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Testing Data (testing + data)
Selected AbstractsValidity of suspected alcohol and drug violations in aviation employeesADDICTION, Issue 10 2010Guohua Li ABSTRACT Aims In the United States, transportation employees who are suspected of using alcohol and drugs are subject to reasonable-cause testing. This study aims to assess the validity of suspected alcohol and drug violations in aviation employees. Methods Using reasonable-cause testing and random testing data from the Federal Aviation Administration for the years 1995,2005, we calculated the positive predictive value (PPV) and positive likelihood ratio (LR+) of suspected alcohol and drug violations. The true status of violations was based on testing results, with an alcohol violation being defined as a blood alcohol concentration of ,0.04 mg/dl and a drug violation as a test positive for marijuana, cocaine, amphetamines, phencyclidine or opiates. Results During the 11-year study period, a total of 2284 alcohol tests and 2015 drug tests were performed under the reasonable-cause testing program. The PPV was 37.7% [95% confidence interval (CI), 35.7,39.7%] for suspected alcohol violations and 12.6% (95% CI, 11.2,14.1%) for suspected drug violations. Random testing revealed an overall prevalence of 0.09% for alcohol violations and 0.6% for drug violations. The LR+ was 653.6 (95% CI, 581.7,734.3) for suspected alcohol violations and 22.5 (95% CI, 19.6,25.7) for suspected drug violations. Conclusion The discriminative power of reasonable-cause testing suggests that, despite its limited positive predictive value, physical and behavioral observation represents an efficient screening method for detecting alcohol and drug violations. The limited positive predictive value of reasonable-cause testing in aviation employees is due in part to the very low prevalence of alcohol and drug violations. [source] Financial decision support using neural networks and support vector machinesEXPERT SYSTEMS, Issue 4 2008Chih-Fong Tsai Abstract: Bankruptcy prediction and credit scoring are the two important problems facing financial decision support. The multilayer perceptron (MLP) network has shown its applicability to these problems and its performance is usually superior to those of other traditional statistical models. Support vector machines (SVMs) are the core machine learning techniques and have been used to compare with MLP as the benchmark. However, the performance of SVMs is not fully understood in the literature because an insufficient number of data sets is considered and different kernel functions are used to train the SVMs. In this paper, four public data sets are used. In particular, three different sizes of training and testing data in each of the four data sets are considered (i.e. 3:7, 1:1 and 7:3) in order to examine and fully understand the performance of SVMs. For SVM model construction, the linear, radial basis function and polynomial kernel functions are used to construct the SVMs. Using MLP as the benchmark, the SVM classifier only performs better in one of the four data sets. On the other hand, the prediction results of the MLP and SVM classifiers are not significantly different for the three different sizes of training and testing data. [source] Hybrid identification of fuzzy rule-based modelsINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 1 2002Sung-Kwun Oh In this study, we propose a hybrid identification algorithm for a class of fuzzy rule-based systems. The rule-based fuzzy modeling concerns structure optimization and parameter identification using the fuzzy inference methods and hybrid structure combined with two methods of optimization theories for nonlinear systems. Two types of inference methods of a fuzzy model concern a simplified and linear type of inference. The proposed hybrid optimal identification algorithm is carried out using a combination of genetic algorithms and an improved complex method. The genetic algorithms determine initial parameters of the membership function of the premise part of the fuzzy rules. In the sequel, the improved complex method (being in essence a powerful auto-tuning algorithm) leads to fine-tuning of the parameters of the respective membership functions. An aggregate performance index with a weighting factor is proposed in order to achieve a balance between performance of the fuzzy model obtained for the training and testing data. Numerical examples are included to evaluate the performance of the proposed model. They are also contrasted with the performance of the fuzzy models existing in the literature. © 2002 John Wiley & Sons, Inc. [source] Hip Fractures and the Contribution of Cortical Versus Trabecular Bone to Femoral Neck Strength,JOURNAL OF BONE AND MINERAL RESEARCH, Issue 3 2009Gerold Holzer Abstract Osteoporotic fractures are caused by both cortical thinning and trabecular bone loss. Both are seen to be important for bone fragility. The relative contributions of cortical versus trabecular bone have not been established. The aim of this study was to test the contribution of cortical versus trabecular bone to femoral neck stability in bone strength. In one femur from each pair of 18 human cadaver femurs (5 female; 4 male), trabecular bone was completely removed from the femoral neck, providing one bone with intact and the other without any trabecular structure in the femoral neck. Geometrical, X-ray, and DXA measurements were carried out before biomechanical testing (forces to fracture). Femoral necks were osteotomized, slices were analyzed for cross-sectional area (CSA) and cross-sectional moment of inertia (CSMI), and results were compared with biomechanical testing data. Differences between forces needed to fracture excavated and intact femurs (,F/F mean) was 7.0% on the average (range, 4.6,17.3%). CSA of removed spongiosa did not correlate with difference of fracture load (,F/F mean), nor did BMD. The relative contribution of trabecular versus cortical bone in respect to bone strength in the femoral neck seems to be marginal and seems to explain the subordinate role of trabecular bone and its changes in fracture risk and the effects of treatment options in preventing fractures. [source] Prediction model for increasing propylene from FCC gasoline secondary reactions based on Levenberg,Marquardt algorithm coupled with support vector machinesJOURNAL OF CHEMOMETRICS, Issue 9 2010Xiaowei Zhou Abstract Levenberg,Marquardt (LM) algorithm was adopted to optimize the multiple parameters of the support vector machines (SVM) model to overcome the difficulty in selecting the parameters of SVM and to fit relational expression of high nonlinearity. Strategy of dividing the training data into working data to train SVM and the testing data so as to avoid over-fitting was performed. Comparison of the proposed LM/SVM method with three reported hybridized SVM approaches (GA/SVM, SM/SVM and SQP/SVM) was also carried out. The new method was applied in modelling for the prediction of propylene by secondary reactions of FCC gasoline. Best performance of LM/SVM employing polynomial kernel was demonstrated. Good agreement between predicted results and experimental data suggests that the LM/SVM method is successfully developed and the SVM model for increasing propylene is well established. Finally, sequential quadratic programming (SQP) algorithm was employed to optimize the operation conditions of FCC gasoline secondary reaction for maximizing the propylene yield. The obtained optimization conditions are consistent with experimental data and reported results, indicating that the optimization results are reliable. Copyright © 2010 John Wiley & Sons, Ltd. [source] DYNAMIC MODELING OF RETORT PROCESSING USING NEURAL NETWORKSJOURNAL OF FOOD PROCESSING AND PRESERVATION, Issue 2 2002C. R. CHEN ABSTRACT Two neural network approaches , a moving-window and hybrid neural network , which combine neural network with polynomial regression models, were used for modeling F(t) and Qv(t) dynamic functions under constant retort temperature processing. The dynamic functions involved six variables: retort temperature (116,132C), thermal diffusivity (1.5,2.3 × 10,7m2/s), can radius (40,61 mm), can height (40,61 mm), and quality kinetic parameters z (15,39C) and D (150,250 min). A computer simulation designed for process calculations of food thermal processing systems was used to provide the fundamental data for training and generalization of ANN models. Training data and testing data were constructed by both second order central composite design and orthogonal array, respectively. The optimal configurations of ANN models were obtained by varying the number of hidden layers, number of neurons in hidden layer and learning runs, and a combination of learning rules and transfer function. Results demonstrated that both neural network models well described the F(t) and Qv(t) dynamic functions, but moving-window network had better modeling performance than the hybrid ANN models. By comparison of the configuration parameters, moving-window ANN models required more neurons in the hidden layer and more learning runs for training than the hybrid ANN models. [source] Computer-aided detection of brain tumor invasion using multiparametric MRIJOURNAL OF MAGNETIC RESONANCE IMAGING, Issue 3 2009Todd R. Jensen PhD Abstract Purpose To determine the potential of using a computer-aided detection method to intelligently distinguish peritumoral edema alone from peritumor edema consisting of tumor using a combination of high-resolution morphological and physiological magnetic resonance imaging (MRI) techniques available on most clinical MRI scanners. Materials and Methods This retrospective study consisted of patients with two types of primary brain tumors: meningiomas (n = 7) and glioblastomas (n = 11). Meningiomas are typically benign and have a clear delineation of tumor and edema. Glioblastomas are known to invade outside the contrast-enhancing area. Four classifiers of differing designs were trained using morphological, diffusion-weighted, and perfusion-weighted features derived from MRI to discriminate tumor and edema, tested on edematous regions surrounding tumors, and assessed for their ability to detect nonenhancing tumor invasion. Results The four classifiers provided similar measures of accuracy when applied to the training and testing data. Each classifier was able to identify areas of nonenhancing tumor invasion supported with adjunct images or follow-up studies. Conclusion The combination of features derived from morphological and physiological imaging techniques contains the information necessary for computer-aided detection of tumor invasion and allows for the identification of tumor invasion not previously visualized on morphological, diffusion-weighted, and perfusion-weighted images and maps. Further validation of this approach requires obtaining spatially coregistered tissue samples in a study with a larger sample size. J. Magn. Reson. Imaging 2009;30:481,489. © 2009 Wiley-Liss, Inc. [source] Quantitative structure/property relationship analysis of Caco-2 permeability using a genetic algorithm-based partial least squares methodJOURNAL OF PHARMACEUTICAL SCIENCES, Issue 10 2002Fumiyoshi Yamashita Abstract Caco-2 cell monolayers are widely used systems for predicting human intestinal absorption. This study was carried out to develop a quantitative structure,property relationship (QSPR) model of Caco-2 permeability using a novel genetic algorithm-based partial least squares (GA-PLS) method. The Caco-2 permeability data for 73 compounds were taken from the literature. Molconn-Z descriptors of these compounds were calculated as molecular descriptors, and the optimal subset of the descriptors was explored by GA-PLS analysis. A fitness function considering both goodness-of-fit to the training data and predictability of the testing data was adopted throughout the genetic algorithm-driven optimization procedure. The final PLS model consisting of 24 descriptors gave a correlation coefficient (r) of 0.886 for the entire dataset and a predictive correlation coefficient (rpred) of 0.825 that was evaluated by a leave-some-out cross-validation procedure. Thus, the GA-PLS analysis proved to be a reasonable QSPR modeling approach for predicting Caco-2 permeability. © 2002 Wiley-Liss Inc. and the American Pharmaceutical Association J Pharm Sci 91:2230,2239, 2002 [source] Likelihood inference for a class of latent Markov models under linear hypotheses on the transition probabilitiesJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES B (STATISTICAL METHODOLOGY), Issue 2 2006Francesco Bartolucci Summary., For a class of latent Markov models for discrete variables having a longitudinal structure, we introduce an approach for formulating and testing linear hypotheses on the transition probabilities of the latent process. For the maximum likelihood estimation of a latent Markov model under hypotheses of this type, we outline an EM algorithm that is based on well-known recursions in the hidden Markov literature. We also show that, under certain assumptions, the asymptotic null distribution of the likelihood ratio statistic for testing a linear hypothesis on the transition probabilities of a latent Markov model, against a less stringent linear hypothesis on the transition probabilities of the same model, is of type. As a particular case, we derive the asymptotic distribution of the likelihood ratio statistic between a latent class model and its latent Markov version, which may be used to test the hypothesis of absence of transition between latent states. The approach is illustrated through a series of simulations and two applications, the first of which is based on educational testing data that have been collected within the National Assessment of Educational Progress 1996, and the second on data, concerning the use of marijuana, which have been collected within the National Youth Survey 1976,1980. [source] Investigating the importance of flow when utilizing hyaluronan scaffolds for tissue engineeringJOURNAL OF TISSUE ENGINEERING AND REGENERATIVE MEDICINE, Issue 2 2010Gail C. Donegan Abstract Esterified hyaluronan scaffolds offer significant advantages for tissue engineering. They are recognized by cellular receptors, interact with many other extracellular matrix proteins and their metabolism is mediated by intrinsic cellular pathways. In this study differences in the viability and structural integrity of vascular tissue models cultured on hyaluronan scaffolds under laminar flow conditions highlighted potential differences in the biodegradation kinetics, processes and end-products, depending on the culture environment. Critical factors are likely to include seeding densities and the duration and magnitude of applied biomechanical stress. Proteomic evaluation of the timing and amount of remodelling protein expression, the resulting biomechanical changes arising from this response and metabolic cell viability assay, together with examination of tissue morphology, were conducted in vascular tissue models cultured on esterified hyaluronan felt and PTFE mesh scaffolds. The vascular tissue models were derived using complete cell sheets derived from harvested and expanded umbilical cord vein cells. This seeding method utilizes high-density cell populations from the outset, while the cells are already supported by their own abundant extracellular matrix. Type I and type IV collagen expression in parallel with MMP-1 and MMP-2 expression were monitored in the tissue models over a 10 day culture period under laminar flow regimes using protein immobilization technologies. Uniaxial tensile testing and scanning electron microscopy were used to compare the resulting effects of hydrodynamic stimulation upon structural integrity, while viability assays were conducted to evaluate the effects of shear on metabolic function. The proteomic results showed that the hyaluronan felt-supported tissues expressed higher levels of all remodelling proteins than those cultured on PTFE mesh. Overall, a 21% greater expression of type I collagen, 24% higher levels of type IV collagen, 24% higher levels of MMP-1 and 34% more MMP-2 were observed during hydrodynamic stress. This was coupled with a loss of structural integrity in these models after the introduction of laminar flow, as compared to the increases in all mechanical properties observed in the PTFE mesh-supported tissues. However, under flow conditions, the hyaluronan-supported tissues showed some recovery of the viability originally lost during static culture conditions, in contrast to PTFE mesh-based models, where initial gains were followed by a decline in metabolic viability after applied shear stress. Proteomic, cell viability and mechanical testing data emphasized the need for extended in vitro evaluations to enable better understanding of multi-stage remodelling and reparative processes in tissues cultured on biodegradable scaffolds. This study also highlighted the possibility that in high-density tissue culture with a biodegradable component, dynamic conditions may be more conducive to optimal tissue development than the static environment because they facilitate the efficient removal of high concentrations of degradation end-products accumulating in the pericellular space. Copyright © 2009 John Wiley & Sons, Ltd. [source] Toxic gas release caused by the thermal decomposition of a bulk powder blend containing sodium dichloroisocyanuratePROCESS SAFETY PROGRESS, Issue 2 2003Andrew R. Carpenter P.E. A thermal runaway reaction occurred during the mixing of a batch of a bulk powder that resulted in the production and release of toxic gases. The mixture consisted of an oxidizer (sodium dichloroisocyanurate), some organic compounds, and inert compounds. This toxic release led to the evacuation of the building and resulted in extensive damage to the facility. This was only the fourth time an 1,100-pound batch of this material had been mixed in this equipment. Prior to this production run, the material had been prepared in small batches of 2 to 50 kilograms. Accelerated Rate Calorimetry (ARC) testing had been performed prior to the scale-up to production batches. This paper looks into the root causes of this particular accident and demonstrates how proper analysis of the testing data and other warning signs observed during the bench testing could have revealed the likelihood of this accident. Further, this paper will consider how simple design changes to the manufacturing process resulted in an inherently safer design. [source] Application of source removal and natural attenuation remediation strategies at MGP sites in WisconsinREMEDIATION, Issue 4 2003James W. Lingle This article presents site closure strategies of source material removal and dissolved-phase groundwater natural attenuation that were applied at two manufactured gas plant (MGP) sites in Wisconsin. The source removal actions were implemented in 1999 and 2000 with groundwater monitoring activities preceding and following those actions. Both of these sites have unique geological and hydrogeological conditions. The article briefly presents site background information and source removal activities at both of these sites and focuses on groundwater analytical testing data that demonstrate remediation of dissolved-phase MGP-related groundwater impacts by natural attenuation. A statistical evaluation of the data supports a stable or declining MGP parameter concentration trend at each of the sites. A comparison of the site natural attenuation evaluation is made to compare with the requirements for site closure under the Wisconsin Department of Natural Resources regulations and guidance. © 2003 Wiley Periodicals, Inc. [source] Characteristics of Abnormal Pressure Systems and Their Responses of Fluid in Huatugou Oil Field, Qaidam BasinACTA GEOLOGICA SINICA (ENGLISH EDITION), Issue 5 2009Xiaozhi CHEN Abstract: Based on the comprehensive study of core samples, well testing data, and reservoir fluid properties, the construction and the distribution of the abnormal pressure systems of the Huatugou oil field in Qaidam Basin are discussed. The correlation between the pressure systems and hydrocarbon accumulation is addressed by analyzing the corresponding fluid characteristics. The results show that the Huatugou oil field as a whole has low formation pressure and low fluid energy; therefore, the hydrocarbons are hard to migrate, which facilitates the forming of primary reservoirs. The study reservoirs, located at the Xiayoushashan Formation (N21) and the Shangganchaigou Formation (N1) are relatively shallow and have medium porosity and low permeability. They are abnormal low-pressure reservoirs with an average formation pressure coefficient of 0.61 and 0.72 respectively. According to the pressure coefficient and geothermal anomaly, the N1 and N21 Formations belong to two independent temperature-pressure systems, and the former has slightly higher energy. The low-pressure compartments consist of a distal bar as the main body, prodelta mud as the top boundary, and shore and shallow lake mud or algal mound as the bottom boundary. They are vertically overlapped and horizontally paralleled. The formation water is abundant in the Cl, ion and can be categorized as CaCl2 type with high salinity, which indicates that the abnormal low-pressure compartments are in good sealing condition and beneficial for oil and gas accumulation and preservation. [source] | ||||||||||||||||