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Sample records for hawt performance prediction

  1. Performance and wake predictions of HAWTs in wind farms

    Energy Technology Data Exchange (ETDEWEB)

    Leclerc, C.; Masson, C.; Paraschivoiu, I. [Ecole Polytechnique, Montreal (Canada)

    1997-12-31

    The present contribution proposes and describes a promising way towards performance prediction of an arbitrary array of turbines. It is based on the solution of the time-averaged, steady-state, incompressible Navier-Stokes equations with an appropriate turbulence closure model. The turbines are represented by distributions of momentum sources in the Navier-Stokes equations. In this paper, the applicability and viability of the proposed methodology is demonstrated using an axisymmetric implementation. The k-{epsilon} model has been chosen for the closure of the time-averaged, turbulent flow equations and the properties of the incident flow correspond to those of a neutral atmospheric boundary layer. The proposed mathematical model is solved using a Control-Volume Finite Element Method (CVFEM). Detailed results have been obtained using the proposed method for an isolated wind turbine and for two turbines one behind another. In the case of an isolated turbine, accurate wake velocity deficit predictions are obtained and an increase in power due to atmospheric turbulence is found in agreement with measurements. In the case of two turbines, the proposed methodology provides an appropriate modelling of the wind-turbine wake and a realistic prediction of the performance degradation of the downstream turbine.

  2. A fully unsteady prescribed wake model for HAWT performance prediction in yawed flow

    Energy Technology Data Exchange (ETDEWEB)

    Coton, F.N.; Tongguang, Wang; Galbraith, R.A.M.; Lee, D. [Univ. of Glasgow (United Kingdom)

    1997-12-31

    This paper describes the development of a fast, accurate, aerodynamic prediction scheme for yawed flow on horizontal axis wind turbines (HAWTs). The method is a fully unsteady three-dimensional model which has been developed over several years and is still being enhanced in a number of key areas. The paper illustrates the current ability of the method by comparison with field data from the NREL combined experiment and also describes the developmental work in progress. In particular, an experimental test programme designed to yield quantitative wake convection information is summarised together with modifications to the numerical model which are necessary for meaningful comparison with the experiments. Finally, current and future work on aspects such as tower-shadow and improved unsteady aerodynamic modelling are discussed.

  3. Prediction of H.A.W.T. blade stall and performance

    Energy Technology Data Exchange (ETDEWEB)

    Giannakidis, G.; Graham, J.M.R. [Imperial College, Dept. of Aeronautics, London (United Kingdom)

    1996-09-01

    A model is being developed for the prediction of Horizontal Axis Wind Turbine blade stall and performance coupled with a simple aeroelastic analysis model. For the aerodynamic calculation a two dimensional unsteady Navier-Stokes solver on a sectional basis on the blade is coupled with a three dimensional vortex lattice wake. Pressure coefficient distributions are calculated from the two dimensional viscous flow in each blade section. The aerodynamic computations are coupled with a vibrating beam model in order to incorporate flapwise deformations of the blade. (au) 17 refs.

  4. The Performance Test of Three Different Horizontal Axis Wind Turbine (HAWT Blade Shapes Using Experimental and Numerical Methods

    Directory of Open Access Journals (Sweden)

    Wen-Tong Chong

    2013-06-01

    Full Text Available Three different horizontal axis wind turbine (HAWT blade geometries with the same diameter of 0.72 m using the same NACA4418 airfoil profile have been investigated both experimentally and numerically. The first is an optimum (OPT blade shape, obtained using improved blade element momentum (BEM theory. A detailed description of the blade geometry is also given. The second is an untapered and optimum twist (UOT blade with the same twist distributions as the OPT blade. The third blade is untapered and untwisted (UUT. Wind tunnel experiments were used to measure the power coefficients of these blades, and the results indicate that both the OPT and UOT blades perform with the same maximum power coefficient, Cp = 0.428, but it is located at different tip speed ratio, λ = 4.92 for the OPT blade and λ = 4.32 for the UOT blade. The UUT blade has a maximum power coefficient of Cp = 0.210 at λ = 3.86. After the tests, numerical simulations were performed using a full three-dimensional computational fluid dynamics (CFD method using the k-ω SST turbulence model. It has been found that CFD predictions reproduce the most accurate model power coefficients. The good agreement between the measured and computed power coefficients of the three models strongly suggest that accurate predictions of HAWT blade performance at full-scale conditions are also possible using the CFD method.

  5. Numerical study of effect of pitch angle on performance characteristics of a HAWT

    Directory of Open Access Journals (Sweden)

    Sudhamshu A.R.

    2016-03-01

    Full Text Available Wind energy is one of the clean renewable forms of energy that can handle the existing global fossil fuel crisis. Although it contributes to 2.5% of the global electricity demand, with diminishing fossil fuel sources, it is important that wind energy is harnessed to a greater extent to meet the energy crisis and problem of pollution. The present work involves study of effect of pitch angle on the performance of a horizontal axis wind turbine (HAWT, NREL Phase VI. The wind velocities considered for the study are 7, 15.1 and 25.1 m/s. The simulations are performed using a commercial CFD code Fluent. A frozen rotor model is used for simulation, wherein the governing equations are solved in the moving frame of reference rotating with the rotor speed. The SST k-ω turbulence model has been used. It is seen that the thrust increases with increase in wind velocity, and decreases with increase in pitch angle. For a given wind velocity, there is an optimum pitch angle where the power generated by the turbine is maximum. The observed effect of pitch angle on the power produced has been correlated to the stall characteristics of the airfoil blade.

  6. Experimental study of improved HAWT performance in simulated natural wind by an active controlled multi-fan wind tunnel

    Science.gov (United States)

    Toshimitsu, Kazuhiko; Narihara, Takahiko; Kikugawa, Hironori; Akiyoshi, Arata; Kawazu, Yuuya

    2017-04-01

    The effects of turbulent intensity and vortex scale of simulated natural wind on performance of a horizontal axis wind turbine (HAWT) are mainly investigated in this paper. In particular, the unsteadiness and turbulence of wind in Japan are stronger than ones in Europe and North America in general. Hence, Japanese engineers should take account of the velocity unsteadiness of natural wind at installed open-air location to design a higher performance wind turbine. Using the originally designed five wind turbines on the basis of NACA and MEL blades, the dependencies of the wind frequency and vortex scale of the simulated natural wind are presented. As the results, the power coefficient of the newly designed MEL3-type rotor in the simulated natural wind is 130% larger than one in steady wind.

  7. BOUNDARY LAYER AND AMPLIFIED GRID EFFECTS ON AERODYNAMIC PERFORMANCES OF S809 AIRFOIL FOR HORIZONTAL AXIS WIND TURBINE (HAWT

    Directory of Open Access Journals (Sweden)

    YOUNES EL KHCHINE

    2017-11-01

    Full Text Available The design of rotor blades has a great effect on the aerodynamics performances of horizontal axis wind turbine and its efficiency. This work presents the effects of mesh refinement and boundary layer on aerodynamic performances of wind turbine S809 rotor. Furthermore, the simulation of fluid flow is taken for S809 airfoil wind turbine blade using ANSYS/FLUENT software. The problem is solved by the conservation of mass and momentum equations for unsteady and incompressible flow using advanced SST k-ω turbulence model, in order to predict the effects of mesh refinement and boundary layer on aerodynamics performances. Lift and drag coefficients are the most important parameters in studying the wind turbine performance, these coefficients are calculated for four meshes refinement and different angles of attacks with Reynolds number is 106. The study is applied to S809 airfoil which has 21% thickness, specially designed by NREL for horizontal axis wind turbines.

  8. Comparison between OpenFOAM CFD & BEM theory for variable speed – variable pitch HAWT

    Directory of Open Access Journals (Sweden)

    ElQatary Islam

    2014-01-01

    Full Text Available OpenFoam is used to compare computational fluid dynamics (CFD with blade element momentum theory (BEM for a variable speed - variable pitch HAWT (Horizontal Axis Wind Turbine. The wind turbine is first designed using the BEM to determine the blade chord, twist and operating conditions. The wind turbine blade has an outer diameter of 14 m, uses a NACA 63–415 profile for the entire blade and root to tip twist distribution of 15deg (Figure 3. The RPM varies from 20–75 for freestream velocities varying between 3–10.5 m/s (variable speed and a constant RPM of 78.78 for velocities ranging between 11–25 m/s (variable pitch. OpenFOAM is used to investigate the wind turbine performance at several operating points including cut-in wind speed (3 m/s, rated wind speed (10.5 m/s and in the variable pitch zone. Simulation results show that in the variable-speed operating range, both CFD and BEM compare reasonably well. This agreement can be attributed to the fact that the complex three-dimensional flow around the turbine blades can be split into two radial segments. For radii less than the mid-span, the flow is three-dimensional, whereas for radii greater than the mid-span, the flow is approximately two-dimensional. Since the majority of the power is produced from sections beyond the mid-span, the agreement between CFD and BEM is reasonable. For the variable-pitch operating range the CFD results and BEM deviate considerably. In this case the majority of the power is produced from the inner sections in which the flow is three-dimensional and can no longer be predicted by the BEM. The results show that differences in pitch angles up to 10deg can result to regulate the power for high wind speeds in the variable-pitch operation zone.

  9. Analytical study on different blade-shape design of HAWT for wasted kinetic energy recovery system (WKERS)

    Science.gov (United States)

    Goh, J. B.; Jamaludin, Z.; Jafar, F. A.; Mat Ali, M.; Mokhtar, M. N. Ali; Tan, C. H.

    2017-06-01

    Wasted kinetic energy recovery system (WKERS) is a wind renewable gadget installed above a cooling tower outlet to harvest the discharged wind for electrical regeneration purpose. The previous WKERS is operated by a horizontal axis wind turbine (HAWT) with delta blade design but the performance is still not at the optimum level. Perhaps, a better blade-shape design should be determined to obtain the optimal performance, as it is believed that the blade-shape design plays a critical role in HAWT. Hence, to determine a better blade-shape design for a new generation of WKERS, elliptical blade, swept blade and NREL Phase IV blade are selected for this benchmarking process. NREL Phase IV blade is a modern HAWT’s blade design by National Renewable Energy Laboratory (NREL) research lab. During the process of benchmarking, Computational Fluid Dynamics (CFD) analysis was ran by using SolidWorks design software, where all the designs are simulated with linear flow simulation. The wind speed in the simulation is set at 10.0 m/s, which is compatible with the average wind speed produced by a standard size cooling tower. The result is obtained by flow trajectories of air motion, surface plot and cut plot of the applied blade-shape. Besides, the aspect ratio of each blade is calculated and included as one of the reference in the comparison. Hence, the final selection of the best blade-shape design will bring to the new generation of WKERS.

  10. Torque-Matched Aerodynamic Shape Optimization of HAWT Rotor

    International Nuclear Information System (INIS)

    Al-Abadi, Ali; Ertunç, Özgür; Beyer, Florian; Delgado, Antonio

    2014-01-01

    Schmitz and Blade Element Momentum (BEM) theories are integrated to a gradient based optimization algorithm to optimize the blade shape of a horizontal axis wind turbine (HAWT). The Schmitz theory is used to generate an initial blade design. BEM theory is used to calculate the forces, torque and power extracted by the turbine. The airfoil shape (NREL S809) is kept the same, so that the shape optimization comprises only the chord and the pitch angle distribution. The gradient based optimization of the blade shape is constrained to the torque-rotational speed characteristic of the generator, which is going to be a part of the experimental set-up used to validate the results of the optimization study. Hence, the objective of the optimization is the maximization of the turbines power coefficient C p while keeping the torque matched to that of the generator. The wind velocities and the rotational speeds are limited to those achievable in the wind tunnel and by the generator, respectively. After finding the optimum blade shape with the maximum C p within the given range of parameters, the C p of the turbine is evaluated at wind-speeds deviating from the optimum operating condition. For this purpose, a second optimization algorithm is used to find out the correct rotational speed for a given wind-speed, which is again constrained to the generator's torque rotational speed characteristic. The design and optimization procedures are later validated by high-fidelity numerical simulations. The agreement between the design and the numerical simulations is very satisfactory

  11. Gate valve performance prediction

    International Nuclear Information System (INIS)

    Harrison, D.H.; Damerell, P.S.; Wang, J.K.; Kalsi, M.S.; Wolfe, K.J.

    1994-01-01

    The Electric Power Research Institute is carrying out a program to improve the performance prediction methods for motor-operated valves. As part of this program, an analytical method to predict the stem thrust required to stroke a gate valve has been developed and has been assessed against data from gate valve tests. The method accounts for the loads applied to the disc by fluid flow and for the detailed mechanical interaction of the stem, disc, guides, and seats. To support development of the method, two separate-effects test programs were carried out. One test program determined friction coefficients for contacts between gate valve parts by using material specimens in controlled environments. The other test program investigated the interaction of the stem, disc, guides, and seat using a special fixture with full-sized gate valve parts. The method has been assessed against flow-loop and in-plant test data. These tests include valve sizes from 3 to 18 in. and cover a considerable range of flow, temperature, and differential pressure. Stem thrust predictions for the method bound measured results. In some cases, the bounding predictions are substantially higher than the stem loads required for valve operation, as a result of the bounding nature of the friction coefficients in the method

  12. Performance Prediction Toolkit

    Energy Technology Data Exchange (ETDEWEB)

    2017-09-25

    The Performance Prediction Toolkit (PPT), is a scalable co-design tool that contains the hardware and middle-ware models, which accept proxy applications as input in runtime prediction. PPT relies on Simian, a parallel discrete event simulation engine in Python or Lua, that uses the process concept, where each computing unit (host, node, core) is a Simian entity. Processes perform their task through message exchanges to remain active, sleep, wake-up, begin and end. The PPT hardware model of a compute core (such as a Haswell core) consists of a set of parameters, such as clock speed, memory hierarchy levels, their respective sizes, cache-lines, access times for different cache levels, average cycle counts of ALU operations, etc. These parameters are ideally read off a spec sheet or are learned using regression models learned from hardware counters (PAPI) data. The compute core model offers an API to the software model, a function called time_compute(), which takes as input a tasklist. A tasklist is an unordered set of ALU, and other CPU-type operations (in particular virtual memory loads and stores). The PPT application model mimics the loop structure of the application and replaces the computational kernels with a call to the hardware model's time_compute() function giving tasklists as input that model the compute kernel. A PPT application model thus consists of tasklists representing kernels and the high-er level loop structure that we like to think of as pseudo code. The key challenge for the hardware model's time_compute-function is to translate virtual memory accesses into actual cache hierarchy level hits and misses.PPT also contains another CPU core level hardware model, Analytical Memory Model (AMM). The AMM solves this challenge soundly, where our previous alternatives explicitly include the L1,L2,L3 hit-rates as inputs to the tasklists. Explicit hit-rates inevitably only reflect the application modeler's best guess, perhaps informed by a few

  13. A New Method for Horizontal Axis Wind Turbine (HAWT Blade Optimization

    Directory of Open Access Journals (Sweden)

    Mohammadreza Mohammadi

    2016-02-01

    Full Text Available Iran has a great potential for wind energy. This paper introduces optimization of 7 wind turbine blades for small and medium scales in a determined wind condition of Zabol site, Iran, where the average wind speed is considered 7 m /s. Considered wind turbines are 3 bladed and radius of 7 case study turbine blades are 4.5 m, 6.5 m, 8 m, 9 m, 10 m, 15.5 m and 20 m. As the first step, an initial design is performed using one airfoil (NACA 63-215 across the blade. In the next step, every blade is divided into three sections, while the 20 % of first part of the blade is considered as root, the 5% of last the part is considered as tip and the rest of the blade as mid part. Providing necessary input data, suitable airfoils for wind turbines including 43 airfoils are extracted and their experimental data are entered in optimization process. Three variables in this optimization problem would be airfoil type, attack angle and chord, where the objective function is maximum output torque. A MATLAB code was written for design and optimization of the blade, which was validated with a previous experimental work. In addition, a comparison was made to show the effect of optimization with two variables (airfoil type and attack angle versus optimization with three variables (airfoil type, attack angle and chord on output torque increase. Results of this research shows a dramatic increase in comparison to initial designed blade with one airfoil where two variable optimization causes 7.7% to 22.27 % enhancement and three variable optimization causes 17.91% up to 24.48% rise in output torque .Article History: Received Oct 15, 2015; Received in revised form January 2, 2016; Accepted January 14, 2016; Available online How to Cite This Article: Mohammadi, M., Mohammadi, A. and Farahat, S. (2016 A New Method for Horizontal Axis Wind Turbine (HAWT Blade Optimization. Int. Journal of Renewable Energy Development, 5(1,1-8. http://dx.doi.org/10.14710/ijred.5.1.1-8

  14. Predicting emergency diesel starting performance

    International Nuclear Information System (INIS)

    DeBey, T.M.

    1989-01-01

    The US Department of Energy effort to extend the operational lives of commercial nuclear power plants has examined methods for predicting the performance of specific equipment. This effort focuses on performance prediction as a means for reducing equipment surveillance, maintenance, and outages. Realizing these goals will result in nuclear plants that are more reliable, have lower maintenance costs, and have longer lives. This paper describes a monitoring system that has been developed to predict starting performance in emergency diesels. A prototype system has been built and tested on an engine at Sandia National Laboratories. 2 refs

  15. EPRI MOV performance prediction program

    International Nuclear Information System (INIS)

    Hosler, J.F.; Damerell, P.S.; Eidson, M.G.; Estep, N.E.

    1994-01-01

    An overview of the EPRI Motor-Operated Valve (MOV) Performance Prediction Program is presented. The objectives of this Program are to better understand the factors affecting the performance of MOVs and to develop and validate methodologies to predict MOV performance. The Program involves valve analytical modeling, separate-effects testing to refine the models, and flow-loop and in-plant MOV testing to provide a basis for model validation. The ultimate product of the Program is an MOV Performance Prediction Methodology applicable to common gate, globe, and butterfly valves. The methodology predicts thrust and torque requirements at design-basis flow and differential pressure conditions, assesses the potential for gate valve internal damage, and provides test methods to quantify potential for gate valve internal damage, and provides test methods to quantify potential variations in actuator output thrust with loading condition. Key findings and their potential impact on MOV design and engineering application are summarized

  16. Predictive performance models and multiple task performance

    Science.gov (United States)

    Wickens, Christopher D.; Larish, Inge; Contorer, Aaron

    1989-01-01

    Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.

  17. Iowa calibration of MEPDG performance prediction models.

    Science.gov (United States)

    2013-06-01

    This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement : performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 : representative p...

  18. The Real World Significance of Performance Prediction

    Science.gov (United States)

    Pardos, Zachary A.; Wang, Qing Yang; Trivedi, Shubhendu

    2012-01-01

    In recent years, the educational data mining and user modeling communities have been aggressively introducing models for predicting student performance on external measures such as standardized tests as well as within-tutor performance. While these models have brought statistically reliable improvement to performance prediction, the real world…

  19. Calibration of PMIS pavement performance prediction models.

    Science.gov (United States)

    2012-02-01

    Improve the accuracy of TxDOTs existing pavement performance prediction models through calibrating these models using actual field data obtained from the Pavement Management Information System (PMIS). : Ensure logical performance superiority patte...

  20. Predicting Performance Ratings Using Motivational Antecedents

    National Research Council Canada - National Science Library

    Zazania, Michelle

    1998-01-01

    This research examined the role of motivation in predicting peer and trainer ratings of student performance and contrasted the relative importance of various antecedents for peer and trainer ratings...

  1. 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)

  2. A Comparison of Off-Grid-Pumped Hydro Storage and Grid-Tied Options for an IRSOFC-HAWT Power Generator

    Directory of Open Access Journals (Sweden)

    Mahdi Majidniya

    2017-01-01

    Full Text Available An Internal Reforming Solid Oxide Fuel Cell (IRSOFC is modeled thermodynamically; a Horizontal Axis Wind Turbine (HAWT is designed; the combined IRSOFC-HAWT system should create a reliable source of electricity for the demand of a village located in Manjil, Iran. The output power of HAWT is unstable, but by controlling the fuel rate for the IRSOFC it is possible to have a stable power output from the combined system. When the electricity demand is over the peak or the wind speed is low/unstable/significantly high, the generated power may not be sufficient. To solve this problem, two scenarios are considered: connecting to the grid or using a Pumped Hydro Storage (PHS. For the second scenario, the extra produced electricity is saved when the production is more than demand and can be used when the extra power is needed. The economic analysis is done based on the economic conditions in Iran. The results will show a period of return about 9.5 and 13 years with the levelized cost of electricity about 0.0747 and 0.0882 $/kWh for the first and second scenarios, respectively. Furthermore, effects of some parameters such as the electricity price and the real interest rate are discussed.

  3. A statistical model for predicting muscle performance

    Science.gov (United States)

    Byerly, Diane Leslie De Caix

    The objective of these studies was to develop a capability for predicting muscle performance and fatigue to be utilized for both space- and ground-based applications. To develop this predictive model, healthy test subjects performed a defined, repetitive dynamic exercise to failure using a Lordex spinal machine. Throughout the exercise, surface electromyography (SEMG) data were collected from the erector spinae using a Mega Electronics ME3000 muscle tester and surface electrodes placed on both sides of the back muscle. These data were analyzed using a 5th order Autoregressive (AR) model and statistical regression analysis. It was determined that an AR derived parameter, the mean average magnitude of AR poles, significantly correlated with the maximum number of repetitions (designated Rmax) that a test subject was able to perform. Using the mean average magnitude of AR poles, a test subject's performance to failure could be predicted as early as the sixth repetition of the exercise. This predictive model has the potential to provide a basis for improving post-space flight recovery, monitoring muscle atrophy in astronauts and assessing the effectiveness of countermeasures, monitoring astronaut performance and fatigue during Extravehicular Activity (EVA) operations, providing pre-flight assessment of the ability of an EVA crewmember to perform a given task, improving the design of training protocols and simulations for strenuous International Space Station assembly EVA, and enabling EVA work task sequences to be planned enhancing astronaut performance and safety. Potential ground-based, medical applications of the predictive model include monitoring muscle deterioration and performance resulting from illness, establishing safety guidelines in the industry for repetitive tasks, monitoring the stages of rehabilitation for muscle-related injuries sustained in sports and accidents, and enhancing athletic performance through improved training protocols while reducing

  4. Using Machine Learning to Predict Student Performance

    OpenAIRE

    Pojon, Murat

    2017-01-01

    This thesis examines the application of machine learning algorithms to predict whether a student will be successful or not. The specific focus of the thesis is the comparison of machine learning methods and feature engineering techniques in terms of how much they improve the prediction performance. Three different machine learning methods were used in this thesis. They are linear regression, decision trees, and naïve Bayes classification. Feature engineering, the process of modification ...

  5. Genomic Prediction of Barley Hybrid Performance

    Directory of Open Access Journals (Sweden)

    Norman Philipp

    2016-07-01

    Full Text Available Hybrid breeding in barley ( L. offers great opportunities to accelerate the rate of genetic improvement and to boost yield stability. A crucial requirement consists of the efficient selection of superior hybrid combinations. We used comprehensive phenotypic and genomic data from a commercial breeding program with the goal of examining the potential to predict the hybrid performances. The phenotypic data were comprised of replicated grain yield trials for 385 two-way and 408 three-way hybrids evaluated in up to 47 environments. The parental lines were genotyped using a 3k single nucleotide polymorphism (SNP array based on an Illumina Infinium assay. We implemented ridge regression best linear unbiased prediction modeling for additive and dominance effects and evaluated the prediction ability using five-fold cross validations. The prediction ability of hybrid performances based on general combining ability (GCA effects was moderate, amounting to 0.56 and 0.48 for two- and three-way hybrids, respectively. The potential of GCA-based hybrid prediction requires that both parental components have been evaluated in a hybrid background. This is not necessary for genomic prediction for which we also observed moderate cross-validated prediction abilities of 0.51 and 0.58 for two- and three-way hybrids, respectively. This exemplifies the potential of genomic prediction in hybrid barley. Interestingly, prediction ability using the two-way hybrids as training population and the three-way hybrids as test population or vice versa was low, presumably, because of the different genetic makeup of the parental source populations. Consequently, further research is needed to optimize genomic prediction approaches combining different source populations in barley.

  6. Modelling the predictive performance of credit scoring

    Directory of Open Access Journals (Sweden)

    Shi-Wei Shen

    2013-07-01

    Research purpose: The purpose of this empirical paper was to examine the predictive performance of credit scoring systems in Taiwan. Motivation for the study: Corporate lending remains a major business line for financial institutions. However, in light of the recent global financial crises, it has become extremely important for financial institutions to implement rigorous means of assessing clients seeking access to credit facilities. Research design, approach and method: Using a data sample of 10 349 observations drawn between 1992 and 2010, logistic regression models were utilised to examine the predictive performance of credit scoring systems. Main findings: A test of Goodness of fit demonstrated that credit scoring models that incorporated the Taiwan Corporate Credit Risk Index (TCRI, micro- and also macroeconomic variables possessed greater predictive power. This suggests that macroeconomic variables do have explanatory power for default credit risk. Practical/managerial implications: The originality in the study was that three models were developed to predict corporate firms’ defaults based on different microeconomic and macroeconomic factors such as the TCRI, asset growth rates, stock index and gross domestic product. Contribution/value-add: The study utilises different goodness of fits and receiver operator characteristics during the examination of the robustness of the predictive power of these factors.

  7. Plant corrosion: prediction of materials performance

    International Nuclear Information System (INIS)

    Strutt, J.E.; Nicholls, J.R.

    1987-01-01

    Seventeen papers have been compiled forming a book on computer-based approaches to corrosion prediction in a wide range of industrial sectors, including the chemical, petrochemical and power generation industries. Two papers have been selected and indexed separately. The first describes a system operating within BNFL's Reprocessing Division to predict materials performance in corrosive conditions to aid future plant design. The second describes the truncation of the distribution function of pit depths during high temperature oxidation of a 20Cr austenitic steel in the fuel cladding in AGR systems. (U.K.)

  8. Hanford grout: predicting long-term performance

    International Nuclear Information System (INIS)

    Sewart, G.H.; Mitchell, D.H.; Treat, R.L.; McMakin, A.H.

    1987-01-01

    Grouted disposal is being planned for the low-level portion of liquid radioactive wastes at the Hanford site in Washington state. The performance of the disposal system must be such that it will protect people and the environment for thousands of years after disposal. To predict whether a specific grout disposal system will comply with existing and foreseen regulations, a performance assessment (PA) is performed. Long-term PAs are conducted for a range of performance conditions. Performance assessment is an inexact science. Quantifying projected impacts is especially difficult when only scant data exist on the behavior of certain components of the disposal system over thousands of years. To develop defensible results, we are honing the models and obtaining experimental data. The combination of engineered features and PA refinements is being used to ensure that Hanford grout will meet its principal goal: to protect people and the environment in the future

  9. What predicts performance during clinical psychology training?

    OpenAIRE

    Scior, Katrina; Bradley, Caroline E; Potts, Henry W W; Woolf, Katherine; de C Williams, Amanda C

    2013-01-01

    Objectives While the question of who is likely to be selected for clinical psychology training has been studied, evidence on performance during training is scant. This study explored data from seven consecutive intakes of the UK's largest clinical psychology training course, aiming to identify what factors predict better or poorer outcomes. Design Longitudinal cross-sectional study using prospective and retrospective data. Method Characteristics at application were analysed in relation to a r...

  10. Predicting sample size required for classification performance

    Directory of Open Access Journals (Sweden)

    Figueroa Rosa L

    2012-02-01

    Full Text Available Abstract Background Supervised learning methods need annotated data in order to generate efficient models. Annotated data, however, is a relatively scarce resource and can be expensive to obtain. For both passive and active learning methods, there is a need to estimate the size of the annotated sample required to reach a performance target. Methods We designed and implemented a method that fits an inverse power law model to points of a given learning curve created using a small annotated training set. Fitting is carried out using nonlinear weighted least squares optimization. The fitted model is then used to predict the classifier's performance and confidence interval for larger sample sizes. For evaluation, the nonlinear weighted curve fitting method was applied to a set of learning curves generated using clinical text and waveform classification tasks with active and passive sampling methods, and predictions were validated using standard goodness of fit measures. As control we used an un-weighted fitting method. Results A total of 568 models were fitted and the model predictions were compared with the observed performances. Depending on the data set and sampling method, it took between 80 to 560 annotated samples to achieve mean average and root mean squared error below 0.01. Results also show that our weighted fitting method outperformed the baseline un-weighted method (p Conclusions This paper describes a simple and effective sample size prediction algorithm that conducts weighted fitting of learning curves. The algorithm outperformed an un-weighted algorithm described in previous literature. It can help researchers determine annotation sample size for supervised machine learning.

  11. Predicting the performance of fingerprint similarity searching.

    Science.gov (United States)

    Vogt, Martin; Bajorath, Jürgen

    2011-01-01

    Fingerprints are bit string representations of molecular structure that typically encode structural fragments, topological features, or pharmacophore patterns. Various fingerprint designs are utilized in virtual screening and their search performance essentially depends on three parameters: the nature of the fingerprint, the active compounds serving as reference molecules, and the composition of the screening database. It is of considerable interest and practical relevance to predict the performance of fingerprint similarity searching. A quantitative assessment of the potential that a fingerprint search might successfully retrieve active compounds, if available in the screening database, would substantially help to select the type of fingerprint most suitable for a given search problem. The method presented herein utilizes concepts from information theory to relate the fingerprint feature distributions of reference compounds to screening libraries. If these feature distributions do not sufficiently differ, active database compounds that are similar to reference molecules cannot be retrieved because they disappear in the "background." By quantifying the difference in feature distribution using the Kullback-Leibler divergence and relating the divergence to compound recovery rates obtained for different benchmark classes, fingerprint search performance can be quantitatively predicted.

  12. Comparing theories' performance in predicting violence.

    Science.gov (United States)

    Haas, Henriette; Cusson, Maurice

    2015-01-01

    The stakes of choosing the best theory as a basis for violence prevention and offender rehabilitation are high. However, no single theory of violence has ever been universally accepted by a majority of established researchers. Psychiatry, psychology and sociology are each subdivided into different schools relying upon different premises. All theories can produce empirical evidence for their validity, some of them stating the opposite of each other. Calculating different models with multivariate logistic regression on a dataset of N = 21,312 observations and ninety-two influences allowed a direct comparison of the performance of operationalizations of some of the most important schools. The psychopathology model ranked as the best model in terms of predicting violence right after the comprehensive interdisciplinary model. Next came the rational choice and lifestyle model and third the differential association and learning theory model. Other models namely the control theory model, the childhood-trauma model and the social conflict and reaction model turned out to have low sensitivities for predicting violence. Nevertheless, all models produced acceptable results in predictions of a non-violent outcome. Copyright © 2015. Published by Elsevier Ltd.

  13. Axisymmetric thrust-vectoring nozzle performance prediction

    International Nuclear Information System (INIS)

    Wilson, E. A.; Adler, D.; Bar-Yoseph, P.Z

    1998-01-01

    Throat-hinged geometrically variable converging-diverging thrust-vectoring nozzles directly affect the jet flow geometry and rotation angle at the nozzle exit as a function of the nozzle geometry, the nozzle pressure ratio and flight velocity. The consideration of nozzle divergence in the effective-geometric nozzle relation is theoretically considered here for the first time. In this study, an explicit calculation procedure is presented as a function of nozzle geometry at constant nozzle pressure ratio, zero velocity and altitude, and compared with experimental results in a civil thrust-vectoring scenario. This procedure may be used in dynamic thrust-vectoring nozzle design performance predictions or analysis for civil and military nozzles as well as in the definition of initial jet flow conditions in future numerical VSTOL/TV jet performance studies

  14. An insight into the separate flow and stall delay for HAWT

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Guohua; Shen, Xin; Zhu, Xiaocheng; Du, Zhaohui [School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China)

    2011-01-15

    The flow characteristics and the stall delay phenomenon of wind turbine rotor due to blade rotation in the steady state non-yawed conditions are investigated. An incompressible Reynolds-averaged Navier-Stokes solver is applied to carry out all the cases at different wind speeds from 5 m/s to 10 m/s with an interval of 1 m/s. CFD results turn out to agree well with experimental ones at incoming wind speeds below 10 m/s, though at 10 m/s some deviations exist due to the relative large flow separation and 3D spanwise flow over the suction surface of the blade. In the meanwhile, a lifting surface code with and without Du-Selig stall delay model is used to predict the power. A MATLAB code is developed to extract aerodynamic force coefficients from 3D CFD computations which are compared with the 2D airfoil wind tunnel experiment to demonstrate the stall delay and augmented lift phenomenon particularly at inboard span locations of the blade. The computational results are compared with the corrected value by the Du-Selig model and a lifting surface method derived data based on the measurements of the Unsteady Aerodynamic Experiment at the NASA Ames wind tunnel. (author)

  15. Predicting Expressive Dynamics in Piano Performances using Neural Networks

    NARCIS (Netherlands)

    van Herwaarden, Sam; Grachten, Maarten; de Haas, W. Bas

    2014-01-01

    This paper presents a model for predicting expressive accentuation in piano performances with neural networks. Using Restricted Boltzmann Machines (RBMs), features are learned from performance data, after which these features are used to predict performed loudness. During feature learning, data

  16. Predicting the Performance of Organic Corrosion Inhibitors

    Directory of Open Access Journals (Sweden)

    David A. Winkler

    2017-12-01

    Full Text Available The withdrawal of effective but toxic corrosion inhibitors has provided an impetus for the discovery of new, benign organic compounds to fill that role. Concurrently, developments in the high-throughput synthesis of organic compounds, the establishment of large libraries of available chemicals, accelerated corrosion inhibition testing technologies, and the increased capability of machine learning methods have made discovery of new corrosion inhibitors much faster and cheaper than it used to be. We summarize these technical developments in the corrosion inhibition field and describe how data-driven machine learning methods can generate models linking molecular properties to corrosion inhibition that can be used to predict the performance of materials not yet synthesized or tested. We briefly summarize the literature on quantitative structure–property relationships models of small organic molecule corrosion inhibitors. The success of these models provides a paradigm for rapid discovery of novel, effective corrosion inhibitors for a range of metals and alloys in diverse environments.

  17. Pavement Performance : Approaches Using Predictive Analytics

    Science.gov (United States)

    2018-03-23

    Acceptable pavement condition is paramount to road safety. Using predictive analytics techniques, this project attempted to develop models that provide an assessment of pavement condition based on an array of indictors that include pavement distress,...

  18. Stochastic Prediction of Ventilation System Performance

    DEFF Research Database (Denmark)

    Haghighat, F.; Brohus, Henrik; Frier, Christian

    The paper briefly reviews the existing techniques for predicting the airflow rate due to the random nature of forcing functions, e.g. wind speed. The effort is to establish the relationship between the statistics of the output of a system and the statistics of the random input variables and param......The paper briefly reviews the existing techniques for predicting the airflow rate due to the random nature of forcing functions, e.g. wind speed. The effort is to establish the relationship between the statistics of the output of a system and the statistics of the random input variables...

  19. System Predicts Critical Runway Performance Parameters

    Science.gov (United States)

    Millen, Ernest W.; Person, Lee H., Jr.

    1990-01-01

    Runway-navigation-monitor (RNM) and critical-distances-process electronic equipment designed to provide pilot with timely and reliable predictive navigation information relating to takeoff, landing and runway-turnoff operations. Enables pilot to make critical decisions about runway maneuvers with high confidence during emergencies. Utilizes ground-referenced position data only to drive purely navigational monitor system independent of statuses of systems in aircraft.

  20. Performance samples on academic tasks : improving prediction of academic performance

    NARCIS (Netherlands)

    Tanilon, Jenny

    2011-01-01

    This thesis is about the development and validation of a performance-based test, labeled as Performance Samples on academic tasks in Education and Child Studies (PSEd). PSEd is designed to identify students who are most able to perform the academic tasks involved in an Education and Child Studies

  1. Performance analysis and prediction in triathlon.

    Science.gov (United States)

    Ofoghi, Bahadorreza; Zeleznikow, John; Macmahon, Clare; Rehula, Jan; Dwyer, Dan B

    2016-01-01

    Performance in triathlon is dependent upon factors that include somatotype, physiological capacity, technical proficiency and race strategy. Given the multidisciplinary nature of triathlon and the interaction between each of the three race components, the identification of target split times that can be used to inform the design of training plans and race pacing strategies is a complex task. The present study uses machine learning techniques to analyse a large database of performances in Olympic distance triathlons (2008-2012). The analysis reveals patterns of performance in five components of triathlon (three race "legs" and two transitions) and the complex relationships between performance in each component and overall performance in a race. The results provide three perspectives on the relationship between performance in each component of triathlon and the final placing in a race. These perspectives allow the identification of target split times that are required to achieve a certain final place in a race and the opportunity to make evidence-based decisions about race tactics in order to optimise performance.

  2. Predicting Students' Performance in the Senior Secondary ...

    African Journals Online (AJOL)

    cce

    correlation design. ... the JSC examinations were a good predictor of performance at SSC ..... Table 12: Effects of the Independent Variables (JSCE 2000) on the .... JAMB Brochure, Abuja: Joint Admissions and Matriculation Examinations, 2-3.

  3. SYRUS: Understanding and Predicting Multitasking Performance

    National Research Council Canada - National Science Library

    Oswald, Frederick L; Hambrick, D. Z; Jones, L. A; Ghumman, Sonia S

    2007-01-01

    .... Fourth, related to the previous point, a summarization of our initial empirical work on multitasking, based on college-student participants who engaged in a computerized multitasking performance task...

  4. Dichotic listening performance predicts language comprehension.

    Science.gov (United States)

    Asbjørnsen, Arve E; Helland, Turid

    2006-05-01

    Dichotic listening performance is considered a reliable and valid procedure for the assessment of language lateralisation in the brain. However, the documentation of a relationship between language functions and dichotic listening performance is sparse, although it is accepted that dichotic listening measures language perception. In particular, language comprehension should show close correspondence to perception of language stimuli. In the present study, we tested samples of reading-impaired and normally achieving children between 10 and 13 years of age with tests of reading skills, language comprehension, and dichotic listening to consonant-vowel (CV) syllables. A high correlation between the language scores and the dichotic listening performance was expected. However, since the left ear score is believed to be an error when assessing language laterality, covariation was expected for the right ear scores only. In addition, directing attention to one ear input was believed to reduce the influence of random factors, and thus show a more concise estimate of left hemisphere language capacity. Thus, a stronger correlation between language comprehension skills and the dichotic listening performance when attending to the right ear was expected. The analyses yielded a positive correlation between the right ear score in DL and language comprehension, an effect that was stronger when attending to the right ear. The present results confirm the assumption that dichotic listening with CV syllables measures an aspect of language perception and language skills that is related to general language comprehension.

  5. Challenges of student selection: Predicting academic performance ...

    African Journals Online (AJOL)

    Finding accurate predictors of tertiary academic performance, specifically for disadvantaged students, is essential because of budget constraints and the need of the labour market to address employment equity. Increased retention, throughput and decreased dropout rates are vital. When making admission decisions, the

  6. Goal Setting and Expectancy Theory Predictions of Effort and Performance.

    Science.gov (United States)

    Dossett, Dennis L.; Luce, Helen E.

    Neither expectancy (VIE) theory nor goal setting alone are effective determinants of individual effort and task performance. To test the combined ability of VIE and goal setting to predict effort and performance, 44 real estate agents and their managers completed questionnaires. Quarterly income goals predicted managers' ratings of agents' effort,…

  7. Statistical and Machine Learning Models to Predict Programming Performance

    OpenAIRE

    Bergin, Susan

    2006-01-01

    This thesis details a longitudinal study on factors that influence introductory programming success and on the development of machine learning models to predict incoming student performance. Although numerous studies have developed models to predict programming success, the models struggled to achieve high accuracy in predicting the likely performance of incoming students. Our approach overcomes this by providing a machine learning technique, using a set of three significant...

  8. Predicting sales performance: Strengthening the personality – job performance linkage

    NARCIS (Netherlands)

    T.B. Sitser (Thomas)

    2014-01-01

    markdownabstract__Abstract__ Many organizations worldwide use personality measures to select applicants for sales jobs or to assess incumbent sales employees. In the present dissertation, consisting of four independent studies, five approaches to strengthen the personality-sales performance

  9. Does IQ Really Predict Job Performance?

    Science.gov (United States)

    Richardson, Ken; Norgate, Sarah H.

    2015-01-01

    IQ has played a prominent part in developmental and adult psychology for decades. In the absence of a clear theoretical model of internal cognitive functions, however, construct validity for IQ tests has always been difficult to establish. Test validity, therefore, has always been indirect, by correlating individual differences in test scores with what are assumed to be other criteria of intelligence. Job performance has, for several reasons, been one such criterion. Correlations of around 0.5 have been regularly cited as evidence of test validity, and as justification for the use of the tests in developmental studies, in educational and occupational selection and in research programs on sources of individual differences. Here, those correlations are examined together with the quality of the original data and the many corrections needed to arrive at them. It is concluded that considerable caution needs to be exercised in citing such correlations for test validation purposes. PMID:26405429

  10. Numerical modeling capabilities to predict repository performance

    International Nuclear Information System (INIS)

    1979-09-01

    This report presents a summary of current numerical modeling capabilities that are applicable to the design and performance evaluation of underground repositories for the storage of nuclear waste. The report includes codes that are available in-house, within Golder Associates and Lawrence Livermore Laboratories; as well as those that are generally available within the industry and universities. The first listing of programs are in-house codes in the subject areas of hydrology, solute transport, thermal and mechanical stress analysis, and structural geology. The second listing of programs are divided by subject into the following categories: site selection, structural geology, mine structural design, mine ventilation, hydrology, and mine design/construction/operation. These programs are not specifically designed for use in the design and evaluation of an underground repository for nuclear waste; but several or most of them may be so used

  11. Reliable predictions of waste performance in a geologic repository

    International Nuclear Information System (INIS)

    Pigford, T.H.; Chambre, P.L.

    1985-08-01

    Establishing reliable estimates of long-term performance of a waste repository requires emphasis upon valid theories to predict performance. Predicting rates that radionuclides are released from waste packages cannot rest upon empirical extrapolations of laboratory leach data. Reliable predictions can be based on simple bounding theoretical models, such as solubility-limited bulk-flow, if the assumed parameters are reliably known or defensibly conservative. Wherever possible, performance analysis should proceed beyond simple bounding calculations to obtain more realistic - and usually more favorable - estimates of expected performance. Desire for greater realism must be balanced against increasing uncertainties in prediction and loss of reliability. Theoretical predictions of release rate based on mass-transfer analysis are bounding and the theory can be verified. Postulated repository analogues to simulate laboratory leach experiments introduce arbitrary and fictitious repository parameters and are shown not to agree with well-established theory. 34 refs., 3 figs., 2 tabs

  12. Enhancing pavement performance prediction models for the Illinois Tollway System

    OpenAIRE

    Laxmikanth Premkumar; William R. Vavrik

    2016-01-01

    Accurate pavement performance prediction represents an important role in prioritizing future maintenance and rehabilitation needs, and predicting future pavement condition in a pavement management system. The Illinois State Toll Highway Authority (Tollway) with over 2000 lane miles of pavement utilizes the condition rating survey (CRS) methodology to rate pavement performance. Pavement performance models developed in the past for the Illinois Department of Transportation (IDOT) are used by th...

  13. Integrating geophysics and hydrology for reducing the uncertainty of groundwater model predictions and improved prediction performance

    DEFF Research Database (Denmark)

    Christensen, Nikolaj Kruse; Christensen, Steen; Ferre, Ty

    the integration of geophysical data in the construction of a groundwater model increases the prediction performance. We suggest that modelers should perform a hydrogeophysical “test-bench” analysis of the likely value of geophysics data for improving groundwater model prediction performance before actually...... and the resulting predictions can be compared with predictions from the ‘true’ model. By performing this analysis we expect to give the modeler insight into how the uncertainty of model-based prediction can be reduced.......A major purpose of groundwater modeling is to help decision-makers in efforts to manage the natural environment. Increasingly, it is recognized that both the predictions of interest and their associated uncertainties should be quantified to support robust decision making. In particular, decision...

  14. Performance prediction method for a multi-stage Knudsen pump

    Science.gov (United States)

    Kugimoto, K.; Hirota, Y.; Kizaki, Y.; Yamaguchi, H.; Niimi, T.

    2017-12-01

    In this study, the novel method to predict the performance of a multi-stage Knudsen pump is proposed. The performance prediction method is carried out in two steps numerically with the assistance of a simple experimental result. In the first step, the performance of a single-stage Knudsen pump was measured experimentally under various pressure conditions, and the relationship of the mass flow rate was obtained with respect to the average pressure between the inlet and outlet of the pump and the pressure difference between them. In the second step, the performance of a multi-stage pump was analyzed by a one-dimensional model derived from the mass conservation law. The performances predicted by the 1D-model of 1-stage, 2-stage, 3-stage, and 4-stage pumps were validated by the experimental results for the corresponding number of stages. It was concluded that the proposed prediction method works properly.

  15. Hybrid Corporate Performance Prediction Model Considering Technical Capability

    Directory of Open Access Journals (Sweden)

    Joonhyuck Lee

    2016-07-01

    Full Text Available Many studies have tried to predict corporate performance and stock prices to enhance investment profitability using qualitative approaches such as the Delphi method. However, developments in data processing technology and machine-learning algorithms have resulted in efforts to develop quantitative prediction models in various managerial subject areas. We propose a quantitative corporate performance prediction model that applies the support vector regression (SVR algorithm to solve the problem of the overfitting of training data and can be applied to regression problems. The proposed model optimizes the SVR training parameters based on the training data, using the genetic algorithm to achieve sustainable predictability in changeable markets and managerial environments. Technology-intensive companies represent an increasing share of the total economy. The performance and stock prices of these companies are affected by their financial standing and their technological capabilities. Therefore, we apply both financial indicators and technical indicators to establish the proposed prediction model. Here, we use time series data, including financial, patent, and corporate performance information of 44 electronic and IT companies. Then, we predict the performance of these companies as an empirical verification of the prediction performance of the proposed model.

  16. Essays on predictability of emerging markets growth and financial performance

    OpenAIRE

    Banegas, Maria Ayelen

    2011-01-01

    This dissertation seeks to better understand the underlying factors driving financial performance and economic activity in international markets. The first chapter "Predictability of Growth in Emerging Markets: Information in Financial Aggregates" tests for predictability of output growth in a panel of twenty-two emerging market economies. I use pooled panel data methods that control for endogeneity and persistence in the predictor variables to test the predictive power of a large set of fina...

  17. Mastery and Performance Goals Predict Epistemic and Relational Conflict Regulation

    Science.gov (United States)

    Darnon, Celine; Muller, Dominique; Schrager, Sheree M.; Pannuzzo, Nelly; Butera, Fabrizio

    2006-01-01

    The present research examines whether mastery and performance goals predict different ways of reacting to a sociocognitive conflict with another person over materials to be learned, an issue not yet addressed by the achievement goal literature. Results from 2 studies showed that mastery goals predicted epistemic conflict regulation (a conflict…

  18. Comparison and Prediction of Preclinical Students' Performance in ...

    African Journals Online (AJOL)

    olayemitoyin

    The data support the hypothesis that students who performed well in one discipline were likely to .... predict success in the clinical curriculum (Baciewicz,. 1990). Similarly ... the International Association of Medical Science. Educators. 17-20.

  19. Determining Mean Predicted Performance for Army Job Families

    National Research Council Canada - National Science Library

    Zeidner, Joseph

    2003-01-01

    The present study is designed to obtain mean predicted performance (MPPs) for the 9- and 17-job families, using composites based on 7 ASVAB tests, using a triple cross validation design permitting completely unbiased estimates of MPP...

  20. Predictive factors for masticatory performance in Duchenne muscular dystrophy

    NARCIS (Netherlands)

    Bruggen, H.W. van; Engel-Hoek, L. van den; Steenks, M.H.; Bronkhorst, E.M.; Creugers, N.H.; Groot, I.J.M. de; Kalaykova, S.

    2014-01-01

    Patients with Duchenne muscular dystrophy (DMD) report masticatory and swallowing problems. Such problems may cause complications such as choking, and feeling of food sticking in the throat. We investigated whether masticatory performance in DMD is objectively impaired, and explored predictive

  1. Predictive testing of performance of metals in HTR service environments

    International Nuclear Information System (INIS)

    Kondo, T.; Shindo, M.; Tamura, M.; Tsuji, H.; Kurata, Y.; Tsukada, T.

    1982-01-01

    Status of the material testing in simulated HTGR environment is reviewed with special attention focused on the methodology of the prediction of performance in long time. Importance of controlling effective chemical potentials relations in the material-environmental interface is stressed in regard of the complex inter-dependent kinetic relation between oxidation and carbon transport. Based on the recent experimental observations, proposals are made to establish some procedures for conservative prediction of the metal performance

  2. Prediction of Job Performance: Review of Military Studies

    Science.gov (United States)

    1982-03-01

    an assessment center to predict filed leadership performance of Army officers and NCOs. Proceedings of the 19th Annual Military Testing Association...C. Behaviors, results, and organizational effectiveness: The problem of criteria. In Dunnette, M. D. (Ed.), Handbook of Industrial and organizatin ...than for the Navy enlisted group. 30. Dyer, F. N., & Hlilligoss, R. Z. Using an assessment center to predict field leadership performance of Army

  3. Measuring and Predicting Sleep and Performance During Military Operations

    Science.gov (United States)

    2012-08-23

    strengths of this modeling approach is that accurate predictions of fatigue, performance, or alert- ness can be made from observed sleep timing...and, in which fatigue, performance, or alertness predictions are required prior to the task. Limitations of Current Models The strengths and...mean ± SD, 35.9 ± 1.2 hours), crews flew to Auckland , New Zealand, where another short layover was un- dertaken (23.6 ± 0.95 hours). A final flight

  4. Performance Prediction of Constrained Waveform Design for Adaptive Radar

    Science.gov (United States)

    2016-11-01

    the famous Woodward quote, having a ubiquitous feeling for all radar waveform design (and performance prediction) researchers , that is found at the end...discuss research that develops performance prediction models to quantify the impact on SINR when an amplitude constraint is placed on a radar waveform...optimize the radar perfor- mance for the particular scenario and tasks. There have also been several survey papers on various topics in waveform design for

  5. Multivariate performance reliability prediction in real-time

    International Nuclear Information System (INIS)

    Lu, S.; Lu, H.; Kolarik, W.J.

    2001-01-01

    This paper presents a technique for predicting system performance reliability in real-time considering multiple failure modes. The technique includes on-line multivariate monitoring and forecasting of selected performance measures and conditional performance reliability estimates. The performance measures across time are treated as a multivariate time series. A state-space approach is used to model the multivariate time series. Recursive forecasting is performed by adopting Kalman filtering. The predicted mean vectors and covariance matrix of performance measures are used for the assessment of system survival/reliability with respect to the conditional performance reliability. The technique and modeling protocol discussed in this paper provide a means to forecast and evaluate the performance of an individual system in a dynamic environment in real-time. The paper also presents an example to demonstrate the technique

  6. Comparison of Simple Versus Performance-Based Fall Prediction Models

    Directory of Open Access Journals (Sweden)

    Shekhar K. Gadkaree BS

    2015-05-01

    Full Text Available Objective: To compare the predictive ability of standard falls prediction models based on physical performance assessments with more parsimonious prediction models based on self-reported data. Design: We developed a series of fall prediction models progressing in complexity and compared area under the receiver operating characteristic curve (AUC across models. Setting: National Health and Aging Trends Study (NHATS, which surveyed a nationally representative sample of Medicare enrollees (age ≥65 at baseline (Round 1: 2011-2012 and 1-year follow-up (Round 2: 2012-2013. Participants: In all, 6,056 community-dwelling individuals participated in Rounds 1 and 2 of NHATS. Measurements: Primary outcomes were 1-year incidence of “ any fall ” and “ recurrent falls .” Prediction models were compared and validated in development and validation sets, respectively. Results: A prediction model that included demographic information, self-reported problems with balance and coordination, and previous fall history was the most parsimonious model that optimized AUC for both any fall (AUC = 0.69, 95% confidence interval [CI] = [0.67, 0.71] and recurrent falls (AUC = 0.77, 95% CI = [0.74, 0.79] in the development set. Physical performance testing provided a marginal additional predictive value. Conclusion: A simple clinical prediction model that does not include physical performance testing could facilitate routine, widespread falls risk screening in the ambulatory care setting.

  7. Comparisons of Faulting-Based Pavement Performance Prediction Models

    Directory of Open Access Journals (Sweden)

    Weina Wang

    2017-01-01

    Full Text Available Faulting prediction is the core of concrete pavement maintenance and design. Highway agencies are always faced with the problem of lower accuracy for the prediction which causes costly maintenance. Although many researchers have developed some performance prediction models, the accuracy of prediction has remained a challenge. This paper reviews performance prediction models and JPCP faulting models that have been used in past research. Then three models including multivariate nonlinear regression (MNLR model, artificial neural network (ANN model, and Markov Chain (MC model are tested and compared using a set of actual pavement survey data taken on interstate highway with varying design features, traffic, and climate data. It is found that MNLR model needs further recalibration, while the ANN model needs more data for training the network. MC model seems a good tool for pavement performance prediction when the data is limited, but it is based on visual inspections and not explicitly related to quantitative physical parameters. This paper then suggests that the further direction for developing the performance prediction model is incorporating the advantages and disadvantages of different models to obtain better accuracy.

  8. Predicting Document Retrieval System Performance: An Expected Precision Measure.

    Science.gov (United States)

    Losee, Robert M., Jr.

    1987-01-01

    Describes an expected precision (EP) measure designed to predict document retrieval performance. Highlights include decision theoretic models; precision and recall as measures of system performance; EP graphs; relevance feedback; and computing the retrieval status value of a document for two models, the Binary Independent Model and the Two Poisson…

  9. Predicting Academic Performance Based on Students' Blog and Microblog Posts

    NARCIS (Netherlands)

    Dascalu, Mihai; Popescu, Elvira; Becheru, Alexandru; Crossley, Scott; Trausan-Matu, Stefan

    2016-01-01

    This study investigates the degree to which textual complexity indices applied on students’ online contributions, corroborated with a longitudinal analysis performed on their weekly posts, predict academic performance. The source of student writing consists of blog and microblog posts, created in

  10. Performance reliability prediction for thermal aging based on kalman filtering

    International Nuclear Information System (INIS)

    Ren Shuhong; Wen Zhenhua; Xue Fei; Zhao Wensheng

    2015-01-01

    The performance reliability of the nuclear power plant main pipeline that failed due to thermal aging was studied by the performance degradation theory. Firstly, through the data obtained from the accelerated thermal aging experiments, the degradation process of the impact strength and fracture toughness of austenitic stainless steel material of the main pipeline was analyzed. The time-varying performance degradation model based on the state space method was built, and the performance trends were predicted by using Kalman filtering. Then, the multi-parameter and real-time performance reliability prediction model for the main pipeline thermal aging was developed by considering the correlation between the impact properties and fracture toughness, and by using the stochastic process theory. Thus, the thermal aging performance reliability and reliability life of the main pipeline with multi-parameter were obtained, which provides the scientific basis for the optimization management of the aging maintenance decision making for nuclear power plant main pipelines. (authors)

  11. The prediction of swimming performance in competition from behavioral information.

    Science.gov (United States)

    Rushall, B S; Leet, D

    1979-06-01

    The swimming performances of the Canadian Team at the 1976 Olympic Games were categorized as being improved or worse than previous best times in the events contested. The two groups had been previously assessed on the Psychological Inventories for Competitive Swimmers. A stepwise multiple-discriminant analysis of the inventory responses revealed that 13 test questions produced a perfect discrimination of group membership. The resultant discriminant functions for predicting performance classification were applied to the test responses of 157 swimmers at the 1977 Canadian Winter National Swimming Championships. Using the same performance classification criteria the accuracy of prediction was not better than chance in three of four sex by performance classifications. This yielded a failure to locate a set of behavioral factors which determine swimming performance improvements in elite competitive circumstances. The possibility of sets of factors which do not discriminate between performances in similar environments or between similar groups of swimmers was raised.

  12. Predicting Performance in Higher Education Using Proximal Predictors

    Science.gov (United States)

    Niessen, A. Susan M.; Meijer, Rob R.; Tendeiro, Jorge N.

    2016-01-01

    We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach, and specific skills tests in English and math. Test scores were used to predict academic achievement and progress after the first year, achievement in specific course types, enrollment, and dropout after the first year. All tests showed positive significant correlations with the criteria. The trial-studying test was consistently the best predictor in the admission procedure. We found no significant differences between the predictive validity of the trial-studying test and prior educational performance, and substantial shared explained variance between the two predictors. Only applicants with lower trial-studying scores were significantly less likely to enroll in the program. In conclusion, the trial-studying test yielded predictive validities similar to that of prior educational performance and possibly enabled self-selection. In admissions aimed at student-program fit, or in admissions in which past educational performance is difficult to use, a trial-studying test is a good instrument to predict academic performance. PMID:27073859

  13. Aqua/Aura Updated Inclination Adjust Maneuver Performance Prediction Model

    Science.gov (United States)

    Boone, Spencer

    2017-01-01

    This presentation will discuss the updated Inclination Adjust Maneuver (IAM) performance prediction model that was developed for Aqua and Aura following the 2017 IAM series. This updated model uses statistical regression methods to identify potential long-term trends in maneuver parameters, yielding improved predictions when re-planning past maneuvers. The presentation has been reviewed and approved by Eric Moyer, ESMO Deputy Project Manager.

  14. Adding propensity scores to pure prediction models fails to improve predictive performance

    Directory of Open Access Journals (Sweden)

    Amy S. Nowacki

    2013-08-01

    Full Text Available Background. Propensity score usage seems to be growing in popularity leading researchers to question the possible role of propensity scores in prediction modeling, despite the lack of a theoretical rationale. It is suspected that such requests are due to the lack of differentiation regarding the goals of predictive modeling versus causal inference modeling. Therefore, the purpose of this study is to formally examine the effect of propensity scores on predictive performance. Our hypothesis is that a multivariable regression model that adjusts for all covariates will perform as well as or better than those models utilizing propensity scores with respect to model discrimination and calibration.Methods. The most commonly encountered statistical scenarios for medical prediction (logistic and proportional hazards regression were used to investigate this research question. Random cross-validation was performed 500 times to correct for optimism. The multivariable regression models adjusting for all covariates were compared with models that included adjustment for or weighting with the propensity scores. The methods were compared based on three predictive performance measures: (1 concordance indices; (2 Brier scores; and (3 calibration curves.Results. Multivariable models adjusting for all covariates had the highest average concordance index, the lowest average Brier score, and the best calibration. Propensity score adjustment and inverse probability weighting models without adjustment for all covariates performed worse than full models and failed to improve predictive performance with full covariate adjustment.Conclusion. Propensity score techniques did not improve prediction performance measures beyond multivariable adjustment. Propensity scores are not recommended if the analytical goal is pure prediction modeling.

  15. Proactive Supply Chain Performance Management with Predictive Analytics

    Directory of Open Access Journals (Sweden)

    Nenad Stefanovic

    2014-01-01

    Full Text Available Today’s business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators. Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment.

  16. Proactive Supply Chain Performance Management with Predictive Analytics

    Science.gov (United States)

    Stefanovic, Nenad

    2014-01-01

    Today's business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI) model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators). Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment. PMID:25386605

  17. Proactive supply chain performance management with predictive analytics.

    Science.gov (United States)

    Stefanovic, Nenad

    2014-01-01

    Today's business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI) model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators). Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment.

  18. Enhancing pavement performance prediction models for the Illinois Tollway System

    Directory of Open Access Journals (Sweden)

    Laxmikanth Premkumar

    2016-01-01

    Full Text Available Accurate pavement performance prediction represents an important role in prioritizing future maintenance and rehabilitation needs, and predicting future pavement condition in a pavement management system. The Illinois State Toll Highway Authority (Tollway with over 2000 lane miles of pavement utilizes the condition rating survey (CRS methodology to rate pavement performance. Pavement performance models developed in the past for the Illinois Department of Transportation (IDOT are used by the Tollway to predict the future condition of its network. The model projects future CRS ratings based on pavement type, thickness, traffic, pavement age and current CRS rating. However, with time and inclusion of newer pavement types there was a need to calibrate the existing pavement performance models, as well as, develop models for newer pavement types.This study presents the results of calibrating the existing models, and developing new models for the various pavement types in the Illinois Tollway network. The predicted future condition of the pavements is used in estimating its remaining service life to failure, which is of immediate use in recommending future maintenance and rehabilitation requirements for the network. Keywords: Pavement performance models, Remaining life, Pavement management

  19. Predicting university performance in psychology: the role of previous performance and discipline-specific knowledge

    OpenAIRE

    Betts, LR; Elder, TJ; Hartley, J; Blurton, A

    2008-01-01

    Recent initiatives to enhance retention and widen participation ensure it is crucial to understand the factors that predict students' performance during their undergraduate degree. The present research used Structural Equation Modeling (SEM) to test three separate models that examined the extent to which British Psychology students' A-level entry qualifications predicted: (1) their performance in years 1-3 of their Psychology degree, and (2) their overall degree performance. Students' overall...

  20. The Search Performance Evaluation and Prediction in Exploratory Search

    OpenAIRE

    LIU, FEI

    2016-01-01

    The exploratory search for complex search tasks requires an effective search behavior model to evaluate and predict user search performance. Few studies have investigated the relationship between user search behavior and search performance in exploratory search. This research adopts a mixed approach combining search system development, user search experiment, search query log analysis, and multivariate regression analysis to resolve the knowledge gap. Through this study, it is shown that expl...

  1. Predictive Bias and Sensitivity in NRC Fuel Performance Codes

    Energy Technology Data Exchange (ETDEWEB)

    Geelhood, Kenneth J.; Luscher, Walter G.; Senor, David J.; Cunningham, Mitchel E.; Lanning, Donald D.; Adkins, Harold E.

    2009-10-01

    The latest versions of the fuel performance codes, FRAPCON-3 and FRAPTRAN were examined to determine if the codes are intrinsically conservative. Each individual model and type of code prediction was examined and compared to the data that was used to develop the model. In addition, a brief literature search was performed to determine if more recent data have become available since the original model development for model comparison.

  2. STUDENT ACADEMIC PERFORMANCE PREDICTION USING SUPPORT VECTOR MACHINE

    OpenAIRE

    S.A. Oloruntoba1 ,J.L.Akinode2

    2017-01-01

    This paper investigates the relationship between students' preadmission academic profile and final academic performance. Data Sample of students in one of the Federal Polytechnic in south West part of Nigeria was used. The preadmission academic profile used for this study is the 'O' level grades(terminal high school results).The academic performance is defined using student's Grade Point Average(GPA). This research focused on using data mining technique to develop a model for predicting stude...

  3. Children's biological responsivity to acute stress predicts concurrent cognitive performance.

    Science.gov (United States)

    Roos, Leslie E; Beauchamp, Kathryn G; Giuliano, Ryan; Zalewski, Maureen; Kim, Hyoun K; Fisher, Philip A

    2018-04-10

    Although prior research has characterized stress system reactivity (i.e. hypothalamic-pituitary-adrenal axis, HPAA; autonomic nervous system, ANS) in children, it has yet to examine the extent to which biological reactivity predicts concurrent goal-directed behavior. Here, we employed a stressor paradigm that allowed concurrent assessment of both stress system reactivity and performance on a speeded-response task to investigate the links between biological reactivity and cognitive function under stress. We further investigated gender as a moderator given previous research suggesting that the ANS may be particularly predictive of behavior in males due to gender differences in socialization. In a sociodemographically diverse sample of young children (N = 58, M age = 5.38 yrs; 44% male), individual differences in sociodemographic covariates (age, household income), HPAA (i.e. cortisol), and ANS (i.e. respiratory sinus arrhythmia, RSA, indexing the parasympathetic branch; pre-ejection period, PEP, indexing the sympathetic branch) function were assessed as predictors of cognitive performance under stress. We hypothesized that higher income, older age, and greater cortisol reactivity would be associated with better performance overall, and flexible ANS responsivity (i.e. RSA withdrawal, PEP shortening) would be predictive of performance for males. Overall, females performed better than males. Two-group SEM analyses suggest that, for males, greater RSA withdrawal to the stressor was associated with better performance, while for females, older age, higher income, and greater cortisol reactivity were associated with better performance. Results highlight the relevance of stress system reactivity to cognitive performance under stress. Future research is needed to further elucidate for whom and in what situations biological reactivity predicts goal-directed behavior.

  4. Analysis of Factors that Predict Clinical Performance in Medical School

    Science.gov (United States)

    White, Casey B.; Dey, Eric L.; Fantone, Joseph C.

    2009-01-01

    Academic achievement indices including GPAs and MCAT scores are used to predict the spectrum of medical student academic performance types. However, use of these measures ignores two changes influencing medical school admissions: student diversity and affirmative action, and an increased focus on communication skills. To determine if GPA and MCAT…

  5. Predicting Performance in Higher Education Using Proximal Predictors

    NARCIS (Netherlands)

    Niessen, A Susan M; Meijer, Rob R; Tendeiro, Jorge N

    2016-01-01

    We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach,

  6. Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

    DEFF Research Database (Denmark)

    Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

    2008-01-01

    This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...

  7. Image processing system performance prediction and product quality evaluation

    Science.gov (United States)

    Stein, E. K.; Hammill, H. B. (Principal Investigator)

    1976-01-01

    The author has identified the following significant results. A new technique for image processing system performance prediction and product quality evaluation was developed. It was entirely objective, quantitative, and general, and should prove useful in system design and quality control. The technique and its application to determination of quality control procedures for the Earth Resources Technology Satellite NASA Data Processing Facility are described.

  8. Predicting High-Power Performance in Professional Cyclists.

    Science.gov (United States)

    Sanders, Dajo; Heijboer, Mathieu; Akubat, Ibrahim; Meijer, Kenneth; Hesselink, Matthijs K

    2017-03-01

    To assess if short-duration (5 to ~300 s) high-power performance can accurately be predicted using the anaerobic power reserve (APR) model in professional cyclists. Data from 4 professional cyclists from a World Tour cycling team were used. Using the maximal aerobic power, sprint peak power output, and an exponential constant describing the decrement in power over time, a power-duration relationship was established for each participant. To test the predictive accuracy of the model, several all-out field trials of different durations were performed by each cyclist. The power output achieved during the all-out trials was compared with the predicted power output by the APR model. The power output predicted by the model showed very large to nearly perfect correlations to the actual power output obtained during the all-out trials for each cyclist (r = .88 ± .21, .92 ± .17, .95 ± .13, and .97 ± .09). Power output during the all-out trials remained within an average of 6.6% (53 W) of the predicted power output by the model. This preliminary pilot study presents 4 case studies on the applicability of the APR model in professional cyclists using a field-based approach. The decrement in all-out performance during high-intensity exercise seems to conform to a general relationship with a single exponential-decay model describing the decrement in power vs increasing duration. These results are in line with previous studies using the APR model to predict performance during brief all-out trials. Future research should evaluate the APR model with a larger sample size of elite cyclists.

  9. Entity versus incremental theories predict older adults' memory performance.

    Science.gov (United States)

    Plaks, Jason E; Chasteen, Alison L

    2013-12-01

    The authors examined whether older adults' implicit theories regarding the modifiability of memory in particular (Studies 1 and 3) and abilities in general (Study 2) would predict memory performance. In Study 1, individual differences in older adults' endorsement of the "entity theory" (a belief that one's ability is fixed) or "incremental theory" (a belief that one's ability is malleable) of memory were measured using a version of the Implicit Theories Measure (Dweck, 1999). Memory performance was assessed with a free-recall task. Results indicated that the higher the endorsement of the incremental theory, the better the free recall. In Study 2, older and younger adults' theories were measured using a more general version of the Implicit Theories Measure that focused on the modifiability of abilities in general. Again, for older adults, the higher the incremental endorsement, the better the free recall. Moreover, as predicted, implicit theories did not predict younger adults' memory performance. In Study 3, participants read mock news articles reporting evidence in favor of either the entity or incremental theory. Those in the incremental condition outperformed those in the entity condition on reading span and free-recall tasks. These effects were mediated by pretask worry such that, for those in the entity condition, higher worry was associated with lower performance. Taken together, these studies suggest that variation in entity versus incremental endorsement represents a key predictor of older adults' memory performance. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  10. Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

    DEFF Research Database (Denmark)

    Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

    2008-01-01

    This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...... reference tracking and disturbance rejection in an economically optimal way. The performance function is chosen as a mixture of the `1-norm and a linear weighting to model the economics of the system. Simulations show a significant improvement of the performance of the MPC compared to the current...

  11. Calibration between Undergraduate Students' Prediction of and Actual Performance: The Role of Gender and Performance Attributions

    Science.gov (United States)

    Gutierrez, Antonio P.; Price, Addison F.

    2017-01-01

    This study investigated changes in male and female students' prediction and postdiction calibration accuracy and bias scores, and the predictive effects of explanatory styles on these variables beyond gender. Seventy undergraduate students rated their confidence in performance before and after a 40-item exam. There was an improvement in students'…

  12. Predictive Measures of Locomotor Performance on an Unstable Walking Surface

    Science.gov (United States)

    Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Caldwell, E. E.; Batson, C. D.; De Dios, Y. E.; Gadd, N. E.; Goel, R.; Wood, S. J.; Cohen, H. S.; hide

    2016-01-01

    Locomotion requires integration of visual, vestibular, and somatosensory information to produce the appropriate motor output to control movement. The degree to which these sensory inputs are weighted and reorganized in discordant sensory environments varies by individual and may be predictive of the ability to adapt to novel environments. The goals of this project are to: 1) develop a set of predictive measures capable of identifying individual differences in sensorimotor adaptability, and 2) use this information to inform the design of training countermeasures designed to enhance the ability of astronauts to adapt to gravitational transitions improving balance and locomotor performance after a Mars landing and enhancing egress capability after a landing on Earth.

  13. Predicting Performance on MOOC Assessments using Multi-Regression Models

    OpenAIRE

    Ren, Zhiyun; Rangwala, Huzefa; Johri, Aditya

    2016-01-01

    The past few years has seen the rapid growth of data min- ing approaches for the analysis of data obtained from Mas- sive Open Online Courses (MOOCs). The objectives of this study are to develop approaches to predict the scores a stu- dent may achieve on a given grade-related assessment based on information, considered as prior performance or prior ac- tivity in the course. We develop a personalized linear mul- tiple regression (PLMR) model to predict the grade for a student, prior to attempt...

  14. Real-time Tsunami Inundation Prediction Using High Performance Computers

    Science.gov (United States)

    Oishi, Y.; Imamura, F.; Sugawara, D.

    2014-12-01

    Recently off-shore tsunami observation stations based on cabled ocean bottom pressure gauges are actively being deployed especially in Japan. These cabled systems are designed to provide real-time tsunami data before tsunamis reach coastlines for disaster mitigation purposes. To receive real benefits of these observations, real-time analysis techniques to make an effective use of these data are necessary. A representative study was made by Tsushima et al. (2009) that proposed a method to provide instant tsunami source prediction based on achieving tsunami waveform data. As time passes, the prediction is improved by using updated waveform data. After a tsunami source is predicted, tsunami waveforms are synthesized from pre-computed tsunami Green functions of linear long wave equations. Tsushima et al. (2014) updated the method by combining the tsunami waveform inversion with an instant inversion of coseismic crustal deformation and improved the prediction accuracy and speed in the early stages. For disaster mitigation purposes, real-time predictions of tsunami inundation are also important. In this study, we discuss the possibility of real-time tsunami inundation predictions, which require faster-than-real-time tsunami inundation simulation in addition to instant tsunami source analysis. Although the computational amount is large to solve non-linear shallow water equations for inundation predictions, it has become executable through the recent developments of high performance computing technologies. We conducted parallel computations of tsunami inundation and achieved 6.0 TFLOPS by using 19,000 CPU cores. We employed a leap-frog finite difference method with nested staggered grids of which resolution range from 405 m to 5 m. The resolution ratio of each nested domain was 1/3. Total number of grid points were 13 million, and the time step was 0.1 seconds. Tsunami sources of 2011 Tohoku-oki earthquake were tested. The inundation prediction up to 2 hours after the

  15. A comparison of SAR ATR performance with information theoretic predictions

    Science.gov (United States)

    Blacknell, David

    2003-09-01

    Performance assessment of automatic target detection and recognition algorithms for SAR systems (or indeed any other sensors) is essential if the military utility of the system / algorithm mix is to be quantified. This is a relatively straightforward task if extensive trials data from an existing system is used. However, a crucial requirement is to assess the potential performance of novel systems as a guide to procurement decisions. This task is no longer straightforward since a hypothetical system cannot provide experimental trials data. QinetiQ has previously developed a theoretical technique for classification algorithm performance assessment based on information theory. The purpose of the study presented here has been to validate this approach. To this end, experimental SAR imagery of targets has been collected using the QinetiQ Enhanced Surveillance Radar to allow algorithm performance assessments as a number of parameters are varied. In particular, performance comparisons can be made for (i) resolutions up to 0.1m, (ii) single channel versus polarimetric (iii) targets in the open versus targets in scrubland and (iv) use versus non-use of camouflage. The change in performance as these parameters are varied has been quantified from the experimental imagery whilst the information theoretic approach has been used to predict the expected variation of performance with parameter value. A comparison of these measured and predicted assessments has revealed the strengths and weaknesses of the theoretical technique as will be discussed in the paper.

  16. Prediction of Tennis Performance in Junior Elite Tennis Players

    Directory of Open Access Journals (Sweden)

    Tamara Kramer, Barbara C.H. Huijgen, Marije T. Elferink-Gemser, Chris Visscher

    2017-03-01

    Full Text Available Predicting current and future tennis performance can lead to improving the development of junior tennis players. The aim of this study is to investigate whether age, maturation, or physical fitness in junior elite tennis players in U13 can explain current and future tennis performance. The value of current tennis performance for future tennis performance is also investigated. A total of 86 junior elite tennis players (boys, n = 44; girls, n = 42 U13 (aged: 12.5 ± 0.3 years, and followed to U16, took part in this study. All players were top-30 ranked on the Dutch national ranking list at U13, and top-50 at U16. Age, maturation, and physical fitness, were measured at U13. A principal component analysis was used to extract four physical components from eight tests (medicine ball throwing overhead and reverse, ball throwing, SJ, CMJas, Sprint 5 and 10 meter, and the spider test. The possible relationship of age, maturation, and the physical components; “upper body power”, “lower body power”, “speed”, and “agility” with tennis performance at U13 and U16 was analyzed. Tennis performance was measured by using the ranking position on the Dutch national ranking list at U13 and U16. Regression analyses were conducted based on correlations between variables and tennis performance for boys and girls, separately. In boys U13, positive correlations were found between upper body power and tennis performance (R2 is 25%. In girls, positive correlations between maturation and lower body power with tennis performance were found at U13. Early maturing players were associated with a better tennis performance (R2 is 15%. In girls U16, only maturation correlated with tennis performance (R2 is 13%; later-maturing girls at U13 had better tennis performances at U16. Measuring junior elite tennis players at U13 is important for monitoring their development. These measurements did not predict future tennis performance of junior elite tennis players three

  17. Development of a Mobile Application for Building Energy Prediction Using Performance Prediction Model

    Directory of Open Access Journals (Sweden)

    Yu-Ri Kim

    2016-03-01

    Full Text Available Recently, the Korean government has enforced disclosure of building energy performance, so that such information can help owners and prospective buyers to make suitable investment plans. Such a building energy performance policy of the government makes it mandatory for the building owners to obtain engineering audits and thereby evaluate the energy performance levels of their buildings. However, to calculate energy performance levels (i.e., asset rating methodology, a qualified expert needs to have access to at least the full project documentation and/or conduct an on-site inspection of the buildings. Energy performance certification costs a lot of time and money. Moreover, the database of certified buildings is still actually quite small. A need, therefore, is increasing for a simplified and user-friendly energy performance prediction tool for non-specialists. Also, a database which allows building owners and users to compare best practices is required. In this regard, the current study developed a simplified performance prediction model through experimental design, energy simulations and ANOVA (analysis of variance. Furthermore, using the new prediction model, a related mobile application was also developed.

  18. When predictions take control: The effect of task predictions on task switching performance

    Directory of Open Access Journals (Sweden)

    Wout eDuthoo

    2012-08-01

    Full Text Available In this paper, we aimed to investigate the role of self-generated predictions in the flexible control of behaviour. Therefore, we ran a task switching experiment in which participants were asked to try to predict the upcoming task in three conditions varying in switch rate (30%, 50% and 70%. Irrespective of their predictions, the colour of the target indicated which task participants had to perform. In line with previous studies (Mayr, 2006; Monsell & Mizon, 2006, the switch cost was attenuated as the switch rate increased. Importantly, a clear task repetition bias was found in all conditions, yet the task repetition prediction rate dropped from 78% over 66% to 49% with increasing switch probability in the three conditions. Irrespective of condition, the switch cost was strongly reduced in expectation of a task alternation compared to the cost of an unexpected task alternation following repetition predictions. Hence, our data suggest that the reduction in the switch cost with increasing switch probability is caused by a diminished expectancy for the task to repeat. Taken together, this paper highlights the importance of predictions in the flexible control of behaviour, and suggests a crucial role for task repetition expectancy in the context-sensitive adjusting of task switching performance.

  19. Genomic Prediction of Testcross Performance in Canola (Brassica napus)

    Science.gov (United States)

    Jan, Habib U.; Abbadi, Amine; Lücke, Sophie; Nichols, Richard A.; Snowdon, Rod J.

    2016-01-01

    Genomic selection (GS) is a modern breeding approach where genome-wide single-nucleotide polymorphism (SNP) marker profiles are simultaneously used to estimate performance of untested genotypes. In this study, the potential of genomic selection methods to predict testcross performance for hybrid canola breeding was applied for various agronomic traits based on genome-wide marker profiles. A total of 475 genetically diverse spring-type canola pollinator lines were genotyped at 24,403 single-copy, genome-wide SNP loci. In parallel, the 950 F1 testcross combinations between the pollinators and two representative testers were evaluated for a number of important agronomic traits including seedling emergence, days to flowering, lodging, oil yield and seed yield along with essential seed quality characters including seed oil content and seed glucosinolate content. A ridge-regression best linear unbiased prediction (RR-BLUP) model was applied in combination with 500 cross-validations for each trait to predict testcross performance, both across the whole population as well as within individual subpopulations or clusters, based solely on SNP profiles. Subpopulations were determined using multidimensional scaling and K-means clustering. Genomic prediction accuracy across the whole population was highest for seed oil content (0.81) followed by oil yield (0.75) and lowest for seedling emergence (0.29). For seed yieId, seed glucosinolate, lodging resistance and days to onset of flowering (DTF), prediction accuracies were 0.45, 0.61, 0.39 and 0.56, respectively. Prediction accuracies could be increased for some traits by treating subpopulations separately; a strategy which only led to moderate improvements for some traits with low heritability, like seedling emergence. No useful or consistent increase in accuracy was obtained by inclusion of a population substructure covariate in the model. Testcross performance prediction using genome-wide SNP markers shows considerable

  20. Modeling and prediction of flotation performance using support vector regression

    Directory of Open Access Journals (Sweden)

    Despotović Vladimir

    2017-01-01

    Full Text Available Continuous efforts have been made in recent year to improve the process of paper recycling, as it is of critical importance for saving the wood, water and energy resources. Flotation deinking is considered to be one of the key methods for separation of ink particles from the cellulose fibres. Attempts to model the flotation deinking process have often resulted in complex models that are difficult to implement and use. In this paper a model for prediction of flotation performance based on Support Vector Regression (SVR, is presented. Representative data samples were created in laboratory, under a variety of practical control variables for the flotation deinking process, including different reagents, pH values and flotation residence time. Predictive model was created that was trained on these data samples, and the flotation performance was assessed showing that Support Vector Regression is a promising method even when dataset used for training the model is limited.

  1. Locomotion With Loads: Practical Techniques for Predicting Performance Outcomes

    Science.gov (United States)

    2015-05-01

    Metabolic energy consumption as a function of speed and body size in birds and mammals. J Exp Biol. 97, 1-21. Weyand, P., Smith, B., Puyau, M. and...height, weight (including load), speed, and grade algorithms proposed will allow walking metabolic rates to be predicted to within 6.0 and 12.0% in...gait, metabolism , performance, load carriage 16. SECURITY CLASSIFICATION OF: Unclassified 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME

  2. Decline Curve Based Models for Predicting Natural Gas Well Performance

    OpenAIRE

    Kamari, Arash; Mohammadi, Amir H.; Lee, Moonyong; Mahmood, Tariq; Bahadori, Alireza

    2016-01-01

    The productivity of a gas well declines over its production life as cannot cover economic policies. To overcome such problems, the production performance of gas wells should be predicted by applying reliable methods to analyse the decline trend. Therefore, reliable models are developed in this study on the basis of powerful artificial intelligence techniques viz. the artificial neural network (ANN) modelling strategy, least square support vector machine (LSSVM) approach, adaptive neuro-fuzzy ...

  3. Sexual victimization history predicts academic performance in college women.

    Science.gov (United States)

    Baker, Majel R; Frazier, Patricia A; Greer, Christiaan; Paulsen, Jacob A; Howard, Kelli; Meredith, Liza N; Anders, Samantha L; Shallcross, Sandra L

    2016-11-01

    College women frequently report having experienced sexual victimization (SV) in their lifetime, including child sexual abuse and adolescent/adult sexual assault. Although the harmful mental health sequelae of SV have been extensively studied, recent research suggests that SV is also a risk factor for poorer college academic performance. The current studies examined whether exposure to SV uniquely predicted poorer college academic performance, even beyond contributions from three well-established predictors of academic performance: high school rank, composite standardized test scores (i.e., American College Testing [ACT]), and conscientiousness. Study 1 analyzed longitudinal data from a sample of female college students (N = 192) who were assessed at the beginning and end of one semester. SV predicted poorer cumulative end-of-semester grade point average (GPA) while controlling for well-established predictors of academic performance. Study 2 replicated these findings in a second longitudinal study of female college students (N = 390) and extended the analyses to include follow-up data on the freshmen and sophomore students (n = 206) 4 years later. SV predicted students' GPA in their final term at the university above the contributions of well-established academic predictors, and it was the only factor related to leaving college. These findings highlight the importance of expanding the scope of outcomes of SV to include academic performance, and they underscore the need to assess SV and other adverse experiences on college campuses to target students who may be at risk of poor performance or leaving college. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  4. Predicting work Performance through selection interview ratings and Psychological assessment

    Directory of Open Access Journals (Sweden)

    Liziwe Nzama

    2008-11-01

    Full Text Available The aim of the study was to establish whether selection interviews used in conjunction with psychological assessments of personality traits and cognitive functioning contribute to predicting work performance. The sample consisted of 102 managers who were appointed recently in a retail organisation. The independent variables were selection interview ratings obtained on the basis of structured competency-based interview schedules by interviewing panels, fve broad dimensions of personality defned by the Five Factor Model as measured by the 15 Factor Questionnaire (15FQ+, and cognitive processing variables (current level of work, potential level of work, and 12 processing competencies measured by the Cognitive Process Profle (CPP. Work performance was measured through annual performance ratings that focused on measurable outputs of performance objectives. Only two predictor variables correlated statistically signifcantly with the criterion variable, namely interview ratings (r = 0.31 and CPP Verbal Abstraction (r = 0.34. Following multiple regression, only these variables contributed signifcantly to predicting work performance, but only 17.8% of the variance of the criterion was accounted for.

  5. Predicting BCI subject performance using probabilistic spatio-temporal filters.

    Directory of Open Access Journals (Sweden)

    Heung-Il Suk

    Full Text Available Recently, spatio-temporal filtering to enhance decoding for Brain-Computer-Interfacing (BCI has become increasingly popular. In this work, we discuss a novel, fully Bayesian-and thereby probabilistic-framework, called Bayesian Spatio-Spectral Filter Optimization (BSSFO and apply it to a large data set of 80 non-invasive EEG-based BCI experiments. Across the full frequency range, the BSSFO framework allows to analyze which spatio-spectral parameters are common and which ones differ across the subject population. As expected, large variability of brain rhythms is observed between subjects. We have clustered subjects according to similarities in their corresponding spectral characteristics from the BSSFO model, which is found to reflect their BCI performances well. In BCI, a considerable percentage of subjects is unable to use a BCI for communication, due to their missing ability to modulate their brain rhythms-a phenomenon sometimes denoted as BCI-illiteracy or inability. Predicting individual subjects' performance preceding the actual, time-consuming BCI-experiment enhances the usage of BCIs, e.g., by detecting users with BCI inability. This work additionally contributes by using the novel BSSFO method to predict the BCI-performance using only 2 minutes and 3 channels of resting-state EEG data recorded before the actual BCI-experiment. Specifically, by grouping the individual frequency characteristics we have nicely classified them into the subject 'prototypes' (like μ - or β -rhythm type subjects or users without ability to communicate with a BCI, and then by further building a linear regression model based on the grouping we could predict subjects' performance with the maximum correlation coefficient of 0.581 with the performance later seen in the actual BCI session.

  6. Cognitive load predicts point-of-care ultrasound simulator performance.

    Science.gov (United States)

    Aldekhyl, Sara; Cavalcanti, Rodrigo B; Naismith, Laura M

    2018-02-01

    The ability to maintain good performance with low cognitive load is an important marker of expertise. Incorporating cognitive load measurements in the context of simulation training may help to inform judgements of competence. This exploratory study investigated relationships between demographic markers of expertise, cognitive load measures, and simulator performance in the context of point-of-care ultrasonography. Twenty-nine medical trainees and clinicians at the University of Toronto with a range of clinical ultrasound experience were recruited. Participants answered a demographic questionnaire then used an ultrasound simulator to perform targeted scanning tasks based on clinical vignettes. Participants were scored on their ability to both acquire and interpret ultrasound images. Cognitive load measures included participant self-report, eye-based physiological indices, and behavioural measures. Data were analyzed using a multilevel linear modelling approach, wherein observations were clustered by participants. Experienced participants outperformed novice participants on ultrasound image acquisition. Ultrasound image interpretation was comparable between the two groups. Ultrasound image acquisition performance was predicted by level of training, prior ultrasound training, and cognitive load. There was significant convergence between cognitive load measurement techniques. A marginal model of ultrasound image acquisition performance including prior ultrasound training and cognitive load as fixed effects provided the best overall fit for the observed data. In this proof-of-principle study, the combination of demographic and cognitive load measures provided more sensitive metrics to predict ultrasound simulator performance. Performance assessments which include cognitive load can help differentiate between levels of expertise in simulation environments, and may serve as better predictors of skill transfer to clinical practice.

  7. Decline curve based models for predicting natural gas well performance

    Directory of Open Access Journals (Sweden)

    Arash Kamari

    2017-06-01

    Full Text Available The productivity of a gas well declines over its production life as cannot cover economic policies. To overcome such problems, the production performance of gas wells should be predicted by applying reliable methods to analyse the decline trend. Therefore, reliable models are developed in this study on the basis of powerful artificial intelligence techniques viz. the artificial neural network (ANN modelling strategy, least square support vector machine (LSSVM approach, adaptive neuro-fuzzy inference system (ANFIS, and decision tree (DT method for the prediction of cumulative gas production as well as initial decline rate multiplied by time as a function of the Arps' decline curve exponent and ratio of initial gas flow rate over total gas flow rate. It was concluded that the results obtained based on the models developed in current study are in satisfactory agreement with the actual gas well production data. Furthermore, the results of comparative study performed demonstrates that the LSSVM strategy is superior to the other models investigated for the prediction of both cumulative gas production, and initial decline rate multiplied by time.

  8. Predicting introductory programming performance: A multi-institutional multivariate study

    Science.gov (United States)

    Bergin, Susan; Reilly, Ronan

    2006-12-01

    A model for predicting student performance on introductory programming modules is presented. The model uses attributes identified in a study carried out at four third-level institutions in the Republic of Ireland. Four instruments were used to collect the data and over 25 attributes were examined. A data reduction technique was applied and a logistic regression model using 10-fold stratified cross validation was developed. The model used three attributes: Leaving Certificate Mathematics result (final mathematics examination at second level), number of hours playing computer games while taking the module and programming self-esteem. Prediction success was significant with 80% of students correctly classified. The model also works well on a per-institution level. A discussion on the implications of the model is provided and future work is outlined.

  9. Numerical simulation of a twin screw expander for performance prediction

    Science.gov (United States)

    Papes, Iva; Degroote, Joris; Vierendeels, Jan

    2015-08-01

    With the increasing use of twin screw expanders in waste heat recovery applications, the performance prediction of these machines plays an important role. This paper presents a mathematical model for calculating the performance of a twin screw expander. From the mass and energy conservation laws, differential equations are derived which are then solved together with the appropriate Equation of State in the instantaneous control volumes. Different flow processes that occur inside the screw expander such as filling (accompanied by a substantial pressure loss) and leakage flows through the clearances are accounted for in the model. The mathematical model employs all geometrical parameters such as chamber volume, suction and leakage areas. With R245fa as working fluid, the Aungier Redlich-Kwong Equation of State has been used in order to include real gas effects. To calculate the mass flow rates through the leakage paths formed inside the screw expander, flow coefficients are considered as constant and they are derived from 3D Computational Fluid Dynamic calculations at given working conditions and applied to all other working conditions. The outcome of the mathematical model is the P-V indicator diagram which is compared to CFD results of the same twin screw expander. Since CFD calculations require significant computational time, developed mathematical model can be used for the faster performance prediction.

  10. Neighborhood Integration and Connectivity Predict Cognitive Performance and Decline

    Directory of Open Access Journals (Sweden)

    Amber Watts PhD

    2015-08-01

    Full Text Available Objective: Neighborhood characteristics may be important for promoting walking, but little research has focused on older adults, especially those with cognitive impairment. We evaluated the role of neighborhood characteristics on cognitive function and decline over a 2-year period adjusting for measures of walking. Method: In a study of 64 older adults with and without mild Alzheimer’s disease (AD, we evaluated neighborhood integration and connectivity using geographical information systems data and space syntax analysis. In multiple regression analyses, we used these characteristics to predict 2-year declines in factor analytically derived cognitive scores (attention, verbal memory, mental status adjusting for age, sex, education, and self-reported walking. Results : Neighborhood integration and connectivity predicted cognitive performance at baseline, and changes in cognitive performance over 2 years. The relationships between neighborhood characteristics and cognitive performance were not fully explained by self-reported walking. Discussion : Clearer definitions of specific neighborhood characteristics associated with walkability are needed to better understand the mechanisms by which neighborhoods may impact cognitive outcomes. These results have implications for measuring neighborhood characteristics, design and maintenance of living spaces, and interventions to increase walking among older adults. We offer suggestions for future research measuring neighborhood characteristics and cognitive function.

  11. Prediction of performance and evaluation of flexible pavement rehabilitation strategies

    Directory of Open Access Journals (Sweden)

    Kang-Won Wayne Lee

    2017-04-01

    Full Text Available Five test sections with different additives and strategies were established to rehabilitate a State-maintained highway more effectively in Rhode Island (RI: control, calcium chloride, asphalt emulsion, Portland cement and geogrid. Resilient moduli of subgrade soils and subbase materials before and after full depth rehabilitation were employed as input parameters to predict the performance of pavement structures using AASHTOWare Pavement ME Design (Pavement ME software in terms of rutting, cracking and roughness. It was attempted to use Level 1 input (which includes traffic full spectrum data, climate data and structural layer properties for Pavement ME. Traffic data was obtained from a Weigh-in-Motion (WIM instrument and Providence station was used for collecting climatic data. Volumetric properties, dynamic modulus and creep compliance were used as input parameters for 19 mm (0.75 in. warm mix asphalt (WMA base and 12.5 mm (0.5 in. WMA surface layer. The results indicated that all test sections observed AC top-down (longitudinal cracking except Portland cement section which passed for all criteria. The order in terms of performance (best to worst for all test sections by Pavement ME was Portland cement, calcium chloride, control, geogrid, and asphalt emulsion. It was also observed that all test sections passed for both bottom up and top down fatigue cracking by increasing thickness of either of the two top asphalt layers. Test sections with five different base/subbase materials were evaluated in last two years through visual condition survey and measurements of deflection and roughness to confirm the prediction, but there was no serious distress and roughness. Thus these experiments allowed selecting the best rehabilitation/reconstruction techniques for the particular and/or similar highway, and a framework was formulated to select an optimal technique and/or strategy for future rehabilitation/reconstruction projects. Finally, guidelines for

  12. Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

    Science.gov (United States)

    Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

    2014-01-01

    This paper presents recent thermal model results of the Advanced Stirling Radioisotope Generator (ASRG). The three-dimensional (3D) ASRG thermal power model was built using the Thermal Desktop(trademark) thermal analyzer. The model was correlated with ASRG engineering unit test data and ASRG flight unit predictions from Lockheed Martin's (LM's) I-deas(trademark) TMG thermal model. The auxiliary cooling system (ACS) of the ASRG is also included in the ASRG thermal model. The ACS is designed to remove waste heat from the ASRG so that it can be used to heat spacecraft components. The performance of the ACS is reported under nominal conditions and during a Venus flyby scenario. The results for the nominal case are validated with data from Lockheed Martin. Transient thermal analysis results of ASRG for a Venus flyby with a representative trajectory are also presented. In addition, model results of an ASRG mounted on a Cassini-like spacecraft with a sunshade are presented to show a way to mitigate the high temperatures of a Venus flyby. It was predicted that the sunshade can lower the temperature of the ASRG alternator by 20 C for the representative Venus flyby trajectory. The 3D model also was modified to predict generator performance after a single Advanced Stirling Convertor failure. The geometry of the Microtherm HT insulation block on the outboard side was modified to match deformation and shrinkage observed during testing of a prototypic ASRG test fixture by LM. Test conditions and test data were used to correlate the model by adjusting the thermal conductivity of the deformed insulation to match the post-heat-dump steady state temperatures. Results for these conditions showed that the performance of the still-functioning inboard ACS was unaffected.

  13. Bayesian calibration of power plant models for accurate performance prediction

    International Nuclear Information System (INIS)

    Boksteen, Sowande Z.; Buijtenen, Jos P. van; Pecnik, Rene; Vecht, Dick van der

    2014-01-01

    Highlights: • Bayesian calibration is applied to power plant performance prediction. • Measurements from a plant in operation are used for model calibration. • A gas turbine performance model and steam cycle model are calibrated. • An integrated plant model is derived. • Part load efficiency is accurately predicted as a function of ambient conditions. - Abstract: Gas turbine combined cycles are expected to play an increasingly important role in the balancing of supply and demand in future energy markets. Thermodynamic modeling of these energy systems is frequently applied to assist in decision making processes related to the management of plant operation and maintenance. In most cases, model inputs, parameters and outputs are treated as deterministic quantities and plant operators make decisions with limited or no regard of uncertainties. As the steady integration of wind and solar energy into the energy market induces extra uncertainties, part load operation and reliability are becoming increasingly important. In the current study, methods are proposed to not only quantify various types of uncertainties in measurements and plant model parameters using measured data, but to also assess their effect on various aspects of performance prediction. The authors aim to account for model parameter and measurement uncertainty, and for systematic discrepancy of models with respect to reality. For this purpose, the Bayesian calibration framework of Kennedy and O’Hagan is used, which is especially suitable for high-dimensional industrial problems. The article derives a calibrated model of the plant efficiency as a function of ambient conditions and operational parameters, which is also accurate in part load. The article shows that complete statistical modeling of power plants not only enhances process models, but can also increases confidence in operational decisions

  14. Variability, Predictability, and Race Factors Affecting Performance in Elite Biathlon.

    Science.gov (United States)

    Skattebo, Øyvind; Losnegard, Thomas

    2018-03-01

    To investigate variability, predictability, and smallest worthwhile performance enhancement in elite biathlon sprint events. In addition, the effects of race factors on performance were assessed. Data from 2005 to 2015 including >10,000 and >1000 observations for each sex for all athletes and annual top-10 athletes, respectively, were included. Generalized linear mixed models were constructed based on total race time, skiing time, shooting time, and proportions of targets hit. Within-athlete race-to-race variability was expressed as coefficient of variation of performance times and standard deviation (SD) in proportion units (%) of targets hit. The models were adjusted for random and fixed effects of subject identity, season, event identity, and race factors. The within-athlete variability was independent of sex and performance standard of athletes: 2.5-3.2% for total race time, 1.5-1.8% for skiing time, and 11-15% for shooting times. The SD of the proportion of hits was ∼10% in both shootings combined (meaning ±1 hit in 10 shots). The predictability in total race time was very high to extremely high for all athletes (ICC .78-.84) but trivial for top-10 athletes (ICC .05). Race times during World Championships and Olympics were ∼2-3% faster than in World Cups. Moreover, race time increased by ∼2% per 1000 m of altitude, by ∼5% per 1% of gradient, by 1-2% per 1 m/s of wind speed, and by ∼2-4% on soft vs hard tracks. Researchers and practitioners should focus on strategies that improve biathletes' performance by at least 0.8-0.9%, corresponding to the smallest worthwhile enhancement (0.3 × within-athlete variability).

  15. Predictive neuromechanical simulations indicate why walking performance declines with ageing.

    Science.gov (United States)

    Song, Seungmoon; Geyer, Hartmut

    2018-04-01

    Although the natural decline in walking performance with ageing affects the quality of life of a growing elderly population, its physiological origins remain unknown. By using predictive neuromechanical simulations of human walking with age-related neuro-musculo-skeletal changes, we find evidence that the loss of muscle strength and muscle contraction speed dominantly contribute to the reduced walking economy and speed. The findings imply that focusing on recovering these muscular changes may be the only effective way to improve performance in elderly walking. More generally, the work is of interest for investigating the physiological causes of altered gait due to age, injury and disorders. Healthy elderly people walk slower and energetically less efficiently than young adults. This decline in walking performance lowers the quality of life for a growing ageing population, and understanding its physiological origin is critical for devising interventions that can delay or revert it. However, the origin of the decline in walking performance remains unknown, as ageing produces a range of physiological changes whose individual effects on gait are difficult to separate in experiments with human subjects. Here we use a predictive neuromechanical model to separately address the effects of common age-related changes to the skeletal, muscular and nervous systems. We find in computer simulations of this model that the combined changes produce gait consistent with elderly walking and that mainly the loss of muscle strength and mass reduces energy efficiency. In addition, we find that the slower preferred walking speed of elderly people emerges in the simulations when adapting to muscle fatigue, again mainly caused by muscle-related changes. The results suggest that a focus on recovering these muscular changes may be the only effective way to improve performance in elderly walking. © 2018 The Authors. The Journal of Physiology © 2018 The Physiological Society.

  16. Performance Prediction and Validation: Data, Frameworks, and Considerations

    Energy Technology Data Exchange (ETDEWEB)

    Tinnesand, Heidi

    2017-05-19

    Improving the predictability and reliability of wind power generation and operations will reduce costs and potentially establish a framework to attract new capital into the distributed wind sector, a key cost reduction requirement highlighted in results from the distributed wind future market assessment conducted with dWind. Quantifying and refining the accuracy of project performance estimates will also directly address several of the key challenges identified by industry stakeholders in 2015 as part of the distributed wind resource assessment workshop and be cross-cutting for several other facets of the distributed wind portfolio. This presentation covers the efforts undertaken in 2016 to address these topics.

  17. Numerical analysis of the performance prediction for a thermoelectric generator

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Chang Nyung [Kyung Hee University, Yongin (Korea, Republic of)

    2015-09-15

    The present study develops a two-dimensional numerical code that can predict the performance of a thermoelectric generator module including a p-leg/n-leg pair and top and bottom electrodes. The present code can simulate the detailed thermoelectric phenomena including the heat flow, electric current, Joule heating, Peltier heating, and Thomson heating, together with the efficiency of the modules whose properties depend on the temperature. The present numerical code can be used for the design optimization of a thermoelectric power generator.

  18. Predicting Students’ Performance using Modified ID3 Algorithm

    OpenAIRE

    Ramanathan L; Saksham Dhanda; Suresh Kumar D

    2013-01-01

    The ability to predict performance of students is very crucial in our present education system. We can use data mining concepts for this purpose. ID3 algorithm is one of the famous algorithms present today to generate decision trees. But this algorithm has a shortcoming that it is inclined to attributes with many values. So , this research aims to overcome this shortcoming of the algorithm by using gain ratio(instead of information gain) as well as by giving weights to each attribute at every...

  19. Performance prediction of a multi-basin solar still

    International Nuclear Information System (INIS)

    Mahdi, N.Al.

    1992-01-01

    A transient analysis for the prediction of the performance of a multi-basin solar still is presented. The energy-balance equations for the glass covers, the water masses and the absorber plate are manipulated to obtain a set of ordinary differential equations which are solved numerically. The analysis is applied to investigate the effect of the number of basins on the daily productivity of the still. Meteorological data corresponding to a June day in Bahrain have been used for the computation. The results indicate that the daily distillate output is increased by increasing the number of basins in the still. (author)

  20. Cold-Blooded Attention: Finger Temperature Predicts Attentional Performance.

    Science.gov (United States)

    Vergara, Rodrigo C; Moënne-Loccoz, Cristóbal; Maldonado, Pedro E

    2017-01-01

    Thermal stress has been shown to increase the chances of unsafe behavior during industrial and driving performances due to reductions in mental and attentional resources. Nonetheless, establishing appropriate safety standards regarding environmental temperature has been a major problem, as modulations are also be affected by the task type, complexity, workload, duration, and previous experience with the task. To bypass this attentional and thermoregulatory problem, we focused on the body rather than environmental temperature. Specifically, we measured tympanic, forehead, finger and environmental temperatures accompanied by a battery of attentional tasks. We considered a 10 min baseline period wherein subjects were instructed to sit and relax, followed by three attentional tasks: a continuous performance task (CPT), a flanker task (FT) and a counting task (CT). Using multiple linear regression models, we evaluated which variable(s) were the best predictors of performance. The results showed a decrement in finger temperature due to instruction and task engagement that was absent when the subject was instructed to relax. No changes were observed in tympanic or forehead temperatures, while the environmental temperature remained almost constant for each subject. Specifically, the magnitude of the change in finger temperature was the best predictor of performance in all three attentional tasks. The results presented here suggest that finger temperature can be used as a predictor of alertness, as it predicted performance in attentional tasks better than environmental temperature. These findings strongly support that peripheral temperature can be used as a tool to prevent unsafe behaviors and accidents.

  1. Cold-Blooded Attention: Finger Temperature Predicts Attentional Performance

    Directory of Open Access Journals (Sweden)

    Rodrigo C. Vergara

    2017-09-01

    Full Text Available Thermal stress has been shown to increase the chances of unsafe behavior during industrial and driving performances due to reductions in mental and attentional resources. Nonetheless, establishing appropriate safety standards regarding environmental temperature has been a major problem, as modulations are also be affected by the task type, complexity, workload, duration, and previous experience with the task. To bypass this attentional and thermoregulatory problem, we focused on the body rather than environmental temperature. Specifically, we measured tympanic, forehead, finger and environmental temperatures accompanied by a battery of attentional tasks. We considered a 10 min baseline period wherein subjects were instructed to sit and relax, followed by three attentional tasks: a continuous performance task (CPT, a flanker task (FT and a counting task (CT. Using multiple linear regression models, we evaluated which variable(s were the best predictors of performance. The results showed a decrement in finger temperature due to instruction and task engagement that was absent when the subject was instructed to relax. No changes were observed in tympanic or forehead temperatures, while the environmental temperature remained almost constant for each subject. Specifically, the magnitude of the change in finger temperature was the best predictor of performance in all three attentional tasks. The results presented here suggest that finger temperature can be used as a predictor of alertness, as it predicted performance in attentional tasks better than environmental temperature. These findings strongly support that peripheral temperature can be used as a tool to prevent unsafe behaviors and accidents.

  2. Aerodynamic performance prediction of Darrieus-type wind turbines

    Directory of Open Access Journals (Sweden)

    Ion NILĂ

    2010-06-01

    Full Text Available The prediction of Darrieus wind turbine aerodynamic performances provides the necessarydesign and operational data base related to the wind potential. In this sense it provides the type ofturbine suitable to the area where it is to be installed. Two calculation methods are analyzed for arotor with straight blades. The first one is a global method that allows an assessment of the turbinenominal power by a brief calculation. This method leads to an overestimation of performances. Thesecond is the calculation method of the gust factor and momentum which deals with the pale as beingcomposed of different elements that don’t influence each other. This method, developed based on thetheory of the turbine blades, leads to values close to the statistical data obtained experimentally. Thevalues obtained by the calculation method of gust factor - momentum led to the concept of a Darrieusturbine, which will be tested for different wind values in the INCAS subsonic wind tunnel.

  3. Performance prediction of rotary compressor with hydrocarbon refrigerant mixtures

    Energy Technology Data Exchange (ETDEWEB)

    Park, M.W.; Chung, Y.G. [Hanyang University Graduate School, Seoul (Korea); Park, K.W. [LG Industrial System Corporation Limited (Korea); Park, H.Y. [Hanyang University, Seoul (Korea)

    1999-04-01

    This paper presents the modeling approach that can be predicted transient behavior of rotary compressor. Mass and energy conservation laws are applied to the control volume, and real gas state equation is used to obtain thermodynamic properties of refrigerant. The valve equation is solved to analyze discharge process also. Dynamic analysis of vane and roller is carried out to gain friction work. From above modeling, the performance of rotary compressor with radial clearance and friction loss is investigated numerically. The performance of each refrigerant and the possibility of using the hydrocarbon refrigerant mixtures in an existing rotary compressor are estimated by applying R12, R134a, R290/R600a mixture also. (author). 6 refs., 13 figs., 1 tab.

  4. Tracking Neuronal Connectivity from Electric Brain Signals to Predict Performance.

    Science.gov (United States)

    Vecchio, Fabrizio; Miraglia, Francesca; Rossini, Paolo Maria

    2018-05-01

    The human brain is a complex container of interconnected networks. Network neuroscience is a recent venture aiming to explore the connection matrix built from the human brain or human "Connectome." Network-based algorithms provide parameters that define global organization of the brain; when they are applied to electroencephalographic (EEG) signals network, configuration and excitability can be monitored in millisecond time frames, providing remarkable information on their instantaneous efficacy also for a given task's performance via online evaluation of the underlying instantaneous networks before, during, and after the task. Here we provide an updated summary on the connectome analysis for the prediction of performance via the study of task-related dynamics of brain network organization from EEG signals.

  5. Planetary Suit Hip Bearing Model for Predicting Design vs. Performance

    Science.gov (United States)

    Cowley, Matthew S.; Margerum, Sarah; Harvil, Lauren; Rajulu, Sudhakar

    2011-01-01

    , the suited performance trends were comparable between the model and the suited subjects. With the three off-nominal bearing configurations compared to the nominal bearing configurations, human subjects showed decreases in hip flexion of 64%, 6%, and 13% and in hip abduction of 59%, 2%, and 20%. Likewise the solid model showed decreases in hip flexion of 58%, 1%, and 25% and in hip abduction of 56%, 0%, and 30%, under the same condition changes from the nominal configuration. Differences seen between the model predictions and the human subject performance data could be attributed to the model lacking dynamic elements and performing kinematic analysis only, the level of fit of the subjects with the suit, the levels of the subject s suit experience.

  6. The prediction of the hydrodynamic performance of tidal current turbines

    International Nuclear Information System (INIS)

    Xiao, B Y; Zhou, L J; Xiao, Y X; Wang, Z W

    2013-01-01

    Nowadays tidal current energy is considered to be one of the most promising alternative green energy resources and tidal current turbines are used for power generation. Prediction of the open water performance around tidal turbines is important for the reason that it can give some advice on installation and array of tidal current turbines. This paper presents numerical computations of tidal current turbines by using a numerical model which is constructed to simulate an isolated turbine. This paper aims at studying the installation of marine current turbine of which the hydro-environmental impacts influence by means of numerical simulation. Such impacts include free-stream velocity magnitude, seabed and inflow direction of velocity. The results of the open water performance prediction show that the power output and efficiency of marine current turbine varies from different marine environments. The velocity distribution should be clearly and the suitable unit installation depth and direction be clearly chosen, which can ensure the most effective strategy for energy capture before installing the marine current turbine. The findings of this paper are expected to be beneficial in developing tidal current turbines and array in the future

  7. Predicting the Impacts of Intravehicular Displays on Driving Performance with Human Performance Modeling

    Science.gov (United States)

    Mitchell, Diane Kuhl; Wojciechowski, Josephine; Samms, Charneta

    2012-01-01

    A challenge facing the U.S. National Highway Traffic Safety Administration (NHTSA), as well as international safety experts, is the need to educate car drivers about the dangers associated with performing distraction tasks while driving. Researchers working for the U.S. Army Research Laboratory have developed a technique for predicting the increase in mental workload that results when distraction tasks are combined with driving. They implement this technique using human performance modeling. They have predicted workload associated with driving combined with cell phone use. In addition, they have predicted the workload associated with driving military vehicles combined with threat detection. Their technique can be used by safety personnel internationally to demonstrate the dangers of combining distracter tasks with driving and to mitigate the safety risks.

  8. Burst muscle performance predicts the speed, acceleration, and turning performance of Anna's hummingbirds.

    Science.gov (United States)

    Segre, Paolo S; Dakin, Roslyn; Zordan, Victor B; Dickinson, Michael H; Straw, Andrew D; Altshuler, Douglas L

    2015-11-19

    Despite recent advances in the study of animal flight, the biomechanical determinants of maneuverability are poorly understood. It is thought that maneuverability may be influenced by intrinsic body mass and wing morphology, and by physiological muscle capacity, but this hypothesis has not yet been evaluated because it requires tracking a large number of free flight maneuvers from known individuals. We used an automated tracking system to record flight sequences from 20 Anna's hummingbirds flying solo and in competition in a large chamber. We found that burst muscle capacity predicted most performance metrics. Hummingbirds with higher burst capacity flew with faster velocities, accelerations, and rotations, and they used more demanding complex turns. In contrast, body mass did not predict variation in maneuvering performance, and wing morphology predicted only the use of arcing turns and high centripetal accelerations. Collectively, our results indicate that burst muscle capacity is a key predictor of maneuverability.

  9. Assessment of the performance of various airfoil sections on power generation from a wind turbine using the blade element momentum theory

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Xiaomin; Agarwal, Ramesh [Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, Jolley Hall, Campus Box 1185, One Brookings Drive, St. Louis, Missouri, 63130 (United States)

    2013-07-01

    It is well established that the power generated by a Horizontal-Axis Wind Turbine (HAWT) is a function of the number of blades, the tip speed ratio (blade tip speed/wind free stream velocity) and the lift to drag ratio (CL /CD) of the airfoil sections of the blade. The airfoil sections used in HAWT are generally thick airfoils such as the S, DU, FX, Flat-back and NACA 6-series of airfoils. These airfoils vary in (CL /CD) for a given blade and ratio and therefore the power generated by HAWT for different blade airfoil sections will vary. The goal of this paper is to evaluate the effect of different airfoil sections on HAWT performance using the Blade Element Momentum (BEM) theory. In this study, we employ DU 91-W2-250, FX 66-S196-V1, NACA 64421, and Flat-back series of airfoils (FB-3500-0050, FB-3500-0875, and FB-3500-1750) and compare their performance with S809 airfoil used in NREL Phase II and III wind turbines; the lift and drag coefficient data for these airfoils sections are available. The output power of the turbine is calculated using these airfoil section blades for a given blade and ratio and is compared with the original NREL Phase II and Phase III turbines using S809 airfoil section. It is shown that by a suitable choice of airfoil section of HAWT blade, the power generated by the turbine can be significantly increased. Parametric studies are also conducted by varying the turbine diameter.

  10. Predicting students' intention to use stimulants for academic performance enhancement.

    Science.gov (United States)

    Ponnet, Koen; Wouters, Edwin; Walrave, Michel; Heirman, Wannes; Van Hal, Guido

    2015-02-01

    The non-medical use of stimulants for academic performance enhancement is becoming a more common practice among college and university students. The objective of this study is to gain a better understanding of students' intention to use stimulant medication for the purpose of enhancing their academic performance. Based on an extended model of Ajzen's theory of planned behavior, we examined the predictive value of attitude, subjective norm, perceived behavioral control, psychological distress, procrastination, substance use, and alcohol use on students' intention to use stimulants to improve their academic performance. The sample consisted of 3,589 Flemish university and college students (mean age: 21.59, SD: 4.09), who participated anonymously in an online survey conducted in March and April 2013. Structural equation modeling was used to investigate the relationships among the study variables. Our results indicate that subjective norm is the strongest predictor of students' intention to use stimulant medication, followed by attitude and perceived behavioral control. To a lesser extent, procrastinating tendencies, psychological distress, and substance abuse contribute to students' intention. Conclusions/ Importance: Based on these findings, we provide several recommendations on how to curtail students' intention to use stimulant medication for the purpose of improving their academic performance. In addition, we urge researchers to identify other psychological variables that might be related to students' intention.

  11. Near peripheral motion contrast threshold predicts older drivers' simulator performance.

    Science.gov (United States)

    Henderson, Steven; Gagnon, Sylvain; Collin, Charles; Tabone, Ricardo; Stinchcombe, Arne

    2013-01-01

    Our group has previously demonstrated that peripheral motion contrast threshold (PMCT) is significantly associated with self-reported accident risk of older drivers (questionnaire assessment), and with Useful Field of View(®) subtest 2 (UFOV2). It has not been shown, however, that PMCT is significantly associated with driving performance. Using the method of descending limits (spatial two-alternative forced choice) we assessed motion contrast thresholds of 28 young participants (25-45), and 21 older drivers (63-86) for 0.4 cycle/degree drifting Gabor stimuli at 15° eccentricity and examined whether it was related to performance on a simulated on-road test and to a measure of visual attention (UFOV(®) subtests 2 and 3). Peripheral motion contrast thresholds (PMCT) of younger participants were significantly lower than older participants. PMCT and UFOV2 significantly predicted driving examiners' scores of older drivers' simulator performance, as well as number of crashes. Within the older group, PMCT correlated significantly with UFOV2, UFOV3, and age. Within the younger group, PMCT was not significantly related to either UFOV(®) scores or age. Partial correlations showed that: substantial association between PMCT and UFOV2 was not age-related (within the older driver group); PMCT and UFOV2 tapped a common visual function; and PMCT assessed a component not captured by UFOV2. PMCT is potentially a useful assessment tool for predicting accident risk of older drivers, and for informing efforts to develop effective countermeasures to remediate this functional deficit as much as possible. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. Performance analysis of tracked panel according to predicted global radiation

    International Nuclear Information System (INIS)

    Chang, T.P.

    2009-01-01

    In this paper, the performance of a south facing single-axis tracked panel was analyzed according to global radiation predicted by empirical model. Mathematic expressions appropriate for single-axis tracking system were derived to calculate the radiation on it. Instantaneous increments of solar energy collected by the tracked panel relative to fixed panel are illustrated. The validity of the empirical model to Taiwan area will also be examined with the actual irradiation data observed in Taipei. The results are summarized as follows: the gains made by the tracked panel relative to a fixed panel are between 20.0% and 33.9% for four specified days of year, between 20.9% and 33.2% for the four seasons and 27.6% over the entire year. For latitudes below 65 deg., the yearly optimal tilt angle of a fixed panel is close to 0.8 times latitude, the irradiation ratio of the tracked panel to the fixed panel is about 1.3, which are smaller than the corresponding values calculated from extraterrestrial radiation, suggesting us that the installation angle should be adjusted toward a flatter angle and that the gain of the tracked panel will reduce while it works in cloudy climate or in air pollution environment. Although the captured radiation increases with the maximal rotation angle of panel, but the benefit on the global radiation case is still not so good as that on extraterrestrial radiation case. The irradiation data observed is much less than the data predicted by the empirical model, however the trend of fitting curve to the observed data is somewhat in agreement with that to the predicted one; the yearly gain is 14.3% when a tracked panel is employed throughout the year.

  13. Predictive Performance Tuning of OpenACC Accelerated Applications

    KAUST Repository

    Siddiqui, Shahzeb

    2014-05-04

    Graphics Processing Units (GPUs) are gradually becoming mainstream in supercomputing as their capabilities to significantly accelerate a large spectrum of scientific applications have been clearly identified and proven. Moreover, with the introduction of high level programming models such as OpenACC [1] and OpenMP 4.0 [2], these devices are becoming more accessible and practical to use by a larger scientific community. However, performance optimization of OpenACC accelerated applications usually requires an in-depth knowledge of the hardware and software specifications. We suggest a prediction-based performance tuning mechanism [3] to quickly tune OpenACC parameters for a given application to dynamically adapt to the execution environment on a given system. This approach is applied to a finite difference kernel to tune the OpenACC gang and vector clauses for mapping the compute kernels into the underlying accelerator architecture. Our experiments show a significant performance improvement against the default compiler parameters and a faster tuning by an order of magnitude compared to the brute force search tuning.

  14. Music-related reward responses predict episodic memory performance.

    Science.gov (United States)

    Ferreri, Laura; Rodriguez-Fornells, Antoni

    2017-12-01

    Music represents a special type of reward involving the recruitment of the mesolimbic dopaminergic system. According to recent theories on episodic memory formation, as dopamine strengthens the synaptic potentiation produced by learning, stimuli triggering dopamine release could result in long-term memory improvements. Here, we behaviourally test whether music-related reward responses could modulate episodic memory performance. Thirty participants rated (in terms of arousal, familiarity, emotional valence, and reward) and encoded unfamiliar classical music excerpts. Twenty-four hours later, their episodic memory was tested (old/new recognition and remember/know paradigm). Results revealed an influence of music-related reward responses on memory: excerpts rated as more rewarding were significantly better recognized and remembered. Furthermore, inter-individual differences in the ability to experience musical reward, measured through the Barcelona Music Reward Questionnaire, positively predicted memory performance. Taken together, these findings shed new light on the relationship between music, reward and memory, showing for the first time that music-driven reward responses are directly implicated in higher cognitive functions and can account for individual differences in memory performance.

  15. Application of Machine Learning Algorithms for the Query Performance Prediction

    Directory of Open Access Journals (Sweden)

    MILICEVIC, M.

    2015-08-01

    Full Text Available This paper analyzes the relationship between the system load/throughput and the query response time in a real Online transaction processing (OLTP system environment. Although OLTP systems are characterized by short transactions, which normally entail high availability and consistent short response times, the need for operational reporting may jeopardize these objectives. We suggest a new approach to performance prediction for concurrent database workloads, based on the system state vector which consists of 36 attributes. There is no bias to the importance of certain attributes, but the machine learning methods are used to determine which attributes better describe the behavior of the particular database server and how to model that system. During the learning phase, the system's profile is created using multiple reference queries, which are selected to represent frequent business processes. The possibility of the accurate response time prediction may be a foundation for automated decision-making for database (DB query scheduling. Possible applications of the proposed method include adaptive resource allocation, quality of service (QoS management or real-time dynamic query scheduling (e.g. estimation of the optimal moment for a complex query execution.

  16. Mental Strategies Predict Performance and Satisfaction with Performance among Soccer Players.

    Science.gov (United States)

    Kruk, Magdalena; Blecharz, Jan; Boberska, Monika; Zarychta, Karolina; Luszczynska, Aleksandra

    2017-10-01

    This study investigated the changes in mental strategies across the season and their effects on performance and satisfaction with individual performance. Data were collected three times: at the pre-season at Time 1 (T1; baseline), in the mid-season at Time 2 (T2; two-month follow-up), and at the end-of-season at Time 3 (T3; nine-month follow-up) among male soccer players (N = 97) aged 16-27. Athletes completed the questionnaires assessing the use of nine psychological strategies in competition and the level of satisfaction with individual performance. Endurance performance was measured objectively with a 300 m run. A high level of relaxation (T1) explained better 300 m run performance (T3) and a high level of self-talk explained a higher satisfaction with individual performance (T3). A rare use of distractibility and emotional control (T1) predicted a higher level of satisfaction with individual performance (T3). No predictive role of other psychological strategies was found. The use of emotional control, relaxation, and distractibility increased over the season, whereas the use of imagery and negative thinking declined. Besides the roles of self-talk, imagery, relaxation and goal-setting, the effects of distractibility and emotional control should be taken into account when considering athletes' mental training programs.

  17. Mining Behavior Based Safety Data to Predict Safety Performance

    Energy Technology Data Exchange (ETDEWEB)

    Jeffrey C. Joe

    2010-06-01

    The Idaho National Laboratory (INL) operates a behavior based safety program called Safety Observations Achieve Results (SOAR). This peer-to-peer observation program encourages employees to perform in-field observations of each other's work practices and habits (i.e., behaviors). The underlying premise of conducting these observations is that more serious accidents are prevented from occurring because lower level “at risk” behaviors are identified and corrected before they can propagate into culturally accepted “unsafe” behaviors that result in injuries or fatalities. Although the approach increases employee involvement in safety, the premise of the program has not been subject to sufficient empirical evaluation. The INL now has a significant amount of SOAR data on these lower level “at risk” behaviors. This paper describes the use of data mining techniques to analyze these data to determine whether they can predict if and when a more serious accident will occur.

  18. Do Maximal Roller Skiing Speed and Double Poling Performance Predict Youth Cross-Country Skiing Performance?

    Directory of Open Access Journals (Sweden)

    Roland Stöggl, Erich Müller, Thomas Stöggl

    2017-09-01

    Full Text Available The aims of the current study were to analyze whether specific roller skiing tests and cycle length are determinants of youth cross-country (XC skiing performance, and to evaluate sex specific differences by applying non-invasive diagnostics. Forty-nine young XC skiers (33 boys; 13.8 ± 0.6 yrs and 16 girls; 13.4 ± 0.9 yrs performed roller skiing tests consisting of both shorter (50 m and longer durations (575 m. Test results were correlated with on snow XC skiing performance (PXC based on 3 skating and 3 classical distance competitions (3 to 6 km. The main findings of the current study were: 1 Anthropometrics and maturity status were related to boys’, but not to girls’ PXC; 2 Significant moderate to acceptable correlations between girls’ and boys’ short duration maximal roller skiing speed (double poling, V2 skating, leg skating and PXC were found; 3 Boys’ PXC was best predicted by double poling test performance on flat and uphill, while girls’ performance was mainly predicted by uphill double poling test performance; 4 When controlling for maturity offset, boys’ PXC was still highly associated with the roller skiing tests. The use of simple non-invasive roller skiing tests for determination of PXC represents practicable support for ski clubs, schools or skiing federations in the guidance and evaluation of young talent.

  19. Performance prediction of hot mix asphalt from asphalt binders

    International Nuclear Information System (INIS)

    Hafeez, I.; Kamal, M.A.; Shahzad, Q.; Bashir, N.; Ahadi, M.R.

    2012-01-01

    Asphalt binder being a high weight hydrocarbon contains asphaltene and maltene and is widely used as cementing materials in the construction of flexible pavements. Its performance in hot mix asphalt also depends on combining with different proportions of aggregates. The main objective of this study was to characterize asphalt cement rheological behavior and to investigate the influence of asphalt on asphalt-aggregate mixtures prepared with virgin binders and using polymers. Binder rheology and mixtures stiffness were determined under a range of cyclic loadings and temperature conditions. Master curves were developed for the evaluation of relationship between parameters like complex modulus and phase angle at different frequencies. Horizontal shift factors were also computed to determine time and temperature response of binders and mixes. The results showed that the stiffness of both the binder and the mixes depends on temperature and frequency of load. Polymer modified binder is least susceptible to temperature variations as compared to other virgin asphalt cement. Performance of asphalt mixtures can be predicted from those of asphalt binders using the master curve technique. (author)

  20. Prediction of Gas Injection Performance for Heterogeneous Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Blunt, Martin J.; Orr, Franklin M.

    1999-05-17

    This report describes research carried out in the Department of Petroleum Engineering at Stanford University from September 1997 - September 1998 under the second year of a three-year grant from the Department of Energy on the "Prediction of Gas Injection Performance for Heterogeneous Reservoirs." The research effort is an integrated study of the factors affecting gas injection, from the pore scale to the field scale, and involves theoretical analysis, laboratory experiments, and numerical simulation. The original proposal described research in four areas: (1) Pore scale modeling of three phase flow in porous media; (2) Laboratory experiments and analysis of factors influencing gas injection performance at the core scale with an emphasis on the fundamentals of three phase flow; (3) Benchmark simulations of gas injection at the field scale; and (4) Development of streamline-based reservoir simulator. Each state of the research is planned to provide input and insight into the next stage, such that at the end we should have an integrated understanding of the key factors affecting field scale displacements.

  1. Preparatory neural activity predicts performance on a conflict task.

    Science.gov (United States)

    Stern, Emily R; Wager, Tor D; Egner, Tobias; Hirsch, Joy; Mangels, Jennifer A

    2007-10-24

    Advance preparation has been shown to improve the efficiency of conflict resolution. Yet, with little empirical work directly linking preparatory neural activity to the performance benefits of advance cueing, it is not clear whether this relationship results from preparatory activation of task-specific networks, or from activity associated with general alerting processes. Here, fMRI data were acquired during a spatial Stroop task in which advance cues either informed subjects of the upcoming relevant feature of conflict stimuli (spatial or semantic) or were neutral. Informative cues decreased reaction time (RT) relative to neutral cues, and cues indicating that spatial information would be task-relevant elicited greater activity than neutral cues in multiple areas, including right anterior prefrontal and bilateral parietal cortex. Additionally, preparatory activation in bilateral parietal cortex and right dorsolateral prefrontal cortex predicted faster RT when subjects responded to spatial location. No regions were found to be specific to semantic cues at conventional thresholds, and lowering the threshold further revealed little overlap between activity associated with spatial and semantic cueing effects, thereby demonstrating a single dissociation between activations related to preparing a spatial versus semantic task-set. This relationship between preparatory activation of spatial processing networks and efficient conflict resolution suggests that advance information can benefit performance by leading to domain-specific biasing of task-relevant information.

  2. Further developments in performance prediction techniques of adiabatic diesel engines

    Energy Technology Data Exchange (ETDEWEB)

    Rasihhan, Y

    1990-01-01

    The engine cycle simulation program 'SPICE', developed at Bath University, has been used extensively for insulated diesel engine research. The present study introduces more comprehensive engine heat transfer models thus enabling us to study the insulated engine heat transfer and performance characteristics in more detail. The new version of 'SPICE' separates the gas to wall heat transfer into two parts, convective and radiative. For this purpose, a detailed radiative heat transfer model which considers both the flame (gas and soot) and wall to wall radiative heat transfer is written. The previous engine resistance model is refined and replaced by a more detailed resistance model which considers piston-liner conduction heat transfer and 2-D heat flow in the liner. The wall surface temperature swing is also included in the engine heat transfer calculations which is quite significant in low conductivity ceramic insulated engines. A 1-D finite difference model is written for the transient heat transfer region of the wall and linked to the engine resistance model. This new version of 'SPICE' is used to predict the insulated engine heat transfer and performance for the experimental Petter PH1W engine for various insulation levels and schemes. An answer to the controversy of increase in engine heat loss with insulation is looked for. The effect of wall deposits on engine heat transfer and its significance for the insulated engine is highlighted. (Author).

  3. PREDICTING THERMAL PERFORMANCE OF ROOFING SYSTEMS IN SURABAYA

    Directory of Open Access Journals (Sweden)

    MINTOROGO Danny Santoso

    2015-07-01

    Full Text Available Traditional roofing systems in the developing country likes Indonesia are still be dominated by the 30o, 45o, and more pitched angle roofs; the roofing cover materials are widely used to traditional clay roof tiles, then modern concrete roof tiles, and ceramic roof tiles. In the 90’s decay, shop houses are prosperous built with flat concrete roofs dominant. Green roofs and roof ponds are almost rarely built to meet the sustainable environmental issues. Some tested various roof systems in Surabaya were carried out to observe the roof thermal performances. Mathematical equation model from three references are also performed in order to compare with the real project tested. Calculated with equation (Kabre et al., the 30o pitched concrete-roof-tile, 30o clay-roof-tile, 45o pitched concrete-roof-tile are the worst thermal heat flux coming to room respectively. In contrast, the bare soil concrete roof and roof pond system are the least heat flux streamed onto room. Based on predicted calculation without insulation and cross-ventilation attic space, the roof pond and bare soil concrete roof (greenery roof are the appropriate roof systems for the Surabaya’s climate; meanwhile the most un-recommended roof is pitched 30o or 45o angle with concrete-roof tiles roofing systems.

  4. Maintenance personnel performance simulation (MAPPS): a model for predicting maintenance performance reliability in nuclear power plants

    International Nuclear Information System (INIS)

    Knee, H.E.; Krois, P.A.; Haas, P.M.; Siegel, A.I.; Ryan, T.G.

    1983-01-01

    The NRC has developed a structured, quantitative, predictive methodology in the form of a computerized simulation model for assessing maintainer task performance. Objective of the overall program is to develop, validate, and disseminate a practical, useful, and acceptable methodology for the quantitative assessment of NPP maintenance personnel reliability. The program was organized into four phases: (1) scoping study, (2) model development, (3) model evaluation, and (4) model dissemination. The program is currently nearing completion of Phase 2 - Model Development

  5. Exploration of Machine Learning Approaches to Predict Pavement Performance

    Science.gov (United States)

    2018-03-23

    Machine learning (ML) techniques were used to model and predict pavement condition index (PCI) for various pavement types using a variety of input variables. The primary objective of this research was to develop and assess PCI predictive models for t...

  6. Numerical investigation of optimal yaw misalignment and collective pitch angle for load imbalance reduction of rigid and flexible HAWT blades under sheared inflow

    International Nuclear Information System (INIS)

    Jeong, Min-Soo; Cha, Myung-Chan; Kim, Sang-Woo; Lee, In

    2015-01-01

    Wind shear can strongly influence the cyclic loading on horizontal axis wind turbine blades. These load fluctuation causes a variation of power output and introduces fatigue load. Thus, individual pitch controllers have been developed that are focused on the load alleviations, however, comes at a price of actuator requirements for control. Moreover, these controllers are unable to apply to already existing wind turbines with active yaw and collective pitch control system. Therefore, the investigations for minimizing load imbalance through the adjustments of yaw misalignment and collective pitch angle are implemented for the rigid and flexible blades under the sheared inflow. By applying the optimization process based on a sequential quadratic programming approach, the optimal yaw and pitch angle can be estimated. Then, the numerical simulations for predicting the performance are performed. The results showed that the fluctuation range of the root flapwise bending moment for the rigid blades can be reduced by 84.5%, whereas the vibratory bending moment for the flexible blades can be reduced by up to approximately 82.4% in the best case. Therefore, the magnitudes of load imbalance can be minimized by the adjustment of the optimal yaw misalignment and collective pitch angle without any power loss. - Highlights: • We propose a novel method for the reduction of load imbalance under sheared inflow. • We estimate optimal yaw misalignment and collective pitch angle through optimization. • Numerical results of performance are predicted for rigid and flexible blades. • By applying optimal angles, load variations are reduced without any power loss

  7. Gaussian Process Regression for WDM System Performance Prediction

    DEFF Research Database (Denmark)

    Wass, Jesper; Thrane, Jakob; Piels, Molly

    2017-01-01

    Gaussian process regression is numerically and experimentally investigated to predict the bit error rate of a 24 x 28 CiBd QPSK WDM system. The proposed method produces accurate predictions from multi-dimensional and sparse measurement data.......Gaussian process regression is numerically and experimentally investigated to predict the bit error rate of a 24 x 28 CiBd QPSK WDM system. The proposed method produces accurate predictions from multi-dimensional and sparse measurement data....

  8. Does Residency Selection Criteria Predict Performance in Orthopaedic Surgery Residency?

    Science.gov (United States)

    Raman, Tina; Alrabaa, Rami George; Sood, Amit; Maloof, Paul; Benevenia, Joseph; Berberian, Wayne

    2016-04-01

    More than 1000 candidates applied for orthopaedic residency positions in 2014, and the competition is intense; approximately one-third of the candidates failed to secure a position in the match. However, the criteria used in the selection process often are subjective and studies have differed in terms of which criteria predict either objective measures or subjective ratings of resident performance by faculty. Do preresidency selection factors serve as predictors of success in residency? Specifically, we asked which preresidency selection factors are associated or correlated with (1) objective measures of resident knowledge and performance; and (2) subjective ratings by faculty. Charts of 60 orthopaedic residents from our institution were reviewed. Preresidency selection criteria examined included United States Medical Licensing Examination (USMLE) Step 1 and Step 2 scores, Medical College Admission Test (MCAT) scores, number of clinical clerkship honors, number of letters of recommendation, number of away rotations, Alpha Omega Alpha (AOA) honor medical society membership, fourth-year subinternship at our institution, and number of publications. Resident performance was assessed using objective measures including American Board of Orthopaedic Surgery (ABOS) Part I scores and Orthopaedics In-Training Exam (OITE) scores and subjective ratings by faculty including global evaluation scores and faculty rankings of residents. We tested associations between preresidency criteria and the subsequent objective and subjective metrics using linear correlation analysis and Mann-Whitney tests when appropriate. Objective measures of resident performance namely, ABOS Part I scores, had a moderate linear correlation with the USMLE Step 2 scores (r = 0.55, p communication skills" subsection of the global evaluations. We found that USMLE Step 2, number of honors in medical school clerkships, and AOA membership demonstrated the strongest correlations with resident performance. Our

  9. Climbing fibers predict movement kinematics and performance errors.

    Science.gov (United States)

    Streng, Martha L; Popa, Laurentiu S; Ebner, Timothy J

    2017-09-01

    Requisite for understanding cerebellar function is a complete characterization of the signals provided by complex spike (CS) discharge of Purkinje cells, the output neurons of the cerebellar cortex. Numerous studies have provided insights into CS function, with the most predominant view being that they are evoked by error events. However, several reports suggest that CSs encode other aspects of movements and do not always respond to errors or unexpected perturbations. Here, we evaluated CS firing during a pseudo-random manual tracking task in the monkey ( Macaca mulatta ). This task provides extensive coverage of the work space and relative independence of movement parameters, delivering a robust data set to assess the signals that activate climbing fibers. Using reverse correlation, we determined feedforward and feedback CSs firing probability maps with position, velocity, and acceleration, as well as position error, a measure of tracking performance. The direction and magnitude of the CS modulation were quantified using linear regression analysis. The major findings are that CSs significantly encode all three kinematic parameters and position error, with acceleration modulation particularly common. The modulation is not related to "events," either for position error or kinematics. Instead, CSs are spatially tuned and provide a linear representation of each parameter evaluated. The CS modulation is largely predictive. Similar analyses show that the simple spike firing is modulated by the same parameters as the CSs. Therefore, CSs carry a broader array of signals than previously described and argue for climbing fiber input having a prominent role in online motor control. NEW & NOTEWORTHY This article demonstrates that complex spike (CS) discharge of cerebellar Purkinje cells encodes multiple parameters of movement, including motor errors and kinematics. The CS firing is not driven by error or kinematic events; instead it provides a linear representation of each

  10. Frontoparietal white matter integrity predicts haptic performance in chronic stroke

    Directory of Open Access Journals (Sweden)

    Alexandra L. Borstad

    2016-01-01

    . Age strongly correlated with the shared variance across tracts in the control, but not in the poststroke participants. A moderate to good relationship was found between ipsilesional T–M1 MD and affected hand HASTe score (r = −0.62, p = 0.006 and less affected hand HASTe score (r = −0.53, p = 0.022. Regression analysis revealed approximately 90% of the variance in affected hand HASTe score was predicted by the white matter integrity in the frontoparietal network (as indexed by MD in poststroke participants while 87% of the variance in HASTe score was predicted in control participants. This study demonstrates the importance of frontoparietal white matter in mediating haptic performance and specifically identifies that T–M1 and precuneus interhemispheric tracts may be appropriate targets for piloting rehabilitation interventions, such as noninvasive brain stimulation, when the goal is to improve poststroke haptic performance.

  11. Frontoparietal white matter integrity predicts haptic performance in chronic stroke.

    Science.gov (United States)

    Borstad, Alexandra L; Choi, Seongjin; Schmalbrock, Petra; Nichols-Larsen, Deborah S

    2016-01-01

    strongly correlated with the shared variance across tracts in the control, but not in the poststroke participants. A moderate to good relationship was found between ipsilesional T-M1 MD and affected hand HASTe score (r = - 0.62, p = 0.006) and less affected hand HASTe score (r = - 0.53, p = 0.022). Regression analysis revealed approximately 90% of the variance in affected hand HASTe score was predicted by the white matter integrity in the frontoparietal network (as indexed by MD) in poststroke participants while 87% of the variance in HASTe score was predicted in control participants. This study demonstrates the importance of frontoparietal white matter in mediating haptic performance and specifically identifies that T-M1 and precuneus interhemispheric tracts may be appropriate targets for piloting rehabilitation interventions, such as noninvasive brain stimulation, when the goal is to improve poststroke haptic performance.

  12. Burst muscle performance predicts the speed, acceleration, and turning performance of Anna’s hummingbirds

    Science.gov (United States)

    Segre, Paolo S; Dakin, Roslyn; Zordan, Victor B; Dickinson, Michael H; Straw, Andrew D; Altshuler, Douglas L

    2015-01-01

    Despite recent advances in the study of animal flight, the biomechanical determinants of maneuverability are poorly understood. It is thought that maneuverability may be influenced by intrinsic body mass and wing morphology, and by physiological muscle capacity, but this hypothesis has not yet been evaluated because it requires tracking a large number of free flight maneuvers from known individuals. We used an automated tracking system to record flight sequences from 20 Anna's hummingbirds flying solo and in competition in a large chamber. We found that burst muscle capacity predicted most performance metrics. Hummingbirds with higher burst capacity flew with faster velocities, accelerations, and rotations, and they used more demanding complex turns. In contrast, body mass did not predict variation in maneuvering performance, and wing morphology predicted only the use of arcing turns and high centripetal accelerations. Collectively, our results indicate that burst muscle capacity is a key predictor of maneuverability. DOI: http://dx.doi.org/10.7554/eLife.11159.001 PMID:26583753

  13. Prediction of mandibular rotation: an empirical test of clinician performance.

    Science.gov (United States)

    Baumrind, S; Korn, E L; West, E E

    1984-11-01

    An experiment was conducted in an attempt to determine empirically how effective a number of expert clinicians were at differentiating "backward rotators" from "forward rotators" on the basis of head-film information which might reasonably have been available to them prior to instituting treatment for the correction of Class II malocclusion. As a result of a previously reported ongoing study, pre- and posttreatment head films were available for 188 patients treated in the mixed dentition for the correction of Class II malocclusion and for 50 untreated Class II subjects. These subjects were divided into 14 groups (average size of group, 17; range, 6 to 23) solely on the basis of type of treatment and the clinician from whose clinic the records had originated. From within each group, we selected the two or three subjects who had exhibited the most extreme backward rotation and the two or three subjects who had exhibited the most extreme forward rotation of the mandible during the interval between films. The sole criterion for classification was magnitude of change in the mandibular plane angle of Downs between the pre- and posttreatment films of each patient. The resulting sample contained 32 backward-rotator subjects and 32 forward-rotator subjects. Five expert judges (mean clinical experience, 28 years) were asked to identify the backward-rotator subjects by examination of the pretreatment films. The findings may be summarized as follows: (1) No judge performed significantly better than chance. (2) There was strong evidence that the judges used a shared, though relatively ineffective, set of rules in making their discriminations between forward and backward rotators. (3) Statistical analysis of the predictive power of a set of standard cephalometric measurements which had previously been made for this set of subjects indicated that the numerical data also failed to identify potential backward rotators at a rate significantly better than chance. We infer from these

  14. MHA admission criteria and program performance: do they predict career performance?

    Science.gov (United States)

    Porter, J; Galfano, V J

    1987-01-01

    The purpose of this study was to determine to what extent admission criteria predict graduate school and career performance. The study also analyzed which objective and subjective criteria served as the best predictors. MHA graduates of the University of Minnesota from 1974 to 1977 were surveyed to assess career performance. Student files served as the data base on admission criteria and program performance. Career performance was measured by four variables: total compensation, satisfaction, fiscal responsibility, and level of authority. High levels of MHA program performance were associated with women who had high undergraduate GPAs from highly selective undergraduate colleges, were undergraduate business majors, and participated in extracurricular activities. High levels of compensation were associated with relatively low undergraduate GPAs, high levels of participation in undergraduate extracurricular activities, and being single at admission to graduate school. Admission to MHA programs should be based upon both objective and subjective criteria. Emphasis should be placed upon the selection process for MHA students since admission criteria are shown to explain 30 percent of the variability in graduate program performance, and as much as 65 percent of the variance in level of position authority.

  15. Assessing Prediction Performance of Neoadjuvant Chemotherapy Response in Bladder Cancer

    OpenAIRE

    Cremer, Chris

    2016-01-01

    Neoadjuvant chemotherapy is a treatment routinely prescribed to patients diagnosed with muscle-invasive bladder cancer. Unfortunately, not all patients are responsive to this treatment and would greatly benefit from an accurate prediction of their expected response to chemotherapy. In this project, I attempt to develop a model that will predict response using tumour microarray data. I show that using my dataset, every method is insufficient at accurately classifying responders and non-respond...

  16. Texas cracking performance prediction, simulation, and binder recommendation.

    Science.gov (United States)

    2014-10-01

    Recent studies show some mixes with softer binders used outside of Texas (e.g., Minnesotas Cold Weather Road Research Facility mixes) have both good rutting and cracking performance. However, the current binder performance grading (PG) system fail...

  17. Predicting Performance with Contextualized Inventories, No Frame-of-reference Effect?

    NARCIS (Netherlands)

    Holtrop, D.J.; Born, M.P.; de Vries, R.E.

    2014-01-01

    A recent meta-analysis showed that contextualized personality inventories have incremental predictive validity over generic personality inventories when predicting job performance. This study aimed to investigate the differences between two types of contextualization of items: Adding an 'at work'

  18. Architectural Development and Performance Analysis of a Primary Data Cache with Read Miss Address Prediction Capability

    National Research Council Canada - National Science Library

    Christensen, Kathryn

    1998-01-01

    .... The Predictive Read Cache (PRC) further improves the overall memory hierarchy performance by tracking the data read miss patterns of memory accesses, developing a prediction for the next access and prefetching the data into the faster cache memory...

  19. Holland Type as a Moderator of Personality-Performance Predictions.

    Science.gov (United States)

    Fritzsche, Barbara A.; McIntire, Sandra A.; Yost, Amy Powell

    2002-01-01

    Data from 559 undergraduates provided modest evidence that Holland's taxonomy of work environments moderated the relationship between personality and performance. The traits of agreeableness and conscientiousness were better predictors of performance in certain environments. The important relationship between personality and performance may be…

  20. The trickle-down effect of predictability: Secondary task performance benefits from predictability in the primary task.

    Directory of Open Access Journals (Sweden)

    Magdalena Ewa Król

    Full Text Available Predictions optimize processing by reducing attentional resources allocation to expected or predictable sensory data. Our study demonstrates that these saved processing resources can be then used on concurrent stimuli, and in consequence improve their processing and encoding. We illustrate this "trickle-down" effect with a dual task, where the primary task varied in terms of predictability. The primary task involved detection of a pre-specified symbol that appeared at some point of a short video of a dot moving along a random, semi-predictable or predictable trajectory. The concurrent secondary task involved memorization of photographs representing either emotionally neutral or non-neutral (social or threatening content. Performance in the secondary task was measured by a memory test. We found that participants allocated more attention to unpredictable (random and semi-predictable stimuli than to predictable stimuli. Additionally, when the stimuli in the primary task were more predictable, participants performed better in the secondary task, as evidenced by higher sensitivity in the memory test. Finally, social or threatening stimuli were allocated more "looking time" and a larger number of saccades than neutral stimuli. This effect was stronger for the threatening stimuli than social stimuli. Thus, predictability of environmental input is used in optimizing the allocation of attentional resources, which trickles-down and benefits the processing of concurrent stimuli.

  1. The trickle-down effect of predictability: Secondary task performance benefits from predictability in the primary task.

    Science.gov (United States)

    Król, Magdalena Ewa; Król, Michał

    2017-01-01

    Predictions optimize processing by reducing attentional resources allocation to expected or predictable sensory data. Our study demonstrates that these saved processing resources can be then used on concurrent stimuli, and in consequence improve their processing and encoding. We illustrate this "trickle-down" effect with a dual task, where the primary task varied in terms of predictability. The primary task involved detection of a pre-specified symbol that appeared at some point of a short video of a dot moving along a random, semi-predictable or predictable trajectory. The concurrent secondary task involved memorization of photographs representing either emotionally neutral or non-neutral (social or threatening) content. Performance in the secondary task was measured by a memory test. We found that participants allocated more attention to unpredictable (random and semi-predictable) stimuli than to predictable stimuli. Additionally, when the stimuli in the primary task were more predictable, participants performed better in the secondary task, as evidenced by higher sensitivity in the memory test. Finally, social or threatening stimuli were allocated more "looking time" and a larger number of saccades than neutral stimuli. This effect was stronger for the threatening stimuli than social stimuli. Thus, predictability of environmental input is used in optimizing the allocation of attentional resources, which trickles-down and benefits the processing of concurrent stimuli.

  2. Flow Simulation and Performance Prediction of Centrifugal Pumps ...

    African Journals Online (AJOL)

    With the aid of computational fluid dynamics, the complex internal flows in water pump impellers can be well predicted, thus facilitating the product development process of pumps. In this paper a commercial CFD code was used to solve the governing equations of the flow field. A 2-D simulation of turbulent fluid flow is ...

  3. Next-Term Student Performance Prediction: A Recommender Systems Approach

    Science.gov (United States)

    Sweeney, Mack; Rangwala, Huzefa; Lester, Jaime; Johri, Aditya

    2016-01-01

    An enduring issue in higher education is student retention to successful graduation. National statistics indicate that most higher education institutions have four-year degree completion rates around 50%, or just half of their student populations. While there are prediction models which illuminate what factors assist with college student success,…

  4. Predicting Student Performance in a Collaborative Learning Environment

    Science.gov (United States)

    Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol

    2015-01-01

    Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

  5. Selection procedures in sports: Improving predictions of athletes’ future performance

    NARCIS (Netherlands)

    den Hartigh, Jan Rudolf; Niessen, Anna; Frencken, Wouter; Meijer, Rob R.

    The selection of athletes has been a central topic in sports sciences for decades. Yet, little consideration has been given to the theoretical underpinnings and predictive validity of the procedures. In this paper, we evaluate current selection procedures in sports given what we know from the

  6. Performance prediction model for distributed applications on multicore clusters

    CSIR Research Space (South Africa)

    Khanyile, NP

    2012-07-01

    Full Text Available discusses some of the short comings of this law in the current age. We propose a theoretical model for predicting the behavior of a distributed algorithm given the network restrictions of the cluster used. The paper focuses on the impact of latency...

  7. Performance of immunological response in predicting virological failure.

    Science.gov (United States)

    Ingole, Nayana; Mehta, Preeti; Pazare, Amar; Paranjpe, Supriya; Sarkate, Purva

    2013-03-01

    In HIV-infected individuals on antiretroviral therapy (ART), the decision on when to switch from first-line to second-line therapy is dictated by treatment failure, and this can be measured in three ways: clinically, immunologically, and virologically. While viral load (VL) decreases and CD4 cell increases typically occur together after starting ART, discordant responses may be seen. Hence the current study was designed to determine the immunological and virological response to ART and to evaluate the utility of immunological response to predict virological failure. All treatment-naive HIV-positive individuals aged >18 years who were eligible for ART were enrolled and assessed at baseline, 6 months, and 12 months clinically and by CD4 cell count and viral load estimations. The patients were categorized as showing concordant favorable (CF), immunological only (IO), virological only (VO), and concordant unfavorable responses (CU). The efficiency of immunological failure to predict virological failure was analyzed across various levels of virological failure (VL>50, >500, and >5,000 copies/ml). At 6 months, 87(79.81%), 7(5.5%), 13 (11.92%), and 2 (1.83%) patients and at 12 months 61(69.3%), 9(10.2%), 16 (18.2%), and 2 (2.3%) patients had CF, IO, VO, and CU responses, respectively. Immunological failure criteria had a very low sensitivity (11.1-40%) and positive predictive value (8.3-25%) to predict virological failure. Immunological criteria do not accurately predict virological failure resulting in significant misclassification of therapeutic responses. There is an urgent need for inclusion of viral load testing in the initiation and monitoring of ART.

  8. Assessing Discriminative Performance at External Validation of Clinical Prediction Models.

    Directory of Open Access Journals (Sweden)

    Daan Nieboer

    Full Text Available External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting.We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1 the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2 the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury.The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples and heterogeneous in scenario 2 (in 17%-39% of simulated samples. Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2.The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients.

  9. Dataset size and composition impact the reliability of performance benchmarks for peptide-MHC binding predictions

    DEFF Research Database (Denmark)

    Kim, Yohan; Sidney, John; Buus, Søren

    2014-01-01

    Background: It is important to accurately determine the performance of peptide: MHC binding predictions, as this enables users to compare and choose between different prediction methods and provides estimates of the expected error rate. Two common approaches to determine prediction performance...... are cross-validation, in which all available data are iteratively split into training and testing data, and the use of blind sets generated separately from the data used to construct the predictive method. In the present study, we have compared cross-validated prediction performances generated on our last...

  10. Computational Model-Based Prediction of Human Episodic Memory Performance Based on Eye Movements

    Science.gov (United States)

    Sato, Naoyuki; Yamaguchi, Yoko

    Subjects' episodic memory performance is not simply reflected by eye movements. We use a ‘theta phase coding’ model of the hippocampus to predict subjects' memory performance from their eye movements. Results demonstrate the ability of the model to predict subjects' memory performance. These studies provide a novel approach to computational modeling in the human-machine interface.

  11. Predicting Performance of a Face Recognition System Based on Image Quality

    NARCIS (Netherlands)

    Dutta, A.

    2015-01-01

    In this dissertation, we focus on several aspects of models that aim to predict performance of a face recognition system. Performance prediction models are commonly based on the following two types of performance predictor features: a) image quality features; and b) features derived solely from

  12. Knowledge Tracing and Prediction of Future Trainee Performance

    National Research Council Canada - National Science Library

    Jastrzembski, Tiffany S; Gluck, Kevin A; Gunzelmann, Glenn

    2006-01-01

    ...). This model represents the system's estimate of the student's current knowledge or skill level, established from a performance history. Knowledge tracing (Aleven & Koedinger, 2002; Anderson, Conrad, & Corbett, 1989...

  13. Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan

    Directory of Open Access Journals (Sweden)

    Senol Celik

    Full Text Available ABSTRACT The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF in biometrical data of Mengali rams. To compare the predictive capability of the algorithms, the biometrical data regarding body (body length, withers height, and heart girth and testicular (testicular length, scrotal length, and scrotal circumference measurements of Mengali rams in predicting live body weight were evaluated by most goodness of fit criteria. In addition, age was considered as a continuous independent variable. In this context, MARS data mining algorithm was used for the first time to predict body weight in two forms, without (MARS_1 and with interaction (MARS_2 terms. The superiority order in the predictive accuracy of the algorithms was found as CART > CHAID ≈ Exhaustive CHAID > MARS_2 > MARS_1 > RBF > MLP. Moreover, all tested algorithms provided a strong predictive accuracy for estimating body weight. However, MARS is the only algorithm that generated a prediction equation for body weight. Therefore, it is hoped that the available results might present a valuable contribution in terms of predicting body weight and describing the relationship between the body weight and body and testicular measurements in revealing breed standards and the conservation of indigenous gene sources for Mengali sheep breeding. Therefore, it will be possible to perform more profitable and productive sheep production. Use of data mining algorithms is useful for revealing the relationship between body weight and testicular traits in describing breed standards of Mengali sheep.

  14. Experiments on the Performance of Small Horizontal Axis Wind Turbine with Passive Pitch Control by Disk Pulley

    Directory of Open Access Journals (Sweden)

    Yu-Jen Chen

    2016-05-01

    Full Text Available The present work is to design a passive pitch-control mechanism for small horizontal axis wind turbine (HAWT to generate stable power at high wind speeds. The mechanism uses a disk pulley as an actuator to passively adjust the pitch angle of blades by centrifugal force. For this design, aerodynamic braking is caused by the adjustment of pitch angles at high wind speeds. As a marked advantage, this does not require mechanical brakes that would incur electrical burn-out and structural failure under high speed rotation. This can ensure the survival of blades and generator in sever operation environments. In this paper, the analysis uses blade element momentum theory (BEMT to develop graphical user interface software to facilitate the performance assessment of the small-scale HAWT using passive pitch control (PPC. For verification, the HAWT system was tested in a full-scale wind tunnel for its aerodynamic performance. At low wind speeds, this system performed the same as usual, yet at high wind speeds, the equipped PPC system can effectively reduce the rotational speed to generate stable power.

  15. A unified tool for performance modelling and prediction

    International Nuclear Information System (INIS)

    Gilmore, Stephen; Kloul, Leila

    2005-01-01

    We describe a novel performability modelling approach, which facilitates the efficient solution of performance models extracted from high-level descriptions of systems. The notation which we use for our high-level designs is the Unified Modelling Language (UML) graphical modelling language. The technology which provides the efficient representation capability for the underlying performance model is the multi-terminal binary decision diagram (MTBDD)-based PRISM probabilistic model checker. The UML models are compiled through an intermediate language, the stochastic process algebra PEPA, before translation into MTBDDs for solution. We illustrate our approach on a real-world analysis problem from the domain of mobile telephony

  16. Frequency weighted model predictive control of wind turbine

    DEFF Research Database (Denmark)

    Klauco, Martin; Poulsen, Niels Kjølstad; Mirzaei, Mahmood

    2013-01-01

    This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work are the rotatio...... predictive controller are presented. Statistical comparison between frequency weighted MPC, standard MPC and baseline PI controller is shown as well.......This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work...... are the rotational degree of freedom of the rotor and the tower for-aft movement. The MPC design is based on a receding horizon policy and a linearised model of the wind turbine. Due to the change of dynamics according to wind speed, several linearisation points must be considered and the control design adjusted...

  17. Prediction of polymer flooding performance using an analytical method

    International Nuclear Information System (INIS)

    Tan Czek Hoong; Mariyamni Awang; Foo Kok Wai

    2001-01-01

    The study investigated the applicability of an analytical method developed by El-Khatib in polymer flooding. Results from a simulator UTCHEM and experiments were compared with the El-Khatib prediction method. In general, by assuming a constant viscosity polymer injection, the method gave much higher recovery values than the simulation runs and the experiments. A modification of the method gave better correlation, albeit only oil production. Investigation is continuing on modifying the method so that a better overall fit can be obtained for polymer flooding. (Author)

  18. IT infrastructure and competitive aggressiveness in explaining and predicting performance

    NARCIS (Netherlands)

    Ajamieh, Aseel; Benitez, Jose; Braojos, Jessica; Gelhard, Carsten Volker

    2016-01-01

    While prior Information Systems and Operations Management literature emphasizes the role of both the firm's IT infrastructure and the general degree of competition as antecedents of firm performance, the organizational capabilities that mediate these important relationships remain undetermined.

  19. Utilizing Lab Tests to Predict Asphalt Concrete Overlay Performance

    Science.gov (United States)

    2017-12-01

    A series of five experimental projects and three demonstration projects were constructed to better understand the performance of pavement overlays using various levels of asphalt binder replacement (ABR) from reclaimed asphalt pavement (RAP), recycle...

  20. Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

    Science.gov (United States)

    Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

    2014-01-01

    This presentation describes the capabilities of three-dimensional thermal power model of advanced stirling radioisotope generator (ASRG). The performance of the ASRG is presented for different scenario, such as Venus flyby with or without the auxiliary cooling system.

  1. SKread predicts handwriting performance in patients with low vision.

    Science.gov (United States)

    Downes, Ken; Walker, Laura L; Fletcher, Donald C

    2015-06-01

    To assess whether performance on the Smith-Kettlewell Reading (SKread) test is a reliable predictor of handwriting performance in patients with low vision. Cross-sectional study. Sixty-six patients at their initial low-vision rehabilitation evaluation. The patients completed all components of a routine low-vision appointment including logMAR acuity, performed the SKread test, and performed a handwriting task. Patients were timed while performing each task and their accuracy was recorded. The handwriting task was performed by having patients write 5 5-letter words into sets of boxes where each letter is separated by a box. The boxes were 15 × 15 mm, and accuracy was scored with 50 points possible from 25 letters: 1 point for each letter within the confines of a box and 1 point if the letter was legible. Correlation analysis was then performed. Median age of participants was 84 (range 54-97) years. Fifty-seven patients (86%) had age-related macular degeneration or some other maculopathy, whereas 9 patients (14%) had visual impairment from media opacity or neurologic impairment. Median Early Treatment Diabetic Retinopathy Study acuity was 20/133 (range 20/22 to 20/1000), and median logMAR acuity was 0.82 (range 0.04-1.70). SKread errors per block correlated with logMAR acuity (r = 0.6), and SKread time per block correlated with logMAR acuity (r = 0.51). SKread errors per block correlated with handwriting task time/accuracy ratio (r = 0.61). SKread time per block correlated with handwriting task time/accuracy ratio (r = 0.7). LogMAR acuity score correlated with handwriting task time/accuracy ratio (r = 0.42). All p values were handwriting performance in patients with low vision better than logMAR acuity. Copyright © 2015 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.

  2. Working memory in children predicts performance on a gambling task.

    Science.gov (United States)

    Audusseau, Jean; Juhel, Jacques

    2015-01-01

    The authors investigated whether working memory (WM) plays a significant role in the development of decision making in children, operationalized by the Children's Gambling Task (CGT). A total of 105 children aged 6-7, 8-9, and 10-11 years old carried out the CGT. Children aged 6-7 years old were found to have a lower performance than older children, which shows that the CGT is sensitive to participant's age. The hypothesis that WM plays a significant role in decision making was then tested following two approaches: (a) an experimental approach, comparing between groups the performance on the CGT in a control condition (the CGT only was administered) to that in a double task condition (participants had to carry out a recall task in addition to the CGT); (b) an interindividual approach, probing the relationship between CGT performance and performance on tasks measuring WM efficiency. The between-groups approach evidenced a better performance in the control group. Moreover, the interindividual approach showed that the higher the participants' WM efficiency was, the higher their performance in the CGT was. Taken together, these two approaches yield converging results that support the hypothesis that WM plays a significant role in decision making in children.

  3. Predicting Subsequent Task Performance From Goal Motivation and Goal Failure

    Directory of Open Access Journals (Sweden)

    Laura Catherine Healy

    2015-07-01

    Full Text Available Recent research has demonstrated that the cognitive processes associated with goal pursuit can continue to interfere with unrelated tasks when a goal is unfulfilled. Drawing from the self-regulation and goal-striving literatures, the present study explored the impact of goal failure on subsequent cognitive and physical task performance. Furthermore, we examined if the autonomous or controlled motivation underpinning goal striving moderates the responses to goal failure. Athletes (75 male, 59 female, Mage = 19.90 years, SDage = 3.50 completed a cycling trial with the goal of covering a given distance in 8 minutes. Prior to the trial, their motivation was primed using a video. During the trial they were provided with manipulated performance feedback, thus creating conditions of goal success or failure. No differences emerged in the responses to goal failure between the primed motivation or performance feedback conditions. We make recommendations for future research into how individuals can deal with failure in goal striving.

  4. Sensorimotor abilities predict on-field performance in professional baseball.

    Science.gov (United States)

    Burris, Kyle; Vittetoe, Kelly; Ramger, Benjamin; Suresh, Sunith; Tokdar, Surya T; Reiter, Jerome P; Appelbaum, L Gregory

    2018-01-08

    Baseball players must be able to see and react in an instant, yet it is hotly debated whether superior performance is associated with superior sensorimotor abilities. In this study, we compare sensorimotor abilities, measured through 8 psychomotor tasks comprising the Nike Sensory Station assessment battery, and game statistics in a sample of 252 professional baseball players to evaluate the links between sensorimotor skills and on-field performance. For this purpose, we develop a series of Bayesian hierarchical latent variable models enabling us to compare statistics across professional baseball leagues. Within this framework, we find that sensorimotor abilities are significant predictors of on-base percentage, walk rate and strikeout rate, accounting for age, position, and league. We find no such relationship for either slugging percentage or fielder-independent pitching. The pattern of results suggests performance contributions from both visual-sensory and visual-motor abilities and indicates that sensorimotor screenings may be useful for player scouting.

  5. Predicted performance of an integrated modular engine system

    Science.gov (United States)

    Binder, Michael; Felder, James L.

    1993-01-01

    Space vehicle propulsion systems are traditionally comprised of a cluster of discrete engines, each with its own set of turbopumps, valves, and a thrust chamber. The Integrated Modular Engine (IME) concept proposes a vehicle propulsion system comprised of multiple turbopumps, valves, and thrust chambers which are all interconnected. The IME concept has potential advantages in fault-tolerance, weight, and operational efficiency compared with the traditional clustered engine configuration. The purpose of this study is to examine the steady-state performance of an IME system with various components removed to simulate fault conditions. An IME configuration for a hydrogen/oxygen expander cycle propulsion system with four sets of turbopumps and eight thrust chambers has been modeled using the Rocket Engine Transient Simulator (ROCETS) program. The nominal steady-state performance is simulated, as well as turbopump thrust chamber and duct failures. The impact of component failures on system performance is discussed in the context of the system's fault tolerant capabilities.

  6. Methodologies for predicting the part-load performance of aero-derivative gas turbines

    DEFF Research Database (Denmark)

    Haglind, Fredrik; Elmegaard, Brian

    2009-01-01

    Prediction of the part-load performance of gas turbines is advantageous in various applications. Sometimes reasonable part-load performance is sufficient, while in other cases complete agreement with the performance of an existing machine is desirable. This paper is aimed at providing some guidance...... on methodologies for predicting part-load performance of aero-derivative gas turbines. Two different design models – one simple and one more complex – are created. Subsequently, for each of these models, the part-load performance is predicted using component maps and turbine constants, respectively. Comparisons...... with manufacturer data are made. With respect to the design models, the simple model, featuring a compressor, combustor and turbines, results in equally good performance prediction in terms of thermal efficiency and exhaust temperature as does a more complex model. As for part-load predictions, the results suggest...

  7. Performance prediction of industrial centrifuges using scale-down models.

    Science.gov (United States)

    Boychyn, M; Yim, S S S; Bulmer, M; More, J; Bracewell, D G; Hoare, M

    2004-12-01

    Computational fluid dynamics was used to model the high flow forces found in the feed zone of a multichamber-bowl centrifuge and reproduce these in a small, high-speed rotating disc device. Linking the device to scale-down centrifugation, permitted good estimation of the performance of various continuous-flow centrifuges (disc stack, multichamber bowl, CARR Powerfuge) for shear-sensitive protein precipitates. Critically, the ultra scale-down centrifugation process proved to be a much more accurate predictor of production multichamber-bowl performance than was the pilot centrifuge.

  8. Financial performance evaluation and bankruptcy prediction (failure1

    Directory of Open Access Journals (Sweden)

    Talal A. Al-Kassar, Dr.

    2014-10-01

    The research also demonstrates the need to include measures of both financial and non-financial performance in the evaluation as they complement each other. Without both financial and non-financial, the evaluation process is incomplete and does not provide desired results or the correct image of the process. The research suggests including comprehensive measures of performance evaluation of projects by using indicators of adopted criteria. Thus, the application of both models leads to better results and assists users in maintaining greater objectivity while obtaining more accurate results than from analysis based on personal evaluation alone.

  9. Nonlinear Dynamic Inversion Baseline Control Law: Architecture and Performance Predictions

    Science.gov (United States)

    Miller, Christopher J.

    2011-01-01

    A model reference dynamic inversion control law has been developed to provide a baseline control law for research into adaptive elements and other advanced flight control law components. This controller has been implemented and tested in a hardware-in-the-loop simulation; the simulation results show excellent handling qualities throughout the limited flight envelope. A simple angular momentum formulation was chosen because it can be included in the stability proofs for many basic adaptive theories, such as model reference adaptive control. Many design choices and implementation details reflect the requirements placed on the system by the nonlinear flight environment and the desire to keep the system as basic as possible to simplify the addition of the adaptive elements. Those design choices are explained, along with their predicted impact on the handling qualities.

  10. Translation Ambiguity but Not Word Class Predicts Translation Performance

    Science.gov (United States)

    Prior, Anat; Kroll, Judith F.; Macwhinney, Brian

    2013-01-01

    We investigated the influence of word class and translation ambiguity on cross-linguistic representation and processing. Bilingual speakers of English and Spanish performed translation production and translation recognition tasks on nouns and verbs in both languages. Words either had a single translation or more than one translation. Translation…

  11. Predictive Performance Tuning of OpenACC Accelerated Applications

    KAUST Repository

    Siddiqui, Shahzeb; Feki, Saber

    2014-01-01

    , with the introduction of high level programming models such as OpenACC [1] and OpenMP 4.0 [2], these devices are becoming more accessible and practical to use by a larger scientific community. However, performance optimization of OpenACC accelerated applications usually

  12. Predicting Performance Under Acute Stress : The Role of Individual Characteristics

    NARCIS (Netherlands)

    Delahaij, R.; Dam, K. van; Gaillard, A.W.K.; Soeters, J.

    2011-01-01

    This prospective study examined how differences in coping style, coping self-efficacy, and metacognitive awareness influence coping behavior and performance during a realistic acute stressful exercise in 2 military samples (n = 122 and n = 132). Results showed that coping self-efficacy and coping

  13. Goal orientations predict academic performance beyond intelligence and personality

    NARCIS (Netherlands)

    Steinmayr, R.; Bipp, T.; Spinath, B.

    2011-01-01

    Goal orientations are thought to be an important predictor of scholastic achievement. The present paper investigated the joint influence of goal orientations, intelligence, and personality on school performance in a sample of N = 520 11th and 12th graders (303 female; mean age M = 16.94 years).

  14. Fine-motor skills testing and prediction of endovascular performance

    DEFF Research Database (Denmark)

    Bech, Bo; Lönn, Lars; Schroeder, Torben V

    2013-01-01

    Performing endovascular procedures requires good control of fine-motor digital movements and hand-eye coordination. Objective assessment of such skills is difficult. Trainees acquire control of catheter/wire movements at various paces. However, little is known to what extent talent plays for novice...

  15. Competitive Learning Neural Network Ensemble Weighted by Predicted Performance

    Science.gov (United States)

    Ye, Qiang

    2010-01-01

    Ensemble approaches have been shown to enhance classification by combining the outputs from a set of voting classifiers. Diversity in error patterns among base classifiers promotes ensemble performance. Multi-task learning is an important characteristic for Neural Network classifiers. Introducing a secondary output unit that receives different…

  16. Predicting timing performance of advanced mechatronics control systems

    NARCIS (Netherlands)

    Voeten, J.P.M.; Hendriks, T.; Theelen, B.D.; Schuddemat, J.; Tabingh Suermondt, W.; Gemei, J.; Kotterink, C.; Huet, van J.; Eichler, G.; Kuepper, A.; Schau, V.; Fouchal, H.; Unger, H.

    2011-01-01

    Embedded control is a key product technology differentiator for many high-tech industries, including ASML. The strong increase in complexity of embedded control systems, combined with the occurrence of late changes in control requirements, results in many timing performance problems showing up only

  17. Students' Metacomprehension Knowledge: Components That Predict Comprehension Performance

    Science.gov (United States)

    Zabrucky, Karen M.; Moore, DeWayne; Agler, Lin-Miao Lin; Cummings, Andrea M.

    2015-01-01

    In the present study, we assessed students' metacomprehension knowledge and examined the components of knowledge most related to comprehension of expository texts. We used the Revised Metacomprehension Scale (RMCS) to investigate the relations between students' metacomprehension knowledge and comprehension performance. Students who evaluated and…

  18. Adult age differences in predicting memory performance: the effects of normative information and task experience.

    Science.gov (United States)

    McDonald-Miszczak, L; Hunter, M A; Hultsch, D F

    1994-03-01

    Two experiments addressed the effects of task information and experience on younger and older adults' ability to predict their memory for words. The first study examined the effects of normative task information on subjects' predictions for 30-word lists across three trials. The second study looked at the effects of making predictions and recalling either an easy (15) or a difficult (45) word list prior to making predictions and recalling a moderately difficult (30) word list. The results from both studies showed that task information and experience affected subjects' predictions and that elderly adults predicted their performance more accurately than younger adults.

  19. Mean platelet volume (MPV) predicts middle distance running performance.

    Science.gov (United States)

    Lippi, Giuseppe; Salvagno, Gian Luca; Danese, Elisa; Skafidas, Spyros; Tarperi, Cantor; Guidi, Gian Cesare; Schena, Federico

    2014-01-01

    Running economy and performance in middle distance running depend on several physiological factors, which include anthropometric variables, functional characteristics, training volume and intensity. Since little information is available about hematological predictors of middle distance running time, we investigated whether some hematological parameters may be associated with middle distance running performance in a large sample of recreational runners. The study population consisted in 43 amateur runners (15 females, 28 males; median age 47 years), who successfully concluded a 21.1 km half-marathon at 75-85% of their maximal aerobic power (VO2max). Whole blood was collected 10 min before the run started and immediately thereafter, and hematological testing was completed within 2 hours after sample collection. The values of lymphocytes and eosinophils exhibited a significant decrease compared to pre-run values, whereas those of mean corpuscular volume (MCV), platelets, mean platelet volume (MPV), white blood cells (WBCs), neutrophils and monocytes were significantly increased after the run. In univariate analysis, significant associations with running time were found for pre-run values of hematocrit, hemoglobin, mean corpuscular hemoglobin (MCH), red blood cell distribution width (RDW), MPV, reticulocyte hemoglobin concentration (RetCHR), and post-run values of MCH, RDW, MPV, monocytes and RetCHR. In multivariate analysis, in which running time was entered as dependent variable whereas age, sex, blood lactate, body mass index, VO2max, mean training regimen and the hematological parameters significantly associated with running performance in univariate analysis were entered as independent variables, only MPV values before and after the trial remained significantly associated with running time. After adjustment for platelet count, the MPV value before the run (p = 0.042), but not thereafter (p = 0.247), remained significantly associated with running

  20. Mean platelet volume (MPV predicts middle distance running performance.

    Directory of Open Access Journals (Sweden)

    Giuseppe Lippi

    Full Text Available Running economy and performance in middle distance running depend on several physiological factors, which include anthropometric variables, functional characteristics, training volume and intensity. Since little information is available about hematological predictors of middle distance running time, we investigated whether some hematological parameters may be associated with middle distance running performance in a large sample of recreational runners.The study population consisted in 43 amateur runners (15 females, 28 males; median age 47 years, who successfully concluded a 21.1 km half-marathon at 75-85% of their maximal aerobic power (VO2max. Whole blood was collected 10 min before the run started and immediately thereafter, and hematological testing was completed within 2 hours after sample collection.The values of lymphocytes and eosinophils exhibited a significant decrease compared to pre-run values, whereas those of mean corpuscular volume (MCV, platelets, mean platelet volume (MPV, white blood cells (WBCs, neutrophils and monocytes were significantly increased after the run. In univariate analysis, significant associations with running time were found for pre-run values of hematocrit, hemoglobin, mean corpuscular hemoglobin (MCH, red blood cell distribution width (RDW, MPV, reticulocyte hemoglobin concentration (RetCHR, and post-run values of MCH, RDW, MPV, monocytes and RetCHR. In multivariate analysis, in which running time was entered as dependent variable whereas age, sex, blood lactate, body mass index, VO2max, mean training regimen and the hematological parameters significantly associated with running performance in univariate analysis were entered as independent variables, only MPV values before and after the trial remained significantly associated with running time. After adjustment for platelet count, the MPV value before the run (p = 0.042, but not thereafter (p = 0.247, remained significantly associated with running

  1. Utilizing Machine Learning and Automated Performance Metrics to Evaluate Robot-Assisted Radical Prostatectomy Performance and Predict Outcomes.

    Science.gov (United States)

    Hung, Andrew J; Chen, Jian; Che, Zhengping; Nilanon, Tanachat; Jarc, Anthony; Titus, Micha; Oh, Paul J; Gill, Inderbir S; Liu, Yan

    2018-05-01

    Surgical performance is critical for clinical outcomes. We present a novel machine learning (ML) method of processing automated performance metrics (APMs) to evaluate surgical performance and predict clinical outcomes after robot-assisted radical prostatectomy (RARP). We trained three ML algorithms utilizing APMs directly from robot system data (training material) and hospital length of stay (LOS; training label) (≤2 days and >2 days) from 78 RARP cases, and selected the algorithm with the best performance. The selected algorithm categorized the cases as "Predicted as expected LOS (pExp-LOS)" and "Predicted as extended LOS (pExt-LOS)." We compared postoperative outcomes of the two groups (Kruskal-Wallis/Fisher's exact tests). The algorithm then predicted individual clinical outcomes, which we compared with actual outcomes (Spearman's correlation/Fisher's exact tests). Finally, we identified five most relevant APMs adopted by the algorithm during predicting. The "Random Forest-50" (RF-50) algorithm had the best performance, reaching 87.2% accuracy in predicting LOS (73 cases as "pExp-LOS" and 5 cases as "pExt-LOS"). The "pExp-LOS" cases outperformed the "pExt-LOS" cases in surgery time (3.7 hours vs 4.6 hours, p = 0.007), LOS (2 days vs 4 days, p = 0.02), and Foley duration (9 days vs 14 days, p = 0.02). Patient outcomes predicted by the algorithm had significant association with the "ground truth" in surgery time (p algorithm in predicting, were largely related to camera manipulation. To our knowledge, ours is the first study to show that APMs and ML algorithms may help assess surgical RARP performance and predict clinical outcomes. With further accrual of clinical data (oncologic and functional data), this process will become increasingly relevant and valuable in surgical assessment and training.

  2. A Bayesian Performance Prediction Model for Mathematics Education: A Prototypical Approach for Effective Group Composition

    Science.gov (United States)

    Bekele, Rahel; McPherson, Maggie

    2011-01-01

    This research work presents a Bayesian Performance Prediction Model that was created in order to determine the strength of personality traits in predicting the level of mathematics performance of high school students in Addis Ababa. It is an automated tool that can be used to collect information from students for the purpose of effective group…

  3. Simplified Predictive Models for CO2 Sequestration Performance Assessment

    Science.gov (United States)

    Mishra, Srikanta; RaviGanesh, Priya; Schuetter, Jared; Mooney, Douglas; He, Jincong; Durlofsky, Louis

    2014-05-01

    We present results from an ongoing research project that seeks to develop and validate a portfolio of simplified modeling approaches that will enable rapid feasibility and risk assessment for CO2 sequestration in deep saline formation. The overall research goal is to provide tools for predicting: (a) injection well and formation pressure buildup, and (b) lateral and vertical CO2 plume migration. Simplified modeling approaches that are being developed in this research fall under three categories: (1) Simplified physics-based modeling (SPM), where only the most relevant physical processes are modeled, (2) Statistical-learning based modeling (SLM), where the simulator is replaced with a "response surface", and (3) Reduced-order method based modeling (RMM), where mathematical approximations reduce the computational burden. The system of interest is a single vertical well injecting supercritical CO2 into a 2-D layered reservoir-caprock system with variable layer permeabilities. In the first category (SPM), we use a set of well-designed full-physics compositional simulations to understand key processes and parameters affecting pressure propagation and buoyant plume migration. Based on these simulations, we have developed correlations for dimensionless injectivity as a function of the slope of fractional-flow curve, variance of layer permeability values, and the nature of vertical permeability arrangement. The same variables, along with a modified gravity number, can be used to develop a correlation for the total storage efficiency within the CO2 plume footprint. In the second category (SLM), we develop statistical "proxy models" using the simulation domain described previously with two different approaches: (a) classical Box-Behnken experimental design with a quadratic response surface fit, and (b) maximin Latin Hypercube sampling (LHS) based design with a Kriging metamodel fit using a quadratic trend and Gaussian correlation structure. For roughly the same number of

  4. Ski jump takeoff performance predictions for a mixed-flow, remote-lift STOVL aircraft

    Science.gov (United States)

    Birckelbaw, Lourdes G.

    1992-01-01

    A ski jump model was developed to predict ski jump takeoff performance for a short takeoff and vertical landing (STOVL) aircraft. The objective was to verify the model with results from a piloted simulation of a mixed flow, remote lift STOVL aircraft. The prediction model is discussed. The predicted results are compared with the piloted simulation results. The ski jump model can be utilized for basic research of other thrust vectoring STOVL aircraft performing a ski jump takeoff.

  5. Evaluation and prediction of the performance of positive displacement motor

    Energy Technology Data Exchange (ETDEWEB)

    Tudor, R.; Ginzburg, L. [Canadian Fracmaster Ltd., Calgary, AB (Canada); Xu, H. [Japan National Oil Corp (Japan); Li, J.; Robello, G.; Grigor, C.

    1998-12-31

    Test results of positive displacement motors (PDMs) collected by using various PDMs from a number of different suppliers have been analyzed. Various correlations have been developed and motor performance pumped with incompressible drilling fluid was evaluated based on test data provided by suppliers in the form of pressure drop versus torque output. Conclusions drawn from the study suggest that when a motor is operated at less than full load, the correlation between mechanical power and hydraulic power across the PDM power section can be described with a simple linear equation (different for each PDM type). Assuming the availability of patented geometric information for each PDM type, the performance of PDMs can be described by both the geometric parameters of the motor and the rheological properties of the circulation fluid. 9 refs., 8 figs.

  6. Revised MITG design, fabrication procedure, and performance predictions

    International Nuclear Information System (INIS)

    Schock, A.

    1983-01-01

    The design, analysis, and key features of the Modular Isotopic Thermoelectric Generator (MITG) were described in a 1981 IECEC paper; and the design, fabrication, testing, and post-test analysis of test assemblies simulating prototypical MITG modules were described in preceding papers in these proceedings. These analyses succeeded in identifying and explaining the principal causes of thermal-stress problems encountered in the tests, and in confirming the effectiveness of design changes for alleviating them. The present paper presents additional design improvements for solving these and other problems, and describes new thermoelectric material properties generated by independent laboratories over the past two years. Based on these changes and on a revised fabrication procedure, it presents a reoptimization of the MITG design and computes the power-to-weight ratio for the revised design. That ratio is appreciably lower than the 1981 prediction, primarily because of changes in material properties; but it is still much higher than the specific power of current-generation RTGs

  7. Research of performance prediction to energy on hydraulic turbine

    International Nuclear Information System (INIS)

    Quan, H; Li, R N; Li, Q F; Han, W; Su, Q M

    2012-01-01

    Refer to the low specific speed Francis turbine blade design principle and double-suction pump structure. Then, design a horizontal double-channel hydraulic turbine Francis. Through adding different guide vane airfoil and and no guide vane airfoil on the hydraulic conductivity components to predict hydraulic turbine energy and using Fluent software to numerical simulation that the operating conditions and point. The results show that the blade pressure surface and suction surface pressure is low when the hydraulic turbine installation is added standard positive curvature of the guide vane and modified positive curvature of guide vane. Therefore, the efficiency of energy recovery is low. However, the pressure of negative curvature guide vane and symmetric guide vane added on hydraulic turbine installations is larger than that of the former ones, and it is conducive to working of runner. With the decreasing of guide vane opening, increasing of inlet angle, flow state gets significantly worse. Then, others obvious phenomena are that the reflux and horizontal flow appeared in blade pressure surface. At the same time, the vortex was formed in Leaf Road, leading to the loss of energy. Through analyzing the distribution of pressure, velocity, flow lines of over-current flow in the the back hydraulic conductivity components in above programs we can known that the hydraulic turbine installation added guide vane is more reasonable than without guide vanes, it is conducive to improve efficiency of energy conversion.

  8. Performance predictions affect attentional processes of event-based prospective memory.

    Science.gov (United States)

    Rummel, Jan; Kuhlmann, Beatrice G; Touron, Dayna R

    2013-09-01

    To investigate whether making performance predictions affects prospective memory (PM) processing, we asked one group of participants to predict their performance in a PM task embedded in an ongoing task and compared their performance with a control group that made no predictions. A third group gave not only PM predictions but also ongoing-task predictions. Exclusive PM predictions resulted in slower ongoing-task responding both in a nonfocal (Experiment 1) and in a focal (Experiment 2) PM task. Only in the nonfocal task was the additional slowing accompanied by improved PM performance. Even in the nonfocal task, however, was the correlation between ongoing-task speed and PM performance reduced after predictions, suggesting that the slowing was not completely functional for PM. Prediction-induced changes could be avoided by asking participants to additionally predict their performance in the ongoing task. In sum, the present findings substantiate a role of metamemory for attention-allocation strategies of PM. Copyright © 2013 Elsevier Inc. All rights reserved.

  9. Cognition and procedure representational requirements for predictive human performance models

    Science.gov (United States)

    Corker, K.

    1992-01-01

    Models and modeling environments for human performance are becoming significant contributors to early system design and analysis procedures. Issues of levels of automation, physical environment, informational environment, and manning requirements are being addressed by such man/machine analysis systems. The research reported here investigates the close interaction between models of human cognition and models that described procedural performance. We describe a methodology for the decomposition of aircrew procedures that supports interaction with models of cognition on the basis of procedures observed; that serves to identify cockpit/avionics information sources and crew information requirements; and that provides the structure to support methods for function allocation among crew and aiding systems. Our approach is to develop an object-oriented, modular, executable software representation of the aircrew, the aircraft, and the procedures necessary to satisfy flight-phase goals. We then encode in a time-based language, taxonomies of the conceptual, relational, and procedural constraints among the cockpit avionics and control system and the aircrew. We have designed and implemented a goals/procedures hierarchic representation sufficient to describe procedural flow in the cockpit. We then execute the procedural representation in simulation software and calculate the values of the flight instruments, aircraft state variables and crew resources using the constraints available from the relationship taxonomies. The system provides a flexible, extensible, manipulative and executable representation of aircrew and procedures that is generally applicable to crew/procedure task-analysis. The representation supports developed methods of intent inference, and is extensible to include issues of information requirements and functional allocation. We are attempting to link the procedural representation to models of cognitive functions to establish several intent inference methods

  10. Algorithms and Methods for High-Performance Model Predictive Control

    DEFF Research Database (Denmark)

    Frison, Gianluca

    routines employed in the numerical tests. The main focus of this thesis is on linear MPC problems. In this thesis, both the algorithms and their implementation are equally important. About the implementation, a novel implementation strategy for the dense linear algebra routines in embedded optimization...... is proposed, aiming at improving the computational performance in case of small matrices. About the algorithms, they are built on top of the proposed linear algebra, and they are tailored to exploit the high-level structure of the MPC problems, with special care on reducing the computational complexity....

  11. Basic considerations in predicting error probabilities in human task performance

    International Nuclear Information System (INIS)

    Fleishman, E.A.; Buffardi, L.C.; Allen, J.A.; Gaskins, R.C. III

    1990-04-01

    It is well established that human error plays a major role in the malfunctioning of complex systems. This report takes a broad look at the study of human error and addresses the conceptual, methodological, and measurement issues involved in defining and describing errors in complex systems. In addition, a review of existing sources of human reliability data and approaches to human performance data base development is presented. Alternative task taxonomies, which are promising for establishing the comparability on nuclear and non-nuclear tasks, are also identified. Based on such taxonomic schemes, various data base prototypes for generalizing human error rates across settings are proposed. 60 refs., 3 figs., 7 tabs

  12. Can Medical School Performance Predict Residency Performance? Resident Selection and Predictors of Successful Performance in Obstetrics and Gynecology

    Science.gov (United States)

    Stohl, Hindi E.; Hueppchen, Nancy A.; Bienstock, Jessica L.

    2010-01-01

    Background During the evaluation process, Residency Admissions Committees typically gather data on objective and subjective measures of a medical student's performance through the Electronic Residency Application Service, including medical school grades, standardized test scores, research achievements, nonacademic accomplishments, letters of recommendation, the dean's letter, and personal statements. Using these data to identify which medical students are likely to become successful residents in an academic residency program in obstetrics and gynecology is difficult and to date, not well studied. Objective To determine whether objective information in medical students' applications can help predict resident success. Method We performed a retrospective cohort study of all residents who matched into the Johns Hopkins University residency program in obstetrics and gynecology between 1994 and 2004 and entered the program through the National Resident Matching Program as a postgraduate year-1 resident. Residents were independently evaluated by faculty and ranked in 4 groups according to perceived level of success. Applications from residents in the highest and lowest group were abstracted. Groups were compared using the Fisher exact test and the Student t test. Results Seventy-five residents met inclusion criteria and 29 residents were ranked in the highest and lowest quartiles (15 in highest, 14 in lowest). Univariate analysis identified no variables as consistent predictors of resident success. Conclusion In a program designed to train academic obstetrician-gynecologists, objective data from medical students' applications did not correlate with successful resident performance in our obstetrics-gynecology residency program. We need to continue our search for evaluation criteria that can accurately and reliably select the medical students that are best fit for our specialty. PMID:21976076

  13. Submillimetre wave imaging and security: imaging performance and prediction

    Science.gov (United States)

    Appleby, R.; Ferguson, S.

    2016-10-01

    Within the European Commission Seventh Framework Programme (FP7), CONSORTIS (Concealed Object Stand-Off Real-Time Imaging for Security) has designed and is fabricating a stand-off system operating at sub-millimetre wave frequencies for the detection of objects concealed on people. This system scans people as they walk by the sensor. This paper presents the top level system design which brings together both passive and active sensors to provide good performance. The passive system operates in two bands between 100 and 600GHz and is based on a cryogen free cooled focal plane array sensor whilst the active system is a solid-state 340GHz radar. A modified version of OpenFX was used for modelling the passive system. This model was recently modified to include realistic location-specific skin temperature and to accept animated characters wearing up to three layers of clothing that move dynamically, such as those typically found in cinematography. Targets under clothing have been modelled and the performance simulated. The strengths and weaknesses of this modelling approach are discussed.

  14. Investigation into the performance of different models for predicting stutter.

    Science.gov (United States)

    Bright, Jo-Anne; Curran, James M; Buckleton, John S

    2013-07-01

    In this paper we have examined five possible models for the behaviour of the stutter ratio, SR. These were two log-normal models, two gamma models, and a two-component normal mixture model. A two-component normal mixture model was chosen with different behaviours of variance; at each locus SR was described with two distributions, both with the same mean. The distributions have difference variances: one for the majority of the observations and a second for the less well-behaved ones. We apply each model to a set of known single source Identifiler™, NGM SElect™ and PowerPlex(®) 21 DNA profiles to show the applicability of our findings to different data sets. SR determined from the single source profiles were compared to the calculated SR after application of the models. The model performance was tested by calculating the log-likelihoods and comparing the difference in Akaike information criterion (AIC). The two-component normal mixture model systematically outperformed all others, despite the increase in the number of parameters. This model, as well as performing well statistically, has intuitive appeal for forensic biologists and could be implemented in an expert system with a continuous method for DNA interpretation. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  15. Predicting performance in competitive apnea diving, part II: dynamic apnoea.

    Science.gov (United States)

    Schagatay, Erika

    2010-03-01

    Part I of this series of articles identified the main physiological factors defining the limits of static apnea, while this paper reviews the factors involved when physical work is added in the dynamic distance disciplines, performed in shallow water in a swimming pool. Little scientific work has been done concerning the prerequisites and limitations of swimming with or without fins whilst breath holding to extreme limits. Apneic duration influences all competitive apnea disciplines, and can be prolonged by any means that increase gas storage or tolerance to asphyxia, or reduce metabolic rate, as reviewed in the first article. For horizontal underwater distance swimming, the main challenge is to restrict metabolism despite the work, and to direct blood flow only to areas where demand is greatest, to allow sustained function. Here, work economy, local tissue energy and oxygen stores and the anaerobic capacity of the muscles are key components. Improvements in swimming techniques and, especially in swimming with fins, equipment have already contributed to enhanced performance and may do so further. High lactate levels observed after competition swims suggest a high anaerobic component, and muscle hypoxia could ultimately limit muscle work and swimming distance. However, the frequency of syncope, especially in swimming without fins, suggests that cerebral oxygenation may often be compromised before this occurs. In these pool disciplines, safety is high and the dive can be interrupted by the competitor or safety diver within seconds. The safety routines in place during pool competitions are described.

  16. Predicting Performance: A Comparison of University Supervisors' Predictions and Teacher Candidates' Scores on a Teaching Performance Assessment

    Science.gov (United States)

    Sandholtz, Judith Haymore; Shea, Lauren M.

    2012-01-01

    The implementation of teaching performance assessments has prompted a range of concerns. Some educators question whether these assessments provide information beyond what university supervisors gain through their formative evaluations and classroom observations of candidates. This research examines the relationship between supervisors' predictions…

  17. Plasma property and performance prediction for mercury ion thrusters

    Science.gov (United States)

    Longhurst, G. R.; Wilbur, P. J.

    1979-01-01

    The discharge chambers of mercury ion thrusters are modelled so the principal effects and processes which govern discharge plasma properties and thruster performance are described. The conservation relations for mass, charge and energy when applied to the Maxwellian electron population in the ion production region yield equations which may be made one-dimensional by the proper choice of coordinates. Solutions to these equations with the appropriate boundary conditions give electron density and temperature profiles which agree reasonably well with measurements. It is then possible to estimate plasma properties from thruster design data and those operating parameters which are directly controllable. By varying the operating parameter inputs to the computer code written to solve these equations, perfromance curves are obtained which agree quite well with measurements.

  18. Predicting neuropsychological test performance on the basis of temporal orientation.

    Science.gov (United States)

    Ryan, Joseph J; Glass, Laura A; Bartels, Jared M; Bergner, CariAnn M; Paolo, Anthony M

    2009-05-01

    Temporal orientation is often disrupted in the context of psychiatric or neurological disease; tests assessing this function are included in most mental status examinations. The present study examined the relationship between scores on the Temporal Orientation Scale (TOS) and performance on a battery of tests that assess memory, language, and cognitive functioning in a sample of patients with Alzheimer's disease (N = 55). Pearson-product moment correlations showed that, in all but two instances, the TOS was significantly correlated with each neuropsychological measure, p values < or = .05. Also, severely disoriented (i.e., TOS score < or = -8) patients were consistently 'impaired' on memory tests but not on tests of language and general cognitive functioning.

  19. Performance prediction of electrohydrodynamic thrusters by the perturbation method

    International Nuclear Information System (INIS)

    Shibata, H.; Watanabe, Y.; Suzuki, K.

    2016-01-01

    In this paper, we present a novel method for analyzing electrohydrodynamic (EHD) thrusters. The method is based on a perturbation technique applied to a set of drift-diffusion equations, similar to the one introduced in our previous study on estimating breakdown voltage. The thrust-to-current ratio is generalized to represent the performance of EHD thrusters. We have compared the thrust-to-current ratio obtained theoretically with that obtained from the proposed method under atmospheric air conditions, and we have obtained good quantitative agreement. Also, we have conducted a numerical simulation in more complex thruster geometries, such as the dual-stage thruster developed by Masuyama and Barrett [Proc. R. Soc. A 469, 20120623 (2013)]. We quantitatively clarify the fact that if the magnitude of a third electrode voltage is low, the effective gap distance shortens, whereas if the magnitude of the third electrode voltage is sufficiently high, the effective gap distance lengthens.

  20. Prediction of the Effect of Vortex Generators on Airfoil Performance

    International Nuclear Information System (INIS)

    Sørensen, Niels N; Zahle, F; Bak, C; Vronsky, T

    2014-01-01

    Vortex Generators (VGs) are widely used by the wind turbine industry, to control the flow over blade sections. The present work describes a computational fluid dynamic procedure that can handle a geometrical resolved VG on an airfoil section. After describing the method, it is applied to two different airfoils at a Reynolds number of 3 million, the FFA- W3-301 and FFA-W3-360, respectively. The computations are compared with wind tunnel measurements from the Stuttgart Laminar Wind Tunnel with respect to lift and drag variation as function of angle of attack. Even though the method does not exactly capture the measured performance, it can be used to compare different VG setups qualitatively with respect to chord- wise position, inter and intra-spacing and inclination of the VGs already in the design phase

  1. Serum 25-hydroxyvitamin D predicts cognitive performance in adults

    Directory of Open Access Journals (Sweden)

    Darwish H

    2015-08-01

    Full Text Available Hala Darwish,1 Pia Zeinoun,2 Husam Ghusn,3,4 Brigitte Khoury,2 Hani Tamim,5 Samia J Khoury6 1Hariri School of Nursing, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 2Psychiatry Department, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 3Internal Medicine Department, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 4Geriatrics Department, Ain Wazein Hospital, El Chouf, Lebanon; 5Clinical Research Institute, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 6Neurology Department, Faculty of Medicine, American University of Beirut, Beirut, Lebanon Background: Vitamin D is an endogenous hormone known to regulate calcium levels in the body and plays a role in cognitive performance. Studies have shown an association between vitamin D deficiency and cognitive impairment in older adults. Lebanon has a high 25-hydroxyvitamin D (25(OHD deficiency prevalence across all age groups. Methods: In this cross-sectional study, we explored the cognitive performance and serum 25(OHD levels using an electrochemoluminescent immunoassay in 254 older (>60 years as well as younger (30–60 years adults. Subjects’ characteristics, including age, years of education, wearing of veil, alcohol consumption, smoking, and physical exercise, were collected. Participants were screened for depression prior to cognitive screening using the Montreal Cognitive Assessment Arabic version. Visuospatial memory was tested using the Rey Complex Figure Test and Recognition Trial, and speed of processing was assessed using the Symbol Digit Modalities test. Results: Pearson’s correlation and stepwise linear regression analyses showed that a low vitamin D level was associated with greater risk of cognitive impairment in older as well as younger adults. Conclusion: These findings suggest that correction of vitamin D needs to be explored as an intervention to prevent cognitive impairment. Prospective

  2. Performance prediction for a magnetostrictive actuator using a simplified model

    Science.gov (United States)

    Yoo, Jin-Hyeong; Jones, Nicholas J.

    2018-03-01

    Iron-Gallium alloys (Galfenol) are promising transducer materials that combine high magnetostriction, desirable mechanical properties, high permeability, and a wide operational temperature range. Most of all, the material is capable of operating under tensile stress, and is relatively resistant to shock. These materials are generally characterized using a solid, cylindrically-shaped specimen under controlled compressive stress and magnetization conditions. Because the magnetostriction strongly depends on both the applied stress and magnetization, the characterization of the material is usually conducted under controlled conditions so each parameter is varied independently of the other. However, in a real application the applied stress and magnetization will not be maintained constant during operation. Even though the controlled characterization measurement gives insight into standard material properties, usage of this data in an application, while possible, is not straight forward. This study presents an engineering modeling methodology for magnetostrictive materials based on a piezo-electric governing equation. This model suggests phenomenological, nonlinear, three-dimensional functions for strain and magnetic flux density responses as functions of applied stress and magnetic field. Load line performances as a function of maximum magnetic field input were simulated based on the model. To verify the modeling performance, a polycrystalline magnetostrictive rod (Fe-Ga alloy, Galfenol) was characterized under compressive loads using a dead-weight test setup, with strain gages on the rod and a magnetic field driving coil around the sample. The magnetic flux density through the Galfenol rod was measured with a sensing coil; the compressive loads were measured using a load cell on the bottom of the Galfenol rod. The experimental results are compared with the simulation results using the suggested model, showing good agreement.

  3. The joint effects of personality and workplace social exchange relationships in predicting task performance and citizenship performance.

    Science.gov (United States)

    Kamdar, Dishan; Van Dyne, Linn

    2007-09-01

    This field study examines the joint effects of social exchange relationships at work (leader-member exchange and team-member exchange) and employee personality (conscientiousness and agreeableness) in predicting task performance and citizenship performance. Consistent with trait activation theory, matched data on 230 employees, their coworkers, and their supervisors demonstrated interactions in which high quality social exchange relationships weakened the positive relationships between personality and performance. Results demonstrate the benefits of consonant predictions in which predictors and outcomes are matched on the basis of specific targets. We discuss theoretical and practical implications. (c) 2007 APA.

  4. Learning to avoid spiders: fear predicts performance, not competence.

    Science.gov (United States)

    Luo, Xijia; Becker, Eni S; Rinck, Mike

    2018-01-05

    We used an immersive virtual environment to examine avoidance learning in spider-fearful participants. In 3 experiments, participants were asked to repeatedly lift one of 3 virtual boxes, under which either a toy car or a spider appeared and then approached the participant. Participants were not told that the probability of encountering a spider differed across boxes. When the difference was large (Exps. 1 and 2), spider-fearfuls learned to avoid spiders by lifting the few-spiders-box more often and the many-spiders-box less often than non-fearful controls did. However, they hardly managed to do so when the probability differences were small (Exp. 3), and they did not escape from threat more quickly (Exp. 2). In contrast to the observed performance differences, spider-fearfuls and non-fearfuls showed equal competence, that is comparable post-experimental knowledge about the probability to encounter spiders under the 3 boxes. The limitations and implications of the present study are discussed.

  5. Working memory capacity predicts conflict-task performance.

    Science.gov (United States)

    Gulbinaite, Rasa; Johnson, Addie

    2014-01-01

    The relationship between the ability to maintain task goals and working memory capacity (WMC) is firmly established, but evidence for WMC-related differences in conflict processing is mixed. We investigated whether WMC (measured using two complex-span tasks) mediates differences in adjustments of cognitive control in response to conflict. Participants performed a Simon task in which congruent and incongruent trials were equiprobable, but in which the proportion of congruency repetitions (congruent trials followed by congruent trials or incongruent trials followed by incongruent trials) and thus the need for trial-by-trial adjustments in cognitive control varied by block. The overall Simon effect did not depend on WMC capacity. However, for the low-WMC participants the Simon effect decreased as the proportion of congruency repetitions decreased, whereas for the high- and average-WMC participants it was relatively constant across conditions. Distribution analysis of the Simon effect showed more evidence for the inhibition of stimulus location in the low- than in the high-WMC participants, especially when the proportion of congruency repetitions was low. We hypothesize that low-WMC individuals exhibit more interference from task-irrelevant information due to weaker preparatory control prior to stimulus presentation and, thus, stronger reliance on reactive recruitment of cognitive control.

  6. Investigation and Prediction of RF Window Performance in APT Accelerators

    International Nuclear Information System (INIS)

    Humphries, S. Jr.

    1997-01-01

    The work described in this report was performed between November 1996 and May 1997 in support of the APT (Accelerator Production of Tritium) Program at Los Alamos National Laboratory. The goal was to write and to test computer programs for charged particle orbits in RF fields. The well-documented programs were written in portable form and compiled for standard personal computers for easy distribution to LANL researchers. They will be used in several APT applications including the following. Minimization of multipactor effects in the moderate β superconducting linac cavities under design for the APT accelerator. Investigation of suppression techniques for electron multipactoring in high-power RF feedthroughs. Modeling of the response of electron detectors for the protection of high power RF vacuum windows. In the contract period two new codes, Trak-RF and WaveSim, were completed and several critical benchmark etests were carried out. Trak-RF numerically tracks charged particle orbits in combined electrostatic, magnetostatic and electromagnetic fields. WaveSim determines frequency-domain RF field solutions and provides a key input to Trak-RF. The two-dimensional programs handle planar or cylindrical geometries. They have several unique characteristics

  7. Predictive validity of pre-admission assessments on medical student performance.

    Science.gov (United States)

    Dabaliz, Al-Awwab; Kaadan, Samy; Dabbagh, M Marwan; Barakat, Abdulaziz; Shareef, Mohammad Abrar; Al-Tannir, Mohamad; Obeidat, Akef; Mohamed, Ayman

    2017-11-24

    To examine the predictive validity of pre-admission variables on students' performance in a medical school in Saudi Arabia. In this retrospective study, we collected admission and college performance data for 737 students in preclinical and clinical years. Data included high school scores and other standardized test scores, such as those of the National Achievement Test and the General Aptitude Test. Additionally, we included the scores of the Test of English as a Foreign Language (TOEFL) and the International English Language Testing System (IELTS) exams. Those datasets were then compared with college performance indicators, namely the cumulative Grade Point Average (cGPA) and progress test, using multivariate linear regression analysis. In preclinical years, both the National Achievement Test (p=0.04, B=0.08) and TOEFL (p=0.017, B=0.01) scores were positive predictors of cGPA, whereas the General Aptitude Test (p=0.048, B=-0.05) negatively predicted cGPA. Moreover, none of the pre-admission variables were predictive of progress test performance in the same group. On the other hand, none of the pre-admission variables were predictive of cGPA in clinical years. Overall, cGPA strongly predict-ed students' progress test performance (p<0.001 and B=19.02). Only the National Achievement Test and TOEFL significantly predicted performance in preclinical years. However, these variables do not predict progress test performance, meaning that they do not predict the functional knowledge reflected in the progress test. We report various strengths and deficiencies in the current medical college admission criteria, and call for employing more sensitive and valid ones that predict student performance and functional knowledge, especially in the clinical years.

  8. Predictions from the cloud: using data science to predict sports performance

    NARCIS (Netherlands)

    Blaauw, Frank; Emerencia, Armando Celino; den Hartigh, Jan Rudolf; Milovanović, Marko; Stoter, Inge; de Jonge, Peter

    2018-01-01

    In sport science, a major aim is to unravel the variables and parameters that influence sports performance. A key requirement for investigating these parameters is the availability of high quality data. More specifically, data that contains the variables of interest, and data that could be analyzed

  9. Studying the effect of the shape parameters on the performance of the darrieus wind turbine using the multiple double disk stream tube theory

    International Nuclear Information System (INIS)

    Elmabrok, Ali Mohamed; Al-makhlufi, Ahmed A.

    2006-01-01

    The performance of the Darrieus vertical axis turbine is comparable with that of the more common horizontal axis machines. It has a number of aerodynamic and structural advantages over HAWTS. However the darrieus turbines are not self-starting at low wind speeds which is a considerable disadvantage for a simple small scale installation. Generally, papers concerning vertical axis turbine do not study the behavior of the rotor at low tip speed ratios. Therefore they do not deal with the self starting problems. A number of analytical methods were investigated to see whether they could predict the starting performance of vertical axis turbines. The chosen methods and 'actuator disc theory' for multiple stream tubes. In this paper the multiple stream tube model is applied using two discs in tandem. The computational analysis of all models simulates the blade aerodynamics throughout the full range of incidence from 180 degree centigrade. The effects of varying various geometric parameters of the windmill upon the performance of the rotor are investigated to find a design with improved self starting characteristics. The best agreement between theory and experiment was obtained using the multiple stream tube (double disc) models.(Author)

  10. Goal orientation and work role performance: predicting adaptive and proactive work role performance through self-leadership strategies.

    Science.gov (United States)

    Marques-Quinteiro, Pedro; Curral, Luís Alberto

    2012-01-01

    This article explores the relationship between goal orientation, self-leadership dimensions, and adaptive and proactive work role performances. The authors hypothesize that learning orientation, in contrast to performance orientation, positively predicts proactive and adaptive work role performances and that this relationship is mediated by self-leadership behavior-focused strategies. It is posited that self-leadership natural reward strategies and thought pattern strategies are expected to moderate this relationship. Workers (N = 108) from a software company participated in this study. As expected, learning orientation did predict adaptive and proactive work role performance. Moreover, in the relationship between learning orientation and proactive work role performance through self-leadership behavior-focused strategies, a moderated mediation effect was found for self-leadership natural reward and thought pattern strategies. In the end, the authors discuss the results and implications are discussed and future research directions are proposed.

  11. Predicting race performance in triathlon: the role of perfectionism, achievement goals, and personal goal setting.

    Science.gov (United States)

    Stoeber, Joachim; Uphill, Mark A; Hotham, Sarah

    2009-04-01

    The question of how perfectionism affects performance is highly debated. Because empirical studies examining perfectionism and competitive sport performance are missing, the present research investigated how perfectionism affected race performance and what role athletes' goals played in this relationship in two prospective studies with competitive triathletes (Study 1: N = 112; Study 2: N = 321). Regression analyses showed that perfectionistic personal standards, high performance-approach goals, low performance-avoidance goals, and high personal goals predicted race performance beyond athletes' performance level. Moreover, the contrast between performance-avoidance and performance-approach goals mediated the relationship between perfectionistic personal standards and performance, whereas personal goal setting mediated the relationship between performance-approach goals and performance. The findings indicate that perfectionistic personal standards do not undermine competitive performance, but are associated with goals that help athletes achieve their best possible performance.

  12. A human capital predictive model for agent performance in contact centres

    Directory of Open Access Journals (Sweden)

    Chris Jacobs

    2011-10-01

    Research purpose: The primary focus of this article was to develop a theoretically derived human capital predictive model for agent performance in contact centres and Business Process Outsourcing (BPO based on a review of current empirical research literature. Motivation for the study: The study was motivated by the need for a human capital predictive model that can predict agent and overall business performance. Research design: A nonempirical (theoretical research paradigm was adopted for this study and more specifically a theory or model-building approach was followed. A systematic review of published empirical research articles (for the period 2000–2009 in scholarly search portals was performed. Main findings: Eight building blocks of the human capital predictive model for agent performance in contact centres were identified. Forty-two of the human capital contact centre related articles are detailed in this study. Key empirical findings suggest that person– environment fit, job demands-resources, human resources management practices, engagement, agent well-being, agent competence; turnover intention; and agent performance are related to contact centre performance. Practical/managerial implications: The human capital predictive model serves as an operational management model that has performance implications for agents and ultimately influences the contact centre’s overall business performance. Contribution/value-add: This research can contribute to the fields of human resource management (HRM, human capital and performance management within the contact centre and BPO environment.

  13. Driving and Low Vision: Validity of Assessments for Predicting Performance of Drivers

    Science.gov (United States)

    Strong, J. Graham; Jutai, Jeffrey W.; Russell-Minda, Elizabeth; Evans, Mal

    2008-01-01

    The authors conducted a systematic review to examine whether vision-related assessments can predict the driving performance of individuals who have low vision. The results indicate that measures of visual field, contrast sensitivity, cognitive and attention-based tests, and driver screening tools have variable utility for predicting real-world…

  14. Early Prediction of Student Dropout and Performance in MOOCSs Using Higher Granularity Temporal Information

    Science.gov (United States)

    Ye, Cheng; Biswas, Gautam

    2014-01-01

    Our project is motivated by the early dropout and low completion rate problem in MOOCs. We have extended traditional features for MOOC analysis with richer and higher granularity information to make more accurate predictions of dropout and performance. The results show that finer-grained temporal information increases the predictive power in the…

  15. Predicting Story Goodness Performance from Cognitive Measures Following Traumatic Brain Injury

    Science.gov (United States)

    Le, Karen; Coelho, Carl; Mozeiko, Jennifer; Krueger, Frank; Grafman, Jordan

    2012-01-01

    Purpose: This study examined the prediction of performance on measures of the Story Goodness Index (SGI; Le, Coelho, Mozeiko, & Grafman, 2011) from executive function (EF) and memory measures following traumatic brain injury (TBI). It was hypothesized that EF and memory measures would significantly predict SGI outcomes. Method: One hundred…

  16. A Prediction Model for Community Colleges Using Graduation Rate as the Performance Indicator

    Science.gov (United States)

    Moosai, Susan

    2010-01-01

    In this thesis a prediction model using graduation rate as the performance indicator is obtained for community colleges for three cohort years, 2003, 2004, and 2005 in the states of California, Florida, and Michigan. Multiple Regression analysis, using an aggregate of seven predictor variables, was employed in determining this prediction model.…

  17. Numerical prediction of a bulb turbine performance hill chart through RANS simulations

    International Nuclear Information System (INIS)

    Guénette, V; Houde, S; Ciocan, G D; Deschênes, C; Dumas, G; Huang, J

    2012-01-01

    Within the framework of an international research consortium on low-head hydraulic turbine flow dynamics, the predictive behavior of Reynolds Averaged Navier-Stokes (RANS) simulations of the efficiency (η) hill chart of a bulb turbine is investigated. The paper presents the impacts of the blade tip gap and the hub gaps on performance predictions.

  18. Prediction of the aerodynamic performance of the Mexico rotor by using airfoil data extracted from CFD

    DEFF Research Database (Denmark)

    Yang, Hua; Shen, Wen Zhong; Xu, Haoran

    2013-01-01

    Blade Element Momentum (BEM) theory is a widely used technique for prediction of wind turbine aerodynamics performance, but the reliability of airfoil data is an important factor to improve the prediction accuracy of aerodynamic loads and power using a BEM code. The airfoil characteristics used...

  19. Prediction of the wind turbine performance by using BEM with airfoil data extracted from CFD

    DEFF Research Database (Denmark)

    Yang, Hua; Shen, Wen Zhong; Xu, Haoran

    2014-01-01

    Blade element momentum (BEM) theory with airfoil data is a widely used technique for prediction of wind turbine aerodynamic performance, but the reliability of the airfoil data is an important factor for the prediction accuracy of aerodynamic loads and power. The airfoil characteristics used in BEM...

  20. Hyperformance: predicting high-speed performance of a b-double

    CSIR Research Space (South Africa)

    Berman, Robert J

    2016-11-01

    Full Text Available of the vehicles. The prediction model bridges that gap in the form of a light-weight methodology to predict the PBS performance of a new vehicle design given a set of vehicle input data. Such a model was developed for typical South African 9-axle B-double PBS...

  1. Predicting Eight Grade Students' Equation Solving Performances via Concepts of Variable and Equality

    Science.gov (United States)

    Ertekin, Erhan

    2017-01-01

    This study focused on how two algebraic concepts- equality and variable- predicted 8th grade students' equation solving performance. In this study, predictive design as a correlational research design was used. Randomly selected 407 eight-grade students who were from the central districts of a city in the central region of Turkey participated in…

  2. A multi-source, multi-study investigation of job performance prediction by political skill

    DEFF Research Database (Denmark)

    Blickle, G.; Ferris, G.R.; Munyon, T.P.

    2011-01-01

    -sectional and longitudinal designs, this research tested the hypotheses that employee political skill, measured from the perspective of employees' assessor A, will positively predict job performance rated by assessor B (i.e. Hypothesis 1a), and vice versa, that employee political skill measured by assessor B will predict...

  3. Building Predictive Human Performance Models of Skill Acquisition in a Data Entry Task

    National Research Council Canada - National Science Library

    Fu, Wai-Tat; Gonzalez, Cleotilde; Healy, Alice F; Kole, James A; Bourne, Jr., Lyle E

    2006-01-01

    .... Since data entry is a central component in most human-machine interaction, a predictive model of performance will provide useful information that informs interface design and effectiveness of training...

  4. In vitro models for the prediction of in vivo performance of oral dosage forms

    NARCIS (Netherlands)

    Kostewicz, E.S.; Abrahamsson, B.; Brewster, M.; Brouwers, J.; Butler, J.; Carlert, S.; Dickinson, P.A.; Dressman, J.; Holm, R.; Klein, S.; Mann, J.; McAllister, M.; Minekus, M.; Muenster, U.; Müllertz, A.; Verwei, M.; Vertzoni, M.; Weitschies, W.; Augustijns, P.

    2014-01-01

    Accurate prediction of the in vivo biopharmaceutical performance of oral drug formulations is critical to efficient drug development. Traditionally, in vitro evaluation of oral drug formulations has focused on disintegration and dissolution testing for quality control (QC) purposes. The connection

  5. Biological lifestyle factors in adult distance education: predicting cognitive and learning performance

    NARCIS (Netherlands)

    Gijselaers, Jérôme

    2015-01-01

    Gijselaers, H. J. M. (2015, 20 October). Biological lifestyle factors in adult distance education: predicting cognitive and learning performance. Presentation given for the inter-faculty Data Science group at the Open University of the Netherlands, Heerlen, The Netherlands.

  6. Gender Differences in Performance Predictions: Evidence from the Cognitive Reflection Test.

    Science.gov (United States)

    Ring, Patrick; Neyse, Levent; David-Barett, Tamas; Schmidt, Ulrich

    2016-01-01

    This paper studies performance predictions in the 7-item Cognitive Reflection Test (CRT) and whether they differ by gender. After participants completed the CRT, they predicted their own (i), the other participants' (ii), men's (iii), and women's (iv) number of correct answers. In keeping with existing literature, men scored higher on the CRT than women and both men and women were too optimistic about their own performance. When we compare gender-specific predictions, we observe that men think they perform significantly better than other men and do so significantly more than women. The equality between women's predictions about their own performance and their female peers cannot be rejected. Our findings contribute to the growing literature on the underpinnings of behavior in economics and in psychology by uncovering gender differences in confidence about one's ability relative to same and opposite sex peers.

  7. Gender Differences in Performance Predictions: Evidence from the Cognitive Reflection Test

    Directory of Open Access Journals (Sweden)

    Patrick Ring

    2016-11-01

    Full Text Available This paper studies performance predictions in the 7-item Cognitive Reflection Test (CRT and whether they differ by gender. After participants completed the CRT, they predicted their own (i, the other participants’ (ii, men’s (iii, and women’s (iv number of correct answers. In keeping with existing literature, men scored higher on the CRT than women and both men and women were too optimistic about their own performance. When we compare gender-specific predictions, we observe that men think they perform significantly better than other men and do so significantly more than women. The equality between women’s predictions about their own performance and their female peers cannot be rejected. Our findings contribute to the growing literature on the underpinnings of behavior in economics and in psychology by uncovering gender differences in confidence about one’s ability relative to same and opposite sex peers.

  8. Mean streamline analysis for performance prediction of cross-flow fans

    International Nuclear Information System (INIS)

    Kim, Jae Won; Oh, Hyoung Woo

    2004-01-01

    This paper presents the mean streamline analysis using the empirical loss correlations for performance prediction of cross-flow fans. Comparison of overall performance predictions with test data of a cross-flow fan system with a simplified vortex wall scroll casing and with the published experimental characteristics for a cross-flow fan has been carried out to demonstrate the accuracy of the proposed method. Predicted performance curves by the present mean streamline analysis agree well with experimental data for two different cross-flow fans over the normal operating conditions. The prediction method presented herein can be used efficiently as a tool for the preliminary design and performance analysis of general-purpose cross-flow fans

  9. When bad stress goes good: increased threat reactivity predicts improved category learning performance.

    Science.gov (United States)

    Ell, Shawn W; Cosley, Brandon; McCoy, Shannon K

    2011-02-01

    The way in which we respond to everyday stressors can have a profound impact on cognitive functioning. Maladaptive stress responses in particular are generally associated with impaired cognitive performance. We argue, however, that the cognitive system mediating task performance is also a critical determinant of the stress-cognition relationship. Consistent with this prediction, we observed that stress reactivity consistent with a maladaptive, threat response differentially predicted performance on two categorization tasks. Increased threat reactivity predicted enhanced performance on an information-integration task (i.e., learning is thought to depend upon a procedural-based memory system), and a (nonsignificant) trend for impaired performance on a rule-based task (i.e., learning is thought to depend upon a hypothesis-testing system). These data suggest that it is critical to consider both variability in the stress response and variability in the cognitive system mediating task performance in order to fully understand the stress-cognition relationship.

  10. Prediction of Rowing Ergometer Performance from Functional Anaerobic Power, Strength and Anthropometric Components

    Directory of Open Access Journals (Sweden)

    Akça Firat

    2014-07-01

    Full Text Available The aim of this research was to develop different regression models to predict 2000 m rowing ergometer performance with the use of anthropometric, anaerobic and strength variables and to determine how precisely the prediction models constituted by different variables predict performance, when conducted together in the same equation or individually. 38 male collegiate rowers (20.17 ± 1.22 years participated in this study. Anthropometric, strength, 2000 m maximal rowing ergometer and rowing anaerobic power tests were applied. Multiple linear regression procedures were employed in SPSS 16 to constitute five different regression formulas using a different group of variables. The reliability of the regression models was expressed by R2 and the standard error of estimate (SEE. Relationships of all parameters with performance were investigated through Pearson correlation coefficients. The prediction model using a combination of anaerobic, strength and anthropometric variables was found to be the most reliable equation to predict 2000 m rowing ergometer performance (R2 = 0.92, SEE= 3.11 s. Besides, the equation that used rowing anaerobic and strength test results also provided a reliable prediction (R2 = 0.85, SEE= 4.27 s. As a conclusion, it seems clear that physiological determinants which are affected by anaerobic energy pathways should also get involved in the processes and models used for performance prediction and talent identification in rowing.

  11. User's Self-Prediction of Performance in Motor Imagery Brain-Computer Interface.

    Science.gov (United States)

    Ahn, Minkyu; Cho, Hohyun; Ahn, Sangtae; Jun, Sung C

    2018-01-01

    Performance variation is a critical issue in motor imagery brain-computer interface (MI-BCI), and various neurophysiological, psychological, and anatomical correlates have been reported in the literature. Although the main aim of such studies is to predict MI-BCI performance for the prescreening of poor performers, studies which focus on the user's sense of the motor imagery process and directly estimate MI-BCI performance through the user's self-prediction are lacking. In this study, we first test each user's self-prediction idea regarding motor imagery experimental datasets. Fifty-two subjects participated in a classical, two-class motor imagery experiment and were asked to evaluate their easiness with motor imagery and to predict their own MI-BCI performance. During the motor imagery experiment, an electroencephalogram (EEG) was recorded; however, no feedback on motor imagery was given to subjects. From EEG recordings, the offline classification accuracy was estimated and compared with several questionnaire scores of subjects, as well as with each subject's self-prediction of MI-BCI performance. The subjects' performance predictions during motor imagery task showed a high positive correlation ( r = 0.64, p performance even without feedback information. This implies that the human brain is an active learning system and, by self-experiencing the endogenous motor imagery process, it can sense and adopt the quality of the process. Thus, it is believed that users may be able to predict MI-BCI performance and results may contribute to a better understanding of low performance and advancing BCI.

  12. Neither here, nor there: impression management does not predict expatriate adjustment and job performance

    OpenAIRE

    HANNAH JACKSON FOLDES; DENIZ S. ONES; HANDAN KEPIR SINANGIL

    2006-01-01

    Social desirability scale scores reflect substantive individual differences related to personality. The objective of the current study was to examine whether social desirability, and impression management specifically (a component of social desirability), is predictive of adjustment and job performance for expatriates. Based on theoretical considerations, it was proposed that impression management might be linked to expatriate job performance in a predictive and mediated relationship through ...

  13. Comparative values of medical school assessments in the prediction of internship performance.

    Science.gov (United States)

    Lee, Ming; Vermillion, Michelle

    2018-02-01

    Multiple undergraduate achievements have been used for graduate admission consideration. Their relative values in the prediction of residency performance are not clear. This study compared the contributions of major undergraduate assessments to the prediction of internship performance. Internship performance ratings of the graduates of a medical school were collected from 2012 to 2015. Hierarchical multiple regression analyses were used to examine the predictive values of undergraduate measures assessing basic and clinical sciences knowledge and clinical performances, after controlling for differences in the Medical College Admission Test (MCAT). Four hundred eighty (75%) graduates' archived data were used in the study. Analyses revealed that clinical competencies, assessed by the USMLE Step 2 CK, NBME medicine exam, and an eight-station objective structured clinical examination (OSCE), were strong predictors of internship performance. Neither the USMLE Step 1 nor the inpatient internal medicine clerkship evaluation predicted internship performance. The undergraduate assessments as a whole showed a significant collective relationship with internship performance (ΔR 2  = 0.12, p < 0.001). The study supports the use of clinical competency assessments, instead of pre-clinical measures, in graduate admission consideration. It also provides validity evidence for OSCE scores in the prediction of workplace performance.

  14. Predicting Subcontractor Performance Using Web-Based Evolutionary Fuzzy Neural Networks

    Directory of Open Access Journals (Sweden)

    Chien-Ho Ko

    2013-01-01

    Full Text Available Subcontractor performance directly affects project success. The use of inappropriate subcontractors may result in individual work delays, cost overruns, and quality defects throughout the project. This study develops web-based Evolutionary Fuzzy Neural Networks (EFNNs to predict subcontractor performance. EFNNs are a fusion of Genetic Algorithms (GAs, Fuzzy Logic (FL, and Neural Networks (NNs. FL is primarily used to mimic high level of decision-making processes and deal with uncertainty in the construction industry. NNs are used to identify the association between previous performance and future status when predicting subcontractor performance. GAs are optimizing parameters required in FL and NNs. EFNNs encode FL and NNs using floating numbers to shorten the length of a string. A multi-cut-point crossover operator is used to explore the parameter and retain solution legality. Finally, the applicability of the proposed EFNNs is validated using real subcontractors. The EFNNs are evolved using 22 historical patterns and tested using 12 unseen cases. Application results show that the proposed EFNNs surpass FL and NNs in predicting subcontractor performance. The proposed approach improves prediction accuracy and reduces the effort required to predict subcontractor performance, providing field operators with web-based remote access to a reliable, scientific prediction mechanism.

  15. Predicting subcontractor performance using web-based Evolutionary Fuzzy Neural Networks.

    Science.gov (United States)

    Ko, Chien-Ho

    2013-01-01

    Subcontractor performance directly affects project success. The use of inappropriate subcontractors may result in individual work delays, cost overruns, and quality defects throughout the project. This study develops web-based Evolutionary Fuzzy Neural Networks (EFNNs) to predict subcontractor performance. EFNNs are a fusion of Genetic Algorithms (GAs), Fuzzy Logic (FL), and Neural Networks (NNs). FL is primarily used to mimic high level of decision-making processes and deal with uncertainty in the construction industry. NNs are used to identify the association between previous performance and future status when predicting subcontractor performance. GAs are optimizing parameters required in FL and NNs. EFNNs encode FL and NNs using floating numbers to shorten the length of a string. A multi-cut-point crossover operator is used to explore the parameter and retain solution legality. Finally, the applicability of the proposed EFNNs is validated using real subcontractors. The EFNNs are evolved using 22 historical patterns and tested using 12 unseen cases. Application results show that the proposed EFNNs surpass FL and NNs in predicting subcontractor performance. The proposed approach improves prediction accuracy and reduces the effort required to predict subcontractor performance, providing field operators with web-based remote access to a reliable, scientific prediction mechanism.

  16. Predicting space telerobotic operator training performance from human spatial ability assessment

    Science.gov (United States)

    Liu, Andrew M.; Oman, Charles M.; Galvan, Raquel; Natapoff, Alan

    2013-11-01

    Our goal was to determine whether existing tests of spatial ability can predict an astronaut's qualification test performance after robotic training. Because training astronauts to be qualified robotics operators is so long and expensive, NASA is interested in tools that can predict robotics performance before training begins. Currently, the Astronaut Office does not have a validated tool to predict robotics ability as part of its astronaut selection or training process. Commonly used tests of human spatial ability may provide such a tool to predict robotics ability. We tested the spatial ability of 50 active astronauts who had completed at least one robotics training course, then used logistic regression models to analyze the correlation between spatial ability test scores and the astronauts' performance in their evaluation test at the end of the training course. The fit of the logistic function to our data is statistically significant for several spatial tests. However, the prediction performance of the logistic model depends on the criterion threshold assumed. To clarify the critical selection issues, we show how the probability of correct classification vs. misclassification varies as a function of the mental rotation test criterion level. Since the costs of misclassification are low, the logistic models of spatial ability and robotic performance are reliable enough only to be used to customize regular and remedial training. We suggest several changes in tracking performance throughout robotics training that could improve the range and reliability of predictive models.

  17. A comprehensive performance evaluation on the prediction results of existing cooperative transcription factors identification algorithms.

    Science.gov (United States)

    Lai, Fu-Jou; Chang, Hong-Tsun; Huang, Yueh-Min; Wu, Wei-Sheng

    2014-01-01

    Eukaryotic transcriptional regulation is known to be highly connected through the networks of cooperative transcription factors (TFs). Measuring the cooperativity of TFs is helpful for understanding the biological relevance of these TFs in regulating genes. The recent advances in computational techniques led to various predictions of cooperative TF pairs in yeast. As each algorithm integrated different data resources and was developed based on different rationales, it possessed its own merit and claimed outperforming others. However, the claim was prone to subjectivity because each algorithm compared with only a few other algorithms and only used a small set of performance indices for comparison. This motivated us to propose a series of indices to objectively evaluate the prediction performance of existing algorithms. And based on the proposed performance indices, we conducted a comprehensive performance evaluation. We collected 14 sets of predicted cooperative TF pairs (PCTFPs) in yeast from 14 existing algorithms in the literature. Using the eight performance indices we adopted/proposed, the cooperativity of each PCTFP was measured and a ranking score according to the mean cooperativity of the set was given to each set of PCTFPs under evaluation for each performance index. It was seen that the ranking scores of a set of PCTFPs vary with different performance indices, implying that an algorithm used in predicting cooperative TF pairs is of strength somewhere but may be of weakness elsewhere. We finally made a comprehensive ranking for these 14 sets. The results showed that Wang J's study obtained the best performance evaluation on the prediction of cooperative TF pairs in yeast. In this study, we adopted/proposed eight performance indices to make a comprehensive performance evaluation on the prediction results of 14 existing cooperative TFs identification algorithms. Most importantly, these proposed indices can be easily applied to measure the performance of new

  18. Predicting law enforcement officer job performance with the Personality Assessment Inventory.

    Science.gov (United States)

    Lowmaster, Sara E; Morey, Leslie C

    2012-01-01

    This study examined the descriptive and predictive characteristics of the Personality Assessment Inventory (PAI; Morey, 1991) in a sample of 85 law enforcement officer candidates. Descriptive results indicate that mean PAI full-scale and subscale scores are consistently lower than normative community sample scores, with some exceptions noted typically associated with defensive responding. Predictive validity was examined by relating PAI full-scale and subscale scores to supervisor ratings in the areas of job performance, integrity problems, and abuse of disability status. Modest correlations were observed for all domains; however, predictive validity was moderated by defensive response style, with greater predictive validity observed among less defensive responders. These results suggest that the PAI's full scales and subscales are able to predict law enforcement officers' performance, but their utility is appreciably improved when taken in the context of indicators of defensive responding.

  19. Deep Recurrent Model for Server Load and Performance Prediction in Data Center

    Directory of Open Access Journals (Sweden)

    Zheng Huang

    2017-01-01

    Full Text Available Recurrent neural network (RNN has been widely applied to many sequential tagging tasks such as natural language process (NLP and time series analysis, and it has been proved that RNN works well in those areas. In this paper, we propose using RNN with long short-term memory (LSTM units for server load and performance prediction. Classical methods for performance prediction focus on building relation between performance and time domain, which makes a lot of unrealistic hypotheses. Our model is built based on events (user requests, which is the root cause of server performance. We predict the performance of the servers using RNN-LSTM by analyzing the log of servers in data center which contains user’s access sequence. Previous work for workload prediction could not generate detailed simulated workload, which is useful in testing the working condition of servers. Our method provides a new way to reproduce user request sequence to solve this problem by using RNN-LSTM. Experiment result shows that our models get a good performance in generating load and predicting performance on the data set which has been logged in online service. We did experiments with nginx web server and mysql database server, and our methods can been easily applied to other servers in data center.

  20. A Unified Model of Performance for Predicting the Effects of Sleep and Caffeine.

    Science.gov (United States)

    Ramakrishnan, Sridhar; Wesensten, Nancy J; Kamimori, Gary H; Moon, James E; Balkin, Thomas J; Reifman, Jaques

    2016-10-01

    Existing mathematical models of neurobehavioral performance cannot predict the beneficial effects of caffeine across the spectrum of sleep loss conditions, limiting their practical utility. Here, we closed this research gap by integrating a model of caffeine effects with the recently validated unified model of performance (UMP) into a single, unified modeling framework. We then assessed the accuracy of this new UMP in predicting performance across multiple studies. We hypothesized that the pharmacodynamics of caffeine vary similarly during both wakefulness and sleep, and that caffeine has a multiplicative effect on performance. Accordingly, to represent the effects of caffeine in the UMP, we multiplied a dose-dependent caffeine factor (which accounts for the pharmacokinetics and pharmacodynamics of caffeine) to the performance estimated in the absence of caffeine. We assessed the UMP predictions in 14 distinct laboratory- and field-study conditions, including 7 different sleep-loss schedules (from 5 h of sleep per night to continuous sleep loss for 85 h) and 6 different caffeine doses (from placebo to repeated 200 mg doses to a single dose of 600 mg). The UMP accurately predicted group-average psychomotor vigilance task performance data across the different sleep loss and caffeine conditions (6% caffeine resulted in improved predictions (after caffeine consumption) by up to 70%. The UMP provides the first comprehensive tool for accurate selection of combinations of sleep schedules and caffeine countermeasure strategies to optimize neurobehavioral performance. © 2016 Associated Professional Sleep Societies, LLC.

  1. The better model to predict and improve pediatric health care quality: performance or importance-performance?

    Science.gov (United States)

    Olsen, Rebecca M; Bryant, Carol A; McDermott, Robert J; Ortinau, David

    2013-01-01

    The perpetual search for ways to improve pediatric health care quality has resulted in a multitude of assessments and strategies; however, there is little research evidence as to their conditions for maximum effectiveness. A major reason for the lack of evaluation research and successful quality improvement initiatives is the methodological challenge of measuring quality from the parent perspective. Comparison of performance-only and importance-performance models was done to determine the better predictor of pediatric health care quality and more successful method for improving the quality of care provided to children. Fourteen pediatric health care centers serving approximately 250,000 patients in 70,000 households in three West Central Florida counties were studied. A cross-sectional design was used to determine the importance and performance of 50 pediatric health care attributes and four global assessments of pediatric health care quality. Exploratory factor analysis revealed five dimensions of care (physician care, access, customer service, timeliness of services, and health care facility). Hierarchical multiple regression compared the performance-only and the importance-performance models. In-depth interviews, participant observations, and a direct cognitive structural analysis identified 50 health care attributes included in a mailed survey to parents(n = 1,030). The tailored design method guided survey development and data collection. The importance-performance multiplicative additive model was a better predictor of pediatric health care quality. Attribute importance moderates performance and quality, making the importance-performance model superior for measuring and providing a deeper understanding of pediatric health care quality and a better method for improving the quality of care provided to children. Regardless of attribute performance, if the level of attribute importance is not taken into consideration, health care organizations may spend valuable

  2. Predictive models for PEM-electrolyzer performance using adaptive neuro-fuzzy inference systems

    Energy Technology Data Exchange (ETDEWEB)

    Becker, Steffen [University of Tasmania, Hobart 7001, Tasmania (Australia); Karri, Vishy [Australian College of Kuwait (Kuwait)

    2010-09-15

    Predictive models were built using neural network based Adaptive Neuro-Fuzzy Inference Systems for hydrogen flow rate, electrolyzer system-efficiency and stack-efficiency respectively. A comprehensive experimental database forms the foundation for the predictive models. It is argued that, due to the high costs associated with the hydrogen measuring equipment; these reliable predictive models can be implemented as virtual sensors. These models can also be used on-line for monitoring and safety of hydrogen equipment. The quantitative accuracy of the predictive models is appraised using statistical techniques. These mathematical models are found to be reliable predictive tools with an excellent accuracy of {+-}3% compared with experimental values. The predictive nature of these models did not show any significant bias to either over prediction or under prediction. These predictive models, built on a sound mathematical and quantitative basis, can be seen as a step towards establishing hydrogen performance prediction models as generic virtual sensors for wider safety and monitoring applications. (author)

  3. Prediction of intrinsic motivation and sports performance using 2 x 2 achievement goal framework.

    Science.gov (United States)

    Li, Chiung-Huang; Chi, Likang; Yeh, Suh-Ruu; Guo, Kwei-Bin; Ou, Cheng-Tsung; Kao, Chun-Chieh

    2011-04-01

    The purpose of this study was to examine the influence of 2 x 2 achievement goals on intrinsic motivation and performance in handball. Participants were 164 high school athletes. All completed the 2 x 2 Achievement Goals Questionnaire for Sport and the Intrinsic Motivation subscale of the Sport Motivation Scale; the coach for each team rated his athletes' overall sports performance. Using simultaneous-regression analyses, mastery-approach goals positively predicted both intrinsic motivation and performance in sports, whereas performance-avoidance goals negatively predicted sports performance. These results suggest that athletes who pursue task mastery and improvement of their competence perform well and enjoy their participation. In contrast, those who focus on avoiding normative incompetence perform poorly.

  4. Predicting performance and performance satisfaction: mindfulness and beliefs about the ability to deal with social barriers in sport.

    Science.gov (United States)

    Blecharz, Jan; Luszczynska, Aleksandra; Scholz, Urte; Schwarzer, Ralf; Siekanska, Malgorzata; Cieslak, Roman

    2014-05-01

    This research investigates the role of beliefs about the ability to deal with specific social barriers and its relationships to mindfulness, football performance, and satisfaction with one's own and team performance. Study 1 aimed at eliciting these social barriers. Study 2 tested (i) whether self-efficacy referring to social barriers would predict performance over and above task-related self-efficacy and collective efficacy and (ii) the mediating role of self-efficacy to overcome social barriers in the relationship between mindfulness and performance. Participants were football (soccer) players aged 16-21 years (Study 1: N=30; Study 2: N=101, longitudinal sample: n=88). Study 1 resulted in eliciting 82 social barriers referring to team, peer leadership, and coaches. Study 2 showed that task-related self-efficacy and collective efficacy explained performance satisfaction at seven-month follow-up, whereas self-efficacy referring to social barriers explained shooting performance at seven-month follow-up. Indirect associations between mindfulness and performance were found with three types of self-efficacy referring to social barriers, operating as parallel mediators. Results provide evidence for the role of beliefs about the ability to cope with social barriers and show a complex interplay between different types of self-efficacy and collective efficacy in predicting team sport performance.

  5. Performance of local information-based link prediction: a sampling perspective

    Science.gov (United States)

    Zhao, Jichang; Feng, Xu; Dong, Li; Liang, Xiao; Xu, Ke

    2012-08-01

    Link prediction is pervasively employed to uncover the missing links in the snapshots of real-world networks, which are usually obtained through different kinds of sampling methods. In the previous literature, in order to evaluate the performance of the prediction, known edges in the sampled snapshot are divided into the training set and the probe set randomly, without considering the underlying sampling approaches. However, different sampling methods might lead to different missing links, especially for the biased ways. For this reason, random partition-based evaluation of performance is no longer convincing if we take the sampling method into account. In this paper, we try to re-evaluate the performance of local information-based link predictions through sampling method governed division of the training set and the probe set. It is interesting that we find that for different sampling methods, each prediction approach performs unevenly. Moreover, most of these predictions perform weakly when the sampling method is biased, which indicates that the performance of these methods might have been overestimated in the prior works.

  6. In Silico Modeling of Gastrointestinal Drug Absorption: Predictive Performance of Three Physiologically Based Absorption Models.

    Science.gov (United States)

    Sjögren, Erik; Thörn, Helena; Tannergren, Christer

    2016-06-06

    Gastrointestinal (GI) drug absorption is a complex process determined by formulation, physicochemical and biopharmaceutical factors, and GI physiology. Physiologically based in silico absorption models have emerged as a widely used and promising supplement to traditional in vitro assays and preclinical in vivo studies. However, there remains a lack of comparative studies between different models. The aim of this study was to explore the strengths and limitations of the in silico absorption models Simcyp 13.1, GastroPlus 8.0, and GI-Sim 4.1, with respect to their performance in predicting human intestinal drug absorption. This was achieved by adopting an a priori modeling approach and using well-defined input data for 12 drugs associated with incomplete GI absorption and related challenges in predicting the extent of absorption. This approach better mimics the real situation during formulation development where predictive in silico models would be beneficial. Plasma concentration-time profiles for 44 oral drug administrations were calculated by convolution of model-predicted absorption-time profiles and reported pharmacokinetic parameters. Model performance was evaluated by comparing the predicted plasma concentration-time profiles, Cmax, tmax, and exposure (AUC) with observations from clinical studies. The overall prediction accuracies for AUC, given as the absolute average fold error (AAFE) values, were 2.2, 1.6, and 1.3 for Simcyp, GastroPlus, and GI-Sim, respectively. The corresponding AAFE values for Cmax were 2.2, 1.6, and 1.3, respectively, and those for tmax were 1.7, 1.5, and 1.4, respectively. Simcyp was associated with underprediction of AUC and Cmax; the accuracy decreased with decreasing predicted fabs. A tendency for underprediction was also observed for GastroPlus, but there was no correlation with predicted fabs. There were no obvious trends for over- or underprediction for GI-Sim. The models performed similarly in capturing dependencies on dose and

  7. Predicting failing performance on a standardized patient clinical performance examination: the importance of communication and professionalism skills deficits.

    Science.gov (United States)

    Chang, Anna; Boscardin, Christy; Chou, Calvin L; Loeser, Helen; Hauer, Karen E

    2009-10-01

    The purpose is to determine which assessment measures identify medical students at risk of failing a clinical performance examination (CPX). Retrospective case-control, multiyear design, contingency table analysis, n = 149. We identified two predictors of CPX failure in patient-physician interaction skills: low clerkship ratings (odds ratio 1.79, P = .008) and student progress review for communication or professionalism concerns (odds ratio 2.64, P = .002). No assessments predicted CPX failure in clinical skills. Performance concerns in communication and professionalism identify students at risk of failing the patient-physician interaction portion of a CPX. This correlation suggests that both faculty and standardized patients can detect noncognitive traits predictive of failing performance. Early identification of these students may allow for development of a structured supplemental curriculum with increased opportunities for practice and feedback. The lack of predictors in the clinical skills portion suggests limited faculty observation or feedback.

  8. Interactions of Team Mental Models and Monitoring Behaviors Predict Team Performance in Simulated Anesthesia Inductions

    Science.gov (United States)

    Burtscher, Michael J.; Kolbe, Michaela; Wacker, Johannes; Manser, Tanja

    2011-01-01

    In the present study, we investigated how two team mental model properties (similarity vs. accuracy) and two forms of monitoring behavior (team vs. systems) interacted to predict team performance in anesthesia. In particular, we were interested in whether the relationship between monitoring behavior and team performance was moderated by team…

  9. Predicting Examination Performance Using an Expanded Integrated Hierarchical Model of Test Emotions and Achievement Goals

    Science.gov (United States)

    Putwain, Dave; Deveney, Carolyn

    2009-01-01

    The aim of this study was to examine an expanded integrative hierarchical model of test emotions and achievement goal orientations in predicting the examination performance of undergraduate students. Achievement goals were theorised as mediating the relationship between test emotions and performance. 120 undergraduate students completed…

  10. A Cross-Validation Study of Police Recruit Performance as Predicted by the IPI and MMPI.

    Science.gov (United States)

    Shusman, Elizabeth J.; And Others

    Validation and cross-validation studies were conducted using the Minnesota Multiphasic Personality Inventory (MMPI) and Inwald Personality Inventory (IPI) to predict job performance for 698 urban male police officers who completed a six-month training academy. Job performance criteria evaluated included absence, lateness, derelictions, negative…

  11. Assessing the performance of prediction models: a framework for traditional and novel measures

    DEFF Research Database (Denmark)

    Steyerberg, Ewout W; Vickers, Andrew J; Cook, Nancy R

    2010-01-01

    The performance of prediction models can be assessed using a variety of methods and metrics. Traditional measures for binary and survival outcomes include the Brier score to indicate overall model performance, the concordance (or c) statistic for discriminative ability (or area under the receiver...

  12. Assessing the performance of prediction models: A framework for traditional and novel measures

    NARCIS (Netherlands)

    E.W. Steyerberg (Ewout); A.J. Vickers (Andrew); N.R. Cook (Nancy); T.A. Gerds (Thomas); M. Gonen (Mithat); N. Obuchowski (Nancy); M. Pencina (Michael); M.W. Kattan (Michael)

    2010-01-01

    textabstractThe performance of prediction models can be assessed using a variety of methods and metrics. Traditional measures for binary and survival outcomes include the Brier score to indicate overall model performance, the concordance (or c) statistic for discriminative ability (or area under the

  13. Predicting Arithmetical Achievement from Neuro-Psychological Performance: A Longitudinal Study.

    Science.gov (United States)

    Fayol, Michel; Barrouillet, Pierre; Marinthe, Catherine

    1998-01-01

    Assessed whether performances of 5- and 6-year olds in arithmetic tests can be predicted from their performances in neuropsychological tests. Participants completed neuropsychological, drawing, and arithmetic tests at 5 and 6 years of age. Findings at older age were correctly assumed by conclusions of first evaluation. (LBT)

  14. The Prediction of College Student Academic Performance and Retention: Application of Expectancy and Goal Setting Theories

    Science.gov (United States)

    Friedman, Barry A.; Mandel, Rhonda G.

    2010-01-01

    Student retention and performance in higher education are important issues for educators, students, and the nation facing critical professional labor shortages. Expectancy and goal setting theories were used to predict academic performance and college student retention. Students' academic expectancy motivation at the start of the college…

  15. The Role of Resilience, Delayed Gratification and Stress in Predicting Academic Performance

    Science.gov (United States)

    Cheng, Vivienne; Catling, Jonathan

    2015-01-01

    Transition to university is an important and potentially stressful life event for students. Previous studies have shown that resilience, delay of gratification and stress can affect the academic performance of students. However, none have shown the effect of these factors in predicting academic performance, hence the current study aimed to look at…

  16. Harvested Energy Prediction Schemes for Wireless Sensor Networks: Performance Evaluation and Enhancements

    Directory of Open Access Journals (Sweden)

    Muhammad

    2017-01-01

    Full Text Available We review harvested energy prediction schemes to be used in wireless sensor networks and explore the relative merits of landmark solutions. We propose enhancements to the well-known Profile-Energy (Pro-Energy model, the so-called Improved Profile-Energy (IPro-Energy, and compare its performance with Accurate Solar Irradiance Prediction Model (ASIM, Pro-Energy, and Weather Conditioned Moving Average (WCMA. The performance metrics considered are the prediction accuracy and the execution time which measure the implementation complexity. In addition, the effectiveness of the considered models, when integrated in an energy management scheme, is also investigated in terms of the achieved throughput and the energy consumption. Both solar irradiance and wind power datasets are used for the evaluation study. Our results indicate that the proposed IPro-Energy scheme outperforms the other candidate models in terms of the prediction accuracy achieved by up to 78% for short term predictions and 50% for medium term prediction horizons. For long term predictions, its prediction accuracy is comparable to the Pro-Energy model but outperforms the other models by up to 64%. In addition, the IPro scheme is able to achieve the highest throughput when integrated in the developed energy management scheme. Finally, the ASIM scheme reports the smallest implementation complexity.

  17. Analysis of predicted and measured performance of an integrated compound parabolic concentrator (ICPC)

    Energy Technology Data Exchange (ETDEWEB)

    Winston, R.; O' Gallagher, J.J.; Muschaweck, J.; Mahoney, A.R.; Dudley, V.

    1999-07-01

    A variety of configurations of evacuated Integrated Compound Parabolic Concentrator (ICPC) tubes have been under development for many years. A particularly favorable optical design corresponds to the unit concentration limit for a fin CPC solution which is then coupled to a practical, thin, wedge-shaped absorber. Prototype collector modules using tubes with two different fin orientations (horizontal and vertical) have been fabricated and tested. Comprehensive measurements of the optical characteristics of the reflector and absorber have been used together with a detailed ray trace analysis to predict the optical performance characteristics of these designs. The observed performance agrees well with the predicted performance.

  18. A Comparative Study to Predict Student’s Performance Using Educational Data Mining Techniques

    Science.gov (United States)

    Uswatun Khasanah, Annisa; Harwati

    2017-06-01

    Student’s performance prediction is essential to be conducted for a university to prevent student fail. Number of student drop out is one of parameter that can be used to measure student performance and one important point that must be evaluated in Indonesia university accreditation. Data Mining has been widely used to predict student’s performance, and data mining that applied in this field usually called as Educational Data Mining. This study conducted Feature Selection to select high influence attributes with student performance in Department of Industrial Engineering Universitas Islam Indonesia. Then, two popular classification algorithm, Bayesian Network and Decision Tree, were implemented and compared to know the best prediction result. The outcome showed that student’s attendance and GPA in the first semester were in the top rank from all Feature Selection methods, and Bayesian Network is outperforming Decision Tree since it has higher accuracy rate.

  19. Performance prediction of a proton exchange membrane fuel cell using the ANFIS model

    Energy Technology Data Exchange (ETDEWEB)

    Vural, Yasemin; Ingham, Derek B.; Pourkashanian, Mohamed [Centre for Computational Fluid Dynamics, University of Leeds, Houldsworth Building, LS2 9JT Leeds (United Kingdom)

    2009-11-15

    In this study, the performance (current-voltage curve) prediction of a Proton Exchange Membrane Fuel Cell (PEMFC) is performed for different operational conditions using an Adaptive Neuro-Fuzzy Inference System (ANFIS). First, ANFIS is trained with a set of input and output data. The trained model is then tested with an independent set of experimental data. The trained and tested model is then used to predict the performance curve of the PEMFC under various operational conditions. The model shows very good agreement with the experimental data and this indicates that ANFIS is capable of predicting fuel cell performance (in terms of cell voltage) with a high accuracy in an easy, rapid and cost effective way for the case presented. Finally, the capabilities and the limitations of the model for the application in fuel cells have been discussed. (author)

  20. Prospects and Potential Uses of Genomic Prediction of Key Performance Traits in Tetraploid Potato

    Directory of Open Access Journals (Sweden)

    Benjamin Stich

    2018-03-01

    Full Text Available Genomic prediction is a routine tool in breeding programs of most major animal and plant species. However, its usefulness for potato breeding has not yet been evaluated in detail. The objectives of this study were to (i examine the prospects of genomic prediction of key performance traits in a diversity panel of tetraploid potato modeling additive, dominance, and epistatic effects, (ii investigate the effects of size and make up of training set, number of test environments and molecular markers on prediction accuracy, and (iii assess the effect of including markers from candidate genes on the prediction accuracy. With genomic best linear unbiased prediction (GBLUP, BayesA, BayesCπ, and Bayesian LASSO, four different prediction methods were used for genomic prediction of relative area under disease progress curve after a Phytophthora infestans infection, plant maturity, maturity corrected resistance, tuber starch content, tuber starch yield (TSY, and tuber yield (TY of 184 tetraploid potato clones or subsets thereof genotyped with the SolCAP 8.3k SNP array. The cross-validated prediction accuracies with GBLUP and the three Bayesian approaches for the six evaluated traits ranged from about 0.5 to about 0.8. For traits with a high expected genetic complexity, such as TSY and TY, we observed an 8% higher prediction accuracy using a model with additive and dominance effects compared with a model with additive effects only. Our results suggest that for oligogenic traits in general and when diagnostic markers are available in particular, the use of Bayesian methods for genomic prediction is highly recommended and that the diagnostic markers should be modeled as fixed effects. The evaluation of the relative performance of genomic prediction vs. phenotypic selection indicated that the former is superior, assuming cycle lengths and selection intensities that are possible to realize in commercial potato breeding programs.

  1. Numerical simulation of turbulence flow in a Kaplan turbine -Evaluation on turbine performance prediction accuracy-

    Science.gov (United States)

    Ko, P.; Kurosawa, S.

    2014-03-01

    The understanding and accurate prediction of the flow behaviour related to cavitation and pressure fluctuation in a Kaplan turbine are important to the design work enhancing the turbine performance including the elongation of the operation life span and the improvement of turbine efficiency. In this paper, high accuracy turbine and cavitation performance prediction method based on entire flow passage for a Kaplan turbine is presented and evaluated. Two-phase flow field is predicted by solving Reynolds-Averaged Navier-Stokes equations expressed by volume of fluid method tracking the free surface and combined with Reynolds Stress model. The growth and collapse of cavitation bubbles are modelled by the modified Rayleigh-Plesset equation. The prediction accuracy is evaluated by comparing with the model test results of Ns 400 Kaplan model turbine. As a result that the experimentally measured data including turbine efficiency, cavitation performance, and pressure fluctuation are accurately predicted. Furthermore, the cavitation occurrence on the runner blade surface and the influence to the hydraulic loss of the flow passage are discussed. Evaluated prediction method for the turbine flow and performance is introduced to facilitate the future design and research works on Kaplan type turbine.

  2. Numerical simulation of turbulence flow in a Kaplan turbine -Evaluation on turbine performance prediction accuracy-

    International Nuclear Information System (INIS)

    Ko, P; Kurosawa, S

    2014-01-01

    The understanding and accurate prediction of the flow behaviour related to cavitation and pressure fluctuation in a Kaplan turbine are important to the design work enhancing the turbine performance including the elongation of the operation life span and the improvement of turbine efficiency. In this paper, high accuracy turbine and cavitation performance prediction method based on entire flow passage for a Kaplan turbine is presented and evaluated. Two-phase flow field is predicted by solving Reynolds-Averaged Navier-Stokes equations expressed by volume of fluid method tracking the free surface and combined with Reynolds Stress model. The growth and collapse of cavitation bubbles are modelled by the modified Rayleigh-Plesset equation. The prediction accuracy is evaluated by comparing with the model test results of Ns 400 Kaplan model turbine. As a result that the experimentally measured data including turbine efficiency, cavitation performance, and pressure fluctuation are accurately predicted. Furthermore, the cavitation occurrence on the runner blade surface and the influence to the hydraulic loss of the flow passage are discussed. Evaluated prediction method for the turbine flow and performance is introduced to facilitate the future design and research works on Kaplan type turbine

  3. A Unified Model of Performance for Predicting the Effects of Sleep and Caffeine

    Science.gov (United States)

    Ramakrishnan, Sridhar; Wesensten, Nancy J.; Kamimori, Gary H.; Moon, James E.; Balkin, Thomas J.; Reifman, Jaques

    2016-01-01

    Study Objectives: Existing mathematical models of neurobehavioral performance cannot predict the beneficial effects of caffeine across the spectrum of sleep loss conditions, limiting their practical utility. Here, we closed this research gap by integrating a model of caffeine effects with the recently validated unified model of performance (UMP) into a single, unified modeling framework. We then assessed the accuracy of this new UMP in predicting performance across multiple studies. Methods: We hypothesized that the pharmacodynamics of caffeine vary similarly during both wakefulness and sleep, and that caffeine has a multiplicative effect on performance. Accordingly, to represent the effects of caffeine in the UMP, we multiplied a dose-dependent caffeine factor (which accounts for the pharmacokinetics and pharmacodynamics of caffeine) to the performance estimated in the absence of caffeine. We assessed the UMP predictions in 14 distinct laboratory- and field-study conditions, including 7 different sleep-loss schedules (from 5 h of sleep per night to continuous sleep loss for 85 h) and 6 different caffeine doses (from placebo to repeated 200 mg doses to a single dose of 600 mg). Results: The UMP accurately predicted group-average psychomotor vigilance task performance data across the different sleep loss and caffeine conditions (6% caffeine resulted in improved predictions (after caffeine consumption) by up to 70%. Conclusions: The UMP provides the first comprehensive tool for accurate selection of combinations of sleep schedules and caffeine countermeasure strategies to optimize neurobehavioral performance. Citation: Ramakrishnan S, Wesensten NJ, Kamimori GH, Moon JE, Balkin TJ, Reifman J. A unified model of performance for predicting the effects of sleep and caffeine. SLEEP 2016;39(10):1827–1841. PMID:27397562

  4. An ensemble based top performing approach for NCI-DREAM drug sensitivity prediction challenge.

    Directory of Open Access Journals (Sweden)

    Qian Wan

    Full Text Available We consider the problem of predicting sensitivity of cancer cell lines to new drugs based on supervised learning on genomic profiles. The genetic and epigenetic characterization of a cell line provides observations on various aspects of regulation including DNA copy number variations, gene expression, DNA methylation and protein abundance. To extract relevant information from the various data types, we applied a random forest based approach to generate sensitivity predictions from each type of data and combined the predictions in a linear regression model to generate the final drug sensitivity prediction. Our approach when applied to the NCI-DREAM drug sensitivity prediction challenge was a top performer among 47 teams and produced high accuracy predictions. Our results show that the incorporation of multiple genomic characterizations lowered the mean and variance of the estimated bootstrap prediction error. We also applied our approach to the Cancer Cell Line Encyclopedia database for sensitivity prediction and the ability to extract the top targets of an anti-cancer drug. The results illustrate the effectiveness of our approach in predicting drug sensitivity from heterogeneous genomic datasets.

  5. Evaluation of Design & Analysis Code, CACTUS, for Predicting Crossflow Hydrokinetic Turbine Performance

    Energy Technology Data Exchange (ETDEWEB)

    Wosnik, Martin [Univ. of New Hampshire, Durham, NH (United States). Center for Ocean Renewable Energy; Bachant, Pete [Univ. of New Hampshire, Durham, NH (United States). Center for Ocean Renewable Energy; Neary, Vincent Sinclair [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Murphy, Andrew W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2016-09-01

    CACTUS, developed by Sandia National Laboratories, is an open-source code for the design and analysis of wind and hydrokinetic turbines. While it has undergone extensive validation for both vertical axis and horizontal axis wind turbines, and it has been demonstrated to accurately predict the performance of horizontal (axial-flow) hydrokinetic turbines, its ability to predict the performance of crossflow hydrokinetic turbines has yet to be tested. The present study addresses this problem by comparing the predicted performance curves derived from CACTUS simulations of the U.S. Department of Energy’s 1:6 scale reference model crossflow turbine to those derived by experimental measurements in a tow tank using the same model turbine at the University of New Hampshire. It shows that CACTUS cannot accurately predict the performance of this crossflow turbine, raising concerns on its application to crossflow hydrokinetic turbines generally. The lack of quality data on NACA 0021 foil aerodynamic (hydrodynamic) characteristics over the wide range of angles of attack (AoA) and Reynolds numbers is identified as the main cause for poor model prediction. A comparison of several different NACA 0021 foil data sources, derived using both physical and numerical modeling experiments, indicates significant discrepancies at the high AoA experienced by foils on crossflow turbines. Users of CACTUS for crossflow hydrokinetic turbines are, therefore, advised to limit its application to higher tip speed ratios (lower AoA), and to carefully verify the reliability and accuracy of their foil data. Accurate empirical data on the aerodynamic characteristics of the foil is the greatest limitation to predicting performance for crossflow turbines with semi-empirical models like CACTUS. Future improvements of CACTUS for crossflow turbine performance prediction will require the development of accurate foil aerodynamic characteristic data sets within the appropriate ranges of Reynolds numbers and AoA.

  6. Using tipping points of emotional intelligence and cognitive competencies to predict financial performance of leaders.

    Science.gov (United States)

    Boyatzis, Richard E

    2006-01-01

    Competencies have been shown to differentiate outstanding managers and leaders from their less effective counterparts. Some of the competencies related to effectiveness reflect cognitive intelligence, but many of them are behavioral manifestations of emotional intelligence. Meanwhile, the performance measures used have often been an approximation of effectiveness. A study of leaders in a multi-national, consulting company shows that the frequency with which they demonstrate a variety of competencies, as seen by others, predicts financial performance in the seven quarters following the competency assessment. This, like other studies only clarify which competencies are necessary for outstanding performance. Borrowing from complexity theory, a tipping point analysis allows examination of how much of the competency is sufficient for outstanding performance. Using the tipping point analysis shows an even greater impact of competencies on the financial performance measures of the leaders in the study. The emotional intelligence competencies constituted most (i.e., 13/14) of the validated competencies predicting financial performance.

  7. A Free Wake Numerical Simulation for Darrieus Vertical Axis Wind Turbine Performance Prediction

    Science.gov (United States)

    Belu, Radian

    2010-11-01

    In the last four decades, several aerodynamic prediction models have been formulated for the Darrieus wind turbine performances and characteristics. We can identified two families: stream-tube and vortex. The paper presents a simplified numerical techniques for simulating vertical axis wind turbine flow, based on the lifting line theory and a free vortex wake model, including dynamic stall effects for predicting the performances of a 3-D vertical axis wind turbine. A vortex model is used in which the wake is composed of trailing stream-wise and shedding span-wise vortices, whose strengths are equal to the change in the bound vortex strength as required by the Helmholz and Kelvin theorems. Performance parameters are computed by application of the Biot-Savart law along with the Kutta-Jukowski theorem and a semi-empirical stall model. We tested the developed model with an adaptation of the earlier multiple stream-tube performance prediction model for the Darrieus turbines. Predictions by using our method are shown to compare favorably with existing experimental data and the outputs of other numerical models. The method can predict accurately the local and global performances of a vertical axis wind turbine, and can be used in the design and optimization of wind turbines for built environment applications.

  8. Performance Evaluation of 14 Neural Network Architectures Used for Predicting Heat Transfer Characteristics of Engine Oils

    Science.gov (United States)

    Al-Ajmi, R. M.; Abou-Ziyan, H. Z.; Mahmoud, M. A.

    2012-01-01

    This paper reports the results of a comprehensive study that aimed at identifying best neural network architecture and parameters to predict subcooled boiling characteristics of engine oils. A total of 57 different neural networks (NNs) that were derived from 14 different NN architectures were evaluated for four different prediction cases. The NNs were trained on experimental datasets performed on five engine oils of different chemical compositions. The performance of each NN was evaluated using a rigorous statistical analysis as well as careful examination of smoothness of predicted boiling curves. One NN, out of the 57 evaluated, correctly predicted the boiling curves for all cases considered either for individual oils or for all oils taken together. It was found that the pattern selection and weight update techniques strongly affect the performance of the NNs. It was also revealed that the use of descriptive statistical analysis such as R2, mean error, standard deviation, and T and slope tests, is a necessary but not sufficient condition for evaluating NN performance. The performance criteria should also include inspection of the smoothness of the predicted curves either visually or by plotting the slopes of these curves.

  9. Predictions of biochar production and torrefaction performance from sugarcane bagasse using interpolation and regression analysis.

    Science.gov (United States)

    Chen, Wei-Hsin; Hsu, Hung-Jen; Kumar, Gopalakrishnan; Budzianowski, Wojciech M; Ong, Hwai Chyuan

    2017-12-01

    This study focuses on the biochar formation and torrefaction performance of sugarcane bagasse, and they are predicted using the bilinear interpolation (BLI), inverse distance weighting (IDW) interpolation, and regression analysis. It is found that the biomass torrefied at 275°C for 60min or at 300°C for 30min or longer is appropriate to produce biochar as alternative fuel to coal with low carbon footprint, but the energy yield from the torrefaction at 300°C is too low. From the biochar yield, enhancement factor of HHV, and energy yield, the results suggest that the three methods are all feasible for predicting the performance, especially for the enhancement factor. The power parameter of unity in the IDW method provides the best predictions and the error is below 5%. The second order in regression analysis gives a more reasonable approach than the first order, and is recommended for the predictions. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Standardizing the performance evaluation of short-term wind prediction models

    DEFF Research Database (Denmark)

    Madsen, Henrik; Pinson, Pierre; Kariniotakis, G.

    2005-01-01

    Short-term wind power prediction is a primary requirement for efficient large-scale integration of wind generation in power systems and electricity markets. The choice of an appropriate prediction model among the numerous available models is not trivial, and has to be based on an objective...... evaluation of model performance. This paper proposes a standardized protocol for the evaluation of short-term wind-poser preciction systems. A number of reference prediction models are also described, and their use for performance comparison is analysed. The use of the protocol is demonstrated using results...... from both on-shore and off-shore wind forms. The work was developed in the frame of the Anemos project (EU R&D project) where the protocol has been used to evaluate more than 10 prediction systems....

  11. Enhancing performance of next generation FSO communication systems using soft computing-based predictions.

    Science.gov (United States)

    Kazaura, Kamugisha; Omae, Kazunori; Suzuki, Toshiji; Matsumoto, Mitsuji; Mutafungwa, Edward; Korhonen, Timo O; Murakami, Tadaaki; Takahashi, Koichi; Matsumoto, Hideki; Wakamori, Kazuhiko; Arimoto, Yoshinori

    2006-06-12

    The deterioration and deformation of a free-space optical beam wave-front as it propagates through the atmosphere can reduce the link availability and may introduce burst errors thus degrading the performance of the system. We investigate the suitability of utilizing soft-computing (SC) based tools for improving performance of free-space optical (FSO) communications systems. The SC based tools are used for the prediction of key parameters of a FSO communications system. Measured data collected from an experimental FSO communication system is used as training and testing data for a proposed multi-layer neural network predictor (MNNP) used to predict future parameter values. The predicted parameters are essential for reducing transmission errors by improving the antenna's accuracy of tracking data beams. This is particularly essential for periods considered to be of strong atmospheric turbulence. The parameter values predicted using the proposed tool show acceptable conformity with original measurements.

  12. The Role of Sleep in Predicting College Academic Performance: Is It A Unique Predictor?

    OpenAIRE

    Taylor, Daniel J.; Vatthauer, Karlyn E.; Bramoweth, Adam D.; Ruggero, Camilo; Roane, Brandy

    2013-01-01

    Few studies have looked at the predictability of academic performance (i.e., cumulative grade point average [GPA]) using sleep when common nonsleep predictors of academic performance are included. The present project studied psychological, demographic, educational, and sleep risk factors of decreased academic performance in college undergraduates. Subjects (N = 867) completed a questionnaire packet and sleep diary. It was hypothesized that low total sleep time (TST), increased sleep onset lat...

  13. Does teacher evaluation based on student performance predict motivation, well-being, and ill-being?

    Science.gov (United States)

    Cuevas, Ricardo; Ntoumanis, Nikos; Fernandez-Bustos, Juan G; Bartholomew, Kimberley

    2018-06-01

    This study tests an explanatory model based on self-determination theory, which posits that pressure experienced by teachers when they are evaluated based on their students' academic performance will differentially predict teacher adaptive and maladaptive motivation, well-being, and ill-being. A total of 360 Spanish physical education teachers completed a multi-scale inventory. We found support for a structural equation model that showed that perceived pressure predicted teacher autonomous motivation negatively, predicted amotivation positively, and was unrelated to controlled motivation. In addition, autonomous motivation predicted vitality positively and exhaustion negatively, whereas controlled motivation and amotivation predicted vitality negatively and exhaustion positively. Amotivation significantly mediated the relation between pressure and vitality and between pressure and exhaustion. The results underline the potential negative impact of pressure felt by teachers due to this type of evaluation on teacher motivation and psychological health. Copyright © 2018 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  14. On the increase of predictive performance with high-level data fusion

    International Nuclear Information System (INIS)

    Doeswijk, T.G.; Smilde, A.K.; Hageman, J.A.; Westerhuis, J.A.; Eeuwijk, F.A. van

    2011-01-01

    The combination of the different data sources for classification purposes, also called data fusion, can be done at different levels: low-level, i.e. concatenating data matrices, medium-level, i.e. concatenating data matrices after feature selection and high-level, i.e. combining model outputs. In this paper the predictive performance of high-level data fusion is investigated. Partial least squares is used on each of the data sets and dummy variables representing the classes are used as response variables. Based on the estimated responses y-hat j for data set j and class k, a Gaussian distribution p(g k |y-hat j ) is fitted. A simulation study is performed that shows the theoretical performance of high-level data fusion for two classes and two data sets. Within group correlations of the predicted responses of the two models and differences between the predictive ability of each of the separate models and the fused models are studied. Results show that the error rate is always less than or equal to the best performing subset and can theoretically approach zero. Negative within group correlations always improve the predictive performance. However, if the data sets have a joint basis, as with metabolomics data, this is not likely to happen. For equally performing individual classifiers the best results are expected for small within group correlations. Fusion of a non-predictive classifier with a classifier that exhibits discriminative ability lead to increased predictive performance if the within group correlations are strong. An example with real life data shows the applicability of the simulation results.

  15. Predictive Validity of National Basketball Association Draft Combine on Future Performance.

    Science.gov (United States)

    Teramoto, Masaru; Cross, Chad L; Rieger, Randall H; Maak, Travis G; Willick, Stuart E

    2018-02-01

    Teramoto, M, Cross, CL, Rieger, RH, Maak, TG, and Willick, SE. Predictive validity of national basketball association draft combine on future performance. J Strength Cond Res 32(2): 396-408, 2018-The National Basketball Association (NBA) Draft Combine is an annual event where prospective players are evaluated in terms of their athletic abilities and basketball skills. Data collected at the Combine should help NBA teams select right the players for the upcoming NBA draft; however, its value for predicting future performance of players has not been examined. This study investigated predictive validity of the NBA Draft Combine on future performance of basketball players. We performed a principal component analysis (PCA) on the 2010-2015 Combine data to reduce correlated variables (N = 234), a correlation analysis on the Combine data and future on-court performance to examine relationships (maximum pairwise N = 217), and a robust principal component regression (PCR) analysis to predict first-year and 3-year on-court performance from the Combine measures (N = 148 and 127, respectively). Three components were identified within the Combine data through PCA (= Combine subscales): length-size, power-quickness, and upper-body strength. As per the correlation analysis, the individual Combine items for anthropometrics, including height without shoes, standing reach, weight, wingspan, and hand length, as well as the Combine subscale of length-size, had positive, medium-to-large-sized correlations (r = 0.313-0.545) with defensive performance quantified by Defensive Box Plus/Minus. The robust PCR analysis showed that the Combine subscale of length-size was a predictor most significantly associated with future on-court performance (p ≤ 0.05), including Win Shares, Box Plus/Minus, and Value Over Replacement Player, followed by upper-body strength. In conclusion, the NBA Draft Combine has value for predicting future performance of players.

  16. Reverse translated and gold standard continuous performance tests predict global cognitive performance in schizophrenia.

    Science.gov (United States)

    Bismark, Andrew W; Thomas, Michael L; Tarasenko, Melissa; Shiluk, Alexandra L; Rackelmann, Sonia Y; Young, Jared W; Light, Gregory A

    2018-04-12

    Attentional dysfunction contributes to functional impairments in schizophrenia (SZ). Sustained attention is typically assessed via continuous performance tasks (CPTs), though many CPTs have limited cross-species translational validity and place demands on additional cognitive domains. A reverse-translated 5-Choice Continuous Performance Task (5C-CPT) for human testing-originally developed for use in rodents-was designed to minimize demands on perceptual, visual learning, processing speed, or working memory functions. To-date, no studies have validated the 5C-CPT against gold standard attentional measures nor evaluated how 5C-CPT scores relate to cognition in SZ. Here we examined the relationship between the 5C-CPT and the CPT-Identical Pairs (CPT-IP), an established and psychometrically robust measure of vigilance from the MATRICS Consensus Cognitive Battery (MCCB) in a sample of SZ patients (n = 35). Relationships to global and individual subdomains of cognition were also assessed. 5C-CPT and CPT-IP measures of performance (d-prime) were strongly correlated (r = 0.60). In a regression model, the 5C-CPT and CPT-IP collectively accounted for 54% of the total variance in MCCB total scores, and 27.6% of overall cognitive variance was shared between the 5C-CPT and CPT-IP. These results indicate that the reverse translated 5C-CPT and the gold standard CPT-IP index a common attentional construct that also significantly overlaps with variance in general cognitive performance. The use of simple, cross-species validated behavioral indices of attentional/cognitive functioning such as the 5C-CPT could accelerate the development of novel generalized pro-cognitive therapeutics for SZ and related neuropsychiatric disorders.

  17. Estimating the Performance of Random Forest versus Multiple Regression for Predicting Prices of the Apartments

    Directory of Open Access Journals (Sweden)

    Marjan Čeh

    2018-05-01

    Full Text Available The goal of this study is to analyse the predictive performance of the random forest machine learning technique in comparison to commonly used hedonic models based on multiple regression for the prediction of apartment prices. A data set that includes 7407 records of apartment transactions referring to real estate sales from 2008–2013 in the city of Ljubljana, the capital of Slovenia, was used in order to test and compare the predictive performances of both models. Apparent challenges faced during modelling included (1 the non-linear nature of the prediction assignment task; (2 input data being based on transactions occurring over a period of great price changes in Ljubljana whereby a 28% decline was noted in six consecutive testing years; and (3 the complex urban form of the case study area. Available explanatory variables, organised as a Geographic Information Systems (GIS ready dataset, including the structural and age characteristics of the apartments as well as environmental and neighbourhood information were considered in the modelling procedure. All performance measures (R2 values, sales ratios, mean average percentage error (MAPE, coefficient of dispersion (COD revealed significantly better results for predictions obtained by the random forest method, which confirms the prospective of this machine learning technique on apartment price prediction.

  18. Individualized performance prediction during total sleep deprivation: accounting for trait vulnerability to sleep loss.

    Science.gov (United States)

    Ramakrishnan, Sridhar; Laxminarayan, Srinivas; Thorsley, David; Wesensten, Nancy J; Balkin, Thomas J; Reifman, Jaques

    2012-01-01

    Individual differences in vulnerability to sleep loss can be considerable, and thus, recent efforts have focused on developing individualized models for predicting the effects of sleep loss on performance. Individualized models constructed using a Bayesian formulation, which combines an individual's available performance data with a priori performance predictions from a group-average model, typically need at least 40 h of individual data before showing significant improvement over the group-average model predictions. Here, we improve upon the basic Bayesian formulation for developing individualized models by observing that individuals may be classified into three sleep-loss phenotypes: resilient, average, and vulnerable. For each phenotype, we developed a phenotype-specific group-average model and used these models to identify each individual's phenotype. We then used the phenotype-specific models within the Bayesian formulation to make individualized predictions. Results on psychomotor vigilance test data from 48 individuals indicated that, on average, ∼85% of individual phenotypes were accurately identified within 30 h of wakefulness. The percentage improvement of the proposed approach in 10-h-ahead predictions was 16% for resilient subjects and 6% for vulnerable subjects. The trade-off for these improvements was a slight decrease in prediction accuracy for average subjects.

  19. Genome-Wide Polygenic Scores Predict Reading Performance Throughout the School Years.

    Science.gov (United States)

    Selzam, Saskia; Dale, Philip S; Wagner, Richard K; DeFries, John C; Cederlöf, Martin; O'Reilly, Paul F; Krapohl, Eva; Plomin, Robert

    2017-07-04

    It is now possible to create individual-specific genetic scores, called genome-wide polygenic scores (GPS). We used a GPS for years of education ( EduYears ) to predict reading performance assessed at UK National Curriculum Key Stages 1 (age 7), 2 (age 12) and 3 (age 14) and on reading tests administered at ages 7 and 12 in a UK sample of 5,825 unrelated individuals. EduYears GPS accounts for up to 5% of the variance in reading performance at age 14. GPS predictions remained significant after accounting for general cognitive ability and family socioeconomic status. Reading performance of children in the lowest and highest 12.5% of the EduYears GPS distribution differed by a mean growth in reading ability of approximately two school years. It seems certain that polygenic scores will be used to predict strengths and weaknesses in education.

  20. Computerized heat balance models to predict performance of operating nuclear power plants

    International Nuclear Information System (INIS)

    Breeding, C.L.; Carter, J.C.; Schaefer, R.C.

    1983-01-01

    The use of computerized heat balance models has greatly enhanced the decision making ability of TVA's Division of Nuclear Power. These models are utilized to predict the effects of various operating modes and to analyze changes in plant performance resulting from turbine cycle equipment modifications with greater speed and accuracy than was possible before. Computer models have been successfully used to optimize plant output by predicting the effects of abnormal condenser circulating water conditions. They were utilized to predict the degradation in performance resulting from installation of a baffle plate assembly to replace damaged low-pressure blading, thereby providing timely information allowing an optimal economic judgement as to when to replace the blading. Future use will be for routine performance test analysis. This paper presents the benefits of utility use of computerized heat balance models

  1. Personality traits measured at baseline can predict academic performance in upper secondary school three years late.

    Science.gov (United States)

    Rosander, Pia; Bäckström, Martin

    2014-12-01

    The aim of the present study was to explore the ability of personality to predict academic performance in a longitudinal study of a Swedish upper secondary school sample. Academic performance was assessed throughout a three-year period via final grades from the compulsory school and upper secondary school. The Big Five personality factors (Costa & McCrae, ) - particularly Conscientiousness and Neuroticism - were found to predict overall academic performance, after controlling for general intelligence. Results suggest that Conscientiousness, as measured at the age of 16, can explain change in academic performance at the age of 19. The effect of Neuroticism on Conscientiousness indicates that, as regarding getting good grades, it is better to be a bit neurotic than to be stable. The study extends previous work by assessing the relationship between the Big Five and academic performance over a three-year period. The results offer educators avenues for improving educational achievement. © 2014 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

  2. The role of sleep in predicting college academic performance: is it a unique predictor?

    Science.gov (United States)

    Taylor, Daniel J; Vatthauer, Karlyn E; Bramoweth, Adam D; Ruggero, Camilo; Roane, Brandy

    2013-01-01

    Few studies have looked at the predictability of academic performance (i.e., cumulative grade point average [GPA]) using sleep when common nonsleep predictors of academic performance are included. This project studied psychological, demographic, educational, and sleep risk factors of decreased academic performance in college undergraduates. Participants (N = 867) completed a questionnaire packet and sleep diary. It was hypothesized that low total sleep time (TST), increased sleep onset latency, later bedtimes, later wake times, and TST inconsistency would predict decreased academic performance. The most significant predictors of academic performance were high school GPA, standardized test scores (i.e., SAT/ACT), TST, time awake before arising (TWAK), TST inconsistency, and the quadratic terms of perceived stress (PSS) and TST.

  3. Neither here, nor there: impression management does not predict expatriate adjustment and job performance

    Directory of Open Access Journals (Sweden)

    HANNAH JACKSON FOLDES

    2006-09-01

    Full Text Available Social desirability scale scores reflect substantive individual differences related to personality. The objective of the current study was to examine whether social desirability, and impression management specifically (a component of social desirability, is predictive of adjustment and job performance for expatriates. Based on theoretical considerations, it was proposed that impression management might be linked to expatriate job performance in a predictive and mediated relationship through adjustment. Job performance ratings provided by host country national co-workers were obtained for 308 expatriates on assignment in Turkey. Expatriates responded to a measure of personality and cross cultural adjustment. It was found that impression management scale scores were not related to either adjustment or job performance. These results are discussed in the broader context of research on social desirability, expatriate job performance, and expatriate research in general.

  4. Occupational-Specific Strength Predicts Astronaut-Related Task Performance in a Weighted Suit.

    Science.gov (United States)

    Taylor, Andrew; Kotarsky, Christopher J; Bond, Colin W; Hackney, Kyle J

    2018-01-01

    Future space missions beyond low Earth orbit will require deconditioned astronauts to perform occupationally relevant tasks within a planetary spacesuit. The prediction of time-to-completion (TTC) of astronaut tasks will be critical for crew safety, autonomous operations, and mission success. This exploratory study determined if the addition of task-specific strength testing to current standard lower body testing would enhance the prediction of TTC in a 1-G test battery. Eight healthy participants completed NASA lower body strength tests, occupationally specific strength tests, and performed six task simulations (hand drilling, construction wrenching, incline walking, collecting weighted samples, and dragging an unresponsive crewmember to safety) in a 48-kg weighted suit. The TTC for each task was recorded and summed to obtain a total TTC for the test battery. Linear regression was used to predict total TTC with two models: 1) NASA lower body strength tests; and 2) NASA lower body strength tests + occupationally specific strength tests. Total TTC of the test battery ranged from 20.2-44.5 min. The lower body strength test alone accounted for 61% of the variability in total TTC. The addition of hand drilling and wrenching strength tests accounted for 99% of the variability in total TTC. Adding occupationally specific strength tests (hand drilling and wrenching) to standard lower body strength tests successfully predicted total TTC in a performance test battery within a weighted suit. Future research should couple these strength tests with higher fidelity task simulations to determine the utility and efficacy of task performance prediction.Taylor A, Kotarsky CJ, Bond CW, Hackney KJ. Occupational-specific strength predicts astronaut-related task performance in a weighted suit. Aerosp Med Hum Perform. 2018; 89(1):58-62.

  5. Scientific basis for long-term prediction of waste-form performance under repository conditions

    International Nuclear Information System (INIS)

    Mendel, J.E.

    1982-10-01

    This paper presents an overview of the fundamental principles involved in predicting long-term performance of waste forms by the as-low-as-reasonably-achievable approach. Repository conditions which make up the waste-form environment, the aging of the waste form, the important radionuclides in the waste form, the chemistry of repository fluids, and multicomponent interactions testing were considered in order to describe these principles. The need for confidence limits on the prediction of waste-form performance and ways of achieving a definition of the confidence limits are discussed

  6. A fuzzy expert system for predicting the performance of switched reluctance motor

    International Nuclear Information System (INIS)

    Mirzaeian, B.; Moallem, M.; Lucas, Caro

    2001-01-01

    In this paper a fuzzy expert system for predicting the performance of a switched reluctance motor has been developed. The design vector consists of design parameters, and output performance variables are efficiency and torque ripple. An accurate analysis program based on Improved Magnetic Equivalent Circuit method has been used to generate the input-output data. These input-output data is used to produce the initial fuzzy rules for predicting the performance of Switched Reluctance Motor. The initial set of fuzzy rules with triangular membership functions has been devised using a table look-up scheme. The initial fuzzy rules have been optimized to a set of fuzzy rules with Gaussian membership functions using gradient descent training scheme. The performance prediction results for a 6/8, 4 kw, Switched Reluctance Motor shows good agreement with the results obtained from Improved Magnetic Equivalent Circuit method or Finite Element analysis. The developed fuzzy expert system can be used for fast prediction of motor performance in the optimal design process or on-line control schemes of Switched Reluctance motor

  7. Playing off the curve - testing quantitative predictions of skill acquisition theories in development of chess performance.

    Science.gov (United States)

    Gaschler, Robert; Progscha, Johanna; Smallbone, Kieran; Ram, Nilam; Bilalić, Merim

    2014-01-01

    Learning curves have been proposed as an adequate description of learning processes, no matter whether the processes manifest within minutes or across years. Different mechanisms underlying skill acquisition can lead to differences in the shape of learning curves. In the current study, we analyze the tournament performance data of 1383 chess players who begin competing at young age and play tournaments for at least 10 years. We analyze the performance development with the goal to test the adequacy of learning curves, and the skill acquisition theories they are based on, for describing and predicting expertise acquisition. On the one hand, we show that the skill acquisition theories implying a negative exponential learning curve do a better job in both describing early performance gains and predicting later trajectories of chess performance than those theories implying a power function learning curve. On the other hand, the learning curves of a large proportion of players show systematic qualitative deviations from the predictions of either type of skill acquisition theory. While skill acquisition theories predict larger performance gains in early years and smaller gains in later years, a substantial number of players begin to show substantial improvements with a delay of several years (and no improvement in the first years), deviations not fully accounted for by quantity of practice. The current work adds to the debate on how learning processes on a small time scale combine to large-scale changes.

  8. Examining the Roles of Reasoning and Working Memory in Predicting Casual Game Performance across Extended Gameplay.

    Science.gov (United States)

    Kranz, Michael B; Baniqued, Pauline L; Voss, Michelle W; Lee, Hyunkyu; Kramer, Arthur F

    2017-01-01

    The variety and availability of casual video games presents an exciting opportunity for applications such as cognitive training. Casual games have been associated with fluid abilities such as working memory (WM) and reasoning, but the importance of these cognitive constructs in predicting performance may change across extended gameplay and vary with game structure. The current investigation examined the relationship between cognitive abilities and casual game performance over time by analyzing first and final session performance over 4-5 weeks of game play. We focused on two groups of subjects who played different types of casual games previously shown to relate to WM and reasoning when played for a single session: (1) puzzle-based games played adaptively across sessions and (2) speeded switching games played non-adaptively across sessions. Reasoning uniquely predicted first session casual game scores for both groups and accounted for much of the relationship with WM. Furthermore, over time, WM became uniquely important for predicting casual game performance for the puzzle-based adaptive games but not for the speeded switching non-adaptive games. These results extend the burgeoning literature on cognitive abilities involved in video games by showing differential relationships of fluid abilities across different game types and extended play. More broadly, the current study illustrates the usefulness of using multiple cognitive measures in predicting performance, and provides potential directions for game-based cognitive training research.

  9. Examining the Roles of Reasoning and Working Memory in Predicting Casual Game Performance across Extended Gameplay

    Science.gov (United States)

    Kranz, Michael B.; Baniqued, Pauline L.; Voss, Michelle W.; Lee, Hyunkyu; Kramer, Arthur F.

    2017-01-01

    The variety and availability of casual video games presents an exciting opportunity for applications such as cognitive training. Casual games have been associated with fluid abilities such as working memory (WM) and reasoning, but the importance of these cognitive constructs in predicting performance may change across extended gameplay and vary with game structure. The current investigation examined the relationship between cognitive abilities and casual game performance over time by analyzing first and final session performance over 4–5 weeks of game play. We focused on two groups of subjects who played different types of casual games previously shown to relate to WM and reasoning when played for a single session: (1) puzzle-based games played adaptively across sessions and (2) speeded switching games played non-adaptively across sessions. Reasoning uniquely predicted first session casual game scores for both groups and accounted for much of the relationship with WM. Furthermore, over time, WM became uniquely important for predicting casual game performance for the puzzle-based adaptive games but not for the speeded switching non-adaptive games. These results extend the burgeoning literature on cognitive abilities involved in video games by showing differential relationships of fluid abilities across different game types and extended play. More broadly, the current study illustrates the usefulness of using multiple cognitive measures in predicting performance, and provides potential directions for game-based cognitive training research. PMID:28326042

  10. Genome-Wide Prediction of the Performance of Three-Way Hybrids in Barley

    Directory of Open Access Journals (Sweden)

    Zuo Li

    2017-03-01

    Full Text Available Predicting the grain yield performance of three-way hybrids is challenging. Three-way crosses are relevant for hybrid breeding in barley ( L. and maize ( L. adapted to East Africa. The main goal of our study was to implement and evaluate genome-wide prediction approaches of the performance of three-way hybrids using data of single-cross hybrids for a scenario in which parental lines of the three-way hybrids originate from three genetically distinct subpopulations. We extended the ridge regression best linear unbiased prediction (RRBLUP and devised a genomic selection model allowing for subpopulation-specific marker effects (GSA-RRBLUP: general and subpopulation-specific additive RRBLUP. Using an empirical barley data set, we showed that applying GSA-RRBLUP tripled the prediction ability of three-way hybrids from 0.095 to 0.308 compared with RRBLUP, modeling one additive effect for all three subpopulations. The experimental findings were further substantiated with computer simulations. Our results emphasize the potential of GSA-RRBLUP to improve genome-wide hybrid prediction of three-way hybrids for scenarios of genetically diverse parental populations. Because of the advantages of the GSA-RRBLUP model in dealing with hybrids from different parental populations, it may also be a promising approach to boost the prediction ability for hybrid breeding programs based on genetically diverse heterotic groups.

  11. Climate Prediction for Brazil's Nordeste: Performance of Empirical and Numerical Modeling Methods.

    Science.gov (United States)

    Moura, Antonio Divino; Hastenrath, Stefan

    2004-07-01

    Comparisons of performance of climate forecast methods require consistency in the predictand and a long common reference period. For Brazil's Nordeste, empirical methods developed at the University of Wisconsin use preseason (October January) rainfall and January indices of the fields of meridional wind component and sea surface temperature (SST) in the tropical Atlantic and the equatorial Pacific as input to stepwise multiple regression and neural networking. These are used to predict the March June rainfall at a network of 27 stations. An experiment at the International Research Institute for Climate Prediction, Columbia University, with a numerical model (ECHAM4.5) used global SST information through February to predict the March June rainfall at three grid points in the Nordeste. The predictands for the empirical and numerical model forecasts are correlated at +0.96, and the period common to the independent portion of record of the empirical prediction and the numerical modeling is 1968 99. Over this period, predicted versus observed rainfall are evaluated in terms of correlation, root-mean-square error, absolute error, and bias. Performance is high for both approaches. Numerical modeling produces a correlation of +0.68, moderate errors, and strong negative bias. For the empirical methods, errors and bias are small, and correlations of +0.73 and +0.82 are reached between predicted and observed rainfall.

  12. Predictive validity of the comprehensive basic science examination mean score for assessment of medical students' performance

    Directory of Open Access Journals (Sweden)

    Firouz Behboudi

    2002-04-01

    Full Text Available Background Medical education curriculum improvements can be achieved bye valuating students performance. Medical students have to pass two undergraduate comprehensive examinations, basic science and preinternship, in Iran. Purpose To measure validity of the students' mean score in comprehensive basic science exam (CBSE for predicting their performance in later curriculum phases. Methods This descriptive cross-sectional study was conducted on 95 (38 women and 55 men Guilan medical university students. Their admission to the university was 81% by regional quota and 12% by shaheed and other organizations' share. They first enrolled in 1994 and were able to pass CBS£ at first try. Data on gender, regional quota, and average grades of CBS£, PC, and CPIE were collected by a questionnaire. The calculations were done by SPSS package. Results The correlation coefficient between CBS£ and CPIE mean scores (0.65 was higher than correlation coefficient between CBS£ and PC mean scores (0.49. The predictive validity of CBS£ average grade was significant for students' performance in CPIE; however, the predictive validity of CBSE mean scores for students I pe1jormance in PC was lower. Conclusion he students' mean score in CBSE can be a good denominator for their further admission. We recommend further research to assess the predictive validity for each one of the basic courses. Keywords predictive validity, comprehensive basic exam

  13. Using individual differences to predict job performance: correcting for direct and indirect restriction of range.

    Science.gov (United States)

    Sjöberg, Sofia; Sjöberg, Anders; Näswall, Katharina; Sverke, Magnus

    2012-08-01

    The present study investigates the relationship between individual differences, indicated by personality (FFM) and general mental ability (GMA), and job performance applying two different methods of correction for range restriction. The results, derived by analyzing meta-analytic correlations, show that the more accurate method of correcting for indirect range restriction increased the operational validity of individual differences in predicting job performance and that this increase primarily was due to general mental ability being a stronger predictor than any of the personality traits. The estimates for single traits can be applied in practice to maximize prediction of job performance. Further, differences in the relative importance of general mental ability in relation to overall personality assessment methods was substantive and the estimates provided enables practitioners to perform a correct utility analysis of their overall selection procedure. © 2012 The Authors. Scandinavian Journal of Psychology © 2012 The Scandinavian Psychological Associations.

  14. Prediction of small spark ignited engine performance using producer gas as fuel

    Directory of Open Access Journals (Sweden)

    N. Homdoung

    2015-03-01

    Full Text Available Producer gas from biomass gasification is expected to contribute to greater energy mix in the future. Therefore, effect of producer gas on engine performance is of great interest. Evaluation of engine performances can be hard and costly. Ideally, they may be predicted mathematically. This work was to apply mathematical models in evaluating performance of a small producer gas engine. The engine was a spark ignition, single cylinder unit with a CR of 14:1. Simulation was carried out on full load and varying engine speeds. From simulated results, it was found that the simple mathematical model can predict the performance of the gas engine and gave good agreement with experimental results. The differences were within ±7%.

  15. Applying mathematical models to predict resident physician performance and alertness on traditional and novel work schedules.

    Science.gov (United States)

    Klerman, Elizabeth B; Beckett, Scott A; Landrigan, Christopher P

    2016-09-13

    In 2011 the U.S. Accreditation Council for Graduate Medical Education began limiting first year resident physicians (interns) to shifts of ≤16 consecutive hours. Controversy persists regarding the effectiveness of this policy for reducing errors and accidents while promoting education and patient care. Using a mathematical model of the effects of circadian rhythms and length of time awake on objective performance and subjective alertness, we quantitatively compared predictions for traditional intern schedules to those that limit work to ≤ 16 consecutive hours. We simulated two traditional schedules and three novel schedules using the mathematical model. The traditional schedules had extended duration work shifts (≥24 h) with overnight work shifts every second shift (including every third night, Q3) or every third shift (including every fourth night, Q4) night; the novel schedules had two different cross-cover (XC) night team schedules (XC-V1 and XC-V2) and a Rapid Cycle Rotation (RCR) schedule. Predicted objective performance and subjective alertness for each work shift were computed for each individual's schedule within a team and then combined for the team as a whole. Our primary outcome was the amount of time within a work shift during which a team's model-predicted objective performance and subjective alertness were lower than that expected after 16 or 24 h of continuous wake in an otherwise rested individual. The model predicted fewer hours with poor performance and alertness, especially during night-time work hours, for all three novel schedules than for either the traditional Q3 or Q4 schedules. Three proposed schedules that eliminate extended shifts may improve performance and alertness compared with traditional Q3 or Q4 schedules. Predicted times of worse performance and alertness were at night, which is also a time when supervision of trainees is lower. Mathematical modeling provides a quantitative comparison approach with potential to aid

  16. Comparison of measured and predicted long term performance of grid a connected photovoltaic system

    International Nuclear Information System (INIS)

    Mondol, Jayanta Deb; Yohanis, Yigzaw G.; Norton, Brian

    2007-01-01

    Predicted performance of a grid connected photovoltaic (PV) system using TRNSYS was compared with measured data. A site specific global-diffuse correlation model was developed and used to calculate the beam and diffuse components of global horizontal insolation. A PV module temperature equation and a correlation relating input and output power of an inverter were developed using measured data and used in TRNSYS to perform PV array and inverter outputs simulation. Different combinations of the tilted surface radiation model, global-diffuse correlation model and PV module temperature equation were used in the simulations. Statistical error analysis was performed to compare the results for each combination. The simulation accuracy was improved by using the new global-diffuse correlation and module temperature equation in the TRNSYS simulation. For an isotropic sky tilted surface radiation model, the average monthly difference between measured and predicted PV output before and after modification of the TRNSYS component were 10.2% and 3.3%, respectively, and, for an anisotropic sky model, 15.4% and 10.7%, respectively. For inverter output, the corresponding errors were 10.4% and 3.3% and 15.8% and 8.6%, respectively. Measured PV efficiency, overall system efficiency, inverter efficiency and performance ratio of the system were compared with the predicted results. The predicted PV performance parameters agreed more closely with the measured parameters in summer than in winter. The difference between predicted performances using an isotropic and an anisotropic sky tilted surface models is between 1% and 2%

  17. Determination of Constructs and Dimensions of Employability Skills Based Work Performance Prediction: A Triangular Approach

    OpenAIRE

    Rahmat, Normala; Buntat, Yahya; Ayub, Abdul Rahman

    2015-01-01

    The level of the employability skills of the graduates as determined by job role and mapped to the employability skills, which correspond to the requirement of employers, will have significant impact on the graduates’ job performance. The main objective of this study was to identify the constructs and dimensions of employability skills, which can predict the work performance of electronic polytechnic graduate in electrical and electronics industry. A triangular qualitative approach was used i...

  18. Using social media and machine learning to predict financial performance of a company

    OpenAIRE

    Forouzani, Sepehr

    2016-01-01

    Social media have recently become one of the most popular communicating form of media for numerous number of people. the text and posts shared on social media is widely used by researcher to analyze, study and relate them to various fields. In this master thesis, sentiment analysis has been performed on posts containing information about two companies that are shared on Twitter, and machine learning algorithms has been used to predict the financial performance of these companies.

  19. On predicting student performance using low-rank matrix factorization techniques

    DEFF Research Database (Denmark)

    Lorenzen, Stephan Sloth; Pham, Dang Ninh; Alstrup, Stephen

    2017-01-01

    Predicting the score of a student is one of the important problems in educational data mining. The scores given by an individual student reflect how a student understands and applies the knowledge conveyed in class. A reliable performance prediction enables teachers to identify weak students...... that require remedial support, generate adaptive hints, and improve the learning of students. This work focuses on predicting the score of students in the quiz system of the Clio Online learning platform, the largest Danish supplier of online learning materials, covering 90% of Danish elementary schools...... and the current version of the data set is very sparse, the very low-rank approximation can capture enough information. This means that the simple baseline approach achieves similar performance compared to other advanced methods. In future work, we will restrict the quiz data set, e.g. only including quizzes...

  20. Using micro saint to predict performance in a nuclear power plant control room

    International Nuclear Information System (INIS)

    Lawless, M.T.; Laughery, K.R.; Persenky, J.J.

    1995-09-01

    The United States Nuclear Regulatory Commission (NRC) requires a technical basis for regulatory actions. In the area of human factors, one possible technical basis is human performance modeling technology including task network modeling. This study assessed the feasibility and validity of task network modeling to predict the performance of control room crews. Task network models were built that matched the experimental conditions of a study on computerized procedures that was conducted at North Carolina State University. The data from the open-quotes paper proceduresclose quotes conditions were used to calibrate the task network models. Then, the models were manipulated to reflect expected changes when computerized procedures were used. These models' predictions were then compared to the experimental data from the open-quotes computerized conditionsclose quotes of the North Carolina State University study. Analyses indicated that the models predicted some subsets of the data well, but not all. Implications for the use of task network modeling are discussed

  1. Intraindividual Variability in Basic Reaction Time Predicts Middle-Aged and Older Pilots’ Flight Simulator Performance

    Science.gov (United States)

    2013-01-01

    Objectives. Intraindividual variability (IIV) is negatively associated with cognitive test performance and is positively associated with age and some neurological disorders. We aimed to extend these findings to a real-world task, flight simulator performance. We hypothesized that IIV predicts poorer initial flight performance and increased rate of decline in performance among middle-aged and older pilots. Method. Two-hundred and thirty-six pilots (40–69 years) completed annual assessments comprising a cognitive battery and two 75-min simulated flights in a flight simulator. Basic and complex IIV composite variables were created from measures of basic reaction time and shifting and divided attention tasks. Flight simulator performance was characterized by an overall summary score and scores on communication, emergencies, approach, and traffic avoidance components. Results. Although basic IIV did not predict rate of decline in flight performance, it had a negative association with initial performance for most flight measures. After taking into account processing speed, basic IIV explained an additional 8%–12% of the negative age effect on initial flight performance. Discussion. IIV plays an important role in real-world tasks and is another aspect of cognition that underlies age-related differences in cognitive performance. PMID:23052365

  2. Intraindividual variability in basic reaction time predicts middle-aged and older pilots' flight simulator performance.

    Science.gov (United States)

    Kennedy, Quinn; Taylor, Joy; Heraldez, Daniel; Noda, Art; Lazzeroni, Laura C; Yesavage, Jerome

    2013-07-01

    Intraindividual variability (IIV) is negatively associated with cognitive test performance and is positively associated with age and some neurological disorders. We aimed to extend these findings to a real-world task, flight simulator performance. We hypothesized that IIV predicts poorer initial flight performance and increased rate of decline in performance among middle-aged and older pilots. Two-hundred and thirty-six pilots (40-69 years) completed annual assessments comprising a cognitive battery and two 75-min simulated flights in a flight simulator. Basic and complex IIV composite variables were created from measures of basic reaction time and shifting and divided attention tasks. Flight simulator performance was characterized by an overall summary score and scores on communication, emergencies, approach, and traffic avoidance components. Although basic IIV did not predict rate of decline in flight performance, it had a negative association with initial performance for most flight measures. After taking into account processing speed, basic IIV explained an additional 8%-12% of the negative age effect on initial flight performance. IIV plays an important role in real-world tasks and is another aspect of cognition that underlies age-related differences in cognitive performance.

  3. The Role of Goal Importance in Predicting University Students' High Academic Performance

    Science.gov (United States)

    Kyle, Vanessa A.; White, Katherine M.; Hyde, Melissa K.; Occhipinti, Stefano

    2014-01-01

    We examined goal importance, focusing on high, but not exclusive priority goals, in the theory of planned behaviour (TPB) to predict students' academic performance. At the beginning of semester, students in a psychology subject (N = 197) completed TPB and goal importance items for achieving a high grade. Regression analyses revealed partial…

  4. Towards accurate performance prediction of a vertical axis wind turbine operating at different tip speed ratios

    NARCIS (Netherlands)

    Rezaeiha, A.; Kalkman, I.; Blocken, B.J.E.

    2017-01-01

    Accurate prediction of the performance of a vertical-axis wind turbine (VAWT) using CFD simulation requires the employment of a sufficiently fine azimuthal increment (dθ) combined with a mesh size at which essential flow characteristics can be accurately resolved. Furthermore, the domain size needs

  5. Validity of the Optometry Admission Test in Predicting Performance in Schools and Colleges of Optometry.

    Science.gov (United States)

    Kramer, Gene A.; Johnston, JoElle

    1997-01-01

    A study examined the relationship between Optometry Admission Test scores and pre-optometry or undergraduate grade point average (GPA) with first and second year performance in optometry schools. The test's predictive validity was limited but significant, and comparable to those reported for other admission tests. In addition, the scores…

  6. Geographic and temporal validity of prediction models: Different approaches were useful to examine model performance

    NARCIS (Netherlands)

    P.C. Austin (Peter); D. van Klaveren (David); Y. Vergouwe (Yvonne); D. Nieboer (Daan); D.S. Lee (Douglas); E.W. Steyerberg (Ewout)

    2016-01-01

    textabstractObjective: Validation of clinical prediction models traditionally refers to the assessment of model performance in new patients. We studied different approaches to geographic and temporal validation in the setting of multicenter data from two time periods. Study Design and Setting: We

  7. Towards cycle-accurate performance predictions for real-time embedded systems

    NARCIS (Netherlands)

    Triantafyllidis, K.; Bondarev, E.; With, de P.H.N.; Arabnia, H.R.; Deligiannidis, L.; Jandieri, G.

    2013-01-01

    In this paper we present a model-based performance analysis method for component-based real-time systems, featuring cycle-accurate predictions of latencies and enhanced system robustness. The method incorporates the following phases: (a) instruction-level profiling of SW components, (b) modeling the

  8. Performance of genomic prediction within and across generations in maritime pine

    NARCIS (Netherlands)

    Bartholomé, Jérôme; Heerwaarden, Van Joost; Isik, Fikret; Boury, Christophe; Vidal, Marjorie; Plomion, Christophe; Bouffier, Laurent

    2016-01-01

    Background: Genomic selection (GS) is a promising approach for decreasing breeding cycle length in forest trees. Assessment of progeny performance and of the prediction accuracy of GS models over generations is therefore a key issue. Results: A reference population of maritime pine (Pinus

  9. Person-Environment Congruence and Personality Domains in the Prediction of Job Performance and Work Quality

    Science.gov (United States)

    Kieffer, Kevin M.; Schinka, John A.; Curtiss, Glenn

    2004-01-01

    This study examined the contributions of the 5-Factor Model (FFM; P. T. Costa & R. R. McCrae, 1992) and RIASEC (J. L. Holland, 1994) constructs of consistency, differentiation, and person-environment congruence in predicting job performance ratings in a large sample (N = 514) of employees. Hierarchical regression analyses conducted separately by…

  10. Hybrid ANN–PLS approach to scroll compressor thermodynamic performance prediction

    International Nuclear Information System (INIS)

    Tian, Z.; Gu, B.; Yang, L.; Lu, Y.

    2015-01-01

    In this paper, a scroll compressor thermodynamic performance prediction was carried out by applying a hybrid ANN–PLS model. Firstly, an experimental platform with second-refrigeration calorimeter was set up and steady-state scroll compressor data sets were collected from experiments. Then totally 148 data sets were introduced to train and verify the validity of the ANN–PLS model for predicting the scroll compressor parameters such as volumetric efficiency, refrigerant mass flow rate, discharge temperature and power consumption. The ANN–PLS model was determined with 5 hidden neurons and 7 latent variables through the training process. Ultimately, the ANN–PLS model showed better performance than the ANN model and the PLS model working separately. ANN–PLS predictions agree well with the experimental values with mean relative errors (MREs) in the range of 0.34–1.96%, correlation coefficients (R 2 ) in the range of 0.9703–0.9999 and very low root mean square errors (RMSEs). - Highlights: • Hybrid ANN–PLS is utilized to predict the thermodynamic performance of scroll compressor. • ANN–PLS model is determined with 5 hidden neurons and 7 latent variables. • ANN–PLS model demonstrates better performance than ANN and PLS working separately. • The values of MRE and RMSE are in the range of 0.34–1.96% and 0.9703–0.9999, respectively

  11. The Impact of Team Identification on Biased Predictions of Player Performance

    Science.gov (United States)

    Wann, Daniel L.; Koch, Katrina; Knoth, Tasha; Fox, David; Aljubaily, Hesham; Lantz, Christopher D.

    2006-01-01

    The current investigation examined sport fans' impressions of an athlete described as a potential member of their team or a potential member of a rival team. In Study 1, we predicted that individuals would exhibit an ingroup favoritism effect by reporting more positive evaluations of the player's performance when he was described as a…

  12. Performance of Simplified Acute Physiology Score 3 In Predicting Hospital Mortality In Emergency Intensive Care Unit

    Directory of Open Access Journals (Sweden)

    Qing-Bian Ma

    2017-01-01

    Conclusions: The SAPS 3 score system exhibited satisfactory performance even superior to APACHE II in discrimination. In predicting hospital mortality, SAPS 3 did not exhibit good calibration and overestimated hospital mortality, which demonstrated that SAPS 3 needs improvement in the future.

  13. Could Learning Outcomes of the First Course in Accounting Predict Overall Academic Performance?

    Science.gov (United States)

    Alanzi, Khalid A.; Alfraih, Mishari M.

    2017-01-01

    Purpose: This study aims to question whether learning outcomes of the first course in accounting could predict the overall academic performance of accounting students as measured by their graduating grade point average (GPA). Design/methodology/approach The sample of the present study was drawn from accounting students who were graduated during…

  14. Correlation and Predictive Relationship between Self-Determination Instruction and Academic Performance of Students with Disabilities

    Science.gov (United States)

    Chao, Pen-Chiang; Chou, Yu-Chi

    2017-01-01

    The purpose of this study was to investigate the correlation and probable predictive relationship between self-determination skills taught by special education teachers and the academic performance of students with disabilities from junior high schools in Taiwan. The subjects included teachers from resource rooms and self-contained classrooms (n =…

  15. Improved Fuzzy Modelling to Predict the Academic Performance of Distance Education Students

    Directory of Open Access Journals (Sweden)

    Osman Yildiz

    2013-12-01

    Full Text Available It is essential to predict distance education students’ year-end academic performance early during the course of the semester and to take precautions using such prediction-based information. This will, in particular, help enhance their academic performance and, therefore, improve the overall educational quality. The present study was on the development of a mathematical model intended to predict distance education students’ year-end academic performance using the first eight-week data on the learning management system. First, two fuzzy models were constructed, namely the classical fuzzy model and the expert fuzzy model, the latter being based on expert opinion. Afterwards, a gene-fuzzy model was developed optimizing membership functions through genetic algorithm. The data on distance education were collected through Moodle, an open source learning management system. The data were on a total of 218 students who enrolled in Basic Computer Sciences in 2012. The input data consisted of the following variables: When a student logged on to the system for the last time after the content of a lesson was uploaded, how often he/she logged on to the system, how long he/she stayed online in the last login, what score he/she got in the quiz taken in Week 4, and what score he/she got in the midterm exam taken in Week 8. A comparison was made among the predictions of the three models concerning the students’ year-end academic performance.

  16. Integrated Simulation for HVAC Performance Prediction: State-of-the-Art Illustration

    NARCIS (Netherlands)

    Hensen, J.L.M.; Clarke, J.A.

    2000-01-01

    This paper aims to outline the current state-of-the-art in integrated building simulation for performance prediction of heating, ventilating and air-conditioning (HVAC) systems. The ESP-r system is used as an example where integrated simulation is a core philosophy behind the development. The

  17. Genome-Wide Polygenic Scores Predict Reading Performance throughout the School Years

    Science.gov (United States)

    Selzam, Saskia; Dale, Philip S.; Wagner, Richard K.; DeFries, John C.; Cederlöf, Martin; O'Reilly, Paul F.; Krapohl, Eva; Plomin, Robert

    2017-01-01

    It is now possible to create individual-specific genetic scores, called genome-wide polygenic scores (GPS). We used a GPS for years of education ("EduYears") to predict reading performance assessed at UK National Curriculum Key Stages 1 (age 7), 2 (age 12) and 3 (age 14) and on reading tests administered at ages 7 and 12 in a UK sample…

  18. Identification of the Predictive Power of Five Factor Personality Traits for Individual Instrument Performance Anxiety

    Science.gov (United States)

    Özdemir, Gökhan; Dalkiran, Esra

    2017-01-01

    This study, with the aim of identifying the predictive power of the five-factor personality traits of music teacher candidates on individual instrument performance anxiety, was designed according to the relational screening model. The study population was students attending the Music Education branch of Fine Arts Education Departments in…

  19. Prediction of Human Performance Using Electroencephalography under Different Indoor Room Temperatures

    Science.gov (United States)

    Zhang, Tinghe; Mao, Zijing; Xu, Xiaojing; Zhang, Lin; Pack, Daniel J.; Dong, Bing; Huang, Yufei

    2018-01-01

    Varying indoor environmental conditions is known to affect office worker’s performance; wherein past research studies have reported the effects of unfavorable indoor temperature and air quality causing sick building syndrome (SBS) among office workers. Thus, investigating factors that can predict performance in changing indoor environments have become a highly important research topic bearing significant impact in our society. While past research studies have attempted to determine predictors for performance, they do not provide satisfactory prediction ability. Therefore, in this preliminary study, we attempt to predict performance during office-work tasks triggered by different indoor room temperatures (22.2 °C and 30 °C) from human brain signals recorded using electroencephalography (EEG). Seven participants were recruited, from whom EEG, skin temperature, heart rate and thermal survey questionnaires were collected. Regression analyses were carried out to investigate the effectiveness of using EEG power spectral densities (PSD) as predictors of performance. Our results indicate EEG PSDs as predictors provide the highest R2 (> 0.70), that is 17 times higher than using other physiological signals as predictors and is more robust. Finally, the paper provides insight on the selected predictors based on brain activity patterns for low- and high-performance levels under different indoor-temperatures. PMID:29690601

  20. Predicting energy performance of a net-zero energy building: A statistical approach

    International Nuclear Information System (INIS)

    Kneifel, Joshua; Webb, David

    2016-01-01

    Highlights: • A regression model is applied to actual energy data from a net-zero energy building. • The model is validated through a rigorous statistical analysis. • Comparisons are made between model predictions and those of a physics-based model. • The model is a viable baseline for evaluating future models from the energy data. - Abstract: Performance-based building requirements have become more prevalent because it gives freedom in building design while still maintaining or exceeding the energy performance required by prescriptive-based requirements. In order to determine if building designs reach target energy efficiency improvements, it is necessary to estimate the energy performance of a building using predictive models and different weather conditions. Physics-based whole building energy simulation modeling is the most common approach. However, these physics-based models include underlying assumptions and require significant amounts of information in order to specify the input parameter values. An alternative approach to test the performance of a building is to develop a statistically derived predictive regression model using post-occupancy data that can accurately predict energy consumption and production based on a few common weather-based factors, thus requiring less information than simulation models. A regression model based on measured data should be able to predict energy performance of a building for a given day as long as the weather conditions are similar to those during the data collection time frame. This article uses data from the National Institute of Standards and Technology (NIST) Net-Zero Energy Residential Test Facility (NZERTF) to develop and validate a regression model to predict the energy performance of the NZERTF using two weather variables aggregated to the daily level, applies the model to estimate the energy performance of hypothetical NZERTFs located in different cities in the Mixed-Humid Climate Zone, and compares these

  1. Accomplishments and Compromises in Prediction Research for World Records and Best Performances in Track and Field and Swimming

    Science.gov (United States)

    Liu, Yuanlong; Paul, Stanley; Fu, Frank H.

    2012-01-01

    The conductors of this study reviewed prediction research and studied the accomplishments and compromises in predicting world records and best performances in track and field and swimming. The results of the study showed that prediction research only promises to describe the historical trends in track and field and swimming performances, to study…

  2. Intrinsic motivation and extrinsic incentives jointly predict performance: a 40-year meta-analysis.

    Science.gov (United States)

    Cerasoli, Christopher P; Nicklin, Jessica M; Ford, Michael T

    2014-07-01

    More than 4 decades of research and 9 meta-analyses have focused on the undermining effect: namely, the debate over whether the provision of extrinsic incentives erodes intrinsic motivation. This review and meta-analysis builds on such previous reviews by focusing on the interrelationship among intrinsic motivation, extrinsic incentives, and performance, with reference to 2 moderators: performance type (quality vs. quantity) and incentive contingency (directly performance-salient vs. indirectly performance-salient), which have not been systematically reviewed to date. Based on random-effects meta-analytic methods, findings from school, work, and physical domains (k = 183, N = 212,468) indicate that intrinsic motivation is a medium to strong predictor of performance (ρ = .21-45). The importance of intrinsic motivation to performance remained in place whether incentives were presented. In addition, incentive salience influenced the predictive validity of intrinsic motivation for performance: In a "crowding out" fashion, intrinsic motivation was less important to performance when incentives were directly tied to performance and was more important when incentives were indirectly tied to performance. Considered simultaneously through meta-analytic regression, intrinsic motivation predicted more unique variance in quality of performance, whereas incentives were a better predictor of quantity of performance. With respect to performance, incentives and intrinsic motivation are not necessarily antagonistic and are best considered simultaneously. Future research should consider using nonperformance criteria (e.g., well-being, job satisfaction) as well as applying the percent-of-maximum-possible (POMP) method in meta-analyses. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  3. Predictive tool of energy performance of cold storage in agrifood industries: The Portuguese case study

    International Nuclear Information System (INIS)

    Nunes, José; Neves, Diogo; Gaspar, Pedro D.; Silva, Pedro D.; Andrade, Luís P.

    2014-01-01

    Highlights: • A predictive tool for assessment of the energy performance in agrifood industries that use cold storage is developed. • The correlations used by the predictive tool result from the greatest number of data sets collected to date in Portugal. • Strong relationships between raw material, energy consumption and volume of cold stores were established. • Case studies were analyzed that demonstrate the applicability of the tool. • The tool results are useful in the decision-making process of practice measures for the improvement of energy efficiency. - Abstract: Food processing and conservation represent decisive factors for the sustainability of the planet given the significant growth of the world population in the last decades. Therefore, the cooling process during the manufacture and/or storage of food products has been subject of study and improvement in order to ensure the food supply with good quality and safety. A predictive tool for assessment of the energy performance in agrifood industries that use cold storage is developed in order to contribute to the improvement of the energy efficiency of this industry. The predictive tool is based on a set of characteristic correlated parameters: amount of raw material annually processed, annual energy consumption and volume of cold rooms. Case studies of application of the predictive tool consider industries in the meat sector, specifically slaughterhouses. The results obtained help on the decision-making of practice measures for improvement of the energy efficiency in this industry

  4. Improved Helicopter Rotor Performance Prediction through Loose and Tight CFD/CSD Coupling

    Science.gov (United States)

    Ickes, Jacob C.

    Helicopters and other Vertical Take-Off or Landing (VTOL) vehicles exhibit an interesting combination of structural dynamic and aerodynamic phenomena which together drive the rotor performance. The combination of factors involved make simulating the rotor a challenging and multidisciplinary effort, and one which is still an active area of interest in the industry because of the money and time it could save during design. Modern tools allow the prediction of rotorcraft physics from first principles. Analysis of the rotor system with this level of accuracy provides the understanding necessary to improve its performance. There has historically been a divide between the comprehensive codes which perform aeroelastic rotor simulations using simplified aerodynamic models, and the very computationally intensive Navier-Stokes Computational Fluid Dynamics (CFD) solvers. As computer resources become more available, efforts have been made to replace the simplified aerodynamics of the comprehensive codes with the more accurate results from a CFD code. The objective of this work is to perform aeroelastic rotorcraft analysis using first-principles simulations for both fluids and structural predictions using tools available at the University of Toledo. Two separate codes are coupled together in both loose coupling (data exchange on a periodic interval) and tight coupling (data exchange each time step) schemes. To allow the coupling to be carried out in a reliable and efficient way, a Fluid-Structure Interaction code was developed which automatically performs primary functions of loose and tight coupling procedures. Flow phenomena such as transonics, dynamic stall, locally reversed flow on a blade, and Blade-Vortex Interaction (BVI) were simulated in this work. Results of the analysis show aerodynamic load improvement due to the inclusion of the CFD-based airloads in the structural dynamics analysis of the Computational Structural Dynamics (CSD) code. Improvements came in the form

  5. Online physician ratings fail to predict actual performance on measures of quality, value, and peer review.

    Science.gov (United States)

    Daskivich, Timothy J; Houman, Justin; Fuller, Garth; Black, Jeanne T; Kim, Hyung L; Spiegel, Brennan

    2018-04-01

    Patients use online consumer ratings to identify high-performing physicians, but it is unclear if ratings are valid measures of clinical performance. We sought to determine whether online ratings of specialist physicians from 5 platforms predict quality of care, value of care, and peer-assessed physician performance. We conducted an observational study of 78 physicians representing 8 medical and surgical specialties. We assessed the association of consumer ratings with specialty-specific performance scores (metrics including adherence to Choosing Wisely measures, 30-day readmissions, length of stay, and adjusted cost of care), primary care physician peer-review scores, and administrator peer-review scores. Across ratings platforms, multivariable models showed no significant association between mean consumer ratings and specialty-specific performance scores (β-coefficient range, -0.04, 0.04), primary care physician scores (β-coefficient range, -0.01, 0.3), and administrator scores (β-coefficient range, -0.2, 0.1). There was no association between ratings and score subdomains addressing quality or value-based care. Among physicians in the lowest quartile of specialty-specific performance scores, only 5%-32% had consumer ratings in the lowest quartile across platforms. Ratings were consistent across platforms; a physician's score on one platform significantly predicted his/her score on another in 5 of 10 comparisons. Online ratings of specialist physicians do not predict objective measures of quality of care or peer assessment of clinical performance. Scores are consistent across platforms, suggesting that they jointly measure a latent construct that is unrelated to performance. Online consumer ratings should not be used in isolation to select physicians, given their poor association with clinical performance.

  6. Assessing fitness-for-duty and predicting performance with cognitive neurophysiological measures

    Science.gov (United States)

    Smith, Michael E.; Gevins, Alan

    2005-05-01

    Progress is described in developing a novel test of neurocognitive status for fitness-for-duty testing. The Sustained Attention & Memory (SAM) test combines neurophysiologic (EEG) measures of brain activation with performance measures during a psychometric test of sustained attention and working memory, and then gauges changes in neurocognitive status relative to an individual"s normative baseline. In studies of the effects of common psychoactive substances that can affect job performance, including sedating antihistamines, caffeine, alcohol, marijuana, and prescription medications, test sensitivity was greater for the combined neurophysiological and performance measures than for task performance measures by themselves. The neurocognitive effects of overnight sleep deprivation were quite evident, and such effects predicted subsequent performance impairment on a flight simulator task. Sensitivity to diurnal circadian variations was also demonstrated. With further refinement and independent validation, the SAM Test may prove useful for assessing readiness-to-perform in high-asset personnel working in demanding, high risk situations.

  7. Predicting memory performance in normal ageing using different measures of hippocampal size

    International Nuclear Information System (INIS)

    Lye, T.C.; Creasey, H.; Kril, J.J.; Grayson, D.A.; Piguet, O.; Bennett, H.P.; Ridley, L.J.; Broe, G.A.

    2006-01-01

    A number of different methods have been employed to correct hippocampal volumes for individual variation in head size. Researchers have previously used qualitative visual inspection to gauge hippocampal atrophy. The purpose of this study was to determine the best measure(s) of hippocampal size for predicting memory functioning in 102 community-dwelling individuals over 80 years of age. Hippocampal size was estimated using magnetic resonance imaging (MRI) volumetry and qualitative visual assessment. Right and left hippocampal volumes were adjusted by three different estimates of head size: total intracranial volume (TICV), whole-brain volume including ventricles (WB+V) and a more refined measure of whole-brain volume with ventricles extracted (WB). We compared the relative efficacy of these three volumetric adjustment methods and visual ratings of hippocampal size in predicting memory performance using linear regression. All four measures of hippocampal size were significant predictors of memory performance. TICV-adjusted volumes performed most poorly in accounting for variance in memory scores. Hippocampal volumes adjusted by either measure of whole-brain volume performed equally well, although qualitative visual ratings of the hippocampus were at least as effective as the volumetric measures in predicting memory performance in community-dwelling individuals in the ninth or tenth decade of life. (orig.)

  8. Improving behavioral performance under full attention by adjusting response criteria to changes in stimulus predictability.

    Science.gov (United States)

    Katzner, Steffen; Treue, Stefan; Busse, Laura

    2012-09-04

    One of the key features of active perception is the ability to predict critical sensory events. Humans and animals can implicitly learn statistical regularities in the timing of events and use them to improve behavioral performance. Here, we used a signal detection approach to investigate whether such improvements in performance result from changes of perceptual sensitivity or rather from adjustments of a response criterion. In a regular sequence of briefly presented stimuli, human observers performed a noise-limited motion detection task by monitoring the stimulus stream for the appearance of a designated target direction. We manipulated target predictability through the hazard rate, which specifies the likelihood that a target is about to occur, given it has not occurred so far. Analyses of response accuracy revealed that improvements in performance could be accounted for by adjustments of the response criterion; a growing hazard rate was paralleled by an increasing tendency to report the presence of a target. In contrast, the hazard rate did not affect perceptual sensitivity. Consistent with previous research, we also found that reaction time decreases as the hazard rate grows. A simple rise-to-threshold model could well describe this decrease and attribute predictability effects to threshold adjustments rather than changes in information supply. We conclude that, even under conditions of full attention and constant perceptual sensitivity, behavioral performance can be optimized by dynamically adjusting the response criterion to meet ongoing changes in the likelihood of a target.

  9. Predictive performance of DSGE model for small open economy – the case study of Czech Republic

    Directory of Open Access Journals (Sweden)

    Tomáš Jeřábek

    2013-01-01

    Full Text Available Multivariate time series forecasting is applied in a wide range of economic activities related to regional competitiveness and is the basis of almost all macroeconomic analysis. From the point of view of political practice is appropriate to seek a model that reached a quality prediction performance for all the variables. As monitored variables were used GDP growth, inflation and interest rates. The paper focuses on performance prediction evaluation of the small open economy New Keynesian DSGE model for the Czech republic, where Bayesian method are used for their parameters estimation, against different types of Bayesian and naive random walk model. The performance of models is identified using historical dates including domestic economy and foreign economy, which is represented by countries of the Eurozone. The results indicate that the DSGE model generates estimates that are competitive with other models used in this paper.

  10. Observer performance in detecting multiple radiographic signals: prediction and analysis using a generalized ROC approach

    International Nuclear Information System (INIS)

    Metz, C.E.; Starr, S.J.; Lusted, L.B.

    1975-01-01

    The theories of decision processes and signal detection provide a framework for the evaluation of observer performance. Some radiologic procedures involve a search for multiple similar lesions, as in gallstone or pneumoconiosis examinations. A model is presented which attempts to predict, from the conventional receiver operating characteristic (ROC) curve describing the detectability of a single visual signal in a radiograph, observer performance in an experiment requiring detection of more than one such signal. An experiment is described which tests the validity of this model for the case of detecting the presence of zero, one, or two low-contrast radiographic images of a two-mm.-diameter lucite bead embedded in radiographic mottle. Results from six observers, including three radiologists, confirm the validity of the model and suggest that human observer performance for relatively complex detection tasks can be predicted from the results of simpler experiments

  11. Prediction of the thermohydraulic performance of porous-media reservoirs for compressed-air energy storage

    Energy Technology Data Exchange (ETDEWEB)

    Wiles, L.E.; McCann, R.A.

    1981-09-01

    The numerical modeling capability that has been developed at the Pacific Northwest Laboratory (PNL) for the prediction of the thermohydraulic performance of porous media reservoirs for compressed air energy storage (CAES) is described. The capability of the numerical models was demonstrated by application to a variety of parametric analyses and the support analyses for the CAES porous media field demonstration program. The demonstration site analyses include calculations for the displacement of aquifer water to develop the air storage zone, the potential for water coning, thermal development in the reservoir, and the dehydration of the near-wellbore region. Unique features of the demonstration site reservoir that affect the thermohydraulic performance are identified and contrasted against the predicted performance for conditions that would be considered more typical of a commercial CAES site.

  12. Prediction of Hydraulic Performance of a Scaled-Down Model of SMART Reactor Coolant Pump

    Energy Technology Data Exchange (ETDEWEB)

    Kwon, Sun Guk; Park, Jin Seok; Yu, Je Yong; Lee, Won Jae [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2010-08-15

    An analysis was conducted to predict the hydraulic performance of a reactor coolant pump (RCP) of SMART at the off-design as well as design points. In order to reduce the analysis time efficiently, a single passage containing an impeller and a diffuser was considered as the computational domain. A stage scheme was used to perform a circumferential averaging of the flux on the impeller-diffuser interface. The pressure difference between the inlet and outlet of the pump was determined and was used to compute the head, efficiency, and break horse power (BHP) of a scaled-down model under conditions of steady-state incompressible flow. The predicted curves of the hydraulic performance of an RCP were similar to the typical characteristic curves of a conventional mixed-flow pump. The complex internal fluid flow of a pump, including the internal recirculation loss due to reverse flow, was observed at a low flow rate.

  13. 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.

  14. Evaluation of performance of seasonal precipitation prediction at regional scale over India

    Science.gov (United States)

    Mohanty, U. C.; Nageswararao, M. M.; Sinha, P.; Nair, A.; Singh, A.; Rai, R. K.; Kar, S. C.; Ramesh, K. J.; Singh, K. K.; Ghosh, K.; Rathore, L. S.; Sharma, R.; Kumar, A.; Dhekale, B. S.; Maurya, R. K. S.; Sahoo, R. K.; Dash, G. P.

    2018-03-01

    The seasonal scale precipitation amount is an important ingredient in planning most of the agricultural practices (such as a type of crops, and showing and harvesting schedules). India being an agroeconomic country, the seasonal scale prediction of precipitation is directly linked to the socioeconomic growth of the nation. At present, seasonal precipitation prediction at regional scale is a challenging task for the scientific community. In the present study, an attempt is made to develop multi-model dynamical-statistical approach for seasonal precipitation prediction at the regional scale (meteorological subdivisions) over India for four prominent seasons which are winter (from December to February; DJF), pre-monsoon (from March to May; MAM), summer monsoon (from June to September; JJAS), and post-monsoon (from October to December; OND). The present prediction approach is referred as extended range forecast system (ERFS). For this purpose, precipitation predictions from ten general circulation models (GCMs) are used along with the India Meteorological Department (IMD) rainfall analysis data from 1982 to 2008 for evaluation of the performance of the GCMs, bias correction of the model results, and development of the ERFS. An extensive evaluation of the performance of the ERFS is carried out with dependent data (1982-2008) as well as independent predictions for the period 2009-2014. In general, the skill of the ERFS is reasonably better and consistent for all the seasons and different regions over India as compared to the GCMs and their simple mean. The GCM products failed to explain the extreme precipitation years, whereas the bias-corrected GCM mean and the ERFS improved the prediction and well represented the extremes in the hindcast period. The peak intensity, as well as regions of maximum precipitation, is better represented by the ERFS than the individual GCMs. The study highlights the improvement of forecast skill of the ERFS over 34 meteorological subdivisions

  15. Performance behavior of prediction filters for respiratory motion compensation in radiotherapy

    Directory of Open Access Journals (Sweden)

    Jöhl Alexander

    2017-09-01

    Full Text Available Introduction: In radiotherapy, tumors may move due to the patient’s respiration, which decreases treatment accuracy. Some motion mitigation methods require measuring the tumor position during treatment. Current available sensors often suffer from time delays, which degrade the motion mitigation performance. However, the tumor motion is often periodic and continuous, which allows predicting the motion ahead. Method and Materials: A couch tracking system was simulated in MATLAB and five prediction filters selected from literature were implemented and tested on 51 respiration signals (median length: 103 s. The five filters were the linear filter (LF, the local regression (LOESS, the neural network (NN, the support vector regression (SVR, and the wavelet least mean squares (wLMS. The time delay to compensate was 320 ms. The normalized root mean square error (nRMSE was calculated for all prediction filters and respiration signals. The correlation coefficients between the nRMSE of the prediction filters were computed. Results: The prediction filters were grouped into a low and a high nRMSE group. The low nRMSE group consisted of the LF, the NN, and the wLMS with a median nRMSE of 0.14, 0.15, and 0.14, respectively. The high nRMSE group consisted of the LOESS and the SVR with both a median nRMSE of 0.34. The correlations between the low nRMSE filters were above 0.87 and between the high nRMSE filters it was 0.64. Conclusion: The low nRMSE prediction filters not only have similar median nRMSEs but also similar nRMSEs for the same respiration signals as the high correlation shows. Therefore, good prediction filters perform similarly for identical respiration patterns, which might indicate a minimally achievable nRMSE for a given respiration pattern.

  16. The honeymoon effect in job performance - Temporal increases in the predictive power of achievement motivation

    Science.gov (United States)

    Helmreich, Robert L.; Sawin, Linda L.; Carsrud, Alan L.

    1986-01-01

    Correlations between a job performance criterion and personality measures reflecting achievement motivation and an interpersonal orientation were examined at three points in time after completion of job training for a sample of airline reservations agents. Although correlations between the personality predictors and performance were small and nonsignificant for the 3-month period after beginning the job, by the end of six and eight months a number of significant relationships had emerged. Implications for the utility of personality measures in selection and performance prediction are discussed.

  17. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

    KAUST Repository

    Liu, Guozheng

    2016-07-06

    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

  18. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat.

    Directory of Open Access Journals (Sweden)

    Guozheng Liu

    Full Text Available Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1 examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2 explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3 investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L. and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs, but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

  19. Analytical prediction of thermal performance of hypervapotron and its application to ITER

    International Nuclear Information System (INIS)

    Baxi, C.B.; Falter, H.

    1992-09-01

    A hypervapotron (HV) is a water cooled device made of high thermal conductivity material such as copper. A surface heat flux of up to 30 MW/m 2 has been achieved in copper hypervapotrans cooled by water at a velocity of 10 m/s and at a pressure of six bar. Hypervapotrons have been used in the past as beam dumps at the Joint European Torus (JET). It is planned to use them for diverter cooling during Mark II upgrade of the JET. Although a large amount of experimental data has been collected on these devices, an analytical performance prediction has not been done before due to the complexity of the heat transfer mechanisms. A method to analytically predict the thermal performance of the hypervapotron is described. The method uses a combination of a number of thermal hydraulic correlations and a finite element analysis. The analytical prediction shows an excellent agreement with experimental results over a wide range of velocities, pressures, subcooling, and geometries. The method was used to predict the performance of hypervapotron made of beryllium. Merits for the use of hypervapotrons for International Thermonuclear Experimental Reactor (ITER) and Tokamak Physics Experiment (TPX) are discussed

  20. On line performance monitoring for predictive maintenance [Paper No.: VIA - 2

    International Nuclear Information System (INIS)

    Gupta, R.K.; Chandra, Rajesh

    1981-01-01

    There will always be progressive deterioration in the performance of dynamic equipment due to normal inevitable wear, malfunctions, failures and other reasons. In most cases it is possible to monitor some parameters of a system which would get progressively affected with the deterioration in the health of the system. By on-line monitoring of such predetermined parameters, compared with preset base data generated for a healthy system earlier, would prove very helpful in avoiding breakdowns and in proper planning of preventive and predictive maintenance. With increasing use of on-line computerised controls the generation of design base data and also the in-built self checking feature of monitoring the equipment health can be achieved by incorporating suitable software. This type of system will be helpful in: (a) predicting the life of component, (b) prewarning the operator about impending malfunctions, (c) establishing a maintenance schedule and spare inventory, and (d) analysing the failures. This type of centralised predictive maintenance is increasingly becoming important where: (a) the number of equipments are large, (b) the operation of equipment is critical from safety criteria, and (c) the minimum safety margin in the performance of the component is to be maintained. Keeping this in mind, the Fuel Handling System of Narora Atomic Power Project and the future power plants having computerised controls will have facility for on-line performance monitoring for predictive maintenance. The paper also describes methodology of the technique in detail, with a few representative cases. (author)

  1. Modelling and Predicting Backstroke Start Performance Using Non-Linear and Linear Models.

    Science.gov (United States)

    de Jesus, Karla; Ayala, Helon V H; de Jesus, Kelly; Coelho, Leandro Dos S; Medeiros, Alexandre I A; Abraldes, José A; Vaz, Mário A P; Fernandes, Ricardo J; Vilas-Boas, João Paulo

    2018-03-01

    Our aim was to compare non-linear and linear mathematical model responses for backstroke start performance prediction. Ten swimmers randomly completed eight 15 m backstroke starts with feet over the wedge, four with hands on the highest horizontal and four on the vertical handgrip. Swimmers were videotaped using a dual media camera set-up, with the starts being performed over an instrumented block with four force plates. Artificial neural networks were applied to predict 5 m start time using kinematic and kinetic variables and to determine the accuracy of the mean absolute percentage error. Artificial neural networks predicted start time more robustly than the linear model with respect to changing training to the validation dataset for the vertical handgrip (3.95 ± 1.67 vs. 5.92 ± 3.27%). Artificial neural networks obtained a smaller mean absolute percentage error than the linear model in the horizontal (0.43 ± 0.19 vs. 0.98 ± 0.19%) and vertical handgrip (0.45 ± 0.19 vs. 1.38 ± 0.30%) using all input data. The best artificial neural network validation revealed a smaller mean absolute error than the linear model for the horizontal (0.007 vs. 0.04 s) and vertical handgrip (0.01 vs. 0.03 s). Artificial neural networks should be used for backstroke 5 m start time prediction due to the quite small differences among the elite level performances.

  2. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

    KAUST Repository

    Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

    2016-01-01

    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

  3. Computer simulation for prediction of performance and thermodynamic parameters of high energy materials

    International Nuclear Information System (INIS)

    Muthurajan, H.; Sivabalan, R.; Talawar, M.B.; Asthana, S.N.

    2004-01-01

    A new code viz., Linear Output Thermodynamic User-friendly Software for Energetic Systems (LOTUSES) developed during this work predicts the theoretical performance parameters such as density, detonation factor, velocity of detonation, detonation pressure and thermodynamic properties such as heat of detonation, heat of explosion, volume of explosion gaseous products. The same code also assists in the prediction of possible explosive decomposition products after explosion and power index. The developed code has been validated by calculating the parameters of standard explosives such as TNT, PETN, RDX, and HMX. Theoretically predicated parameters are accurate to the order of ±5% deviation. To the best of our knowledge, no such code is reported in literature which can predict a wide range of characteristics of known/unknown explosives with minimum input parameters. The code can be used to obtain thermochemical and performance parameters of high energy materials (HEMs) with reasonable accuracy. The code has been developed in Visual Basic having enhanced windows environment, and thereby advantages over the conventional codes, written in Fortran. The theoretically predicted HEMs performance can be directly printed as well as stored in text (.txt) or HTML (.htm) or Microsoft Word (.doc) or Adobe Acrobat (.pdf) format in the hard disk. The output can also be copied into the Random Access Memory as clipboard text which can be imported/pasted in other software as in the case of other codes

  4. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

    Science.gov (United States)

    Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

    2016-01-01

    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population. PMID:27383841

  5. Thermodynamic simulation model for predicting the performance of spark ignition engines using biogas as fuel

    International Nuclear Information System (INIS)

    Nunes de Faria, Mário M.; Vargas Machuca Bueno, Juan P.; Ayad, Sami M.M. Elmassalami; Belchior, Carlos R. Pereira

    2017-01-01

    Highlights: • A 0-D model for performance prediction of SI ICE fueled with biogas is proposed. • Relative difference between simulated and experimental values was under 5%. • Can be adapted for different biogas compositions and operating ranges. • Could be a valuable tool for predicting trends and guiding experimentation. • Is suitable for use with biogas supplies in developing regions. - Abstract: Biogas found its way from developing countries and is now an alternative to fossil fuels in internal combustion engines and with the advantage of lower greenhouse gas emissions. However, its use in gas engines requires engine modifications or adaptations that may be costly. This paper reports the results of experimental performance and emissions tests of an engine-generator unit fueled with biogas produced in a sewage plant in Brazil, operating under different loads, and with suitable engine modifications. These emissions and performance results were in agreement with the literature and it was confirmed that the penalties to engine performance were more significant than emission reduction in the operating range tested. Furthermore, a zero dimensional simulation model was employed to predict performance characteristics. Moreover, a differential thermodynamic equation system was solved, obtaining the pressure inside the cylinder as a function of the crank angle for different engine conditions. Mean effective pressure and indicated power were also obtained. The results of simulation and experimental tests of the engine in similar conditions were compared and the model validated. Although several simplifying assumptions were adopted and empirical correlations were used for Wiebe function, the model was adequate in predicting engine performance as the relative difference between simulated and experimental values was lower than 5%. The model can be adapted for use with different raw or enriched biogas compositions and could prove to be a valuable tool to guide

  6. Theory of mind and switching predict prospective memory performance in adolescents.

    Science.gov (United States)

    Altgassen, Mareike; Vetter, Nora C; Phillips, Louise H; Akgün, Canan; Kliegel, Matthias

    2014-11-01

    Research indicates ongoing development of prospective memory as well as theory of mind and executive functions across late childhood and adolescence. However, so far the interplay of these processes has not been investigated. Therefore, the purpose of the current study was to investigate whether theory of mind and executive control processes (specifically updating, switching, and inhibition) predict prospective memory development across adolescence. In total, 42 adolescents and 41 young adults participated in this study. Young adults outperformed adolescents on tasks of prospective memory, theory of mind, and executive functions. Switching and theory of mind predicted prospective memory performance in adolescents. Copyright © 2014 Elsevier Inc. All rights reserved.

  7. Performance prediction of a permanent magnet servomotor using finite element analysis

    International Nuclear Information System (INIS)

    O'Dwyer, J.; Brady, G.; Byrne, J.V.

    1998-01-01

    Finite element analysis package ''MAGSOLVE'' is employed to predict the performance of a brushless permanent magnet servomotor. Equations are developed for a scaling method to predict motor rated stall torque. The torque v. current characteristic is determined using the Maxwell stress method and compared to experimental results. Less than 2% difference is observed over the current range. The solution is substantially independent of the location of the stress contour in the airgap. Valuable insight is also obtained regarding demagnetisation and torque ripple attributes of the motor. (orig.)

  8. Development of Simple Drying Model for Performance Prediction of Solar Dryer: Theoretical Analysis

    DEFF Research Database (Denmark)

    Singh, Shobhana; Kumar, Subodh

    2012-01-01

    An analytical moisture diffusion model which considers the influence of external resistance to mass transfer is developed to predict thermal performance of dryer system. The moisture diffusion coefficient, Deff that is necessary to evaluate the prediction model has been determined in terms...... of experimental drying parameters. A laboratory model of mixed-mode solar dryer system is tested with cylindrical potato samples of thickness 5 and 18 mm under simulated indoor conditions. The potato samples were dried at a constant absorbed thermal energy of 750 W/m2 and air mass flow rate of 0.011 kg...

  9. Predictive analytics tools to adjust and monitor performance metrics for the ATLAS Production System

    CERN Document Server

    Barreiro Megino, Fernando Harald; The ATLAS collaboration

    2017-01-01

    Having information such as an estimation of the processing time or possibility of system outage (abnormal behaviour) helps to assist to monitor system performance and to predict its next state. The current cyber-infrastructure presents computing conditions in which contention for resources among high-priority data analysis happens routinely, that might lead to significant workload and data handling interruptions. The lack of the possibility to monitor and to predict the behaviour of the analysis process (its duration) and system’s state itself caused to focus on design of the built-in situational awareness analytic tools.

  10. Retrospective lifetime dietary patterns predict cognitive performance in community-dwelling older Australians.

    Science.gov (United States)

    Hosking, Diane E; Nettelbeck, Ted; Wilson, Carlene; Danthiir, Vanessa

    2014-07-28

    Dietary intake is a modifiable exposure that may have an impact on cognitive outcomes in older age. The long-term aetiology of cognitive decline and dementia, however, suggests that the relevance of dietary intake extends across the lifetime. In the present study, we tested whether retrospective dietary patterns from the life periods of childhood, early adulthood, adulthood and middle age predicted cognitive performance in a cognitively healthy sample of 352 older Australian adults >65 years. Participants completed the Lifetime Diet Questionnaire and a battery of cognitive tests designed to comprehensively assess multiple cognitive domains. In separate regression models, lifetime dietary patterns were the predictors of cognitive factor scores representing ten constructs derived by confirmatory factor analysis of the cognitive test battery. All regression models were progressively adjusted for the potential confounders of current diet, age, sex, years of education, English as native language, smoking history, income level, apoE ɛ4 status, physical activity, other past dietary patterns and health-related variables. In the adjusted models, lifetime dietary patterns predicted cognitive performance in this sample of older adults. In models additionally adjusted for intake from the other life periods and mechanistic health-related variables, dietary patterns from the childhood period alone reached significance. Higher consumption of the 'coffee and high-sugar, high-fat extras' pattern predicted poorer performance on simple/choice reaction time, working memory, retrieval fluency, short-term memory and reasoning. The 'vegetable and non-processed' pattern negatively predicted simple/choice reaction time, and the 'traditional Australian' pattern positively predicted perceptual speed and retrieval fluency. Identifying early-life dietary antecedents of older-age cognitive performance contributes to formulating strategies for delaying or preventing cognitive decline.

  11. Predicting performance at medical school: can we identify at-risk students?

    Directory of Open Access Journals (Sweden)

    Shaban S

    2011-05-01

    Full Text Available Sami Shaban, Michelle McLeanDepartment of Medical Education, Faculty of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab EmiratesBackground: The purpose of this study was to examine the predictive potential of multiple indicators (eg, preadmission scores, unit, module and clerkship grades, course and examination scores on academic performance at medical school, with a view to identifying students at risk.Methods: An analysis was undertaken of medical student grades in a 6-year medical school program at the Faculty of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates, over the past 14 years.Results: While high school scores were significantly (P < 0.001 correlated with the final integrated examination, predictability was only 6.8%. Scores for the United Arab Emirates university placement assessment (Common Educational Proficiency Assessment were only slightly more promising as predictors with 14.9% predictability for the final integrated examination. Each unit or module in the first four years was highly correlated with the next unit or module, with 25%–60% predictability. Course examination scores (end of years 2, 4, and 6 were significantly correlated (P < 0.001 with the average scores in that 2-year period (59.3%, 64.8%, and 55.8% predictability, respectively. Final integrated examination scores were significantly correlated (P < 0.001 with National Board of Medical Examiners scores (35% predictability. Multivariate linear regression identified key grades with the greatest predictability of the final integrated examination score at three stages in the program.Conclusion: This study has demonstrated that it may be possible to identify “at-risk” students relatively early in their studies through continuous data archiving and regular analysis. The data analysis techniques used in this study are not unique to this institution.Keywords: at-risk students, grade

  12. Performance prediction and flow field calculation for airfoil fan with impeller inlet clearance

    International Nuclear Information System (INIS)

    Kang, Shin Hyoung; Cao, Renjing; Zhang, Yangjun

    2000-01-01

    The performance prediction of an airfoil fan using a commercial code, STAR/CD, is verified by comparing the calculated results with measured performance data and velocity fields of an airfoil fan. The effects of inlet tip clearance on performance are investigated. The calculations overestimate the pressure rise performance by about 10-25 percent. However, the performance reduction due to tip clearance is well predicted by numerical simulations. Main source of performance decrease is not only the slip factor but also impeller efficiency. The reduction in performance is 12-16 percent for 1 percent gap of the diameter. The calculated reductions in impeller efficiency and slip factor are also linearly proportional to the gap size. The span-wise distributions of phase averaged velocity and pressure at the impeller exit are strongly influenced by the radial gap size. The radial component of velocity and the flow angle increase over the passage as the gap increases. The slip factor decreases and the loss increases with the gap size. The high velocity of leakage jet affects the impeller inlet and passage flows. With a larger clearance, the main stream moves to the impeller hub side and high loss region extends from the shroud to the hub

  13. Do physiological measures predict selected CrossFit(®) benchmark performance?

    Science.gov (United States)

    Butcher, Scotty J; Neyedly, Tyler J; Horvey, Karla J; Benko, Chad R

    2015-01-01

    CrossFit(®) is a new but extremely popular method of exercise training and competition that involves constantly varied functional movements performed at high intensity. Despite the popularity of this training method, the physiological determinants of CrossFit performance have not yet been reported. The purpose of this study was to determine whether physiological and/or muscle strength measures could predict performance on three common CrossFit "Workouts of the Day" (WODs). Fourteen CrossFit Open or Regional athletes completed, on separate days, the WODs "Grace" (30 clean and jerks for time), "Fran" (three rounds of thrusters and pull-ups for 21, 15, and nine repetitions), and "Cindy" (20 minutes of rounds of five pull-ups, ten push-ups, and 15 bodyweight squats), as well as the "CrossFit Total" (1 repetition max [1RM] back squat, overhead press, and deadlift), maximal oxygen consumption (VO2max), and Wingate anaerobic power/capacity testing. Performance of Grace and Fran was related to whole-body strength (CrossFit Total) (r=-0.88 and -0.65, respectively) and anaerobic threshold (r=-0.61 and -0.53, respectively); however, whole-body strength was the only variable to survive the prediction regression for both of these WODs (R (2)=0.77 and 0.42, respectively). There were no significant associations or predictors for Cindy. CrossFit benchmark WOD performance cannot be predicted by VO2max, Wingate power/capacity, or either respiratory compensation or anaerobic thresholds. Of the data measured, only whole-body strength can partially explain performance on Grace and Fran, although anaerobic threshold also exhibited association with performance. Along with their typical training, CrossFit athletes should likely ensure an adequate level of strength and aerobic endurance to optimize performance on at least some benchmark WODs.

  14. Does resident ranking during recruitment accurately predict subsequent performance as a surgical resident?

    Science.gov (United States)

    Fryer, Jonathan P; Corcoran, Noreen; George, Brian; Wang, Ed; Darosa, Debra

    2012-01-01

    While the primary goal of ranking applicants for surgical residency training positions is to identify the candidates who will subsequently perform best as surgical residents, the effectiveness of the ranking process has not been adequately studied. We evaluated our general surgery resident recruitment process between 2001 and 2011 inclusive, to determine if our recruitment ranking parameters effectively predicted subsequent resident performance. We identified 3 candidate ranking parameters (United States Medical Licensing Examination [USMLE] Step 1 score, unadjusted ranking score [URS], and final adjusted ranking [FAR]), and 4 resident performance parameters (American Board of Surgery In-Training Examination [ABSITE] score, PGY1 resident evaluation grade [REG], overall REG, and independent faculty rating ranking [IFRR]), and assessed whether the former were predictive of the latter. Analyses utilized Spearman correlation coefficient. We found that the URS, which is based on objective and criterion based parameters, was a better predictor of subsequent performance than the FAR, which is a modification of the URS based on subsequent determinations of the resident selection committee. USMLE score was a reliable predictor of ABSITE scores only. However, when we compared our worst residence performances with the performances of the other residents in this evaluation, the data did not produce convincing evidence that poor resident performances could be reliably predicted by any of the recruitment ranking parameters. Finally, stratifying candidates based on their rank range did not effectively define a ranking cut-off beyond which resident performance would drop off. Based on these findings, we recommend surgery programs may be better served by utilizing a more structured resident ranking process and that subsequent adjustments to the rank list generated by this process should be undertaken with caution. Copyright © 2012 Association of Program Directors in Surgery

  15. Prediction of Cognitive Performance and Subjective Sleepiness Using a Model of Arousal Dynamics.

    Science.gov (United States)

    Postnova, Svetlana; Lockley, Steven W; Robinson, Peter A

    2018-04-01

    A model of arousal dynamics is applied to predict objective performance and subjective sleepiness measures, including lapses and reaction time on a visual Performance Vigilance Test (vPVT), performance on a mathematical addition task (ADD), and the Karolinska Sleepiness Scale (KSS). The arousal dynamics model is comprised of a physiologically based flip-flop switch between the wake- and sleep-active neuronal populations and a dynamic circadian oscillator, thus allowing prediction of sleep propensity. Published group-level experimental constant routine (CR) and forced desynchrony (FD) data are used to calibrate the model to predict performance and sleepiness. Only the studies using dim light (performance measures during CR and FD protocols, with sleep-wake cycles ranging from 20 to 42.85 h and a 2:1 wake-to-sleep ratio. New metrics relating model outputs to performance and sleepiness data are developed and tested against group average outcomes from 7 (vPVT lapses), 5 (ADD), and 8 (KSS) experimental protocols, showing good quantitative and qualitative agreement with the data (root mean squared error of 0.38, 0.19, and 0.35, respectively). The weights of the homeostatic and circadian effects are found to be different between the measures, with KSS having stronger homeostatic influence compared with the objective measures of performance. Using FD data in addition to CR data allows us to challenge the model in conditions of both acute sleep deprivation and structured circadian misalignment, ensuring that the role of the circadian and homeostatic drives in performance is properly captured.

  16. Performance prediction for silicon photonics integrated circuits with layout-dependent correlated manufacturing variability.

    Science.gov (United States)

    Lu, Zeqin; Jhoja, Jaspreet; Klein, Jackson; Wang, Xu; Liu, Amy; Flueckiger, Jonas; Pond, James; Chrostowski, Lukas

    2017-05-01

    This work develops an enhanced Monte Carlo (MC) simulation methodology to predict the impacts of layout-dependent correlated manufacturing variations on the performance of photonics integrated circuits (PICs). First, to enable such performance prediction, we demonstrate a simple method with sub-nanometer accuracy to characterize photonics manufacturing variations, where the width and height for a fabricated waveguide can be extracted from the spectral response of a racetrack resonator. By measuring the spectral responses for a large number of identical resonators spread over a wafer, statistical results for the variations of waveguide width and height can be obtained. Second, we develop models for the layout-dependent enhanced MC simulation. Our models use netlist extraction to transfer physical layouts into circuit simulators. Spatially correlated physical variations across the PICs are simulated on a discrete grid and are mapped to each circuit component, so that the performance for each component can be updated according to its obtained variations, and therefore, circuit simulations take the correlated variations between components into account. The simulation flow and theoretical models for our layout-dependent enhanced MC simulation are detailed in this paper. As examples, several ring-resonator filter circuits are studied using the developed enhanced MC simulation, and statistical results from the simulations can predict both common-mode and differential-mode variations of the circuit performance.

  17. Single-leg squats can predict leg alignment in dancers performing ballet movements in "turnout".

    Science.gov (United States)

    Hopper, Luke S; Sato, Nahoko; Weidemann, Andries L

    2016-01-01

    The physical assessments used in dance injury surveillance programs are often adapted from the sports and exercise domain. Bespoke physical assessments may be required for dance, particularly when ballet movements involve "turning out" or external rotation of the legs beyond that typically used in sports. This study evaluated the ability of the traditional single-leg squat to predict the leg alignment of dancers performing ballet movements with turnout. Three-dimensional kinematic data of dancers performing the single-leg squat and five ballet movements were recorded and analyzed. Reduction of the three-dimensional data into a one-dimensional variable incorporating the ankle, knee, and hip joint center positions provided the strongest predictive model between the single-leg squat and the ballet movements. The single-leg squat can predict leg alignment in dancers performing ballet movements, even in "turned out" postures. Clinicians should pay careful attention to observational positioning and rating criteria when assessing dancers performing the single-leg squat.

  18. Predicting story goodness performance from cognitive measures following traumatic brain injury.

    Science.gov (United States)

    Lê, Karen; Coelho, Carl; Mozeiko, Jennifer; Krueger, Frank; Grafman, Jordan

    2012-05-01

    This study examined the prediction of performance on measures of the Story Goodness Index (SGI; Lê, Coelho, Mozeiko, & Grafman, 2011) from executive function (EF) and memory measures following traumatic brain injury (TBI). It was hypothesized that EF and memory measures would significantly predict SGI outcomes. One hundred sixty-seven individuals with TBI participated in the study. Story retellings were analyzed using the SGI protocol. Three cognitive measures--Delis-Kaplan Executive Function System (D-KEFS; Delis, Kaplan, & Kramer, 2001) Sorting Test, Wechsler Memory Scale--Third Edition (WMS-III; Wechsler, 1997) Working Memory Primary Index (WMI), and WMS-III Immediate Memory Primary Index (IMI)--were entered into a multiple linear regression model for each discourse measure. Two sets of regression analyses were performed, the first with the Sorting Test as the first predictor and the second with it as the last. The first set of regression analyses identified the Sorting Test and IMI as the only significant predictors of performance on measures of the SGI. The second set identified all measures as significant predictors when evaluating each step of the regression function. The cognitive variables predicted performance on the SGI measures, although there were differences in the amount of explained variance. The results (a) suggest that storytelling ability draws on a number of underlying skills and (b) underscore the importance of using discrete cognitive tasks rather than broad cognitive indices to investigate the cognitive substrates of discourse.

  19. Assess and Predict Automatic Generation Control Performances for Thermal Power Generation Units Based on Modeling Techniques

    Science.gov (United States)

    Zhao, Yan; Yang, Zijiang; Gao, Song; Liu, Jinbiao

    2018-02-01

    Automatic generation control(AGC) is a key technology to maintain real time power generation and load balance, and to ensure the quality of power supply. Power grids require each power generation unit to have a satisfactory AGC performance, being specified in two detailed rules. The two rules provide a set of indices to measure the AGC performance of power generation unit. However, the commonly-used method to calculate these indices is based on particular data samples from AGC responses and will lead to incorrect results in practice. This paper proposes a new method to estimate the AGC performance indices via system identification techniques. In addition, a nonlinear regression model between performance indices and load command is built in order to predict the AGC performance indices. The effectiveness of the proposed method is validated through industrial case studies.

  20. Plasmonic Light Trapping in Thin-Film Solar Cells: Impact of Modeling on Performance Prediction

    Directory of Open Access Journals (Sweden)

    Alberto Micco

    2015-06-01

    Full Text Available We present a comparative study on numerical models used to predict the absorption enhancement in thin-film solar cells due to the presence of structured back-reflectors exciting, at specific wavelengths, hybrid plasmonic-photonic resonances. To evaluate the effectiveness of the analyzed models, they have been applied in a case study: starting from a U-shaped textured glass thin-film, µc-Si:H solar cells have been successfully fabricated. The fabricated cells, with different intrinsic layer thicknesses, have been morphologically, optically and electrically characterized. The experimental results have been successively compared with the numerical predictions. We have found that, in contrast to basic models based on the underlying schematics of the cell, numerical models taking into account the real morphology of the fabricated device, are able to effectively predict the cells performances in terms of both optical absorption and short-circuit current values.

  1. A new model for predicting performance of fin-and-tube heat exchanger under frost condition

    International Nuclear Information System (INIS)

    Cui, J.; Li, W.Z.; Liu, Y.; Zhao, Y.S.

    2011-01-01

    Accurate prediction of frost characteristics has crucial influence on designing effective heat exchangers. In this paper, a new CFD (Computational Fluid Dynamics) model has been proposed to predict the frost behaviour. The initial period of frost formation can be predicted and the influence of surface structure can be considered. The numerical simulations have been carried out to investigate the performance of fin-and-tube heat exchanger under frost condition. The results have been validated by comparison of simulations with the data computed by empirical formulas. The transient local frost formation has been obtained. The average frost thickness, heat exchanger coefficient and pressure drop on air side has been analysed as well. In addition, the influence factors have also been discussed, such as fin pitch, relative humidity, air flow rate and evaporating temperature of refrigerant.

  2. Selecting the minimum prediction base of historical data to perform 5-year predictions of the cancer burden: The GoF-optimal method.

    Science.gov (United States)

    Valls, Joan; Castellà, Gerard; Dyba, Tadeusz; Clèries, Ramon

    2015-06-01

    Predicting the future burden of cancer is a key issue for health services planning, where a method for selecting the predictive model and the prediction base is a challenge. A method, named here Goodness-of-Fit optimal (GoF-optimal), is presented to determine the minimum prediction base of historical data to perform 5-year predictions of the number of new cancer cases or deaths. An empirical ex-post evaluation exercise for cancer mortality data in Spain and cancer incidence in Finland using simple linear and log-linear Poisson models was performed. Prediction bases were considered within the time periods 1951-2006 in Spain and 1975-2007 in Finland, and then predictions were made for 37 and 33 single years in these periods, respectively. The performance of three fixed different prediction bases (last 5, 10, and 20 years of historical data) was compared to that of the prediction base determined by the GoF-optimal method. The coverage (COV) of the 95% prediction interval and the discrepancy ratio (DR) were calculated to assess the success of the prediction. The results showed that (i) models using the prediction base selected through GoF-optimal method reached the highest COV and the lowest DR and (ii) the best alternative strategy to GoF-optimal was the one using the base of prediction of 5-years. The GoF-optimal approach can be used as a selection criterion in order to find an adequate base of prediction. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Poor Gait Performance and Prediction of Dementia: Results From a Meta-Analysis.

    Science.gov (United States)

    Beauchet, Olivier; Annweiler, Cédric; Callisaya, Michele L; De Cock, Anne-Marie; Helbostad, Jorunn L; Kressig, Reto W; Srikanth, Velandai; Steinmetz, Jean-Paul; Blumen, Helena M; Verghese, Joe; Allali, Gilles

    2016-06-01

    Poor gait performance predicts risk of developing dementia. No structured critical evaluation has been conducted to study this association yet. The aim of this meta-analysis was to systematically examine the association of poor gait performance with incidence of dementia. An English and French Medline search was conducted in June 2015, with no limit of date, using the medical subject headings terms "Gait" OR "Gait Disorders, Neurologic" OR "Gait Apraxia" OR "Gait Ataxia" AND "Dementia" OR "Frontotemporal Dementia" OR "Dementia, Multi-Infarct" OR "Dementia, Vascular" OR "Alzheimer Disease" OR "Lewy Body Disease" OR "Frontotemporal Dementia With Motor Neuron Disease" (Supplementary Concept). Poor gait performance was defined by standardized tests of walking, and dementia was diagnosed according to international consensus criteria. Four etiologies of dementia were identified: any dementia, Alzheimer disease (AD), vascular dementia (VaD), and non-AD (ie, pooling VaD, mixed dementias, and other dementias). Fixed effects meta-analyses were performed on the estimates in order to generate summary values. Of the 796 identified abstracts, 12 (1.5%) were included in this systematic review and meta-analysis. Poor gait performance predicted dementia [pooled hazard ratio (HR) combined with relative risk and odds ratio = 1.53 with P analysis provides evidence that poor gait performance predicts dementia. This association depends on the type of dementia; poor gait performance is a stronger predictor of non-AD dementias than AD. Copyright © 2016 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

  4. Evaluation of a Nutrition Model in Predicting Performance of Vietnamese Cattle

    Directory of Open Access Journals (Sweden)

    David Parsons

    2012-09-01

    level 1 solution can predict DMI reasonably well for this type of animal, but it was not entirely clear if animals consumed at their voluntary intake and/or if the roughness of the diet decreased DMI. A deficit of ruminally-undegradable protein and/or a lack of microbial protein may have limited the performance of these animals. Based on these evaluations, the LRNS level 1 solution may be an alternative to predict animal performance when, under specific circumstances, the fractional degradation rates of the carbohydrate and protein fractions are not known.

  5. Long‐Term Post‐CABG Survival: Performance of Clinical Risk Models Versus Actuarial Predictions

    Science.gov (United States)

    Carr, Brendan M.; Romeiser, Jamie; Ruan, Joyce; Gupta, Sandeep; Seifert, Frank C.; Zhu, Wei

    2015-01-01

    Abstract Background/aim Clinical risk models are commonly used to predict short‐term coronary artery bypass grafting (CABG) mortality but are less commonly used to predict long‐term mortality. The added value of long‐term mortality clinical risk models over traditional actuarial models has not been evaluated. To address this, the predictive performance of a long‐term clinical risk model was compared with that of an actuarial model to identify the clinical variable(s) most responsible for any differences observed. Methods Long‐term mortality for 1028 CABG patients was estimated using the Hannan New York State clinical risk model and an actuarial model (based on age, gender, and race/ethnicity). Vital status was assessed using the Social Security Death Index. Observed/expected (O/E) ratios were calculated, and the models' predictive performances were compared using a nested c‐index approach. Linear regression analyses identified the subgroup of risk factors driving the differences observed. Results Mortality rates were 3%, 9%, and 17% at one‐, three‐, and five years, respectively (median follow‐up: five years). The clinical risk model provided more accurate predictions. Greater divergence between model estimates occurred with increasing long‐term mortality risk, with baseline renal dysfunction identified as a particularly important driver of these differences. Conclusions Long‐term mortality clinical risk models provide enhanced predictive power compared to actuarial models. Using the Hannan risk model, a patient's long‐term mortality risk can be accurately assessed and subgroups of higher‐risk patients can be identified for enhanced follow‐up care. More research appears warranted to refine long‐term CABG clinical risk models. doi: 10.1111/jocs.12665 (J Card Surg 2016;31:23–30) PMID:26543019

  6. Do workaholism and work engagement predict employee well-being and performance in opposite directions?

    Science.gov (United States)

    Shimazu, Akihito; Schaufeli, Wilmar B; Kubota, Kazumi; Kawakami, Norito

    2012-01-01

    This study investigated the distinctiveness between workaholism and work engagement by examining their longitudinal relationships (measurement interval=7 months) with well-being and performance in a sample of 1,967 Japanese employees from various occupations. Based on a previous cross-sectional study (Shimazu & Schaufeli, 2009), we expected that workaholism predicts future unwell-being (i.e., high ill-health and low life satisfaction) and poor job performance, whereas work engagement predicts future well-being (i.e., low ill-health and high life satisfaction) and superior job performance. T1-T2 changes in ill-health, life satisfaction and job performance were measured as residual scores that were then included in the structural equation model. Results showed that workaholism and work engagement were weakly and positively related to each other. In addition, workaholism was related to an increase in ill-health and to a decrease in life satisfaction. In contrast, work engagement was related to a decrease in ill-health and to increases in both life satisfaction and job performance. These findings suggest that workaholism and work engagement are two different kinds of concepts that are oppositely related to well-being and performance.

  7. Review and evaluation of performance measures for survival prediction models in external validation settings

    Directory of Open Access Journals (Sweden)

    M. Shafiqur Rahman

    2017-04-01

    Full Text Available Abstract Background When developing a prediction model for survival data it is essential to validate its performance in external validation settings using appropriate performance measures. Although a number of such measures have been proposed, there is only limited guidance regarding their use in the context of model validation. This paper reviewed and evaluated a wide range of performance measures to provide some guidelines for their use in practice. Methods An extensive simulation study based on two clinical datasets was conducted to investigate the performance of the measures in external validation settings. Measures were selected from categories that assess the overall performance, discrimination and calibration of a survival prediction model. Some of these have been modified to allow their use with validation data, and a case study is provided to describe how these measures can be estimated in practice. The measures were evaluated with respect to their robustness to censoring and ease of interpretation. All measures are implemented, or are straightforward to implement, in statistical software. Results Most of the performance measures were reasonably robust to moderate levels of censoring. One exception was Harrell’s concordance measure which tended to increase as censoring increased. Conclusions We recommend that Uno’s concordance measure is used to quantify concordance when there are moderate levels of censoring. Alternatively, Gönen and Heller’s measure could be considered, especially if censoring is very high, but we suggest that the prediction model is re-calibrated first. We also recommend that Royston’s D is routinely reported to assess discrimination since it has an appealing interpretation. The calibration slope is useful for both internal and external validation settings and recommended to report routinely. Our recommendation would be to use any of the predictive accuracy measures and provide the corresponding predictive

  8. Modification in the FUDA computer code to predict fuel performance at high burnup

    Energy Technology Data Exchange (ETDEWEB)

    Das, M; Arunakumar, B V; Prasad, P N [Nuclear Power Corp., Mumbai (India)

    1997-08-01

    The computer code FUDA (FUel Design Analysis) participated in the blind exercises organized by the IAEA CRP (Co-ordinated Research Programme) on FUMEX (Fuel Modelling at Extended Burnup). While the code prediction compared well with the experiments at Halden under various parametric and operating conditions, the fission gas release and fission gas pressure were found to be slightly over-predicted, particularly at high burnups. In view of the results of 6 FUMEX cases, the main models and submodels of the code were reviewed and necessary improvements were made. The new version of the code FUDA MOD 2 is now able to predict fuel performance parameter for burn-ups up to 50000 MWD/TeU. The validation field of the code has been extended to prediction of thorium oxide fuel performance. An analysis of local deformations at pellet interfaces and near the end caps is carried out considering the hourglassing of the pellet by finite element technique. (author). 15 refs, 1 fig.

  9. Modification in the FUDA computer code to predict fuel performance at high burnup

    International Nuclear Information System (INIS)

    Das, M.; Arunakumar, B.V.; Prasad, P.N.

    1997-01-01

    The computer code FUDA (FUel Design Analysis) participated in the blind exercises organized by the IAEA CRP (Co-ordinated Research Programme) on FUMEX (Fuel Modelling at Extended Burnup). While the code prediction compared well with the experiments at Halden under various parametric and operating conditions, the fission gas release and fission gas pressure were found to be slightly over-predicted, particularly at high burnups. In view of the results of 6 FUMEX cases, the main models and submodels of the code were reviewed and necessary improvements were made. The new version of the code FUDA MOD 2 is now able to predict fuel performance parameter for burn-ups up to 50000 MWD/TeU. The validation field of the code has been extended to prediction of thorium oxide fuel performance. An analysis of local deformations at pellet interfaces and near the end caps is carried out considering the hourglassing of the pellet by finite element technique. (author). 15 refs, 1 fig

  10. The predictive validity of the BioMedical Admissions Test for pre-clinical examination performance.

    Science.gov (United States)

    Emery, Joanne L; Bell, John F

    2009-06-01

    Some medical courses in the UK have many more applicants than places and almost all applicants have the highest possible previous and predicted examination grades. The BioMedical Admissions Test (BMAT) was designed to assist in the student selection process specifically for a number of 'traditional' medical courses with clear pre-clinical and clinical phases and a strong focus on science teaching in the early years. It is intended to supplement the information provided by examination results, interviews and personal statements. This paper reports on the predictive validity of the BMAT and its predecessor, the Medical and Veterinary Admissions Test. Results from the earliest 4 years of the test (2000-2003) were matched to the pre-clinical examination results of those accepted onto the medical course at the University of Cambridge. Correlation and logistic regression analyses were performed for each cohort. Section 2 of the test ('Scientific Knowledge') correlated more strongly with examination marks than did Section 1 ('Aptitude and Skills'). It also had a stronger relationship with the probability of achieving the highest examination class. The BMAT and its predecessor demonstrate predictive validity for the pre-clinical years of the medical course at the University of Cambridge. The test identifies important differences in skills and knowledge between candidates, not shown by their previous attainment, which predict their examination performance. It is thus a valid source of additional admissions information for medical courses with a strong scientific emphasis when previous attainment is very high.

  11. Performance predictions for solar-chemical converters based on photoelectrochemical I-V curves

    Energy Technology Data Exchange (ETDEWEB)

    Luttmer, J.D.; Trachtenberg, I.

    1985-06-01

    Texas Instruments' solar energy system contains a solar-chemical converter (SCC) which converts solar energy into chemical energy via the electrolysis of hydrobromic acid (HBr) into hydrogen (H/sub 2/) and bromine (Br/sub 2/). Previous predictions of SCC performance have employed electrical dry-probe data and a computer simulation model to predict the H/sub 2/ generation rates. The method of prediction described here makes use of the photoelectrochemical Icurves to determine the ''wet'' probe parameters of V /SUB oc/ J /SUB sc/ FF, and efficiency for anodes and cathodes. The advantages of this technique over the dry-probe/computer simulation method are discussed. A comparison of predicted and measured H/sub 2/ generation rates is presented. Solar to chemical efficiencies of 8.6% have been both predicted and measured for the electrolysis of 48% HBr to hydrogen and bromine by a full anode/cathode array. Individual cathode solar to hydrogen efficiencies of 9.5% have been obtained.

  12. Navier-Stokes and Comprehensive Analysis Performance Predictions of the NREL Phase VI Experiment

    Science.gov (United States)

    Duque, Earl P. N.; Burklund, Michael D.; Johnson, Wayne

    2003-01-01

    A vortex lattice code, CAMRAD II, and a Reynolds-Averaged Navier-Stoke code, OVERFLOW-D2, were used to predict the aerodynamic performance of a two-bladed horizontal axis wind turbine. All computations were compared with experimental data that was collected at the NASA Ames Research Center 80- by 120-Foot Wind Tunnel. Computations were performed for both axial as well as yawed operating conditions. Various stall delay models and dynamics stall models were used by the CAMRAD II code. Comparisons between the experimental data and computed aerodynamic loads show that the OVERFLOW-D2 code can accurately predict the power and spanwise loading of a wind turbine rotor.

  13. Prediction of multi performance characteristics of wire EDM process using grey ANFIS

    Science.gov (United States)

    Kumanan, Somasundaram; Nair, Anish

    2017-09-01

    Super alloys are used to fabricate components in ultra-supercritical power plants. These hard to machine materials are processed using non-traditional machining methods like Wire cut electrical discharge machining and needs attention. This paper details about multi performance optimization of wire EDM process using Grey ANFIS. Experiments are designed to establish the performance characteristics of wire EDM such as surface roughness, material removal rate, wire wear rate and geometric tolerances. The control parameters are pulse on time, pulse off time, current, voltage, flushing pressure, wire tension, table feed and wire speed. Grey relational analysis is employed to optimise the multi objectives. Analysis of variance of the grey grades is used to identify the critical parameters. A regression model is developed and used to generate datasets for the training of proposed adaptive neuro fuzzy inference system. The developed prediction model is tested for its prediction ability.

  14. TBM performance prediction in Yucca Mountain welded tuff from linear cutter tests

    International Nuclear Information System (INIS)

    Gertsch, R.; Ozdemir, L.; Gertsch, L.

    1992-01-01

    This paper discusses performance prediction which were developed for tunnel boring machines operating in welded tuff for the construction of the experimental study facility and the potential nuclear waste repository at Yucca Mountain. The predictions were based on test data obtained from an extensive series of linear cutting tests performed on samples of Topopah String welded tuff from the Yucca Mountain Project site. Using the cutter force, spacing, and penetration data from the experimental program, the thrust, torque, power, and rate of penetration were estimated for a 25 ft diameter tunnel boring machine (TBM) operating in welded tuff. The result show that the Topopah Spring welded tuff (TSw2) can be excavated at relatively high rates of advance with state-of-the-art TBMs. The result also show, however, that the TBM torque and power requirements will be higher than estimated based on rock physical properties and past tunneling experience in rock formations of similar strength

  15. Comparison of Taxi Time Prediction Performance Using Different Taxi Speed Decision Trees

    Science.gov (United States)

    Lee, Hanbong

    2017-01-01

    In the STBO modeler and tactical surface scheduler for ATD-2 project, taxi speed decision trees are used to calculate the unimpeded taxi times of flights taxiing on the airport surface. The initial taxi speed values in these decision trees did not show good prediction accuracy of taxi times. Using the more recent, reliable surveillance data, new taxi speed values in ramp area and movement area were computed. Before integrating these values into the STBO system, we performed test runs using live data from Charlotte airport, with different taxi speed settings: 1) initial taxi speed values and 2) new ones. Taxi time prediction performance was evaluated by comparing various metrics. The results show that the new taxi speed decision trees can calculate the unimpeded taxi-out times more accurately.

  16. In vitro models for the prediction of in vivo performance of oral dosage forms

    DEFF Research Database (Denmark)

    Kostewicz, Edmund S; Abrahamsson, Bertil; Brewster, Marcus

    2014-01-01

    Accurate prediction of the in vivo biopharmaceutical performance of oral drug formulations is critical to efficient drug development. Traditionally, in vitro evaluation of oral drug formulations has focused on disintegration and dissolution testing for quality control (QC) purposes. The connection...... of formulations that rely on complex intraluminal processes (e.g. solubilization, supersaturation, precipitation…) remains extremely challenging. Concomitantly, the increasing demand for complex formulations to overcome low drug solubility or to control drug release rates urges the development of new in vitro...

  17. A Novel Analysis of Performance Classification and Workload Prediction Using Electroencephalography (EEG) Frequency Data

    Science.gov (United States)

    2015-03-26

    calming music to ease the individual before the start of the study [8]. EEG data contains noise ranging from muscle twitches, blinking and other functions...depict brain activity visually, Borghini et al was also able to note the trend of the supposed learning process using only the Theta EEG frequency...named Prediction of Operator Performance ( POP ). One of the assumptions of this model is that only a small number of cognitive activities can be

  18. Performance Characteristics and Prediction of Bodyweight using Linear Body Measurements in Four Strains of Broiler Chicken

    OpenAIRE

    I. Udeh; J.O. Isikwenu and G. Ukughere

    2011-01-01

    The objectives of this study were to compare the performance characteristics of four strains of broiler chicken from 2 to 8 weeks of age and predict body weight of the broilers using linear body measurements. The four strains of broiler chicken used were Anak, Arbor Acre, Ross and Marshall. The parameters recorded were bodyweight, weight gain, total feed intake, feed conversion ratio, mortality and some linear body measurements (body length, body width, breast width, drumstick length, shank l...

  19. Performance prediction of high Tc superconducting small antennas using a two-fluid-moment method model

    Science.gov (United States)

    Cook, G. G.; Khamas, S. K.; Kingsley, S. P.; Woods, R. C.

    1992-01-01

    The radar cross section and Q factors of electrically small dipole and loop antennas made with a YBCO high Tc superconductor are predicted using a two-fluid-moment method model, in order to determine the effects of finite conductivity on the performances of such antennas. The results compare the useful operating bandwidths of YBCO antennas exhibiting varying degrees of impurity with their copper counterparts at 77 K, showing a linear relationship between bandwidth and impurity level.

  20. Re-parametrization of a swine model to predict growth performance of broilers

    OpenAIRE

    Dukhta, G.; van Milgen, Jacob; Kövér, G.; Halas, V.

    2017-01-01

    The aim of the study was to investigate whether a pig growth model is suitable to be modified and adapted for broilers. As monogastric animals, pigs and poultry share many similarities in their digestion and metabolism, many structures (body protein and lipid stores) and the nutrient flows of the underlying metabolic pathways are similar among species. For that purpose, the InraPorc model was used as a basis to predict growth performance and body composition at slaughter in broilers. First...

  1. The Value of Different Customer Satisfaction and Loyalty Metrics in Predicting Business Performance

    OpenAIRE

    Neil A. Morgan; Lopo Leotte Rego

    2006-01-01

    Managers commonly use customer feedback data to set goals and monitor performance on metrics such as “Top 2 Box” customer satisfaction scores and “intention-to-repurchase” loyalty scores. However, analysts have advocated a number of different customer feedback metrics including average customer satisfaction scores and the number of “net promoters” among a firm's customers. We empirically examine which commonly used and widely advocated customer feedback metrics are most valuable in predicting...

  2. Individual reactions to stress predict performance during a critical aviation incident.

    Science.gov (United States)

    Vine, Samuel J; Uiga, Liis; Lavric, Aureliu; Moore, Lee J; Tsaneva-Atanasova, Krasimira; Wilson, Mark R

    2015-01-01

    Understanding the influence of stress on human performance is of theoretical and practical importance. An individual's reaction to stress predicts their subsequent performance; with a "challenge" response to stress leading to better performance than a "threat" response. However, this contention has not been tested in truly stressful environments with highly skilled individuals. Furthermore, the effect of challenge and threat responses on attentional control during visuomotor tasks is poorly understood. Thus, this study aimed to examine individual reactions to stress and their influence on attentional control, among a cohort of commercial pilots performing a stressful flight assessment. Sixteen pilots performed an "engine failure on take-off" scenario, in a high-fidelity flight simulator. Reactions to stress were indexed via self-report; performance was assessed subjectively (flight instructor assessment) and objectively (simulator metrics); gaze behavior data were captured using a mobile eye tracker, and measures of attentional control were subsequently calculated (search rate, stimulus driven attention, and entropy). Hierarchical regression analyses revealed that a threat response was associated with poorer performance and disrupted attentional control. The findings add to previous research showing that individual reactions to stress influence performance and shed light on the processes through which stress influences performance.

  3. Incremental Validity of Personality Measures in Predicting Underwater Performance and Adaptation.

    Science.gov (United States)

    Colodro, Joaquín; Garcés-de-Los-Fayos, Enrique J; López-García, Juan J; Colodro-Conde, Lucía

    2015-03-17

    Intelligence and personality traits are currently considered effective predictors of human behavior and job performance. However, there are few studies about their relevance in the underwater environment. Data from a sample of military personnel performing scuba diving courses were analyzed with regression techniques, testing the contribution of individual differences and ascertaining the incremental validity of the personality in an environment with extreme psychophysical demands. The results confirmed the incremental validity of personality traits (ΔR 2 = .20, f 2 = .25) over the predictive contribution of general mental ability (ΔR 2 = .07, f 2 = .08) in divers' performance. Moreover, personality (R(L)2 = .34) also showed a higher validity to predict underwater adaptation than general mental ability ( R(L)2 = .09). The ROC curve indicated 86% of the maximum possible discrimination power for the prediction of underwater adaptation, AUC = .86, p personality traits as predictors of an effective response to the changing circumstances of military scuba diving. They also may improve the understanding of the behavioral effects and psychophysiological complications of diving and can also provide guidance for psychological intervention and prevention of risk in this extreme environment.

  4. An approach for prediction of petroleum production facility performance considering Arctic influence factors

    International Nuclear Information System (INIS)

    Gao Xueli; Barabady, Javad; Markeset, Tore

    2010-01-01

    As the oil and gas (O and G) industry is increasing the focus on petroleum exploration and development in the Arctic region, it is becoming increasingly important to design exploration and production facilities to suit the local operating conditions. The cold and harsh climate, the long distance from customer and suppliers' markets, and the sensitive environment may have considerable influence on the choice of design solutions and production performance characteristics such as throughput capacity, reliability, availability, maintainability, and supportability (RAMS) as well as operational and maintenance activities. Due to this, data and information collected for similar systems used in a normal climate may not be suitable. Hence, it is important to study and develop methods for prediction of the production performance characteristics during the design and operation phases. The aim of this paper is to present an approach for prediction of the production performance for oil and gas production facilities considering influencing factors in Arctic conditions. The proportional repair model (PRM) is developed in order to predict repair rate in Arctic conditions. The model is based on the proportional hazard model (PHM). A simple case study is used to demonstrate how the proposed approach can be applied.

  5. Predicting the Performance of Chain Saw Machines Based on Shore Scleroscope Hardness

    Science.gov (United States)

    Tumac, Deniz

    2014-03-01

    Shore hardness has been used to estimate several physical and mechanical properties of rocks over the last few decades. However, the number of researches correlating Shore hardness with rock cutting performance is quite limited. Also, rather limited researches have been carried out on predicting the performance of chain saw machines. This study differs from the previous investigations in the way that Shore hardness values (SH1, SH2, and deformation coefficient) are used to determine the field performance of chain saw machines. The measured Shore hardness values are correlated with the physical and mechanical properties of natural stone samples, cutting parameters (normal force, cutting force, and specific energy) obtained from linear cutting tests in unrelieved cutting mode, and areal net cutting rate of chain saw machines. Two empirical models developed previously are improved for the prediction of the areal net cutting rate of chain saw machines. The first model is based on a revised chain saw penetration index, which uses SH1, machine weight, and useful arm cutting depth as predictors. The second model is based on the power consumed for only cutting the stone, arm thickness, and specific energy as a function of the deformation coefficient. While cutting force has a strong relationship with Shore hardness values, the normal force has a weak or moderate correlation. Uniaxial compressive strength, Cerchar abrasivity index, and density can also be predicted by Shore hardness values.

  6. A Family of High-Performance Solvers for Linear Model Predictive Control

    DEFF Research Database (Denmark)

    Frison, Gianluca; Sokoler, Leo Emil; Jørgensen, John Bagterp

    2014-01-01

    In Model Predictive Control (MPC), an optimization problem has to be solved at each sampling time, and this has traditionally limited the use of MPC to systems with slow dynamic. In this paper, we propose an e_cient solution strategy for the unconstrained sub-problems that give the search......-direction in Interior-Point (IP) methods for MPC, and that usually are the computational bottle-neck. This strategy combines a Riccati-like solver with the use of high-performance computing techniques: in particular, in this paper we explore the performance boost given by the use of single precision computation...

  7. Combining Results from Distinct MicroRNA Target Prediction Tools Enhances the Performance of Analyses

    Directory of Open Access Journals (Sweden)

    Arthur C. Oliveira

    2017-05-01

    Full Text Available Target prediction is generally the first step toward recognition of bona fide microRNA (miRNA-target interactions in living cells. Several target prediction tools are now available, which use distinct criteria and stringency to provide the best set of candidate targets for a single miRNA or a subset of miRNAs. However, there are many false-negative predictions, and consensus about the optimum strategy to select and use the output information provided by the target prediction tools is lacking. We compared the performance of four tools cited in literature—TargetScan (TS, miRanda-mirSVR (MR, Pita, and RNA22 (R22, and we determined the most effective approach for analyzing target prediction data (individual, union, or intersection. For this purpose, we calculated the sensitivity, specificity, precision, and correlation of these approaches using 10 miRNAs (miR-1-3p, miR-17-5p, miR-21-5p, miR-24-3p, miR-29a-3p, miR-34a-5p, miR-124-3p, miR-125b-5p, miR-145-5p, and miR-155-5p and 1,400 genes (700 validated and 700 non-validated as targets of these miRNAs. The four tools provided a subset of high-quality predictions and returned few false-positive predictions; however, they could not identify several known true targets. We demonstrate that union of TS/MR and TS/MR/R22 enhanced the quality of in silico prediction analysis of miRNA targets. We conclude that the union rather than the intersection of the aforementioned tools is the best strategy for maximizing performance while minimizing the loss of time and resources in subsequent in vivo and in vitro experiments for functional validation of miRNA-target interactions.

  8. Perceived Medical School stress of undergraduate medical students predicts academic performance: an observational study.

    Science.gov (United States)

    Kötter, Thomas; Wagner, Josefin; Brüheim, Linda; Voltmer, Edgar

    2017-12-16

    Medical students are exposed to high amounts of stress. Stress and poor academic performance can become part of a vicious circle. In order to counteract this circularity, it seems important to better understand the relationship between stress and performance during medical education. The most widespread stress questionnaire designed for use in Medical School is the "Perceived Medical School Stress Instrument" (PMSS). It addresses a wide range of stressors, including workload, competition, social isolation and financial worries. Our aim was to examine the relation between the perceived Medical School stress of undergraduate medical students and academic performance. We measured Medical School stress using the PMSS at two different time points (at the end of freshman year and at the end of sophomore year) and matched stress scores together with age and gender to the first medical examination (M1) grade of the students (n = 456). PMSS scores from 2 and 14 months before M1 proved to be significant predictors for medical students' M1 grade. Age and gender also predict academic performance, making older female students with high stress scores a potential risk group for entering the vicious circle of stress and poor academic performance. PMSS sum scores 2 and 14 months before the M1 exam seem to have an independent predictive validity for medical students' M1 grade. More research is needed to identify potential confounders.

  9. Trait impulsivity predicts D-KEFS tower test performance in university students.

    Science.gov (United States)

    Lyvers, Michael; Basch, Vanessa; Duff, Helen; Edwards, Mark S

    2015-01-01

    The present study examined a widely used self-report index of trait impulsiveness in relation to performance on a well-known neuropsychological executive function test in 70 university undergraduate students (50 women, 20 men) aged 18 to 24 years old. Participants completed the Barratt Impulsiveness Scale (BIS-11) and the Frontal Systems Behavior Scale (FrSBe), after which they performed the Tower Test of the Delis-Kaplan Executive Function System. Hierarchical linear regression showed that after controlling for gender, current alcohol consumption, age at onset of weekly alcohol use, and FrSBe scores, BIS-11 significantly predicted Tower Test Achievement scores, β = -.44, p impulsiveness is associated with poorer executive cognitive performance even in a sample likely to be characterized by relatively high general cognitive functioning (i.e., university students). The results also support the role of inhibition as a key aspect of executive task performance. Elevated scores on the BIS-11 and FrSBe are known to be linked to risky drinking in young adults as confirmed in this sample; however, only BIS-11 predicted Tower Test performance.

  10. Design and performance of an analysis-by-synthesis class of predictive speech coders

    Science.gov (United States)

    Rose, Richard C.; Barnwell, Thomas P., III

    1990-01-01

    The performance of a broad class of analysis-by-synthesis linear predictive speech coders is quantified experimentally. The class of coders includes a number of well-known techniques as well as a very large number of speech coders which have not been named or studied. A general formulation for deriving the parametric representation used in all of the coders in the class is presented. A new coder, named the self-excited vocoder, is discussed because of its good performance with low complexity, and because of the insight this coder gives to analysis-by-synthesis coders in general. The results of a study comparing the performances of different members of this class are presented. The study takes the form of a series of formal subjective and objective speech quality tests performed on selected coders. The results of this study lead to some interesting and important observations concerning the controlling parameters for analysis-by-synthesis speech coders.

  11. A face only an investor could love: CEOs' facial structure predicts their firms' financial performance.

    Science.gov (United States)

    Wong, Elaine M; Ormiston, Margaret E; Haselhuhn, Michael P

    2011-12-01

    Researchers have theorized that innate personal traits are related to leadership success. Although links between psychological characteristics and leadership success have been well established, research has yet to identify any objective physical traits of leaders that predict organizational performance. In the research reported here, we identified leaders' facial structure as a specific physical trait that correlates with organizational performance. Specifically, we found that firms whose male CEOs have wider faces (relative to facial height) achieve superior financial performance. Decision-making dynamics within a firm's leadership team moderate this effect, such that the relationship between a given CEO's facial measurements and his firm's financial performance is stronger in firms with cognitively simple leadership teams.

  12. The interactive roles of mastery climate and performance climate in predicting intrinsic motivation.

    Science.gov (United States)

    Buch, R; Nerstad, C G L; Säfvenbom, R

    2017-02-01

    This study examined the interplay between perceived mastery and performance climates in predicting increased intrinsic motivation. The results of a two-wave longitudinal study comprising of 141 individuals from three military academies revealed a positive relationship between a perceived mastery climate and increased intrinsic motivation only for individuals who perceived a low performance climate. This finding suggests a positive relationship between a perceived mastery climate and increased intrinsic motivation only when combined with low perceptions of a performance climate. Hence, introducing a performance climate in addition to a mastery climate can be an undermining motivational strategy, as it attenuates the positive relationship between a mastery climate and increased intrinsic motivation. Implications for future research and practice are discussed. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  13. Performance Feedback Processing Is Positively Biased As Predicted by Attribution Theory.

    Directory of Open Access Journals (Sweden)

    Christoph W Korn

    Full Text Available A considerable literature on attribution theory has shown that healthy individuals exhibit a positivity bias when inferring the causes of evaluative feedback on their performance. They tend to attribute positive feedback internally (e.g., to their own abilities but negative feedback externally (e.g., to environmental factors. However, all empirical demonstrations of this bias suffer from at least one of the three following drawbacks: First, participants directly judge explicit causes for their performance. Second, participants have to imagine events instead of experiencing them. Third, participants assess their performance only after receiving feedback and thus differences in baseline assessments cannot be excluded. It is therefore unclear whether the classically reported positivity bias generalizes to setups without these drawbacks. Here, we aimed at establishing the relevance of attributions for decision-making by showing an attribution-related positivity bias in a decision-making task. We developed a novel task, which allowed us to test how participants changed their evaluations in response to positive and negative feedback about performance. Specifically, we used videos of actors expressing different facial emotional expressions. Participants were first asked to evaluate the actors' credibility in expressing a particular emotion. After this initial rating, participants performed an emotion recognition task and did--or did not--receive feedback on their veridical performance. Finally, participants re-rated the actors' credibility, which provided a measure of how they changed their evaluations after feedback. Attribution theory predicts that participants change their evaluations of the actors' credibility toward the positive after receiving positive performance feedback and toward the negative after negative performance feedback. Our results were in line with this prediction. A control condition without feedback showed that correct or

  14. Performance Feedback Processing Is Positively Biased As Predicted by Attribution Theory.

    Science.gov (United States)

    Korn, Christoph W; Rosenblau, Gabriela; Rodriguez Buritica, Julia M; Heekeren, Hauke R

    2016-01-01

    A considerable literature on attribution theory has shown that healthy individuals exhibit a positivity bias when inferring the causes of evaluative feedback on their performance. They tend to attribute positive feedback internally (e.g., to their own abilities) but negative feedback externally (e.g., to environmental factors). However, all empirical demonstrations of this bias suffer from at least one of the three following drawbacks: First, participants directly judge explicit causes for their performance. Second, participants have to imagine events instead of experiencing them. Third, participants assess their performance only after receiving feedback and thus differences in baseline assessments cannot be excluded. It is therefore unclear whether the classically reported positivity bias generalizes to setups without these drawbacks. Here, we aimed at establishing the relevance of attributions for decision-making by showing an attribution-related positivity bias in a decision-making task. We developed a novel task, which allowed us to test how participants changed their evaluations in response to positive and negative feedback about performance. Specifically, we used videos of actors expressing different facial emotional expressions. Participants were first asked to evaluate the actors' credibility in expressing a particular emotion. After this initial rating, participants performed an emotion recognition task and did--or did not--receive feedback on their veridical performance. Finally, participants re-rated the actors' credibility, which provided a measure of how they changed their evaluations after feedback. Attribution theory predicts that participants change their evaluations of the actors' credibility toward the positive after receiving positive performance feedback and toward the negative after negative performance feedback. Our results were in line with this prediction. A control condition without feedback showed that correct or incorrect performance

  15. Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns.

    Directory of Open Access Journals (Sweden)

    Camille Jeunet

    Full Text Available Mental-Imagery based Brain-Computer Interfaces (MI-BCIs allow their users to send commands to a computer using their brain-activity alone (typically measured by ElectroEncephaloGraphy-EEG, which is processed while they perform specific mental tasks. While very promising, MI-BCIs remain barely used outside laboratories because of the difficulty encountered by users to control them. Indeed, although some users obtain good control performances after training, a substantial proportion remains unable to reliably control an MI-BCI. This huge variability in user-performance led the community to look for predictors of MI-BCI control ability. However, these predictors were only explored for motor-imagery based BCIs, and mostly for a single training session per subject. In this study, 18 participants were instructed to learn to control an EEG-based MI-BCI by performing 3 MI-tasks, 2 of which were non-motor tasks, across 6 training sessions, on 6 different days. Relationships between the participants' BCI control performances and their personality, cognitive profile and neurophysiological markers were explored. While no relevant relationships with neurophysiological markers were found, strong correlations between MI-BCI performances and mental-rotation scores (reflecting spatial abilities were revealed. Also, a predictive model of MI-BCI performance based on psychometric questionnaire scores was proposed. A leave-one-subject-out cross validation process revealed the stability and reliability of this model: it enabled to predict participants' performance with a mean error of less than 3 points. This study determined how users' profiles impact their MI-BCI control ability and thus clears the way for designing novel MI-BCI training protocols, adapted to the profile of each user.

  16. Comparison of Different Approaches to Predict the Performance of Pumps As Turbines (PATs

    Directory of Open Access Journals (Sweden)

    Mauro Venturini

    2018-04-01

    Full Text Available This paper deals with the comparison of different methods which can be used for the prediction of the performance curves of pumps as turbines (PATs. The considered approaches are four, i.e., one physics-based simulation model (“white box” model, two “gray box” models, which integrate theory on turbomachines with specific data correlations, and one “black box” model. More in detail, the modeling approaches are: (1 a physics-based simulation model developed by the same authors, which includes the equations for estimating head, power, and efficiency and uses loss coefficients and specific parameters; (2 a model developed by Derakhshan and Nourbakhsh, which first predicts the best efficiency point of a PAT and then reconstructs their complete characteristic curves by means of two ad hoc equations; (3 the prediction model developed by Singh and Nestmann, which predicts the complete turbine characteristics based on pump shape and size; (4 an Evolutionary Polynomial Regression model, which represents a data-driven hybrid scheme which can be used for identifying the explicit mathematical relationship between PAT and pump curves. All approaches are applied to literature data, relying on both pump and PAT performance curves of head, power, and efficiency over the entire range of operation. The experimental data were provided by Derakhshan and Nourbakhsh for four different turbomachines, working in both pump and PAT mode with specific speed values in the range 1.53–5.82. This paper provides a quantitative assessment of the predictions made by means of the considered approaches and also analyzes consistency from a physical point of view. Advantages and drawbacks of each method are also analyzed and discussed.

  17. Technical player profiles related to the physical fitness of young female volleyball players predict team performance.

    Science.gov (United States)

    Dávila-Romero, C; Hernández-Mocholí, M A; García-Hermoso, A

    2015-03-01

    This study is divided into three sequential stages: identification of fitness and game performance profiles (individual player performance), an assessment of the relationship between these profiles, and an assessment of the relationship between individual player profiles and team performance during play (in championship performance). The overall study sample comprised 525 (19 teams) female volleyball players aged 12-16 years and a subsample (N.=43) used to examine study aims one and two was selected from overall sample. Anthropometric, fitness and individual player performance (actual game) data were collected in the subsample. These data were analyzed through clustering methods, ANOVA and independence chi-square test. Then, we investigated whether the proportion of players with the highest individual player performance profile might predict a team's results in the championship. Cluster analysis identified three volleyball fitness profiles (high, medium, and low) and two individual player performance profiles (high and low). The results showed a relationship between both types of profile (fitness and individual player performance). Then, linear regression revealed a moderate relationship between the number of players with a high volleyball fitness profile and a team's results in the championship (R2=0.23). The current study findings may enable coaches and trainers to manage training programs more efficiently in order to obtain tailor-made training, identify volleyball-specific physical fitness training requirements and reach better results during competitions.

  18. Predicting the outcomes of performance error indicators on accreditation status in the nuclear power industry

    International Nuclear Information System (INIS)

    Wilson, P.A.

    1986-01-01

    The null hypothesis for this study suggested that there was no significant difference in the types of performance error indicators between accredited and non-accredited programs on the following types of indicators: (1) number of significant event reports per unit, (2) number of forced outages per unit, (3) number of unplanned automatic scrams per unit, and (4) amount of equivalent availability per unit. A sample of 90 nuclear power plants was selected for this study. Data were summarized from two data bases maintained by the Institute of Nuclear Power Operations. Results of this study did not support the research hypothesis. There was no significant difference between the accredited and non-accredited programs on any of the four performance error indicators. The primary conclusions of this include the following: (1) The four selected performance error indicators cannot be used individually or collectively to predict accreditation status in the nuclear power industry. (2) Annual performance error indicator ratings cannot be used to determine the effects of performance-based training on plant performance. (3) The four selected performance error indicators cannot be used to measure the effect of operator job performance on plant effectiveness

  19. Influence of covariate distribution on the predictive performance of pharmacokinetic models in paediatric research

    Science.gov (United States)

    Piana, Chiara; Danhof, Meindert; Della Pasqua, Oscar

    2014-01-01

    Aims The accuracy of model-based predictions often reported in paediatric research has not been thoroughly characterized. The aim of this exercise is therefore to evaluate the role of covariate distributions when a pharmacokinetic model is used for simulation purposes. Methods Plasma concentrations of a hypothetical drug were simulated in a paediatric population using a pharmacokinetic model in which body weight was correlated with clearance and volume of distribution. Two subgroups of children were then selected from the overall population according to a typical study design, in which pre-specified body weight ranges (10–15 kg and 30–40 kg) were used as inclusion criteria. The simulated data sets were then analyzed using non-linear mixed effects modelling. Model performance was assessed by comparing the accuracy of AUC predictions obtained for each subgroup, based on the model derived from the overall population and by extrapolation of the model parameters across subgroups. Results Our findings show that systemic exposure as well as pharmacokinetic parameters cannot be accurately predicted from the pharmacokinetic model obtained from a population with a different covariate range from the one explored during model building. Predictions were accurate only when a model was used for prediction in a subgroup of the initial population. Conclusions In contrast to current practice, the use of pharmacokinetic modelling in children should be limited to interpolations within the range of values observed during model building. Furthermore, the covariate point estimate must be kept in the model even when predictions refer to a subset different from the original population. PMID:24433411

  20. Performance Investigation of A Mix Wind Turbine Using A Clutch Mechanism At Low Wind Speed Condition

    Science.gov (United States)

    Jamanun, M. J.; Misaran, M. S.; Rahman, M.; Muzammil, W. K.

    2017-07-01

    Wind energy is one of the methods that generates energy from sustainable resources. This technology has gained prominence in this era because it produces no harmful product to the society. There is two fundamental type of wind turbine are generally used this day which is Horizontal axis wind turbine (HAWT) and Vertical axis wind turbine (VAWT). The VAWT technology is more preferable compare to HAWT because it gives better efficiency and cost effectiveness as a whole. However, VAWT is known to have distinct disadvantage compared to HAWT; self-start ability and efficiency at low wind speed condition. Different solution has been proposed to solve these issues which includes custom design blades, variable angle of attack mechanism and mix wind turbine. A new type of clutch device was successfully developed in UMS to be used in a mix Savonius-Darrieus wind turbine configuration. The clutch system which barely audible when in operation compared to a ratchet clutch system interconnects the Savonius and Darrieus rotor; allowing the turbine to self-start at low wind speed condition as opposed to a standalone Darrieus turbine. The Savonius height were varied at three different size in order to understand the effect of the Savonius rotor to the mix wind turbine performance. The experimental result shows that the fabricated Savonius rotor show that the height of the Savonius rotor affecting the RPM for the turbine. The swept area (SA), aspect ratio (AR) and tip speed ratio (TSR) also calculated in this paper. The highest RPM recorded in this study is 90 RPM for Savonius rotor 0.22-meter height at 2.75 m/s. The Savonius rotor 0.22-meter also give the highest TSR for each range of speed from 0.75 m/s, 1.75 m/s and 2.75 m/s where it gives 1.03 TSR, 0.76 TSR, and 0.55 TSR.

  1. Predictive modeling of performance of a helium charged Stirling engine using an artificial neural network

    International Nuclear Information System (INIS)

    Özgören, Yaşar Önder; Çetinkaya, Selim; Sarıdemir, Suat; Çiçek, Adem; Kara, Fuat

    2013-01-01

    Highlights: ► Max torque and power values were obtained at 3.5 bar Pch, 1273 K Hst and 1.4:1 r. ► According to ANOVA, the most influential parameter on power was Hst with 48.75%. ► According to ANOVA, the most influential parameter on torque was Hst with 41.78%. ► ANN (R 2 = 99.8% for T, P) was superior to regression method (R 2 = 92% for T, 81% for P). ► LM was the best learning algorithm in predicting both power and torque. - Abstract: In this study, an artificial neural network (ANN) model was developed to predict the torque and power of a beta-type Stirling engine using helium as the working fluid. The best results were obtained by 5-11-7-1 and 5-13-7-1 network architectures, with double hidden layers for the torque and power respectively. For these network architectures, the Levenberg–Marquardt (LM) learning algorithm was used. Engine performance values predicted with the developed ANN model were compared with the actual performance values measured experimentally, and substantially coinciding results were observed. After ANN training, correlation coefficients (R 2 ) of both engine performance values for testing and training data were very close to 1. Similarly, root-mean-square error (RMSE) and mean error percentage (MEP) values for the testing and training data were less than 0.02% and 3.5% respectively. These results showed that the ANN is an acceptable model for prediction of the torque and power of the beta-type Stirling engine

  2. Contribution of temporal data to predictive performance in 30-day readmission of morbidly obese patients

    Directory of Open Access Journals (Sweden)

    Petra Povalej Brzan

    2017-04-01

    Full Text Available Background Reduction of readmissions after discharge represents an important challenge for many hospitals and has attracted the interest of many researchers in the past few years. Most of the studies in this field focus on building cross-sectional predictive models that aim to predict the occurrence of readmission within 30-days based on information from the current hospitalization. The aim of this study is demonstration of predictive performance gain obtained by inclusion of information from historical hospitalization records among morbidly obese patients. Methods The California Statewide inpatient database was used to build regularized logistic regression models for prediction of readmission in morbidly obese patients (n = 18,881. Temporal features were extracted from historical patient hospitalization records in a one-year timeframe. Five different datasets of patients were prepared based on the number of available hospitalizations per patient. Sample size of the five datasets ranged from 4,787 patients with more than five hospitalizations to 20,521 patients with at least two hospitalization records in one year. A 10-fold cross validation was repeted 100 times to assess the variability of the results. Additionally, random forest and extreme gradient boosting were used to confirm the results. Results Area under the ROC curve increased significantly when including information from up to three historical records on all datasets. The inclusion of more than three historical records was not efficient. Similar results can be observed for Brier score and PPV value. The number of selected predictors corresponded to the complexity of the dataset ranging from an average of 29.50 selected features on the smallest dataset to 184.96 on the largest dataset based on 100 repetitions of 10-fold cross-validation. Discussion The results show positive influence of adding information from historical hospitalization records on predictive performance using all

  3. Predictive value of age of walking for later motor performance in children with mental retardation.

    Science.gov (United States)

    Kokubun, M; Haishi, K; Okuzumi, H; Hosobuchi, T; Koike, T

    1996-12-01

    The purpose of the present study was to clarify the predictive value of age of walking for later motor performance in children with mental retardation. While paying due attention to other factors, our investigation focused on the relationship between a subject's age of walking, and his or her subsequent beam-walking performance. The subjects were 85 children with mental retardation with an average age of 13 years and 3 months. Beam-walking performance was measured by a procedure developed by the authors. Five low beams (5 cm) which varied in width (12.5, 10, 7.5, 5 and 2.5 cm) were employed. The performance of subjects was scored from zero to five points according to the width of the beam that they were able to walk without falling off. From the results of multiple regression analysis, three independent variables were found to be significantly related to beam-walking performance. The age of walking was the most basic variable: partial correlation coefficient (PCC) = -45; standardized partial regression coefficient (SPRC) = -0.41. The next variable in importance was walking duration (PCC = 0.38; SPRC = 0.31). The autism variable also contributed significantly (PCC = 0.28; SPRC = 0.22). Therefore, within the age range used in the present study, the age of walking in children with mental retardation was thought to have sufficient predictive value, even when the variables which might have possibly affected their subsequent performance were taken into consideration; the earlier the age of walking, the better the beam-walking performance.

  4. Visuospatial and psychomotor aptitude predicts endovascular performance of inexperienced individuals on a virtual reality simulator.

    Science.gov (United States)

    Van Herzeele, Isabelle; O'Donoghue, Kevin G L; Aggarwal, Rajesh; Vermassen, Frank; Darzi, Ara; Cheshire, Nicholas J W

    2010-04-01

    This study evaluated virtual reality (VR) simulation for endovascular training of medical students to determine whether innate perceptual, visuospatial, and psychomotor aptitude (VSA) can predict initial and plateau phase of technical endovascular skills acquisition. Twenty medical students received didactic and endovascular training on a commercially available VR simulator. Each student treated a series of 10 identical noncomplex renal artery stenoses endovascularly. The simulator recorded performance data instantly and objectively. An experienced interventionalist rated the performance at the initial and final sessions using generic (out of 40) and procedure-specific (out of 30) rating scales. VSA were tested with fine motor dexterity (FMD, Perdue Pegboard), psychomotor ability (minimally invasive virtual reality surgical trainer [MIST-VR]), image recall (Rey-Osterrieth), and organizational aptitude (map-planning). VSA performance scores were correlated with the assessment parameters of endovascular skills at commencement and completion of training. Medical students exhibited statistically significant learning curves from the initial to the plateau performance for contrast usage (medians, 28 vs 17 mL, P dexterity as well as with image recall at end of the training period. In addition to current recruitment strategies, VSA may be a useful tool for predictive validity studies.

  5. A cross docking pipeline for improving pose prediction and virtual screening performance

    Science.gov (United States)

    Kumar, Ashutosh; Zhang, Kam Y. J.

    2018-01-01

    Pose prediction and virtual screening performance of a molecular docking method depend on the choice of protein structures used for docking. Multiple structures for a target protein are often used to take into account the receptor flexibility and problems associated with a single receptor structure. However, the use of multiple receptor structures is computationally expensive when docking a large library of small molecules. Here, we propose a new cross-docking pipeline suitable to dock a large library of molecules while taking advantage of multiple target protein structures. Our method involves the selection of a suitable receptor for each ligand in a screening library utilizing ligand 3D shape similarity with crystallographic ligands. We have prospectively evaluated our method in D3R Grand Challenge 2 and demonstrated that our cross-docking pipeline can achieve similar or better performance than using either single or multiple-receptor structures. Moreover, our method displayed not only decent pose prediction performance but also better virtual screening performance over several other methods.

  6. A core competency-based objective structured clinical examination (OSCE) can predict future resident performance.

    Science.gov (United States)

    Wallenstein, Joshua; Heron, Sheryl; Santen, Sally; Shayne, Philip; Ander, Douglas

    2010-10-01

    This study evaluated the ability of an objective structured clinical examination (OSCE) administered in the first month of residency to predict future resident performance in the Accreditation Council for Graduate Medical Education (ACGME) core competencies. Eighteen Postgraduate Year 1 (PGY-1) residents completed a five-station OSCE in the first month of postgraduate training. Performance was graded in each of the ACGME core competencies. At the end of 18 months of training, faculty evaluations of resident performance in the emergency department (ED) were used to calculate a cumulative clinical evaluation score for each core competency. The correlations between OSCE scores and clinical evaluation scores at 18 months were assessed on an overall level and in each core competency. There was a statistically significant correlation between overall OSCE scores and overall clinical evaluation scores (R = 0.48, p competencies of patient care (R = 0.49, p competencies. An early-residency OSCE has the ability to predict future postgraduate performance on a global level and in specific core competencies. Used appropriately, such information can be a valuable tool for program directors in monitoring residents' progress and providing more tailored guidance. © 2010 by the Society for Academic Emergency Medicine.

  7. Anthropometric analysis and performance characteristics to predict selection in young male and female handball players

    Directory of Open Access Journals (Sweden)

    Juan J. Fernández-Romero

    Full Text Available Abstract The aim of this study was two-fold. The first aim was to determine if there were any anthropometric and physical performance differences (controlling for maturation between male and female handball players selected in training categories as well asthe relation of these differences with the performance level achieved. The second aim was to identify the discriminatory variables between the performance levels achieved. A total of 216 young handball players (125 men and 91 women participated in the study. The data were classified by selection level (regional n=154; national n=62, gender (men; women and age category (under-15; under-17. The use of MANCOVA analyses, controllingfor maturation, identified how gender could determine variables related to handball players' future competitive levels. The results revealed that anthropometric variables such as height, arm span, trochanter height, thigh girth, and leg girth were more influential in men than in women. In addition, the physical performance tests of vertical jump (squat jump and counter movement jump with/without arm and 10x5m shuttle run were determinants in both sexes. Discriminatory analysis predicted that a combination of five variables (counter movement jump with arm, body mass, 10x5m shuttle run, dominant hand length and trochanter height would successfully distinguish between regional and national players, with a predictive accuracy of 81.9% for all players.

  8. The Chaotic Prediction for Aero-Engine Performance Parameters Based on Nonlinear PLS Regression

    Directory of Open Access Journals (Sweden)

    Chunxiao Zhang

    2012-01-01

    Full Text Available The prediction of the aero-engine performance parameters is very important for aero-engine condition monitoring and fault diagnosis. In this paper, the chaotic phase space of engine exhaust temperature (EGT time series which come from actual air-borne ACARS data is reconstructed through selecting some suitable nearby points. The partial least square (PLS based on the cubic spline function or the kernel function transformation is adopted to obtain chaotic predictive function of EGT series. The experiment results indicate that the proposed PLS chaotic prediction algorithm based on biweight kernel function transformation has significant advantage in overcoming multicollinearity of the independent variables and solve the stability of regression model. Our predictive NMSE is 16.5 percent less than that of the traditional linear least squares (OLS method and 10.38 percent less than that of the linear PLS approach. At the same time, the forecast error is less than that of nonlinear PLS algorithm through bootstrap test screening.

  9. Improved Performance and Safety for High Energy Batteries Through Use of Hazard Anticipation and Capacity Prediction

    Science.gov (United States)

    Atwater, Terrill

    1993-01-01

    Prediction of the capacity remaining in used high rate, high energy batteries is important information to the user. Knowledge of the capacity remaining in used batteries results in better utilization. This translates into improved readiness and cost savings due to complete, efficient use. High rate batteries, due to their chemical nature, are highly sensitive to misuse (i.e., over discharge or very high rate discharge). Battery failure due to misuse or manufacturing defects could be disastrous. Since high rate, high energy batteries are expensive and energetic, a reliable method of predicting both failures and remaining energy has been actively sought. Due to concerns over safety, the behavior of lithium/sulphur dioxide cells at different temperatures and current drains was examined. The main thrust of this effort was to determine failure conditions for incorporation in hazard anticipation circuitry. In addition, capacity prediction formulas have been developed from test data. A process that performs continuous, real-time hazard anticipation and capacity prediction was developed. The introduction of this process into microchip technology will enable the production of reliable, safe, and efficient high energy batteries.

  10. Remaining uncertainties in predicting long-term performance of nuclear waste glass from experiments

    International Nuclear Information System (INIS)

    Grambow, B.

    1994-01-01

    The current knowledge on the glass dissolution mechanism and the representation of glass dissolution concepts within overall repository performance assessment models are briefly summarized and uncertainties related to mechanism, radionuclide chemistry and parameters are discussed. Understanding of the major glass dissolution processes has been significantly increased in recent years. Long-term glass stability is related to the long-term maintenance of silica saturated conditions. The behavior of individual radionuclides in the presence of a dissolving glass has not been sufficiently and results do no yet allow meaningful predictions. Conserving long-term predictions of glass matrix dissolution as upper limit for radionuclide release can be made with sufficient confidence, however these estimations generally result in a situation where the barrier function of the glass is masked by the efficiency of the geologic barrier. Realistic long-term predictions may show that the borosilicate waste glass contributes to overall repository safety to a much larger extent than indicated by overconservatism. Today realistic predictions remain highly uncertain and much more research work is necessary. In particular, the long-term rate under silica saturated conditions needs to be understood and the behavior of individual radionuclides in the presence of a dissolving glass deserves more systematic investigations

  11. Text Comprehension Mediates Morphological Awareness, Syntactic Processing, and Working Memory in Predicting Chinese Written Composition Performance

    Science.gov (United States)

    Guan, Connie Qun; Ye, Feifei; Wagner, Richard K.; Meng, Wanjin; Leong, Che Kan

    2014-01-01

    The goal of the present study was to test opposing views about four issues concerning predictors of individual differences in Chinese written composition: (a) Whether morphological awareness, syntactic processing, and working memory represent distinct and measureable constructs in Chinese or are just manifestations of general language ability; (b) whether they are important predictors of Chinese written composition, and if so, the relative magnitudes and independence of their predictive relations; (c) whether observed predictive relations are mediated by text comprehension; and (d) whether these relations vary or are developmentally invariant across three years of writing development. Based on analyses of the performance of students in grades 4 (n = 246), 5 (n = 242) and 6 (n = 261), the results supported morphological awareness, syntactic processing, and working memory as distinct yet correlated abilities that made independent contributions to predicting Chinese written composition, with working memory as the strongest predictor. However, predictive relations were mediated by text comprehension. The final model accounted for approximately 75 percent of the variance in Chinese written composition. The results were largely developmentally invariant across the three grades from which participants were drawn. PMID:25530630

  12. Application of the aberration ring test (ARTEMIS) to determine lens quality and predict its lithographic performance

    Science.gov (United States)

    Moers, Marco H. P.; van der Laan, Hans; Zellenrath, Mark; de Boeij, Wim; Beaudry, Neil A.; Cummings, Kevin D.; van Zwol, Adriaan; Brecht, Arthur; Willekers, Rob

    2001-09-01

    ARTEMISTM (Aberration Ring Test Exposed at Multiple Illumination Settings) is a technique to determine in-situ, full-field, low and high order lens aberrations. In this paper we are analyzing the ARTEMISTM data of PAS5500/750TM DUV Step & Scan systems and its use as a lithographic prediction tool. ARTEMISTM is capable of determining Zernike coefficients up to Z25 with a 3(sigma) reproducibility range from 1.5 to 4.5 nm depending on the aberration type. 3D electric field simulations, that take the extended geometry of the phase shift feature into account, have been used for an improved treatment of the extraction of the spherical Zernike coefficients. Knowledge of the extracted Zernike coefficients allows an accurate prediction of the lithographic performance of the scanner system. This ability is demonstrated for a two bar pattern and an isolation pattern. The RMS difference between the ARTEMISTM-based lithographic prediction and the lithographic measurement is 2.5 nm for the two bar pattern and 3 nm for the isolation pattern. The 3(sigma) reproducibility of the prediction for the two bar pattern is 2.5 nm and 1 nm for the isolation pattern. This is better than the reproducibility of the lithographic measurements themselves.

  13. Performance Comparison Between Support Vector Regression and Artificial Neural Network for Prediction of Oil Palm Production

    Directory of Open Access Journals (Sweden)

    Mustakim Mustakim

    2016-02-01

    Full Text Available The largest region that produces oil palm in Indonesia has an important role in improving the welfare of society and economy. Oil palm has increased significantly in Riau Province in every period, to determine the production development for the next few years with the functions and benefits of oil palm carried prediction production results that were seen from time series data last 8 years (2005-2013. In its prediction implementation, it was done by comparing the performance of Support Vector Regression (SVR method and Artificial Neural Network (ANN. From the experiment, SVR produced the best model compared with ANN. It is indicated by the correlation coefficient of 95% and 6% for MSE in the kernel Radial Basis Function (RBF, whereas ANN produced only 74% for R2 and 9% for MSE on the 8th experiment with hiden neuron 20 and learning rate 0,1. SVR model generates predictions for next 3 years which increased between 3% - 6% from actual data and RBF model predictions.

  14. Applying Machine Learning and High Performance Computing to Water Quality Assessment and Prediction

    Directory of Open Access Journals (Sweden)

    Ruijian Zhang

    2017-12-01

    Full Text Available Water quality assessment and prediction is a more and more important issue. Traditional ways either take lots of time or they can only do assessments. In this research, by applying machine learning algorithm to a long period time of water attributes’ data; we can generate a decision tree so that it can predict the future day’s water quality in an easy and efficient way. The idea is to combine the traditional ways and the computer algorithms together. Using machine learning algorithms, the assessment of water quality will be far more efficient, and by generating the decision tree, the prediction will be quite accurate. The drawback of the machine learning modeling is that the execution takes quite long time, especially when we employ a better accuracy but more time-consuming algorithm in clustering. Therefore, we applied the high performance computing (HPC System to deal with this problem. Up to now, the pilot experiments have achieved very promising preliminary results. The visualized water quality assessment and prediction obtained from this project would be published in an interactive website so that the public and the environmental managers could use the information for their decision making.

  15. FREC-4A: a computer program to predict fuel rod performance under normal reactor operation

    International Nuclear Information System (INIS)

    Harayama, Yasuo; Izumi, Fumio

    1981-10-01

    The program FREC-4A (Fuel Reliability Evaluation Code-version 4A) is used for predicting fuel rod performance in normal reactor operation. The performance is calculated in accordance with the irradiation history of fuel rods. Emphasis is placed on the prediction of the axial elongation of claddings induced by pellet-cladding mechanical interaction, including the influence of initially preloaded springs inserted in fuel rod lower plenums. In the FREC-4A, an fuel rod is divided into axial segments. In each segment, it is assumed that the temperature, stress and strain are axi-symmetrical, and the axial strain in constant in fuel pellets and in a cladding, though the values in the pellets and in the cladding are different. The calculation of the contact load and the clearance along the length of a fuel rod and the stress and strain in each segment is explained. The method adopted in the FREC-4A is simple, and suitable to predict the deformation of fuel rods over their full length. This report is described on the outline of the program, the method of solving the stiffness equations, the calculation models, the input data such as irradiation history, output distribution, material properties and pores, the printing-out of input data and calculated results. (Kako, I.)

  16. 10 km running performance predicted by a multiple linear regression model with allometrically adjusted variables.

    Science.gov (United States)

    Abad, Cesar C C; Barros, Ronaldo V; Bertuzzi, Romulo; Gagliardi, João F L; Lima-Silva, Adriano E; Lambert, Mike I; Pires, Flavio O

    2016-06-01

    The aim of this study was to verify the power of VO 2max , peak treadmill running velocity (PTV), and running economy (RE), unadjusted or allometrically adjusted, in predicting 10 km running performance. Eighteen male endurance runners performed: 1) an incremental test to exhaustion to determine VO 2max and PTV; 2) a constant submaximal run at 12 km·h -1 on an outdoor track for RE determination; and 3) a 10 km running race. Unadjusted (VO 2max , PTV and RE) and adjusted variables (VO 2max 0.72 , PTV 0.72 and RE 0.60 ) were investigated through independent multiple regression models to predict 10 km running race time. There were no significant correlations between 10 km running time and either the adjusted or unadjusted VO 2max . Significant correlations (p 0.84 and power > 0.88. The allometrically adjusted predictive model was composed of PTV 0.72 and RE 0.60 and explained 83% of the variance in 10 km running time with a standard error of the estimate (SEE) of 1.5 min. The unadjusted model composed of a single PVT accounted for 72% of the variance in 10 km running time (SEE of 1.9 min). Both regression models provided powerful estimates of 10 km running time; however, the unadjusted PTV may provide an uncomplicated estimation.

  17. Performance of a Predictive Model for Calculating Ascent Time to a Target Temperature

    Directory of Open Access Journals (Sweden)

    Jin Woo Moon

    2016-12-01

    Full Text Available The aim of this study was to develop an artificial neural network (ANN prediction model for controlling building heating systems. This model was used to calculate the ascent time of indoor temperature from the setback period (when a building was not occupied to a target setpoint temperature (when a building was occupied. The calculated ascent time was applied to determine the proper moment to start increasing the temperature from the setback temperature to reach the target temperature at an appropriate time. Three major steps were conducted: (1 model development; (2 model optimization; and (3 performance evaluation. Two software programs—Matrix Laboratory (MATLAB and Transient Systems Simulation (TRNSYS—were used for model development, performance tests, and numerical simulation methods. Correlation analysis between input variables and the output variable of the ANN model revealed that two input variables (current indoor air temperature and temperature difference from the target setpoint temperature, presented relatively strong relationships with the ascent time to the target setpoint temperature. These two variables were used as input neurons. Analyzing the difference between the simulated and predicted values from the ANN model provided the optimal number of hidden neurons (9, hidden layers (3, moment (0.9, and learning rate (0.9. At the study’s conclusion, the optimized model proved its prediction accuracy with acceptable errors.

  18. IAMBUS, a computer code for the design and performance prediction of fast breeder fuel rods

    International Nuclear Information System (INIS)

    Toebbe, H.

    1990-05-01

    IAMBUS is a computer code for the thermal and mechanical design, in-pile performance prediction and post-irradiation analysis of fast breeder fuel rods. The code deals with steady, non-steady and transient operating conditions and enables to predict in-pile behavior of fuel rods in power reactors as well as in experimental rigs. Great effort went into the development of a realistic account of non-steady fuel rod operating conditions. The main emphasis is placed on characterizing the mechanical interaction taking place between the cladding tube and the fuel as a result of contact pressure and friction forces, with due consideration of axial and radial crack configuration within the fuel as well as the gradual transition at the elastic/plastic interface in respect to fuel behavior. IAMBUS can be readily adapted to various fuel and cladding materials. The specific models and material correlations of the reference version deal with the actual in-pile behavior and physical properties of the KNK II and SNR 300 related fuel rod design, confirmed by comparison of the fuel performance model with post-irradiation data. The comparison comprises steady, non-steady and transient irradiation experiments within the German/Belgian fuel rod irradiation program. The code is further validated by comparison of model predictions with post-irradiation data of standard fuel and breeder rods of Phenix and PFR as well as selected LWR fuel rods in non-steady operating conditions

  19. ANALYSIS OF THE PREDICTIVE DMC CONTROLLER PERFORMANCE APPLIED TO A FEED-BATCH BIOREACTOR

    Directory of Open Access Journals (Sweden)

    J. A. D. RODRIGUES

    1997-12-01

    Full Text Available Two control algorithms were implemented in the stabilization of the dissolved oxygen concentration of the penicillin process production phase. A deterministic and nonstructured mathematical model was used, where were considered the balances of cell, substrate, dissolved oxygen and product formation as well as kinetic of the growth, respiration, product inhibition due to excess of substrate, penicillin hydrolyze, yield factors among cell growth, substrate consumption and dissolved oxygen consumption. The bioreactor was operated in a feed-batch way using an optimal strategy for the operational policy. The agitation speed was used as manipulated variable in order to achieve the dissolved oxygen control because it was found to be the most sensitive one. Two types of control configurations were implemented. First, the PID feedback control with the parameters estimated through Modified Simplex optimization method using the IAE index, and second, the DMC predictive control that had as control parameters the model, prediction and control horizons as well as suppression factor and the trajectory parameter. A sensitivity analysis of these two control algorithms was performed using the sample time and dead time as the index to make stability evaluation. Both configurations showed stable performance, however, the predictive one was found to be more robust in relation to the sample time, as well as the dead time variations. This is a very important characteristic to be considered for the implementation of control scheme in real fermentative process

  20. How the choice of safety performance function affects the identification of important crash prediction variables.

    Science.gov (United States)

    Wang, Ketong; Simandl, Jenna K; Porter, Michael D; Graettinger, Andrew J; Smith, Randy K

    2016-03-01

    Across the nation, researchers and transportation engineers are developing safety performance functions (SPFs) to predict crash rates and develop crash modification factors to improve traffic safety at roadway segments and intersections. Generalized linear models (GLMs), such as Poisson or negative binomial regression, are most commonly used to develop SPFs with annual average daily traffic as the primary roadway characteristic to predict crashes. However, while more complex to interpret, data mining models such as boosted regression trees have improved upon GLMs crash prediction performance due to their ability to handle more data characteristics, accommodate non-linearities, and include interaction effects between the characteristics. An intersection data inventory of 36 safety relevant parameters for three- and four-legged non-signalized intersections along state routes in Alabama was used to study the importance of intersection characteristics on crash rate and the interaction effects between key characteristics. Four different SPFs were investigated and compared: Poisson regression, negative binomial regression, regularized generalized linear model, and boosted regression trees. The models did not agree on which intersection characteristics were most related to the crash rate. The boosted regression tree model significantly outperformed the other models and identified several intersection characteristics as having strong interaction effects. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Prediction of Polymer Flooding Performance with an Artificial Neural Network: A Two-Polymer-Slug Case

    Directory of Open Access Journals (Sweden)

    Jestril Ebaga-Ololo

    2017-07-01

    Full Text Available Many previous contributions to methods of forecasting the performance of polymer flooding using artificial neural networks (ANNs have been made by numerous researchers previously. In most of those forecasting cases, only a single polymer slug was employed to meet the objective of the study. The intent of this manuscript is to propose an efficient recovery factor prediction tool at different injection stages of two polymer slugs during polymer flooding using an ANN. In this regard, a back-propagation algorithm was coupled with six input parameters to predict three output parameters via a hidden layer composed of 10 neurons. Evaluation of the ANN model performance was made with multiple linear regression. With an acceptable correlation coefficient, the proposed ANN tool was able to predict the recovery factor with errors of <1%. In addition, to understand the influence of each parameter on the output parameters, a sensitivity analysis was applied to the input parameters. The results showed less impact from the second polymer concentration, owing to changes in permeability after the injection of the first polymer slug.

  2. Predicting the seismic performance of typical R/C healthcare facilities: emphasis on hospitals

    Science.gov (United States)

    Bilgin, Huseyin; Frangu, Idlir

    2017-09-01

    Reinforced concrete (RC) type of buildings constitutes an important part of the current building stock in earthquake prone countries such as Albania. Seismic response of structures during a severe earthquake plays a vital role in the extent of structural damage and resulting injuries and losses. In this context, this study evaluates the expected performance of a five-story RC healthcare facility, representative of common practice in Albania, designed according to older codes. The design was based on the code requirements used in this region during the mid-1980s. Non-linear static and dynamic time history analyses were conducted on the structural model using the Zeus NL computer program. The dynamic time history analysis was conducted with a set of ground motions from real earthquakes. The building responses were estimated in global levels. FEMA 356 criteria were used to predict the seismic performance of the building. The structural response measures such as capacity curve and inter-story drift under the set of ground motions and pushover analyses results were compared and detailed seismic performance assessment was done. The main aim of this study is considering the application and methodology for the earthquake performance assessment of existing buildings. The seismic performance of the structural model varied significantly under different ground motions. Results indicate that case study building exhibit inadequate seismic performance under different seismic excitations. In addition, reasons for the poor performance of the building is discussed.

  3. Does Tacit Knowledge Predict Organizational Performance? A Scrutiny of Firms in the Upstream Sector in Nigeria

    Directory of Open Access Journals (Sweden)

    Vincent I.O Odiri

    2016-02-01

    Full Text Available This paper examined tacit knowledge so as to see whether tacit knowledge when properly put to use can lead to improved performance by upstream sector firms in Nigeria. Knowledge as we believe, is very vital to both corporate entities and individuals. Knowledge encompasses both explicit and tacit. This paper focused on one aspect of knowledge – ‘tacit’ which is in the psyche or brain of the individual possessing it. Inspite of the central role it plays, tacit knowledge has been downplayed by most firms. However, we adopted a survey research design via questionnaires administered to 504 employees randomly selected from 3 different oil firms. The data obtained were analyzed using inferential statistics. Also, multi-collinearity diagnoses of tacit knowledge and organizational performance was performed. The result suggests that tacit knowledge is linearly correlated with organizational performance. This implies that tacit knowledge predicts organizational performance. This study is significant in that the findings would be useful to management of firms, as it divulge how tacit knowledge when properly harnessed can lead to increased performance. Most prior studies in this area were conducted in other countries, hence our study is one of the first in Nigeria that examined tacit knowledge and organizational performance.

  4. The dark and bright sides of self-efficacy in predicting learning, innovative and risky performances.

    Science.gov (United States)

    Salanova, Marisa; Lorente, Laura; Martínez, Isabel M

    2012-11-01

    The objective of this study is to analyze the different role that efficacy beliefs play in the prediction of learning, innovative and risky performances. We hypothesize that high levels of efficacy beliefs in learning and innovative performances have positive consequences (i.e., better academic and innovative performance, respectively), whereas in risky performances they have negative consequences (i.e., less safety performance). To achieve this objective, three studies were conducted, 1) a two-wave longitudinal field study among 527 undergraduate students (learning setting), 2) a three-wave longitudinal lab study among 165 participants performing innovative group tasks (innovative setting), and 3) a field study among 228 construction workers (risky setting). As expected, high levels of efficacy beliefs have positive or negative consequences on performance depending on the specific settings. Unexpectedly, however, we found no time x self-efficacy interaction effect over time in learning and innovative settings. Theoretical and practical implications within the social cognitive theory of A. Bandura framework are discussed.

  5. Balancing Model Performance and Simplicity to Predict Postoperative Primary Care Blood Pressure Elevation.

    Science.gov (United States)

    Schonberger, Robert B; Dai, Feng; Brandt, Cynthia A; Burg, Matthew M

    2015-09-01

    Because of uncertainty regarding the reliability of perioperative blood pressures and traditional notions downplaying the role of anesthesiologists in longitudinal patient care, there is no consensus for anesthesiologists to recommend postoperative primary care blood pressure follow-up for patients presenting for surgery with an increased blood pressure. The decision of whom to refer should ideally be based on a predictive model that balances performance with ease-of-use. If an acceptable decision rule was developed, a new practice paradigm integrating the surgical encounter into broader public health efforts could be tested, with the goal of reducing long-term morbidity from hypertension among surgical patients. Using national data from US veterans receiving surgical care, we determined the prevalence of poorly controlled outpatient clinic blood pressures ≥140/90 mm Hg, based on the mean of up to 4 readings in the year after surgery. Four increasingly complex logistic regression models were assessed to predict this outcome. The first included the mean of 2 preoperative blood pressure readings; other models progressively added a broad array of demographic and clinical data. After internal validation, the C-statistics and the Net Reclassification Index between the simplest and most complex models were assessed. The performance characteristics of several simple blood pressure referral thresholds were then calculated. Among 215,621 patients, poorly controlled outpatient clinic blood pressure was present postoperatively in 25.7% (95% confidence interval [CI], 25.5%-25.9%) including 14.2% (95% CI, 13.9%-14.6%) of patients lacking a hypertension history. The most complex prediction model demonstrated statistically significant, but clinically marginal, improvement in discrimination over a model based on preoperative blood pressure alone (C-statistic, 0.736 [95% CI, 0.734-0.739] vs 0.721 [95% CI, 0.718-0.723]; P for difference 1 of 4 patients (95% CI, 25

  6. Do physiological measures predict selected CrossFit® benchmark performance?

    Science.gov (United States)

    Butcher, Scotty J; Neyedly, Tyler J; Horvey, Karla J; Benko, Chad R

    2015-01-01

    Purpose CrossFit® is a new but extremely popular method of exercise training and competition that involves constantly varied functional movements performed at high intensity. Despite the popularity of this training method, the physiological determinants of CrossFit performance have not yet been reported. The purpose of this study was to determine whether physiological and/or muscle strength measures could predict performance on three common CrossFit “Workouts of the Day” (WODs). Materials and methods Fourteen CrossFit Open or Regional athletes completed, on separate days, the WODs “Grace” (30 clean and jerks for time), “Fran” (three rounds of thrusters and pull-ups for 21, 15, and nine repetitions), and “Cindy” (20 minutes of rounds of five pull-ups, ten push-ups, and 15 bodyweight squats), as well as the “CrossFit Total” (1 repetition max [1RM] back squat, overhead press, and deadlift), maximal oxygen consumption (VO2max), and Wingate anaerobic power/capacity testing. Results Performance of Grace and Fran was related to whole-body strength (CrossFit Total) (r=−0.88 and −0.65, respectively) and anaerobic threshold (r=−0.61 and −0.53, respectively); however, whole-body strength was the only variable to survive the prediction regression for both of these WODs (R2=0.77 and 0.42, respectively). There were no significant associations or predictors for Cindy. Conclusion CrossFit benchmark WOD performance cannot be predicted by VO2max, Wingate power/capacity, or either respiratory compensation or anaerobic thresholds. Of the data measured, only whole-body strength can partially explain performance on Grace and Fran, although anaerobic threshold also exhibited association with performance. Along with their typical training, CrossFit athletes should likely ensure an adequate level of strength and aerobic endurance to optimize performance on at least some benchmark WODs. PMID:26261428

  7. Do physiological measures predict selected CrossFit® benchmark performance?

    Directory of Open Access Journals (Sweden)

    Butcher SJ

    2015-07-01

    Full Text Available Scotty J Butcher,1,2 Tyler J Neyedly,3 Karla J Horvey,1 Chad R Benko2,41Physical Therapy, University of Saskatchewan, 2BOSS Strength Institute, 3Physiology, University of Saskatchewan, 4Synergy Strength and Conditioning, Saskatoon, SK, CanadaPurpose: CrossFit® is a new but extremely popular method of exercise training and competition that involves constantly varied functional movements performed at high intensity. Despite the popularity of this training method, the physiological determinants of CrossFit performance have not yet been reported. The purpose of this study was to determine whether physiological and/or muscle strength measures could predict performance on three common CrossFit "Workouts of the Day" (WODs.Materials and methods: Fourteen CrossFit Open or Regional athletes completed, on separate days, the WODs "Grace" (30 clean and jerks for time, "Fran" (three rounds of thrusters and pull-ups for 21, 15, and nine repetitions, and "Cindy" (20 minutes of rounds of five pull-ups, ten push-ups, and 15 bodyweight squats, as well as the "CrossFit Total" (1 repetition max [1RM] back squat, overhead press, and deadlift, maximal oxygen consumption (VO2max, and Wingate anaerobic power/capacity testing.Results: Performance of Grace and Fran was related to whole-body strength (CrossFit Total (r=-0.88 and -0.65, respectively and anaerobic threshold (r=-0.61 and -0.53, respectively; however, whole-body strength was the only variable to survive the prediction regression for both of these WODs (R2=0.77 and 0.42, respectively. There were no significant associations or predictors for Cindy.Conclusion: CrossFit benchmark WOD performance cannot be predicted by VO2max, Wingate power/capacity, or either respiratory compensation or anaerobic thresholds. Of the data measured, only whole-body strength can partially explain performance on Grace and Fran, although anaerobic threshold also exhibited association with performance. Along with their typical training

  8. Cognitive function predicts listening effort performance during complex tasks in normally aging adults

    Directory of Open Access Journals (Sweden)

    Jennine Harvey

    2017-01-01

    Full Text Available Purpose: This study examines whether cognitive function, as measured by the subtests of the Woodcock–Johnson III (WCJ-III assessment, predicts listening-effort performance during dual tasks across the adults of varying ages. Materials and Methods: Participants were divided into two groups. Group 1 consisted of 14 listeners (number of females = 11 who were 41–61 years old [mean = 53.18; standard deviation (SD = 5.97]. Group 2 consisted of 15 listeners (number of females = 9 who were 63–81 years old (mean = 72.07; SD = 5.11. Participants were administered the WCJ-III Memory for Words, Auditory Working Memory, Visual Matching, and Decision Speed subtests. All participants were tested in each of the following three dual-task experimental conditions, which were varying in complexity: (1 auditory word recognition + visual processing, (2 auditory working memory (word + visual processing, and (3 auditory working memory (sentence + visual processing in noise. Results: A repeated measures analysis of variance revealed that task complexity significantly affected the performance measures of auditory accuracy, visual accuracy, and processing speed. Linear regression revealed that the cognitive subtests of the WCJ-III test significantly predicted performance across dependent variable measures. Conclusion: Listening effort is significantly affected by task complexity, regardless of age. Performance on the WCJ-III test may predict listening effort in adults and may assist speech-language pathologist (SLPs to understand challenges faced by participants when subjected to noise.

  9. Prediction of a photovoltaic system performance using cumulative frequency curves of radiation

    Energy Technology Data Exchange (ETDEWEB)

    Lasnier, F; Sivoththaman, S [Asian Inst. of Technology, Bangkok (TH). Div. of Energy Technology

    1990-01-01

    The system performance of stand-alone photovoltaic systems is analysed. From the hourly radiation data for Bangkok (from 1984 to 1987) the cumulative frequency curves of radiation are generated and a typical meteorological day (TMD) is created each year. The system performance is determined using both the TMD radiation and the actual radiation values. The comparison results show that the TMD method can be applied for the sizing of stand-alone photovoltaic systems. The storage batteries of realistic sizes usually exhibit a daily cyclic variation in state-of-charge, with constant load consumption. Only very large and unrealistic sizes of batteries show a seasonal variation in state-of-charge. This is the fact that prompted the attempt to predict the system performance for a season by using a single representative day (TMD) of that season. Apart from giving reliable results, the TMD method significantly reduces the computation time and simplifies the process. (author).

  10. Reservoir characterization and performance predictions for the E.N. Woods lease

    Energy Technology Data Exchange (ETDEWEB)

    Aka-Milan, Francis A.

    2000-07-07

    The task of this work was to evaluate the past performance of the E.N. WOODS Unit and to forecast its future economic performance by taking into consideration the geology, petrophysics and production history of the reservoir. The Decline Curve Analysis feature of the Appraisal of Petroleum Properties including Taxation Systems (EDAPT) software along with the Production Management Systems (PMS) software were used to evaluate the original volume of hydrocarbon in place and estimate the reserve. The Black Oil Simulator (BOAST II) was then used to model the waterflooding operation and estimate the incremental oil production attributable to the water injection. BOAST II was also used to predict future performance of the reservoir.

  11. Exploring the motivation jungle: Predicting performance on a novel task by investigating constructs from different motivation perspectives in tandem

    NARCIS (Netherlands)

    Nuland, H.J.C. van; Dusseldorp, E.; Martens, R.L.; Boekaerts, M.

    2010-01-01

    Different theoretical viewpoints on motivation make it hard to decide which model has the best potential to provide valid predictions on classroom performance. This study was designed to explore motivation constructs derived from different motivation perspectives that predict performance on a novel

  12. Performance assessment of turbulence models for the prediction of moderator thermal flow inside CANDU calandria

    International Nuclear Information System (INIS)

    Lee, Gong Hee; Bang, Young Seok; Woo, Sweng Woong

    2012-01-01

    The moderator thermal flow in the CANDU calandria is generally complex and highly turbulent because of the interaction of the buoyancy force with the inlet jet inertia. In this study, the prediction performance of turbulence models for the accurate analysis of the moderator thermal flow are assessed by comparing the results calculated with various types of turbulence models in the commercial flow solver FLUENT with experimental data for the test vessel at Sheridan Park Engineering Laboratory (SPEL). Through this comparative study of turbulence models, it is concluded that turbulence models that include the source term to consider the effects of buoyancy on the turbulent flow should be used for the reliable prediction of the moderator thermal flow inside the CANDU calandria

  13. Reliability residual-life prediction method for thermal aging based on performance degradation

    International Nuclear Information System (INIS)

    Ren Shuhong; Xue Fei; Yu Weiwei; Ti Wenxin; Liu Xiaotian

    2013-01-01

    The paper makes the study of the nuclear power plant main pipeline. The residual-life of the main pipeline that failed due to thermal aging has been studied by the use of performance degradation theory and Bayesian updating methods. Firstly, the thermal aging impact property degradation process of the main pipeline austenitic stainless steel has been analyzed by the accelerated thermal aging test data. Then, the thermal aging residual-life prediction model based on the impact property degradation data is built by Bayesian updating methods. Finally, these models are applied in practical situations. It is shown that the proposed methods are feasible and the prediction accuracy meets the needs of the project. Also, it provides a foundation for the scientific management of aging management of the main pipeline. (authors)

  14. Dynamic Model of Centrifugal Compressor for Prediction of Surge Evolution and Performance Variations

    International Nuclear Information System (INIS)

    Jung, Mooncheong; Han, Jaeyoung; Yu, Sangseok

    2016-01-01

    When a control algorithm is developed to protect automotive compressor surges, the simulation model typically selects an empirically determined look-up table. However, it is difficult for a control oriented empirical model to show surge characteristics of the super charger. In this study, a dynamic supercharger model is developed to predict the performance of a centrifugal compressor under dynamic load follow-up. The model is developed using Simulink® environment, and is composed of a compressor, throttle body, valves, and chamber. Greitzer’s compressor model is used, and the geometric parameters are achieved by the actual supercharger. The simulation model is validated with experimental data. It is shown that compressor surge is effectively predicted by this dynamic compressor model under various operating conditions.

  15. Dynamic Model of Centrifugal Compressor for Prediction of Surge Evolution and Performance Variations

    Energy Technology Data Exchange (ETDEWEB)

    Jung, Mooncheong; Han, Jaeyoung; Yu, Sangseok [Chungnam National Univ., Daejeon (Korea, Republic of)

    2016-05-15

    When a control algorithm is developed to protect automotive compressor surges, the simulation model typically selects an empirically determined look-up table. However, it is difficult for a control oriented empirical model to show surge characteristics of the super charger. In this study, a dynamic supercharger model is developed to predict the performance of a centrifugal compressor under dynamic load follow-up. The model is developed using Simulink® environment, and is composed of a compressor, throttle body, valves, and chamber. Greitzer’s compressor model is used, and the geometric parameters are achieved by the actual supercharger. The simulation model is validated with experimental data. It is shown that compressor surge is effectively predicted by this dynamic compressor model under various operating conditions.

  16. Analytical predictions for the performance of a reinforced concrete containment model subject to overpressurization

    International Nuclear Information System (INIS)

    Weatherby, J.R.; Clauss, D.B.

    1987-01-01

    Under the sponsorship of the US Nuclear Regulatory Commission, Sandia National Laboratories is investigating methods for predicting the structural performance of nuclear reactor containment buildings under hypothesized severe accident conditions. As part of this program, a 1/6th-scale reinforced concrete containment model will be pressurized to failure in early 1987. Data generated by the test will be compared to analytical predictions of the structural response in order to assess the accuracy and reliability of the analytical techniques. As part of the pretest analysis effort, Sandia has conducted a number of analyses of the containment structure using the ABAQUS general purpose finite element code. This paper describes results from a nonlinear axisymmetric shell analysis as well as the material models and failure criteria used in conjunction with the analysis

  17. Identification of New Tools to Predict Surgical Performance of Novices using a Plastic Surgery Simulator.

    Science.gov (United States)

    Kazan, Roy; Viezel-Mathieu, Alex; Cyr, Shantale; Hemmerling, Thomas M; Lin, Samuel J; Gilardino, Mirko S

    2018-04-09

    To identify new tools capable of predicting surgical performance of novices on an augmentation mammoplasty simulator. The pace of technical skills acquisition varies between residents and may necessitate more time than that allotted by residency training before reaching competence. Identifying applicants with superior innate technical abilities might shorten learning curves and the time to reach competence. The objective of this study is to identify new tools that could predict surgical performance of novices on a mammoplasty simulator. We recruited 14 medical students and recorded their performance in 2 skill-games: Mikado and Perplexus Epic, and in 2 video games: Star War Racer (Sony Playstation 3) and Super Monkey Ball 2 (Nintendo Wii). Then, each participant performed an augmentation mammoplasty procedure on a Mammoplasty Part-task Trainer, which allows the simulation of the essential steps of the procedure. The average age of participants was 25.4 years. Correlation studies showed significant association between Perplexus Epic, Star Wars Racer, Super Monkey Ball scores and the modified OSATS score with r s = 0.8491 (p 41 (p = 0.005), and r s = 0.7309 (p < 0.003), but not with the Mikado score r s = -0.0255 (p = 0.9). Linear regressions were strongest for Perplexus Epic and Super Monkey Ball scores with coefficients of determination of 0.59 and 0.55, respectively. A combined score (Perplexus/Super-Monkey-Ball) was computed and showed a significant correlation with the modified OSATS score having an r s = 0.8107 (p < 0.001) and R 2 = 0.75, respectively. This study identified a combination of skill games that correlated to better performance of novices on a surgical simulator. With refinement, such tools could serve to help screen plastic surgery applicants and identify those with higher surgical performance predictors. Copyright © 2018 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

  18. Comparing observed and predicted mortality among ICUs using different prognostic systems: why do performance assessments differ?

    Science.gov (United States)

    Kramer, Andrew A; Higgins, Thomas L; Zimmerman, Jack E

    2015-02-01

    To compare ICU performance using standardized mortality ratios generated by the Acute Physiology and Chronic Health Evaluation IVa and a National Quality Forum-endorsed methodology and examine potential reasons for model-based standardized mortality ratio differences. Retrospective analysis of day 1 hospital mortality predictions at the ICU level using Acute Physiology and Chronic Health Evaluation IVa and National Quality Forum models on the same patient cohort. Forty-seven ICUs at 36 U.S. hospitals from January 2008 to May 2013. Eighty-nine thousand three hundred fifty-three consecutive unselected ICU admissions. None. We assessed standardized mortality ratios for each ICU using data for patients eligible for Acute Physiology and Chronic Health Evaluation IVa and National Quality Forum predictions in order to compare unit-level model performance, differences in ICU rankings, and how case-mix adjustment might explain standardized mortality ratio differences. Hospital mortality was 11.5%. Overall standardized mortality ratio was 0.89 using Acute Physiology and Chronic Health Evaluation IVa and 1.07 using National Quality Forum, the latter having a widely dispersed and multimodal standardized mortality ratio distribution. Model exclusion criteria eliminated mortality predictions for 10.6% of patients for Acute Physiology and Chronic Health Evaluation IVa and 27.9% for National Quality Forum. The two models agreed on the significance and direction of standardized mortality ratio only 45% of the time. Four ICUs had standardized mortality ratios significantly less than 1.0 using Acute Physiology and Chronic Health Evaluation IVa, but significantly greater than 1.0 using National Quality Forum. Two ICUs had standardized mortality ratios exceeding 1.75 using National Quality Forum, but nonsignificant performance using Acute Physiology and Chronic Health Evaluation IVa. Stratification by patient and institutional characteristics indicated that units caring for more

  19. Development of a modified equilibrium model for biomass pilot-scale fluidized bed gasifier performance predictions

    International Nuclear Information System (INIS)

    Rodriguez-Alejandro, David A.; Nam, Hyungseok; Maglinao, Amado L.; Capareda, Sergio C.; Aguilera-Alvarado, Alberto F.

    2016-01-01

    The objective of this work is to develop a thermodynamic model considering non-stoichiometric restrictions. The model validation was done from experimental works using a bench-scale fluidized bed gasifier with wood chips, dairy manure, and sorghum. The model was used for a further parametric study to predict the performance of a pilot-scale fluidized biomass gasifier. The Gibbs free energy minimization was applied to the modified equilibrium model considering a heat loss to the surroundings, carbon efficiency, and two non-equilibrium factors based on empirical correlations of ER and gasification temperature. The model was in a good agreement with RMS <4 for the produced gas. The parametric study ranges were 0.01 < ER < 0.99 and 500 °C < T < 900 °C to predict syngas concentrations and its LHV (lower heating value) for the optimization. Higher aromatics in tar were contained in WC gasification compared to manure gasification. A wood gasification tar simulation was produced to predict the amount of tars at specific conditions. The operating conditions for the highest quality syngas were reconciled experimentally with three biomass wastes using a fluidized bed gasifier. The thermodynamic model was used to predict the gasification performance at conditions beyond the actual operation. - Highlights: • Syngas from experimental gasification was used to create a non-equilibrium model. • Different types of biomass (HTS, DM, and WC) were used for gasification modelling. • Different tar compositions were identified with a simulation of tar yields. • The optimum operating conditions were found through the developed model.

  20. Acute Myocardial Infarction Readmission Risk Prediction Models: A Systematic Review of Model Performance.

    Science.gov (United States)

    Smith, Lauren N; Makam, Anil N; Darden, Douglas; Mayo, Helen; Das, Sandeep R; Halm, Ethan A; Nguyen, Oanh Kieu

    2018-01-01

    Hospitals are subject to federal financial penalties for excessive 30-day hospital readmissions for acute myocardial infarction (AMI). Prospectively identifying patients hospitalized with AMI at high risk for readmission could help prevent 30-day readmissions by enabling targeted interventions. However, the performance of AMI-specific readmission risk prediction models is unknown. We systematically searched the published literature through March 2017 for studies of risk prediction models for 30-day hospital readmission among adults with AMI. We identified 11 studies of 18 unique risk prediction models across diverse settings primarily in the United States, of which 16 models were specific to AMI. The median overall observed all-cause 30-day readmission rate across studies was 16.3% (range, 10.6%-21.0%). Six models were based on administrative data; 4 on electronic health record data; 3 on clinical hospital data; and 5 on cardiac registry data. Models included 7 to 37 predictors, of which demographics, comorbidities, and utilization metrics were the most frequently included domains. Most models, including the Centers for Medicare and Medicaid Services AMI administrative model, had modest discrimination (median C statistic, 0.65; range, 0.53-0.79). Of the 16 reported AMI-specific models, only 8 models were assessed in a validation cohort, limiting generalizability. Observed risk-stratified readmission rates ranged from 3.0% among the lowest-risk individuals to 43.0% among the highest-risk individuals, suggesting good risk stratification across all models. Current AMI-specific readmission risk prediction models have modest predictive ability and uncertain generalizability given methodological limitations. No existing models provide actionable information in real time to enable early identification and risk-stratification of patients with AMI before hospital discharge, a functionality needed to optimize the potential effectiveness of readmission reduction interventions

  1. How job demands, resources, and burnout predict objective performance: a constructive replication.

    Science.gov (United States)

    Bakker, Arnold B; Van Emmerik, Hetty; Van Riet, Pim

    2008-07-01

    The present study uses the Job Demands-Resources model (Bakker & Demerouti, 2007) to examine how job characteristics and burnout (exhaustion and cynicism) contribute to explaining variance in objective team performance. A central assumption in the model is that working characteristics evoke two psychologically different processes. In the first process, job demands lead to constant psychological overtaxing and in the long run to exhaustion. In the second process, a lack of job resources precludes actual goal accomplishment, leading to cynicism. In the present study these two processes were used to predict objective team performance. A total of 176 employees from a temporary employment agency completed questionnaires on job characteristics and burnout. These self-reports were linked to information from the company's management information system about teams' (N=71) objective sales performance (actual sales divided by the stated objectives) during the 3 months after the questionnaire data collection period. The results of structural equation modeling analyses did not support the hypothesis that exhaustion mediates the relationship between job demands and performance, but confirmed that cynicism mediates the relationship between job resources and performance suggesting that work conditions influence performance particularly through the attitudinal component of burnout.

  2. Does a selection interview predict year 1 performance in dental school?

    Science.gov (United States)

    McAndrew, R; Ellis, J; Valentine, R A

    2017-05-01

    It is important for dental schools to select students who will complete their degree and progress on to become the dentists of the future. The process should be transparent, fair and ethical and utilise selection tools that select appropriate students. The interview is an integral part of UK dental schools student selection procedures. This study was undertaken in order to determine whether different interview methods (Cardiff with a multiple mini interview and Newcastle with a more traditional interview process) along with other components used in selection predicted academic performance in students. The admissions selection data for two dental schools (Cardiff and Newcastle) were collected and analysed alongside student performance in academic examinations in Year 1 of the respective schools. Correlation statistics were used to determine whether selection tools had any relevance to academic performance once students were admitted to their respective Universities. Data was available for a total of 177 students (77 Cardiff and 100 Newcastle). Examination performance did not correlate with admission interview scores at either school; however UKCAT score was linked to poor academic performance. Although interview methodology does not appear to correlate with academic performance it remains an integral and very necessary part of the admissions process. Ultimately schools need to be comfortable with their admissions procedures in attracting and selecting the calibre of students they desire. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  3. A Compact Methodology to Understand, Evaluate, and Predict the Performance of Automatic Target Recognition

    Science.gov (United States)

    Li, Yanpeng; Li, Xiang; Wang, Hongqiang; Chen, Yiping; Zhuang, Zhaowen; Cheng, Yongqiang; Deng, Bin; Wang, Liandong; Zeng, Yonghu; Gao, Lei

    2014-01-01

    This paper offers a compacted mechanism to carry out the performance evaluation work for an automatic target recognition (ATR) system: (a) a standard description of the ATR system's output is suggested, a quantity to indicate the operating condition is presented based on the principle of feature extraction in pattern recognition, and a series of indexes to assess the output in different aspects are developed with the application of statistics; (b) performance of the ATR system is interpreted by a quality factor based on knowledge of engineering mathematics; (c) through a novel utility called “context-probability” estimation proposed based on probability, performance prediction for an ATR system is realized. The simulation result shows that the performance of an ATR system can be accounted for and forecasted by the above-mentioned measures. Compared to existing technologies, the novel method can offer more objective performance conclusions for an ATR system. These conclusions may be helpful in knowing the practical capability of the tested ATR system. At the same time, the generalization performance of the proposed method is good. PMID:24967605

  4. Dimensionless Numerical Approaches for the Performance Prediction of Marine Waterjet Propulsion Units

    Directory of Open Access Journals (Sweden)

    Marco Altosole

    2012-01-01

    Full Text Available One of the key issues at early design stage of a high-speed craft is the selection and the performance prediction of the propulsion system because at this stage only few information about the vessel are available. The objective of this work is precisely to provide the designer, in the case of waterjet propelled craft, with a simple and reliable calculation tool, able to predict the waterjet working points in design and off-design conditions, allowing to investigate several propulsive options during the ship design process. In the paper two original dimensionless numerical procedures, one referred to jet units for naval applications and the other more suitable for planing boats, are presented. The first procedure is based on a generalized performance map for mixed flow pumps, derived from the analysis of several waterjet pumps by applying similitude principles of the hydraulic machines. The second approach, validated by some comparisons with current waterjet installations, is based on a complete physical approach, from which a set of non-dimensional waterjet characteristics has been drawn by the authors. The presented application examples show the validity and the degree of accuracy of the proposed methodologies for the performance evaluation of waterjet propulsion systems.

  5. The Metabolic Syndrome Predicts Longitudinal Changes in Clock Drawing Test Performance in Older Nondemented Hypertensive Individuals.

    Science.gov (United States)

    Viscogliosi, Giovanni; Chiriac, Iulia Maria; Andreozzi, Paola; Ettorre, Evaristo

    2016-05-01

    The present study evaluated the metabolic syndrome (MetS) as independent predictor of 1-year longitudinal changes in cognitive function. 104 stroke- and dementia-free older hypertensive subjects were studied. MetS was defined by NCEP ATP-III criteria. Cognitive function was assessed by the Clock Drawing Test (CDT); 1-year changes in cognitive function were expressed as annual changes in CDT performance. Brain magnetic resonance imaging studies (1.5T) were performed. Participants with MetS exhibited greater cognitive decline than those without (-1.78 ± 1.47 versus -0.74 ± 1.44 CDT points, t = 3.348, df = 102, p < 0.001). MetS predicted cognitive decline (β = -0.327, t = -3.059, df = 96, p = 0.003) independently of its components, age, baseline cognition, neuroimaging findings, blood pressure levels, and duration of hypertension. With the exception of systolic blood pressure, none of the individual components of MetS explained 1-year changes in CDT performance. MetS as an entity predicted accelerated 1-year decline in cognitive function, assessed by CDT, in a sample of older hypertensive subjects. Copyright © 2016 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

  6. Performance prediction of mechanical excavators from linear cutter tests on Yucca Mountain welded tuffs

    International Nuclear Information System (INIS)

    Gertsch, R.; Ozdemir, L.

    1992-09-01

    The performances of mechanical excavators are predicted for excavations in welded tuff. Emphasis is given to tunnel boring machine evaluations based on linear cutting machine test data obtained on samples of Topopah Spring welded tuff. The tests involve measurement of forces as cutters are applied to the rock surface at certain spacing and penetrations. Two disc and two point-attack cutters representing currently available technology are thus evaluated. The performance predictions based on these direct experimental measurements are believed to be more accurate than any previous values for mechanical excavation of welded tuff. The calculations of performance are predicated on minimizing the amount of energy required to excavate the welded tuff. Specific energy decreases with increasing spacing and penetration, and reaches its lowest at the widest spacing and deepest penetration used in this test program. Using the force, spacing, and penetration data from this experimental program, the thrust, torque, power, and rate of penetration are calculated for several types of mechanical excavators. The results of this study show that the candidate excavators will require higher torque and power than heretofore estimated

  7. Validation of a simple method for predicting the disinfection performance in a flow-through contactor.

    Science.gov (United States)

    Pfeiffer, Valentin; Barbeau, Benoit

    2014-02-01

    Despite its shortcomings, the T10 method introduced by the United States Environmental Protection Agency (USEPA) in 1989 is currently the method most frequently used in North America to calculate disinfection performance. Other methods (e.g., the Integrated Disinfection Design Framework, IDDF) have been advanced as replacements, and more recently, the USEPA suggested the Extended T10 and Extended CSTR (Continuous Stirred-Tank Reactor) methods to improve the inactivation calculations within ozone contactors. To develop a method that fully considers the hydraulic behavior of the contactor, two models (Plug Flow with Dispersion and N-CSTR) were successfully fitted with five tracer tests results derived from four Water Treatment Plants and a pilot-scale contactor. A new method based on the N-CSTR model was defined as the Partially Segregated (Pseg) method. The predictions from all the methods mentioned were compared under conditions of poor and good hydraulic performance, low and high disinfectant decay, and different levels of inactivation. These methods were also compared with experimental results from a chlorine pilot-scale contactor used for Escherichia coli inactivation. The T10 and Extended T10 methods led to large over- and under-estimations. The Segregated Flow Analysis (used in the IDDF) also considerably overestimated the inactivation under high disinfectant decay. Only the Extended CSTR and Pseg methods produced realistic and conservative predictions in all cases. Finally, a simple implementation procedure of the Pseg method was suggested for calculation of disinfection performance. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Study on performance prediction and energy saving of indirect evaporative cooling system

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Seong Yeon; Kim, Tae Ho; Kim, Myung Ho [Dept. of Mechanical Design Engineering, Chungnam National University, Daejeon (Korea, Republic of)

    2015-09-15

    The purpose of this study is to predict the performance of an indirect evaporative cooling system, and to evaluate its energy saving effect when applied to the exhaust heat recovery system of an air-handling unit. We derive the performance correlation of the indirect evaporative cooling system using a plastic heat exchanger based on experimental data obtained in various conditions. We predict the variations in the performance of the system for various return and outdoor air conditioning systems using the obtained correlation. We also analyze the energy saving of the system realized by the exhaust heat recovery using the typical meteorological data for several cities in Korea. The average utilization rate of the sensible cooling system for the exhaust heat recovery is 44.3% during summer, while that of the evaporative cooling system is 96.7%. The energy saving of the evaporative cooling system is much higher compared to the sensible cooling system, and was about 3.89 times the value obtained in Seoul.

  9. Using Mason number to predict MR damper performance from limited test data

    Science.gov (United States)

    Becnel, Andrew C.; Wereley, Norman M.

    2017-05-01

    The Mason number can be used to produce a single master curve which relates MR fluid stress versus strain rate behavior across a wide range of shear rates, temperatures, and applied magnetic fields. As applications of MR fluid energy absorbers expand to a variety of industries and operating environments, Mason number analysis offers a path to designing devices with desired performance from a minimal set of preliminary test data. Temperature strongly affects the off-state viscosity of the fluid, as the passive viscous force drops considerably at higher temperatures. Yield stress is not similarly affected, and stays relatively constant with changing temperature. In this study, a small model-scale MR fluid rotary energy absorber is used to measure the temperature correction factor of a commercially-available MR fluid from LORD Corporation. This temperature correction factor is identified from shear stress vs. shear rate data collected at four different temperatures. Measurements of the MR fluid yield stress are also obtained and related to a standard empirical formula. From these two MR fluid properties - temperature-dependent viscosity and yield stress - the temperature-corrected Mason number is shown to predict the force vs. velocity performance of a full-scale rotary MR fluid energy absorber. This analysis technique expands the design space of MR devices to high shear rates and allows for comprehensive predictions of overall performance across a wide range of operating conditions from knowledge only of the yield stress vs. applied magnetic field and a temperature-dependent viscosity correction factor.

  10. The predictive value of general movement tasks in assessing occupational task performance.

    Science.gov (United States)

    Frost, David M; Beach, Tyson A C; McGill, Stuart M; Callaghan, Jack P

    2015-01-01

    Within the context of evaluating individuals' movement behavior it is generally assumed that the tasks chosen will predict their competency to perform activities relevant to their occupation. This study sought to examine whether a battery of general tasks could be used to predict the movement patterns employed by firefighters to perform select job-specific skills. Fifty-two firefighters performed a battery of general and occupation-specific tasks that simulated the demands of firefighting. Participants' peak lumbar spine and frontal plane knee motion were compared across tasks. During 85% of all comparisons, the magnitude of spine and knee motion was greater during the general movement tasks than observed during the firefighting skills. Certain features of a worker's movement behavior may be exhibited across a range of tasks. Therefore, provided that a movement screen's tasks expose the motions of relevance for the population being tested, general evaluations could offer valuable insight into workers' movement competency or facilitate an opportunity to establish an evidence-informed intervention.

  11. Review Of Mechanistic Understanding And Modeling And Uncertainty Analysis Methods For Predicting Cementitious Barrier Performance

    International Nuclear Information System (INIS)

    Langton, C.; Kosson, D.

    2009-01-01

    Cementitious barriers for nuclear applications are one of the primary controls for preventing or limiting radionuclide release into the environment. At the present time, performance and risk assessments do not fully incorporate the effectiveness of engineered barriers because the processes that influence performance are coupled and complicated. Better understanding the behavior of cementitious barriers is necessary to evaluate and improve the design of materials and structures used for radioactive waste containment, life extension of current nuclear facilities, and design of future nuclear facilities, including those needed for nuclear fuel storage and processing, nuclear power production and waste management. The focus of the Cementitious Barriers Partnership (CBP) literature review is to document the current level of knowledge with respect to: (1) mechanisms and processes that directly influence the performance of cementitious materials (2) methodologies for modeling the performance of these mechanisms and processes and (3) approaches to addressing and quantifying uncertainties associated with performance predictions. This will serve as an important reference document for the professional community responsible for the design and performance assessment of cementitious materials in nuclear applications. This review also provides a multi-disciplinary foundation for identification, research, development and demonstration of improvements in conceptual understanding, measurements and performance modeling that would be lead to significant reductions in the uncertainties and improved confidence in the estimating the long-term performance of cementitious materials in nuclear applications. This report identifies: (1) technology gaps that may be filled by the CBP project and also (2) information and computational methods that are in currently being applied in related fields but have not yet been incorporated into performance assessments of cementitious barriers. The various

  12. REVIEW OF MECHANISTIC UNDERSTANDING AND MODELING AND UNCERTAINTY ANALYSIS METHODS FOR PREDICTING CEMENTITIOUS BARRIER PERFORMANCE

    Energy Technology Data Exchange (ETDEWEB)

    Langton, C.; Kosson, D.

    2009-11-30

    Cementitious barriers for nuclear applications are one of the primary controls for preventing or limiting radionuclide release into the environment. At the present time, performance and risk assessments do not fully incorporate the effectiveness of engineered barriers because the processes that influence performance are coupled and complicated. Better understanding the behavior of cementitious barriers is necessary to evaluate and improve the design of materials and structures used for radioactive waste containment, life extension of current nuclear facilities, and design of future nuclear facilities, including those needed for nuclear fuel storage and processing, nuclear power production and waste management. The focus of the Cementitious Barriers Partnership (CBP) literature review is to document the current level of knowledge with respect to: (1) mechanisms and processes that directly influence the performance of cementitious materials (2) methodologies for modeling the performance of these mechanisms and processes and (3) approaches to addressing and quantifying uncertainties associated with performance predictions. This will serve as an important reference document for the professional community responsible for the design and performance assessment of cementitious materials in nuclear applications. This review also provides a multi-disciplinary foundation for identification, research, development and demonstration of improvements in conceptual understanding, measurements and performance modeling that would be lead to significant reductions in the uncertainties and improved confidence in the estimating the long-term performance of cementitious materials in nuclear applications. This report identifies: (1) technology gaps that may be filled by the CBP project and also (2) information and computational methods that are in currently being applied in related fields but have not yet been incorporated into performance assessments of cementitious barriers. The various

  13. PV (photovoltaics) performance evaluation and simulation-based energy yield prediction for tropical buildings

    International Nuclear Information System (INIS)

    Saber, Esmail M.; Lee, Siew Eang; Manthapuri, Sumanth; Yi, Wang; Deb, Chirag

    2014-01-01

    Air pollution and climate change increased the importance of renewable energy resources like solar energy in the last decades. Rack-mounted PhotoVoltaics (PV) and Building Integrated PhotoVoltaics (BIPV) are the most common photovoltaic systems which convert incident solar radiation on façade or surrounding area to electricity. In this paper the performance of different solar cell types is evaluated for the tropical weather of Singapore. As a case study, on-site measured data of PV systems implemented in a zero energy building in Singapore, is analyzed. Different types of PV systems (silicon wafer and thin film) have been installed on rooftop, façade, car park shelter, railing and etc. The impact of different solar cell generations, arrays environmental conditions (no shading, dappled shading, full shading), orientation (South, North, East or West facing) and inclination (between PV module and horizontal direction) is investigated on performance of modules. In the second stage of research, the whole PV systems in the case study are simulated in EnergyPlus energy simulation software with several PV performance models including Simple, Equivalent one-diode and Sandia. The predicted results by different models are compared with measured data and the validated model is used to provide simulation-based energy yield predictions for wide ranges of scenarios. It has been concluded that orientation of low-slope rooftop PV has negligible impact on annual energy yield but in case of PV external sunshade, east façade and panel slope of 30–40° are the most suitable location and inclination. - Highlights: • Characteristics of PV systems in tropics are analyzed in depth. • The ambiguity toward amorphous panel energy yield in tropics is discussed. • Equivalent-one diode and Sandia models can fairly predict the energy yield. • A general guideline is provided to estimate the energy yield of PV systems in tropics

  14. A New Hybrid Method for Improving the Performance of Myocardial Infarction Prediction

    Directory of Open Access Journals (Sweden)

    Hojatollah Hamidi

    2016-06-01

    Full Text Available Abstract Introduction: Myocardial Infarction, also known as heart attack, normally occurs due to such causes as smoking, family history, diabetes, and so on. It is recognized as one of the leading causes of death in the world. Therefore, the present study aimed to evaluate the performance of classification models in order to predict Myocardial Infarction, using a feature selection method that includes Forward Selection and Genetic Algorithm. Materials & Methods: The Myocardial Infarction data set used in this study contains the information related to 519 visitors to Shahid Madani Specialized Hospital of Khorramabad, Iran. This data set includes 33 features. The proposed method includes a hybrid feature selection method in order to enhance the performance of classification algorithms. The first step of this method selects the features using Forward Selection. At the second step, the selected features were given to a genetic algorithm, in order to select the best features. Classification algorithms entail Ada Boost, Naïve Bayes, J48 decision tree and simpleCART are applied to the data set with selected features, for predicting Myocardial Infarction. Results: The best results have been achieved after applying the proposed feature selection method, which were obtained via simpleCART and J48 algorithms with the accuracies of 96.53% and 96.34%, respectively. Conclusion: Based on the results, the performances of classification algorithms are improved. So, applying the proposed feature selection method, along with classification algorithms seem to be considered as a confident method with respect to predicting the Myocardial Infarction.

  15. Prediction of the performance of an ion chamber amplifier under γ radiation

    International Nuclear Information System (INIS)

    Agarwal, Vivek; Sundarsingh, V.P.; Ramachandran, V.

    2005-01-01

    The ion chamber amplifier (ICA) plays a major role in the proper functioning of a nuclear reactor as it monitors the radiations from the nuclear reactor by measuring the ionic activity inside the ion chamber. The signal conditioning circuitry of the ICA detects and conditions the weak ionic currents coming from the ion chamber dome. Degradation in the performance of the semiconductor devices used in this part of the ICA, can lead to inaccurate monitoring of the reactor operation, resulting in a possible catastrophe due to malfunction. Further, the response of the ICA under irradiation also depends upon the strength of the input signal (ionic) current it is required to handle. The active devices used in the ICA under study are operational amplifiers (Op-Amps) such as DN8500A and OPA111, instrumentation amplifier INA101, transistor 2N2920A and a voltage reference device, AD584. Since these devices may be sensitive to radiation, one must know their radiation behaviour so that the performance of the ICA can be predicted. This paper examines the performance of the ICA by characterising the radiation profiles of its vital components, viz. the Op-Amps, instrumentation amplifiers, transistors, etc. by monitoring their parametric changes on-line, i.e. when the source is on, and the devices are biased. The simulation runs involve the simulation of the entire ICA circuitry using the changed values of the vital parameters such as input bias current and input offset voltage. The main advantage of this method is that it obviates irradiating the whole ICA circuit to study its irradiation performance, and simulates an environment of radiation leakage around the ICA. Based on this study, results are presented to predict the performance of the ICA

  16. Parametric performance predictions for high-power pulsed electric CO lasers

    International Nuclear Information System (INIS)

    Center, R.E.; Caledonia, G.E.

    1975-01-01

    A kinetic model of the pulsed electrical CO laser is used to survey the time-dependent laser performance on parameters such as gas mixture, initial translational temperature, and discharge pulse length for both multiline and selected-line operation. Predictions are presented for the total output efficiency, spectral distributions of the stimulated transitions, energy partitioning in the vibrational and translational modes, and the translational temperature history in CO-N 2 mixtures. A brief description of the kinetic model is included. Simple scaling relationships are presented which can be used to scale the results to other densities in the pressure-broadened regime

  17. Predicting memory performance under conditions of proactive interference: immediate and delayed judgments of learning.

    Science.gov (United States)

    Wahlheim, Christopher N

    2011-07-01

    Four experiments examined the monitoring accuracy of immediate and delayed judgments of learning (JOLs) under conditions of proactive interference (PI). PI was produced using paired-associate learning tasks that conformed to variations of classic A-B, A-D paradigms. Results revealed that the relative monitoring accuracy of interference items was better for delayed than for immediate JOLs. However, delayed JOLs were overconfident for interference items, but not for items devoid of interference. Intrusions retrieved prior to delayed JOLs produced inflated predictions of performance. These results show that delayed JOLs enhance monitoring accuracy in PI situations, except when intrusions are mistaken for target responses.

  18. Corrosion models for predictions of performance of high-level radioactive-waste containers

    Energy Technology Data Exchange (ETDEWEB)

    Farmer, J.C.; McCright, R.D. [Lawrence Livermore National Lab., CA (United States); Gdowski, G.E. [KMI Energy Services, Livermore, CA (United States)

    1991-11-01

    The present plan for disposal of high-level radioactive waste in the US is to seal it in containers before emplacement in a geologic repository. A proposed site at Yucca Mountain, Nevada, is being evaluated for its suitability as a geologic repository. The containers will probably be made of either an austenitic or a copper-based alloy. Models of alloy degradation are being used to predict the long-term performance of the containers under repository conditions. The models are of uniform oxidation and corrosion, localized corrosion, and stress corrosion cracking, and are applicable to worst-case scenarios of container degradation. This paper reviews several of the models.

  19. Performance Prediction of a MongoDB-Based Traceability System in Smart Factory Supply Chains

    Science.gov (United States)

    Kang, Yong-Shin; Park, Il-Ha; Youm, Sekyoung

    2016-01-01

    In the future, with the advent of the smart factory era, manufacturing and logistics processes will become more complex, and the complexity and criticality of traceability will further increase. This research aims at developing a performance assessment method to verify scalability when implementing traceability systems based on key technologies for smart factories, such as Internet of Things (IoT) and BigData. To this end, based on existing research, we analyzed traceability requirements and an event schema for storing traceability data in MongoDB, a document-based Not Only SQL (NoSQL) database. Next, we analyzed the algorithm of the most representative traceability query and defined a query-level performance model, which is composed of response times for the components of the traceability query algorithm. Next, this performance model was solidified as a linear regression model because the response times increase linearly by a benchmark test. Finally, for a case analysis, we applied the performance model to a virtual automobile parts logistics. As a result of the case study, we verified the scalability of a MongoDB-based traceability system and predicted the point when data node servers should be expanded in this case. The traceability system performance assessment method proposed in this research can be used as a decision-making tool for hardware capacity planning during the initial stage of construction of traceability systems and during their operational phase. PMID:27983654

  20. Performance Prediction of a MongoDB-Based Traceability System in Smart Factory Supply Chains.

    Science.gov (United States)

    Kang, Yong-Shin; Park, Il-Ha; Youm, Sekyoung

    2016-12-14

    In the future, with the advent of the smart factory era, manufacturing and logistics processes will become more complex, and the complexity and criticality of traceability will further increase. This research aims at developing a performance assessment method to verify scalability when implementing traceability systems based on key technologies for smart factories, such as Internet of Things (IoT) and BigData. To this end, based on existing research, we analyzed traceability requirements and an event schema for storing traceability data in MongoDB, a document-based Not Only SQL (NoSQL) database. Next, we analyzed the algorithm of the most representative traceability query and defined a query-level performance model, which is composed of response times for the components of the traceability query algorithm. Next, this performance model was solidified as a linear regression model because the response times increase linearly by a benchmark test. Finally, for a case analysis, we applied the performance model to a virtual automobile parts logistics. As a result of the case study, we verified the scalability of a MongoDB-based traceability system and predicted the point when data node servers should be expanded in this case. The traceability system performance assessment method proposed in this research can be used as a decision-making tool for hardware capacity planning during the initial stage of construction of traceability systems and during their operational phase.

  1. Artificial neural network model for prediction of safety performance indicators goals in nuclear plants

    Energy Technology Data Exchange (ETDEWEB)

    Souto, Kelling C.; Nunes, Wallace W. [Instituto Federal de Educacao, Ciencia e Tecnologia do Rio de Janeiro, Nilopolis, RJ (Brazil). Lab. de Aplicacoes Computacionais; Machado, Marcelo D., E-mail: dornemd@eletronuclear.gov.b [ELETROBRAS Termonuclear S.A. (ELETRONUCLEAR), Rio de Janeiro, RJ (Brazil). Gerencia de Combustivel Nuclear - GCN.T

    2011-07-01

    Safety performance indicators have been developed to provide a quantitative indication of the performance and safety in various industry sectors. These indexes can provide assess to aspects ranging from production, design, and human performance up to management issues in accordance with policy, objectives and goals of the company. The use of safety performance indicators in nuclear power plants around the world is a reality. However, it is necessary to periodically set goal values. Such goals are targets relating to each of the indicators to be achieved by the plant over a predetermined period of operation. The current process of defining these goals is carried out by experts in a subjective way, based on actual data from the plant, and comparison with global indices. Artificial neural networks are computational techniques that present a mathematical model inspired by the neural structure of intelligent organisms that acquire knowledge through experience. This paper proposes an artificial neural network model aimed at predicting values of goals to be used in the evaluation of safety performance indicators for nuclear power plants. (author)

  2. Performance Prediction of a MongoDB-Based Traceability System in Smart Factory Supply Chains

    Directory of Open Access Journals (Sweden)

    Yong-Shin Kang

    2016-12-01

    Full Text Available In the future, with the advent of the smart factory era, manufacturing and logistics processes will become more complex, and the complexity and criticality of traceability will further increase. This research aims at developing a performance assessment method to verify scalability when implementing traceability systems based on key technologies for smart factories, such as Internet of Things (IoT and BigData. To this end, based on existing research, we analyzed traceability requirements and an event schema for storing traceability data in MongoDB, a document-based Not Only SQL (NoSQL database. Next, we analyzed the algorithm of the most representative traceability query and defined a query-level performance model, which is composed of response times for the components of the traceability query algorithm. Next, this performance model was solidified as a linear regression model because the response times increase linearly by a benchmark test. Finally, for a case analysis, we applied the performance model to a virtual automobile parts logistics. As a result of the case study, we verified the scalability of a MongoDB-based traceability system and predicted the point when data node servers should be expanded in this case. The traceability system performance assessment method proposed in this research can be used as a decision-making tool for hardware capacity planning during the initial stage of construction of traceability systems and during their operational phase.

  3. Artificial neural network model for prediction of safety performance indicators goals in nuclear plants

    International Nuclear Information System (INIS)

    Souto, Kelling C.; Nunes, Wallace W.; Machado, Marcelo D.

    2011-01-01

    Safety performance indicators have been developed to provide a quantitative indication of the performance and safety in various industry sectors. These indexes can provide assess to aspects ranging from production, design, and human performance up to management issues in accordance with policy, objectives and goals of the company. The use of safety performance indicators in nuclear power plants around the world is a reality. However, it is necessary to periodically set goal values. Such goals are targets relating to each of the indicators to be achieved by the plant over a predetermined period of operation. The current process of defining these goals is carried out by experts in a subjective way, based on actual data from the plant, and comparison with global indices. Artificial neural networks are computational techniques that present a mathematical model inspired by the neural structure of intelligent organisms that acquire knowledge through experience. This paper proposes an artificial neural network model aimed at predicting values of goals to be used in the evaluation of safety performance indicators for nuclear power plants. (author)

  4. Performance Prediction Modelling for Flexible Pavement on Low Volume Roads Using Multiple Linear Regression Analysis

    Directory of Open Access Journals (Sweden)

    C. Makendran

    2015-01-01

    Full Text Available Prediction models for low volume village roads in India are developed to evaluate the progression of different types of distress such as roughness, cracking, and potholes. Even though the Government of India is investing huge quantum of money on road construction every year, poor control over the quality of road construction and its subsequent maintenance is leading to the faster road deterioration. In this regard, it is essential that scientific maintenance procedures are to be evolved on the basis of performance of low volume flexible pavements. Considering the above, an attempt has been made in this research endeavor to develop prediction models to understand the progression of roughness, cracking, and potholes in flexible pavements exposed to least or nil routine maintenance. Distress data were collected from the low volume rural roads covering about 173 stretches spread across Tamil Nadu state in India. Based on the above collected data, distress prediction models have been developed using multiple linear regression analysis. Further, the models have been validated using independent field data. It can be concluded that the models developed in this study can serve as useful tools for the practicing engineers maintaining flexible pavements on low volume roads.

  5. Executive functioning performance predicts subjective and physiological acute stress reactivity: preliminary results.

    Science.gov (United States)

    Hendrawan, Donny; Yamakawa, Kaori; Kimura, Motohiro; Murakami, Hiroki; Ohira, Hideki

    2012-06-01

    Individual differences in baseline executive functioning (EF) capacities have been shown to predict state anxiety during acute stressor exposure. However, no previous studies have clearly demonstrated the relationship between EF and physiological measures of stress. The present study investigated the efficacy of several well-known EF tests (letter fluency, Stroop test, and Wisconsin Card Sorting Test) in predicting both subjective and physiological stress reactivity during acute psychosocial stress exposure. Our results show that letter fluency served as the best predictor for both types of reactivity. Specifically, the higher the letter fluency score, the lower the acute stress reactivity after controlling for the baseline stress response, as indicated by lower levels of state anxiety, negative mood, salivary cortisol, and skin conductance. Moreover, the predictive power of the letter fluency test remained significant for state anxiety and cortisol indices even after further adjustments for covariates by adding the body mass index (BMI) as a covariate. Thus, good EF performance, as reflected by high letter fluency scores, may dampen acute stress responses, which suggests that EF processes are directly associated with aspects of stress regulation. Copyright © 2012 Elsevier B.V. All rights reserved.

  6. Incorporating Scale-Dependent Fracture Stiffness for Improved Reservoir Performance Prediction

    Science.gov (United States)

    Crawford, B. R.; Tsenn, M. C.; Homburg, J. M.; Stehle, R. C.; Freysteinson, J. A.; Reese, W. C.

    2017-12-01

    We present a novel technique for predicting dynamic fracture network response to production-driven changes in effective stress, with the potential for optimizing depletion planning and improving recovery prediction in stress-sensitive naturally fractured reservoirs. A key component of the method involves laboratory geomechanics testing of single fractures in order to develop a unique scaling relationship between fracture normal stiffness and initial mechanical aperture. Details of the workflow are as follows: tensile, opening mode fractures are created in a variety of low matrix permeability rocks with initial, unstressed apertures in the micrometer to millimeter range, as determined from image analyses of X-ray CT scans; subsequent hydrostatic compression of these fractured samples with synchronous radial strain and flow measurement indicates that both mechanical and hydraulic aperture reduction varies linearly with the natural logarithm of effective normal stress; these stress-sensitive single-fracture laboratory observations are then upscaled to networks with fracture populations displaying frequency-length and length-aperture scaling laws commonly exhibited by natural fracture arrays; functional relationships between reservoir pressure reduction and fracture network porosity, compressibility and directional permeabilities as generated by such discrete fracture network modeling are then exported to the reservoir simulator for improved naturally fractured reservoir performance prediction.

  7. Preschoolers' precision of the approximate number system predicts later school mathematics performance.

    Science.gov (United States)

    Mazzocco, Michèle M M; Feigenson, Lisa; Halberda, Justin

    2011-01-01

    The Approximate Number System (ANS) is a primitive mental system of nonverbal representations that supports an intuitive sense of number in human adults, children, infants, and other animal species. The numerical approximations produced by the ANS are characteristically imprecise and, in humans, this precision gradually improves from infancy to adulthood. Throughout development, wide ranging individual differences in ANS precision are evident within age groups. These individual differences have been linked to formal mathematics outcomes, based on concurrent, retrospective, or short-term longitudinal correlations observed during the school age years. However, it remains unknown whether this approximate number sense actually serves as a foundation for these school mathematics abilities. Here we show that ANS precision measured at preschool, prior to formal instruction in mathematics, selectively predicts performance on school mathematics at 6 years of age. In contrast, ANS precision does not predict non-numerical cognitive abilities. To our knowledge, these results provide the first evidence for early ANS precision, measured before the onset of formal education, predicting later mathematical abilities.

  8. Predicting fatigue and psychophysiological test performance from speech for safety critical environments

    Directory of Open Access Journals (Sweden)

    Khan Richard Baykaner

    2015-08-01

    Full Text Available Automatic systems for estimating operator fatigue have application in safety-critical environments. A system which could estimate level of fatigue from speech would have application in domains where operators engage in regular verbal communication as part of their duties. Previous studies on the prediction of fatigue from speech have been limited because of their reliance on subjective ratings and because they lack comparison to other methods for assessing fatigue. In this paper we present an analysis of voice recordings and psychophysiological test scores collected from seven aerospace personnel during a training task in which they remained awake for 60 hours. We show that voice features and test scores are affected by both the total time spent awake and the time position within each subject’s circadian cycle. However, we show that time spent awake and time of day information are poor predictors of the test results; while voice features can give good predictions of the psychophysiological test scores and sleep latency. Mean absolute errors of prediction are possible within about 17.5% for sleep latency and 5-12% for test scores. We discuss the implications for the use of voice as a means to monitor the effects of fatigue on cognitive performance in practical applications.

  9. Markers of preparatory attention predict visual short-term memory performance.

    Science.gov (United States)

    Murray, Alexandra M; Nobre, Anna C; Stokes, Mark G

    2011-05-01

    Visual short-term memory (VSTM) is limited in capacity. Therefore, it is important to encode only visual information that is most likely to be relevant to behaviour. Here we asked which aspects of selective biasing of VSTM encoding predict subsequent memory-based performance. We measured EEG during a selective VSTM encoding task, in which we varied parametrically the memory load and the precision of recall required to compare a remembered item to a subsequent probe item. On half the trials, a spatial cue indicated that participants only needed to encode items from one hemifield. We observed a typical sequence of markers of anticipatory spatial attention: early attention directing negativity (EDAN), anterior attention directing negativity (ADAN), late directing attention positivity (LDAP); as well as of VSTM maintenance: contralateral delay activity (CDA). We found that individual differences in preparatory brain activity (EDAN/ADAN) predicted cue-related changes in recall accuracy, indexed by memory-probe discrimination sensitivity (d'). Importantly, our parametric manipulation of memory-probe similarity also allowed us to model the behavioural data for each participant, providing estimates for the quality of the memory representation and the probability that an item could be retrieved. We found that selective encoding primarily increased the probability of accurate memory recall; that ERP markers of preparatory attention predicted the cue-related changes in recall probability. Copyright © 2011. Published by Elsevier Ltd.

  10. Determination of a suitable set of loss models for centrifugal compressor performance prediction

    Directory of Open Access Journals (Sweden)

    Elkin I. GUTIÉRREZ VELÁSQUEZ

    2017-10-01

    Full Text Available Performance prediction in preliminary design stages of several turbomachinery components is a critical task in order to bring the design processes of these devices to a successful conclusion. In this paper, a review and analysis of the major loss mechanisms and loss models, used to determine the efficiency of a single stage centrifugal compressor, and a subsequent examination to determine an appropriate loss correlation set for estimating the isentropic efficiency in preliminary design stages of centrifugal compressors, were developed. Several semi-empirical correlations, commonly used to predict the efficiency of centrifugal compressors, were implemented in FORTRAN code and then were compared with experimental results in order to establish a loss correlation set to determine, with good approximation, the isentropic efficiency of single stage compressor. The aim of this study is to provide a suitable loss correlation set for determining the isentropic efficiency of a single stage centrifugal compressor, because, with a large amount of loss mechanisms and correlations available in the literature, it is difficult to ascertain how many and which correlations to employ for the correct prediction of the efficiency in the preliminary stage design of a centrifugal compressor. As a result of this study, a set of correlations composed by nine loss mechanisms for single stage centrifugal compressors, conformed by a rotor and a diffuser, are specified.

  11. Performance of Surgical Risk Scores to Predict Mortality after Transcatheter Aortic Valve Implantation

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    Leonardo Sinnott Silva

    2015-01-01

    Full Text Available Abstract Background: Predicting mortality in patients undergoing transcatheter aortic valve implantation (TAVI remains a challenge. Objectives: To evaluate the performance of 5 risk scores for cardiac surgery in predicting the 30-day mortality among patients of the Brazilian Registry of TAVI. Methods: The Brazilian Multicenter Registry prospectively enrolled 418 patients undergoing TAVI in 18 centers between 2008 and 2013. The 30-day mortality risk was calculated using the following surgical scores: the logistic EuroSCORE I (ESI, EuroSCORE II (ESII, Society of Thoracic Surgeons (STS score, Ambler score (AS and Guaragna score (GS. The performance of the risk scores was evaluated in terms of their calibration (Hosmer–Lemeshow test and discrimination [area under the receiver–operating characteristic curve (AUC]. Results: The mean age was 81.5 ± 7.7 years. The CoreValve (Medtronic was used in 86.1% of the cohort, and the transfemoral approach was used in 96.2%. The observed 30-day mortality was 9.1%. The 30-day mortality predicted by the scores was as follows: ESI, 20.2 ± 13.8%; ESII, 6.5 ± 13.8%; STS score, 14.7 ± 4.4%; AS, 7.0 ± 3.8%; GS, 17.3 ± 10.8%. Using AUC, none of the tested scores could accurately predict the 30-day mortality. AUC for the scores was as follows: 0.58 [95% confidence interval (CI: 0.49 to 0.68, p = 0.09] for ESI; 0.54 (95% CI: 0.44 to 0.64, p = 0.42 for ESII; 0.57 (95% CI: 0.47 to 0.67, p = 0.16 for AS; 0.48 (95% IC: 0.38 to 0.57, p = 0.68 for STS score; and 0.52 (95% CI: 0.42 to 0.62, p = 0.64 for GS. The Hosmer–Lemeshow test indicated acceptable calibration for all scores (p > 0.05. Conclusions: In this real world Brazilian registry, the surgical risk scores were inaccurate in predicting mortality after TAVI. Risk models specifically developed for TAVI are required.

  12. Study on the Contra-Rotating Propeller system design and full-scale performance prediction method

    Directory of Open Access Journals (Sweden)

    Keh-Sik Min

    2009-09-01

    Full Text Available A ship's screw-propeller produces thrust by rotation and, at the same time, generates rotational flow behind the propeller. This rotational flow has no contribution to the generation of thrust, but instead produces energy loss. By recovering part of the lost energy in the rotational flow, therefore, it is possible to improve the propulsion efficiency. The contra-rotating propeller (CRP system is the representing example of such devices. Unfortunately, however, neither a design method nor a full-scale performance prediction procedure for the CRP system has been well established yet. The authors have long performed studies on the CRP system, and some of the results from the authors’ studies shall be presented and discussed.

  13. Artificial neural networks for the performance prediction of heat pump hot water heaters

    Science.gov (United States)

    Mathioulakis, E.; Panaras, G.; Belessiotis, V.

    2018-02-01

    The rapid progression in the use of heat pumps, due to the decrease in the equipment cost, together with the favourable economics of the consumed electrical energy, has been combined with the wide dissemination of air-to-water heat pumps (AWHPs) in the residential sector. The entrance of the respective systems in the commercial sector has made important the modelling of the processes. In this work, the suitability of artificial neural networks (ANN) in the modelling of AWHPs is investigated. The ambient air temperature in the evaporator inlet and the water temperature in the condenser inlet have been selected as the input variables; energy performance indices and quantities characterising the operation of the system have been selected as output variables. The results verify that the, easy-to-implement, trained ANN can represent an effective tool for the prediction of the AWHP performance in various operation conditions and the parametrical investigation of their behaviour.

  14. Theta coupling between V4 and prefrontal cortex predicts visual short-term memory performance.

    Science.gov (United States)

    Liebe, Stefanie; Hoerzer, Gregor M; Logothetis, Nikos K; Rainer, Gregor

    2012-01-29

    Short-term memory requires communication between multiple brain regions that collectively mediate the encoding and maintenance of sensory information. It has been suggested that oscillatory synchronization underlies intercortical communication. Yet, whether and how distant cortical areas cooperate during visual memory remains elusive. We examined neural interactions between visual area V4 and the lateral prefrontal cortex using simultaneous local field potential (LFP) recordings and single-unit activity (SUA) in monkeys performing a visual short-term memory task. During the memory period, we observed enhanced between-area phase synchronization in theta frequencies (3-9 Hz) of LFPs together with elevated phase locking of SUA to theta oscillations across regions. In addition, we found that the strength of intercortical locking was predictive of the animals' behavioral performance. This suggests that theta-band synchronization coordinates action potential communication between V4 and prefrontal cortex that may contribute to the maintenance of visual short-term memories.

  15. Excelling at selling: The charming personality style predicts occupational activities, sales performance, and persuasive competence.

    Science.gov (United States)

    Kazén, Miguel; Kuhl, Julius; Boermans, Sylvie; Koole, Sander L

    2013-08-01

    The present research investigates how individual differences in charming personality are related to occupational activities, sales performance, and persuasive competence. Study 1 showed that sales representatives had higher scores on the charming personality style than executive managers. Study 2 showed that the charming personality style predicted actual sales performance among branch managers of a large German insurance company over a period of 2 years; the explicit power motivation served as a mediator in this relation. Finally, Study 3, carried out in a laboratory setting, confirmed the hypothesis that a charming personality is associated with persuasive competence, which suggests that this style is more relevant for sales representatives than for executive managers. The authors conclude that the charming personality style represents an important psychological resource for organizations. © 2013 The Institute of Psychology, Chinese Academy of Sciences and Wiley Publishing Asia Pty Ltd.

  16. Predictions of silicon avalanche photodiode detector performance in water vapor differential absorption lidar

    Science.gov (United States)

    Kenimer, R. L.

    1988-01-01

    Performance analyses are presented which establish that over most of the range of signals expected for a down-looking differential absorption lidar (DIAL) operated at 16 km the silicon avalanche photodiode (APD) is the preferred detector for DIAL measurements of atmospheric water vapor in the 730 nm spectral region. The higher quantum efficiency of the APD's, (0.8-0.9) compared to a photomultiplier's (0.04-0.18) more than offsets the higher noise of an APD receiver. In addition to offering lower noise and hence lower random error the APD's excellent linearity and impulse recovery minimize DIAL systematic errors attributable to the detector. Estimates of the effect of detector system parameters on overall random and systematic DIAL errors are presented, and performance predictions are supported by laboratory characterization data for an APD receiver system.

  17. Performance prediction of a synchronization link for distributed aerospace wireless systems.

    Science.gov (United States)

    Wang, Wen-Qin; Shao, Huaizong

    2013-01-01

    For reasons of stealth and other operational advantages, distributed aerospace wireless systems have received much attention in recent years. In a distributed aerospace wireless system, since the transmitter and receiver placed on separated platforms which use independent master oscillators, there is no cancellation of low-frequency phase noise as in the monostatic cases. Thus, high accurate time and frequency synchronization techniques are required for distributed wireless systems. The use of a dedicated synchronization link to quantify and compensate oscillator frequency instability is investigated in this paper. With the mathematical statistical models of phase noise, closed-form analytic expressions for the synchronization link performance are derived. The possible error contributions including oscillator, phase-locked loop, and receiver noise are quantified. The link synchronization performance is predicted by utilizing the knowledge of the statistical models, system error contributions, and sampling considerations. Simulation results show that effective synchronization error compensation can be achieved by using this dedicated synchronization link.

  18. Prediction of tunnel boring machine performance using machine and rock mass data

    International Nuclear Information System (INIS)

    Dastgir, G.

    2012-01-01

    Performance of the tunnel boring machine and its prediction by different methods has been a hot issue since the first TBM came into being. For the sake of safe and sound transport, improvement of hydro-power, mining, civil and many other tunneling projects that cannot be driven efficiently and economically by conventional drill and blast, TBMs are quite frequently used. TBM parameters and rock mass properties, which heavily influence machine performance, should be estimated or known before choice of TBM-type and start of excavation. By applying linear regression analysis (SPSS19), fuzzy logic tools and a special Math-Lab code on actual field data collected from seven TBM driven tunnels (Hieflau expansion, Queen water tunnel, Vereina, Hemerwald, Maen, Pieve and Varzo tunnel), an attempt was made to provide prediction of rock mass class (RMC), rock fracture class (RFC), penetration rate (PR) and advance rate (AR). For detailed analysis of TBM performance, machine parameters (thrust, machine rpm, torque, power etc.), machine types and specification and rock mass properties (UCS, discontinuity in rock mass, RMC, RFC, RMR, etc.) were analyzed by 3-D surface plotting using statistical software R. Correlations between machine parameters and rock mass properties which effectively influence prediction models, are presented as well. In Hieflau expansion tunnel AR linearly decreases with increase of thrust due to high dependence of machine advance rate upon rock strength. For Hieflau expansion tunnel three types of data (TBM, rock mass and seismic data e.g. amplitude, pseudo velocity etc.) were coupled and simultaneously analyzed by plotting 3-D surfaces. No appreciable correlation between seismic data (Amplitude and Pseudo velocity) and rock mass properties and machine parameters could be found. Tool wear as a function of TBM operational parameters was analyzed which revealed that tool wear is minimum if applied thrust is moderate and that tool wear is high when thrust is

  19. Comparison of nuclear safety research reactor (TRIGA-ACPR) performance with analytical prediction

    International Nuclear Information System (INIS)

    West, G.B.; Whittemore, W.L.

    1976-01-01

    The NSRR was taken critical on June 30, 1975 at the Japan Atomic Energy Research Institute - Tokai-mura, Japan. Following initial core loading and control rod calibration, a series of pulsing tests was performed to characterize the performance of the reactor. A comparison has been made of performance parameters actually measured in the 157 element core versus predicted values based upon design analyses. The nuclear parameters measured were quite close to prediction. A $4.70 pulse produced a minimum period of 1.12 msec, a peak power of 20,500 MW and yielded a prompt energy release of 103 MW-sec. Pulse tests with experimental UO 2 fuel pins in the central irradiation cavity have produced 320 cal/gm, averaged at the axial center of 10% enriched UO 2 , for a 100 MW-sec pulse. The pulse rods for the NSRR contain B 4 C enriched to about 93 percent in Boron-10 in order to achieve maximum design performance with only three pulse rods. The total worth for the three transient rods was measured to be about $5.05 (vs $5.07 calculated for the 165 element core), thus verifying the effectiveness of the Boron-10 enrichment to achieve the desired result. Analysis of fuel temperature measurements made in the NSRR show that, for fuel temperatures produced during pulsing greater than 900 deg. C, heat transfer in the 0.010-inch gap between fuel and clad is enhanced by the minor outgassing of hydrogen which is characteristic of that temperature region. The hydrogen is normally all reabsorbed within about 100 sec of maximum temperature, at which time the heat transfer is characteristic of air (or argon) in the gap. In some of the temperature-instrumented elements, however, all of the hydrogen was not reabsorbed and as a result these elements gave significantly lower temperatures for high power steady state operation than were recorded prior to pulsing. In general, the NSRR parameters measured during startup were quite close to analytical prediction and the overall performance of the

  20. Both Reaction Time and Accuracy Measures of Intraindividual Variability Predict Cognitive Performance in Alzheimer's Disease

    Directory of Open Access Journals (Sweden)

    Björn U. Christ

    2018-04-01

    Full Text Available Dementia researchers around the world prioritize the urgent need for sensitive measurement tools that can detect cognitive and functional change at the earliest stages of Alzheimer's disease (AD. Sensitive indicators of underlying neural pathology assist in the early detection of cognitive change and are thus important for the evaluation of early-intervention clinical trials. One method that may be particularly well-suited to help achieve this goal involves the quantification of intraindividual variability (IIV in cognitive performance. The current study aimed to directly compare two methods of estimating IIV (fluctuations in accuracy-based scores vs. those in latency-based scores to predict cognitive performance in AD. Specifically, we directly compared the relative sensitivity of reaction time (RT—and accuracy-based estimates of IIV to cognitive compromise. The novelty of the present study, however, centered on the patients we tested [a group of patients with Alzheimer's disease (AD] and the outcome measures we used (a measure of general cognitive function and a measure of episodic memory function. Hence, we compared intraindividual standard deviations (iSDs from two RT tasks and three accuracy-based memory tasks in patients with possible or probable Alzheimer's dementia (n = 23 and matched healthy controls (n = 25. The main analyses modeled the relative contributions of RT vs. accuracy-based measures of IIV toward the prediction of performance on measures of (a overall cognitive functioning, and (b episodic memory functioning. Results indicated that RT-based IIV measures are superior predictors of neurocognitive impairment (as indexed by overall cognitive and memory performance than accuracy-based IIV measures, even after adjusting for the timescale of measurement. However, one accuracy-based IIV measure (derived from a recognition memory test also differentiated patients with AD from controls, and significantly predicted episodic memory