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Average Accuracy (average + accuracy)
Selected AbstractsEstimating the Accuracy of Jury VerdictsJOURNAL OF EMPIRICAL LEGAL STUDIES, Issue 2 2007Bruce D. Spencer Average accuracy of jury verdicts for a set of cases can be studied empirically and systematically even when the correct verdict cannot be known. The key is to obtain a second rating of the verdict, for example, the judge's, as in the recent study of criminal cases in the United States by the National Center for State Courts (NCSC). That study, like the famous Kalven-Zeisel study, showed only modest judge-jury agreement. Simple estimates of jury accuracy can be developed from the judge-jury agreement rate; the judge's verdict is not taken as the gold standard. Although the estimates of accuracy are subject to error, under plausible conditions they tend to overestimate the average accuracy of jury verdicts. The jury verdict was estimated to be accurate in no more than 87 percent of the NCSC cases (which, however, should not be regarded as a representative sample with respect to jury accuracy). More refined estimates, including false conviction and false acquittal rates, are developed with models using stronger assumptions. For example, the conditional probability that the jury incorrectly convicts given that the defendant truly was not guilty (a "Type I error") was estimated at 0.25, with an estimated standard error (s.e.) of 0.07, the conditional probability that a jury incorrectly acquits given that the defendant truly was guilty ("Type II error") was estimated at 0.14 (s.e. 0.03), and the difference was estimated at 0.12 (s.e. 0.08). The estimated number of defendants in the NCSC cases who truly are not guilty but are convicted does seem to be smaller than the number who truly are guilty but are acquitted. The conditional probability of a wrongful conviction, given that the defendant was convicted, is estimated at 0.10 (s.e. 0.03). [source] Modeling of loops in protein structuresPROTEIN SCIENCE, Issue 9 2000András Fiser Abstract Comparative protein structure prediction is limited mostly by the errors in alignment and loop modeling. We describe here a new automated modeling technique that significantly improves the accuracy of loop predictions in protein structures. The positions of all nonhydrogen atoms of the loop are optimized in a fixed environment with respect to a pseudo energy function. The energy is a sum of many spatial restraints that include the bond length, bond angle, and improper dihedral angle terms from the CHARMM-22 force field, statistical preferences for the main-chain and side-chain dihedral angles, and statistical preferences for nonbonded atomic contacts that depend on the two atom types, their distance through space, and separation in sequence. The energy function is optimized with the method of conjugate gradients combined with molecular dynamics and simulated annealing. Typically, the predicted loop conformation corresponds to the lowest energy conformation among 500 independent optimizations. Predictions were made for 40 loops of known structure at each length from 1 to 14 residues. The accuracy of loop predictions is evaluated as a function of thoroughness of conformational sampling, loop length, and structural properties of native loops. When accuracy is measured by local superposition of the model on the native loop, 100, 90, and 30% of 4,, 8,, and 12,residue loop predictions, respectively, had <2 Å RMSD error for the mainchain N, Ca, C, and O atoms; the average accuracies were 0.59 6 0.05, 1.16 6 0.10, and 2.61 6 0.16 Å, respectively. To simulate real comparative modeling problems, the method was also evaluated by predicting loops of known structure in only approximately correct environments with errors typical of comparative modeling without misalignment. When the RMSD distortion of the main-chain stem atoms is 2.5 Å, the average loop prediction error increased by 180, 25, and 3% for 4,, 8,, and 12,residue loops, respectively. The accuracy of the lowest energy prediction for a given loop can be estimated from the structural variability among a number of low energy predictions. The relative value of the present method is gauged by (1) comparing it with one of the most successful previously described methods, and (2) describing its accuracy in recent blind predictions of protein structure. Finally, it is shown that the average accuracy of prediction is limited primarily by the accuracy of the energy function rather than by the extent of conformational sampling. [source] Children use categories to maximize accuracy in estimationDEVELOPMENTAL SCIENCE, Issue 6 2006Sean Duffy The present study tests a model of category effects upon stimulus estimation in children. Prior work with adults suggests that people inductively generalize distributional information about a category of stimuli and use this information to adjust their estimates of individual stimuli in a way that maximizes average accuracy in estimation (see Huttenlocher, Hedges & Vevea, 2000). However, little is known about the developmental origin of this cognitive process. In the present study, 5- and 7-year-old children viewed stimuli that varied in size and reproduced each from memory. Consistent with the predictions of a Bayesian model of category effects on estimation, responses were adjusted toward the central value of the stimulus distribution. Additionally, the dispersion of the stimulus distribution affected the pattern of bias and variability of responses in a way that is predicted by the model. The results suggest that, like adults, children use categories for increasing average accuracy in estimating inexact stimuli. [source] Augmentation of a nearest neighbour clustering algorithm with a partial supervision strategy for biomedical data classificationEXPERT SYSTEMS, Issue 1 2009Sameh A. Salem Abstract: In this paper, a partial supervision strategy for a recently developed clustering algorithm, the nearest neighbour clustering algorithm (NNCA), is proposed. The proposed method (NNCA-PS) offers classification capability with a smaller amount of a priori knowledge, where a small number of data objects from the entire data set are used as labelled objects to guide the clustering process towards a better search space. Experimental results show that NNCA-PS gives promising results of 89% sensitivity at 95% specificity when used to segment retinal blood vessels, and a maximum classification accuracy of 99.5% with 97.2% average accuracy when applied to a breast cancer data set. Comparisons with other methods indicate the robustness of the proposed method in classification. Additionally, experiments on parallel environments indicate the suitability and scalability of NNCA-PS in handling larger data sets. [source] Accurate closed-form model for computation of conductor loss of coplanar waveguideINTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING, Issue 1 2010Payal Majumdar Abstract This study estimates the accuracy of HFSS and Sonnet and other models against the experimental results from three sources. A closed-form model for experiment based stopping distance is developed to calculate accurately conductor loss of CPW. The present improved Holloway and Kuester (IHK) model has an average accuracy of 3.7% against the experimental results from different sources in the frequency range 1,120 GHz with conductor thickness of 0.25,1.58 ,m. The original Holloway and Kuester model has an average accuracy of 13.7% and model of Ponchak et al. 17.1 % against same set of experimental results. HFSS and Sonnet have average accuracy of 7.86% and 10.33% against same set of experimental data. The accuracy of IHK model is also examined against HFSS and Sonnet for the conductor thickness up to 9 ,m and substrate relative permittivity in the range of 3.8,20. © 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2010. [source] Estimating the Accuracy of Jury VerdictsJOURNAL OF EMPIRICAL LEGAL STUDIES, Issue 2 2007Bruce D. Spencer Average accuracy of jury verdicts for a set of cases can be studied empirically and systematically even when the correct verdict cannot be known. The key is to obtain a second rating of the verdict, for example, the judge's, as in the recent study of criminal cases in the United States by the National Center for State Courts (NCSC). That study, like the famous Kalven-Zeisel study, showed only modest judge-jury agreement. Simple estimates of jury accuracy can be developed from the judge-jury agreement rate; the judge's verdict is not taken as the gold standard. Although the estimates of accuracy are subject to error, under plausible conditions they tend to overestimate the average accuracy of jury verdicts. The jury verdict was estimated to be accurate in no more than 87 percent of the NCSC cases (which, however, should not be regarded as a representative sample with respect to jury accuracy). More refined estimates, including false conviction and false acquittal rates, are developed with models using stronger assumptions. For example, the conditional probability that the jury incorrectly convicts given that the defendant truly was not guilty (a "Type I error") was estimated at 0.25, with an estimated standard error (s.e.) of 0.07, the conditional probability that a jury incorrectly acquits given that the defendant truly was guilty ("Type II error") was estimated at 0.14 (s.e. 0.03), and the difference was estimated at 0.12 (s.e. 0.08). The estimated number of defendants in the NCSC cases who truly are not guilty but are convicted does seem to be smaller than the number who truly are guilty but are acquitted. The conditional probability of a wrongful conviction, given that the defendant was convicted, is estimated at 0.10 (s.e. 0.03). [source] Modeling of loops in protein structuresPROTEIN SCIENCE, Issue 9 2000András Fiser Abstract Comparative protein structure prediction is limited mostly by the errors in alignment and loop modeling. We describe here a new automated modeling technique that significantly improves the accuracy of loop predictions in protein structures. The positions of all nonhydrogen atoms of the loop are optimized in a fixed environment with respect to a pseudo energy function. The energy is a sum of many spatial restraints that include the bond length, bond angle, and improper dihedral angle terms from the CHARMM-22 force field, statistical preferences for the main-chain and side-chain dihedral angles, and statistical preferences for nonbonded atomic contacts that depend on the two atom types, their distance through space, and separation in sequence. The energy function is optimized with the method of conjugate gradients combined with molecular dynamics and simulated annealing. Typically, the predicted loop conformation corresponds to the lowest energy conformation among 500 independent optimizations. Predictions were made for 40 loops of known structure at each length from 1 to 14 residues. The accuracy of loop predictions is evaluated as a function of thoroughness of conformational sampling, loop length, and structural properties of native loops. When accuracy is measured by local superposition of the model on the native loop, 100, 90, and 30% of 4,, 8,, and 12,residue loop predictions, respectively, had <2 Å RMSD error for the mainchain N, Ca, C, and O atoms; the average accuracies were 0.59 6 0.05, 1.16 6 0.10, and 2.61 6 0.16 Å, respectively. To simulate real comparative modeling problems, the method was also evaluated by predicting loops of known structure in only approximately correct environments with errors typical of comparative modeling without misalignment. When the RMSD distortion of the main-chain stem atoms is 2.5 Å, the average loop prediction error increased by 180, 25, and 3% for 4,, 8,, and 12,residue loops, respectively. The accuracy of the lowest energy prediction for a given loop can be estimated from the structural variability among a number of low energy predictions. The relative value of the present method is gauged by (1) comparing it with one of the most successful previously described methods, and (2) describing its accuracy in recent blind predictions of protein structure. Finally, it is shown that the average accuracy of prediction is limited primarily by the accuracy of the energy function rather than by the extent of conformational sampling. [source] Spatial variability of above-ground net primary production in Uruguayan grasslands: a remote sensing approachAPPLIED VEGETATION SCIENCE, Issue 1 2010S. Baeza Abstract Question: How does above-ground net primary production (ANPP) differ (estimated from remotely sensed data) among vegetation units in sub-humid temperate grasslands? Location: Centre-north Uruguay. Methods: A vegetation map of the study area was generated from LANDSAT imagery and the landscape configuration described. The functional heterogeneity of mapping units was analysed in terms of the fraction of photosynthetically active radiation absorbed by green vegetation (fPAR), calculated from the normalized difference vegetation index (NDVI) images provided by the moderate resolution imaging spectroradiometer (MODIS) sensor. Finally, the ANPP of each grassland class was estimated using NDVI and climatic data. Results: Supervised classification presented a good overall accuracy and moderate to good average accuracy for grassland classes. Meso-xerophytic grasslands occupied 45% of the area, Meso-hydrophytic grasslands 43% and Lithophytic steppes 6%. The landscape was shaped by a matrix of large, unfragmented patches of Meso-xerophytic and Meso-hydrophytic grasslands. The region presented the lowest anthropic fragmentation degree reported for the Rio de la Plata grasslands. All grassland units showed bimodal annual fPAR seasonality, with spring and autumn peaks. Meso-hydrophytic grasslands showed a radiation interception 10% higher than the other units. On an annual basis, Meso-hydrophytic grasslands produced 3800 kg dry matter (DM) ha,1 yr,1 and Meso-xerophytic grasslands and Lithophytic steppes around 3400 kg·DM·ha,1·yr,1. Meso-xerophytic grasslands had the largest spatial variation during most of the year. The ANPP temporal variation was higher than the fPAR variability. Conclusions: Our results provide valuable information for grazing management (identifying spatial and temporal variations of ANPP) and grassland conservation (identifying the spatial distribution of vegetation units). [source] Speckle observations with PISCO in Merate: VIII.ASTRONOMISCHE NACHRICHTEN, Issue 3 2010Astrometric measurements of visual binaries in 200, new orbits of the multiple system Zeta Aqr Abstract We present relative astrometric measurements of visual binaries made during the second semester of 2007, with the speckle camera PISCO at the 102 cm Zeiss telescope of Brera Astronomical Observatory, in Merate. Our sample contains orbital couples as well as binaries whose motion is still uncertain. We obtained 283 new measurements of 279 objects, with angular separations in the range 0,.17,4,.4, and an average accuracy of 0,.014. The mean error on the position angles is 0°.6. Most of the position angles were determined without the usual 180° ambiguity with the application of triple-correlation techniques and/or by inspection of the long integration files. We also present the new orbit we have computed for Zeta Aqr AB (ADS 15971), for which our measurements lead to large residuals with the previously computed orbit. We were also able to compute the elements of the perturbation orbit Bb-P caused by an invisible companion, whose mass is estimated at 0.7 M, (© 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] Speckle observations with PISCO in Merate: VI.ASTRONOMISCHE NACHRICHTEN, Issue 1 2009Astrometric measurements of visual binaries in 200 Abstract We present relative astrometric measurements of visual binaries made during the second semester of 2006, with the speckle camera PISCO at the 102 cm Zeiss telescope of Brera Astronomical Observatory, in Merate. Our sample contains orbital couples as well as binaries whose motion is still uncertain. We obtained 175 new measurements of 169 objects, with angular separations in the range 0,.1,4,.2, and an average accuracy of 0,.01. The mean error on the position angles is 0°.6. Most of the position angles could be determined without the usual 180° ambiguity with the application of triplecorrelation techniques and/or by inspection of the long integration files. We also present the new orbits we have computed for ADS 11479, 11584 and 16538, for which our measurements lead to large residuals and/or for which the revision was justified by the significant number of observations made since the last orbit computation (© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] | ||||||||||