis on expert systems.

Use of expert systems in nuclear safety

International Nuclear Information System (INIS)

1990-02-01

One dominant aspect of improvement in safe nuclear power plant operation is the very high speed in the development and introduction of computer technologies. This development commenced recently when advanced control technology was incorporated into the nuclear industry. This led to an increasing implementation of information displays, annunciator windows and other devices inside the control room, eventually overburdening the control room operator with detailed information. Expert systems are a further step in this direction being designed to apply large knowledge bases to solve practical problems. These ''intelligent'' systems have to incorporate enough knowledge to reach expert levels of importance and represent a very advanced man-machine interface. The aims of the Technical Committee were addressed by the three Working Groups and summarized in Sections 2, 3 and 4 of this report. Section 2 summarizes the results and discussions on the current capabilities of expert systems and identifies features for the future development and use of Expert Systems in Nuclear Power Plants. Section 3 provides an overview of the discussions and investigations into the current status of Expert Systems in NPPs. This section develops a method for assessing the overall benefit of different applications and recommends a broad strategy for priority developments of Expert Systems in NPPs. Section 4 assesses the overall use of PSA type studies in Expert Systems in NPPs and identifies specific features to be adopted in the design of these systems in future applications. The conclusions of the three Working Groups are presented in Section 5. The 15 papers presented at the meeting formed the Annex of this document. A separate abstract was prepared for each of these papers. Refs, figs, tabs and pictures

WINE ADVISOR EXPERT SYSTEM USING DECISION RULES

Directory of Open Access Journals (Sweden)

Dinuca Elena Claudia

2013-07-01

Full Text Available In this article I focus on developing an expert system for advising the choice of wine that best matches a specific occasion. An expert system is a computer application that performs a task that would be performed by a human expert. The implementation is done using Delphi programming language. I used to represent the knowledge bases a set of rules. The rules are of type IF THEN ELSE rules, decision rules based on different important wine features.

Industrial disasters - the expert systems solution

International Nuclear Information System (INIS)

Sachs, P.

1986-01-01

Six mistakes by the operators led to the accident at the Cherobyl nuclear reactor. These have been studied. It is suggested that an expert systems approach could prevent similar accidents. The expert system is a new approach to software programming where programs are required to perform intelligent analyses of complex situations. It separates the knowledge of a problem from the procedural code that performs the decision. An expert system will evaluate data and indicate a priority on alarms in real time. Now software systems can detect the cause of a problem in a process plant and present their findings to the operators in the control room. This should enable operators to make the correct decisions as they will know which underlying process faults are causing the alarms to operate. The Chernobyl post-mortem meeting made 13 proposals for improving safety. Two in particular are noted as relevant to expert advice systems; international collaboration on man-reactor relationships and a conference to explore the balance of automation and human action to minimise operating errors. (U.K.)

Expert Systems: A Challenge for the Reading Profession.

Science.gov (United States)

Balajthy, Ernest

The expert systems are designed to imitate the reasoning of a human expert in a content area field. Designed to be advisors, these software systems combine the content area knowledge and decision-making ability of an expert with the user's understanding and knowledge of particular circumstances. The reading diagnosis system, the RD2P System…

New horizons in predictive toxicology: current status and application

National Research Council Canada - National Science Library

Wilson, A. G. E

2012-01-01

"In this comprehensive discussion of predictive toxicology and its applications, leading experts express their views on the technologies currently available and the potential for future developments...

Innovation on Energy Power Technology (22)Challenge to Development of Expert System stored Knowledge of Expert Power Network Operators

Science.gov (United States)

Sakaguchi, Hideharu

Do you remember an expert system? I think there are various impressions about the system. For example, some might say “It reminds me of old days”. On the other hand, some might say “It was really troublesome”. About 25 years ago, from late 1980s to the middle of 1990s, when the Showa era was about to change into the Heisei Era, artificial intelligence boomed. Research and development for an expert system which was equipped with expertise and worked as smart as expert, was advanced in various fields. Our company also picked up the system as the new system which covered weak point of conventional computer technology. We started research and development in 1984, and installed an expert system in a SCADA system, which started operating in March 1990 in the Fukuoka Integrated Control Center. In this essay, as an electric power engineer who involved in development at that time, I introduce the situation and travail story about developing an expert system which support restorative actions from the outage and overload condition of power networks.

Expert Systems Research.

Science.gov (United States)

Duda, Richard O.; Shortliffe, Edward H.

1983-01-01

Discusses a class of artificial intelligence computer programs (often called "expert systems" because they address problems normally thought to require human specialists for their solution) intended to serve as consultants for decision making. Also discusses accomplishments (including information systematization in medical diagnosis and…

A fuzzy expert system based on relations

International Nuclear Information System (INIS)

Hall, L.O.; Kandel, A.

1986-01-01

The Fuzzy Expert System (FESS) is an expert system which makes use of the theory of fuzzy relations to perform inference. Relations are very general and can be used for any application, which only requires different types of relations be implemented and used. The incorporation of fuzzy reasoning techniques enables the expert system to deal with imprecision in a well-founded manner. The knowledge is represented in relational frames. FESS may operate in either a forward chaining or backward chaining manner. It uses primarily implication and factual relations. A unique methodology for combination of evidence has been developed. It makes uses of a blackboard for communication between the various knowledge sources which may operate in parallel. The expert system has been designed in such a manner that it may be used for diverse applications

Development and validation of a multivariate prediction model for patients with acute pancreatitis in Intensive Care Medicine.

Science.gov (United States)

Zubia-Olaskoaga, Felix; Maraví-Poma, Enrique; Urreta-Barallobre, Iratxe; Ramírez-Puerta, María-Rosario; Mourelo-Fariña, Mónica; Marcos-Neira, María-Pilar; García-García, Miguel Ángel

2018-03-01

Development and validation of a multivariate prediction model for patients with acute pancreatitis (AP) admitted in Intensive Care Units (ICU). A prospective multicenter observational study, in 1 year period, in 46 international ICUs (EPAMI study). adults admitted to an ICU with AP and at least one organ failure. Development of a multivariate prediction model, using the worst data of the stay in ICU, based in multivariate analysis, simple imputation in a development cohort. The model was validated in another cohort. 374 patients were included (mortality of 28.9%). Variables with statistical significance in multivariate analysis were age, no alcoholic and no biliary etiology, development of shock, development of respiratory failure, need of continuous renal replacement therapy, and intra-abdominal pressure. The model created with these variables presented an AUC of ROC curve of 0.90 (CI 95% 0.81-0.94) in the validation cohort. We developed a multivariable prediction model, and AP cases could be classified as low mortality risk (between 2 and 9.5 points, mortality of 1.35%), moderate mortality risk (between 10 and 12.5 points, 28.92% of mortality), and high mortality risk (13 points of more, mortality of 88.37%). Our model presented better AUC of ROC curve than APACHE II (0.91 vs 0.80) and SOFA in the first 24 h (0.91 vs 0.79). We developed and validated a multivariate prediction model, which can be applied in any moment of the stay in ICU, with better discriminatory power than APACHE II and SOFA in the first 24 h. Copyright © 2018 IAP and EPC. Published by Elsevier B.V. All rights reserved.

Predicting outcome of rethoracotomy for suspected pericardial tamponade following cardio-thoracic surgery in the intensive care unit

Directory of Open Access Journals (Sweden)

Beishuizen Albertus

2011-05-01

Full Text Available Abstract Objectives Pericardial tamponade after cardiac surgery is difficult to diagnose, thereby rendering timing of rethoracotomy hard. We aimed at identifying factors predicting the outcome of surgery for suspected tamponade after cardio-thoracic surgery, in the intensive care unit (ICU. Methods Twenty-one consecutive patients undergoing rethoracotomy for suspected pericardial tamponade in the ICU, admitted after primary cardio-thoracic surgery, were identified for this retrospective study. We compared patients with or without a decrease in severe haemodynamic compromise after rethoracotomy, according to the cardiovascular component of the sequential organ failure assessment (SOFA score. Results A favourable haemodynamic response to rethoracotomy was observed in 11 (52% of patients and characterized by an increase in cardiac output, and less fluid and norepinephrine requirements. Prior to surgery, the absence of treatment by heparin, a minimum cardiac index 2 and a positive fluid balance (> 4,683 mL were predictive of a beneficial haemodynamic response. During surgery, the evacuation of clots and > 500 mL of pericardial fluid was associated with a beneficial haemodynamic response. Echocardiographic parameters were of limited help in predicting the postoperative course, even though 9 of 13 pericardial clots found at surgery were detected preoperatively. Conclusion Clots and fluids in the pericardial space causing regional tamponade and responding to surgical evacuation after primary cardio-thoracic surgery, are difficult to diagnose preoperatively, by clinical, haemodynamic and even echocardiographic evaluation in the ICU. Only absence of heparin treatment, a large positive fluid balance and low cardiac index predicted a favourable haemodynamic response to rethoracotomy. These data might help in deciding and timing of reinterventions after primary cardio-thoracic surgery.

The effect of fidelity: how expert behavior changes in a virtual reality environment.

Science.gov (United States)

Ioannou, Ioanna; Avery, Alex; Zhou, Yun; Szudek, Jacek; Kennedy, Gregor; O'Leary, Stephen

2014-09-01

We compare the behavior of expert surgeons operating on the "gold standard" of simulation-the cadaveric temporal bone-against a high-fidelity virtual reality (VR) simulation. We aim to determine whether expert behavior changes within the virtual environment and to understand how the fidelity of simulation affects users' behavior. Five expert otologists performed cortical mastoidectomy and cochleostomy on a human cadaveric temporal bone and a VR temporal bone simulator. Hand movement and video recordings were used to derive a range of measures, to facilitate an analysis of surgical technique, and to compare expert behavior between the cadaveric and simulator environments. Drilling time was similar across the two environments. Some measures such as total time and burr change count differed predictably due to the ease of switching burrs within the simulator. Surgical strokes were generally longer in distance and duration in VR, but these measures changed proportionally to cadaveric measures across the stages of the procedure. Stroke shape metrics differed, which was attributed to the modeling of burr behavior within the simulator. This will be corrected in future versions. Slight differences in drill interaction between a virtual environment and the real world can have measurable effects on surgical technique, particularly in terms of stroke length, duration, and curvature. It is important to understand these effects when designing and implementing surgical training programs based on VR simulation--and when improving the fidelity of VR simulators to facilitate use of a similar technique in both real and simulated situations. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

Predictive factors of local-regional recurrences following parotid sparing intensity modulated or 3D conformal radiotherapy for head and neck cancer

International Nuclear Information System (INIS)

Feng, Mary; Jabbari, Siavash; Lin, Alexander; Bradford, Carol R.; Chepeha, Douglas B.; Teknos, Theodoros N.; Worden, Francis P.; Tsien, Christina; Schipper, Matthew J.; Wolf, Gregory T.; Dawson, Laura A.; Eisbruch, Avraham

2005-01-01

Background and purpose: Predictive factors for local-regional (LR) failures after parotid-sparing, Intensity modulated (IMRT) or 3D conformal radiotherapy for head and neck (HN) cancers were assessed. Patients and methods: One hundred and fifty-eight patients with mostly stages III-IV HN squamous cell carcinoma underwent curative bilateral neck irradiation aimed at sparing the parotid glands. Patient, tumor, and treatment factors were analyzed as predictive factors for LR failure. Results: Twenty-three patients had LR recurrence (19 in-field and four marginal). No differences were found in the doses delivered to the PTVs of patients with or without in-field recurrences. In univariate analysis, tumor site was highly predictive for LR failure in both postoperative and definitive RT patients. In postoperative RT patients, pathologic tumor size, margin status, extracapsular extension (ECE) and number of lymph node metastases, were also significantly predictive. Multivariate analysis showed tumor site (oropharynx vs. other sites) to be a significant predictor in all patients, and involved margins and number of involved lymph nodes in postoperative patients. Conclusions: Clinical rather than dosimetric factors predicted for LR failures in this series, and were similar to those reported following standard RT. These factors may aid in the selection of patients for studies of treatment intensification using IMRT

Cataloging Expert Systems: Optimism and Frustrated Reality.

Science.gov (United States)

Olmstadt, William J.

2000-01-01

Discusses artificial intelligence and attempts to catalog expert systems. Topics include the nature of expertise; examples of cataloging expert systems; barriers to implementation; and problems, including total automation, cataloging expertise, priorities, and system design. (LRW)

Accuracy and artifact: reexamining the intensity bias in affective forecasting.

Science.gov (United States)

Levine, Linda J; Lench, Heather C; Kaplan, Robin L; Safer, Martin A

2012-10-01

Research on affective forecasting shows that people have a robust tendency to overestimate the intensity of future emotion. We hypothesized that (a) people can accurately predict the intensity of their feelings about events and (b) a procedural artifact contributes to people's tendency to overestimate the intensity of their feelings in general. People may misinterpret the forecasting question as asking how they will feel about a focal event, but they are later asked to report their feelings in general without reference to that event. In the current investigation, participants predicted and reported both their feelings in general and their feelings about an election outcome (Study 1) and an exam grade (Study 3). We also assessed how participants interpreted forecasting questions (Studies 2 and 4) and conducted a meta-analysis of affective forecasting research (Study 5). The results showed that participants accurately predicted the intensity of their feelings about events. They overestimated only when asked to predict how they would feel in general and later report their feelings without reference to the focal event. Most participants, however, misinterpreted requests to predict their feelings in general as asking how they would feel when they were thinking about the focal event. Clarifying the meaning of the forecasting question significantly reduced overestimation. These findings reveal that people have more sophisticated self-knowledge than is commonly portrayed in the affective forecasting literature. Overestimation of future emotion is partly due to a procedure in which people predict one thing but are later asked to report another.

Expert witness and Jungian archetypes.

Science.gov (United States)

Lallave, Juan Antonio; Gutheil, Thomas Gordon

2012-01-01

Jung's theories of archetype, shadow, and the personal and collective unconscious provide a postmodern framework in which to consider the role of the expert witness in judicial proceedings. Archetypal themes, motifs, and influences help to illuminate the shadow of the judicial system and projections and behaviors among the cast of the court in pursuing justice. This article speaks to archetypal influences and dialectical tensions encountered by the expert witness in this judicial drama. The archetype of Justice is born from the human need for order and relational fairness in a world of chaos. The persona of justice is the promise of truth in the drama. The shadow of justice is untruth, the need to win by any means. The dynamics of the trickster archetype serve and promote injustice. These influences are examined by means of a case example. This approach will deepen understanding of court proceedings and the role of the expert witness in the heroic quest for justice. Copyright © 2012 Elsevier Ltd. All rights reserved.

Hazard perception, risk perception, and the need for decontamination by residents exposed to soil pollution: the role of sustainability and the limits of expert knowledge.

Science.gov (United States)

Vandermoere, Frédéric

2008-04-01

This case study examines the hazard and risk perception and the need for decontamination according to people exposed to soil pollution. Using an ecological-symbolic approach (ESA), a multidisciplinary model is developed that draws upon psychological and sociological perspectives on risk perception and includes ecological variables by using data from experts' risk assessments. The results show that hazard perception is best predicted by objective knowledge, subjective knowledge, estimated knowledge of experts, and the assessed risks. However, experts' risk assessments induce an increase in hazard perception only when residents know the urgency of decontamination. Risk perception is best predicted by trust in the risk management. Additionally, need for decontamination relates to hazard perception, risk perception, estimated knowledge of experts, and thoughts about sustainability. In contrast to the knowledge deficit model, objective and subjective knowledge did not significantly relate to risk perception and need for decontamination. The results suggest that residents can make a distinction between hazards in terms of the seriousness of contamination on the one hand, and human health risks on the other hand. Moreover, next to the importance of social determinants of environmental risk perception, this study shows that the output of experts' risk assessments-or the objective risks-can create a hazard awareness rather than an alarming risk consciousness, despite residents' distrust of scientific knowledge.

Hurricane feedback research may improve intensity forecasts

Science.gov (United States)

Schultz, Colin

2012-06-01

Forecasts of a hurricane's intensity are generally much less accurate than forecasts of its most likely path. Large-scale atmospheric patterns dictate where a hurricane will go and how quickly it will get there. The storm's intensity, however, depends on small-scale shifts in atmospheric stratification, upwelling rates, and other transient dynamics that are difficult to predict. Properly understanding the risk posed by an impending storm depends on having a firm grasp of all three properties: translational speed, intensity, and path. Drawing on 40 years of hurricane records representing 3090 different storms, Mei et al. propose that a hurricane's translational speed and intensity may be closely linked.

The Role of Parental Perceptions of Tic Frequency and Intensity in Predicting Tic-Related Functional Impairment in Youth with Chronic Tic Disorders

OpenAIRE

Espil, Flint M.; Capriotti, Matthew R.; Conelea, Christine A.; Woods, Douglas W.

2014-01-01

Tic severity is composed of several dimensions. Tic frequency and intensity are two such dimensions, but little empirical data exist regarding their relative contributions to functional impairment in those with Chronic Tic Disorders (CTD). The present study examined the relative contributions of these dimensions in predicting tic-related impairment across several psychosocial domains. Using data collected from parents of youth with CTD, multivariate regression analyses revealed that both tic ...

Expert music performance: cognitive, neural, and developmental bases.

Science.gov (United States)

Brown, Rachel M; Zatorre, Robert J; Penhune, Virginia B

2015-01-01

In this chapter, we explore what happens in the brain of an expert musician during performance. Understanding expert music performance is interesting to cognitive neuroscientists not only because it tests the limits of human memory and movement, but also because studying expert musicianship can help us understand skilled human behavior in general. In this chapter, we outline important facets of our current understanding of the cognitive and neural basis for music performance, and developmental factors that may underlie musical ability. We address three main questions. (1) What is expert performance? (2) How do musicians achieve expert-level performance? (3) How does expert performance come about? We address the first question by describing musicians' ability to remember, plan, execute, and monitor their performances in order to perform music accurately and expressively. We address the second question by reviewing evidence for possible cognitive and neural mechanisms that may underlie or contribute to expert music performance, including the integration of sound and movement, feedforward and feedback motor control processes, expectancy, and imagery. We further discuss how neural circuits in auditory, motor, parietal, subcortical, and frontal cortex all contribute to different facets of musical expertise. Finally, we address the third question by reviewing evidence for the heritability of musical expertise and for how expertise develops through training and practice. We end by discussing outlooks for future work. © 2015 Elsevier B.V. All rights reserved.

Sugeno-Fuzzy Expert System Modeling for Quality Prediction of Non-Contact Machining Process

Science.gov (United States)

Sivaraos; Khalim, A. Z.; Salleh, M. S.; Sivakumar, D.; Kadirgama, K.

2018-03-01

Modeling can be categorised into four main domains: prediction, optimisation, estimation and calibration. In this paper, the Takagi-Sugeno-Kang (TSK) fuzzy logic method is examined as a prediction modelling method to investigate the taper quality of laser lathing, which seeks to replace traditional lathe machines with 3D laser lathing in order to achieve the desired cylindrical shape of stock materials. Three design parameters were selected: feed rate, cutting speed and depth of cut. A total of twenty-four experiments were conducted with eight sequential runs and replicated three times. The results were found to be 99% of accuracy rate of the TSK fuzzy predictive model, which suggests that the model is a suitable and practical method for non-linear laser lathing process.

Expert system for accelerator single-freedom nonlinear components

International Nuclear Information System (INIS)

Wang Sheng; Xie Xi; Liu Chunliang

1995-01-01

An expert system by Arity Prolog is developed for accelerator single-freedom nonlinear components. It automatically yields any order approximate analytical solutions for various accelerator single-freedom nonlinear components. As an example, the eighth order approximate analytical solution is derived by this expert system for a general accelerator single-freedom nonlinear component, showing that the design of the expert system is successful

[Intensive care medicine-survival and prospect of life].

Science.gov (United States)

Valentin, A

2017-10-01

Intensive care medicine has achieved a significant increase in survival rates from critical illness. In addition to short-term outcomes like intensive care unit or hospital mortality, long-term prognosis and prospect of life of intensive care patients have recently become increasingly important. Pure survival is no longer a sole goal of intensive care medicine. The prediction of an intensive care patient's individual course should include the period after intensive care. A relevant proportion of all intensive care patients is affected by physical, psychological, cognitive, and social limitations after discharge from the intensive care unit. The prognosis of the status of the patient after discharge from the intensive care unit is an important part of the decision-making process with respect to the implementation or discontinuation of intensive care measures. The heavy burden of intensive care treatment should not solely be argued by pure survival but an anticipated sound prospect of life.

Fear of food prospectively predicts drive for thinness in an eating disorder sample recently discharged from intensive treatment.

Science.gov (United States)

Levinson, Cheri A; Brosof, Leigh C; Ma, Jackie; Fewell, Laura; Lenze, Eric J

2017-12-01

Fears of food are common in individuals with eating disorders and contribute to the high relapse rates. However, it is unknown how fears of food contribute to eating disorder symptoms across time, potentially contributing to an increased likelihood of relapse. Participants diagnosed with an eating disorder (N=168) who had recently completed intensive treatment were assessed after discharge and one month later regarding fear of food, eating disorder symptoms, anxiety sensitivity, and negative affect. Cross lagged path analysis was utilized to determine if fear of food predicted subsequent eating disorder symptoms one month later. Fear of food-specifically, anxiety about eating and feared concerns about eating-predicted drive for thinness, a core symptom domain of eating disorders. These relationships held while accounting for anxiety sensitivity and negative affect. There is a specific, direct relationship between anxiety about eating and feared concerns about eating and drive for thinness. Future research should test if interventions designed to target fear of food can decrease drive for thinness and thereby prevent relapse. Copyright © 2017 Elsevier Ltd. All rights reserved.

Expert systems for assisting in design reviews

International Nuclear Information System (INIS)

Brtis, J.S.; Johnson, W.J.; Weber, N.; Naser, J.

1990-01-01

This paper discusses Sargent and Lundy's (S and L's) use of expert system technologies to computerize the procedures used for engineering design reviews. This paper discusses expert systems and the advantages that result from using them to computerize the decision-making process. This paper also discusses the design review expert systems that S and L has developed to perform fire protection and ALARA (as low as reasonably achievable) design reviews, and is currently developing for the Electric Power Research Institute (EPRI) to perform 10 CFR 50.59 safety reviews

Expert systems and computer based industrial systems

International Nuclear Information System (INIS)

Dunand, R.

1989-01-01

Framentec is the artificial intelligence subsidiary of FRAMATOME. It is involved in expert-system activities of Shells, developments, methodology and software for maintenance (Maintex) and consulting and methodology. Specific applications in the nuclear field are presented. The first is an expert system to assist in the piping support design prototype, the second is an expert system that assists an ultrasonic testing operator in determining the nature of a welding defect and the third is a welding machine diagnosis advisor. Maintex is a software tool to provide assistance in the repair of complex industrial equipment. (author)

An expert system for dispersion model interpretation

International Nuclear Information System (INIS)

Skyllingstad, E.D.; Ramsdell, J.V.

1988-10-01

A prototype expert system designed to diagnose dispersion model uncertainty is described in this paper with application to a puff transport model. The system obtains qualitative information from the model user and through an expert-derived knowledge base, performs a rating of the current simulation. These results can then be used in combination with dispersion model output for deciding appropriate evacuation measures. Ultimately, the goal of this work is to develop an expert system that may be operated accurately by an individual uneducated in meteorology or dispersion modeling. 5 refs., 3 figs

MARBLE: A system for executing expert systems in parallel

Science.gov (United States)

Myers, Leonard; Johnson, Coe; Johnson, Dean

1990-01-01

This paper details the MARBLE 2.0 system which provides a parallel environment for cooperating expert systems. The work has been done in conjunction with the development of an intelligent computer-aided design system, ICADS, by the CAD Research Unit of the Design Institute at California Polytechnic State University. MARBLE (Multiple Accessed Rete Blackboard Linked Experts) is a system of C Language Production Systems (CLIPS) expert system tool. A copied blackboard is used for communication between the shells to establish an architecture which supports cooperating expert systems that execute in parallel. The design of MARBLE is simple, but it provides support for a rich variety of configurations, while making it relatively easy to demonstrate the correctness of its parallel execution features. In its most elementary configuration, individual CLIPS expert systems execute on their own processors and communicate with each other through a modified blackboard. Control of the system as a whole, and specifically of writing to the blackboard is provided by one of the CLIPS expert systems, an expert control system.

High-intensity sweetener consumption and gut microbiome content and predicted gene function in a cross-sectional study of adults in the United States.

Science.gov (United States)

Frankenfeld, Cara L; Sikaroodi, Masoumeh; Lamb, Evan; Shoemaker, Sarah; Gillevet, Patrick M

2015-10-01

To evaluate gut microbiome in relation to recent high-intensity sweetener consumption in healthy adults. Thirty-one adults completed a four-day food record and provided a fecal sample on the fifth day. Bacterial community in the samples was analyzed using multitag pyrosequencing. Across consumers and nonconsumers of aspartame and acesulfame-K, bacterial abundance was compared using nonparametric statistics, and bacterial diversity was compared using UniFrac analysis. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) was used to predict mean relative abundance of gene function. There were seven aspartame consumers and seven acesulfame-K consumers. Three individuals overlapped groups, consuming both sweeteners. There were no differences in median bacterial abundance (class or order) across consumers and nonconsumers of either sweetener. Overall bacterial diversity was different across nonconsumers and consumers of aspartame (P Bacterial abundance profiles and predicted gene function were not associated with recent dietary high-intensity sweetener consumption. However, bacterial diversity differed across consumers and nonconsumers. Given the increasing consumption of sweeteners and the role that the microbiome may have in chronic disease outcomes, work in further studies is warranted. Copyright © 2015 Elsevier Inc. All rights reserved.

Impact of intensity and loss assessment following the great Wenchuan Earthquake

Science.gov (United States)

Yuan, Yifan

2008-09-01

The great Wenchuan Earthquake occurred on May 12, 2008 in the Sichuan Province of China, and had a magnitude of 8.0. It is the most serious earthquake disaster in China since the great Tangshan Earthquake ( M s=7.8, July 28, 1976). According to official reports, there were 69,225 deaths, 379,640 injuries and 17,939 missing as of Aug. 11, 2008. The China Earthquake Administration quickly sent hundreds of experts to the field immediately after the event, to investigate the damage and assess the economic losses. This paper emphasizes the impact of seismic intensity and presents a preliminary loss assessment. A brief description of the geological features of the affected region is provided, followed by a summary of the earthquake damage. An isoseismal map is developed that shows that the high intensity region is distributed like a belt around the seimogenic fault, and that the epicentral intensity reached XI (Chinese Intensity Scale, similar to the Modified Mercalli Scale). The direct economic loss resulting from the earthquake is 692 billions RMB (about 100 billions US).

Predictive coding of music--brain responses to rhythmic incongruity.

Science.gov (United States)

Vuust, Peter; Ostergaard, Leif; Pallesen, Karen Johanne; Bailey, Christopher; Roepstorff, Andreas

2009-01-01

During the last decades, models of music processing in the brain have mainly discussed the specificity of brain modules involved in processing different musical components. We argue that predictive coding offers an explanatory framework for functional integration in musical processing. Further, we provide empirical evidence for such a network in the analysis of event-related MEG-components to rhythmic incongruence in the context of strong metric anticipation. This is seen in a mismatch negativity (MMNm) and a subsequent P3am component, which have the properties of an error term and a subsequent evaluation in a predictive coding framework. There were both quantitative and qualitative differences in the evoked responses in expert jazz musicians compared with rhythmically unskilled non-musicians. We propose that these differences trace a functional adaptation and/or a genetic pre-disposition in experts which allows for a more precise rhythmic prediction.

Expert finding by the Dempster‐Shafer theory for evidence combination

NARCIS (Netherlands)

Torkzadeh mahani, N.; Dehghani, M.; Mirian, M.S.; Shakery, A.; Taheri, K.

The expertise of human experts can be formally extracted from their written documents, research projects, and everyday activities. The process whereby experts are recognized according to their activities is called expert finding. In this paper, we propose an approach to identify the experts in a

Intensity ratio to improve black hole assessment in multiple sclerosis.

Science.gov (United States)

Adusumilli, Gautam; Trinkaus, Kathryn; Sun, Peng; Lancia, Samantha; Viox, Jeffrey D; Wen, Jie; Naismith, Robert T; Cross, Anne H

2018-01-01

Improved imaging methods are critical to assess neurodegeneration and remyelination in multiple sclerosis. Chronic hypointensities observed on T1-weighted brain MRI, "persistent black holes," reflect severe focal tissue damage. Present measures consist of determining persistent black holes numbers and volumes, but do not quantitate severity of individual lesions. Develop a method to differentiate black and gray holes and estimate the severity of individual multiple sclerosis lesions using standard magnetic resonance imaging. 38 multiple sclerosis patients contributed images. Intensities of lesions on T1-weighted scans were assessed relative to cerebrospinal fluid intensity using commercial software. Magnetization transfer imaging, diffusion tensor imaging and clinical testing were performed to assess associations with T1w intensity-based measures. Intensity-based assessments of T1w hypointensities were reproducible and achieved > 90% concordance with expert rater determinations of "black" and "gray" holes. Intensity ratio values correlated with magnetization transfer ratios (R = 0.473) and diffusion tensor imaging metrics (R values ranging from 0.283 to -0.531) that have been associated with demyelination and axon loss. Intensity ratio values incorporated into T1w hypointensity volumes correlated with clinical measures of cognition. This method of determining the degree of hypointensity within multiple sclerosis lesions can add information to conventional imaging. Copyright © 2017 Elsevier B.V. All rights reserved.

Expert Systems as a Mindtool To Facilitate Mental Model Learning.

Science.gov (United States)

Mason-Mason, Susan Dale; Tessmer, Martin A.

2000-01-01

This exploratory study investigated whether the process of constructing an expert system model promotes the formation of expert-like mental models. Discusses expert systems as mindtools, expert systems as learning tools, the assessment of mental models, results of pretests and posttests, and future research. (Contains 56 references.) (Author/LRW)

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support.

Science.gov (United States)

Gibert, Karina; García-Alonso, Carlos; Salvador-Carulla, Luis

2010-09-30

Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. This paper presents EbCA and shows the convenience of

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

Directory of Open Access Journals (Sweden)

García-Alonso Carlos

2010-09-01

Full Text Available Abstract Background Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. Method This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA, which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1 Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA, and 2 Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR. In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. Results EbCA is a new methodology composed by 6 steps:. 1 Data collection and data preparation; 2 acquisition of "Prior Expert Knowledge" (PEK and design of the "Prior Knowledge Base" (PKB; 3 PKB-guided analysis; 4 support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited; 5 incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6 post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering, applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. Discussion This

Rainfall intensity effects on crusting and mode of seedling ...

African Journals Online (AJOL)

Predicted changes in rainfall intensity due to climate change are likely to influence key soil health parameters, especially structural attributes and crop growth. Variations in rainfall intensity will impact crop ... and growth in these soils. Keywords: climate change, crusting, mineralogy, penetration resistance, soil organic matter ...

Risks, doubt, scientific and technical expert appraisement

International Nuclear Information System (INIS)

Decrop, G.

1993-01-01

In complex systems which compose modern societies, expert report is going to take an increasing place. In its usual definition, expert is justified by a superior authority, his knowledge comes from experience, he is present as a third party where he has to work. It is often forgotten two other important points, connected with the situation: it is a tangling of technical or natural systems with a social system and above all there is a risk of uncertainty. Then, the job of expert is different from scientific work done in laboratories and different from operational work done by engineers

Computers start to think with expert systems

Energy Technology Data Exchange (ETDEWEB)

1983-03-21

A growing number of professionals-notably in oil and mineral exploration, plasma research, medicine, VLSI circuit design, drug design and robotics-are beginning to use computerised expert systems. A computer program uses knowledge and inference procedures to solve problems which are sufficiently difficult to require significant human expertise for their solution. The facts constitute a body of information that is widely shared, publicly available and generally agreed upon by experts in the field. The heuristics are mostly private, and little discussed, rules of good judgement (rules of plausible reasoning, rules of good guessing, etc.) that characterise expert-level decision making in the field.

Expert System for Diagnostics and Status Monitoring of NPP Water Chemistry Condition

International Nuclear Information System (INIS)

Shvedova, M.N.; Kritski, V.G.; Zakharova, S.V.; Nikolaev, F.V.; Benediktov, V.B.

2002-01-01

range of numerical estimates, which were calculated by the use of expert data, and to make a credible prediction of an existing situation development. The integrated use of analytical methods and artificial intelligence methods is one of the system's advantages. This combination allows the successful implementation of one of the main purposes of the system: the early detection of deviations from specified process conditions and the taking into account of even minor changes in parameters to provide an advanced WCC control and to prevent non-regular situations. (authors)

Prediction and early detection of delirium in the intensive care unit by using heart rate variability and machine learning.

Science.gov (United States)

Oh, Jooyoung; Cho, Dongrae; Park, Jaesub; Na, Se Hee; Kim, Jongin; Heo, Jaeseok; Shin, Cheung Soo; Kim, Jae-Jin; Park, Jin Young; Lee, Boreom

2018-03-27

Delirium is an important syndrome found in patients in the intensive care unit (ICU), however, it is usually under-recognized during treatment. This study was performed to investigate whether delirious patients can be successfully distinguished from non-delirious patients by using heart rate variability (HRV) and machine learning. Electrocardiography data of 140 patients was acquired during daily ICU care, and HRV data were analyzed. Delirium, including its type, severity, and etiologies, was evaluated daily by trained psychiatrists. HRV data and various machine learning algorithms including linear support vector machine (SVM), SVM with radial basis function (RBF) kernels, linear extreme learning machine (ELM), ELM with RBF kernels, linear discriminant analysis, and quadratic discriminant analysis were utilized to distinguish delirium patients from non-delirium patients. HRV data of 4797 ECGs were included, and 39 patients had delirium at least once during their ICU stay. The maximum classification accuracy was acquired using SVM with RBF kernels. Our prediction method based on HRV with machine learning was comparable to previous delirium prediction models using massive amounts of clinical information. Our results show that autonomic alterations could be a significant feature of patients with delirium in the ICU, suggesting the potential for the automatic prediction and early detection of delirium based on HRV with machine learning.

CHOOZ-A expert assessment program