WorldWideScience

Sample records for swat predictive performance

  1. Quantifying the Uncertainty in Streamflow Predictions Using Swat for Brazos-Colorado Coastal Watershed, Texas

    Science.gov (United States)

    Mandal, D.; Bhatia, N.; Srivastav, R. K.

    2016-12-01

    Soil Water Assessment Tool (SWAT) is one of the most comprehensive hydrologic models to simulate streamflow for a watershed. The two major inputs for a SWAT model are: (i) Digital Elevation Models (DEM), and (ii) Land Use and Land Cover Maps (LULC). This study aims to quantify the uncertainty in streamflow predictions using SWAT for San Bernard River in Brazos-Colorado coastal watershed, Texas, by incorporating the respective datasets from different sources: (i) DEM data will be obtained from ASTER GDEM V2, GMTED2010, NHD DEM, and SRTM DEM datasets with ranging resolution from 1/3 arc-second to 30 arc-second, and (ii) LULC data will be obtained from GLCC V2, MRLC NLCD2011, NOAA's C-CAP, USGS GAP, and TCEQ databases. Weather variables (Precipitation and Max-Min Temperature at daily scale) will be obtained from National Climatic Data Centre (NCDC) and SWAT in-built STASGO tool will be used to obtain the soil maps. The SWAT model will be calibrated using SWAT-CUP SUFI-2 approach and its performance will be evaluated using the statistical indices of Nash-Sutcliffe efficiency (NSE), ratio of Root-Mean-Square-Error to standard deviation of observed streamflow (RSR), and Percent-Bias Error (PBIAS). The study will help understand the performance of SWAT model with varying data sources and eventually aid the regional state water boards in planning, designing, and managing hydrologic systems.

  2. Prediction of phosphorus loads in an artificially drained lowland catchment using a modified SWAT model

    Science.gov (United States)

    Bauwe, Andreas; Eckhardt, Kai-Uwe; Lennartz, Bernd

    2017-04-01

    Eutrophication is still one of the main environmental problems in the Baltic Sea. Currently, agricultural diffuse sources constitute the major portion of phosphorus (P) fluxes to the Baltic Sea and have to be reduced to achieve the HELCOM targets and improve the ecological status. Eco-hydrological models are suitable tools to identify sources of nutrients and possible measures aiming at reducing nutrient loads into surface waters. In this study, the Soil and Water Assessment Tool (SWAT) was applied to the Warnow river basin (3300 km2), the second largest watershed in Germany discharging into the Baltic Sea. The Warnow river basin is located in northeastern Germany and characterized by lowlands with a high proportion of artificially drained areas. The aim of this study were (i) to estimate P loadings for individual flow fractions (point sources, surface runoff, tile flow, groundwater flow), spatially distributed on sub-basin scale. Since the official version of SWAT does not allow for the modeling of P in tile drains, we tested (ii) two different approaches of simulating P in tile drains by changing the SWAT source code. The SWAT source code was modified so that (i) the soluble P concentration of the groundwater was transferred to the tile water and (ii) the soluble P in the soil was transferred to the tiles. The SWAT model was first calibrated (2002-2011) and validated (1992-2001) for stream flow at 7 headwater catchments at a daily time scale. Based on this, the stream flow at the outlet of the Warnow river basin was simulated. Performance statistics indicated at least satisfactory model results for each sub-basin. Breaking down the discharge into flow constituents, it becomes visible that stream flow is mainly governed by groundwater and tile flow. Due to the topographic situation with gentle slopes, surface runoff played only a minor role. Results further indicate that the prediction of soluble P loads was improved by the modified SWAT versions. Major sources of

  3. The modified SWAT model for predicting fecal coliforms in the Wachusett Reservoir Watershed, USA.

    Science.gov (United States)

    Cho, Kyung Hwa; Pachepsky, Yakov A; Kim, Joon Ha; Kim, Jung-Woo; Park, Mi-Hyun

    2012-10-01

    This study assessed fecal coliform contamination in the Wachusett Reservoir Watershed in Massachusetts, USA using Soil and Water Assessment Tool (SWAT) because bacteria are one of the major water quality parameters of concern. The bacteria subroutine in SWAT, considering in-stream bacteria die-off only, was modified in this study to include solar radiation-associated die-off and the contribution of wildlife. The result of sensitivity analysis demonstrates that solar radiation is one of the most significant fate factors of fecal coliform. A water temperature-associated function to represent the contribution of beaver activity in the watershed to fecal contamination improved prediction accuracy. The modified SWAT model provides an improved estimate of bacteria from the watershed. Our approach will be useful for simulating bacterial concentrations to provide predictive and reliable information of fecal contamination thus facilitating the implementation of effective watershed management. Copyright © 2012 Elsevier Ltd. All rights reserved.

  4. SWAT Model Prediction of Phosphorus Loading in a South Carolina Karst Watershed with a Downstream Embayment

    Science.gov (United States)

    Devendra M. Amatya; Manoj K. Jha; Thomas M. Williams; Amy E. Edwards; Daniel R.. Hitchcock

    2013-01-01

    The SWAT model was used to predict total phosphorus (TP) loadings for a 1555-ha karst watershed—Chapel Branch Creek (CBC)—which drains to a lake via a reservoir-like embayment (R-E). The model was first tested for monthly streamflow predictions from tributaries draining three potential source areas as well as the downstream R-E, followed by TP loadings using data...

  5. Improving streamflow simulations and forecasting performance of SWAT model by assimilating remotely sensed soil moisture observations

    Science.gov (United States)

    Patil, Amol; Ramsankaran, RAAJ

    2017-12-01

    This article presents a study carried out using EnKF based assimilation of coarser-scale SMOS soil moisture retrievals to improve the streamflow simulations and forecasting performance of SWAT model in a large catchment. This study has been carried out in Munneru river catchment, India, which is about 10,156 km2. In this study, an EnkF based new approach is proposed for improving the inherent vertical coupling of soil layers of SWAT hydrological model during soil moisture data assimilation. Evaluation of the vertical error correlation obtained between surface and subsurface layers indicates that the vertical coupling can be improved significantly using ensemble of soil storages compared to the traditional static soil storages based EnKF approach. However, the improvements in the simulated streamflow are moderate, which is due to the limitations in SWAT model in reflecting the profile soil moisture updates in surface runoff computations. Further, it is observed that the durability of streamflow improvements is longer when the assimilation system effectively updates the subsurface flow component. Overall, the results of the present study indicate that the passive microwave-based coarser-scale soil moisture products like SMOS hold significant potential to improve the streamflow estimates when assimilating into large-scale distributed hydrological models operating at a daily time step.

  6. Grid based calibration of SWAT hydrological models

    Directory of Open Access Journals (Sweden)

    D. Gorgan

    2012-07-01

    Full Text Available The calibration and execution of large hydrological models, such as SWAT (soil and water assessment tool, developed for large areas, high resolution, and huge input data, need not only quite a long execution time but also high computation resources. SWAT hydrological model supports studies and predictions of the impact of land management practices on water, sediment, and agricultural chemical yields in complex watersheds. The paper presents the gSWAT application as a web practical solution for environmental specialists to calibrate extensive hydrological models and to run scenarios, by hiding the complex control of processes and heterogeneous resources across the grid based high computation infrastructure. The paper highlights the basic functionalities of the gSWAT platform, and the features of the graphical user interface. The presentation is concerned with the development of working sessions, interactive control of calibration, direct and basic editing of parameters, process monitoring, and graphical and interactive visualization of the results. The experiments performed on different SWAT models and the obtained results argue the benefits brought by the grid parallel and distributed environment as a solution for the processing platform. All the instances of SWAT models used in the reported experiments have been developed through the enviroGRIDS project, targeting the Black Sea catchment area.

  7. Soil and Water Assessment Tool (SWAT) Applicability on Nutrients Loadings Prediction in Mountainous Lower Bear Malad River (LBMR) Watershed, Utah.

    Science.gov (United States)

    Salha, A. A.; Stevens, D. K.

    2014-12-01

    The application of watershed simulation models is indispensable when pollution is generated by a nonpoint source. These models should be able to simulate large complex watersheds with varying soils, land use and management conditions over long periods of time. This study presents the application of Soil and Water Assessment Tool (SWAT) to investigate, manage, and research the transport and fate of nutrients in (Subbasin HUC 16010204) Lower Bear Malad River (LBMR) watershed, Box elder County, Utah. Water quality problems arise primarily from high phosphorus and total suspended sediment concentrations that were caused by increasing agricultural and farming activities and complex network of canals and ducts of varying sizes and carrying capacities that transport water (for farming and agriculture uses). Using the available input data (Digital Elevation Model (DEM), land use/Land cover (LULC), soil map and weather and climate data for 20 years (1990-2010) to predict the water quantity and quality of the LBMR watershed using a spatially distributed model version of hydrological ArcSWAT model (ArcSWAT 2012.10_1.14). No previous studies have been found in the literature regarding an in-depth simulation study of the Lower Bear Malad River (LBMR) watershed to simulate stream flow and to quantify the associated movement of nitrogen, phosphorus, and sediment. It is expected that the model mainly will predict monthly mean total phosphorus (TP) concentration and loadings in a mountainous LBRM watershed (steep Wellsville mountain range with peak of (2,857 m)) having into consideration the snow and runoff variables affecting the prediction process. The simulated nutrient concentrations were properly consistent with observations based on the R2 and Nash- Sutcliffe fitness factors. Further, the model will be able to manage and assess the land application in that area with corresponding to proper BMPs regarding water quality management. Keywords: Water Quality Modeling; Soil and

  8. Comparison of model performance and simulated water balance using NASIM and SWAT for the Wupper River Basin, Germany

    Science.gov (United States)

    Lorza, Paula; Nottebohm, Martin; Scheibel, Marc; aus der Beek, Tim

    2017-04-01

    Under the framework of the Horizon 2020 project BINGO (Bringing INnovation to onGOing water management), climate change impacts on the water cycle in the Wupper catchment area are being studied. With this purpose, a set of hydrological models in NASIM and SWAT have been set up, calibrated, and validated for past conditions using available data. NASIM is a physically-based, lumped, hydrological model based on the water balance equation. For the upper part of the Dhünn catchment area - Wupper River's main tributary - a SWAT model was also implemented. Observed and simulated discharge by NASIM and SWAT for the drainage area upstream of Neumühle hydrometric station (close to Große Dhünn reservoir's inlet) are compared. Comparison of simulated water balance for several hydrological years between the two models is also carried out. While NASIM offers high level of detail for modelling of complex urban areas and the possibility of entering precipitation time series at fine temporal resolution (e.g. minutely data), SWAT enables to study long-term impacts offering a huge variety of input and output variables including different soil properties, vegetation and land management practices. Beside runoff, also sediment and nutrient transport can be simulated. For most calculations, SWAT operates on a daily time step. The objective of this and future work is to determine catchment responses on different meteorological events and to study parameter sensitivity of stationary inputs such as soil parameters, vegetation or land use. Model performance is assessed with different statistical metrics (relative volume error, coefficient of determination, and Nash-Sutcliffe Efficiency).

  9. Comparison of streamflow prediction skills from NOAH-MP/RAPID, VIC/RAPID and SWAT toward an ensemble flood forecasting framework over large scales

    Science.gov (United States)

    Rajib, M. A.; Tavakoly, A. A.; Du, L.; Merwade, V.; Lin, P.

    2015-12-01

    Considering the differences in how individual models represent physical processes for runoff generation and streamflow routing, use of ensemble output is desirable in an operational streamflow estimation and flood forecasting framework. To enable the use of ensemble streamflow, comparison of multiple hydrologic models at finer spatial resolution over a large domain is yet to be explored. The objective of this work is to compare streamflow prediction skills from three different land surface/hydrologic modeling frameworks: NOAH-MP/RAPID, VIC/RAPID and SWAT, over the Ohio River Basin with a drainage area of 491,000 km2. For a uniform comparison, all the three modeling frameworks share the same setup with common weather inputs, spatial resolution, and gauge stations being employed in the calibration procedure. The runoff output from NOAH-MP and VIC land surface models is routed through a vector-based river routing model named RAPID, that is set up on the high resolution NHDPlus reaches and catchments. SWAT model is used with its default tightly coupled surface-subsurface hydrology and channel routing components to obtain streamflow for each NHDPlus reach. Model simulations are performed in two modes, including: (i) hindcasting/calibration mode in which the models are calibrated against USGS daily streamflow observations at multiple locations, and (ii) validation mode in which the calibrated models are executed at 3-hourly time interval for historical flood events. In order to have a relative assessment on the model-specific nature of biases during storm events as well as dry periods, time-series of surface runoff and baseflow components at the specific USGS gauging locations are extracted from corresponding observed/simulated streamflow data using a recursive digital filter. The multi-model comparison presented here provides insights toward future model improvements and also serves as the first step in implementing an operational ensemble flood forecasting framework

  10. An Assessment of Mean Areal Precipitation Methods on Simulated Stream Flow: A SWAT Model Performance Assessment

    Directory of Open Access Journals (Sweden)

    Sean Zeiger

    2017-06-01

    Full Text Available Accurate mean areal precipitation (MAP estimates are essential input forcings for hydrologic models. However, the selection of the most accurate method to estimate MAP can be daunting because there are numerous methods to choose from (e.g., proximate gauge, direct weighted average, surface-fitting, and remotely sensed methods. Multiple methods (n = 19 were used to estimate MAP with precipitation data from 11 distributed monitoring sites, and 4 remotely sensed data sets. Each method was validated against the hydrologic model simulated stream flow using the Soil and Water Assessment Tool (SWAT. SWAT was validated using a split-site method and the observed stream flow data from five nested-scale gauging sites in a mixed-land-use watershed of the central USA. Cross-validation results showed the error associated with surface-fitting and remotely sensed methods ranging from −4.5 to −5.1%, and −9.8 to −14.7%, respectively. Split-site validation results showed the percent bias (PBIAS values that ranged from −4.5 to −160%. Second order polynomial functions especially overestimated precipitation and subsequent stream flow simulations (PBIAS = −160 in the headwaters. The results indicated that using an inverse-distance weighted, linear polynomial interpolation or multiquadric function method to estimate MAP may improve SWAT model simulations. Collectively, the results highlight the importance of spatially distributed observed hydroclimate data for precipitation and subsequent steam flow estimations. The MAP methods demonstrated in the current work can be used to reduce hydrologic model uncertainty caused by watershed physiographic differences.

  11. Performance of salsnes water to algae treatment (swat) technology in a continuous mode for high algae recovery

    OpenAIRE

    Ramos Barragán, Germán

    2014-01-01

    Master's thesis in Environmental technology. *KAR OK,.KONF MAI 2016* Many researchers consider efficient harvesting is the major bottleneck in cost efficient production of microalgae, contributing 20 – 30 % to total production cost. This thesis is the conclusion of a two years research project to develop Salsnes Water to Algae Treatment (SWAT) harvesting technology. SWAT uses two main processes: flocculation and filtration. The SWAT objectives were achieved, 95 % algae removal and p...

  12. Comparison of performance of tile drainage routines in SWAT 2009 and 2012 in an extensively tile-drained watershed in the Midwest

    Science.gov (United States)

    Guo, Tian; Gitau, Margaret; Merwade, Venkatesh; Arnold, Jeffrey; Srinivasan, Raghavan; Hirschi, Michael; Engel, Bernard

    2018-01-01

    Subsurface tile drainage systems are widely used in agricultural watersheds in the Midwestern US and enable the Midwest area to become highly productive agricultural lands, but can also create environmental problems, for example nitrate-N contamination associated with drainage waters. The Soil and Water Assessment Tool (SWAT) has been used to model watersheds with tile drainage. SWAT2012 revisions 615 and 645 provide new tile drainage routines. However, few studies have used these revisions to study tile drainage impacts at both field and watershed scales. Moreover, SWAT2012 revision 645 improved the soil moisture based curve number calculation method, which has not been fully tested. This study used long-term (1991-2003) field site and river station data from the Little Vermilion River (LVR) watershed to evaluate performance of tile drainage routines in SWAT2009 revision 528 (the old routine) and SWAT2012 revisions 615 and 645 (the new routine). Both the old and new routines provided reasonable but unsatisfactory (NSE sediment and annual corn and soybean yield results from SWAT with the old and new tile drainage routines were compared with observed values. Generally, the new routine provided acceptable simulated tile flow (NSE = 0.48-0.65) and nitrate in tile flow (NSE = 0.48-0.68) for field sites with random pattern tile and constant tile spacing, while the old routine simulated tile flow and nitrate in tile flow results for the field site with constant tile spacing were unacceptable (NSE = 0.00-0.32 and -0.29-0.06, respectively). The new modified curve number calculation method in revision 645 (NSE = 0.50-0.81) better simulated surface runoff than revision 615 (NSE = -0.11-0.49). The calibration provided reasonable parameter sets for the old and new routines in the LVR watershed, and the validation results showed that the new routine has the potential to accurately simulate hydrologic processes in mildly sloped watersheds.

  13. A GUIDED SWAT MODEL APPLICATION ON SEDIMENT YIELD MODELING IN PANGANI RIVER BASIN: LESSONS LEARNT

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    Preksedis M. Ndomba

    2008-01-01

    Full Text Available The overall objective of this paper is to report on the lessons learnt from applying Soil and Water Assessment Tool (SWAT in a well guided sediment yield modelling study. The study area is the upstream of Pangani River Basin (PRB, the Nyumba Ya Mungu (NYM reservoir catchment, located in the North Eastern part of Tanzania. It should be noted that, previous modeling exercises in the region applied SWAT with preassumption that inter-rill or sheet erosion was the dominant erosion type. In contrast, in this study SWAT model application was guided by results of analysis of high temporal resolution of sediment flow data and hydro-meteorological data. The runoff component of the SWAT model was calibrated from six-years (i.e. 1977¿1982 of historical daily streamflow data. The sediment component of the model was calibrated using one-year (1977-1988 daily sediment loads estimated from one hydrological year sampling programme (between March and November, 2005 rating curve. A long-term period over 37 years (i.e. 1969-2005 simulation results of the SWAT model was validated to downstream NYM reservoir sediment accumulation information. The SWAT model captured 56 percent of the variance (CE and underestimated the observed daily sediment loads by 0.9 percent according to Total Mass Control (TMC performance indices during a normal wet hydrological year, i.e., between November 1, 1977 and October 31, 1978, as the calibration period. SWAT model predicted satisfactorily the long-term sediment catchment yield with a relative error of 2.6 percent. Also, the model has identified erosion sources spatially and has replicated some erosion processes as determined in other studies and field observations in the PRB. This result suggests that for catchments where sheet erosion is dominant SWAT model may substitute the sediment-rating curve. However, the SWAT model could not capture the dynamics of sediment load delivery in some seasons to the catchment outlet.

  14. Improvement of the R-SWAT-FME framework to support multiple variables and multi-objective functions

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    Wu, Yiping; Liu, Shu-Guang

    2014-01-01

    Application of numerical models is a common practice in the environmental field for investigation and prediction of natural and anthropogenic processes. However, process knowledge, parameter identifiability, sensitivity, and uncertainty analyses are still a challenge for large and complex mathematical models such as the hydrological/water quality model, Soil and Water Assessment Tool (SWAT). In this study, the previously developed R program language-SWAT-Flexible Modeling Environment (R-SWAT-FME) was improved to support multiple model variables and objectives at multiple time steps (i.e., daily, monthly, and annually). This expansion is significant because there is usually more than one variable (e.g., water, nutrients, and pesticides) of interest for environmental models like SWAT. To further facilitate its easy use, we also simplified its application requirements without compromising its merits, such as the user-friendly interface. To evaluate the performance of the improved framework, we used a case study focusing on both streamflow and nitrate nitrogen in the Upper Iowa River Basin (above Marengo) in the United States. Results indicated that the R-SWAT-FME performs well and is comparable to the built-in auto-calibration tool in multi-objective model calibration. Overall, the enhanced R-SWAT-FME can be useful for the SWAT community, and the methods we used can also be valuable for wrapping potential R packages with other environmental models.

  15. Comparison of SWAT and GeoWEPP model in predicting the impact of stone bunds on runoff and erosion processes in the Northern Ethiopian Highlands

    Science.gov (United States)

    Demelash, Nigus; Flagler, Jared; Renschler, Chris; Strohmeier, Stefan; Holzmann, Hubert; Feras, Ziadat; Addis, Hailu; Zucca, Claudio; Bayu, Wondimu; Klik, Andreas

    2017-04-01

    Soil degradation is a major issue in the Ethiopian highlands which are most suitable for agriculture and, therefore, support a major part of human population and livestock. Heavy rainstorms during the rainy season in summer create soil erosion and runoff processes which affect soil fertility and food security. In the last years programs for soil conservation and afforestation were initiated by the Ethiopian government to reduce erosion risk, retain water in the landscape and improve crop yields. The study was done in two adjacent watersheds in the Northwestern highlands of Ethiopia. One of the watersheds is developed by soil and water conservation structures (stone bunds) in 2011 and the other one is without soil and water conservation structures. Spatial distribution of soil textures and other soil properties were determined in the field and in the laboratory and a soil map was derived. A land use map was evaluated based on satellite images and ground truth data. A Digital Elevation Model of the watershed was developed based on conventional terrestrial surveying using a total station. At the outlet of the watersheds weirs with cameras were installed to measure surface runoff. During each event runoff samples were collected and sediment concentration was analyzed. The objective of this study is 1) to assess the impact of stone bunds on runoff and erosion processes by using simulation models, and 2) to compare the performance of two soil erosion models in predicting the measurements. The selected erosion models were the Soil and Water Assessment Tool (SWAT) and the Geospatial Interface to the Water Erosion Prediction Project (GeoWEPP). The simulation models were calibrated/verified for the 2011-2013 periods and validated with 2014-2015 data. Results of this comparison will be presented.

  16. Comparison of performance of tile drainage routines in SWAT 2009 and 2012 in an extensively tile-drained watershed in the Midwest

    Directory of Open Access Journals (Sweden)

    T. Guo

    2018-01-01

    Full Text Available Subsurface tile drainage systems are widely used in agricultural watersheds in the Midwestern US and enable the Midwest area to become highly productive agricultural lands, but can also create environmental problems, for example nitrate-N contamination associated with drainage waters. The Soil and Water Assessment Tool (SWAT has been used to model watersheds with tile drainage. SWAT2012 revisions 615 and 645 provide new tile drainage routines. However, few studies have used these revisions to study tile drainage impacts at both field and watershed scales. Moreover, SWAT2012 revision 645 improved the soil moisture based curve number calculation method, which has not been fully tested. This study used long-term (1991–2003 field site and river station data from the Little Vermilion River (LVR watershed to evaluate performance of tile drainage routines in SWAT2009 revision 528 (the old routine and SWAT2012 revisions 615 and 645 (the new routine. Both the old and new routines provided reasonable but unsatisfactory (NSE  <  0.5 uncalibrated flow and nitrate loss results for a mildly sloped watershed with low runoff. The calibrated monthly tile flow, surface flow, nitrate-N in tile and surface flow, sediment and annual corn and soybean yield results from SWAT with the old and new tile drainage routines were compared with observed values. Generally, the new routine provided acceptable simulated tile flow (NSE  =  0.48–0.65 and nitrate in tile flow (NSE  =  0.48–0.68 for field sites with random pattern tile and constant tile spacing, while the old routine simulated tile flow and nitrate in tile flow results for the field site with constant tile spacing were unacceptable (NSE  =  0.00–0.32 and −0.29–0.06, respectively. The new modified curve number calculation method in revision 645 (NSE  =  0.50–0.81 better simulated surface runoff than revision 615 (NSE  =  −0.11–0.49. The calibration

  17. Avaliação da carga mental de trabalho e do desempenho de medidas de mensuração: NASA TLX e SWAT Evaluation of mental workload and performance measurement: NASA TLX and SWAT

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    Mariane de Souza Cardoso

    2012-12-01

    workload used in studies of ergonomics show workers' skills and limitations, characteristics of work organization, and facilitate the presentation of quantitative and qualitative results. The comparison of the performance of these two mental workload assessment methods proved a relevant investigation to the field of ergonomics since there are few comparative studies on the performance of these methods. With regard to the overall comparison of the performance of these methods, NASA TLX allows the evaluation of mental workload by analyzing several dimensions of the work situation and presents advantages when compared to SWAT because it can be easily implemented and showed greater acceptance by those who evaluated it

  18. HPAC (Hazard Prediction and Assessment Capability) jSWAT (Joint Seminar Wargaming Adjudication Tool) Integration; A Technical Solution

    Science.gov (United States)

    2006-09-01

    Tool is an LOD developed software package (programmed in Java) that aims to facilitate the seminar wargaming process that Army currently uses to...For display, the jSWAT package name has been truncated from “com.classforge.jswat”. Similarly, the actual client and server classes...The above example places a sulphur hexafluoride sensor in the continental US. To place Sarin samplers on Kangaroo Island we might use the

  19. Simulating Flash Floods at Hourly Time-Step Using the SWAT Model

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    Laurie Boithias

    2017-11-01

    Full Text Available Flash floods are natural phenomena with environmental, social and economic impacts. To date, few numerical models are able to simulate hydrological processes at catchment scale at a reasonable time scale to describe flash events with accurate details. Considering a ~810 km2 Mediterranean river coastal basin (southwestern France as a study case, the objective of the present study was to assess the ability of the sub-daily module of the lumped Soil and Water Assessment Tool (SWAT to simulate discharge (1 time-continuously, by testing two sub-basin delineation schemes, two catchment sizes, and two output time-steps; and (2 at flood time-scale, by comparing the performances of SWAT to the performances of the event-based fully distributed MARINE model when simulating flash flood events. We showed that there was no benefit of decreasing the size of the minimum drainage area (e.g., from ~15 km2 down to ~1 km2 when delineating sub-basins in SWAT. We also showed that both the MARINE and SWAT models were equally able to reproduce peak discharge, flood timing and volume, and that they were both limited by rainfall and soil data. Hence, the SWAT model appears to be a reliable modelling tool to predict discharge over long periods of time in large flash-flood-prone basins.

  20. Application of SWAT-HS, a lumped hillslope model to simulate hydrology in the Cannonsville Reservoir watershed, New York

    Science.gov (United States)

    Hoang, Linh; Schneiderman, Elliot; Mukundan, Rajith; Moore, Karen; Owens, Emmet; Steenhuis, Tammo

    2017-04-01

    Surface runoff is the primary mechanism transporting substances such as sediments, agricultural chemicals, and pathogens to receiving waters. In order to predict runoff and pollutant fluxes, and to evaluate management practices, it is essential to accurately predict the areas generating surface runoff, which depend on the type of runoff: infiltration-excess runoff and saturation-excess runoff. The watershed of Cannonsville reservoir is part of the New York City water supply system that provides high quality drinking water to nine million people in New York City (NYC) and nearby communities. Previous research identified saturation-excess runoff as the dominant runoff mechanism in this region. The Soil and Water Assessment Tool (SWAT) is a promising tool to simulate the NYC watershed given its broad application and good performance in many watersheds with different scales worldwide, for its ability to model water quality responses, and to evaluate the effect of management practices on water quality at the watershed scale. However, SWAT predicts runoff based mainly on soil and land use characteristics, and implicitly considers only infiltration-excess runoff. Therefore, we developed a modified version of SWAT, referred to as SWAT-Hillslope (SWAT-HS), which explicitly simulates saturation-excess runoff by redefining Hydrological Response Units (HRUs) based on wetness classes with varying soil water storage capacities, and by introducing a surface aquifer with the ability to route interflow from "drier" to "wetter" wetness classes. SWAT-HS was first tested at Town Brook, a 37 km2 headwater watershed draining to the Cannonsville reservoir using a single sub-basin for the whole watershed. SWAT-HS performed well, and predicted streamflow yielded Nash-Sutcliffe Efficiencies of 0.68 and 0.87 at the daily and monthly time steps, respectively. More importantly, it predicted the spatial distribution of saturated areas accurately. Based on the good performance in the Town Brook

  1. Improving SWAT model performance in the upper Blue Nile Basin using meteorological data integration and subcatchment discretization

    Science.gov (United States)

    Polanco, Erwin Isaac; Fleifle, Amr; Ludwig, Ralf; Disse, Markus

    2017-09-01

    The Blue Nile Basin is confronted by land degradation problems, insufficient agricultural production, and a limited number of developed energy sources. Hydrological models provide useful tools to better understand such complex systems and improve water resources and land management practices. In this study, SWAT was used to model the hydrological processes in the upper Blue Nile Basin. Comparisons between a Climate Forecast System Reanalysis (CFSR) and a conventional ground weather dataset were done under two sub-basin discretization levels (30 and 87 sub-basins) to create an integrated dataset to improve the spatial and temporal limitations of both datasets. A SWAT error index (SEI) was also proposed to compare the reliability of the models under different discretization levels and weather datasets. This index offers an assessment of the model quality based on precipitation and evapotranspiration. SEI demonstrates to be a reliable additional and useful method to measure the level of error of SWAT. The results showed the discrepancies of using different weather datasets with different sub-basin discretization levels. Datasets under 30 sub-basins achieved Nash-Sutcliffe coefficient (NS) values of -0.51, 0.74, and 0.84; p factors of 0.53, 0.66, and 0.70; and r factors of 1.11, 0.83, and 0.67 for the CFSR, ground, and integrated datasets, respectively. Meanwhile, models under 87 sub-basins achieved NS values of -1.54, 0.43, and 0.80; p factors of 0.36, 0.67, and 0.77; r factors of 0.93, 0.68, and 0.54 for the CFSR, ground, and integrated datasets, respectively. Based on the obtained statistical results, the integrated dataset provides a better model of the upper Blue Nile Basin.

  2. Impact of Spatial Scale on Calibration and Model Output for a Grid-based SWAT Model

    Science.gov (United States)

    Pignotti, G.; Vema, V. K.; Rathjens, H.; Raj, C.; Her, Y.; Chaubey, I.; Crawford, M. M.

    2014-12-01

    The traditional implementation of the Soil and Water Assessment Tool (SWAT) model utilizes common landscape characteristics known as hydrologic response units (HRUs). Discretization into HRUs provides a simple, computationally efficient framework for simulation, but also represents a significant limitation of the model as spatial connectivity between HRUs is ignored. SWATgrid, a newly developed, distributed version of SWAT, provides modified landscape routing via a grid, overcoming these limitations. However, the current implementation of SWATgrid has significant computational overhead, which effectively precludes traditional calibration and limits the total number of grid cells in a given modeling scenario. Moreover, as SWATgrid is a relatively new modeling approach, it remains largely untested with little understanding of the impact of spatial resolution on model output. The objective of this study was to determine the effects of user-defined input resolution on SWATgrid predictions in the Upper Cedar Creek Watershed (near Auburn, IN, USA). Original input data, nominally at 30 m resolution, was rescaled for a range of resolutions between 30 and 4,000 m. A 30 m traditional SWAT model was developed as the baseline for model comparison. Monthly calibration was performed, and the calibrated parameter set was then transferred to all other SWAT and SWATgrid models to focus the effects of resolution on prediction uncertainty relative to the baseline. Model output was evaluated with respect to stream flow at the outlet and water quality parameters. Additionally, output of SWATgrid models were compared to output of traditional SWAT models at each resolution, utilizing the same scaled input data. A secondary objective considered the effect of scale on calibrated parameter values, where each standard SWAT model was calibrated independently, and parameters were transferred to SWATgrid models at equivalent scales. For each model, computational requirements were evaluated

  3. Application of WRF - SWAT OpenMI 2.0 based models integration for real time hydrological modelling and forecasting

    Science.gov (United States)

    Bugaets, Andrey; Gonchukov, Leonid

    2014-05-01

    Intake of deterministic distributed hydrological models into operational water management requires intensive collection and inputting of spatial distributed climatic information in a timely manner that is both time consuming and laborious. The lead time of the data pre-processing stage could be essentially reduced by coupling of hydrological and numerical weather prediction models. This is especially important for the regions such as the South of the Russian Far East where its geographical position combined with a monsoon climate affected by typhoons and extreme heavy rains caused rapid rising of the mountain rivers water level and led to the flash flooding and enormous damage. The objective of this study is development of end-to-end workflow that executes, in a loosely coupled mode, an integrated modeling system comprised of Weather Research and Forecast (WRF) atmospheric model and Soil and Water Assessment Tool (SWAT 2012) hydrological model using OpenMI 2.0 and web-service technologies. Migration SWAT into OpenMI compliant involves reorganization of the model into a separate initialization, performing timestep and finalization functions that can be accessed from outside. To save SWAT normal behavior, the source code was separated from OpenMI-specific implementation into the static library. Modified code was assembled into dynamic library and wrapped into C# class implemented the OpenMI ILinkableComponent interface. Development of WRF OpenMI-compliant component based on the idea of the wrapping web-service clients into a linkable component and seamlessly access to output netCDF files without actual models connection. The weather state variables (precipitation, wind, solar radiation, air temperature and relative humidity) are processed by automatic input selection algorithm to single out the most relevant values used by SWAT model to yield climatic data at the subbasin scale. Spatial interpolation between the WRF regular grid and SWAT subbasins centroid (which are

  4. Hydrology and sediment yield calibration for the Barasona reservoir catchment (Spain) using SWAT

    Science.gov (United States)

    Palazón, Leticia; Navas, Ana

    2013-04-01

    Hydrological and soil erosion models, as Soil and Water Assessment Tool (SWAT), have become very useful tools and increasingly serve as vital components of integrated environmental assessments that provide information outside of direct field experiments and causal observation. The purpose of this study was to improve the calibration of SWAT model to use it in an alpine catchment as a simulator of processes related to water quality and soil erosion. SWAT is spatially semi-distributed, agro-hydrological model that operates on a daily time step (as a minimum) at basin scale. It is designed to predict the impact of management on water, sediment and agricultural chemical yields in ungaged catchments. SWAT provides physically based algorithms as an option to define many of the important components of the hydrologic cycle. The input requirements of the model are used to describe the climate, soil properties, topography, vegetation, and land management practices. SWAT analyzes small or large catchments by discretising into sub-basins, which are then further subdivided into hydrological response units (HRUs) with homogeneous land use, soil type and slope. SWAT model (SWAT2009) coupled with a GIS interface (ArcSWAT), was applied to the Barasona reservoir catchment located in the central Spanish Pyrenees. The 1509 km2 agro-forestry catchment presents a mountain type climate, an altitudinal range close to 3000 meters and a precipitation variation close to 1000 mm/km. The mountainous characteristics of the catchment, in addition to the scarcity of climate data in the region, require specific calibration for some processes. Snowfall and snowmelt are significant processes in the hydrologic regime of the area and were calibrated in a previous work. In this work some of the challenges of the catchment to model with SWAT which affected the hydrology and the sediment yield simulation were performed as improvement of the previous calibration. Two reservoirs, a karst system which

  5. Algorithm Theory - SWAT 2006

    DEFF Research Database (Denmark)

    issues of theoretical algorithmics and applications in various fields including graph algorithms, computational geometry, scheduling, approximation algorithms, network algorithms, data storage and manipulation, combinatorics, sorting, searching, online algorithms, optimization, etc.......This book constitutes the refereed proceedings of the 10th Scandinavian Workshop on Algorithm Theory, SWAT 2006, held in Riga, Latvia, in July 2006. The 36 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 154 submissions. The papers address all...

  6. Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds

    Directory of Open Access Journals (Sweden)

    Indrajeet Chaubey

    2010-11-01

    Full Text Available There has been a steady shift towards modeling and model-based approaches as primary methods of assessing watershed response to hydrologic inputs and land management, and of quantifying watershed-wide best management practice (BMP effectiveness. Watershed models often require some degree of calibration and validation to achieve adequate watershed and therefore BMP representation. This is, however, only possible for gauged watersheds. There are many watersheds for which there are very little or no monitoring data available, thus the question as to whether it would be possible to extend and/or generalize model parameters obtained through calibration of gauged watersheds to ungauged watersheds within the same region. This study explored the possibility of developing regionalized model parameter sets for use in ungauged watersheds. The study evaluated two regionalization methods: global averaging, and regression-based parameters, on the SWAT model using data from priority watersheds in Arkansas. Resulting parameters were tested and model performance determined on three gauged watersheds. Nash-Sutcliffe efficiencies (NS for stream flow obtained using regression-based parameters (0.53–0.83 compared well with corresponding values obtained through model calibration (0.45–0.90. Model performance obtained using global averaged parameter values was also generally acceptable (0.4 ≤ NS ≤ 0.75. Results from this study indicate that regionalized parameter sets for the SWAT model can be obtained and used for making satisfactory hydrologic response predictions in ungauged watersheds.

  7. OpenMP-accelerated SWAT simulation using Intel C and FORTRAN compilers: Development and benchmark

    Science.gov (United States)

    Ki, Seo Jin; Sugimura, Tak; Kim, Albert S.

    2015-02-01

    We developed a practical method to accelerate execution of Soil and Water Assessment Tool (SWAT) using open (free) computational resources. The SWAT source code (rev 622) was recompiled using a non-commercial Intel FORTRAN compiler in Ubuntu 12.04 LTS Linux platform, and newly named iOMP-SWAT in this study. GNU utilities of make, gprof, and diff were used to develop the iOMP-SWAT package, profile memory usage, and check identicalness of parallel and serial simulations. Among 302 SWAT subroutines, the slowest routines were identified using GNU gprof, and later modified using Open Multiple Processing (OpenMP) library in an 8-core shared memory system. In addition, a C wrapping function was used to rapidly set large arrays to zero by cross compiling with the original SWAT FORTRAN package. A universal speedup ratio of 2.3 was achieved using input data sets of a large number of hydrological response units. As we specifically focus on acceleration of a single SWAT run, the use of iOMP-SWAT for parameter calibrations will significantly improve the performance of SWAT optimization.

  8. Critical review of the application of SWAT in the upper Nile Basin countries

    Science.gov (United States)

    van Griensven, A.; Ndomba, P.; Yalew, S.; Kilonzo, F.

    2012-03-01

    The Soil and Water Assessment Tool (SWAT) is a hydrological simulation tool that is widely applied within the Nile basin. Up to date, more than 20 peer reviewed papers describe the use of SWAT for a variety of problems in the upper Nile basin countries, such as erosion modeling, land use modeling, climate change impact modeling and water resources management. The majority of the studies are clustered in the tropical highlands in Ethiopia and around Lake Victoria. The popularity of SWAT is attributed to the fact that the tool is freely available and that it is readily applicable through the development of Geographic Information System (GIS) based interfaces and its easy linkage to sensitivity, calibration and uncertainty analysis tools. The online and free availability of basic GIS data that are required for SWAT made its applicability more straight forward even in data scarce areas. However, the easy use of SWAT may not always lead to knowledgeable models. In this paper, we aim at critically reviewing the use of SWAT in the context of the modeling purpose and problem descriptions in the tropical highlands of the Nile Basin countries. A number of criteria are used to evaluate the model set-up, model performances, physical representation of the model parameters, and the correctness of the hydrological model balance. On the basis of performance indicators, the majority of the SWAT models were classified as giving satisfactory to very good results. Nevertheless, the hydrological mass balances as reported in several papers contained losses that might not be justified. Several papers also reported unrealistic parameter values. More worrying is that many papers lack this information. For this reason, it is difficult to give an overall positive evaluation to most of the reported SWAT models. An important gap is the lack of attention that is given to the vegetation and crop processes. None of the papers reported any adaptation to the crop parameters, or any crop related

  9. Critical review of SWAT applications in the upper Nile basin countries

    Directory of Open Access Journals (Sweden)

    A. van Griensven

    2012-09-01

    Full Text Available The Soil and Water Assessment Tool (SWAT is an integrated river basin model that is widely applied within the Nile basin. Up to date, more than 20 peer-reviewed papers describe the use of SWAT for a variety of problems in the upper Nile basin countries, such as erosion modelling, land use and climate change impact modelling and water resources management. The majority of the studies are focused on locations in the tropical highlands in Ethiopia and around Lake Victoria. The popularity of SWAT is attributed to the fact that the tool is freely available and that it is readily applicable through the development of geographic information system (GIS based interfaces and its easy linkage to sensitivity, calibration and uncertainty analysis tools. The online and free availability of basic GIS data that are required for SWAT made its applicability more straightforward even in data-scarce areas. However, the easy use of SWAT may not always lead to appropriate models which is also a consequence of the quality of the available free databases in these regions. In this paper, we aim at critically reviewing the use of SWAT in the context of the modelling purpose and problem descriptions in the tropical highlands of the Nile basin countries. To evaluate the models that are described in journal papers, a number of criteria are used to evaluate the model set-up, model performances, physical representation of the model parameters, and the correctness of the hydrological model balance. On the basis of performance indicators, the majority of the SWAT models were classified as giving satisfactory to very good results. Nevertheless, the hydrological mass balances as reported in several papers contained losses that might not be justified. Several papers also reported the use of unrealistic parameter values. More worrying is that many papers lack this information. For this reason, most of the reported SWAT models have to be evaluated critically. An important gap is

  10. Calibration and Validation of the SWAT2000 Watershed Model for Phosphorus Loading to the Cannonsville Reservoir

    Science.gov (United States)

    Tolson, B. A.; Shoemaker, C. A.

    2002-12-01

    A comprehensive modeling effort was undertaken to simulate phosphorus (P) loading to the Cannonsville Reservoir in upstate New York. The Cannonsville Reservoir is one of the City of New York's drinking water supply reservoirs and drains an 1178 km2 watershed that is predominantly agricultural (dairy farming) and forested. The occurrence of eutrophic conditions in the reservoir, due to excessive P loading, resulted in the reservoir being classified as `phosphorus restricted'. This classification restricts future economic growth in the watershed when the growth directly or indirectly increases P loadings. The Soil and Water Assessment Tool (SWAT2000) was used to model the P loading to the reservoir in order to help investigate the effectiveness of proposed management options for reducing P loading. SWAT2000 is a distributed watershed model developed by the Agricultural Research Service of the United States Department of Agriculture. This study is the first to apply SWAT2000 for P loading predictions in the Northeast US. SWAT2000 model development with respect to P focused initially on developing Cannonsville Watershed specific P inputs. Agricultural practices in the watershed were generalized, initial soil P levels were determined using aggregated watershed-wide soil P test results, manure spreading was based on the available manure masses as projected from local cattle population estimates and manure production characteristics were based on local manure studies. Ten years of daily P loading data were available for calibration and validation of the model. Additional bi-weekly sampling data of surface water P concentrations across the watershed were also utilized to test the spatial performance of the model. Comparison with measured data and further analysis of model equations showed that the model equations for sediment generation under snow melt conditions required modifications. In addition a number of P model parameters required calibration. Calibration results

  11. Modelling streamflow from two small South African experimental catchments using the SWAT model

    Science.gov (United States)

    Govender, M.; Everson, C. S.

    2005-02-01

    Increasing demand for timber products results in the expansion of commercial afforestation in South Africa. The conversion of indigenous seasonally dormant grassland to evergreen forests results in increased transpiration and ultimately a reduction in catchment runoff, creating a negative impact on the country's scarce water supplies. In order to assist managers in the decision-making processes it is important to be able to accurately assess and predict hydrological processes, and the impact that land use change will have on water resources. The Soil and Water Assessment Tool (SWAT) provides a means of performing these assessments. One of the key strengths of the SWAT model lies in its ability to model the relative impacts of changes in management practices, climate and vegetation on water quantity and quality.The aim of this study was to determine if the SWAT model could reasonably simulate hydrological processes in daily time steps from two small South African catchments. To verify the SWAT model a grassland (C VIgrass) and Pinus patula afforested catchment (C IIpine) were selected from the Cathedral Peak hydrological research station in the KwaZulu Natal Drakensberg mountains. These catchments were chosen because of the availability of detailed hydrological records and suitable land use.Observed and simulated streamflow for C VIgrass and C IIpine were compared. When model fits of observed and simulated streamflow for C VIgrass were acceptable, this parameter set was then used in the configuration of C IIpine. Results show that the model performs well for C VIgrass with reasonable agreement between modelled and observed data (R2 = 0.68). Comparisons for C IIpine show a total oversimulation of streamflow for the period 1950 to 1965, with deviations between observed and modelled data increasing from 1959 to 1965, due to the model not accounting for the increase in ET brought about by the maturing pine plantation.

  12. EVA Performance Prediction

    Science.gov (United States)

    Peacock, Brian; Maida, James; Rajulu, Sudhakar

    2004-01-01

    out for EVA activities are based more on extensive domain experience than any formal analytic structure. Conversely, physical task analysis for industrial and structured evidence from training and EV A contexts. Again on earth there is considerable evidence of human performance degradation due to encumbrance and fatigue. These industrial models generally take the form of a discounting equation. The development of performance estimates for space operations, such as timeline predictions for EVA is generally based on specific input from training activity, for example in the NBL or KC135. uniformed services tasks on earth are much more formalized. Human performance data in the space context has two sources: first there is the micro analysis of performance in structured tasks by the space physiology community and second there is the less structured evidence from training and EV A contexts.

  13. Improving the Performance of Temperature Index Snowmelt Model of SWAT by Using MODIS Land Surface Temperature Data

    Science.gov (United States)

    Yang, Yan; Onishi, Takeo; Hiramatsu, Ken

    2014-01-01

    Simulation results of the widely used temperature index snowmelt model are greatly influenced by input air temperature data. Spatially sparse air temperature data remain the main factor inducing uncertainties and errors in that model, which limits its applications. Thus, to solve this problem, we created new air temperature data using linear regression relationships that can be formulated based on MODIS land surface temperature data. The Soil Water Assessment Tool model, which includes an improved temperature index snowmelt module, was chosen to test the newly created data. By evaluating simulation performance for daily snowmelt in three test basins of the Amur River, performance of the newly created data was assessed. The coefficient of determination (R 2) and Nash-Sutcliffe efficiency (NSE) were used for evaluation. The results indicate that MODIS land surface temperature data can be used as a new source for air temperature data creation. This will improve snow simulation using the temperature index model in an area with sparse air temperature observations. PMID:25165746

  14. 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

  15. Soil and Water Assessment Tool (SWAT) Global Applications

    OpenAIRE

    Arnold, J.; Srinivasan, R; Neitsch, S. (ed.); George, C.; Abbaspour, K.; Hao, F.H.; van Griensven, A.; Gosain, A.; Debels, P.; N.W. Kim; Somura, H.; Ella, Victor B.; Leon, L.; Jintrawet, A.; Manuel R. Reyes

    2009-01-01

    Summary: SWAT,the Soil and Water Assessment Tool is a river basin, or watershed, scale model developed to predict the impact of land management practices on water, sediment and agricultural chemical yields in large complex watersheds with varying soils, land use and management conditions over long periods of time. [from the editors' preamble] LTRA-5 (Agroforestry and Sustainable Vegetable Production)

  16. Prediction of mill performance

    Energy Technology Data Exchange (ETDEWEB)

    P.A. Bennett [CoalTech Pty Ltd. (Australia)

    2005-07-01

    This Australian Coal Association Research Program (ACARP) project aimed to demonstrate that the Hardgrove Grindability Index (HGI) coupled with standard Petrographic Analysis can be used to greatly improve the prediction of mill power requirements, mill throughput and product size. The project examined the mill test data from ACIRL's pilot scale vertical spindle mill on 96 coals. A total of 360 mill tests, conducted under a wide range of throughputs, roll pressures and classifier settings, were included into the data set. The mill performance of maceral groups or microlithotypes was assumed to be additive, that is, each maceral group or microlithotype behaved independently and a size fraction of the product PF was the volume weighted sum of the petrographic components of that size fraction. Based on this assumption it was possible to determine the size distribution of the product PF, for a wide range of milling conditions, based solely on petrographic analysis. Microlithotypes were not determined directly but were estimated from the maceral analysis. The size distribution of individual maceral groups or microlithotypes can also be estimated based on developed correlations. Size distribution determined from petrographic analysis proved to be a better estimate than that determined from the HGI. Mill power can be estimated from petrographic analysis, but the HGI was found to be a better predictor of mill power. 19 refs., 4 figs., 1 tab.

  17. Improving SWAT for simulating water and carbon fluxes of forest ecosystems

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Qichun; Zhang, Xuesong

    2016-11-01

    As a widely used watershed model for assessing impacts of anthropogenic and natural disturbances on water quantity and quality, the Soil and Water Assessment Tool (SWAT) has not been extensively tested in simulating water and carbon fluxes of forest ecosystems. Here, we examine SWAT simulations of evapotranspiration (ET), net primary productivity (NPP), net ecosystem exchange (NEE), and plant biomass at ten AmeriFlux forest sites across the U.S. We identify unrealistic radiation use efficiency (Bio_E), large leaf to biomass fraction (Bio_LEAF), and missing phosphorus supply from parent material weathering as the primary causes for the inadequate performance of the default SWAT model in simulating forest dynamics. By further revising the relevant parameters and processes, SWAT’s performance is substantially improved. Based on the comparison between the improved SWAT simulations and flux tower observations, we discuss future research directions for further enhancing model parameterization and representation of water and carbon cycling for forests.

  18. Enabling Large Scale Fine Resolution Flood Modeling Using SWAT and LISFLOOD-FP

    Science.gov (United States)

    Liu, Z.; Rajib, A.; Merwade, V.

    2016-12-01

    Due to computational burden, most large scale hydrologic models are not created to generate streamflow hydrographs for lower order ungauged streams. Similarly, most flood inundation mapping studies are performed at major stream reaches. As a result, it is not possible to get reliable flow estimates and flood extents for vast majority of the areas where no stream gauging stations are available. The objective of this study is to loosely couple spatially distributed hydrologic model, Soil and Water Assessment Tool (SWAT), with a 1D/2D hydrodynamic model, LISFLOOD-FP, for large scale fine resolution flood inundation modeling. The model setup is created for the 491,000 km2 drainage area of the Ohio River Basin in the United States. In the current framework, SWAT model is calibrated with historical streamflow data over the past 80 years (1935-2014) to provide streamflow time-series for more than 100,000 NHDPlus stream reaches in the basin. The post-calibration evaluation shows that the simulated daily streamflow has a Nash-Sutcliffe Efficiency in the range of 0.4-0.7 against observed records across the basin. Streamflow outputs from the calibrated SWAT are subsequently used to drive LISFLOOD-FP and routed along the streams/floodplain using the built-in subgrid solver. LISFLOOD-FP is set up for the Ohio River Basin using 90m digital elevation model, and is executed on high performance computing resources at Purdue University. The flood extents produced by LISFLOOD-FP show good agreement with observed inundation. The current modeling framework lays foundation for near real-time streamflow forecasting and prediction of time-varying flood inundation maps along the NHDPlus network.

  19. Advances in the application of the SWAT model for water resources management

    Science.gov (United States)

    Jayakrishnan, R.; Srinivasan, R.; Santhi, C.; Arnold, J. G.

    2005-02-01

    Developments in computer technology have revolutionized the study of hydrologic systems and water resources management. Several computer-based hydrologic/water quality models have been developed for applications in hydrologic modelling and water resources studies. Distributed parameter models, necessary for basin-scale studies, have large input data requirements. Geographic information systems (GIS) and model-GIS interfaces aid the efficient creation of input data files required by such models. One such model available for the water resources professional is the Soil and Water Assessment Tool (SWAT), a distributed parameter model developed by the United States Department of Agriculture. This paper describes some recent advances made in the application of SWAT and the SWAT-GIS interface for water resources management. Four case studies are presented. The Hydrologic Unit Model for the United States (HUMUS) project used SWAT to conduct a national-scale analysis of the effect of management scenarios on water quantity and quality. Integration of the SWAT model with rainfall data available from the WSR-88D radar network helps us to incorporate the spatial variability of rainfall into the modelling process. This study demonstrates the usefulness of radar rainfall data in distributed hydrologic studies and the potential of SWAT for application in flood analysis and prediction. A hydrologic modelling study of the Sondu river basin in Kenya using SWAT indicates the potential for application of the model in African watersheds and points to the need for development of better model input data sets in Africa, which are critical for detailed water resources studies. The application of SWAT for water quality analysis in the Bosque river basin, Texas demonstrates the strength of the model for analysing different management scenarios to minimize point and non-point pollution, and its potential for application in total maximum daily load (TMDL) studies.

  20. Initial cognitive performance predicts longitudinal aviator performance.

    Science.gov (United States)

    Yesavage, Jerome A; Jo, Booil; Adamson, Maheen M; Kennedy, Quinn; Noda, Art; Hernandez, Beatriz; Zeitzer, Jamie M; Friedman, Leah F; Fairchild, Kaci; Scanlon, Blake K; Murphy, Greer M; Taylor, Joy L

    2011-07-01

    The goal of the study was to improve prediction of longitudinal flight simulator performance by studying cognitive factors that may moderate the influence of chronological age. We examined age-related change in aviation performance in aircraft pilots in relation to baseline cognitive ability measures and aviation expertise. Participants were aircraft pilots (N = 276) aged 40-77.9. Flight simulator performance and cognition were tested yearly; there were an average of 4.3 (± 2.7; range 1-13) data points per participant. Each participant was classified into one of the three levels of aviation expertise based on Federal Aviation Administration pilot proficiency ratings: least, moderate, or high expertise. Addition of measures of cognitive processing speed and executive function to a model of age-related change in aviation performance significantly improved the model. Processing speed and executive function performance interacted such that the slowest rate of decline in flight simulator performance was found in aviators with the highest scores on tests of these abilities. Expertise was beneficial to pilots across the age range studied; however, expertise did not show evidence of reducing the effect of age. These data suggest that longitudinal performance on an important real-world activity can be predicted by initial assessment of relevant cognitive abilities.

  1. Action perception predicts action performance.

    Science.gov (United States)

    Bailey, Heather R; Kurby, Christopher A; Giovannetti, Tania; Zacks, Jeffrey M

    2013-09-01

    Everyday action impairments often are observed in demented older adults, and they are common potential barriers to functional independence. We evaluated whether the ability to segment and efficiently encode activities is related to the ability to execute activities. Further, we evaluated whether brain regions important for segmentation also were important for action performance. Cognitively healthy older adults and those with very mild or mild dementia of the Alzheimer's type watched and segmented movies of everyday activities and then completed the Naturalistic Action Test. Structural MRI was used to measure volume in the dorsolateral prefrontal cortex (DLPFC), medial temporal lobes (MTL), posterior cortex, and anterior cingulate cortex (ACC). Dementia status and the ability to segment everyday activities strongly predicted naturalistic action performance, and MTL volume largely accounted for this relationship. In addition, the current results supported the Omission-Commission Model: Different cognitive and neurological mechanisms predicted different types of action error. Segmentation, dementia severity, and MTL volume predicted everyday omission errors, DLPFC volume predicted commission errors, and ACC volume predicted action additions. These findings suggest that event segmentation may be critical for effective action production, and that the segmentation and production of activities may recruit the same event representation system. © 2013 Elsevier Ltd. All rights reserved.

  2. Analysis of the spatial variation in the parameters of the SWAT model with application in Flanders, Northern Belgium

    Directory of Open Access Journals (Sweden)

    G. Heuvelmans

    2004-01-01

    Full Text Available Operational applications of a hydrological model often require the prediction of stream flow in (future time periods without stream flow observations or in ungauged catchments. Data for a case-specific optimisation of model parameters are not available for such applications, so parameters have to be derived from other catchments or time periods. It has been demonstrated that for applications of the SWAT in Northern Belgium, temporal transfers of the parameters have less influence than spatial transfers on the performance of the model. This study examines the spatial variation in parameter optima in more detail. The aim was to delineate zones wherein model parameters can be transferred without a significant loss of model performance. SWAT was calibrated for 25 catchments that are part of eight larger sub-basins of the Scheldt river basin. Two approaches are discussed for grouping these units in zones with a uniform set of parameters: a single parameter approach considering each parameter separately and a parameter set approach evaluating the parameterisation as a whole. For every catchment, the SWAT model was run with the local parameter optima, with the average parameter values for the entire study region (Flanders, with the zones delineated with the single parameter approach and with the zones obtained by the parameter set approach. Comparison of the model performances of these four parameterisation strategies indicates that both the single parameter and the parameter set zones lead to stream flow predictions that are more accurate than if the entire study region were treated as one single zone. On the other hand, the use of zonal average parameter values results in a considerably worse model fit compared to local parameter optima. Clustering of parameter sets gives a more accurate result than the single parameter approach and is, therefore, the preferred technique for use in the parameterisation of ungauged sub-catchments as part of the

  3. Laser line scan performance prediction

    Science.gov (United States)

    Mahoney, Kevin L.; Schofield, Oscar; Kerfoot, John; Giddings, Tom; Shirron, Joe; Twardowski, Mike

    2007-09-01

    The effectiveness of sensors that use optical measurements for the laser detection and identification of subsurface mines is directly related to water clarity. The primary objective of the work presented here was to use the optical data collected by UUV (Slocum Glider) surveys of an operational areas to estimate the performance of an electro-optical identification (EOID) Laser Line Scan (LLS) system during RIMPAC 06, an international naval exercise off the coast of Hawaii. Measurements of optical backscattering and beam attenuation were made with a Wet Labs, Inc. Scattering Absorption Meter (SAM), mounted on a Rutgers University/Webb Research Slocum glider. The optical data universally indicated extremely clear water in the operational area, except very close to shore. The beam-c values from the SAM sensor were integrated to three attenuation lengths to provide an estimate of how well the LLS would perform in detecting and identifying mines in the operational areas. Additionally, the processed in situ optical data served as near-real-time input to the Electro-Optic Detection Simulator, ver. 3 (EODES-3; Metron, Inc.) model for EOID performance prediction. Both methods of predicting LLS performance suggested a high probability of detection and probability of identification. These predictions were validated by the actual performance of the LLS as the EOID system yielded imagery from which reliable mine identification could be made. Future plans include repeating this work in more optically challenging water types to demonstrate the utility of pre-mission UUV surveys of operational areas as a tactical decision aid for planning EOID missions.

  4. Evaluation of existing and modified wetland equations in the SWAT model

    Science.gov (United States)

    The drainage significantly alters flow and nutrient pathways in small watersheds and reliable simulation at this scale is needed for effective planning of nutrient reduction strategies. The Soil and Water Assessment Tool (SWAT) has been widely utilized for prediction of flow and nutrient loads, but...

  5. Simulation of lateral flow with SWAT

    Science.gov (United States)

    Calibration of the SWAT model for the Goodwater Creek Experimental Watershed (GCEW) showed that percolation through the restrictive claypan layer, lateral flow above that layer, and redistribution of excess moisture up to the ground surface were not correctly simulated. In addition, surface runoff a...

  6. When is query performance prediction effective?

    NARCIS (Netherlands)

    Hauff, C.; Azzopardi, L.

    2009-01-01

    The utility of Query Performance Prediction (QPP) methods is commonly evaluated by reporting correlation coefficients to denote how well the methods perform at predicting the retrieval performance of a set of queries. However, a quintessential question remains unexplored: how strong does the

  7. Rainfall-runoff modelling of Ajay river catchment using SWAT model

    Science.gov (United States)

    Kangsabanik, Subhadip; Murmu, Sneha

    2017-05-01

    The present study is based on SWAT (Soil and Water Assessment Tool) Model which integrates the GIS information with attribute database to estimate the runoff of Ajay River catchment. Soil and Water Assessment Tool (SWAT) is a physically based distributed parameter model which has been developed to predict runoff, erosion, sediment and nutrient transport from agricultural watersheds under different management practices. The SWAT Model works in conjunction with Arc GIS. In the present study the catchment area has been delineated using the DEM (Digital Elevation Model) and then divided into 19 sub-basins. For preparation of landuse map the IRS-P6 LISS-III image has been used and the soil map is extracted from HWSD (Harmonized World Soil Database) Raster world soil map. The sub basins are further divided into 223 HRUs which stands for Hydrological Response Unit. Then by using 30 years of daily rainfall data and daily maximum and minimum temperature data SWAT simulation is done for daily, monthly and yearly basis to find out Runoff for corresponding Rainfall. The coefficient of correlation (r) for rainfall in a period and the corresponding runoff is found to be 0.9419.

  8. Predicting performance : relative importance of students' background and past performance

    NARCIS (Netherlands)

    Stegers-Jager, Karen M.; Themmen, Axel P. N.; Cohen-Schotanus, Janke; Steyerberg, Ewout W.

    ContextDespite evidence for the predictive value of both pre-admission characteristics and past performance at medical school, their relative contribution to predicting medical school performance has not been thoroughly investigated. ObjectivesThis study was designed to determine the relative

  9. Testing predictive performance of binary choice models

    NARCIS (Netherlands)

    A.C.D. Donkers (Bas); B. Melenberg (Bertrand)

    2002-01-01

    textabstractBinary choice models occur frequently in economic modeling. A measure of the predictive performance of binary choice models that is often reported is the hit rate of a model. This paper develops a test for the outperformance of a predictor for binary outcomes over a naive prediction

  10. Assessment of soil erosion risk in Komering watershed, South Sumatera, using SWAT model

    Science.gov (United States)

    Salsabilla, A.; Kusratmoko, E.

    2017-07-01

    Changes in land use watershed led to environmental degradation. Estimated loss of soil erosion is often difficult due to some factors such as topography, land use, climate and human activities. This study aims to predict soil erosion hazard and sediment yield using the Soil and Water Assessment Tools (SWAT) hydrological model. The SWAT was chosen because it can simulate the model with limited data. The study area is Komering watershed (806,001 Ha) in South Sumatera Province. There are two factors land management intervention: 1) land with agriculture, and 2) land with cultivation. These factors selected in accordance with the regulations of spatial plan area. Application of the SWAT demonstrated that the model can predict surface runoff, soil erosion loss and sediment yield. The erosion risk for each watershed can be classified and predicted its changes based on the scenarios which arranged. In this paper, we also discussed the relationship between the distribution of erosion risk and watershed's characteristics in a spatial perspective.

  11. PREDICTING PERFORMANCE OF WEB SERVICES USING SMTQA

    OpenAIRE

    Ch Ram Mohan Reddy; D Evangelin Geetha; KG Srinivasa; T V Suresh Kumar; K Rajani Kanth

    2011-01-01

    Web Service is an interface which implements business logic. Performance is an important quality aspect of Web services because of their distributed nature. Predicting the performance of web services during early stages of software development is significant. In this paper we model web service using Unified Modeling Language, Use Case Diagram, Sequence Diagram. We obtain the Performance metrics by simulating the web services model using a simulation tool Simulation of Multi-Tie...

  12. Early Performance Prediction of Web Services

    OpenAIRE

    Reddy, Ch Ram Mohan; Geetha, D. Evangelin; Srinivasa, K. G.; Kumar, T. V. Suresh; Kanth, K. Rajani

    2012-01-01

    Web Service is an interface which implements business logic. Performance is an important quality aspect of Web services because of their distributed nature. Predicting the performance of web services during early stages of software development is significant. In this paper we model web service using Unified Modeling Language, Use Case Diagram, Sequence Diagram, Deployment Diagram. We obtain the Performance metrics by simulating the web services model using a simulation tool Simulation of Mult...

  13. 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

  14. Strategic consensus predicting outputs of team performance

    OpenAIRE

    Puente-Palacios,Katia; Moreira, Tatiana; Puente, Tamara; Lira, Naianne

    2014-01-01

    Strategic consensus in work teams is a group process related to the shared comprehension among team members of the strategies defined to attain work goals. This study aimedto verify the predictive power of strategic consensus in relation to team performance. The prediction model was constructed based on data collected from teachers and coordi-nators of 70 educational institutions in Ecuador. The individual data were aggregated per institution to obtain group level scores. The results indicate...

  15. 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.

  16. Predicting residents' performance: A prospective study

    Directory of Open Access Journals (Sweden)

    Ozuah Philip O

    2002-07-01

    Full Text Available Abstract Background Objective criteria for predicting residents' performance do not exist. The purpose of this study was to test the hypothesis that global assessment by an intern selection committee (ISC would correlate with the future performance of residents. Methods A prospective study of 277 residents between 1992 and 1999. Global assessment at the time of interview was compared to subsequent clinical (assessed by chief residents and cognitive performance (assessed by the American Board of Pediatrics in-service training examination. Results ISC ratings correlated significantly with clinical performance at 24 and 36 months of training (r = 0.58, P st, 2nd, and 3rd years of training (r = 0.35, P = .0016; r = 0.39, P = 0.0003; r = 0.50, P = 0.005 respectively. Conclusions Global assessment by an ISC predicted residents' clinical and cognitive performances.

  17. What predicts performance during clinical psychology training?

    Science.gov (United States)

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

    2014-06-01

    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. Longitudinal cross-sectional study using prospective and retrospective data. Characteristics at application were analysed in relation to a range of in-course assessments for 274 trainee clinical psychologists who had completed or were in the final stage of their training. Trainees were diverse in age, pre-training experience, and academic performance at A-level (advanced level certificate required for university admission), but not in gender or ethnicity. Failure rates across the three performance domains (academic, clinical, research) were very low, suggesting that selection was successful in screening out less suitable candidates. Key predictors of good performance on the course were better A-levels and better degree class. Non-white students performed less well on two outcomes. Type and extent of pre-training clinical experience on outcomes had varied effects on outcome. Research supervisor ratings emerged as global indicators and predicted nearly all outcomes, but may have been biased as they were retrospective. Referee ratings predicted only one of the seven outcomes examined, and interview ratings predicted none of the outcomes. Predicting who will do well or poorly in clinical psychology training is complex. Interview and referee ratings may well be successful in screening out unsuitable candidates, but appear to be a poor guide to performance on the course. © 2013 The Authors. British Journal of Clinical Psychology published by John Wiley & Sons Ltd on behalf of the British Psychological Society.

  18. Why Do Spatial Abilities Predict Mathematical Performance?

    Science.gov (United States)

    Tosto, Maria Grazia; Hanscombe, Ken B.; Haworth, Claire M. A.; Davis, Oliver S. P.; Petrill, Stephen A.; Dale, Philip S.; Malykh, Sergey; Plomin, Robert; Kovas, Yulia

    2014-01-01

    Spatial ability predicts performance in mathematics and eventual expertise in science, technology and engineering. Spatial skills have also been shown to rely on neuronal networks partially shared with mathematics. Understanding the nature of this association can inform educational practices and intervention for mathematical underperformance.…

  19. What predicts performance during clinical psychology training?

    Science.gov (United States)

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

    2014-01-01

    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 range of in-course assessments for 274 trainee clinical psychologists who had completed or were in the final stage of their training. Results Trainees were diverse in age, pre-training experience, and academic performance at A-level (advanced level certificate required for university admission), but not in gender or ethnicity. Failure rates across the three performance domains (academic, clinical, research) were very low, suggesting that selection was successful in screening out less suitable candidates. Key predictors of good performance on the course were better A-levels and better degree class. Non-white students performed less well on two outcomes. Type and extent of pre-training clinical experience on outcomes had varied effects on outcome. Research supervisor ratings emerged as global indicators and predicted nearly all outcomes, but may have been biased as they were retrospective. Referee ratings predicted only one of the seven outcomes examined, and interview ratings predicted none of the outcomes. Conclusions Predicting who will do well or poorly in clinical psychology training is complex. Interview and referee ratings may well be successful in screening out unsuitable candidates, but appear to be a poor guide to performance on the course. Practitioner points While referee and selection interview ratings did not predict performance during training, they may be useful in screening out unsuitable candidates at the application stage High school final academic performance

  20. 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.

  1. Modelling the predictive performance of credit scoring

    Directory of Open Access Journals (Sweden)

    Shi-Wei Shen

    2013-02-01

    Full Text Available Orientation: The article discussed the importance of rigour in credit risk assessment.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.

  2. Modelling water-harvesting systems in the arid south of Tunisia using SWAT

    Directory of Open Access Journals (Sweden)

    M. Ouessar

    2009-10-01

    Full Text Available In many arid countries, runoff water-harvesting systems support the livelihood of the rural population. Little is known, however, about the effect of these systems on the water balance components of arid watersheds. The objective of this study was to adapt and evaluate the GIS-based watershed model SWAT (Soil Water Assessment Tool for simulating the main hydrologic processes in arid environments. The model was applied to the 270-km2 watershed of wadi Koutine in southeast Tunisia, which receives about 200 mm annual rain. The main adjustment for adapting the model to this dry Mediterranean environment was the inclusion of water-harvesting systems, which capture and use surface runoff for crop production in upstream subbasins, and a modification of the crop growth processes. The adjusted version of the model was named SWAT-WH. Model evaluation was performed based on 38 runoff events recorded at the Koutine station between 1973 and 1985. The model predicted that the average annual watershed rainfall of the 12-year evaluation period (209 mm was split into ET (72%, groundwater recharge (22% and outflow (6%. The evaluation coefficients for calibration and validation were, respectively, R2 (coefficient of determination 0.77 and 0.44; E (Nash-Sutcliffe coefficient 0.73 and 0.43; and MAE (Mean Absolute Error 2.6 mm and 3.0 mm, indicating that the model could reproduce the observed events reasonably well. However, the runoff record was dominated by two extreme events, which had a strong effect on the evaluation criteria. Discrepancies remained mainly due to uncertainties in the observed daily rainfall and runoff data. Recommendations for future research include the installation of additional rainfall and runoff gauges with continuous data logging and the collection of more field data to represent the soils and land use. In addition, crop growth and yield monitoring is needed for a proper evaluation of crop production, to

  3. Soil Water and Temperature System (SWATS) Handbook

    Energy Technology Data Exchange (ETDEWEB)

    Bond, D

    2005-01-01

    The soil water and temperature system (SWATS) provides vertical profiles of soil temperature, soil-water potential, and soil moisture as a function of depth below the ground surface at hourly intervals. The temperature profiles are measured directly by in situ sensors at the Central Facility and many of the extended facilities of the SGP climate research site. The soil-water potential and soil moisture profiles are derived from measurements of soil temperature rise in response to small inputs of heat. Atmospheric scientists use the data in climate models to determine boundary conditions and to estimate the surface energy flux. The data are also useful to hydrologists, soil scientists, and agricultural scientists for determining the state of the soil.

  4. Predicting motor learning performance from Electroencephalographic data.

    Science.gov (United States)

    Meyer, Timm; Peters, Jan; Zander, Thorsten O; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

    2014-03-04

    Research on the neurophysiological correlates of visuomotor integration and learning (VMIL) has largely focused on identifying learning-induced activity changes in cortical areas during motor execution. While such studies have generated valuable insights into the neural basis of VMIL, little is known about the processes that represent the current state of VMIL independently of motor execution. Here, we present empirical evidence that a subject's performance in a 3D reaching task can be predicted on a trial-to-trial basis from pre-trial electroencephalographic (EEG) data. This evidence provides novel insights into the brain states that support successful VMIL. Six healthy subjects, attached to a seven degrees-of-freedom (DoF) robot with their right arm, practiced 3D reaching movements in a virtual space, while an EEG recorded their brain's electromagnetic field. A random forest ensemble classifier was used to predict the next trial's performance, as measured by the time needed to reach the goal, from pre-trial data using a leave-one-subject-out cross-validation procedure. The learned models successfully generalized to novel subjects. An analysis of the brain regions, on which the models based their predictions, revealed areas matching prevalent motor learning models. In these brain areas, the α/μ frequency band (8-14 Hz) was found to be most relevant for performance prediction. VMIL induces changes in cortical processes that extend beyond motor execution, indicating a more complex role of these processes than previously assumed. Our results further suggest that the capability of subjects to modulate their α/μ bandpower in brain regions associated with motor learning may be related to performance in VMIL. Accordingly, training subjects in α/μ-modulation, e.g., by means of a brain-computer interface (BCI), may have a beneficial impact on VMIL.

  5. Sensitivity of different satellites gridded data over Brahmaputra Basin byusing Soil and Water Assessment Tool (SWAT)

    Science.gov (United States)

    Paul, S.; Pradhanang, S. M.; Islam, A. S.

    2016-12-01

    More than half a billion people of India, China, Nepal, Bangladesh and Bhutan are dependent on the water resources of the Brahmaputra river. With climatic and anthropogenic change of this basin region is becoming a cause of concern for future water management and sharing with transboundary riparian nations. To address such issues, robust watershed runoff modeling of the basin is essential. Soil and Water Assessment Tool (SWAT) is a widely used semi-distributed watershed model that is capable of analyzing surface runoff, stream flow, water yield, sediment and nutrient transport in a large river basin such as Brahmaputra, but the performance of runoff the model depends on the accuracy of input precipitation datasets. But for a transboundary basin like Brahmaputra, precipitation gauge data from upstream areas is either not available or not accessible to the scientific communities. Satellite rainfall products are very effective where radar datasets are absent and conventional rain gauges are sparse. However, the sensitivity of the SWAT model to different satellite data products as well as hydrologic parameters for the Brahmaputra Basin are largely unknown. Thus in this study, a comparative analysis with different satellite data product has been made to assess the runoff using SWAT model. Here, datafrom three sources: TRMM, APHRDOTIE and GPCP were used as input precipitation satellite data set and ERA-Interim was used as input temperature dataset from 1998 to 2009. The main methods used in modeling the hydrologic processes in SWAT were curve number method for runoff estimating, Penman-Monteith method for PET and Muskingum method for channel routing. Our preliminary results have revealed thatthe TRMM data product is more accurate than APHRODITE and GPCP for runoff analysis. The coefficient of determination (R2) and Nash-Sutcliffe efficiencies for both calibration and validation period from TRMM data are 0.83 and 0.72, respectively.

  6. Predicting performance: relative importance of students' background and past performance.

    Science.gov (United States)

    Stegers-Jager, Karen M; Themmen, Axel P N; Cohen-Schotanus, Janke; Steyerberg, Ewout W

    2015-09-01

    Despite evidence for the predictive value of both pre-admission characteristics and past performance at medical school, their relative contribution to predicting medical school performance has not been thoroughly investigated. This study was designed to determine the relative importance of pre-admission characteristics and past performance in medical school in predicting student performance in pre-clinical and clinical training. This longitudinal prospective study followed six cohorts of students admitted to a Dutch, 6-year, undergraduate medical course during 2002-2007 (n = 2357). Four prediction models were developed using multivariate logistic regression analysis. Main outcome measures were 'Year 1 course completion within 1 year' (models 1a, 1b), 'Pre-clinical course completion within 4 years' (model 2) and 'Achievement of at least three of five clerkship grades of ≥ 8.0' (model 3). Pre-admission characteristics (models 1a, 1b, 2, 3) and past performance at medical school (models 1b, 2, 3) were included as predictor variables. In model 1a - including pre-admission characteristics only - the strongest predictor for Year 1 course completion was pre-university grade point average (GPA). Success factors were 'selected by admission testing' and 'age > 21 years'; risk factors were 'Surinamese/Antillean background', 'foreign pre-university degree', 'doctor parent' and male gender. In model 1b, number of attempts and GPA at 4 months were the strongest predictors for Year 1 course completion, and male gender remained a risk factor. Year 1 GPA was the strongest predictor for pre-clinical course completion, whereas being male or aged 19-21 years were risk factors. Pre-clinical course GPA positively predicted clinical performance, whereas being non-Dutch or a first-generation university student were important risk factors for lower clinical grades. Nagelkerke's R(2) ranged from 0.16 to 0.62. This study not only confirms the importance of past performance as a predictor

  7. Advancing computational methods for calibration of the Soil and Water Assessment Tool (SWAT): Application for modeling climate change impacts on water resources in the Upper Neuse Watershed of North Carolina

    Science.gov (United States)

    Ercan, Mehmet Bulent

    Watershed-scale hydrologic models are used for a variety of applications from flood prediction, to drought analysis, to water quality assessments. A particular challenge in applying these models is calibration of the model parameters, many of which are difficult to measure at the watershed-scale. A primary goal of this dissertation is to contribute new computational methods and tools for calibration of watershed-scale hydrologic models and the Soil and Water Assessment Tool (SWAT) model, in particular. SWAT is a physically-based, watershed-scale hydrologic model developed to predict the impact of land management practices on water quality and quantity. The dissertation follows a manuscript format meaning it is comprised of three separate but interrelated research studies. The first two research studies focus on SWAT model calibration, and the third research study presents an application of the new calibration methods and tools to study climate change impacts on water resources in the Upper Neuse Watershed of North Carolina using SWAT. The objective of the first two studies is to overcome computational challenges associated with calibration of SWAT models. The first study evaluates a parallel SWAT calibration tool built using the Windows Azure cloud environment and a parallel version of the Dynamically Dimensioned Search (DDS) calibration method modified to run in Azure. The calibration tool was tested for six model scenarios constructed using three watersheds of increasing size (the Eno, Upper Neuse, and Neuse) for both a 2 year and 10 year simulation duration. Leveraging the cloud as an on demand computing resource allowed for a significantly reduced calibration time such that calibration of the Neuse watershed went from taking 207 hours on a personal computer to only 3.4 hours using 256 cores in the Azure cloud. The second study aims at increasing SWAT model calibration efficiency by creating an open source, multi-objective calibration tool using the Non

  8. 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.

  9. Development of stream-subsurface flow module in sub-daily simulation of Escherichia coli using SWAT

    Science.gov (United States)

    Kim, Minjeong; Boithias, Laurie; Cho, Kyung Hwa; Silvera, Norbert; Thammahacksa, Chanthamousone; Latsachack, Keooudone; Rochelle-Newall, Emma; Sengtaheuanghoung, Oloth; Pierret, Alain; Pachepsky, Yakov A.; Ribolzi, Olivier

    2017-04-01

    Water contaminated with pathogenic bacteria poses a large threat to public health, especially in the rural areas in the tropics where sanitation and drinking water facilities are often lacking. Several studies have used the Soil and Water Assessment Tool (SWAT) to predict the export of in-stream bacteria at a watershed-scale. However, SWAT is limited to in-stream processes, such as die-off, resuspension and, deposition; and it is usually implemented on a daily time step using the SCS Curve Number method, making it difficult to explore the dynamic fate and transport of bacteria during short but intense events such as flash floods in tropical humid montane headwaters. To address these issues, this study implemented SWAT on an hourly time step using the Green-Ampt infiltration method, and tested the effects of subsurface flow (LATQ+GWQ in SWAT) on bacterial dynamics. We applied the modified SWAT model to the 60-ha Houay Pano catchment in Northern Laos, using sub-daily rainfall and discharge measurements, electric conductivity-derived fractions of overland and subsurface flows, suspended sediments concentrations, and the number of fecal indicator organism Escherichia coli monitored at the catchment outlet from 2011 to 2013. We also took into account land use change by delineating the watershed with the 3-year composite land use map. The results show that low subsurface flow of less than 1 mm recovered the underestimation of E. coli numbers during the dry season, while high subsurface flow caused an overestimation during the wet season. We also found that it is more reasonable to apply the stream-subsurface flow interaction to simulate low in-stream bacteria counts. Using fecal bacteria to identify and understand the possible interactions between overland and subsurface flows may well also provide some insight into the fate of other bacteria, such as those involved in biogeochemical fluxes both in-stream and in the adjacent soils and hyporheic zones.

  10. 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

  11. Introducing a new open source GIS user interface for the SWAT model

    Science.gov (United States)

    The Soil and Water Assessment Tool (SWAT) model is a robust watershed modelling tool. It typically uses the ArcSWAT interface to create its inputs. ArcSWAT is public domain software which works in the licensed ArcGIS environment. The aim of this paper was to develop an open source user interface ...

  12. 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.

  13. Analysis and performance prediction of Stirling cryogenerator

    Science.gov (United States)

    Ghosh, R.; Atrey, M. D.; Narayankhedkar, K. G.

    2002-05-01

    The ratio of swept volume of the compression space to the swept volume of the expansion space is an important design parameter for the Stirling cryogenerator. The swept volume ratio can be varied by changing diameter either of the piston, displacer or both of them. In this paper cyclic simulation of Stirling cycle has been carried out to predict the performance of a Stirling cryogenerator for varying swept volume ratios. The dimensions of other components like cooler, regenerator and condenser are kept constant. For a given diameter of the displacer, piston diameter has been optimized based on COP. Also, an attempt has been made to find the optimum combination of piston and displacer diameters for optimum COP of the cryogenerator. The results can be extended to find out the best combination of the piston and the displacer diameters for a given refrigerating load.

  14. SWAT use of gridded observations for simulating runoff – a Vietnam river basin study

    Directory of Open Access Journals (Sweden)

    M. T. Vu

    2012-08-01

    Full Text Available Many research studies that focus on basin hydrology have applied the SWAT model using station data to simulate runoff. But over regions lacking robust station data, there is a problem of applying the model to study the hydrological responses. For some countries and remote areas, the rainfall data availability might be a constraint due to many different reasons such as lacking of technology, war time and financial limitation that lead to difficulty in constructing the runoff data. To overcome such a limitation, this research study uses some of the available globally gridded high resolution precipitation datasets to simulate runoff. Five popular gridded observation precipitation datasets: (1 Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources (APHRODITE, (2 Tropical Rainfall Measuring Mission (TRMM, (3 Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIANN, (4 Global Precipitation Climatology Project (GPCP, (5 a modified version of Global Historical Climatology Network (GHCN2 and one reanalysis dataset, National Centers for Environment Prediction/National Center for Atmospheric Research (NCEP/NCAR are used to simulate runoff over the Dak Bla river (a small tributary of the Mekong River in Vietnam. Wherever possible, available station data are also used for comparison. Bilinear interpolation of these gridded datasets is used to input the precipitation data at the closest grid points to the station locations. Sensitivity Analysis and Auto-calibration are performed for the SWAT model. The Nash-Sutcliffe Efficiency (NSE and Coefficient of Determination (R2 indices are used to benchmark the model performance. Results indicate that the APHRODITE dataset performed very well on a daily scale simulation of discharge having a good NSE of 0.54 and R2 of 0.55, when compared to the discharge simulation using station data (0

  15. Changes in Memory Prediction Accuracy: Age and Performance Effects

    Science.gov (United States)

    Pearman, Ann; Trujillo, Amanda

    2013-01-01

    Memory performance predictions are subjective estimates of possible memory task performance. The purpose of this study was to examine possible factors related to changes in word list performance predictions made by younger and older adults. Factors included memory self-efficacy, actual performance, and perceptions of performance. The current study…

  16. SWATS: Diurnal Trends in the Soil Temperature Report

    Energy Technology Data Exchange (ETDEWEB)

    Cook, David [Argonne National Lab. (ANL), Argonne, IL (United States); Theisen, Adam [Univ. of Oklahoma, Norman, OK (United States)

    2017-06-30

    During the processing of data for the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility ARMBE2D Value-Added Product (VAP), the developers noticed that the SWATS soil temperatures did not show a decreased temporal variability with increased depth with the new E30+ Extended Facilities (EFs), unlike the older EFs at ARM’s Southern Great Plains (SGP) site. The instrument mentor analyzed the data and reported that all SWATS locations have shown this behavior but that the magnitude of the problem was greatest at EFs E31-E38. The data were analyzed to verify the initial assessments of: 1. 5 cm SWATS data were valid for all EFs and 15 cm soil temperature measurements were valid at all EFs other than E31-E38, 2. Use only nighttime SWATS soil temperature measurements to calculate daily average soil temperatures, 3. Since it seems likely that the soil temperature measurements below 15cm were affected by the solar heating of the enclosure at all but E31-38, and at all depths below 5cm at E31-38, individual measurements of soil temperature at these depths during daylight hours, and daily averages of the same, can ot be trusted on most (particularly sunny) days.

  17. Residues of cypermethrin and endosulfan in soils of Swat valley

    Directory of Open Access Journals (Sweden)

    M. Nafees

    2009-05-01

    Full Text Available Swat Valley was studied for two widely used pesticides; cypermethrin and endosulfan. A total of 63 soil samples were collected from 27 villages selected for this purpose. The collected soil samples were extracted with n-hexane, pesticides were separated, identified and quantified by a GC-ECD system. Endosulfan was 0.24 - 1.51 mg kg-1 and 0.13 - 12.67 mg kg-1 in rainfed and irrigated areas, respectively. The residual level of cypermethrin was comparatively high with a level of0.14 to 27.62 mg kg-1 and 0.05 to 73.75 mg kg-1 in rainfed and irrigated areas, respectively. For assessing the possible causes of pesticide residues in soil, 360 farmers were interviewed. It was found that both, cypermethrin and endosulfan, apart from agriculture were also widely misused for fishing in the entire stretch of River Swat and its tributaries. River Swat is used for irrigation in Swat Valley and this wide misuse of pesticides can also contribute to pesticide residue in soil.

  18. Malnutrition amongst Under-Five Years Children in Swat, Pakistan ...

    African Journals Online (AJOL)

    ... The incidence of malnutrition is about the same for both male and female children. Risk factors for malnutrition in the children include lack of education, teenage pregnancy, lack of immunization, and large family size. Keywords: Malnutrition, Gomezfs classification, Weaning time, Risk factors, Teenage pregnancy, Swat ...

  19. Fecal bacteria source characterization and sensitivity analysis of SWAT 2005

    Science.gov (United States)

    The Soil and Water Assessment Tool (SWAT) version 2005 includes a microbial sub-model to simulate fecal bacteria transport at the watershed scale. The objectives of this study were to demonstrate methods to characterize fecal coliform bacteria (FCB) source loads and to assess the model sensitivity t...

  20. Modeling seasonal variability of fecal coliform in natural surface waters using the modified SWAT

    Science.gov (United States)

    Cho, Kyung Hwa; Pachepsky, Yakov A.; Kim, Minjeong; Pyo, JongCheol; Park, Mi-Hyun; Kim, Young Mo; Kim, Jung-Woo; Kim, Joon Ha

    2016-04-01

    Fecal coliforms are indicators of pathogens and thereby, understanding of their fate and transport in surface waters is important to protect drinking water sources and public health. We compiled fecal coliform observations from four different sites in the USA and Korea and found a seasonal variability with a significant connection to temperature levels. In all observations, fecal coliform concentrations were relatively higher in summer and lower during the winter season. This could be explained by the seasonal dominance of growth or die-off of bacteria in soil and in-stream. Existing hydrologic models, however, have limitations in simulating the seasonal variability of fecal coliform. Soil and in-stream bacterial modules of the Soil and Water Assessment Tool (SWAT) model are oversimplified in that they exclude simulations of alternating bacterial growth. This study develops a new bacteria subroutine for the SWAT in an attempt to improve its prediction accuracy. We introduced critical temperatures as a parameter to simulate the onset of bacterial growth/die-off and to reproduce the seasonal variability of bacteria. The module developed in this study will improve modeling for environmental management schemes.

  1. Prediction of College Performance of Superior Students.

    Science.gov (United States)

    Roberts, Roy J.

    1965-01-01

    Using 857 male National Merit Finalists and Commended Students, scales to predict 1st year college grades and science, writing, art, music, speech, and leadership achievement were developed by analysis of 906 pre-college questionnaire items. Two item analysis strategies were used: responses of achieving subjects (S's) and general samples of…

  2. The Economic Benefits of Predicting Job Performance

    Science.gov (United States)

    1989-09-01

    Estim ated A ttrition Effects ....................................................... 3-41 4. Estimated Recruiting Costs...Assumptions .............................. 3-39 3.15 Logistic Regression Coefficient Estimates Used to Predict A ttrition E ffects...linearly with ever-increasing increments of high aptitude employees : the law of diminishing returns eventually applies. For example, if there are too many

  3. Predicting Product Performance with Social Media

    Directory of Open Access Journals (Sweden)

    Liviu LICA

    2011-01-01

    Full Text Available Last 20 years brought massive growth in IT&C world. Mobile solutions such as netbooks, laptops, mobile phones, tablets enable the wireless connection to the Internet. Anyone can ac-cess it anytime and anywhere. In this context, a part of the activities from the real world have a correspondence in the online discussions. Social media in general and social networks in particular have turned into marketing tools for organizations and a place where people can express their opinions and attitudes about products.The paper shows how social media can be used for predicting the success of a product or service. To showcase this, two case studies are presented; a test to prove that the conversations that take place in social media are a good indicator of success and the second is an exercise to predict the winner of the Oscar for best picture in 2011.

  4. 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

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

    OpenAIRE

    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 bridging program. Many Dutch universities set up bridging programs that aim to prepare students with non-university degrees in the Netherlands for Master’s programs at the university level. Some univ...

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

    African Journals Online (AJOL)

    cce

    performance level was generally low in both examinations, it was recommended that the. State government should intensify ..... analysis. Table 11: Output of the Multiple Regression Analysis. Predictor. Variables. Credit. Perf. 2003. SSCE. English. Credit. Perf. 2003. SSCE. Math. Credit. Perf. 2003. SSCE. Physics. Credit.

  7. Predictability of steer performance in the feedlot

    African Journals Online (AJOL)

    biological type on postweaning feedlot performance and carcass traits. Animal Science Research Report. Oklahoma State. University, Stillwater, p. 47. HUTCHESON, D.P., 1982. Observations on receiving new cattle. In: Beef cattle research in Texas. Texas A & M University,. College Station, p. 39. MEISSNER, H.H., 1977.

  8. A comparison of user and system query performance predictions

    NARCIS (Netherlands)

    Hauff, C.; Kelly, Diane; Azzopardi, Leif

    2010-01-01

    Query performance prediction methods are usually applied to estimate the retrieval effectiveness of queries, where the evaluation is largely system sided. However, little work has been conducted to understand query performance prediction from the user's perspective. The question we consider is,

  9. 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

  10. Alpine Skiing Recommendation Tool and Performance Prediction

    Directory of Open Access Journals (Sweden)

    Camille Brousseau

    2018-02-01

    Full Text Available Selecting appropriate skis remains a difficult task for many customers due to the lack of information provided on the bending and torsional stiffnesses of these products. This work investigates how these mechanical properties influence the on-snow ski performance and how an individual skier profile is related to its preferred mechanical properties. To do so, twelve skis were manufactured to exhibit large variations in stiffnesses. Twenty-three skiers provided on-snow feedback and skier profiles through a questionnaire. Simple and multivariable linear correlation analyses were carried out between the skier profile data, their evaluations of the skis and the stiffnesses of the skis. Strong relationships were found between the properties of the skis and some performance criteria, and between the profile of the skiers and the properties of their favourite skis. With further testing, these relationships could be used to design personalized recommendation tools or to guide the design of custom skis.

  11. Predicting unit performance by assessing transformational and transactional leadership.

    Science.gov (United States)

    Bass, Bernard M; Avolio, Bruce J; Jung, Dong I; Berson, Yair

    2003-04-01

    How do leadership ratings collected from units operating under stable conditions predict subsequent performance of those units operating under high stress and uncertainty? To examine this question, the authors calculated the predictive relationships for the transformational and transactional leadership of 72 light infantry rifle platoon leaders for ratings of unit potency, cohesion, and performance for U.S. Army platoons participating in combat simulation exercises. Both transformational and transactional contingent reward leadership ratings of platoon leaders and sergeants positively predicted unit performance. The relationship of platoon leadership to performance was partially mediated through the unit's level of potency and cohesion. Implications, limitations, and future directions for leadership research are discussed.

  12. Predicted thermal performance of triple vacuum glazing

    Energy Technology Data Exchange (ETDEWEB)

    Fang, Yueping; Hyde, Trevor J.; Hewitt, Neil [School of the Built Environment, University of Ulster, N. Ireland (United Kingdom)

    2010-12-15

    The simulated triple vacuum glazing (TVG) consists of three 4 mm thick glass panes with two vacuum gaps, with each internal glass surface coated with a low-emittance coating with an emittance of 0.03. The two vacuum gaps are sealed by an indium based sealant and separated by a stainless steel pillar array with a height of 0.12 mm and a pillar diameter of 0.3 mm spaced at 25 mm. The thermal transmission at the centre-of-glazing area of the TVG was predicted to be 0.26 W m{sup -2} K{sup -1}. The simulation results show that although the thermal conductivity of solder glass (1 W m{sup -1} K{sup -1}) and indium (83.7 W m{sup -1} K{sup -1}) are very different, the difference in thermal transmission of TVGs resulting from the use of an indium and a solder glass edge seal was 0.01 W m{sup -2} K{sup -1}. This is because the edge seal is so thin (0.12 mm), consequently there is a negligible temperature drop across it irrespective of the material that the seal is made from relative to the total temperature difference across the glazing. The results also show that there is a relatively large increase in the overall thermal conductance of glazings without a frame when the width of the indium edge seal is increased. Increasing the rebate depth in a solid wood frame decreased the heat transmission of the TVG. The overall heat transmission of the simulated 0.5 m by 0.5 m TVG was 32.6% greater than that of the 1 m by 1 m TVG, since heat conduction through the edge seal of the small glazing has a larger contribution to the total glazing heat transfer than that of the larger glazing system. (author)

  13. Numerical modeling capabilities to predict repository performance

    Energy Technology Data Exchange (ETDEWEB)

    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.

  14. Personality predicts prospective memory task performance: an adult lifespan study.

    Science.gov (United States)

    Cuttler, Carrie; Graf, Peter

    2007-06-01

    Do interindividual differences in prospective memory task performance reflect individual differences in personality and lifestyle? Do the cognitive abilities known to change with age retain their power to predict episodic prospective memory task performance after controlling for personality and lifestyle variables, and do personality and lifestyle variables offer predictive power apart from that provided by cognitive ability measures? To answer these questions, we conducted a study with community-living healthy individuals (n= 141) between 18 and 81 years of age. They completed three different episodic prospective memory tasks--two laboratory tasks and one field task--as well as various measures of personality, lifestyle, and cognitive ability. The results indicated that personality and lifestyle reliably predicted who will succeed and who will fail on all three episodic prospective memory tasks. Conscientiousness predicted performance on two of the prospective memory tasks; socially prescribed perfectionism and neuroticism each predicted performance on one of the prospective memory tasks. Cognitive ability predicted performance on one of the laboratory prospective memory tasks but not on the other two prospective memory tasks. After we controlled for individual differences in personality and lifestyle variables, cognitive ability was no longer able to predict performance on the laboratory prospective memory task. By contrast, controlling for cognitive ability had no influence on the predictive power of the personality and lifestyle variables.

  15. A multivariable approach toward predicting dental motor skill performance.

    Science.gov (United States)

    Wilson, S G; Husak, W S

    1988-08-01

    The purpose of the present study was to examine the potential of a multivariable approach in predicting dental motor skill performance. Variables measuring cognitive knowledge, motor abilities, educational background, and family demographics were examined. Data were obtained from 33 first-year dental students. Scaling and root planing tests were administered to each student at the beginning and end of a 14-week preclinical periodontal course. Correlations were low and no variable significantly predicted pre- or posttest scaling and root planing performance. Results are discussed in terms of the problems associated with predicting motor performance.

  16. An improved SWAT vegetation growth module and its evaluation for four tropical ecosystems

    Science.gov (United States)

    Alemayehu, Tadesse; van Griensven, Ann; Taddesse Woldegiorgis, Befekadu; Bauwens, Willy

    2017-09-01

    The Soil and Water Assessment Tool (SWAT) is a globally applied river basin ecohydrological model used in a wide spectrum of studies, ranging from land use change and climate change impacts studies to research for the development of the best water management practices. However, SWAT has limitations in simulating the seasonal growth cycles for trees and perennial vegetation in the tropics, where rainfall rather than temperature is the dominant plant growth controlling factor. Our goal is to improve the vegetation growth module of SWAT for simulating the vegetation variables - such as the leaf area index (LAI) - for tropical ecosystems. Therefore, we present a modified SWAT version for the tropics (SWAT-T) that uses a straightforward but robust soil moisture index (SMI) - a quotient of rainfall (P) and reference evapotranspiration (ETr) - to dynamically initiate a new growth cycle within a predefined period. Our results for the Mara Basin (Kenya/Tanzania) show that the SWAT-T-simulated LAI corresponds well with the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI for evergreen forest, savanna grassland and shrubland. This indicates that the SMI is reliable for triggering a new annual growth cycle. The water balance components (evapotranspiration and streamflow) simulated by the SWAT-T exhibit a good agreement with remote-sensing-based evapotranspiration (ET-RS) and observed streamflow. The SWAT-T model, with the proposed vegetation growth module for tropical ecosystems, can be a robust tool for simulating the vegetation growth dynamics in hydrologic models in tropical regions.

  17. SWATMOD-PREP: Graphical user interface for preparing coupled SWAT-modflow simulations

    Science.gov (United States)

    This paper presents SWATMOD-Prep, a graphical user interface that couples a SWAT watershed model with a MODFLOW groundwater flow model. The interface is based on a recently published SWAT-MODFLOW code that couples the models via mapping schemes. The spatial layout of SWATMOD-Prep guides the user t...

  18. 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.

  19. Predictive Variables of Half-Marathon Performance for Male Runners.

    Science.gov (United States)

    Gómez-Molina, Josué; Ogueta-Alday, Ana; Camara, Jesus; Stickley, Christoper; Rodríguez-Marroyo, José A; García-López, Juan

    2017-06-01

    The aims of this study were to establish and validate various predictive equations of half-marathon performance. Seventy-eight half-marathon male runners participated in two different phases. Phase 1 (n = 48) was used to establish the equations for estimating half-marathon performance, and Phase 2 (n = 30) to validate these equations. Apart from half-marathon performance, training-related and anthropometric variables were recorded, and an incremental test on a treadmill was performed, in which physiological (VO2max, speed at the anaerobic threshold, peak speed) and biomechanical variables (contact and flight times, step length and step rate) were registered. In Phase 1, half-marathon performance could be predicted to 90.3% by variables related to training and anthropometry (Equation 1), 94.9% by physiological variables (Equation 2), 93.7% by biomechanical parameters (Equation 3) and 96.2% by a general equation (Equation 4). Using these equations, in Phase 2 the predicted time was significantly correlated with performance (r = 0.78, 0.92, 0.90 and 0.95, respectively). The proposed equations and their validation showed a high prediction of half-marathon performance in long distance male runners, considered from different approaches. Furthermore, they improved the prediction performance of previous studies, which makes them a highly practical application in the field of training and performance.

  20. Predictive Variables of Half-Marathon Performance for Male Runners

    Directory of Open Access Journals (Sweden)

    Josué Gómez-Molina, Ana Ogueta-Alday, Jesus Camara, Christoper Stickley, José A. Rodríguez-Marroyo, Juan García-López

    2017-06-01

    Full Text Available The aims of this study were to establish and validate various predictive equations of half-marathon performance. Seventy-eight half-marathon male runners participated in two different phases. Phase 1 (n = 48 was used to establish the equations for estimating half-marathon performance, and Phase 2 (n = 30 to validate these equations. Apart from half-marathon performance, training-related and anthropometric variables were recorded, and an incremental test on a treadmill was performed, in which physiological (VO2max, speed at the anaerobic threshold, peak speed and biomechanical variables (contact and flight times, step length and step rate were registered. In Phase 1, half-marathon performance could be predicted to 90.3% by variables related to training and anthropometry (Equation 1, 94.9% by physiological variables (Equation 2, 93.7% by biomechanical parameters (Equation 3 and 96.2% by a general equation (Equation 4. Using these equations, in Phase 2 the predicted time was significantly correlated with performance (r = 0.78, 0.92, 0.90 and 0.95, respectively. The proposed equations and their validation showed a high prediction of half-marathon performance in long distance male runners, considered from different approaches. Furthermore, they improved the prediction performance of previous studies, which makes them a highly practical application in the field of training and performance.

  1. Predicting Expatriate Job Performance for Selection Purposes: A Quantitative Review

    NARCIS (Netherlands)

    S.T. Mol (Stefan); M.Ph. Born (Marise); M.E. Willemsen (Madde); H.T. van der Molen (Henk)

    2005-01-01

    textabstractThis article meta-analytically reviews empirical studies on the prediction of expatriate job performance. Using 30 primary studies (total N=4046), it was found that predictive validities of the big five were similar to big five validities reported for domestic employees (Barrick & Mount,

  2. Predicting expatriate job performance for selection purposes: A quantitative review

    NARCIS (Netherlands)

    H.T. van der Molen (Henk); M.Ph. Born (Marise); M.E. Willemsen (Madde)

    2005-01-01

    textabstractThis article meta-analytically reviews empirical studies on the prediction of expatriate job performance. Using 30 primary studies (total N=4,046), it was found that predictive validities of the Big Five were similar to Big Five validities reported for domestic employees. Extraversion,

  3. Implementation of new pavement performance prediction models in PMIS : report

    Science.gov (United States)

    2012-08-01

    Pavement performance prediction models and maintenance and rehabilitation (M&R) optimization processes : enable managers and engineers to plan and prioritize pavement M&R activities in a cost-effective manner. : This report describes TxDOTs effort...

  4. 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

  5. Performance prediction model for distributed applications on multicore clusters

    CSIR Research Space (South Africa)

    Khanyile, NP

    2012-07-01

    Full Text Available Distributed processing offers a way of successfully dealing with computationally demanding applications such as scientific problems. Over the years, researchers have investigated ways to predict the performance of parallel algorithms. Amdahl’s law...

  6. Prediction of indoor climbing performance in women rock climbers.

    Science.gov (United States)

    Wall, Christopher B; Starek, Joanna E; Fleck, Steven J; Byrnes, William C

    2004-02-01

    In an attempt to more clearly understand the strength characteristics of female rock climbers and whether those variables affect and predict climbing performance, 2 indoor climbing performance tests (route and bouldering) were compared to a series of muscular strength tests performed by moderate (n = 6), intermediate (n = 6), and expert (n = 6) female rock climbers. Significant differences (p climbing specific hand strength, as well as 1-arm lock-off strength when expressed as a strength-to-weight ratio. Multiple correlations showed that these variables (r > 0.426) as well as a questionnaire of past climbing performance (r > 0.86) significantly correlated to the tests of indoor climbing performance. In conclusion, climbing-specific tests of hand strength and of one arm lock-off strength reliably and sensitively measured 2 significant variables in the performance of indoor rock climbing, and a questionnaire of past best performance may be an accurate tool for the prediction of indoor climbing performance.

  7. 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.

  8. 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.

  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. The Combination and Evaluation of Query Performance Prediction Methods

    NARCIS (Netherlands)

    Hauff, C.; Azzopardi, L.; Hiemstra, Djoerd

    2009-01-01

    In this paper, we examine a number of newly applied methods for combining pre-retrieval query performance predictors in order to obtain a better prediction of the query's performance. However, in order to adequately and appropriately compare such techniques, we critically examine the current

  11. Prediction of Tennis Performance in Junior Elite Tennis Players

    NARCIS (Netherlands)

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

    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

  12. Reading Performance Is Predicted by More Than Phonological Processing

    Directory of Open Access Journals (Sweden)

    Michelle Y. Kibby

    2014-09-01

    Full Text Available We compared three phonological processing components (phonological awareness, rapid automatized naming and phonological memory, verbal working memory, and attention control in terms of how well they predict the various aspects of reading: word recognition, pseudoword decoding, fluency and comprehension, in a mixed sample of 182 children ages 8-12 years. Participants displayed a wide range of reading ability and attention control. Multiple regression was used to determine how well the phonological processing components, verbal working memory, and attention control predict reading performance. All equations were highly significant. Phonological memory predicted word identification and decoding. In addition, phonological awareness and rapid automatized naming predicted every aspect of reading assessed, supporting the notion that phonological processing is a core contributor to reading ability. Nonetheless, phonological processing was not the only predictor of reading performance. Verbal working memory predicted fluency, decoding and comprehension, and attention control predicted fluency. Based upon our results, when using Baddeley’s model of working memory it appears that the phonological loop contributes to basic reading ability, whereas the central executive contributes to fluency and comprehension, along with decoding. Attention control was of interest as some children with ADHD have poor reading ability even if it is not sufficiently impaired to warrant diagnosis. Our finding that attention control predicts reading fluency is consistent with prior research which showed sustained attention plays a role in fluency. Taken together, our results suggest that reading is a highly complex skill that entails more than phonological processing to perform well.

  13. Using the Soil and Water Assessment Tool (SWAT) to model ecosystem services: A systematic review

    Science.gov (United States)

    Francesconi, Wendy; Srinivasan, Raghavan; Pérez-Miñana, Elena; Willcock, Simon P.; Quintero, Marcela

    2016-04-01

    SWAT, a watershed modeling tool has been proposed to help quantify ecosystem services. The concept of ecosystem services incorporates the collective benefits natural systems provide primarily to human beings. It is becoming increasingly important to track the impact that human activities have on the environment in order to determine its resilience and sustainability. The objectives of this paper are to provide an overview of efforts using SWAT to quantify ecosystem services, to determine the model's capability examining various types of services, and to describe the approach used by various researchers. A literature review was conducted to identify studies in which SWAT was explicitly used for quantifying ecosystem services in terms of provisioning, regulating, supporting, and cultural aspects. A total of 44 peer reviewed publications were identified. Most of these used SWAT to quantify provisioning services (34%), regulating services (27%), or a combination of both (25%). While studies using SWAT for evaluating ecosystem services are limited (approximately 1% of SWAT's peered review publications), and usage (vs. potential) of services by beneficiaries is a current model limitation, the available literature sets the stage for the continuous development and potential of SWAT as a methodological framework for quantifying ecosystem services to assist in decision-making.

  14. 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.

  15. SWAT Modeling for Depression-Dominated Areas: How Do Depressions Manipulate Hydrologic Modeling?

    Directory of Open Access Journals (Sweden)

    Mohsen Tahmasebi Nasab

    2017-01-01

    Full Text Available Modeling hydrologic processes for depression-dominated areas such as the North American Prairie Pothole Region is complex and reliant on a clear understanding of dynamic filling-spilling-merging-splitting processes of numerous depressions over the surface. Puddles are spatially distributed over a watershed and their sizes, storages, and interactions vary over time. However, most hydrologic models fail to account for these dynamic processes. Like other traditional methods, depressions are filled as a required preprocessing step in the Soil and Water Assessment Tool (SWAT. The objective of this study was to facilitate hydrologic modeling for depression-dominated areas by coupling SWAT with a Puddle Delineation (PD algorithm. In the coupled PD-SWAT model, the PD algorithm was utilized to quantify topographic details, including the characteristics, distribution, and hierarchical relationships of depressions, which were incorporated into SWAT at the hydrologic response unit (HRU scale. The new PD-SWAT model was tested for a large watershed in North Dakota under real precipitation events. In addition, hydrologic modeling of a small watershed was conducted under two extreme high and low synthetic precipitation conditions. In particular, the PD-SWAT was compared against the regular SWAT based on depressionless DEMs. The impact of depressions on the hydrologic modeling of the large and small watersheds was evaluated. The simulation results for the large watershed indicated that SWAT systematically overestimated the outlet discharge, which can be attributed to the failure to account for the hydrologic effects of depressions. It was found from the PD-SWAT modeling results that at the HRU scale surface runoff initiation was significantly delayed due to the threshold control of depressions. Under the high precipitation scenario, depressions increased the surface runoff peak. However, the low precipitation scenario could not fully fill depressions to reach

  16. Predator personality and prey behavioural predictability jointly determine foraging performance.

    Science.gov (United States)

    Chang, Chia-Chen; Teo, Huey Yee; Norma-Rashid, Y; Li, Daiqin

    2017-01-17

    Predator-prey interactions play important roles in ecological communities. Personality, consistent inter-individual differences in behaviour, of predators, prey or both are known to influence inter-specific interactions. An individual may also behave differently under the same situation and the level of such variability may differ between individuals. Such intra-individual variability (IIV) or predictability may be a trait on which selection can also act. A few studies have revealed the joint effect of personality types of both predators and prey on predator foraging performance. However, how personality type and IIV of both predators and prey jointly influence predator foraging performance remains untested empirically. Here, we addressed this using a specialized spider-eating jumping spider, Portia labiata (Salticidae), as the predator, and a jumping spider, Cosmophasis umbratica, as the prey. We examined personality types and IIVs of both P. labiata and C. umbratica and used their inter- and intra-individual behavioural variation as predictors of foraging performance (i.e., number of attempts to capture prey). Personality type and predictability had a joint effect on predator foraging performance. Aggressive predators performed better in capturing unpredictable (high IIV) prey than predictable (low IIV) prey, while docile predators demonstrated better performance when encountering predictable prey. This study highlights the importance of the joint effect of both predator and prey personality types and IIVs on predator-prey interactions.

  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. PMID:25386605

  18. 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.

  19. 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.

  20. Assessment of basic human performance resources predicts operative performance of laparoscopic surgery.

    Science.gov (United States)

    Gettman, Matthew T; Kondraske, George V; Traxer, Olivier; Ogan, Ken; Napper, Cheryl; Jones, Daniel B; Pearle, Margaret S; Cadeddu, Jeffrey A

    2003-09-01

    Interest in laparoscopic surgery has prompted development of educational programs designed to teach and assess laparoscopic skills. Although these programs are beneficial, because of the inherent demands imposed by laparoscopy some aspects of operative performance might not improve with practice. This suggests that innate ability could predict level of operative skill. Assessment of operative and technical potential to date has relied largely on subjective rather than objective criteria. In this study, the relationships between objective measures of human basic performance resources (BPRs) and laparoscopic performance were evaluated using Nonlinear Causal Resource Analysis (NCRA), a novel predictive and explanatory modeling approach based on General Systems Performance Theory. Twenty urology residents were voluntary enrolled. Thirteen validated BPRs were measured and analyzed relative to operative laparoscopic performance (assessed by two experts) of two porcine laparoscopic nephrectomies (LN). The laparoscopic procedure, representing a High Level Task (HLT), was evaluated using a modified Global Rating of Operative Performance Scale. NCRA models were devised to predict performance of the HLT laparoscopic nephrectomies based on BPRs and to determine the limiting performance resource. NCRA models predicted excellent agreement with actual operative performance, suggesting that measures of innate ability (or BPRs) predicted performance of laparoscopic nephrectomy. In 65%, the prediction by NCRA was near identical to the expert rating on the HLT. In 25% of cases, NCRA overpredicted performance; in 10%, NCRA underpredicted performance of the HLT compared to the subjective ratings. Neuromotor channel capacity was the most common performance-limiting resource. Preliminary findings suggest objective prediction of laparoscopic performance with limiting resource diagnostics for an individual surgeon is possible and practical using appropriate new measurement and modeling

  1. Comparison of prediction performance using statistical postprocessing methods

    Science.gov (United States)

    Han, Keunhee; Choi, JunTae; Kim, Chansoo

    2016-11-01

    As the 2018 Winter Olympics are to be held in Pyeongchang, both general weather information on Pyeongchang and specific weather information on this region, which can affect game operation and athletic performance, are required. An ensemble prediction system has been applied to provide more accurate weather information, but it has bias and dispersion due to the limitations and uncertainty of its model. In this study, homogeneous and nonhomogeneous regression models as well as Bayesian model averaging (BMA) were used to reduce the bias and dispersion existing in ensemble prediction and to provide probabilistic forecast. Prior to applying the prediction methods, reliability of the ensemble forecasts was tested by using a rank histogram and a residualquantile-quantile plot to identify the ensemble forecasts and the corresponding verifications. The ensemble forecasts had a consistent positive bias, indicating over-forecasting, and were under-dispersed. To correct such biases, statistical post-processing methods were applied using fixed and sliding windows. The prediction skills of methods were compared by using the mean absolute error, root mean square error, continuous ranked probability score, and continuous ranked probability skill score. Under the fixed window, BMA exhibited better prediction skill than the other methods in most observation station. Under the sliding window, on the other hand, homogeneous and non-homogeneous regression models with positive regression coefficients exhibited better prediction skill than BMA. In particular, the homogeneous regression model with positive regression coefficients exhibited the best prediction skill.

  2. Does the MCAT predict medical school and PGY-1 performance?

    Science.gov (United States)

    Saguil, Aaron; Dong, Ting; Gingerich, Robert J; Swygert, Kimberly; LaRochelle, Jeffrey S; Artino, Anthony R; Cruess, David F; Durning, Steven J

    2015-04-01

    The Medical College Admissions Test (MCAT) is a high-stakes test required for entry to most U. S. medical schools; admissions committees use this test to predict future accomplishment. Although there is evidence that the MCAT predicts success on multiple choice-based assessments, there is little information on whether the MCAT predicts clinical-based assessments of undergraduate and graduate medical education performance. This study looked at associations between the MCAT and medical school grade point average (GPA), Medical Licensing Examination (USMLE) scores, observed patient care encounters, and residency performance assessments. This study used data collected as part of the Long-Term Career Outcome Study to determine associations between MCAT scores, USMLE Step 1, Step 2 clinical knowledge and clinical skill, and Step 3 scores, Objective Structured Clinical Examination performance, medical school GPA, and PGY-1 program director (PD) assessment of physician performance for students graduating 2010 and 2011. MCAT data were available for all students, and the PGY PD evaluation response rate was 86.2% (N = 340). All permutations of MCAT scores (first, last, highest, average) were weakly associated with GPA, Step 2 clinical knowledge scores, and Step 3 scores. MCAT scores were weakly to moderately associated with Step 1 scores. MCAT scores were not significantly associated with Step 2 clinical skills Integrated Clinical Encounter and Communication and Interpersonal Skills subscores, Objective Structured Clinical Examination performance or PGY-1 PD evaluations. MCAT scores were weakly to moderately associated with assessments that rely on multiple choice testing. The association is somewhat stronger for assessments occurring earlier in medical school, such as USMLE Step 1. The MCAT was not able to predict assessments relying on direct clinical observation, nor was it able to predict PD assessment of PGY-1 performance. Reprint & Copyright © 2015 Association of

  3. 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.

  4. Simulator driving performance predicts accident reports five years later.

    Science.gov (United States)

    Hoffman, Lesa; McDowd, Joan M

    2010-09-01

    L. Hoffman, J. M. McDowd, P. Atchley, and R. A. Dubinsky (2005) reported that visual and attentional impairment (measured by the Useful Field of View test and DriverScan) and performance in a low-fidelity driving simulator did not predict self-reported accidents in the previous 3 years. The present study applied these data to predict accidents occurring within a subsequent 5-year period (N = 114 older adults, 75% retention rate). Multivariate path models revealed that accidents in which the driver was at least partially at fault were significantly more likely in persons who had shown impaired simulator performance. These results suggest that even low-fidelity driving simulators may be useful in predicting real-world outcomes. (c) 2010 APA, all rights reserved.

  5. Hydrodynamic properties of fin whale flippers predict maximum rolling performance.

    Science.gov (United States)

    Segre, Paolo S; Cade, David E; Fish, Frank E; Potvin, Jean; Allen, Ann N; Calambokidis, John; Friedlaender, Ari S; Goldbogen, Jeremy A

    2016-11-01

    Maneuverability is one of the most important and least understood aspects of animal locomotion. The hydrofoil-like flippers of cetaceans are thought to function as control surfaces that effect maneuvers, but quantitative tests of this hypothesis have been lacking. Here, we constructed a simple hydrodynamic model to predict the longitudinal-axis roll performance of fin whales, and we tested its predictions against kinematic data recorded by on-board movement sensors from 27 free-swimming fin whales. We found that for a given swimming speed and roll excursion, the roll velocity of fin whales calculated from our field data agrees well with that predicted by our hydrodynamic model. Although fluke and body torsion may further influence performance, our results indicate that lift generated by the flippers is sufficient to drive most of the longitudinal-axis rolls used by fin whales for feeding and maneuvering. © 2016. Published by The Company of Biologists Ltd.

  6. Gesture Performance in Schizophrenia Predicts Functional Outcome After 6 Months.

    Science.gov (United States)

    Walther, Sebastian; Eisenhardt, Sarah; Bohlhalter, Stephan; Vanbellingen, Tim; Müri, René; Strik, Werner; Stegmayer, Katharina

    2016-11-01

    The functional outcome of schizophrenia is heterogeneous and markers of the course are missing. Functional outcome is associated with social cognition and negative symptoms. Gesture performance and nonverbal social perception are critically impaired in schizophrenia. Here, we tested whether gesture performance or nonverbal social perception could predict functional outcome and the ability to adequately perform relevant skills of everyday function (functional capacity) after 6 months. In a naturalistic longitudinal study, 28 patients with schizophrenia completed tests of nonverbal communication at baseline and follow-up. In addition, functional outcome, social and occupational functioning, as well as functional capacity at follow-up were assessed. Gesture performance and nonverbal social perception at baseline predicted negative symptoms, functional outcome, and functional capacity at 6-month follow-up. Gesture performance predicted functional outcome beyond the baseline measure of functioning. Patients with gesture deficits at baseline had stable negative symptoms and experienced a decline in social functioning. While in patients without gesture deficits, negative symptom severity decreased and social functioning remained stable. Thus, a simple test of hand gesture performance at baseline may indicate favorable outcomes in short-term follow-up. The results further support the importance of nonverbal communication skills in subjects with schizophrenia. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

  7. 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...

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

    DEFF Research Database (Denmark)

    Frison, Gianluca

    The goal of this thesis is to investigate algorithms and methods to reduce the solution time of solvers for Model Predictive Control (MPC). The thesis is accompanied with an open-source toolbox for High-Performance implementation of solvers for MPC (HPMPC), that contains the source code of all...

  9. Predicting Performance of One-Year MBA Students

    Science.gov (United States)

    Fish, Lynn A.; Wilson, F. Scott

    2007-01-01

    Although several studies have been performed, Graduate Admissions programs are still encountering difficulties uncovering criteria that will predict academic success in their programs. Researchers have analyzed Executive, full and part-time MBA programs and can only conclude that undergraduate grade point average and the GMAT are significant…

  10. Personality characteristics that predict effective performance of sales people

    NARCIS (Netherlands)

    W.J.M.I. Verbeke (Willem)

    1993-01-01

    textabstractIn sales literature the role of personality traits in the prediction of salespeople's performance is a hot topic. This study, based upon an administered personality test, suggests that salespeople's personality traits — specifically, the ability to elicit information from others, to

  11. Prediction of Military Turnover Using Intentions, Satisfaction, and Performance.

    Science.gov (United States)

    Knapp, Deirdre J.; And Others

    Although researchers have examined the link between job attitudes and turnover, some studies claim that civilian samples may not be generalizable to military personnel. This paper addresses two central questions: (1) To what extent does job satisfaction, job performance, and reenlistment intentions predict reenlistment behavior?; (2) To what…

  12. 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.

  13. 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.

  14. Soil Water and Temperature System (SWATS) Instrument Handbook

    Energy Technology Data Exchange (ETDEWEB)

    Cook, David R. [Argonne National Lab. (ANL), Argonne, IL (United States)

    2016-04-01

    The soil water and temperature system (SWATS) provides vertical profiles of soil temperature, soil-water potential, and soil moisture as a function of depth below the ground surface at hourly intervals. The temperature profiles are measured directly by in situ sensors at the Central Facility and many of the extended facilities of the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility Southern Great Plains (SGP) site. The soil-water potential and soil moisture profiles are derived from measurements of soil temperature rise in response to small inputs of heat. Atmospheric scientists use the data in climate models to determine boundary conditions and to estimate the surface energy flux. The data are also useful to hydrologists, soil scientists, and agricultural scientists for determining the state of the soil.

  15. Ethnobotanical Study of Tehsil Kabal, Swat District, KPK, Pakistan

    Directory of Open Access Journals (Sweden)

    Imtiaz Ahmad

    2011-01-01

    Full Text Available A total of 140 plants have been reported ethnobotanically from Tehsil Kabal, Swat District. These include the 133 plants (95% of angiosperms, 3 (2.14% of gymnosperms, and 2 (1.42% each of pteridophytes and fungi. The largest family is Lamiaceae represented by 11 species followed by Rosaceae represented by 9 species. Among angiosperms 76 (55.63% were herbs, 17 (12.78% were shrubs, and 40 (30.07% were trees; 127 plants (95.48% were dicot while 6 plants (4.51% were monocot. Most of the plants were used for more than one purpose. Generally the plants were used for medicinal, fuel, timber wood, food, and fodder for cattle purposes.

  16. Simulation of photovoltaic power systems and their performance prediction

    Energy Technology Data Exchange (ETDEWEB)

    Rahman, S.; Chowdhury, B.H. (Electrical Engineering Dept., Virginia Tech, Blacksburg, VA (US))

    1988-09-01

    The objective of this paper is two-fold. The first is to examine and test a number of photovoltaic performance analysis models for their ability to estimate the AC power output, and vaildate those against historical observations from a PV test facility. The second is to develop a method to estimate meteorological parameters for use in PV performance models for predicting future AC power output from a PV test site. The authors have examined 12 such PV performance models and extensively tested PVFORM - System Analysis Program and LCP - Lifetime Cost and Performance model. These two models are tested using (TMY) the Typical Meteorological Year and the VPI model generated estimates of long-term data. Performance prediction results are compared against actual observations at a 4-kW PV test facility in Raleigh, North Carolina. The authors' results show that the VPI model generated data, when used with PVFORM model, provide the best predictions for AC power output from this 4-kW PV test facility.

  17. 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'…

  18. An improved SWAT vegetation growth module and its evaluation for four tropical ecosystems

    Directory of Open Access Journals (Sweden)

    T. Alemayehu

    2017-09-01

    Full Text Available The Soil and Water Assessment Tool (SWAT is a globally applied river basin ecohydrological model used in a wide spectrum of studies, ranging from land use change and climate change impacts studies to research for the development of the best water management practices. However, SWAT has limitations in simulating the seasonal growth cycles for trees and perennial vegetation in the tropics, where rainfall rather than temperature is the dominant plant growth controlling factor. Our goal is to improve the vegetation growth module of SWAT for simulating the vegetation variables – such as the leaf area index (LAI – for tropical ecosystems. Therefore, we present a modified SWAT version for the tropics (SWAT-T that uses a straightforward but robust soil moisture index (SMI – a quotient of rainfall (P and reference evapotranspiration (ETr – to dynamically initiate a new growth cycle within a predefined period. Our results for the Mara Basin (Kenya/Tanzania show that the SWAT-T-simulated LAI corresponds well with the Moderate Resolution Imaging Spectroradiometer (MODIS LAI for evergreen forest, savanna grassland and shrubland. This indicates that the SMI is reliable for triggering a new annual growth cycle. The water balance components (evapotranspiration and streamflow simulated by the SWAT-T exhibit a good agreement with remote-sensing-based evapotranspiration (ET-RS and observed streamflow. The SWAT-T model, with the proposed vegetation growth module for tropical ecosystems, can be a robust tool for simulating the vegetation growth dynamics in hydrologic models in tropical regions.

  19. Performance Study and CFD Predictions of a Ducted Fan System

    Science.gov (United States)

    Abrego, Anita I.; Chang, I-Chung; Bulaga, Robert W.; Rutkowski, Michael (Technical Monitor)

    2002-01-01

    An experimental investigation was completed in the NASA Ames 7 by 10-Foot Wind Tunnel to study the performance characteristics of a ducted fan. The goal of this effort is to study the effect of ducted fan geometry and utilize Computational Fluid Dynamics (CFD) analysis to provide a baseline for correlation. A 38-inch diameter, 10-inch chord duct with a five-bladed fixed-pitch fan was tested. Duct performance data were obtained in hover, vertical climb, and forward flight test conditions. This paper will present a description of the test, duct performance results and correlation with CFD predictions.

  20. Assessing Thermally Stressful Events in a Rhode Island Coldwater Fish Habitat Using the SWAT Model

    Directory of Open Access Journals (Sweden)

    Britta Chambers

    2017-09-01

    Full Text Available It has become increasingly important to recognize historical water quality trends so that the future impacts of climate change may be better understood. Climate studies have suggested that inland stream temperatures and average streamflow will increase over the next century in New England, thereby putting aquatic species sustained by coldwater habitats at risk. In this study we evaluated two different approaches for modeling historical streamflow and stream temperature in a Rhode Island, USA, watershed with the Soil and Water Assessment Tool (SWAT, using (i original SWAT and (ii SWAT plus a hydroclimatological model component that considers both hydrological inputs and air temperature. Based on daily calibration results with six years of measured streamflow and four years of stream temperature data, we examined occurrences of stressful conditions for brook trout (Salvelinus fontinalis using the hydroclimatological model. SWAT with the hydroclimatological component improved modestly during calibration (NSE of 0.93, R2 of 0.95 compared to the original SWAT (NSE of 0.83, R2 of 0.93. Between 1980–2009, the number of stressful events, a moment in time where high or low flows occur simultaneously with stream temperatures exceeding 21 °C, increased by 55% and average streamflow increased by 60%. This study supports using the hydroclimatological SWAT component and provides an example method for assessing stressful conditions in southern New England’s coldwater habitats.

  1. 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

  2. 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.

  3. 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.

  4. Aplicación del modelo hidrológico-swat-en una microcuenca agrícola de La Pampa ondulada Application of the hydrologic model - swat - on a micro agricultural basin of the rolling Pampa

    Directory of Open Access Journals (Sweden)

    Felipe Behrends Kraemer

    2011-07-01

    Full Text Available El modelado hidrológico es a menudo el primer paso en el desarrollo de sistemas de decisión espacial para identificaráreas vulnerables a la contaminación por nutrientes, pesticidas así como también a contaminantes biológicos. En este sentido el SWAT (Soil and Water Assesment Tool fue desarrollado para predecir impactos de las prácticas de manejo de las tierras en las aguas, sedimentos y agroquímicos en cuencas hidrográficas con diferentes suelos, usos y prácticas en largos períodos de tiempo. Aunque el mismo está siendo aplicado en todo el mundo, todavía no esta difundido su uso en la Argentina, no encontrándose al momento reportes al respecto. Este modelo se utilizó en una microcuenca agrícola de la Pampa Ondulada (Argentina y fue calibrado y validado utilizando los valores de escurrimientos medidos in situ. Se encontraron buenas eficiencias a escala diaria (R²: 0,55; R² ENS: 0,52 y pobres a escala mensual (R²: 0,34; R² ENS: 0,04. En la calibración, los escurrimientos fueron sobreestimados en un 31,8% y 32,6% para la escala mensual y diaria respectivamente, mientras que en la validación se sobreestimó un 42,5% para los valores mensuales y un 41,2% para los diarios. La aplicación del SWAT en esta microcuenca agrícola resultó auspiciosa y conduce a la inclusión de dicho modelo en futuros trabajos.A hydrological model is often the first step for the development of spatial decision systems in order to identify vulnerable areas to the pollution by nutrients, pesticides as well as biological contaminants. The SWAT model was developed to predict the impact of land management on water, agrochemicals and sediments in hydrographical basins with different soils, land uses and practices for long time periods. This model is being used all over the world but it has not been applied in Argentina until present. The SWAT model was used in an agricultural microbasin in the Rolling Pampa (Argentina and was calibrated and validated

  5. Genomic Prediction of Testcross Performance in Canola (Brassica napus.

    Directory of Open Access Journals (Sweden)

    Habib U Jan

    Full Text Available 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

  6. 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

  7. Assessment of land-use change on streamflow using GIS, remote sensing and a physically-based model, SWAT

    Directory of Open Access Journals (Sweden)

    J. Y. G. Dos Santos

    2014-09-01

    Full Text Available This study aims to assess the impact of the land-use changes between the periods 1967−1974 and 1997−2008 on the streamflow of Tapacurá catchment (northeastern Brazil using the Soil and Water Assessment Tool (SWAT model. The results show that the most sensitive parameters were the baseflow, Manning factor, time of concentration and soil evaporation compensation factor, which affect the catchment hydrology. The model calibration and validation were performed on a monthly basis, and the streamflow simulation showed a good level of accuracy for both periods. The obtained R2 and Nash-Sutcliffe Efficiency values for each period were respectively 0.82 and 0.81 for 1967−1974, and 0.93 and 0.92 for the period 1997−2008. The evaluation of the SWAT model response to the land cover has shown that the mean monthly flow, during the rainy seasons for 1967−1974, decreased when compared to 1997−2008.

  8. 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).

  9. Sound Zones: On Performance Prediction of Contrast Control Methods

    DEFF Research Database (Denmark)

    Møller, Martin Bo; Olsen, Martin

    2016-01-01

    Low frequency personal sound zones can be created by controlling the squared sound pressure in separate spatial confined control regions. Several methods have been proposed for realizing this scenario, with different constraints and performance. Extrapolating knowledge of the resulting acoustic...... separation from predicted results is a challenge as the obtainable performance relies on both physical setup and the chosen evaluation procedure. In this paper, the influence of the evaluation method is highlighted. Using the proposed evaluation four different control strategies for generation of low...

  10. Prediction of performance on two stretcher-carry tasks.

    Science.gov (United States)

    Rice, V J; Sharp, M A

    1994-01-01

    Pre-placement screening for physically demanding jobs should result in better job performance and fewer injuries, if the test components reflect job demands. The purpose of this study was to determine how seven strength measures, three Army Physical Fitness Test (APFT) scores, and three physical descriptors relate to performance on two stretcher-carry tasks: 1) a repeated short-distance carry and 2) a continuous long-distance carry. Twelve men and 11 women completed both tasks with and without (hand-carry) a shoulder harness. Pearson product moment correlation coefficients compared independent variables and forward stepwise multiple regression analyses were used for predictions. For repeated short distance stretcher-carrying, two-mile run time and handgrip were the best predictors of performance (hand-carry: r2=0.79, p<0.01; harness-carry: r2=0.75, p<0.01). The grip, which was more predictive during the hand-carry, required a sudden maximal contraction to peak force, followed by immediate release, while a sudden maximal contraction to peak force maintained for four seconds, was more predictive of the harness-carry. For the continuous hand-carry, the best predictor was a gradual buildup to a 6-second sustained grip strength (r2=0.74, p<0.01). These results illustrate the necessity for tailoring preplacement tests to accurately reflect job demands.

  11. Prediction of Cone Crusher Performance Considering Liner Wear

    Directory of Open Access Journals (Sweden)

    Yanjun Ma

    2016-12-01

    Full Text Available Cone crushers are used in the aggregates and mining industries to crush rock material. The pressure on cone crusher liners is the key factor that influences the hydraulic pressure, power draw and liner wear. In order to dynamically analyze and calculate cone crusher performance along with liner wear, a series of experiments are performed to obtain the crushed rock material samples from a crushing plant at different time intervals. In this study, piston die tests are carried out and a model relating compression coefficient, compression ratio and particle size distribution to a corresponding pressure is presented. On this basis, a new wear prediction model is proposed combining the empirical model for predicting liner wear with time parameter. A simple and practical model, based on the wear model and interparticle breakage, is presented for calculating compression ratio of each crushing zone along with liner wear. Furthermore, the size distribution of the product is calculated based on existing size reduction process model. A method of analysis of product size distribution and shape in the crushing process considering liner wear is proposed. Finally, the validity of the wear model is verified via testing. The result shows that there is a significant improvement of the prediction of cone crusher performance considering liner wear as compared to the previous model.

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

    Directory of Open Access Journals (Sweden)

    Liziwe Nzama

    2008-12-01

    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.

  13. The validity of physical aggression in predicting adolescent academic performance.

    Science.gov (United States)

    Loveland, James M; Lounsbury, John W; Welsh, Deborah; Buboltz, Walter C

    2007-03-01

    Aggression has a long history in academic research as both a criterion and a predictor variable and it is well documented that aggression is related to a variety of poor academic outcomes such as: lowered academic performance, absenteeism and lower graduation rates. However, recent research has implicated physical aggression as being predictive of lower academic performance. The purpose of this study was to examine the role of the 'Big Five' personality traits of agreeableness, openness to experience, conscientiousness, neuroticism and extraversion and physical aggression in predicting the grade point averages (GPA) of adolescent students and to investigate whether or not there were differences in these relationships between male and female students. A sample of 992 students in grades 9 to 12 from a high school in south-eastern USA as part of a larger study examining the students' preparation for entry into the workforce. The study was correlational in nature: students completed a personality inventory developed by the second author with the GPA information supplied by the school. Results indicated that physical aggression accounts for 16% of variance in GPA and it adds 7% to the prediction of GPA beyond the Big Five. The Big Five traits added only 1.5% to the prediction of GPA after controlling for physical aggression. Interestingly, a significantly larger amount of variance in GPA was predicted by physical aggression for females than for males. Aggression accounts for significantly more variance in the GPA of females than for males, even when controlling for the Big Five personality factors. Future research should examine the differences in the expression of aggression in males and females, as well as how this is affecting interactions between peers and between students and their teachers.

  14. Predicting hybrid performance in rice using genomic best linear unbiased prediction.

    Science.gov (United States)

    Xu, Shizhong; Zhu, Dan; Zhang, Qifa

    2014-08-26

    Genomic selection is an upgrading form of marker-assisted selection for quantitative traits, and it differs from the traditional marker-assisted selection in that markers in the entire genome are used to predict genetic values and the QTL detection step is skipped. Genomic selection holds the promise to be more efficient than the traditional marker-assisted selection for traits controlled by polygenes. Genomic selection for pure breed improvement is based on marker information and thus leads to cost-saving due to early selection before phenotypes are measured. When applied to hybrid breeding, genomic selection is anticipated to be even more efficient because genotypes of hybrids are predetermined by their inbred parents. Hybrid breeding has been an important tool to increase crop productivity. Here we proposed and applied an advanced method to predict hybrid performance, in which a subset of all potential hybrids is used as a training sample to predict trait values of all potential hybrids. The method is called genomic best linear unbiased prediction. The technology applied to hybrids is called genomic hybrid breeding. We used 278 randomly selected hybrids derived from 210 recombinant inbred lines of rice as a training sample and predicted all 21,945 potential hybrids. The average yield of top 100 selection shows a 16% increase compared with the average yield of all potential hybrids. The new strategy of marker-guided prediction of hybrid yields serves as a proof of concept for a new technology that may potentially revolutionize hybrid breeding.

  15. 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.

  16. Predictions of H-mode performance in ITER

    Energy Technology Data Exchange (ETDEWEB)

    Budny, R. V.; Andre, R.; Bateman, G.; Halpern, F.; Kessel, C. E.; Kritz, A.; McCune, D.

    2008-03-03

    Time-dependent integrated predictive modeling is carried out using the PTRANSP code to predict fusion power and parameters such as alpha particle density and pressure in ITER H-mode plasmas. Auxiliary heating by negative ion neutral beam injection and ion cyclotron heating of He3 minority ions are modeled, and the GLF23 transport model is used in the prediction of the evolution of plasma temperature profiles. Effects of beam steering, beam torque, plasma rotation, beam current drive, pedestal temperatures, sawtooth oscillations, magnetic diffusion, and accumulation of He ash are treated self-consistently. Variations in assumptions associated with physics uncertainties for standard base-line DT H-mode plasmas (with Ip=15 MA, BTF=5.3 T, and Greenwald fraction=0.86) lead to a range of predictions for DT fusion power PDT and quasi-steady state fusion QDT (≡ PDT/Paux). Typical predictions assuming Paux = 50-53 MW yield PDT = 250- 720 MW and QDT = 5 - 14. In some cases where Paux is ramped down or shut off after initial flat-top conditions, quasi-steady QDT can be considerably higher, even infinite. Adverse physics assumptions such as existence of an inward pinch of the helium ash and an ash recycling coefficient approaching unity lead to very low values for PDT. Alternative scenarios with different heating and reduced performance regimes are also considered including plasmas with only H or D isotopes, DT plasmas with toroidal field reduced 10 or 20%, and discharges with reduced beam voltage. In full-performance D-only discharges, tritium burn-up is predicted to generate central tritium densities up to 1016/m3 and DT neutron rates up to 5×1016/s, compared with the DD neutron rates of 6×1017/s. Predictions with the toroidal field reduced 10 or 20% below the planned 5.3 T and keeping the same q98, Greenwald fraction, and Βη indicate that the fusion yield PDT and QDT will be lower by about a factor of two (scaling as B3.5).

  17. Heart rate recovery predicts memory performance in older adults.

    Science.gov (United States)

    Pearman, Ann; Lachman, Margie E

    2010-06-01

    The current study examined cardiovascular reactivity and recovery during memory testing in a sample of 28 younger and 28 older adults. Heart rate (HR) levels were measured before, during, and after a memory test (word list recall). Contrary to prediction, older adults did not have a blunted cardiovascular response to memory tasks compared to younger adults. Word list recall performance was predicted by both Age and an Age x HR recovery interaction. As expected, younger adults performed better on the word list task than older adults. In addition, older adults with better posttest HR recovery performed significantly better than older adults with poor posttest HR recovery, whereas HR recovery differences in younger adults were inconsequential. These relationships were not affected by subjective appraisals of anxiety and task difficulty. Overall, cardiac dysregulation, seen here as low HR recovery, represents an important, potentially modifiable, factor in memory performance in older adults. In addition to being beneficial to overall health, interventions designed to help older adults regulate their HR responses may help offset certain memory declines.

  18. Sediment trapping analysis of flood control reservoirs in Upstream Ciliwung River using SWAT Model

    Science.gov (United States)

    Rofiq Ginanjar, Mirwan; Putra, Santosa Sandy

    2017-06-01

    The plans of Sukamahi dam and Ciawi dam construction for Jakarta flood risk reduction purpose had been proposed as feasible solutions to be implemented. However, the risk of the dam outlets clogging, caused by the sediment, is important to be anticipated. The prediction of the max sediment concentration in the reservoir is crucial for the dam operation planning. It is important to avoid the flood outlet tunnel clogging. This paper present a hydrologic sediment budget model of The Upstream Ciliwung River Basin, with flood control dam existence scenarios. The model was constructed within SWAT (Soil and Water Assessment Tools) plugin and run inside the QGIS framework. The free hydrological data from CFSR, soil data from FAO, and topographical data from CGIAR-CSI were implemented as the model input. The model resulted the sediment concentration dynamics of the Sukamahi and Ciawi reservoirs, on some suspended sediment parameter ranges. The sediment trapping efficiency was also computed by different possible dam capacity alternatives. The research findings will give a scientific decision making base for the river authority, in term of flood control dam planning, especially in The Upstream Ciliwung River Basin.

  19. TankSIM: A Cryogenic Tank Performance Prediction Program

    Science.gov (United States)

    Bolshinskiy, L. G.; Hedayat, A.; Hastings, L. J.; Moder, J. P.; Schnell, A. R.; Sutherlin, S. G.

    2015-01-01

    Accurate prediction of the thermodynamic state of the cryogenic propellants in launch vehicle tanks is necessary for mission planning and successful execution. Cryogenic propellant storage and transfer in space environments requires that tank pressure be controlled. The pressure rise rate is determined by the complex interaction of external heat leak, fluid temperature stratification, and interfacial heat and mass transfer. If the required storage duration of a space mission is longer than the period in which the tank pressure reaches its allowable maximum, an appropriate pressure control method must be applied. Therefore, predictions of the pressurization rate and performance of pressure control techniques in cryogenic tanks are required for development of cryogenic fluid long-duration storage technology and planning of future space exploration missions. This paper describes an analytical tool, Tank System Integrated Model (TankSIM), which can be used for modeling pressure control and predicting the behavior of cryogenic propellant for long-term storage for future space missions. It is written in the FORTRAN 90 language and can be compiled with any Visual FORTRAN compiler. A thermodynamic vent system (TVS) is used to achieve tank pressure control. Utilizing TankSIM, the following processes can be modeled: tank self-pressurization, boiloff, ullage venting, and mixing. Details of the TankSIM program and comparisons of its predictions with test data for liquid hydrogen and liquid methane will be presented in the final paper.

  20. Predictive factors for masticatory performance in Duchenne muscular dystrophy.

    Science.gov (United States)

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

    2014-08-01

    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 factors for compromised mastication. Twenty-three patients and 23 controls filled out two questionnaires about mandibular function, and underwent a clinical examination of the masticatory system and measurements of anterior bite force and masticatory performance. In the patients, moreover, quantitative ultrasound of the tongue and motor function measurement was performed. The patients were categorized into ambulatory stage (early or late), early non-ambulatory stage, or late non-ambulatory stage. Masticatory performance, anterior bite force and occlusal contacts were all reduced in the patient group compared to the controls (all p function measurement. The early non-ambulatory and late non-ambulatory stage groups showed less masticatory performance compared to the ambulatory stage group (p masticatory performance (R(2) = 0.52). Anterior bite force, occlusal contacts and masticatory performance in DMD are severely reduced. Copyright © 2014 Elsevier B.V. All rights reserved.

  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. An improved model to predict performance under mental fatigue.

    Science.gov (United States)

    Peng, Henry T; Bouak, Fethi; Wang, Wenbi; Chow, Renee; Vartanian, Oshin

    2018-01-08

    Fatigue has become an increasing problem in our modern society. Using MATLAB as a generic modelling tool, a fatigue model was developed based on an existing one and compared with a commercial fatigue software for prediction of cognitive performance under total and partial sleep deprivation. The flexibility of our fatigue model allowed additions of new algorithms and mechanisms for non-sleep factors and countermeasures and thus improved model predictions and usability for both civilian and military applications. This was demonstrated by model simulations of various scenarios and comparison with experimental studies. Our future work will be focused on model validation and integration with other modelling tools. Practitioner Summary: Mental fatigue affects health, safety and quality of life in our modern society. In this paper, we reported a cognitive fatigue model based on existing models with newly incorporated components taking both the operator's state of alertness and task demand into account. The model provided the additional capability for prediction of cognitive performance in scenarios involving pharmaceutical countermeasures, different task demands and shift work.

  3. Predicting visual performance from optical quality metrics in keratoconus.

    Science.gov (United States)

    Schoneveld, Paul; Pesudovs, Konrad; Coster, Douglas J

    2009-05-01

    The aim was to identify optical quality metrics predictive of visual performance in eyes with keratoconus and penetrating keratoplasty (PK) for keratoconus. Fifty-four participants were recruited for this prospective, cross-sectional study. Data were collected from one eye of each participant: 26 keratoconus, 10 PK and 18 normal eyes: average age (mean +/- standard deviation) 45.2 +/- 10.6 years and 56 per cent female. Visual performance was tested by 10 methods including visual acuity (VA), both high and low contrast (HC- and LC-) and high and low luminance (LL-), and Pelli-Robson contrast sensitivity, all tested with and without glare. Corneal first surface wavefront aberrations were calculated from Orbscan corneal topographic data using VOLPro software v7.08 (Sarver and Associates) as a tenth-order Zernike expansion across three, 4.0 mm and 5.0 mm pupils and converted into 31 optical quality metrics. Pearson correlation coefficients and linear regression were used to relate wavefront aberration metrics to visual performance. Visual performance was highly predictable from optical quality with the average correlation of the order of 0.5. Pupil fraction metrics (for example, PFWc) were responsible for all of the highest correlations at large pupils for example, with HCVA (r = 0.80), LCVA (r = 0.80) and LLLCVA (r = 0.75). Image plane metrics, derived from the optical transfer function (OTF) were responsible for most of the highest correlations at smaller pupils for example, volume under the OTF (VOTF) with HCVA (r = 0.76) and LCVA (r = 0.73). As in normal eyes, visual performance in keratoconus was predicable from optical quality; albeit by different metrics. Optical quality metrics predictive of visual performance in normal eyes, for example, visual Strehl, lack the dynamic range to represent visual performance in highly aberrated eyes with keratoconus. Optical quality outcomes for keratoconus could be reported using many different metrics, but pupil fraction

  4. Meta-analysis of survival prediction with Palliative Performance Scale.

    Science.gov (United States)

    Downing, Michael; Lau, Francis; Lesperance, Mary; Karlson, Nicholas; Shaw, Jack; Kuziemsky, Craig; Bernard, Steve; Hanson, Laura; Olajide, Lola; Head, Barbara; Ritchie, Christine; Harrold, Joan; Casarett, David

    2007-01-01

    This paper aims to reconcile the use of Palliative Performance Scale (PPSv2) for survival prediction in palliative care through an international collaborative study by five research groups. The study involves an individual patient data meta-analysis on 1,808 patients from four original datasets to reanalyze their survival patterns by age, gender, cancer status, and initial PPS score. Our findings reveal a strong association between PPS and survival across the four datasets. The Kaplan-Meier survival curves show each PPS level as distinct, with a strong ordering effect in which higher PPS levels are associated with increased length of survival. Using a stratified Cox proportional hazard model to adjust for study differences, we found females lived significantly longer than males, with a further decrease in hazard for females not diagnosed with cancer. Further work is needed to refine the reporting of survival times/probabilities and to improve prediction accuracy with the inclusion of other variables in the models.

  5. Neighborhood Integration and Connectivity Predict Cognitive Performance and Decline.

    Science.gov (United States)

    Watts, Amber; Ferdous, Farhana; Moore, Keith Diaz; Burns, Jeffrey M

    2015-01-01

    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. 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. 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. 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.

  6. 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.

  7. Theoretical Approach to Predict the Performance of Thermoelectric Generator Modules

    Science.gov (United States)

    Elarusi, Abdulmunaem H.; Fagehi, Hassan; Lee, Hosung; Attar, Alaa

    2017-02-01

    The aim of this work was to examine the validity of the thermoelectric modules' performance predicted by formulating the effective thermoelectric material properties. The three maximum parameters (output power, current, and efficiency) are defined in terms of the average temperature of the thermoelectric generator (TEG). These three maximum parameters, which are either taken from commercial TEG modules or measurements for particular operating conditions, are used to define the effective material properties (Seebeck coefficient, thermal conductivity, and electrical resistivity). The commercial performance curves provided by the manufacturer were compared with the results obtained here by the effective material properties with the simple standard thermoelectric equations. It has been found that this technique predicts the performance of four commercial thermoelectric modules with fair to good accuracy. The characteristics of the TEGs were represented using the normalized charts constructed by formulating the parameters as a fraction of over the maximum parameters. The normalized charts would be universal for any given TEG module once the thermoelectric material is known.

  8. Urinary Squamous Epithelial Cells Do Not Accurately Predict Urine Culture Contamination, but May Predict Urinalysis Performance in Predicting Bacteriuria.

    Science.gov (United States)

    Mohr, Nicholas M; Harland, Karisa K; Crabb, Victoria; Mutnick, Rachel; Baumgartner, David; Spinosi, Stephanie; Haarstad, Michael; Ahmed, Azeemuddin; Schweizer, Marin; Faine, Brett

    2016-03-01

    The presence of squamous epithelial cells (SECs) has been advocated to identify urinary contamination despite a paucity of evidence supporting this practice. We sought to determine the value of using quantitative SECs as a predictor of urinalysis contamination. Retrospective cross-sectional study of adults (≥18 years old) presenting to a tertiary academic medical center who had urinalysis with microscopy and urine culture performed. Patients with missing or implausible demographic data were excluded (2.5% of total sample). The primary analysis aimed to determine an SEC threshold that predicted urine culture contamination using receiver operating characteristics (ROC) curve analysis. The a priori secondary analysis explored how demographic variables (age, sex, body mass index) may modify the SEC test performance and whether SECs impacted traditional urinalysis indicators of bacteriuria. A total of 19,328 records were included. ROC curve analysis demonstrated that SEC count was a poor predictor of urine culture contamination (area under the ROC curve = 0.680, 95% confidence interval [CI] = 0.671 to 0.689). In secondary analysis, the positive likelihood ratio (LR+) of predicting bacteriuria via urinalysis among noncontaminated specimens was 4.98 (95% CI = 4.59 to 5.40) in the absence of SECs, but the LR+ fell to 2.35 (95% CI = 2.17 to 2.54) for samples with more than 8 SECs/low-powered field (lpf). In an independent validation cohort, urinalysis samples with fewer than 8 SECs/lpf predicted bacteriuria better (sensitivity = 75%, specificity = 84%) than samples with more than 8 SECs/lpf (sensitivity = 86%, specificity = 70%; diagnostic odds ratio = 17.5 [14.9 to 20.7] vs. 8.7 [7.3 to 10.5]). Squamous epithelial cells are a poor predictor of urine culture contamination, but may predict poor predictive performance of traditional urinalysis measures. © 2016 by the Society for Academic Emergency Medicine.

  9. 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

  10. Climate Change Impacts and Adaptation to Flow of Swat River and Glaciers in Hindu Kush Ranges, Swat District, Pakistan (2003-2013

    Directory of Open Access Journals (Sweden)

    Saifullah Khan

    2016-06-01

    Full Text Available This work aims at the climate change impacts and adaptation to surface flow of Swat river and glacier resources in Swat river catchments area, Hindu Kush ranges, Northwest Pakistan. The data about temperature and precipitation have been collected from the Pakistan Meteorological Department, Karachi, whereas the Swat River flow data from the Irrigation Department, Peshawar, Khyber Pukhtunkhwa. Two types of climate that is humid and undifferentiated highlands prevail over the area. The total precipitation recorded has been 41.8inches (1061.7 millimeters with mean monthly precipitation of 3.5 inches (88.9 millimeters having a decrease of -0.1 inch (-2.8 millimeters. The area has been humid during 2004 and currently at the threshold of the sub-humid climates (20-40 inches. Kalam valley experiences cold long winters (7 months and short warm summers (5 months. The mean temperature reveals an increase of 0.90C, maximum temperature 0.40C and mean minimum temperature 0.50Celsius. This increase in the temperature of the area has caused water stress and retreat of glaciers and affected the permafrost condition at higher altitudes in the area. The annual flow of the Swat river is 192.2 cubic meter/seconds with a decline of -0.03 cubic m/sec from 2003 to 2013. The annual trend of water flow is directly proportional to precipitation and contrary to maximum temperature during 2003 to 2012 and shows converse condition till 2013. The decrease in the flow of Swat river seems both in winter and summer season. The glaciers and snow covered area of the Kalam valley decreases with passage of time and required mitigation. The vulnerability of the study area to climate change can be minimized by the construction of small reservoirs, river embankments, improvement in sewerage and sanitation, planning for flood water, and revision of the water management policy, implementation, and establishment of research and development funds.

  11. PREDICTION OF GAS INJECTION PERFORMANCE FOR HETEROGENEOUS RESERVOIRS

    Energy Technology Data Exchange (ETDEWEB)

    Martin J. Blunt; Franklin M. Orr Jr

    2000-06-01

    This final report describes research carried out in the Department of Petroleum Engineering at Stanford University from September 1996--May 2000 under a three-year grant from the Department of Energy on the ''Prediction of Gas Injection Performance for Heterogeneous Reservoirs''. The advances from the research include: new tools for streamline-based simulation including the effects of gravity, changing well conditions, and compositional displacements; analytical solutions to 1D compositional displacements which can speed-up gas injection simulation still further; and modeling and experiments that delineate the physics that is unique to three-phase flow.

  12. Prediction of Gas Injection Performance for Heterogeneous Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Franklin M. Orr, Jr; Martin J. Blunt

    1998-03-31

    This project performs research in four main areas: laboratory experiments to measure three-phase relative permeability; network modeling to predict three-phase relative perme- ability; benchmark simulations of gas injection and waterfl ooding at the field scale; and the development of fast streamline techniques to study field-scale oil. The aim of the work is to achieve a comprehensive description of gas injection processes from the pore to the core to the reservoir scale. In this report we provide a detailed description of our measurements of three-phase relative permeability.

  13. 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.

  14. 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.

  15. Impact Assessment of Morphological Features on Watersheds Using SWAT Model

    Science.gov (United States)

    Kaya, S.; Kutukcu, A.

    2016-12-01

    Defining the morphological characteristics of a basin enables carrying out numerous hydrological assessments such as flow value of the basin. In this study the impacts of morphological features designated for the basins on the flow were analyzed. Related to the basin flow shape, drainage density, bifurcation ratio and texture ratio were evaluated using morphological parameters. In the study, Büyük Menderes River Basin and Gediz River Basin which extend across a long valley and flow into the Aegean Sea, were selected as the study area. In the calculation of morphometric parameters regarding the basins, DTM which has 10 m spatial resolution was used. DTM was used as input data for the Soil and Water Assessment Tool - SWAT model which makes significant contributions to the modelling of big basins for hydrologists. The flow value obtained as a result of operating the model facilitates to verify the conducted morphological analyses. On account of operating the model, hydrological parameters on the basis of sub basins were also obtained, which in return makes it possible to understand the hydrological reactions within the basin. The results of the conducted study can be effectively used for integrated watershed management which requires detailed hydrological parameters can be obtained using modern tools such as numerical models.

  16. 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.

  17. Development and application of SWAT to paddy rice district at watershed scale

    Science.gov (United States)

    Shi, Yuzhi; Zhang, Chi; Zhou, Huicheng

    2010-05-01

    In irrigation district, especially in paddy rice fields, agricultural irrigation water use has a great influence on the natural water cycle process at watershed scale. In this study, SWAT model was modified to simulate irrigation water demand and quantify the irrigation return flow coefficient and the irrigation impact coefficient in paddy rice fields. Due to the lack of irrigation observed data, a multi-water source module was add to SWAT to build several feasible extraction scenarios, and a new algorithm of automatic irrigation application was implemented too. According to the simulation accuracy, the optimal scenario was selected to use in the new SWAT model, and then was applied to Changge Irrigation District in Hulan River Basin, northeast China. Comparisons between the enhanced model and old one were conducted at outlet cite, sifangtai. The results showed that the proposed SWAT has higher precision during calibration and validation periods, Nash coefficient of the simulated monthly flow was from 0.74 and 0.69 to 0.88 and 0.80 respectively. in addition, the annual averaged irrigation water and return water were 78 million m3 and 41 million m3, the irrigation return flow coefficient was 0.52, average consumption of irrigation water accounted for 10% of the total runoff. In general, the developed model had been greatly improved as compared to original model. Keywords: SWAT model, hydrological modeling, rice, irrigation return flow coefficient, irrigation impact coefficient

  18. Prediction of Gas Injection Performance for Heterogeneous Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Blunt, Martin J.; Orr, Jr., Franklin M.

    1999-12-20

    This report describes research carried out in the Department of Petroleum Engineering at Stanford University from September 1998 - September 1998 under the third year of a three-year Department of Energy (DOE) grant 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 research is divided into four main 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.

  19. Performance and Prediction: Bayesian Modelling of Fallible Choice in Chess

    Science.gov (United States)

    Haworth, Guy; Regan, Ken; di Fatta, Giuseppe

    Evaluating agents in decision-making applications requires assessing their skill and predicting their behaviour. Both are well developed in Poker-like situations, but less so in more complex game and model domains. This paper addresses both tasks by using Bayesian inference in a benchmark space of reference agents. The concepts are explained and demonstrated using the game of chess but the model applies generically to any domain with quantifiable options and fallible choice. Demonstration applications address questions frequently asked by the chess community regarding the stability of the rating scale, the comparison of players of different eras and/or leagues, and controversial incidents possibly involving fraud. The last include alleged under-performance, fabrication of tournament results, and clandestine use of computer advice during competition. Beyond the model world of games, the aim is to improve fallible human performance in complex, high-value tasks.

  20. 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.

  1. 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.

  2. Do study strategies predict academic performance in medical school?

    Science.gov (United States)

    West, Courtney; Sadoski, Mark

    2011-07-01

     Study strategies, such as time and study management techniques, seem to be consistently related to achievement even when aptitude is controlled for, but the picture is not entirely clear. As there is limited research in this area, we explored the relative strengths of academic aptitude, as measured by the Medical College Admission Test (MCAT), undergraduate grade point average (UGPA) and study strategies, as measured by the Learning and Study Strategies Inventory (LASSI), in predicting academic performance in 106 students in the first semester of an integrated curriculum.  Our purpose was to determine whether relationships could be identified between academic aptitude, study strategies and academic performance which would enable us to provide students with feedback in certain skill areas in order to maximise achievement. Data analysis consisted of four multiple regression analyses. The criterion variables were: semester overall final average, semester written examination average, semester practical examination average, and percentage correct on a customised National Board of Medical Examiners (NBME) examination. The predictor variables in each regression were: MCAT score; UGPA; and subscores on the 10 LASSI subscales for Anxiety, Attitude, Motivation, Concentration, Information Processing, Self-Testing, Selecting Main Idea, Study Aids, Time Management and Test-Taking Strategies. The results of three regressions indicated that two study skills, time management and self-testing, were generally stronger predictors of first-semester academic performance than aptitude. Improving the prioritisation and organisation of study time and teaching students to predict, compose and answer their own questions when studying may help to advance student performance regardless of student aptitude, especially on course-specific examinations. © Blackwell Publishing Ltd 2011.

  3. Predicting Short-term Performance of Multifocal Contact Lenses.

    Science.gov (United States)

    Diec, Jennie; Tilia, Daniel; Naduvilath, Thomas; Bakaraju, Ravi C

    2017-11-01

    To investigate if initial multifocal contact lens (MFCL) performance predicts short-term dispensing performance. A retrospective analysis of 55 participants (Px) in a masked, crossover, clinical trial, using ACUVUE OASYS for Presbyopia and AIR OPTIX AQUA Multifocal. Subjective questionnaires were administered at the following instances: initial fitting, two take home questionnaires (THQ) completed between days 2 and 4 and at assessment, ≥5 days after fitting. Questionnaires included vision clarity and lack of ghosting at distance, intermediate and near at day/night time points rated on a 1 to 10 (1-step, 10 most favorable) rating scale. Vision stability, vision while driving, overall vision satisfaction, willingness to purchase and comfort, as well as acuity-based measures were also collected. There were no statistical differences in comfort and vision at all distances, in vision stability or driving at either time points between THQ and assessment (P>0.05). However, there was a statistical decline in subjective overall vision satisfaction and comfort between fitting and assessment visits (P<0.001). Willingness to purchase remained the same at fitting and assessment in 68% of Px, whereas only 4% of Px converted to a positive willingness to purchase at assessment. The majority of acuity-based measures remained constant between fitting and assessment visits. Initial performance at fitting was not able to predict short-term performance of MFCL. Subjective measures peaked at fitting and declined thereafter whereas acuity-based measures remained constant. Utility of subjective rating tools may aid practitioners to gauge success of MFCL.

  4. Academic performance, career potential, creativity, and job performance: can one construct predict them all?

    Science.gov (United States)

    Kuncel, Nathan R; Hezlett, Sarah A; Ones, Deniz S

    2004-01-01

    This meta-analysis addresses the question of whether 1 general cognitive ability measure developed for predicting academic performance is valid for predicting performance in both educational and work domains. The validity of the Miller Analogies Test (MAT; W. S. Miller, 1960) for predicting 18 academic and work-related criteria was examined. MAT correlations with other cognitive tests (e.g., Raven's Matrices [J. C. Raven, 1965]; Graduate Record Examinations) also were meta-analyzed. The results indicate that the abilities measured by the MAT are shared with other cognitive ability instruments and that these abilities are generalizably valid predictors of academic and vocational criteria, as well as evaluations of career potential and creativity. These findings contradict the notion that intelligence at work is wholly different from intelligence at school, extending the voluminous literature that supports the broad importance of general cognitive ability (g).

  5. Soil and Water Assessment Tool model predictions of annual maximum pesticide concentrations in high vulnerability watersheds.

    Science.gov (United States)

    Winchell, Michael F; Peranginangin, Natalia; Srinivasan, Raghavan; Chen, Wenlin

    2017-11-29

    Recent national regulatory assessments of potential pesticide exposure of threatened and endangered species in aquatic habitats have led to increased need for watershed-scale predictions of pesticide concentrations in flowing water bodies. This study was conducted to assess the ability of the uncalibrated Soil and Water Assessment Tool (SWAT) to predict annual maximum pesticide concentrations in the flowing water bodies of highly vulnerable small- to medium-sized watersheds. The SWAT was applied to 27 watersheds, largely within the midwest corn belt of the United States, ranging from 20 to 386 km2 , and evaluated using consistent input data sets and an uncalibrated parameterization approach. The watersheds were selected from the Atrazine Ecological Exposure Monitoring Program and the Heidelberg Tributary Loading Program, both of which contain high temporal resolution atrazine sampling data from watersheds with exceptionally high vulnerability to atrazine exposure. The model performance was assessed based upon predictions of annual maximum atrazine concentrations in 1-d and 60-d durations, predictions critical in pesticide-threatened and endangered species risk assessments when evaluating potential acute and chronic exposure to aquatic organisms. The simulation results showed that for nearly half of the watersheds simulated, the uncalibrated SWAT model was able to predict annual maximum pesticide concentrations within a narrow range of uncertainty resulting from atrazine application timing patterns. An uncalibrated model's predictive performance is essential for the assessment of pesticide exposure in flowing water bodies, the majority of which have insufficient monitoring data for direct calibration, even in data-rich countries. In situations in which SWAT over- or underpredicted the annual maximum concentrations, the magnitude of the over- or underprediction was commonly less than a factor of 2, indicating that the model and uncalibrated parameterization

  6. 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.

  7. Using the detectability index to predict P300 speller performance

    Science.gov (United States)

    Mainsah, B. O.; Collins, L. M.; Throckmorton, C. S.

    2016-12-01

    Objective. The P300 speller is a popular brain-computer interface (BCI) system that has been investigated as a potential communication alternative for individuals with severe neuromuscular limitations. To achieve acceptable accuracy levels for communication, the system requires repeated data measurements in a given signal condition to enhance the signal-to-noise ratio of elicited brain responses. These elicited brain responses, which are used as control signals, are embedded in noisy electroencephalography (EEG) data. The discriminability between target and non-target EEG responses defines a user’s performance with the system. A previous P300 speller model has been proposed to estimate system accuracy given a certain amount of data collection. However, the approach was limited to a static stopping algorithm, i.e. averaging over a fixed number of measurements, and the row-column paradigm. A generalized method that is also applicable to dynamic stopping (DS) algorithms and other stimulus paradigms is desirable. Approach. We developed a new probabilistic model-based approach to predicting BCI performance, where performance functions can be derived analytically or via Monte Carlo methods. Within this framework, we introduce a new model for the P300 speller with the Bayesian DS algorithm, by simplifying a multi-hypothesis to a binary hypothesis problem using the likelihood ratio test. Under a normality assumption, the performance functions for the Bayesian algorithm can be parameterized with the detectability index, a measure which quantifies the discriminability between target and non-target EEG responses. Main results. Simulations with synthetic and empirical data provided initial verification of the proposed method of estimating performance with Bayesian DS using the detectability index. Analysis of results from previous online studies validated the proposed method. Significance. The proposed method could serve as a useful tool to initially assess BCI performance

  8. Case Study: Effect of Climatic Characterization on River Discharge in an Alpine-Prealpine Catchment of the Spanish Pyrenees Using the SWAT Model

    Directory of Open Access Journals (Sweden)

    Leticia Palazón

    2016-10-01

    Full Text Available The new challenges in assessment of water resources demand new approaches and tools, such as the use of hydrologic models, which could serve to assist managers in the prediction, planning and management of catchment water supplies in view of increased demand of water for irrigation and climatic change. Good characterization of the spatial patterns of climate variables is of paramount importance in hydrological modelling. This is especially so when modelling mountain environments which are characterized by strong altitudinal climate gradients. However, very often there is a poor distribution of climatic stations in these areas, which in many cases, results in under representation of high altitude areas with respect to climatic data. This results in the poor performance of the models. In the present study, the Soil and Water Assessment Tool (SWAT model was applied to the Barasona reservoir catchment in the Central Spanish Pyrenees in order to assess the influence of different climatic characterizations in the monthly river discharges. Four simulations with different input data were assessed, using only the available climate data (A1; the former plus one synthetic dataset at a higher altitude (B1; and both plus the altitudinal climate gradient (A2 and B2. The model’s performance was evaluated against the river discharges for the representative periods of 2003–2005 and 1994–1996 by means of commonly used statistical measures. The best results were obtained using the altitudinal climate gradient alone (scenario A2. This study provided insight into the importance of taking into account the sources and the spatial distribution of weather data in modelling water resources in mountainous catchments.

  9. Twenty Questions game performance on medical school entrance predicts clinical performance.

    Science.gov (United States)

    Williams, Reed G; Klamen, Debra L

    2015-09-01

    This study is based on the premise that the game of 'Twenty Questions' (TQ) tests the knowledge people acquire through their lives and how well they organise and store it so that they can effectively retrieve, combine and use it to address new life challenges. Therefore, performance on TQ may predict how effectively medical school applicants will organise and store knowledge they acquire during medical training to support their work as doctors. This study was designed to determine whether TQ game performance on medical school entrance predicts performance on a clinical performance examination near graduation. This prospective, longitudinal, observational study involved each medical student in one class playing a game of TQ on a non-medical topic during the first week of medical school. Near graduation, these students completed a 14-case clinical performance examination. Performance on the TQ task was compared with performance on the clinical performance examination. The 24 students who exhibited a logical approach to the TQ task performed better on all senior clinical performance examination measures than did the 26 students who exhibited a random approach. Approach to the task was a better predictor of senior examination diagnosis justification performance than was the Medical College Admission Test (MCAT) Biological Science Test score and accounts for a substantial amount of score variation not attributable to a co-relationship with MCAT Biological Science Test performance. Approach to the TQ task appears to be one reasonable indicator of how students process and store knowledge acquired in their everyday lives and may be a useful predictor of how they will process the knowledge acquired during medical training. The TQ task can be fitted into one slot of a mini medical interview. © 2015 John Wiley & Sons Ltd.

  10. 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.

  11. Artificial neural network simulator for SOFC performance prediction

    Science.gov (United States)

    Arriagada, Jaime; Olausson, Pernilla; Selimovic, Azra

    This paper describes the development of a novel modelling tool for evaluation of solid oxide fuel cell (SOFC) performance. An artificial neural network (ANN) is trained with a reduced amount of data generated by a validated cell model, and it is then capable of learning the generic functional relationship between inputs and outputs of the system. Once the network is trained, the ANN-driven simulator can predict different operational parameters of the SOFC (i.e. gas flows, operational voltages, current density, etc.) avoiding the detailed description of the fuel cell processes. The highly parallel connectivity within the ANN further reduces the computational time. In a real case, the necessary data for training the ANN simulator would be extracted from experiments. This simulator could be suitable for different applications in the fuel cell field, such as, the construction of performance maps and operating point optimisation and analysis. All this is performed with minimum time demand and good accuracy. This intelligent model together with the operational conditions may provide useful insight into SOFC operating characteristics and improved means of selecting operating conditions, reducing costs and the need for extensive experiments.

  12. 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.

  13. 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.

  14. Performance Prediction of Mechanical Pump in STELLA-1

    Energy Technology Data Exchange (ETDEWEB)

    Han, Ji-Woong; Cho, Chungho; Jeong, Ji-Young [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2014-10-15

    Under a mid- and long-term nuclear R-D program, STELLA (Sodium Integral Effect Test Loop for Safety Simulation and Assessment) project is in progress in KAERI (Korea Atomic Energy Research Institute). In STELLA-1, the experiments for the evaluation of heat exchangers such as DHX (Decay heat exchanger) and AHX (Air heat exchanger) are being performed, and those for PHTS (Primary heat transport system) mechanical pump are being prepared. The detailed design of each component is based on that of a 600MWe demonstration reactor. The model pump installed in STELLA-1 was scaled down based on the scaling law. Since the reference reactor of STELLA-1 is a 600MWe pool type demonstration reactor, some design modifications were inevitable between pool type prototype pump and loop type model pump, such as outer case and inlet pipe. In this study performance evaluation on the model pump has been done by CFD methods. The Design modeler in ANSYS Workbench was utilized in modeling process. The computations were performed using the commercial code ANSYS CFX. The overall hydraulic behaviors in the model pump have been predicted at a steady state condition.

  15. Orientation toward humans predicts cognitive performance in orang-utans.

    Science.gov (United States)

    Damerius, Laura A; Forss, Sofia I F; Kosonen, Zaida K; Willems, Erik P; Burkart, Judith M; Call, Josep; Galdikas, Birute M F; Liebal, Katja; Haun, Daniel B M; van Schaik, Carel P

    2017-01-09

    Non-human animals sometimes show marked intraspecific variation in their cognitive abilities that may reflect variation in external inputs and experience during the developmental period. We examined variation in exploration and cognitive performance on a problem-solving task in a large sample of captive orang-utans (Pongo abelii &P. pygmaeus, N = 103) that had experienced different rearing and housing conditions during ontogeny, including human exposure. In addition to measuring exploration and cognitive performance, we also conducted a set of assays of the subjects' psychological orientation, including reactions towards an unfamiliar human, summarized in the human orientation index (HOI), and towards novel food and objects. Using generalized linear mixed models we found that the HOI, rather than rearing background, best predicted both exploration and problem-solving success. Our results suggest a cascade of processes: human orientation was accompanied by a change in motivation towards problem-solving, expressed in reduced neophobia and increased exploration variety, which led to greater experience, and thus eventually to higher performance in the task. We propose that different experiences with humans caused individuals to vary in curiosity and understanding of the physical problem-solving task. We discuss the implications of these findings for comparative studies of cognitive ability.

  16. Resilience does not predict academic performance in gross anatomy.

    Science.gov (United States)

    Elizondo-Omaña, Rodrigo Enrique; García-Rodríguez, María de los Angeles; Hinojosa-Amaya, José Miguel; Villarreal-Silva, Eliud Enrique; Avilan, Rosa Ivette Guzmán; Cruz, Juan José Bazaldúa; Guzmán-López, Santos

    2010-01-01

    Few studies have evaluated resilience in an academic environment as it relates to academic success or failure. This work sought to assess resilience in regular and remedial students of gross anatomy during the first and second semesters of medical school and to correlate this personal trait with academic performance. Two groups of students were compared: the first group included first-year medical students in the regular course, and the second group included first-year medical students who did not pass the regular anatomy course and so were enrolled in the remedial course. Both groups completed anonymous surveys designed to gather demographic data and establish scores on the Connor-Davidson resilience scale, which includes 25 statements rated zero to four on a Likert scale (maximum score 100). The average resilience score was the same for both groups, 80 +/- 9. The average anatomy grades differed significantly between regular students (67+/- 15.0) and remedial students (61 +/- 12.0). While there was no overall correlation between resilience score and anatomy grade, regular students with resilience scores of 75 or greater showed slightly better academic performance than their classmates. Similarly, remedial students with resilience scores of 87 or greater faired better academically. Resilience does not predict academic performance in gross anatomy, and further work is necessary to identify those intrinsic and extrinsic factors that influence students' achievements. Copyright 2010 American Association of Anatomists.

  17. Runoff Simulation in the Upper Reaches of Heihe River Basin Based on the RIEMS–SWAT Model

    Directory of Open Access Journals (Sweden)

    Songbing Zou

    2016-10-01

    Full Text Available In the distributed hydrological simulations for complex mountain areas, large amounts of meteorological input parameters with high spatial and temporal resolutions are necessary. However, the extreme scarcity and uneven distribution of the traditional meteorological observation stations in cold and arid regions of Northwest China makes it very difficult in meeting the requirements of hydrological simulations. Alternatively, regional climate models (RCMs, which can provide a variety of distributed meteorological data with high temporal and spatial resolution, have become an effective solution to improve hydrological simulation accuracy and to further study water resource responses to human activities and global climate change. In this study, abundant and evenly distributed virtual weather stations in the upper reaches of the Heihe River Basin (HRB of Northwest China were built for the optimization of the input data, and thus a regional integrated environmental model system (RIEMS based on RCM and a distributed hydrological model of soil and water assessment tool (SWAT were integrated as a coupled climate–hydrological RIEMS-SWAT model, which was applied to simulate monthly runoff from 1995 to 2010 in the region. Results show that the simulated and observed values are close; Nash–Sutcliffe efficiency is higher than 0.65; determination coefficient (R2 values are higher than 0.70; percent bias is controlled within ±20%; and root-mean-square-error-observation standard deviation ratio is less than 0.65. These results indicate that the coupled model can present basin hydrological processes properly, and provide scientific support for prediction and management of basin water resources.

  18. Hydrological effects of the increased CO2 and climate change in the Upper Mississippi River Basin using a modified SWAT

    Science.gov (United States)

    Wu, Y.; Liu, S.; Abdul-Aziz, O. I.

    2012-01-01

    Increased atmospheric CO2 concentration and climate change may significantly impact the hydrological and meteorological processes of a watershed system. Quantifying and understanding hydrological responses to elevated ambient CO2 and climate change is, therefore, critical for formulating adaptive strategies for an appropriate management of water resources. In this study, the Soil and Water Assessment Tool (SWAT) model was applied to assess the effects of increased CO2 concentration and climate change in the Upper Mississippi River Basin (UMRB). The standard SWAT model was modified to represent more mechanistic vegetation type specific responses of stomatal conductance reduction and leaf area increase to elevated CO2 based on physiological studies. For estimating the historical impacts of increased CO2 in the recent past decades, the incremental (i.e., dynamic) rises of CO2 concentration at a monthly time-scale were also introduced into the model. Our study results indicated that about 1–4% of the streamflow in the UMRB during 1986 through 2008 could be attributed to the elevated CO2 concentration. In addition to evaluating a range of future climate sensitivity scenarios, the climate projections by four General Circulation Models (GCMs) under different greenhouse gas emission scenarios were used to predict the hydrological effects in the late twenty-first century (2071–2100). Our simulations demonstrated that the water yield would increase in spring and substantially decrease in summer, while soil moisture would rise in spring and decline in summer. Such an uneven distribution of water with higher variability compared to the baseline level (1961–1990) may cause an increased risk of both flooding and drought events in the basin.

  19. Choosing a method for predicting economic performance of companies

    Directory of Open Access Journals (Sweden)

    J. Dvořáček

    2012-10-01

    Full Text Available This paper reports on the efforts to find a method for predicting economic results of companies. The input data files consist of 93 profitable companies and 93 bankrupt firms. From the total number of 93 firms in both categories, data of 72 firms served for establishing a classification criterion, and for the rest of 21 firms, a prognosis of their economic development was performed. The classification criterion for prognosticating the future economic development has been established by applications of discriminate analysis, logit analysis, and artificial neural network methods. The application of artificial neural networks has provided for better classification accuracies of 90,48 % for successful firms, and 100 % for bankrupt firms.

  20. 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.

  1. Environmental gamma radiation measurement in district Swat, Pakistan.

    Science.gov (United States)

    Jabbar, T; Khan, K; Subhani, M S; Akhter, P; Jabbar, A

    2008-01-01

    External exposure to environmental gamma ray sources is an important component of exposure to the public. A survey was carried out to determine activity concentration levels and associated doses from (226)Ra, (232)Th, (40)K and (137)Cs by means of high-resolution gamma ray spectrometry in the Swat district, famous for tourism. The mean concentrations for (226)Ra, (232)Th and (40)K were found to be 50.4 +/- 0.7, 34.8 +/- 0.7 and 434.5 +/- 7.4 Bq kg(-1), respectively, in soil samples, which are slightly more than the world average values. However, (137)Cs was only found in the soil sample of Barikot with an activity concentration of 34 +/- 1.2 Bq kg(-1). Only (40)K was determined in vegetation samples with an average activity of 172.2 +/- 1.7 Bq kg(-1), whereas in water samples, all radionuclides were found below lower limits of detection. The radium equivalent activity in all soil samples is lower than the limit set in the Organisation for Economic Cooperation and Development report (370 Bq kg(-1)). The value of the external exposure dose has been determined from the content of these radionuclides in soil. The average terrestrial gamma air absorbed dose rate was observed to be 62.4 nGy h(-1), which yields an annual effective dose of 0.08 mSv. The average value of the annual effective dose lies close to the global range of outdoor radiation exposure given in United Nations Scientific Committee on the Effects of Atomic Radiation. However, the main component of the radiation dose to the population residing in the study area arises from cosmic ray due to high altitude.

  2. Application of the Soil and Water Assessment Tool (SWAT Model on a small tropical island (Great River Watershed, Jamaica as a tool in Integrated Watershed and Coastal Zone Management

    Directory of Open Access Journals (Sweden)

    Orville P. Grey

    2014-09-01

    Full Text Available The Great River Watershed, located in north-west Jamaica, is critical for development, particularly for housing, tourism, agriculture, and mining. It is a source of sediment and nutrient loading to the coastal environment including the Montego Bay Marine Park. We produced a modeling framework using the Soil and Water Assessment Tool (SWAT and GIS. The calculated model performance statistics for high flow discharge yielded a Nash-Sutcliffe Efficiency (NSE value of 0.68 and a R² value of 0.70 suggesting good measured and simulated (calibrated discharge correlation. Calibration and validation results for streamflow were similar to the observed streamflows. For the dry season the simulated urban landuse scenario predicted an increase in surface runoff in excess of 150%. During the wet season it is predicted to range from 98 to 234% presenting a significant risk of flooding, erosion and other environmental issues. The model should be used for the remaining 25 watersheds in Jamaica and elsewhere in the Caribbean. The models suggests that projected landuse changes will have serious impacts on available water (streamflow, stream health, potable water treatment, flooding and sensitive coastal ecosystems.

  3. PREDICTION VERSUS REALITY: THE USE OF MATHEMATICAL MODELS TO PREDICT ELITE PERFORMANCE IN SWIMMING AND ATHLETICS AT THE OLYMPIC GAMES

    Directory of Open Access Journals (Sweden)

    Timothy Heazlewood

    2006-12-01

    Full Text Available A number of studies have attempted to predict future Olympic performances in athletics and swimming based on trends displayed in previous Olympic Games. Some have utilised linear models to plot and predict change, whereas others have utilised multiple curve estimation methods based on inverse, sigmoidal, quadratic, cubic, compound, logistic, growth and exponential functions. The non linear models displayed closer fits to the actual data and were used to predict performance changes 10's, 100's and 1000's of years into the future. Some models predicted that in some events male and female times and distances would crossover and females would eventually display superior performance to males. Predictions using mathematical models based on pre-1996 athletics and pre-1998 swimming performances were evaluated based on how closely they predicted sprints and jumps, and freestyle swimming performances for both male and females at the 2000 and 2004 Olympic Games. The analyses revealed predictions were closer for the shorter swimming events where men's 50m and women's 50m and 100m actual times were almost identical to predicted times. For both men and women, as the swim distances increased the accuracy of the predictive model decreased, where predicted times were 4.5-7% faster than actual times achieved. The real trends in some events currently displaying performance declines were not foreseen by the mathematical models, which predicted consistent improvements across all athletic and swimming events selected for in this study

  4. Computational Predictions of the Performance Wright 'Bent End' Propellers

    Science.gov (United States)

    Wang, Xiang-Yu; Ash, Robert L.; Bobbitt, Percy J.; Prior, Edwin (Technical Monitor)

    2002-01-01

    Computational analysis of two 1911 Wright brothers 'Bent End' wooden propeller reproductions have been performed and compared with experimental test results from the Langley Full Scale Wind Tunnel. The purpose of the analysis was to check the consistency of the experimental results and to validate the reliability of the tests. This report is one part of the project on the propeller performance research of the Wright 'Bent End' propellers, intend to document the Wright brothers' pioneering propeller design contributions. Two computer codes were used in the computational predictions. The FLO-MG Navier-Stokes code is a CFD (Computational Fluid Dynamics) code based on the Navier-Stokes Equations. It is mainly used to compute the lift coefficient and the drag coefficient at specified angles of attack at different radii. Those calculated data are the intermediate results of the computation and a part of the necessary input for the Propeller Design Analysis Code (based on Adkins and Libeck method), which is a propeller design code used to compute the propeller thrust coefficient, the propeller power coefficient and the propeller propulsive efficiency.

  5. 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.

  6. Assessing the performance of DNA barcoding using posterior predictive simulations.

    Science.gov (United States)

    Barley, Anthony J; Thomson, Robert C

    2016-05-01

    Accurate estimates of biodiversity are required for research in a broad array of biological subdisciplines including ecology, evolution, systematics, conservation and biodiversity science. The use of statistical models and genetic data, particularly DNA barcoding, has been suggested as an important tool for remedying the large gaps in our current understanding of biodiversity. However, the reliability of biodiversity estimates obtained using these approaches depends on how well the statistical models that are used describe the evolutionary process underlying the genetic data. In this study, we utilize data from the Barcode of Life Database and posterior predictive simulations to assess the performance of DNA barcoding under commonly used substitution models. We demonstrate that the success of DNA barcoding varies widely across DNA substitution models and that model choice has a substantial impact on the number of operational taxonomic units identified (changing results by ~4-31%). Additionally, we demonstrate that the widely followed practice of a priori assuming the Kimura 2-parameter model for DNA barcoding is statistically unjustified and should be avoided. Using both data-based and inference-based test statistics, we detect variation in model performance across taxonomic groups, clustering algorithms, genetic divergence thresholds and substitution models. Taken together, these results illustrate the importance of considering both model selection and model adequacy in studies quantifying biodiversity. © 2016 John Wiley & Sons Ltd.

  7. 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.

  8. Can formative quizzes predict or improve summative exam performance?

    Science.gov (United States)

    Zhang, Niu; Henderson, Charles N R

    2015-03-01

    Despite wide use, the value of formative exams remains unclear. We evaluated the possible benefits of formative assessments in a physical examination course at our chiropractic college. Three hypotheses were examined: (1) Receiving formative quizzes (FQs) will increase summative exam (SX) scores, (2) writing FQ questions will further increase SE scores, and (3) FQs can predict SX scores. Hypotheses were tested across three separate iterations of the class. The SX scores for the control group (Class 3) were significantly less than those of Classes 1 and 2, but writing quiz questions and taking FQs (Class 1) did not produce significantly higher SX scores than only taking FQs (Class 2). The FQ scores were significant predictors of SX scores, accounting for 52% of the SX score. Sex, age, academic degrees, and ethnicity were not significant copredictors. Our results support the assertion that FQs can improve written SX performance, but students producing quiz questions didn't further increase SX scores. We concluded that nonthreatening FQs may be used to enhance student learning and suggest that they also may serve to identify students who, without additional remediation, will perform poorly on subsequent summative written exams.

  9. Can formative quizzes predict or improve summative exam performance?*

    Science.gov (United States)

    Zhang, Niu; Henderson, Charles N.R.

    2015-01-01

    Objective Despite wide use, the value of formative exams remains unclear. We evaluated the possible benefits of formative assessments in a physical examination course at our chiropractic college. Methods Three hypotheses were examined: (1) Receiving formative quizzes (FQs) will increase summative exam (SX) scores, (2) writing FQ questions will further increase SE scores, and (3) FQs can predict SX scores. Hypotheses were tested across three separate iterations of the class. Results The SX scores for the control group (Class 3) were significantly less than those of Classes 1 and 2, but writing quiz questions and taking FQs (Class 1) did not produce significantly higher SX scores than only taking FQs (Class 2). The FQ scores were significant predictors of SX scores, accounting for 52% of the SX score. Sex, age, academic degrees, and ethnicity were not significant copredictors. Conclusion Our results support the assertion that FQs can improve written SX performance, but students producing quiz questions didn't further increase SX scores. We concluded that nonthreatening FQs may be used to enhance student learning and suggest that they also may serve to identify students who, without additional remediation, will perform poorly on subsequent summative written exams. PMID:25517737

  10. Prediction of Gas Injection Performance for Heterogeneous Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Blunt, Michael J.; Orr, Franklin M.

    1999-05-26

    This report describes research carried out in the Department of Petroleum Engineering at Stanford University from September 1996 - September 1997 under the first year of a three-year Department of Energy grant 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 main 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 stage 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.

  11. White matter fractional anisotropy predicts balance performance in older adults.

    Science.gov (United States)

    Van Impe, Annouchka; Coxon, James P; Goble, Daniel J; Doumas, Mihail; Swinnen, Stephan P

    2012-09-01

    Aging is characterized by brain structural changes that may compromise motor functions. In the context of postural control, white matter integrity is crucial for the efficient transfer of visual, proprioceptive and vestibular feedback in the brain. To determine the role of age-related white matter decline as a function of the sensory feedback necessary to correct posture, we acquired diffusion weighted images in young and old subjects. A force platform was used to measure changes in body posture under conditions of compromised proprioceptive and/or visual feedback. In the young group, no significant brain structure-balance relations were found. In the elderly however, the integrity of a cluster in the frontal forceps explained 21% of the variance in postural control when proprioceptive information was compromised. Additionally, when only the vestibular system supplied reliable information, the occipital forceps was the best predictor of balance performance (42%). Age-related white matter decline may thus be predictive of balance performance in the elderly when sensory systems start to degrade. Copyright © 2012 Elsevier Inc. All rights reserved.

  12. 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....

  13. 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

  14. Calibration and validation of the SWAT model for a forested watershed in coastal South Carolina

    Science.gov (United States)

    Devendra M. Amatya; Elizabeth B. Haley; Norman S. Levine; Timothy J. Callahan; Artur Radecki-Pawlik; Manoj K. Jha

    2008-01-01

    Modeling the hydrology of low-gradient coastal watersheds on shallow, poorly drained soils is a challenging task due to the complexities in watershed delineation, runoff generation processes and pathways, flooding, and submergence caused by tropical storms. The objective of the study is to calibrate and validate a GIS-based spatially-distributed hydrologic model, SWAT...

  15. SWAT.nz: New-Zeland-based "Sand Waves and Turbulence" experimental programme

    Science.gov (United States)

    Coleman, Stephen; Nikora, Vladimir; Melville, Bruce; Goring, Derek; Clunie, Thomas; Friedrich, Heide

    2008-06-01

    The SWAT.nz ("New-Zealand-based Sand Waves and Turbulence") research programme was carried out to advance understanding of subaqueous sand waves. The programme was based around detailed measurements at varying scales of bed morphologies and associated flow fields as sand waves formed from plane-bed conditions and grew to equilibrium. This paper outlines the philosophy and details of the SWAT.nz programme, with the aim of providing insight into experiment and analysis design and methodologies for studies of highly-variable bed surfaces and flows. Example challenges addressed in the SWAT.nz programme include the measurement over large spatial domains of developing flow fields and three-dimensional bed morphology, including flow measurements below roughness (sand-wave) crests, and how to interpret the collected measurements. Insights into sand-wave dynamics that have arisen from the programme are presented to illustrate the values of the SWAT.nz programme and the developed methodologies. Results are presented in terms of mobile-bed processes, and flow-bed interaction and flow processes for fixed-bed roughness and erodible beds, respectively.

  16. Modeling crop water productivity using a coupled SWAT-MODSIM model

    Science.gov (United States)

    This study examines the water productivity of irrigated wheat and maize yields in Karkheh River Basin (KRB) in the semi-arid region of Iran using a coupled modeling approach consisting of the hydrological model (SWAT) and the river basin water allocation model (MODSIM). Dynamic irrigation requireme...

  17. Flow forecast by SWAT model and ANN in Pracana basin, Portugal

    NARCIS (Netherlands)

    Demirel, M.C.; Venancio, Anabela; Kahya, Ercan

    2009-01-01

    This study provides a unique opportunity to analyze the issue of flow forecast based on the soil and water assessment tool (SWAT) and artificial neural network (ANN) models. In last two decades, the ANNs have been extensively applied to various water resources system problems. In this study, the

  18. Assimilating Remotely Sensed Surface Soil Moisture into SWAT using Ensemble Kalman Filter

    Science.gov (United States)

    In this study, a 1-D Ensemble Kalman Filter has been used to update the soil moisture states of the Soil and Water Assessment Tool (SWAT) model. Experiments were conducted for the Cobb Creek Watershed in southeastern Oklahoma for 2006-2008. Assimilation of in situ data proved limited success in the ...

  19. Modelling land use change across elevation gradients in district Swat, Pakistan

    NARCIS (Netherlands)

    Qasim, M.; Termansen, M.; Hubacek, K.; Fleskens, L.

    2013-01-01

    District Swat is part of the high mountain Hindu-Kush Himalayan region of Pakistan. Documentation and analysis of land use change in this region is challenging due to very disparate accounts of the state of forest resources and limited accessible data. Such analysis is, however, important due to

  20. Anthropogenic factors as an element of uncertainty in hydrological modelling of water yield with SWAT

    Directory of Open Access Journals (Sweden)

    R. Corobov

    2016-05-01

    Full Text Available In 2014 the SWAT (Soil and Water Assessment Tool model was used as a basis for follow-up investigations of Moldova’s small rivers potential flow. The first step of the study included the validation of SWAT for local conditions. As an experimental area, the Cogilnic River watershed was selected. Interim steps included the watershed delineation aimed to identify the subwatersheds and the Hydrological Response Units (small entities with the same characteristics of hydrologic soil type, land use and slopes. To address these tasks, the land cover, soil and slope layers, based on the Digital Elevation Model, were integrated in the SWAT environment. These thematic layers, alongside with long-term information on local monthly maximum and minimum temperatures and precipitation, enabled reflecting the differences in hydrological conditions and defining the watershed runoff. However, the validation of the modelling outputs, carried out through comparison of a simulated water yield from the studied watershed with actual Cogilnic streamflow measures, observed in 2010-2012, showed a great discrepancy between these parameters caused by anthropogenic loading on this small river. Thus, a ‘classical’ SWAT modelling needs to account for real environmental conditions and water use in the study area.

  1. Individual Differences in Nonsymbolic Ratio Processing Predict Symbolic Math Performance.

    Science.gov (United States)

    Matthews, Percival G; Lewis, Mark Rose; Hubbard, Edward M

    2016-02-01

    What basic capacities lay the foundation for advanced numerical cognition? Are there basic nonsymbolic abilities that support the understanding of advanced numerical concepts, such as fractions? To date, most theories have posited that previously identified core numerical systems, such as the approximate number system (ANS), are ill-suited for learning fraction concepts. However, recent research in developmental psychology and neuroscience has revealed a ratio-processing system (RPS) that is sensitive to magnitudes of nonsymbolic ratios and may be ideally suited for supporting fraction concepts. We provide evidence for this hypothesis by showing that individual differences in RPS acuity predict performance on four measures of mathematical competence, including a university entrance exam in algebra. We suggest that the nonsymbolic RPS may support symbolic fraction understanding much as the ANS supports whole-number concepts. Thus, even abstract mathematical concepts, such as fractions, may be grounded not only in higher-order logic and language, but also in basic nonsymbolic processing abilities. © The Author(s) 2015.

  2. Advance predictive tool to optimise combustion and emission performance

    Energy Technology Data Exchange (ETDEWEB)

    Gimenez, A.; Azcue, J.; Estrela, M.; Benoit, B.; Peledan, F.; Abbas, T.; Pina, J.L.

    2001-07-01

    At the present time, continuous emission monitoring systems (CEMS) have associated high installation and maintenance costs. Moreover, all European industries are involved in policies to increase the process efficiency and reduce cost, evaluating the environmental effect as an internal cost of the process. There is a strategic need to develop alternative systems to optimise the process and environmental performance with an acceptable and competitive cost. In consequence, the main objective of the project is to develop a predictive emission monitoring system (PEMS) as an alternative less expensive and more reliable than the current CEMS systems, achieving an effective combustion optimisation. The RESPEC system and tools are described in the paper. The methodology is being applied in the coal-fired Puente Nuevo Thermoelectric Power Plant to optimise operating conditions. Neural networks are used to control or minimise NOx, SO{sub x} and loss of ignition (LOI); other modules of the system involve application of neuro or fuzzy logic. 9 refs., 11 figs., 10 tabs.

  3. Impacts of manure application on SWAT model outputs in the Xiangxi River watershed

    Science.gov (United States)

    Liu, Ruimin; Wang, Qingrui; Xu, Fei; Men, Cong; Guo, Lijia

    2017-12-01

    SWAT (Soil and Water Assessment Tool) model has been widely used to simulate agricultural non-point source (ANPS) pollution; however, the impacts of livestock manure application on SWAT model outputs have not been well studied. The objective of this study was to investigate the environmental effects of livestock manure application based on the SWAT model in the Xiangxi River watershed, which is one of the largest tributaries of the Three Gorges Reservoir in China. Three newly-built manure databases (NB) were created and applied to different subbasins based on the actual livestock manure discharging amount. The calibration and validation values of SWAT model outputs obtained from the NB manure application and the original mixed (OM) manure were compared. The study results are as follows: (1) The livestock industry of Xingshan County developed quickly between 2005 and 2015. The downstream of the Xiangxi River (Huangliang, Shuiyuesi and Xiakou) had the largest livestock amount, and largely accounted for manure, total nitrogen (TN) and total phosphorus (TP) production (>50%). (2) The NB manure application resulted in less phosphorus pollution (1686.35 kg for ORGP and 31.70 kg for MINP) than the OM manure application. Compared with the upstream, the downstream was influenced more by the manure application. (3) The SWAT results obtained from the NB manure had a better calibration and validation values than those from the OM manure. For ORGP, R2 and NSE values were 0.77 and 0.65 for the NB manure calibration; and the same values for the OM manure were 0.72 and 0.61, respectively. For MINP, R2 values were 0.65 and 0.62 for the NB manure and the OM manure, and the NSE values were 0.60 and 0.58, respectively. The results indicated that the built-in fertilizer database in SWAT has its limitation because it is set up for the simulation in the USA. Thus, when livestock manure is considered in a SWAT simulation, a newly built fertilizer database needs to be set up to represent

  4. Radio link design framework for WSN deployment and performance prediction

    Science.gov (United States)

    Saponara, Sergio; Giannetti, Filippo

    2017-05-01

    For an easy implementation of wireless sensor and actuator networks (WSAN), the state-of-the-art is offering single-chip solutions embedding in the same device a microcontroller core with a wireless transceiver. These internet-on-chip devices support different protocols (Bluetooth, ZigBee, Bluetooth Low Energy, sub- GHz links), from about 300 MHz to 6 GHz, with max. sustained bit-rates from 250 kb/s (sub-GHz links) to 4 Mb/s (Wi-Fi), and different trade-offs between RX sensitivity (from -74 to -100 dBm), RX noise figure (few dB to 10 dB), maximum TX power (from 0 to 22 dBm), link distances, power consumption levels (from few mW to several hundreds of mW). One limit for their successful application is the missing of an easy-to-use modeling and simulation environment to plan their deployment. The need is to predict, before installing a network, at which distances the sensors can be deployed, the real achievable bit-rate, communication latency, outage probability, power consumption, battery duration. To this aim, this paper presents the H2AWKS (Harsh environment and Hardware Aware Wireless linK Simulator) simulator, which allows the planning of a WSAN taking into account environment constraints and hardware parameters. Applications of H2AWKS to real WSAN case studies prove that it is an easy to use simulation environment, which allows design exploration of the system performance of a WSAN as a function of the operating environment and of the hardware parameters of the used devices.

  5. A multi basin SWAT model analysis of runoff and sedimentation in the Blue Nile, Ethiopia

    Directory of Open Access Journals (Sweden)

    Z. M. Easton

    2010-10-01

    Full Text Available A multi basin analysis of runoff and erosion in the Blue Nile Basin, Ethiopia was conducted to elucidate sources of runoff and sediment. Erosion is arguably the most critical problem in the Blue Nile Basin, as it limits agricultural productivity in Ethiopia, degrades benthos in the Nile, and results in sedimentation of dams in downstream countries. A modified version of the Soil and Water Assessment Tool (SWAT model was developed to predict runoff and sediment losses from the Ethiopian Blue Nile Basin. The model simulates saturation excess runoff from the landscape using a simple daily water balance coupled to a topographic wetness index in ways that are consistent with observed runoff processes in the basin. The spatial distribution of landscape erosion is thus simulated more correctly. The model was parameterized in a nested design for flow at eight and sediment at three locations in the basin. Subbasins ranged in size from 1.3 to 174 000 km2, and interestingly, the partitioning of runoff and infiltrating flow could be predicted by topographic information. Model predictions showed reasonable accuracy (Nash Sutcliffe Efficiencies ranged from 0.53–0.92 with measured data across all sites except Kessie, where the water budget could not be closed; however, the timing of flow was well captured. Runoff losses increased with rainfall during the monsoonal season and were greatest from areas with shallow soils and large contributing areas. Analysis of model results indicate that upland landscape erosion dominated sediment delivery to the main stem of the Blue Nile in the early part of the growing season when tillage occurs and before the soil was wetted up and plant cover was established. Once plant cover was established in mid August landscape erosion was negligible and sediment export was dominated by channel processes and re-suspension of landscape sediment deposited early in the growing season. These results imply that targeting small

  6. SWAT-MODSIM-PSO optimization of multi-crop planning in the Karkheh River Basin, Iran, under the impacts of climate change.

    Science.gov (United States)

    Fereidoon, Majid; Koch, Manfred

    2018-02-24

    Agriculture is one of the environmental/economic sectors that may adversely be affected by climate change, especially, in already nowadays water-scarce regions, like the Middle East. One way to cope with future changes in absolute as well as seasonal (irrigation) water amounts can be the adaptation of the agricultural crop pattern in a region, i.e. by planting crops which still provide high yields and so economic benefits to farmers under such varying climate conditions. To do this properly, the whole cascade starting from climate change, effects on hydrology and surface water availability, subsequent effects on crop yield, agricultural areas available, and, finally, economic value of a multi-crop cultivation pattern must be known. To that avail, a complex coupled simulation-optimization tool SWAT-LINGO-MODSIM-PSO (SLMP) has been developed here and used to find the future optimum cultivation area of crops for the maximization of the economic benefits in five irrigation-fed agricultural plains in the south of the Karkheh River Basin (KRB) southwest Iran. Starting with the SWAT distributed hydrological model, the KR-streamflow as well as the inflow into the Karkheh-reservoir, as the major storage of irrigation water, is calibrated and validated, based on 1985-2004 observed discharge data. In the subsequent step, the SWAT-predicted streamflow is fed into the MODSIM river basin Decision Support System to simulate and optimize the water allocation between different water users (agricultural, environmental, municipal and industrial) under standard operating policy (SOP) rules. The final step is the maximization of the economic benefit in the five agricultural plains through constrained PSO (particle swarm optimization) by adjusting the cultivation areas (decision variables) of different crops (wheat, barley, maize and "others"), taking into account their specific prizes and optimal crop yields under water deficiency, with the latter computed in the LINGO

  7. Analyses of PWR spent fuel composition using SCALE and SWAT code systems to find correction factors for criticality safety applications adopting burnup credit

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Hee Sung; Suyama, Kenya; Mochizuki, Hiroki; Okuno, Hiroshi; Nomura, Yasushi [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

    2001-01-01

    The isotopic composition calculations were performed for 26 spent fuel samples from the Obrigheim PWR reactor and 55 spent fuel samples from 7 PWR reactors using the SAS2H module of the SCALE4.4 code system with 27, 44 and 238 group cross-section libraries and the SWAT code system with the 107 group cross-section library. For the analyses of samples from the Obrigheim PWR reactor, geometrical models were constructed for each of SCALE4.4/SAS2H and SWAT. For the analyses of samples from 7 PWR reactors, the geometrical model already adopted in the SCALE/SAS2H was directly converted to the model of SWAT. The four kinds of calculation results were compared with the measured data. For convenience, the ratio of the measured to calculated values was used as a parameter. When the ratio is less than unity, the calculation overestimates the measurement, and the ratio becomes closer to unity, they have a better agreement. For many important nuclides for burnup credit criticality safety evaluation, the four methods applied in this study showed good coincidence with measurements in general. More precise observations showed, however: (1) Less unity ratios were found for Pu-239 and -241 for selected 16 samples out of the 26 samples from the Obrigheim reactor (10 samples were deselected because their burnups were measured with Cs-137 non-destructive method, less reliable than Nd-148 method the rest 16 samples were measured with); (2) Larger than unity ratios were found for Am-241 and Cm-242 for both the 16 and 55 samples; (3) Larger than unity ratios were found for Sm-149 for the 55 samples; (4) SWAT was generally accompanied by larger ratios than those of SAS2H with some exceptions. Based on the measured-to-calculated ratios for 71 samples of a combined set in which 16 selected samples and 55 samples were included, the correction factors that should be multiplied to the calculated isotopic compositions were generated for a conservative estimate of the neutron multiplication factor

  8. Genomic prediction of crossbred performance based on purebred data

    DEFF Research Database (Denmark)

    Esfandyari, Hadi; Bijma, P; Henryon, Mark

    2015-01-01

    Understanding the underlying pleiotropic relationships among quantitative traits is integral to predict correlated responses to artificial selection. The availability of large-scale next-generation sequence data in cattle has provided an opportunity to examine whether pleiotropy is responsible...

  9. The morpho-agronomic characterization study of Lens culinaris germplasm under salt marsh habitat in Swat, Pakistan

    National Research Council Canada - National Science Library

    Rabia Noor; Shujaul Mulk Khan; Fayaz Ahmad; Murtaza Hussain; Elsayed Fathi Abd_Allah; Abdulaziz A. Alqarawi; Abeer Hashem; Abdullah Aldubise

    2017-01-01

    The present research study evaluate and identify the most suitable and high yielding genotypes of Lens culinaris for the salt marsh habitat of Swat in moist temperate sort of agro climatic environment of Pakistan...

  10. Numerical Performance Prediction of a Miniature Ramjet at Mach 4

    Science.gov (United States)

    2012-09-01

    measured using cryogenic strain gauges arranged in a Wheatstone bridge . A CFD cold-flow drag prediction was compared against this measured drag...cryogenic strain gauges arranged in a Wheatstone bridge . A CFD cold-flow drag prediction was compared against this measured drag force to establish...ramjet model mounted in the SSWT ....................................... 31  Figure 31.  Wheatstone bridge for potential difference measurements

  11. A simple rule based model for scheduling farm management operations in SWAT

    Science.gov (United States)

    Schürz, Christoph; Mehdi, Bano; Schulz, Karsten

    2016-04-01

    For many interdisciplinary questions at the watershed scale, the Soil and Water Assessment Tool (SWAT; Arnold et al., 1998) has become an accepted and widely used tool. Despite its flexibility, the model is highly demanding when it comes to input data. At SWAT's core the water balance and the modeled nutrient cycles are plant growth driven (implemented with the EPIC crop growth model). Therefore, land use and crop data with high spatial and thematic resolution, as well as detailed information on cultivation and farm management practices are required. For many applications of the model however, these data are unavailable. In order to meet these requirements, SWAT offers the option to trigger scheduled farm management operations by applying the Potential Heat Unit (PHU) concept. The PHU concept solely takes into account the accumulation of daily mean temperature for management scheduling. Hence, it contradicts several farming strategies that take place in reality; such as: i) Planting and harvesting dates are set much too early or too late, as the PHU concept is strongly sensitivity to inter-annual temperature fluctuations; ii) The timing of fertilizer application, in SWAT this often occurs simultaneously on the same date in in each field; iii) and can also coincide with precipitation events. Particularly, the latter two can lead to strong peaks in modeled nutrient loads. To cope with these shortcomings we propose a simple rule based model (RBM) to schedule management operations according to realistic farmer management practices in SWAT. The RBM involves simple strategies requiring only data that are input into the SWAT model initially, such as temperature and precipitation data. The user provides boundaries of time periods for operation schedules to take place for all crops in the model. These data are readily available from the literature or from crop variety trials. The RBM applies the dates by complying with the following rules: i) Operations scheduled in the

  12. First Assessments of Predicted ICESat-2 Performance Using Aircraft Data

    Science.gov (United States)

    Neumann, Thomas; Markus, Thorsten; Cook, William; Hancock, David; Brenner, Anita; Kelly, Brunt; DeMarco, Eugenia; Reed, Daniel; Walsh, Kaitlin

    2012-01-01

    The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) is a next-generation laser altimeter designed to continue key observations of ice sheet elevation change, sea ice freeboard, vegetation canopy height, earth surface elevation, and sea surface height. Scheduled for launch in mid-2016, ICESat-2 will use a high repetition rate (10 kHz), small footprint (10 m nominal ground diameter) laser, and a single-photon-sensitive detection strategy (photon counting) to measure precise range to the earth's surface. Using green light (532 nm), the six beams of ICESat-2 will provide improved spatial coverage compared with the single beam of ICESat, while the differences in transmit energy among the beams provide a large dynamic range. The six beams are arranged into three pairs of beams which allow slopes to measured on an orbit-by-orbit basis. In order to evaluate models of predicted ICESat-2 performance and provide ICESat-2-like data for algorithm development, an airborne ICESat-2 simulator was developed and first flown in 2010. This simulator, the Multiple Altimeter Beam Experimental Lidar (MABEL) was most recently deployed to Iceland in April 2012 and collected approx 85 hours of science data over land ice, sea ice, and calibration targets. MABEL uses a similar photon-counting measurement strategy to what will be used on ICESat-2. MABEL collects data in 16 green channels and an additional 8 channels in the infrared aligned across the direction of flight. By using NASA's ER-2 aircraft flying at 20km altitude, MABEL flies as close to space as is practical, and collects data through approx 95% of the atmosphere. We present background on the MABEL instrument, and data from the April 2012 deployment to Iceland. Among the 13 MABEL flights, we collected data over the Greenland ice sheet interior and outlet glaciers in the southwest and western Greenland, sea ice data over the Nares Strait and Greenland Sea, and a number of small glaciers and ice caps in Iceland and Svalbard

  13. Using SWAT and Fuzzy TOPSIS to Assess the Impact of Climate Change in the Headwaters of the Segura River Basin (SE Spain

    Directory of Open Access Journals (Sweden)

    Javier Senent-Aparicio

    2017-02-01

    Full Text Available The Segura River Basin is one of the most water-stressed basins in Mediterranean Europe. If we add to the actual situation that most climate change projections forecast important decreases in water resource availability in the Mediterranean region, the situation will become totally unsustainable. This study assessed the impact of climate change in the headwaters of the Segura River Basin using the Soil and Water Assessment Tool (SWAT with bias-corrected precipitation and temperature data from two Regional Climate Models (RCMs for the medium term (2041–2070 and the long term (2071–2100 under two emission scenarios (RCP4.5 and RCP8.5. Bias correction was performed using the distribution mapping approach. The fuzzy TOPSIS technique was applied to rank a set of nine GCM–RCM combinations, choosing the climate models with a higher relative closeness. The study results show that the SWAT performed satisfactorily for both calibration (NSE = 0.80 and validation (NSE = 0.77 periods. Comparing the long-term and baseline (1971–2000 periods, precipitation showed a negative trend between 6% and 32%, whereas projected annual mean temperatures demonstrated an estimated increase of 1.5–3.3 °C. Water resources were estimated to experience a decrease of 2%–54%. These findings provide local water management authorities with very useful information in the face of climate change.

  14. Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model

    Science.gov (United States)

    Lee, Sangchul; Yeo, In-Young; Sadeghi, Ali M.; McCarty, Gregory W.; Hively, Wells D.; Lang, Megan W.; Sharifi, Amir

    2018-01-01

    Water quality problems in the Chesapeake Bay Watershed (CBW) are expected to be exacerbated by climate variability and change. However, climate impacts on agricultural lands and resultant nutrient loads into surface water resources are largely unknown. This study evaluated the impacts of climate variability and change on two adjacent watersheds in the Coastal Plain of the CBW, using the Soil and Water Assessment Tool (SWAT) model. We prepared six climate sensitivity scenarios to assess the individual impacts of variations in CO2 concentration (590 and 850 ppm), precipitation increase (11 and 21 %), and temperature increase (2.9 and 5.0 °C), based on regional general circulation model (GCM) projections. Further, we considered the ensemble of five GCM projections (2085-2098) under the Representative Concentration Pathway (RCP) 8.5 scenario to evaluate simultaneous changes in CO2, precipitation, and temperature. Using SWAT model simulations from 2001 to 2014 as a baseline scenario, predicted hydrologic outputs (water and nitrate budgets) and crop growth were analyzed. Compared to the baseline scenario, a precipitation increase of 21 % and elevated CO2 concentration of 850 ppm significantly increased streamflow and nitrate loads by 50 and 52 %, respectively, while a temperature increase of 5.0 °C reduced streamflow and nitrate loads by 12 and 13 %, respectively. Crop biomass increased with elevated CO2 concentrations due to enhanced radiation- and water-use efficiency, while it decreased with precipitation and temperature increases. Over the GCM ensemble mean, annual streamflow and nitrate loads showed an increase of ˜ 70 % relative to the baseline scenario, due to elevated CO2 concentrations and precipitation increase. Different hydrological responses to climate change were observed from the two watersheds, due to contrasting land use and soil characteristics. The watershed with a larger percent of croplands demonstrated a greater increased rate of 5.2 kg N ha-1 in

  15. Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model

    Science.gov (United States)

    Lee, Sangchul; Yeo, In-Young; Sadeghi, Ali M.; McCarty, Gregory W.; Hively, Wells; Lang, Megan W.; Sharifi, Amir

    2018-01-01

    Water quality problems in the Chesapeake Bay Watershed (CBW) are expected to be exacerbated by climate variability and change. However, climate impacts on agricultural lands and resultant nutrient loads into surface water resources are largely unknown. This study evaluated the impacts of climate variability and change on two adjacent watersheds in the Coastal Plain of the CBW, using the Soil and Water Assessment Tool (SWAT) model. We prepared six climate sensitivity scenarios to assess the individual impacts of variations in CO2concentration (590 and 850 ppm), precipitation increase (11 and 21 %), and temperature increase (2.9 and 5.0 °C), based on regional general circulation model (GCM) projections. Further, we considered the ensemble of five GCM projections (2085–2098) under the Representative Concentration Pathway (RCP) 8.5 scenario to evaluate simultaneous changes in CO2, precipitation, and temperature. Using SWAT model simulations from 2001 to 2014 as a baseline scenario, predicted hydrologic outputs (water and nitrate budgets) and crop growth were analyzed. Compared to the baseline scenario, a precipitation increase of 21 % and elevated CO2 concentration of 850 ppm significantly increased streamflow and nitrate loads by 50 and 52 %, respectively, while a temperature increase of 5.0 °C reduced streamflow and nitrate loads by 12 and 13 %, respectively. Crop biomass increased with elevated CO2 concentrations due to enhanced radiation- and water-use efficiency, while it decreased with precipitation and temperature increases. Over the GCM ensemble mean, annual streamflow and nitrate loads showed an increase of  ∼  70 % relative to the baseline scenario, due to elevated CO2 concentrations and precipitation increase. Different hydrological responses to climate change were observed from the two watersheds, due to contrasting land use and soil characteristics. The watershed with a larger percent of croplands demonstrated a greater

  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 Future Random Events Based on Past Performance

    OpenAIRE

    Donald G. Morrison; David C. Schmittlein

    1981-01-01

    There are many situations where one is interested in predicting the expected number of events in period 2 given that x events occurred in period 1. For example, insurance companies must decide whether or not to cancel the insurance of drivers who had 3 or more accidents during the previous year. In analyzing marketing research data an analyst may wish to predict the number of future purchases to be made by those customers who made x purchases in the previous 3 months. The owner of a baseball ...

  18. 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…

  19. 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…

  20. 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 ...

  1. 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,…

  2. Design of Over Center Valves Based on Predictable Performance

    DEFF Research Database (Denmark)

    Hansen, M.R.; Andersen, T.O.; Pedersen, P.

    2004-01-01

    this assumption and an approach to design over center valve geometries that have negative flow forces is presented with emphasis on predictability. In conclusion it is made clear that negative flow forces in the over center valve cannot solve the instability problem in general, however, it might very well...

  3. Academic Performance, Popularity, and Depression Predict Adolescent Substance Use.

    Science.gov (United States)

    Diego, Miguel A.; Field, Tiffany M.; Sanders, Christopher E.

    2003-01-01

    Eighty-nine high school seniors completed a questionnaire on their feelings and activities, including their use of drugs. Adolescents with a low grade point average, high popularity, and high depression were more likely to smoke cigarettes, drink alcohol, and smoke marijuana than were their peers. Cigarette and alcohol use predicted marijuana use,…

  4. Personality Predicts Academic Performance: Exploring the Moderating Role of Gender

    Science.gov (United States)

    Nguyen, N. T.; Allen, Larry C.; Fraccastoro, K.

    2005-01-01

    In this study, students' personality traits were investigated in relation to course grade in an undergraduate management course taught by the same professor and overall college grade point average (GPA). Conscientiousness positively and significantly predicted overall GPA over and beyond other personality traits of agreeableness, extroversion,…

  5. 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

  6. 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...... benchmark dataset from 2009 with prediction performances generated on data subsequently added to the Immune Epitope Database (IEDB) which served as a blind set. Results: We found that cross-validated performances systematically overestimated performance on the blind set. This was found not to be due...

  7. Semantic Web applications and tools for the life sciences: SWAT4LS 2010.

    Science.gov (United States)

    Burger, Albert; Paschke, Adrian; Romano, Paolo; Marshall, M Scott; Splendiani, Andrea

    2012-01-25

    As Semantic Web technologies mature and new releases of key elements, such as SPARQL 1.1 and OWL 2.0, become available, the Life Sciences continue to push the boundaries of these technologies with ever more sophisticated tools and applications. Unsurprisingly, therefore, interest in the SWAT4LS (Semantic Web Applications and Tools for the Life Sciences) activities have remained high, as was evident during the third international SWAT4LS workshop held in Berlin in December 2010. Contributors to this workshop were invited to submit extended versions of their papers, the best of which are now made available in the special supplement of BMC Bioinformatics. The papers reflect the wide range of work in this area, covering the storage and querying of Life Sciences data in RDF triple stores, tools for the development of biomedical ontologies and the semantics-based integration of Life Sciences as well as clinicial data.

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

    National Research Council Canada - National Science Library

    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...

  9. Performance Analysis of (TDD) Massive MIMO with Kalman Channel Prediction

    OpenAIRE

    Kashyap, Salil; Mollén, Christopher; Emil, Björnson; Larsson, Erik G.

    2017-01-01

    In massive MIMO systems, which rely on uplink pilots to estimate the channel, the time interval between pilot transmissions constrains the length of the downlink.  Since switching between up- and downlink takes time, longer downlink blocks increase the effective spectral efficiency.  We investigate the use of low-complexity channel models and Kalman filters for channel prediction, to allow for longer intervals between the pilots.  Specifically, we quantify how often uplink pilots have to be s...

  10. Predictive Performance of the Binary Logit Model in Unbalanced Samples

    OpenAIRE

    J.S. Cramer

    1998-01-01

    In a binary logit analysis with unequal sample frequencies of the twooutcomes the less frequent outcome always has lower estimatedprediction probabilities than the other one. This effect is unavoidable,and its extent varies inversely with the fit of the model, as given by anew measure that follows naturally from the argument. Unbalanced sampleswith a poor fit are typical for survey analyses of the social sciences andepidemiology, and there the difference in prediction probabilities is mostacu...

  11. Predicting Academic Performance with Applying Data Mining Techniques (Generalizing the results of two Different Case Studies)

    National Research Council Canada - National Science Library

    Rozita Jamili Oskouei; Mohsen Askari

    2014-01-01

    Several research works are attempted to predict students academic performance and assess the evaluating students knowledge or detecting students weakness and probability of failure in final semester examinations...

  12. Autonomous prediction of performance-based standards for heavy vehicles

    CSIR Research Space (South Africa)

    Berman, R

    2015-11-01

    Full Text Available performance-based standards approach which specifies on-road vehicle performance measures. One such standard is the low-speed swept path, which is a measure of road width required by a vehicle to complete a prescribed turning manoeuvre. This is typically...

  13. Tests for predicting endurance kayak performance | Olivier | South ...

    African Journals Online (AJOL)

    Objectives : Previous studies investigating factors contributing to kayak performance have employed sophisticated physiological measures, and the use of specialised dynamometers, to simulate the kayak stroke. Such measures do not have general utility, and the aim of this study was to identify tests that could be performed ...

  14. Work Ethic and Academic Performance: Predicting Citizenship and Counterproductive Behavior

    Science.gov (United States)

    Meriac, John P.

    2012-01-01

    In this study, work ethic was examined as a predictor of academic performance, compared with standardized test scores and high school grade point average (GPA). Academic performance was expanded to include student organizational citizenship behavior (OCB) and student counterproductive behavior, comprised of cheating and disengagement, in addition…

  15. Cohort study on predicting grades: is performance on early MBChB assessments predictive of later undergraduate grades?

    Science.gov (United States)

    Cleland, Jennifer A; Milne, Andrew; Sinclair, Hazel; Lee, Amanda J

    2008-07-01

    Timely intervention, based on early identification of poor performance, is likely to help weaker medical students improve their performance. We wished to identify if poor performance in degree assessments early in the medical degree predicts later undergraduate grades. If it does, this information could be used to signpost strategically placed supportive interventions for our students. We carried out a retrospective, observational study of anonymised databases of student assessment outcomes at the University of Aberdeen Medical School. Data were accessed for students who graduated in the years 2003-07 (n = 861). The main outcome measure was marks for summative degree assessments from the end of Year 2 to the end of Year 5. After adjustment for cohort, maturity, gender, funding source, intercalation and graduate status, poor performance (fail and borderline pass) in the Year 2 first semester written examination Principles of Medicine II was found to be a significant predictor of poor performance in all subsequent written examinations (all P Poor performance in the Year 3 objective structured clinical examination (OSCE) was a significant predictor of poor performance in Year 4 and 5 OSCEs. Relationships between essay-based summative assessments were not significantly predictive. Male gender appeared to significantly predict poor performance. Examinations taken as early as mid-Year 2 can be used to identify medical students who would benefit from intervention and support. Strategic delivery of appropriate intervention at this time may enable poorer students to perform better in subsequent examinations. We can then monitor the impact of remedial support on subsequent performance.

  16. Modeling nitrate-nitrogen load reduction strategies for the des moines river, iowa using SWAT

    Science.gov (United States)

    Schilling, K.E.; Wolter, C.F.

    2009-01-01

    The Des Moines River that drains a watershed of 16,175 km2 in portions of Iowa and Minnesota is impaired for nitrate-nitrogen (nitrate) due to concentrations that exceed regulatory limits for public water supplies. The Soil Water Assessment Tool (SWAT) model was used to model streamflow and nitrate loads and evaluate a suite of basin-wide changes and targeting configurations to potentially reduce nitrate loads in the river. The SWAT model comprised 173 subbasins and 2,516 hydrologic response units and included point and nonpoint nitrogen sources. The model was calibrated for an 11-year period and three basin-wide and four targeting strategies were evaluated. Results indicated that nonpoint sources accounted for 95% of the total nitrate export. Reduction in fertilizer applications from 170 to 50 kg/ha achieved the 38% reduction in nitrate loads, exceeding the 34% reduction required. In terms of targeting, the most efficient load reductions occurred when fertilizer applications were reduced in subbasins nearest the watershed outlet. The greatest load reduction for the area of land treated was associated with reducing loads from 55 subbasins with the highest nitrate loads, achieving a 14% reduction in nitrate loads achieved by reducing applications on 30% of the land area. SWAT model results provide much needed guidance on how to begin implementing load reduction strategies most efficiently in the Des Moines River watershed. ?? 2009 Springer Science+Business Media, LLC.

  17. 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.

  18. Pilot age and expertise predict flight simulator performance

    Science.gov (United States)

    Kennedy, Quinn; Noda, Art; Yesavage, Jerome A.

    2010-01-01

    Background Expert knowledge may compensate for age-related declines in basic cognitive and sensory-motor abilities in some skill domains. We investigated the influence of age and aviation expertise (indexed by Federal Aviation Administration pilot ratings) on longitudinal flight simulator performance. Methods Over a 3-year period, 118 general aviation pilots aged 40 to 69 years were tested annually, in which their flight performance was scored in terms of 1) executing air-traffic controller communications; 2) traffic avoidance; 3) scanning cockpit instruments; 4) executing an approach to landing; and 5) a flight summary score. Results More expert pilots had better flight summary scores at baseline and showed less decline over time. Secondary analyses revealed that expertise effects were most evident in the accuracy of executing aviation communications, the measure on which performance declined most sharply over time. Regarding age, even though older pilots initially performed worse than younger pilots, over time older pilots showed less decline in flight summary scores than younger pilots. Secondary analyses revealed that the oldest pilots did well over time because their traffic avoidance performance improved more vs younger pilots. Conclusions These longitudinal findings support previous cross-sectional studies in aviation as well as non-aviation domains, which demonstrated the advantageous effect of prior experience and specialized expertise on older adults’ skilled cognitive performances. PMID:17325270

  19. Biomimetic Dissolution: A Tool to Predict Amorphous Solid Dispersion Performance.

    Science.gov (United States)

    Puppolo, Michael M; Hughey, Justin R; Dillon, Traciann; Storey, David; Jansen-Varnum, Susan

    2017-11-01

    The presented study describes the development of a membrane permeation non-sink dissolution method that can provide analysis of complete drug speciation and emulate the in vivo performance of poorly water-soluble Biopharmaceutical Classification System class II compounds. The designed membrane permeation methodology permits evaluation of free/dissolved/unbound drug from amorphous solid dispersion formulations with the use of a two-cell apparatus, biorelevant dissolution media, and a biomimetic polymer membrane. It offers insight into oral drug dissolution, permeation, and absorption. Amorphous solid dispersions of felodipine were prepared by hot melt extrusion and spray drying techniques and evaluated for in vitro performance. Prior to ranking performance of extruded and spray-dried felodipine solid dispersions, optimization of the dissolution methodology was performed for parameters such as agitation rate, membrane type, and membrane pore size. The particle size and zeta potential were analyzed during dissolution experiments to understand drug/polymer speciation and supersaturation sustainment of felodipine solid dispersions. Bland-Altman analysis was performed to measure the agreement or equivalence between dissolution profiles acquired using polymer membranes and porcine intestines and to establish the biomimetic nature of the treated polymer membranes. The utility of the membrane permeation dissolution methodology is seen during the evaluation of felodipine solid dispersions produced by spray drying and hot melt extrusion. The membrane permeation dissolution methodology can suggest formulation performance and be employed as a screening tool for selection of candidates to move forward to pharmacokinetic studies. Furthermore, the presented model is a cost-effective technique.

  20. Cracking Tendency Prediction of High-Performance Cementitious Materials

    Directory of Open Access Journals (Sweden)

    Ke Chen

    2014-01-01

    Full Text Available The constraint ring test is widely used to assess the cracking potential for early-age cementitious materials. In this paper, the analytical expressions based on elastic mechanism are presented to estimate the residual stresses of the restrained mortar ring by considering the comprehensive effects of hydration heat, autogenous and drying shrinkage, creeping, and restraint. In the present analytical method, the stress field of the restrained ring is treated as the superposition of those caused by hydration heat, external restraint, autogenous and drying shrinkage, and creep. The factors including the properties of materials, environmental parameters such as relative humidity and temperature, the geometry effect of specimen, and the relative constraint effects of steel ring to mortar ring, are taken into account to predict the strain development with age of mortar. The temperature of the ring, the elastic modulus, the creep strain, and the split tensile strength are measured to validate the model. The age of cracking is predicted by comparing the estimated maximum tensile stress of the restrained mortar ring with the measured split tensile strength of specimen. The suitability of the present analytical method is assessed by comparing with the restraint ring test and a soundly good agreement is observed.

  1. Predictive Model of Graphene Based Polymer Nanocomposites: Electrical Performance

    Science.gov (United States)

    Manta, Asimina; Gresil, Matthieu; Soutis, Constantinos

    2017-04-01

    In this computational work, a new simulation tool on the graphene/polymer nanocomposites electrical response is developed based on the finite element method (FEM). This approach is built on the multi-scale multi-physics format, consisting of a unit cell and a representative volume element (RVE). The FE methodology is proven to be a reliable and flexible tool on the simulation of the electrical response without inducing the complexity of raw programming codes, while it is able to model any geometry, thus the response of any component. This characteristic is supported by its ability in preliminary stage to predict accurately the percolation threshold of experimental material structures and its sensitivity on the effect of different manufacturing methodologies. Especially, the percolation threshold of two material structures of the same constituents (PVDF/Graphene) prepared with different methods was predicted highlighting the effect of the material preparation on the filler distribution, percolation probability and percolation threshold. The assumption of the random filler distribution was proven to be efficient on modelling material structures obtained by solution methods, while the through-the -thickness normal particle distribution was more appropriate for nanocomposites constructed by film hot-pressing. Moreover, the parametrical analysis examine the effect of each parameter on the variables of the percolation law. These graphs could be used as a preliminary design tool for more effective material system manufacturing.

  2. Prediction of cell culture media performance using fluorescence spectroscopy.

    Science.gov (United States)

    Ryan, Paul W; Li, Boyan; Shanahan, Michael; Leister, Kirk J; Ryder, Alan G

    2010-02-15

    Cell culture media used in industrial mammalian cell culture are complex aqueous solutions that are inherently difficult to analyze comprehensively. The analysis of media quality and variance is of utmost importance in efficient manufacturing. We are exploring the use of rapid "holistic" analytical methods that can be used for routine screening of cell culture media used in industrial biotechnology. The application of rapid fluorescence spectroscopic techniques to the routine analysis of cell culture media (Chinese hamster ovary cell-based manufacture) was investigated. We have developed robust methods which can be used to identify compositional changes and ultimately predict the efficacy of individual fed batch media in terms of downstream protein product yield with an accuracy of +/-0.13 g/L. This is achieved through the implementation of chemometric methods such as multiway robust principal component analysis (MROBPCA), and n-way partial least-squares-discriminant analysis and regression (NPLS-DA and NPLS). This ability to observe compositional changes and predict product yield before media use has enormous potential and should permit the effective elimination of one of the major process variables leading to more consistent product quality and improved yield. These robust and reliable methods have the potential to become an important part of upstream biopharmaceutical quality control and analysis.

  3. Test of the classic model for predicting endurance running performance.

    Science.gov (United States)

    McLaughlin, James E; Howley, Edward T; Bassett, David R; Thompson, Dixie L; Fitzhugh, Eugene C

    2010-05-01

    To compare the classic physiological variables linked to endurance performance (VO2max, %VO2max at lactate threshold (LT), and running economy (RE)) with peak treadmill velocity (PTV) as predictors of performance in a 16-km time trial. Seventeen healthy, well-trained distance runners (10 males and 7 females) underwent laboratory testing to determine maximal oxygen uptake (VO2max), RE, percentage of maximal oxygen uptake at the LT (%VO2max at LT), running velocity at LT, and PTV. Velocity at VO2max (vVO2max) was calculated from RE and VO2max. Three stepwise regression models were used to determine the best predictors (classic vs treadmill performance protocols) for the 16-km running time trial. Simple Pearson correlations of the variables with 16-km performance showed vVO2max to have the highest correlation (r = -0.972) and %VO2max at the LT the lowest (r = 0.136). The correlation coefficients for LT, VO2max, and PTV were very similar in magnitude (r = -0.903 to r = -0.892). When VO2max, %VO2max at LT, RE, and PTV were entered into SPSS stepwise analysis, VO2max explained 81.3% of the total variance, and RE accounted for an additional 10.7%. vVO2max was shown to be the best predictor of the 16-km performance, accounting for 94.4% of the total variance. The measured velocity at VO2max (PTV) was highly correlated with the estimated velocity at vVO2max (r = 0.8867). Among well-trained subjects heterogeneous in VO2max and running performance, vVO2max is the best predictor of running performance because it integrates both maximal aerobic power and the economy of running. The PTV is linked to the same physiological variables that determine vVO2max.

  4. 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...

  5. Aggregate Interview Method of ranking orthopedic applicants predicts future performance.

    Science.gov (United States)

    Geissler, Jacqueline; VanHeest, Ann; Tatman, Penny; Gioe, Terence

    2013-07-01

    This article evaluates and describes a process of ranking orthopedic applicants using what the authors term the Aggregate Interview Method. The authors hypothesized that higher-ranking applicants using this method at their institution would perform better than those ranked lower using multiple measures of resident performance. A retrospective review of 115 orthopedic residents was performed at the authors' institution. Residents were grouped into 3 categories by matching rank numbers: 1-5, 6-14, and 15 or higher. Each rank group was compared with resident performance as measured by faculty evaluations, the Orthopaedic In-Training Examination (OITE), and American Board of Orthopaedic Surgery (ABOS) test results. Residents ranked 1-5 scored significantly better on patient care, behavior, and overall competence by faculty evaluation (Porthopedic resident candidates who scored highly on the Accreditation Council for Graduate Medical Education resident core competencies as measured by faculty evaluations, performed above the national average on the OITE, and passed the ABOS part 1 examination at rates exceeding the national average. Copyright 2013, SLACK Incorporated.

  6. Could the deep squat jump predict weightlifting performance?

    Science.gov (United States)

    Vizcaya, Francisco J; Viana, Oscar; del Olmo, Miguel Fernandez; Acero, Rafael Martin

    2009-05-01

    This research was carried out with the aim of describing the deep squat jump (DSJ) and comparing it with the squat (SJ) and countermovement (CMJ) jumps, to introduce it as a strength testing tool in the monitoring and control of training in strength and power sports. Forty-eight male subjects (21 weightlifters, 12 triathletes, and 15 physical education students) performed 3 trials of DSJ, SJ, and CMJ with a 1-minute rest among them. For the weightlifters, snatch and clean and jerk results during the Spanish Championship 2004 and the 35th EU Championships 2007 were collected to study the relationship among vertical jumps and weightlifters' performance. A 1-way analysis of variance (ANOVA) showed significant differences between groups in the vertical jumps, with the highest jumps for the weightlifters and the lowest for the triathletes. An ANOVA for repeated measures (type of jump) showed better results for DSJ and CMJ than SJ in all groups. A linear regression analysis was performed to determine the association between weightlifting and vertical jump performances. Correlations among the weightlifting performance and the vertical jumps were also calculated and determined using Pearson r. Results have shown that both CMJ and DSJ are strongly correlated with weightlifting ability. Therefore, both measures can be useful for coaches as a strength testing tool in the monitoring and control of training in weightlifting.

  7. 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.

  8. Predicting subsequent task performance from goal motivation and goal failure

    Science.gov (United States)

    Healy, Laura C.; Ntoumanis, Nikos; Stewart, Brandon D.; Duda, Joan L.

    2015-01-01

    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 min. 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. PMID:26191029

  9. Motor threshold predicts working memory performance in healthy humans.

    Science.gov (United States)

    Schicktanz, Nathalie; Schwegler, Kyrill; Fastenrath, Matthias; Spalek, Klara; Milnik, Annette; Papassotiropoulos, Andreas; Nyffeler, Thomas; de Quervain, Dominique J-F

    2014-01-01

    Cognitive functions, such as working memory, depend on neuronal excitability in a distributed network of cortical regions. It is not known, however, if interindividual differences in cortical excitability are related to differences in working memory performance. In the present transcranial magnetic stimulation study, which included 188 healthy young subjects, we show that participants with lower resting motor threshold, which is related to higher corticospinal excitability, had increased 2-back working memory performance. The findings may help to better understand the link between cortical excitability and cognitive functions and may also have important clinical implications with regard to conditions of altered cortical excitability.

  10. 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.

  11. 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.

  12. Performance of polygenic scores for predicting phobic anxiety.

    Science.gov (United States)

    Walter, Stefan; Glymour, M Maria; Koenen, Karestan; Liang, Liming; Tchetgen Tchetgen, Eric J; Cornelis, Marilyn; Chang, Shun-Chiao; Rimm, Eric; Kawachi, Ichiro; Kubzansky, Laura D

    2013-01-01

    Anxiety disorders are common, with a lifetime prevalence of 20% in the U.S., and are responsible for substantial burdens of disability, missed work days and health care utilization. To date, no causal genetic variants have been identified for anxiety, anxiety disorders, or related traits. To investigate whether a phobic anxiety symptom score was associated with 3 alternative polygenic risk scores, derived from external genome-wide association studies of anxiety, an internally estimated agnostic polygenic score, or previously identified candidate genes. Longitudinal follow-up study. Using linear and logistic regression we investigated whether phobic anxiety was associated with polygenic risk scores derived from internal, leave-one out genome-wide association studies, from 31 candidate genes, and from out-of-sample genome-wide association weights previously shown to predict depression and anxiety in another cohort. Study participants (n = 11,127) were individuals from the Nurses' Health Study and Health Professionals Follow-up Study. Anxiety symptoms were assessed via the 8-item phobic anxiety scale of the Crown Crisp Index at two time points, from which a continuous phenotype score was derived. We found no genome-wide significant associations with phobic anxiety. Phobic anxiety was also not associated with a polygenic risk score derived from the genome-wide association study beta weights using liberal p-value thresholds; with a previously published genome-wide polygenic score; or with a candidate gene risk score based on 31 genes previously hypothesized to predict anxiety. There is a substantial gap between twin-study heritability estimates of anxiety disorders ranging between 20-40% and heritability explained by genome-wide association results. New approaches such as improved genome imputations, application of gene expression and biological pathways information, and incorporating social or environmental modifiers of genetic risks may be necessary to identify

  13. Performance of polygenic scores for predicting phobic anxiety.

    Directory of Open Access Journals (Sweden)

    Stefan Walter

    Full Text Available CONTEXT: Anxiety disorders are common, with a lifetime prevalence of 20% in the U.S., and are responsible for substantial burdens of disability, missed work days and health care utilization. To date, no causal genetic variants have been identified for anxiety, anxiety disorders, or related traits. OBJECTIVE: To investigate whether a phobic anxiety symptom score was associated with 3 alternative polygenic risk scores, derived from external genome-wide association studies of anxiety, an internally estimated agnostic polygenic score, or previously identified candidate genes. DESIGN: Longitudinal follow-up study. Using linear and logistic regression we investigated whether phobic anxiety was associated with polygenic risk scores derived from internal, leave-one out genome-wide association studies, from 31 candidate genes, and from out-of-sample genome-wide association weights previously shown to predict depression and anxiety in another cohort. SETTING AND PARTICIPANTS: Study participants (n = 11,127 were individuals from the Nurses' Health Study and Health Professionals Follow-up Study. MAIN OUTCOME MEASURE: Anxiety symptoms were assessed via the 8-item phobic anxiety scale of the Crown Crisp Index at two time points, from which a continuous phenotype score was derived. RESULTS: We found no genome-wide significant associations with phobic anxiety. Phobic anxiety was also not associated with a polygenic risk score derived from the genome-wide association study beta weights using liberal p-value thresholds; with a previously published genome-wide polygenic score; or with a candidate gene risk score based on 31 genes previously hypothesized to predict anxiety. CONCLUSION: There is a substantial gap between twin-study heritability estimates of anxiety disorders ranging between 20-40% and heritability explained by genome-wide association results. New approaches such as improved genome imputations, application of gene expression and biological

  14. Predicting the Structural Performance of Composite Structures Under Cyclic Loading

    NARCIS (Netherlands)

    Kassapoglou, C.

    2012-01-01

    The increased use of advanced composite materials on primary aircraft structure has brought back to the forefront the question of how such structures perform under repeated loading. In particular, when damage or other stress risers are present, tests have shown that the load to cause failure after a

  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. 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…

  17. Leadership Styles and Organizational Performance: A Predictive Analysis

    Science.gov (United States)

    Kieu, Hung Q.

    2010-01-01

    Leadership is critically important because it affects the health of the organization. Research has found that leadership is one of the most significant contributors to organizational performance. Expanding and replicating previous research, and focusing on the specific telecommunications sector, this study used multiple correlation and regression…

  18. Comparison of Predictive Models for Photovoltaic Module Performance: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Marion, B.

    2008-05-01

    This paper examines three models used to estimate the performance of photovoltaic (PV) modules when the irradiances and PV cell temperatures are known. The results presented here were obtained by comparing modeled and measured maximum power (Pm) for PV modules that rely on different technologies.

  19. 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...

  20. Predictive performance simulations for a sustainable lecture building complex

    CSIR Research Space (South Africa)

    Conradie, Dirk CU

    2012-06-01

    Full Text Available during operational hours. The following process was used to model the ventilation performance of this mixed-mode building: 1) An insolation analysis was undertaken to establish the effect of cumulative exposure of the Trombe wall surface to solar...

  1. Inhibitory Control Predicts Language Switching Performance in Trilingual Speech Production

    Science.gov (United States)

    Linck, Jared A.; Schwieter, John W.; Sunderman, Gretchen

    2012-01-01

    This study investigated the role of domain-general inhibitory control in trilingual speech production. Taking an individual differences approach, we examined the relationship between performance on a non-linguistic measure of inhibitory control (the Simon task) and a multilingual language switching task for a group of fifty-six native English (L1)…

  2. Predicting Performance on a Firefighter's Ability Test from Fitness Parameters

    Science.gov (United States)

    Michaelides, Marcos A.; Parpa, Koulla M.; Thompson, Jerald; Brown, Barry

    2008-01-01

    The purpose of this project was to identify the relationships between various fitness parameters such as upper body muscular endurance, upper and lower body strength, flexibility, body composition and performance on an ability test (AT) that included simulated firefighting tasks. A second intent was to create a regression model that would predict…

  3. 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

  4. Goal Orientations Predict Academic Performance beyond Intelligence and Personality

    Science.gov (United States)

    Steinmayr, Ricarda; Bipp, Tanja; Spinath, Birgit

    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). Intelligence, the Big Five factors of personality…

  5. 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

  6. 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

  7. Using the 2 x 2 Framework of Achievement Goals to Predict Achievement Emotions and Academic Performance

    Science.gov (United States)

    Putwain, David W.; Sander, Paul; Larkin, Derek

    2013-01-01

    Previous work has established how achievement emotions are related to the trichotomous model of achievement goals, and how they predict academic performance. In our study we examine relations using an additional, mastery-avoidance goal, and whether outcome-focused emotions are predicted by mastery as well as performance goals. Results showed that…

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

    Science.gov (United States)

    Yildiz, Osman; Bal, Abdullah; Gulsecen, Sevinc

    2013-01-01

    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…

  9. 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.

  10. Variable performance of models for predicting methicillin-resistant Staphylococcus aureus carriage in European surgical wards

    OpenAIRE

    Lee, Andie S; Pan, Angelo; Harbarth, Stephan; Patroni, Andrea; Chalfine, Annie; Daikos, George L; Garilli, Silvia; Mart?nez, Jos? Antonio; Cooper, Ben S

    2015-01-01

    BACKGROUND: Predictive models to identify unknown methicillin-resistant Staphylococcus aureus (MRSA) carriage on admission may optimise targeted MRSA screening and efficient use of resources. However, common approaches to model selection can result in overconfident estimates and poor predictive performance. We aimed to compare the performance of various models to predict previously unknown MRSA carriage on admission to surgical wards. METHODS: The study analysed data collected during a prospe...

  11. Improving AVSWAT Stream Flow Simulation by Incorporating Groundwater Recharge Prediction in the Upstream Lesti Watershed, East Java, Indonesia

    Directory of Open Access Journals (Sweden)

    Christina Rahayuningtyas

    2014-01-01

    Full Text Available The upstream Lesti watershed is one of the major watersheds of East Java in Indonesia, covering about 38093 hectares. Although there are enough water resources to meet current demands in the basin, many challenges including high spatial and temporal variability in precipitation from year to year exist. It is essential to understand how the climatic condition affects Lesti River stream flow in each sub basin. This study investigated the applicability of using the Soil and Water Assessment Tool (SWAT with the incorporation of groundwater recharge prediction in stream flow simulation in the upstream Lesti watershed. Four observation wells in the upstream Lesti watershed were used to evaluate the seasonal and annual variations in the water level and estimate the groundwater recharge in the deep aquifer. The results show that annual water level rise was within the 2800 - 5700 mm range in 2007, 3900 - 4700 mm in 2008, 3200 - 5100 mm in 2009, and 2800 - 4600 mm in 2010. Based on the specific yield and the measured water level rise, the area-weighted groundwater predictions at the watershed outlet are 736, 820.9, 786.7, 306.4 mm in 2007, 2008, 2009, and 2010, respectively. The consistency test reveals that the R-square statistical value is greater than 0.7, and the DV (% ranged from 32 - 55.3% in 2007 - 2010. Overall, the SWAT model performs better in the wet season flow simulation than the dry season. It is suggested that the SWAT model needs to be improved for stream flow simulation in tropical regions.

  12. An efficient approach to understanding and predicting the effects of multiple task characteristics on performance.

    Science.gov (United States)

    Richardson, Miles

    2017-04-01

    In ergonomics there is often a need to identify and predict the separate effects of multiple factors on performance. A cost-effective fractional factorial approach to understanding the relationship between task characteristics and task performance is presented. The method has been shown to provide sufficient independent variability to reveal and predict the effects of task characteristics on performance in two domains. The five steps outlined are: selection of performance measure, task characteristic identification, task design for user trials, data collection, regression model development and task characteristic analysis. The approach can be used for furthering knowledge of task performance, theoretical understanding, experimental control and prediction of task performance. Practitioner Summary: A cost-effective method to identify and predict the separate effects of multiple factors on performance is presented. The five steps allow a better understanding of task factors during the design process.

  13. GLOBAL PERFORMANCE PREDICTION FOR DIVERGENCE-BASED IMAGE REGISTRATION CRITERIA

    Science.gov (United States)

    Sricharan, Kumar; Raich, Raviv; Hero, Alfred O.

    2015-01-01

    Divergence measures find application in many areas of statistics, signal processing and machine learning, thus necessitating the need for good estimators of divergence measures. While several estimators of divergence measures have been proposed in literature, the performance of these estimators is not known. We propose a simple kNN density estimation based plug-in estimator for estimation of divergence measures. Based on the properties of kNN density estimates, we derive the bias, variance and mean square error xof the estimator in terms of the sample size, the dimension of the samples and the underlying probability distribution. Based on these results, we specify the optimal choice of tuning parameters for minimum mean square error. We also present results on convergence in distribution of the proposed estimator. These results will establish a basis for analyzing the performance of image registration methods that maximize divergence. PMID:25905108

  14. Prediction of performance on the RCMP physical ability requirement evaluation.

    Science.gov (United States)

    Stanish, H I; Wood, T M; Campagna, P

    1999-08-01

    The Royal Canadian Mounted Police use the Physical Ability Requirement Evaluation (PARE) for screening applicants. The purposes of this investigation were to identify those field tests of physical fitness that were associated with PARE performance and determine which most accurately classified successful and unsuccessful PARE performers. The participants were 27 female and 21 male volunteers. Testing included measures of aerobic power, anaerobic power, agility, muscular strength, muscular endurance, and body composition. Multiple regression analysis revealed a three-variable model for males (70-lb bench press, standing long jump, and agility) explaining 79% of the variability in PARE time, whereas a one-variable model (agility) explained 43% of the variability for females. Analysis of the classification accuracy of the males' data was prohibited because 91% of the males passed the PARE. Classification accuracy of the females' data, using logistic regression, produced a two-variable model (agility, 1.5-mile endurance run) with 93% overall classification accuracy.

  15. 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

  16. Predicting Student Performance Using Online One-Minute Papers

    OpenAIRE

    Lee E. Erickson; Patricia A. Erickson

    2013-01-01

    One-minute papers are often used to encourage students to think and write briefly about their own learning, because teachers believe that metacognition and writing help students to learn. The proportion of online one-minute papers that students submit, however, has not previously been used to explain student achievement in economics. This paper shows that the completion rate is a very significant predictor of student performance after controlling for other variables already noted in the liter...

  17. Research of performance prediction to energy on hydraulic turbine

    Science.gov (United States)

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

    2012-11-01

    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.

  18. Predicting Performance in Technical Preclinical Dental Courses Using Advanced Simulation.

    Science.gov (United States)

    Gottlieb, Riki; Baechle, Mary A; Janus, Charles; Lanning, Sharon K

    2017-01-01

    The aim of this study was to investigate whether advanced simulation parameters, such as simulation exam scores, number of student self-evaluations, time to complete the simulation, and time to complete self-evaluations, served as predictors of dental students' preclinical performance. Students from three consecutive classes (n=282) at one U.S. dental school completed advanced simulation training and exams within the first four months of their dental curriculum. The students then completed conventional preclinical instruction and exams in operative dentistry (OD) and fixed prosthodontics (FP) courses, taken during the first and second years of dental school, respectively. Two advanced simulation exam scores (ASES1 and ASES2) were tested as predictors of performance in the two preclinical courses based on final course grades. ASES1 and ASES2 were found to be predictors of OD and FP preclinical course grades. Other advanced simulation parameters were not significantly related to grades in the preclinical courses. These results highlight the value of an early psychomotor skills assessment in dentistry. Advanced simulation scores may allow early intervention in students' learning process and assist in efficient allocation of resources such as faculty coverage and tutor assignment.

  19. Comparison of Predictive Models for PV Module Performance (Presentation)

    Energy Technology Data Exchange (ETDEWEB)

    Marion, B.

    2008-05-01

    This paper examines three models used to estimate the maximum power (P{sub m}) of PV modules when the irradiance and PV cell temperature are known: (1) the power temperature coefficient model, (2) the PVFORM model, and (3) the bilinear interpolation model. A variation of the power temperature coefficient model is also presented that improved model accuracy. For modeling values of P{sub m}, an 'effective' plane-of-array (POA) irradiance (E{sub e}) and the PV cell temperature (T) are used as model inputs. Using E{sub e} essentially removes the effects of variations in solar spectrum and reflectance losses, and permits the influence of irradiance and temperature on model performance for P{sub m} to be more easily studied. Eq. 1 is used to determine E{sub e} from T and the PV module's measured short-circuit current (I{sub sc}). Zero subscripts denote performance at Standard Reporting Conditions (SRC).

  20. 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…

  1. Allometric scaling and predicting cycling performance in (well-) trained female cyclists.

    Science.gov (United States)

    Lamberts, R P; Davidowitz, K J

    2014-03-01

    As female cycling attains greater professionalism, a larger emphasis is placed on the ability to predict and monitor changes in their cycling performance. The main aim of this study was to determine if peak power output (PPO) adjusted for body mass (W · kg-0.32) accurately predicts flat 40-km time trial performance (40 km TT) in female cyclists as found in men. 20 (well-) trained female cyclists completed a PPO test including maximal oxygen consumption (VO2max) and a flat 40 km TT test. Relationships between cycling performance parameters were also compared to the cycling performance of 45 male cyclists. Allometrically scaled PPW (W · kg(-0.32)) most accurately predicted 40 km TT performance in the female cyclists (r = -0.87, pequations should be used when predicting relative cycling performance parameters. © Georg Thieme Verlag KG Stuttgart · New York.

  2. 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.

  3. Performance prediction of electrohydrodynamic thrusters by the perturbation method

    Energy Technology Data Exchange (ETDEWEB)

    Shibata, H., E-mail: shibata@daedalus.k.u-tokyo.ac.jp; Watanabe, Y. [Department of Aeronautics and Astronautics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Suzuki, K. [Department of Advanced Energy, The University of Tokyo, Kashiwanoha, Kashiwa, Chiba 277-8561 (Japan)

    2016-05-15

    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.

  4. Realistic prediction of dynamic aperture and optics performance for LEP

    CERN Document Server

    Jowett, John M

    1999-01-01

    Over the two-decade lifetime of the LEP project, techniques for evaluating the quality of optical configurations have evolved considerably to exploit the growth in computer power and improved modelling of single-particle dynamics. These developments have culminated in a highly automated Monte-Carlo evaluation process whose stages include the generation of an ensemble of imperfect machines, simulation of the operational correction procedures, correlation studies of the optical functions and parameters of (both) beams, 4-dimensional dynamic aperture scans and tracking with quantum fluctuations to determine the beam core distribution. We outline the process, with examples, and explain why each step is necessary to realistically capture essential physics affecting performance. The mechanisms determining the vertical emittance, radial beam distribution and dynamic aperture are especially important. As a storage ring in which an unusual variety of optics have been tested, LEP provides a valuable test case for the p...

  5. Glucose tolerance predicts performance on tests of memory and cognition.

    Science.gov (United States)

    Donohoe, R T; Benton, D

    The hypothesis that the ability to control blood glucose levels influence memory and other aspects of cognition was considered. Individual differences in the ability to control blood glucose were measured by giving a glucose tolerance test (GTT) to 46 young adult females. A factor analysis of a series of measures of glucose tolerance produced four dimensions. A week later, having eaten their normal breakfast, they took tests of memory, reaction times and vigilance. The speed with which blood glucose increased, having its lowest point in the GTT, was associated with memory measured a week later. While performing the tests those with higher levels of blood glucose on arrival in the laboratory had quicker reaction times when monitoring eight but not four, two or one lamps. The finding was interpreted as demonstrating that higher levels of blood glucose specially influence tasks placing higher demands on the brain.

  6. Trends in the predictive performance of raw ensemble weather forecasts

    Science.gov (United States)

    Hemri, Stephan; Scheuerer, Michael; Pappenberger, Florian; Bogner, Konrad; Haiden, Thomas

    2015-04-01

    Over the last two decades the paradigm in weather forecasting has shifted from being deterministic to probabilistic. Accordingly, numerical weather prediction (NWP) models have been run increasingly as ensemble forecasting systems. The goal of such ensemble forecasts is to approximate the forecast probability distribution by a finite sample of scenarios. Global ensemble forecast systems, like the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble, are prone to probabilistic biases, and are therefore not reliable. They particularly tend to be underdispersive for surface weather parameters. Hence, statistical post-processing is required in order to obtain reliable and sharp forecasts. In this study we apply statistical post-processing to ensemble forecasts of near-surface temperature, 24-hour precipitation totals, and near-surface wind speed from the global ECMWF model. Our main objective is to evaluate the evolution of the difference in skill between the raw ensemble and the post-processed forecasts. The ECMWF ensemble is under continuous development, and hence its forecast skill improves over time. Parts of these improvements may be due to a reduction of probabilistic bias. Thus, we first hypothesize that the gain by post-processing decreases over time. Based on ECMWF forecasts from January 2002 to March 2014 and corresponding observations from globally distributed stations we generate post-processed forecasts by ensemble model output statistics (EMOS) for each station and variable. Parameter estimates are obtained by minimizing the Continuous Ranked Probability Score (CRPS) over rolling training periods that consist of the n days preceding the initialization dates. Given the higher average skill in terms of CRPS of the post-processed forecasts for all three variables, we analyze the evolution of the difference in skill between raw ensemble and EMOS forecasts. The fact that the gap in skill remains almost constant over time, especially for near

  7. 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

  8. Using dynamical uncertainty models estimating uncertainty bounds on power plant performance prediction

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob; Mataji, B.

    2007-01-01

    Predicting the performance of large scale plants can be difficult due to model uncertainties etc, meaning that one can be almost certain that the prediction will diverge from the plant performance with time. In this paper output multiplicative uncertainty models are used as dynamical models of th...... models, is applied to two different sets of measured plant data. The computed uncertainty bounds cover the measured plant output, while the nominal prediction is outside these uncertainty bounds for some samples in these examples.  ......Predicting the performance of large scale plants can be difficult due to model uncertainties etc, meaning that one can be almost certain that the prediction will diverge from the plant performance with time. In this paper output multiplicative uncertainty models are used as dynamical models...... of the prediction error. These proposed dynamical uncertainty models result in an upper and lower bound on the predicted performance of the plant. The dynamical uncertainty models are used to estimate the uncertainty of the predicted performance of a coal-fired power plant. The proposed scheme, which uses dynamical...

  9. The nebulous art of using wind tunnel aerofoil data for predicting rotor performance

    Energy Technology Data Exchange (ETDEWEB)

    Tangler, J.L. [National Renewable Energy Laboratory, Golden, CO (United States). Applied Research Division

    2002-07-01

    The objective of this study was threefold: to evaluate different two-dimensional S809 aerofoil data sets in the prediction of rotor performance; to compare blade element momentum rotor predicted results with lifting surface, prescribed wake results; and to compare the NASA Ames combined experiment rotor measured data with the two different performance prediction methods. The S809 aerofoil data sets evaluated included those from Delft University of Technology, Ohio State University and Colorado State University. Substantial differences in prediction performance resulted from the different two-dimensional aerofoil data sets. Predicted performance comparison with NASA Ames data documents shortcomings of these methods and recommends the use of the lifting surface, prescribed wake method over blade element momentum theory for future analytical improvements. (author)

  10. Performance Prediction of Differential Fibers with a Bi-Directional Optimization Approach

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2013-12-01

    Full Text Available This paper develops a bi-directional prediction approach to predict the production parameters and performance of differential fibers based on neural networks and a multi-objective evolutionary algorithm. The proposed method does not require accurate description and calculation for the multiple processes, different modes and complex conditions of fiber production. The bi-directional prediction approach includes the forward prediction and backward reasoning. Particle swam optimization algorithms with K-means algorithm are used to minimize the prediction error of the forward prediction results. Based on the forward prediction, backward reasoning uses the multi-objective evolutionary algorithm to find the reasoning results. Experiments with polyester filament parameters of differential production conditions indicate that the proposed approach obtains good prediction results. The results can be used to optimize fiber production and to design differential fibers. This study also has important value and widespread application prospects regarding the spinning of differential fiber optimization.

  11. Guidelines for using sensitivity analysis and auto-calibration tools for multi-gage or multi-step calibration in SWAT

    Science.gov (United States)

    Autocalibration of a water quality model such as SWAT (Soil and Water Assessment Tool) can be a powerful, labor-saving tool. When multi-gage or multi-pollutant calibration is desired, autocalibration is essential because the time involved in manual calibration becomes prohibitive. The ArcSWAT Interf...

  12. 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.

  13. Predicting optimum vortex tube performance using a simplified CFD model

    Energy Technology Data Exchange (ETDEWEB)

    Karimi-Esfahani, M; Fartaj, A.; Rankin, G.W. [Univ. of Windsor, Dept. of Mechanical, Automotive and Materials Engineering, Windsor, Ontario (Canada)]. E-mail: mki_60@hotmail.com

    2004-07-01

    The Ranque-Hilsch tube is a particular type of vortex tube device. The flow enters the device tangentially near one end and exits from the open ends of the tube. The inlet air is of a uniform temperature throughout while the outputs are of different temperatures. One outlet is hotter and the other is colder than the inlet air. This device has no moving parts and does not require any additional power for its operation other than that supplied to the device to compress the inlet air. It has, however, not been widely used, mainly because of its low efficiency. In this paper, a simplified 2-dimensional computational fluid dynamics model for the flow in the vortex tube is developed using FLUENT. This model makes use of the assumption of axial symmetry throughout the entire flow domain. Compared to a three-dimensional computational solution, the simplified model requires significantly less computational time. This is important because the model is to be used for an optimization study. A user-defined function is generated to implement a modified version of the k-epsilon model to account for turbulence. This model is validated by comparing a particular solution with available experimental data. The variation of cold temperature drop and efficiency of the device with orifice diameter, inlet pressure and cold mass flow ratio qualitatively agree with experimental results. Variation of these performance indices with tube length did not agree with the experiments for small values of tube length. However, it did agree qualitatively for large values. (author)

  14. Management-oriented sensitivity analysis for pesticide transport in watershed-scale water quality modeling using SWAT

    Energy Technology Data Exchange (ETDEWEB)

    Luo Yuzhou [University of California, Davis, CA 95616 (United States); Wenzhou Medical College, Wenzhou 325035 (China); Zhang Minghua, E-mail: mhzhang@ucdavis.ed [University of California, Davis, CA 95616 (United States); Wenzhou Medical College, Wenzhou 325035 (China)

    2009-12-15

    The Soil and Water Assessment Tool (SWAT) was calibrated for hydrology conditions in an agricultural watershed of Orestimba Creek, California, and applied to simulate fate and transport of two organophosphate pesticides chlorpyrifos and diazinon. The model showed capability in evaluating pesticide fate and transport processes in agricultural fields and instream network. Management-oriented sensitivity analysis was conducted by applied stochastic SWAT simulations for pesticide distribution. Results of sensitivity analysis identified the governing processes in pesticide outputs as surface runoff, soil erosion, and sedimentation in the study area. By incorporating sensitive parameters in pesticide transport simulation, effects of structural best management practices (BMPs) in improving surface water quality were demonstrated by SWAT modeling. This study also recommends conservation practices designed to reduce field yield and in-stream transport capacity of sediment, such as filter strip, grassed waterway, crop residue management, and tailwater pond to be implemented in the Orestimba Creek watershed. - Selected structural BMPs are recommended for reducing loads of OP pesticides.

  15. Modelling of hydrologic processes and potential response to climate change through the use of a multisite SWAT

    DEFF Research Database (Denmark)

    Gül, G.O.; Rosbjerg, Dan

    2010-01-01

    Hydrologic models that use components for integrated modelling of surface water and groundwater systems help conveniently simulate the dynamically linked hydrologic and hydraulic processes that govern flow conditions in watersheds. The Soil and Water Assessment Tool (SWAT) is one such model...... that allows continuous simulations over long time periods in the land phase of the hydrologic cycle by incorporating surface water and groundwater interactions. This study provides a verified structure for the SWAT to evaluate existing flow regimes in a small-sized catchment in Denmark and examines a simple...... simulation to help quantify the effects of climate change on regional water quantities. SWAT can be regarded among the alternative hydrologic simulation tools applicable for catchments with similar characteristics and of similar sizes in Denmark. However, the modellers would be required to determine a proper...

  16. Research on Application of Regression Least Squares Support Vector Machine on Performance Prediction of Hydraulic Excavator

    Directory of Open Access Journals (Sweden)

    Zhan-bo Chen

    2014-01-01

    Full Text Available In order to improve the performance prediction accuracy of hydraulic excavator, the regression least squares support vector machine is applied. First, the mathematical model of the regression least squares support vector machine is studied, and then the algorithm of the regression least squares support vector machine is designed. Finally, the performance prediction simulation of hydraulic excavator based on regression least squares support vector machine is carried out, and simulation results show that this method can predict the performance changing rules of hydraulic excavator correctly.

  17. 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.

  18. Updating and Not Shifting Predicts Learning Performance in Young and Middle-Aged Adults

    Science.gov (United States)

    Gijselaers, Hieronymus J. M.; Meijs, Celeste; Neroni, Joyce; Kirschner, Paul A.; de Groot, Renate H. M.

    2017-01-01

    The goal of this study was to investigate whether single executive function (EF) tests were predictive for learning performance in mainly young and middle-aged adults. The tests measured shifting and updating. Processing speed was also measured. In an observational study, cognitive performance and learning performance were measured objectively in…

  19. Pre-Clinical Grades Predict Clinical Performance in the MBBS Stage ...

    African Journals Online (AJOL)

    Summary: In the preclinical sciences, statistically significant predictive values have been reported between the performances in one discipline and the others, supporting the hypothesis that students who perform well in one discipline were likely to perform well in the other disciplines. We therefore decided to conduct a ...

  20. Assessment of Climate Change Impacts on Water Resources in Zarrinehrud Basin Using SWAT Model

    Directory of Open Access Journals (Sweden)

    B. Mansouri

    2015-06-01

    Full Text Available This paper evaluate impacts of climate change on temperature, rainfall and runoff in the future Using statistical model, LARS-WG, and conceptual hydrological model, SWAT. In order to the Zarrinehrud river basin, as the biggest catchment of the Lake Urmia basin was selected as a case study. At first, for the generation of future weather data in the basin, LARS-WG model was calibrated using meteorological data and then 14 models of AOGCM were applied and results of these models were downscaled using LARS-WG model in 6 synoptic stations for period of 2015 to 2030. SWAT model was used for evaluation of climate change impacts on runoff in the basin. In order to, the model was calibrated and validated using 6 gauging stations for period of 1987-2007 and the value of R2 was between 0.49 and 0.71 for calibration and between 0.54 and 0.77 for validation. Then by introducing average of downscaled results of AOGCM models to the SWAT, runoff changes of the basin were simulated during 2015-2030. Average of results of LARS-WG model indicated that the monthly mean of minimum and maximum temperatures will increase compared to the baseline period. Also monthly average of precipitation will decrease in spring season but will increase in summer and autumn. The results showed that in addition to the amount of precipitation, its pattern will change in the future period, too. The results of runoff simulation showed that the amount of inflow to the Zarrinehrud reservoir will reduce 28.4 percent compared to the baseline period.

  1. Impact of Uncertainty in SWAT Model Simulations on Consequent Decisions on Optimal Crop Management Practices

    Science.gov (United States)

    Krishnan, N.; Sudheer, K. P.; Raj, C.; Chaubey, I.

    2015-12-01

    The diminishing quantities of non-renewable forms of energy have caused an increasing interest in the renewable sources of energy, such as biofuel, in the recent years. However, the demand for biofuel has created a concern for allocating grain between the fuel and food industry. Consequently, appropriate regulations that limit grain based ethanol production have been developed and are put to practice, which resulted in cultivating perennial grasses like Switch grass and Miscanthus to meet the additional cellulose demand. A change in cropping and management practice, therefore, is essential to cater the conflicting requirement for food and biofuel, which has a long-term impact on the downstream water quality. Therefore it is essential to implement optimal cropping practices to reduce the pollutant loadings. Simulation models in conjunction with optimization procedures are useful in developing efficient cropping practices in such situations. One such model is the Soil and Water Assessment Tool (SWAT), which can simulate both the water and the nutrient cycle, as well as quantify long-term impacts of changes in management practice in the watershed. It is envisaged that the SWAT model, along with an optimization algorithm, can be used to identify the optimal cropping pattern that achieves the minimum guaranteed grain production with less downstream pollution, while maximizing the biomass production for biofuel generation. However, the SWAT simulations do have a certain level of uncertainty that needs to be accounted for before making decisions. Therefore, the objectives of this study are twofold: (i) to understand how model uncertainties influence decision-making, and (ii) to develop appropriate management scenarios that account the uncertainty. The simulation uncertainty of the SWAT model is assessed using Shuffled Complex Evolutionary Metropolis Algorithm (SCEM). With the data collected from St. Joseph basin, IN, USA, the preliminary results indicate that model

  2. 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 exp...

  3. Predicting Academic Performance in Children with Language Impairment: The Role of Parent Report

    Science.gov (United States)

    Hall, Nancy E.; Segarra, Veronica Rosa

    2007-01-01

    This study examines the ability of preschool speech-language measures and parent report in predicting later academic performance. Preschool measures of speech, language and communication for 35 children with language impairment were analyzed for their ability to predict reading, writing, spelling, and mathematics in these same children at age…

  4. Analyzing Log Files to Predict Students' Problem Solving Performance in a Computer-Based Physics Tutor

    Science.gov (United States)

    Lee, Young-Jin

    2015-01-01

    This study investigates whether information saved in the log files of a computer-based tutor can be used to predict the problem solving performance of students. The log files of a computer-based physics tutoring environment called Andes Physics Tutor was analyzed to build a logistic regression model that predicted success and failure of students'…

  5. 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...

  6. A New Submaximal Rowing Test to Predict 2,000-m Rowing Ergometer Performance

    NARCIS (Netherlands)

    Otter, Ruby T. A.; Brink, Michel S.; Lamberts, Robert P.; Lemmink, Koen A. P. M.

    Otter, RTA, Brink, MS, Lamberts, RP, and Lemmink, KAPM. A new submaximal rowing test to predict 2,000-m rowing ergometer performance. J Strength Cond Res 29(9): 2426-2433, 2015-The purpose of this study was to assess predictive value of a new submaximal rowing test (SmRT) on 2,000-m ergometer rowing

  7. The Soil and Water Assessment Tool (SWAT) Ecohydrological Model Circa 2015: Global Application Trends, Insights and Issues

    Science.gov (United States)

    Gassman, P. W.; Arnold, J. G.; Srinivasan, R.

    2015-12-01

    The Soil and Water Assessment Tool (SWAT) is one of the most widely used watershed-scale water quality models in the world. Over 2,000 peer-reviewed SWAT-related journal articles have been published and hundreds of other studies have been published in conference proceedings and other formats. The use of SWAT was initially concentrated in North America and Europe but has also expanded dramatically in other countries and regions during the past decade including Brazil, China, India, Iran, South Korea, Southeast Asia and eastern Africa. The SWAT model has proven to be a very flexible tool for investigating a broad range of hydrologic and water quality problems at different watershed scales and environmental conditions, and has proven very adaptable for applications requiring improved hydrologic and other enhanced simulation needs. We investigate here the various technological, networking, and other factors that have supported the expanded use of SWAT, and also highlight current worldwide simulation trends and possible impediments to future increased usage of the model. Examples of technological advances include easy access to web-based documentation, user-support groups, and SWAT literature, a variety of Geographic Information System (GIS) interface tools, pre- and post-processing calibration software and other software, and an open source code which has served as a model development catalyst for multiple user groups. Extensive networking regarding the use of SWAT has further occurred via internet-based user support groups, model training workshops, regional working groups, regional and international conferences, and targeted development workshops. We further highlight several important model development trends that have emerged during the past decade including improved hydrologic, cropping system, best management practice (BMP) and pollutant transport simulation methods. In addition, several current SWAT weaknesses will be addressed and key development needs will be

  8. 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 connectio...

  9. 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.

  10. 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

  11. An analytic model for predicting the performance of distributed applications on multicore clusters

    CSIR Research Space (South Africa)

    Khanyile, NP

    2012-08-01

    Full Text Available Processing, pp. 269?272, 1997. [14] B. Cornea and J. Bourgeois, ?Performance prediction of distributed applications using block benchmarking methods,? in Proceedings of the 19th International Euromicro Conference on Parallel, Distributed and Network...

  12. Prediction of rowing ergometer performance from functional anaerobic power, strength and anthropometric components.

    Science.gov (United States)

    Akça, Fırat

    2014-06-28

    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.

  13. 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.

  14. A Unified Model of Performance: Validation of its Predictions across Different Sleep/Wake Schedules.

    Science.gov (United States)

    Ramakrishnan, Sridhar; Wesensten, Nancy J; Balkin, Thomas J; Reifman, Jaques

    2016-01-01

    Historically, mathematical models of human neurobehavioral performance developed on data from one sleep study were limited to predicting performance in similar studies, restricting their practical utility. We recently developed a unified model of performance (UMP) to predict the effects of the continuum of sleep loss-from chronic sleep restriction (CSR) to total sleep deprivation (TSD) challenges-and validated it using data from two studies of one laboratory. Here, we significantly extended this effort by validating the UMP predictions across a wide range of sleep/wake schedules from different studies and laboratories. We developed the UMP on psychomotor vigilance task (PVT) lapse data from one study encompassing four different CSR conditions (7 d of 3, 5, 7, and 9 h of sleep/night), and predicted performance in five other studies (from four laboratories), including different combinations of TSD (40 to 88 h), CSR (2 to 6 h of sleep/night), control (8 to 10 h of sleep/night), and nap (nocturnal and diurnal) schedules. The UMP accurately predicted PVT performance trends across 14 different sleep/wake conditions, yielding average prediction errors between 7% and 36%, with the predictions lying within 2 standard errors of the measured data 87% of the time. In addition, the UMP accurately predicted performance impairment (average error of 15%) for schedules (TSD and naps) not used in model development. The unified model of performance can be used as a tool to help design sleep/wake schedules to optimize the extent and duration of neurobehavioral performance and to accelerate recovery after sleep loss. © 2016 Associated Professional Sleep Societies, LLC.

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

    OpenAIRE

    Gijselaers, Jérôme

    2015-01-01

    The aim of this dissertation was to explore the characteristics of different student groups (i.e., successful, non-successful, and non-starting). The second aim was to examine whether biological lifestyle factors (e.g. physical activity, sleep, and nutrition) predicted learning performance. Third, it aimed to investigate whether these biological lifestyle factors predicted cognitive performance, as this can be a predictor for learning in traditional education. The final aim was to determine w...

  16. Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

    Science.gov (United States)

    Cai, X.; Yang, Z.-L.; Fisher, J. B.; Zhang, X.; Barlage, M.; Chen, F.

    2016-01-01

    Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station - a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.

  17. Effect of window length on performance of the elbow-joint angle prediction based on electromyography

    Science.gov (United States)

    Triwiyanto; Wahyunggoro, Oyas; Adi Nugroho, Hanung; Herianto

    2017-05-01

    The high performance of the elbow joint angle prediction is essential on the development of the devices based on electromyography (EMG) control. The performance of the prediction depends on the feature of extraction parameters such as window length. In this paper, we evaluated the effect of the window length on the performance of the elbow-joint angle prediction. The prediction algorithm consists of zero-crossing feature extraction and second order of Butterworth low pass filter. The feature was used to extract the EMG signal by varying window length. The EMG signal was collected from the biceps muscle while the elbow was moved in the flexion and extension motion. The subject performed the elbow motion by holding a 1-kg load and moved the elbow in different periods (12 seconds, 8 seconds and 6 seconds). The results indicated that the window length affected the performance of the prediction. The 250 window lengths yielded the best performance of the prediction algorithm of (mean±SD) root mean square error = 5.68%±1.53% and Person’s correlation = 0.99±0.0059.

  18. 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.

  19. 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.

  20. Determinants of Rifle Marksmanship Performance: Predicting Shooting Performance with Advanced Distributed Learning Assessments

    National Research Council Canada - National Science Library

    Chung, Gregory K; Cruz, Girlie C. De La; Vries, Linda F. de; Kim, Jin-Ok; Bewley, William L; Souza e Silva, Adriana A. de; Sylvester, Roxanne M; Baker, Eva L

    2004-01-01

    .... The evidence suggests a knowledge component to shooting performance, and differences in knowledge of rifle marksmanship between participants' pre-classroom training and post-classroom training...

  1. 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

  2. Validity of Treadmill-Derived Critical Speed on Predicting 5000-Meter Track-Running Performance.

    Science.gov (United States)

    Nimmerichter, Alfred; Novak, Nina; Triska, Christoph; Prinz, Bernhard; Breese, Brynmor C

    2017-03-01

    Nimmerichter, A, Novak, N, Triska, C, Prinz, B, and Breese, BC. Validity of treadmill-derived critical speed on predicting 5,000-meter track-running performance. J Strength Cond Res 31(3): 706-714, 2017-To evaluate 3 models of critical speed (CS) for the prediction of 5,000-m running performance, 16 trained athletes completed an incremental test on a treadmill to determine maximal aerobic speed (MAS) and 3 randomly ordered runs to exhaustion at the [INCREMENT]70% intensity, at 110% and 98% of MAS. Critical speed and the distance covered above CS (D') were calculated using the hyperbolic speed-time (HYP), the linear distance-time (LIN), and the linear speed inverse-time model (INV). Five thousand meter performance was determined on a 400-m running track. Individual predictions of 5,000-m running time (t = [5,000-D']/CS) and speed (s = D'/t + CS) were calculated across the 3 models in addition to multiple regression analyses. Prediction accuracy was assessed with the standard error of estimate (SEE) from linear regression analysis and the mean difference expressed in units of measurement and coefficient of variation (%). Five thousand meter running performance (speed: 4.29 ± 0.39 m·s; time: 1,176 ± 117 seconds) was significantly better than the predictions from all 3 models (p performance (-1.0 to 1.1%). The SEE across all models and predictions was approximately 65 seconds or 0.20 m·s and is therefore considered as moderate. The results of this study have shown the importance of aerobic and anaerobic energy system contribution to predict 5,000-m running performance. Using estimates of CS and D' is valuable for predicting performance over race distances of 5,000 m.

  3. Subjective Workload Assessment Technique (SWAT): A User’s Guide

    Science.gov (United States)

    1989-07-01

    The effects of supervisor experience and the presence of a shift technical advisor on the performance of two-man crews in a nuclear power plant...et de Recherches de Medecine Acrospatiale, Laboratoire d’Etudes Medicophysiologiques 16/330). S 110 Potter, S. S., 1986, Subjective workload assessment

  4. 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% effects of 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.

  5. 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.

  6. Towards the integration of multiple classifier pertaining to the Student's performance prediction

    Directory of Open Access Journals (Sweden)

    Mrinal Pandey

    2016-09-01

    Full Text Available Accurate predictions of students’ academic performance at early stages of the degree programme helps in identification of the weak students and enable management to take the corrective actions to prevent them from failure. Existing single classifier based predictive modelling is not easily scalable from one context to another context, Moreover, a predictive model developed for a particular course at a particular institution may not be valid for a different course at the same institution or any other institution. With this necessity, the notion of the integrated multiple classifiers for the predictions of students’ academic performance is proposed in this article. The integrated classifier consists of three complementary algorithms, namely Decision Tree, K-Nearest Neighbour, and Aggregating One-Dependence Estimators (AODE. A product of probability combining rule is employed to integrate the multiple classifiers for the prediction of academic performance of the engineering students. This approach provides a generalized solution for student performance prediction. The proposed method has been applied and compared on three student performance datasets using t-test. The proposed method is also compared with KSTAR, OneR, ZeroR, Naive Bayes, and NB tree classifiers as well as with the individual classifiers.

  7. Predicting Microbial Fuel Cell Biofilm Communities and Bioreactor Performance using Artificial Neural Networks.

    Science.gov (United States)

    Lesnik, Keaton Larson; Liu, Hong

    2017-09-19

    The complex interactions that occur in mixed-species bioelectrochemical reactors, like microbial fuel cells (MFCs), make accurate predictions of performance outcomes under untested conditions difficult. While direct correlations between any individual waste stream characteristic or microbial community structure and reactor performance have not been able to be directly established, the increase in sequencing data and readily available computational power enables the development of alternate approaches. In the current study, 33 MFCs were evaluated under a range of conditions including eight separate substrates and three different wastewaters. Artificial Neural Networks (ANNs) were used to establish mathematical relationships between wastewater/solution characteristics, biofilm communities, and reactor performance. ANN models that incorporated biotic interactions predicted reactor performance outcomes more accurately than those that did not. The average percent error of power density predictions was 16.01 ± 4.35%, while the average percent error of Coulombic efficiency and COD removal rate predictions were 1.77 ± 0.57% and 4.07 ± 1.06%, respectively. Predictions of power density improved to within 5.76 ± 3.16% percent error through classifying taxonomic data at the family versus class level. Results suggest that the microbial communities and performance of bioelectrochemical systems can be accurately predicted using data-mining, machine-learning techniques.

  8. 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

  9. Sediment management modelling in the Blue Nile Basin using SWAT model

    Directory of Open Access Journals (Sweden)

    G. D. Betrie

    2011-03-01

    Full Text Available Soil erosion/sedimentation is an immense problem that has threatened water resources development in the Nile river basin, particularly in the Eastern Nile (Ethiopia, Sudan and Egypt. An insight into soil erosion/sedimentation mechanisms and mitigation methods plays an imperative role for the sustainable water resources development in the region. This paper presents daily sediment yield simulations in the Upper Blue Nile under different Best Management Practice (BMP scenarios. Scenarios applied in this paper are (i maintaining existing conditions, (ii introducing filter strips, (iii applying stone bunds (parallel terraces, and (iv reforestation. The Soil and Water Assessment Tool (SWAT was used to model soil erosion, identify soil erosion prone areas and assess the impact of BMPs on sediment reduction. For the existing conditions scenario, the model results showed a satisfactory agreement between daily observed and simulated sediment concentrations as indicated by Nash-Sutcliffe efficiency greater than 0.83. The simulation results showed that applying filter strips, stone bunds and reforestation scenarios reduced the current sediment yields both at the subbasins and the basin outlets. However, a precise interpretation of the quantitative results may not be appropriate because some physical processes are not well represented in the SWAT model.

  10. User's guide for simulation of waste treatment (SWAT) model

    Energy Technology Data Exchange (ETDEWEB)

    Macal, C.M.

    1979-04-01

    This document is a user's guide for the Simulation of Waste Treatment (SWAT) model computer code. (A detailed description of the logic and assumptions of the model was published previously.) A flow diagram depicting the logic of the SWAT computer code is included. Several river basins or regions can be simulated in a single computer run, with each region having numerous treatment plants. Treatment plants are simulated sequentially to reduce computer storage requirements. All input to the model is in the form of cards and all output is to a line printer. The code is written in FORTRAN IV and consists of approximately 3000 statements. Using the IBM 370/195 under OS, a Gl compiler requires a region of 220K. Execution time is under two minutes for a typical run for a river basin with 23 treatment plants, with each plant having an average of one technology modification over a simulation period of 25 years. In the first section of this report a brief description of the subroutines in the model is given along with an explanation of how the subroutines function in the context of the whole program. The third section indicates formatting for input data; sample input data for a test problem are also presented. Section 4 describes the output resulting from the sample input data. A program listing appears in the appendix.

  11. 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)

  12. 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.

  13. 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…

  14. (Originals) Anthropometric and Physiological Factors Predicting 2000 m Rowing Ergometer Performance Time

    OpenAIRE

    Chie, Yoshiga; Yasuo, Kawakami; Tetsuo, Fukunaga; Graduate School of Education,The University of Tokyo; Graduate School of Arts and Science,The University of Tokyo; Graduate School of Arts and Science,The University of Tokyo

    2000-01-01

    In attempt to predict 2000 m rowing ergometer performance time, we studied anthropometric and physiological limiting factors among 78 collegiate male rowers. Among variables that we measured, 2000 m rowing performance time was significantly and inversely related to lean body mass(r=-0.68), maximal oxygen uptake(-0.64), and leg extension power(-0.54)(p

  15. Ability of Early Literacy Measures to Predict Future State Assessment Performance

    Science.gov (United States)

    Utchell, Lynn A.; Schmitt, Ara J.; McCallum, Elizabeth; McGoey, Kara E.; Piselli, Kate

    2016-01-01

    The purpose of this study was to determine the extent to which early literacy measures administered in kindergarten and Oral Reading Fluency (ORF) measures administered in Grade 1 are related to and predict future state reading assessment performances up to 7 years later. Results indicated that early literacy and ORF performances were…

  16. 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…

  17. Updating and not shifting predicts learning performance in young and middle-aged adults

    NARCIS (Netherlands)

    Gijselaers, Jérôme; Meijs, Celeste; Neroni, Joyce; Kirschner, Paul A.; De Groot, Renate

    2017-01-01

    The goal of this study was to investigate whether single executive function (EF) tests were predictive for learning performance in mainly young and middle-aged adults. The tests measured shifting and updating. Processing speed was also measured. In an observational study, cognitive performance and

  18. A predictive model of flight crew performance in automated air traffic control and flight management operations

    Science.gov (United States)

    1995-01-01

    Prepared ca. 1995. This paper describes Air-MIDAS, a model of pilot performance in interaction with varied levels of automation in flight management operations. The model was used to predict the performance of a two person flight crew responding to c...

  19. 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…

  20. 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…

  1. Predicted and preliminary evaluation of the X-ray performance of the AXAF Technology Mirror Assembly

    Science.gov (United States)

    Van Speybroeck, Leon; Schwartz, Daniel; Reid, Paul; Bilbro, James

    1989-01-01

    The fabrication of the Technology Mirror Assembly (TMA) is complete, and performance predictions were made based upon mechanical and visible light measurements of the surface properties. An X-ray calibration program has been executed, and a preliminary analysis of a portion of the data is presented. The X-ray image distribution results are in reasonable agreement with the performance predictions which were calculated prior the start of the X-ray tests. The measured X-ray imaging performance approaches that expected for the Advanced X-ray Astrophysics Facility (AXAF).

  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

    Political skill is a social effectiveness construct with a demonstrated capacity to predict job performance. However, because performance prediction research in this area to date has made exclusive use of self-reports of political skill, and due to frequent distrust of self-ratings of constructs...... in important personnel decisions, there is a need to investigate how multiple alternative sources of political skill and job performance measures relate, thus raising both theoretical and methodological issues. In three studies, employing a triadic data collection methodology, and utilising both cross...

  3. 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.

  4. 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.

  5. 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)

  6. Hydrologic Response Unit Routing in SWAT to Simulate Effects of Vegetated Filter Strip for South-Korean Conditions Based on VFSMOD

    Directory of Open Access Journals (Sweden)

    Kyoung Jae Lim

    2011-08-01

    Full Text Available The Soil and Water Assessment Tool (SWAT model has been used worldwide for many hydrologic and Non-Point Source (NPS Pollution analyses on a watershed scale. However, it has many limitations in simulating the Vegetative Filter Strip (VFS because it considers only ‘filter strip width’ when the model estimates sediment trapping efficiency and does not consider the routing of sediment with overland flow which is expected to maximize the sediment trapping efficiency from upper agricultural subwatersheds to lower spatially-explicit filter strips. Therefore, the SWAT overland flow option between landuse-subwatersheds with sediment routing capability was enhanced by modifying the SWAT watershed configuration and SWAT engine based on the numerical model VFSMOD applied to South-Korean conditions. The enhanced SWAT can simulate the VFS sediment trapping efficiency for South-Korean conditions in a manner similar to the desktop VFSMOD-w system. Due to this enhancement, SWAT is applicable to simulate the effects of overland flow from upper subwatersheds to reflect increased runoff volume at the lower subwatershed, which occurs in the field if no diversion channel is installed. In this study, the enhanced SWAT model was applied to small watersheds located at Jaun-ri in South-Korea to simulate a diversion channel and spatially-explicit VFS. Sediment can be reduced by 31%, 65%, and 68%, with a diversion channel, the VFS, and the VFS with diversion channel, respectively. The enhanced SWAT should be used in estimating site-specific effects on sediment reduction with diversion channels and VFS, instead of the currently available SWAT, which does not simulate sediment routing in overland flow and does not consider other sensitive factors affecting sediment reduction with VFS.

  7. Macrophyte growth module for the SWAT model – impact of climate change and management on stream ecology

    DEFF Research Database (Denmark)

    Lu, Shenglan; Trolle, Dennis; Erfurt, Jytte

    To access how multiple stressors affect the water quantity and quality and stream ecology at catchment scale under various management and climate change scenarios, we implemented macrophyte growth modules for the Soil and Water Assessment Tool version 2012 (SWAT). The macrophyte growth module ori...

  8. Evalution of Long-Term Impacts of Conservation Practice Within the Little River Watershed Using the SWAT Model

    Science.gov (United States)

    The SWAT model was used to simulate the long-term impacts of conservation practices implemented within the South Georgia Little River Watershed on streamflow hydrology and water quality. Typical practices which have been implemented within the watershed include nutrient management, residue manageme...

  9. Validity of the UKCAT in applicant selection and predicting exam performance in UK dental students.

    Science.gov (United States)

    Lala, Rizwana; Wood, Duncan; Baker, Sarah

    2013-09-01

    The United Kingdom's Clinical Aptitude Test (UKCAT) aims to assess candidates' "natural talent" for dentistry. The aim of this study was to determine the validity of the UKCAT for dental school applicant selection. The relationship of the UKCAT with demographic and academic variables was examined, assessing if the likelihood of being offered a place at a UK dental school was predicted by demographic factors and academic selection tools (predicted grades and existing school results). Finally, the validity of these selection tools in predicting first-year dental exam performance was assessed. Correlational and regression analyses showed that females and poorer students were more likely to have lower UKCAT scores. Gender and social class did not, however, predict first-year dental exam performance. UKCAT scores predicted the likelihood of the candidate being offered a place in the dental course; however, they did not predict exam performance during the first year of the course. Indeed, the only predictor of dental exam performance was existing school results. These findings argue against the use of the UKCAT as the sole determinant in dental applicant selection, instead highlighting the value of using existing school results.

  10. The role of prior mathematical experience in predicting mathematics performance in higher education

    Science.gov (United States)

    Faulkner, Fiona; Hannigan, Ailish; Fitzmaurice, Olivia

    2014-07-01

    Evidence of deficiencies in basic mathematical skills of beginning undergraduates has been documented worldwide. Many different theories have been set out as to why these declines in mathematical competency levels have occurred over time. One such theory is the widening access to higher education which has resulted in a less mathematically prepared profile of beginning undergraduates than ever before. In response to this situation, the present study details the examination of a range of methods through which a student's mathematical performance in higher education could be predicted at the beginning of their third-level studies. Several statistical prediction methods were examined and the most effective method in predicting students' mathematical performance was discriminant analysis. The discriminant analysis correctly classified 71.3% of students in terms of mathematics performance. An ability to carry out such a prediction in turn allows for appropriate mathematics remediation to be offered to students predicted to fail third-level mathematics. The results of the prediction of mathematical performance, which was carried out using a database consisting of over 1000 beginning undergraduates over a 3-year period, are detailed in this article along with the implications of such findings to educational policy and practice.

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

    Directory of Open Access Journals (Sweden)

    Chris Jacobs

    2011-03-01

    Full Text Available Orientation: Currently no integrative model exists that can explain the phenomena contributing to agent performance in the South African contact centre industry.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.

  12. 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.

  13. 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.

  14. 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...

  15. Predicting Energy Performance of a Net-Zero Energy Building: A Statistical Approach

    Science.gov (United States)

    Kneifel, Joshua; Webb, David

    2016-01-01

    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 estimates to the results from already existing EnergyPlus whole building energy simulations. This regression model exhibits agreement with EnergyPlus predictive trends in energy production and net consumption, but differs greatly in energy consumption. The model can be used as a framework for alternative and more complex models based on the

  16. 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.

  17. Predictive performance of microarray gene signatures: impact of tumor heterogeneity and multiple mechanisms of drug resistance

    OpenAIRE

    Ng, Charlotte K. Y.; Weigelt, Britta; A’Hern, Roger; Bidard, Francois-Clement; Lemetre, Christophe; Swanton, Charles; Shen, Ronglai; Reis-Filho, Jorge S.

    2014-01-01

    Gene signatures have failed to predict responses to breast cancer therapy in patients to date. In this study, we used bioinformatic methods to explore the hypothesis that the existence of multiple drug resistance mechanisms in different patients may limit the power of gene signatures to predict responses to therapy. Additionally, we explored whether sub-stratification of resistant cases could improve performance. Gene expression profiles from 1,550 breast cancers analyzed with the same microa...

  18. A Wake Model for the Prediction of Propeller Performance at Low Advance Ratios

    Directory of Open Access Journals (Sweden)

    Ye Tian

    2012-01-01

    Full Text Available A low order panel method is used to predict the performance of propellers. A wake alignment model based on a pseudounsteady scheme is proposed and implemented. The results from this full wake alignment (FWA model are correlated with available experimental data, and results from RANS for some propellers at design and low advance ratios. Significant improvements have been found in the predicted integrated forces and pressure distributions.

  19. Formic Acid Investigation for the Prediction of High Explosive Detonation Properties and Performance

    Science.gov (United States)

    2010-07-01

    Picatinny Arsenal, NJ, January 1993. 4. Cowperthwaite, M. and Zwisler, W. H., "The JCZ Equations of State for Detonation Products and Their...AD AD-E403 298 Technical Report ARMET-TR-10006 FORMIC ACID INVESTIGATION FOR THE PREDICTION OF HIGH EXPLOSIVE DETONATION PROPERTIES AND...DATES COVERED {From - To) 4. TITLE AND SUBTITLE FORMIC ACID INVESTIGATION FOR THE PREDICTION OF HIGH EXPLOSIVE DETONATION PROPERTIES AND PERFORMANCE

  20. Predicting the performance of tungsten in a fusion environment: a literature review

    OpenAIRE

    Abernethy, RG

    2016-01-01

    Tungsten has been proposed for use in the divertor of future fusion devices. In this environment, it will be exposed to high heat fluxes, neutron damage and hydrogen and helium implantation. This review covers previous experimental and modelling work to establish our ability to predict the performance of tungsten in a fusion environment. Surrogates for high-energy neutrons have been used to predict the change in mechanical properties of tungsten, including fission neutron and self-ion exposur...

  1. Experimental Investigation of Typical Aircraft Field Performance Versus Predicted Performance Targets

    Science.gov (United States)

    Wood, Donald L.

    This thesis explores the human factors effects pilots have when controlling the aircraft during the takeoff phase of flight. These variables come into play in the transitory phase from ground roll to flight, and in the initiation of procedures to abort a takeoff during the ground run. The FAA provides regulations for manufacturers and operators to follow, ensuring safe manufacture of aircraft and pilots that fly without endangering the passengers; however, details regarding accounting of piloting variability are lacking. Creation of a numerical simulation allowed for the controlled variation of isolated piloting procedures in order to evaluate effects on field performance. Reduced rotation rates and delayed reaction times were found to cause significant increases in field length requirements over values published in the AFM. A pilot survey was conducted to evaluate common practices for line pilots in the field, which revealed minimum regulatory compliance is exercised with little to no feedback on runway length requirements. Finally, observation of pilots training in a CRJ-200 FTD gathered extensive information on typical piloting timings in the cockpit. AEO and OEI takeoffs were observed, as well as RTOs. Pilots showed large variability in procedures and timings resulting in significant inconsistency in runway distances used as well as V-speed compliance. The observed effects from pilot timing latency correlated with the numerical simulation increased field length outputs. Variability in piloting procedures results in erratic field performance that deviates from AFM published values that invite disaster in an aircraft operating near its field performance limitations.

  2. 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...

  3. Aerodynamic Performance Prediction of Straight-Bladed Vertical Axis Wind Turbine Based on CFD

    Directory of Open Access Journals (Sweden)

    L. X. Zhang

    2013-01-01

    Full Text Available Numerical simulation had become an attractive method to carry out researches on structure design and aerodynamic performance prediction of straight-bladed vertical axis wind turbine, while the prediction accuracy was the major concern of CFD. Based on the present two-dimensional CFD model, a series of systematic investigations were conducted to analyze the effects of computational domain, grid number, near-wall grid, and time step on prediction accuracy. And then efforts were devoted into prediction and analysis of the overall flow field, dynamic performance of blades, and its aerodynamic forces. The calculated results agree well with experimental data, and it demonstrates that RNG k-ε turbulent model is great to predict the tendency of aerodynamic forces but with a high estimate value of turbulence viscosity coefficient. Furthermore, the calculated tangential force is more dependent on near-wall grid and prediction accuracy is poor within the region with serious dynamic stall. In addition, blades experience mild and deep stalls at low tip speed ratio, and thus the leading edge separation vortex and its movement on the airfoil surface have a significant impact on the aerodynamic performance.

  4. The Process of Admission as a Means of Predicting Academic Performance in Higher Education

    Directory of Open Access Journals (Sweden)

    Aída Cortés Flores

    2008-05-01

    Full Text Available The objective of this investigation was to find out the predictive validity of the admission process regarding academic performance during the first year towards a degree in a private university in Mexico City. The grades derived from the National Examination for Admission into Higher Education (EXANI II, the general average grades from Senior High school and the points obtained through a questionnaire on social problems (DIT were considered as variables for predicting performance. Two hundred and forty male and female students, registered in Psychology, took part in this investigation. Their average age was 20 years old. The results showed that the highest grades obtained in the EXANI II were in the areas of numericand verbal reasoning followed by Spanish. Likewise, it was found that the number of points obtained in the EXANI II, the average high school grades and the students’ moral development made it possible to predict academic performance for the first year of their career.

  5. 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

    2014-01-01

    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 latency (SOL), 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 equations of perceived stress (PSS) and TST. PMID:23402597

  6. 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.

  7. 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.

  8. To branch out or stay focused? Affective shifts differentially predict organizational citizenship behavior and task performance.

    Science.gov (United States)

    Yang, Liu-Qin; Simon, Lauren S; Wang, Lei; Zheng, Xiaoming

    2016-06-01

    We draw from personality systems interaction (PSI) theory (Kuhl, 2000) and regulatory focus theory (Higgins, 1997) to examine how dynamic positive and negative affective processes interact to predict both task and contextual performance. Using a twice-daily diary design over the course of a 3-week period, results from multilevel regression analysis revealed that distinct patterns of change in positive and negative affect optimally predicted contextual and task performance among a sample of 71 employees at a medium-sized technology company. Specifically, within persons, increases (upshifts) in positive affect over the course of a workday better predicted the subsequent day's organizational citizenship behavior (OCB) when such increases were coupled with decreases (downshifts) in negative affect. The optimal pattern of change in positive and negative affect differed, however, in predicting task performance. That is, upshifts in positive affect over the course of the workday better predicted the subsequent day's task performance when such upshifts were accompanied by upshifts in negative affect. The contribution of our findings to PSI theory and the broader affective and motivation regulation literatures, along with practical implications, are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  9. Performance of Remotely Controlled Mandibular Protrusion Sleep Studies for Prediction of Oral Appliance Treatment Response.

    Science.gov (United States)

    Sutherland, Kate; Ngiam, Joachim; Cistulli, Peter A

    2017-03-15

    Mandibular protrusion during sleep monitoring has been proposed as a method to predict oral appliance treatment outcome. A commercial remotely controlled mandibular protrusion (RCMP) device has become available for this purpose with predictive accuracy demonstrated in an initial study. Our aim was to validate this RCMP method for oral appliance treatment outcome prediction in a clinical sleep laboratory setting. Forty-two obstructive sleep apnea (OSA) patients (apnea-hypopnea index [AHI] > 10 events/h) were recruited to undergo a RCMP sleep study before commencing oral appliance treatment. The RCMP study was used to make a prediction of treatment "Success" or "Failure" based on a rule of ≤ 1 respiratory event per 5 min supine rapid eye movement sleep. Oral appliance treatment response was verified by polysomonography and defined as treatment AHI 30 events/h). Two participants (5%) were not able to tolerate the RCMP study. Oral appliance treatment outcome was verified in 33 participants (RCMP results: "Success" n = 10, "Failure" n = 15, "Inconclusive" n = 8). In those with a treatment outcome prediction (n = 25) the diagnostic characteristics of the RCMP test were sensitivity 81.8%, specificity 92.9%, positive predictive value 90%, and negative predictive value 86.7% (n = 3 misclassified). The RCMP device was well tolerated by patients and successfully used to perform mandibular protrusion sleep studies in our sleep laboratory. The RCMP sleep study showed good accuracy as a prediction technique for oral appliance treatment outcome, although there was a high rate of inconclusive tests.

  10. Diversity and use of ethno-medicinal plants in the region of Swat, North Pakistan.

    Science.gov (United States)

    Akhtar, Naveed; Rashid, Abdur; Murad, Waheed; Bergmeier, Erwin

    2013-04-15

    Due to its diverse geographical and habitat conditions, northern Pakistan harbors a wealth of medicinal plants. The plants and their traditional use are part of the natural and cultural heritage of the region. This study was carried out to document which medicinal plant species and which plant parts are used in the region of Swat, which syndrome categories are particularly concerned, and which habitat spectrum is frequented by collectors. Finally, we assessed to which extent medicinal plants are vulnerable due to collection and habitat destruction. An ethnobotanical survey was undertaken in the Miandam area of Swat, North Pakistan. Data were collected through field assessment as well as from traditional healers and locals by means of personal interviews and semi-structured questionnaires. A total of 106 ethno-medicinal plant species belonging to 54 plant families were recorded. The most common growth forms were perennial (43%) and short-lived herbs (23%), shrubs (16%), and trees (15%). Most frequently used plant parts were leaves (24%), fruits (18%) and subterranean parts (15%). A considerable proportion of the ethno-medicinal plant species and remedies concerns gastro-intestinal disorders. The remedies were mostly prepared in the form of decoction or powder and were mainly taken orally. Eighty out of 106 ethno-medicinal plants were indigenous. Almost 50% of the plants occurred in synanthropic vegetation while slightly more than 50% were found in semi-natural, though extensively grazed, woodland and grassland vegetation. Three species (Aconitum violaceum, Colchicum luteum, Jasminum humile) must be considered vulnerable due to excessive collection. Woodlands are the main source for non-synanthropic indigenous medicinal plants. The latter include many range-restricted taxa and plants of which rhizomes and other subterranean parts are dug out for further processing as medicine. Medicinal plants are still widely used for treatment in the area of Swat. Some species of

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

    DEFF Research Database (Denmark)

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

    2005-01-01

    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....

  12. Performance Reliability Prediction of Complex System Based on the Condition Monitoring Information

    Directory of Open Access Journals (Sweden)

    Hongxing Wang

    2013-01-01

    Full Text Available Complex system performance reliability prediction is one of the means to understand complex systems reliability level, make maintenance decision, and guarantee the safety of operation. By the use of complex system condition monitoring information and condition monitoring information based on support vector machine, the paper aims to provide an evaluation of the degradation of complex system performance. With degradation assessment results as input variables, the prediction model of reliability is established in Winer random process. Taking the aircraft engine as an example, the effectiveness of the proposed method is verified in the paper.

  13. Comparison of academic, application form and social factors in predicting early performance on the medical course.

    Science.gov (United States)

    Lumb, Andrew B; Vail, Andy

    2004-09-01

    To compare the relative importance of social, academic and application form factors at admission in predicting performance in the first 3 years of a medicine course. Retrospective cohort study. A single UK medical school. A total of 738 students who entered medical school between 1994 and 1997. Performance in Year 3 objective structured clinical examination (OSCE). School-leaving grades were significant predictors of success in the OSCE. Non-academic activities as assessed from the application form were associated with poorer performance. Mature students performed extremely well, and male and ethnic minority students performed less well. Socioeconomic status and type of school attended were not found to affect performance on the course. The relatively poor performance of male and ethnic minority students urgently needs further investigation. Our results carry no suggestion that, other things being equal, widening access to medical school for mature students and those from less affluent backgrounds would result in poorer performance.

  14. Review and evaluation of performance measures for survival prediction models in external validation settings.

    Science.gov (United States)

    Rahman, M Shafiqur; Ambler, Gareth; Choodari-Oskooei, Babak; Omar, Rumana Z

    2017-04-18

    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. 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. 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. 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 accuracy curves. In addition, we recommend to investigate the characteristics

  15. Personality and performance-based measures in the prediction of alcohol use.

    Science.gov (United States)

    Skeel, Reid L; Pilarski, Carrie; Pytlak, Kimberley; Neudecker, John

    2008-09-01

    Research has demonstrated a variable relationship between alcohol consumption and self-report personality measures of novelty seeking and harm avoidance. Research has also demonstrated a relationship between performance-based measures of risk taking and substance use. The current study compared the utility of personality measures and performance-based measures in the prediction of alcohol use. The authors hypothesized that the domains would contribute uniquely and would also interact in the prediction of alcohol consumption. Data on alcohol consumption were collected on a daily basis for 2 weeks. Performance-based measures included the Bechara Gambling Task and the Balloon Analogue Risk Task. The Tridimensional Personality Questionnaire was the primary personality measure. Results partially supported hypotheses, in that personality measures showed strong relationships with alcohol use and interacted with performance-based measures in predicting alcohol consumption. Thus, both behavioral and personality measures contributed to prediction of alcohol consumption, and performance-based measures played a moderating role. Results suggest that a combination of behavioral and self-report personality measures may be useful for those screening groups for risk factors for excessive alcohol consumption. (c) 2008 APA, all rights reserved.

  16. 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.

  17. Do prior knowledge, personality and visual perceptual ability predict student performance in microscopic pathology?

    Science.gov (United States)

    Helle, Laura; Nivala, Markus; Kronqvist, Pauliina; Ericsson, K Anders; Lehtinen, Erno

    2010-06-01

    OBJECTIVES There has been long-standing controversy regarding aptitude testing and selection for medical education. Visual perception is considered particularly important for detecting signs of disease as part of diagnostic procedures in, for example, microscopic pathology, radiology and dermatology and as a component of perceptual motor skills in medical procedures such as surgery. In 1968 the Perceptual Ability Test (PAT) was introduced in dental education. The aim of the present pilot study was to explore possible predictors of performance in diagnostic classification based on microscopic observation in the context of an undergraduate pathology course. METHODS A pre- and post-test of diagnostic classification performance, test of visual perceptual skill (Test of Visual Perceptual Skills, 3rd edition [TVPS-3]) and a self-report instrument of personality (Big Five Personality Inventory) were administered. In addition, data on academic performance (performance in histology and cell biology, a compulsory course taken the previous year, in addition to performance on the microscopy examination and final examination) were collected. RESULTS The results indicated that one personality factor (Conscientiousness) and one element of visual perceptual ability (spatial relationship awareness) predicted performance on the pre-test. The only factor to predict performance on the post-test was performance on the pre-test. Similarly, the microscopy examination score was predicted by the pre-test score, in addition to the histology and cell biology grade. The course examination score was predicted by two personality factors (Conscientiousness and lack of Openness) and the histology and cell biology grade. CONCLUSIONS Visual spatial ability may be related to performance in the initial phase of training in microscopic pathology. However, from a practical point of view, medical students are able to learn basic microscopic pathology using worked-out examples, independently of measures

  18. Predicting Mathematical Performance: The Effect of Cognitive Processes and Self-Regulation Factors

    Directory of Open Access Journals (Sweden)

    Mariel Musso

    2012-01-01

    Full Text Available A substantial number of research studies have investigated the separate influence of working memory, attention, motivation, and learning strategies on mathematical performance and self-regulation in general. There is still little understanding of their impact on performance when taken together, understanding their interactions, and how much each of them contributes to the prediction of mathematical performance. With the emergence of new methodologies and technologies, such as the modelling with predictive systems, it is now possible to study these effects with approaches which use a wide range of data, including student characteristics, to estimate future performance without the need of traditional testing (Boekaerts and Cascallar, 2006. This research examines the different cognitive patterns and complex relations between cognitive variables, motivation, and background variables associated with different levels of mathematical performance using artificial neural networks (ANNs. A sample of 800 entering university students was used to develop three ANN models to identify the expected future level of performance in a mathematics test. These ANN models achieved high degree of precision in the correct classification of future levels of performance, showing differences in the pattern of relative predictive weight amongst those variables. The impact on educational quality, improvement, and accountability is highlighted.

  19. Predicting performance on the Medical Council of Canada Qualifying Exam Part II.

    Science.gov (United States)

    Woloschuk, Wayne; McLaughlin, Kevin; Wright, Bruce

    2013-01-01

    Being able to predict which residents will likely be unsuccessful on high-stakes exams would allow residency programs to provide early intervention. To determine whether measures of clinical performance in clerkship (in-training evaluation reports) and first year of residency (program director ratings) predict pass-fail performance on the Medical Council of Canada Qualifying Exam Part II (MCCQE Part II). Residency program directors assessed the performance of our medical school graduates (Classes 2004-2007) at the end of the 1st postgraduate year. We subsequently collected clerkship in-training evaluation reports for these graduates. Using a neutral third party and unique codes, an anonymous dataset containing clerkship, residency, and MCCQE Part II performance scores was created for our use. Data were analyzed using descriptive statistics, correlations, receiver operating characteristics, and the Youdin index. Regression was also performed to further study the relationship among the variables. Complete data were available for 78.6% of the graduates. Of these participants, 94% passed the licensing exam on their first attempt. Receiver operating characteristics revealed that the area under the curve for clerkship in-training evaluation reports was 0.67 (ptraining evaluation reports and residency program director assessments were 0.30 and 0.23, respectively. Although clerkship in-training evaluation reports and residency program director ratings are significant predictors of pass-fail performance on the MCCQE Part II, the effectiveness of each one to predict pass-fail performance was relatively small. Reasons for these findings are discussed.

  20. 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.

  1. High-Performance Prediction of Human Estrogen Receptor Agonists Based on Chemical Structures

    Directory of Open Access Journals (Sweden)

    Yuki Asako

    2017-04-01

    Full Text Available Many agonists for the estrogen receptor are known to disrupt endocrine functioning. We have developed a computational model that predicts agonists for the estrogen receptor ligand-binding domain in an assay system. Our model was entered into the Tox21 Data Challenge 2014, a computational toxicology competition organized by the National Center for Advancing Translational Sciences. This competition aims to find high-performance predictive models for various adverse-outcome pathways, including the estrogen receptor. Our predictive model, which is based on the random forest method, delivered the best performance in its competition category. In the current study, the predictive performance of the random forest models was improved by strictly adjusting the hyperparameters to avoid overfitting. The random forest models were optimized from 4000 descriptors simultaneously applied to 10,000 activity assay results for the estrogen receptor ligand-binding domain, which have been measured and compiled by Tox21. Owing to the correlation between our model’s and the challenge’s results, we consider that our model currently possesses the highest predictive power on agonist activity of the estrogen receptor ligand-binding domain. Furthermore, analysis of the optimized model revealed some important features of the agonists, such as the number of hydroxyl groups in the molecules.

  2. High-Performance Prediction of Human Estrogen Receptor Agonists Based on Chemical Structures.

    Science.gov (United States)

    Asako, Yuki; Uesawa, Yoshihiro

    2017-04-23

    Many agonists for the estrogen receptor are known to disrupt endocrine functioning. We have developed a computational model that predicts agonists for the estrogen receptor ligand-binding domain in an assay system. Our model was entered into the Tox21 Data Challenge 2014, a computational toxicology competition organized by the National Center for Advancing Translational Sciences. This competition aims to find high-performance predictive models for various adverse-outcome pathways, including the estrogen receptor. Our predictive model, which is based on the random forest method, delivered the best performance in its competition category. In the current study, the predictive performance of the random forest models was improved by strictly adjusting the hyperparameters to avoid overfitting. The random forest models were optimized from 4000 descriptors simultaneously applied to 10,000 activity assay results for the estrogen receptor ligand-binding domain, which have been measured and compiled by Tox21. Owing to the correlation between our model's and the challenge's results, we consider that our model currently possesses the highest predictive power on agonist activity of the estrogen receptor ligand-binding domain. Furthermore, analysis of the optimized model revealed some important features of the agonists, such as the number of hydroxyl groups in the molecules.

  3. 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

  4. 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%.

  5. Shuttle STS-2 mission communication systems RF coverage and performance predictions. Volume 1: Ascent

    Science.gov (United States)

    Porter, J. A.; Gibson, J. S.; Kroll, Q. D.; Loh, Y. C.

    1981-10-01

    The RF communications capabilities and nominally expected performance for the ascent phase of the second orbital flight of the shuttle are provided. Predicted performance is given mainly in the form of plots of signal strength versus elapsed mission time for the STDN (downlink) and shuttle orbiter (uplink) receivers for the S-band PM and FM, and UHF systems. Performance of the NAV and landing RF systems is treated for RTLS abort, since in this case the spacecraft will loop around and return to the launch site. NAV and landing RF systems include TACAN, MSBLS, and C-band altimeter. Signal strength plots were produced by a computer program which combines the spacecraft trajectory, antenna patterns, transmit and receive performance characteristics, and system mathematical models. When available, measured spacecraft parameters were used in the predictions; otherwise, specified values were used. Specified ground station parameter values were also used. Thresholds and other criteria on the graphs are explained.

  6. Pesticide transport to tile-drained fields in SWAT model – macropore flow and sediment

    DEFF Research Database (Denmark)

    Lu, Shenglan; Trolle, Dennis; Blicher-Mathiesen, Gitte

    2015-01-01

    as a fraction of effective rainfall and transported to the tile drains directly. Macropore sediment transport is calculated similarly to the MACRO model (Jarvis et al., 1999). Mobile pesticide transport is calculated with a decay function with the flow, whereas sorbed pesticides transport is associated......Preferential flow and colloidal facilitated transport via macopores connected to tile drains are the main pathways for pesticide transport from agricultural areas to surface waters in some area. We developed a macropore flow module and a sediment transport module for the Soil and Water Assessment...... Tool (SWAT) to simulate transport of both mobile (e.g. Bentazon) and strongly sorbed (e.g. Diuron) pesticides in tile drains. Macropore flow is initiated when soil water content exceeds a threshold and rainfall intensity exceeds infiltration capacity. The amount of macropore flow is calculated...

  7. Heavy metals in agricultural soils and crops and their health risks in Swat District, northern Pakistan.

    Science.gov (United States)

    Khan, Kifayatullah; Lu, Yonglong; Khan, Hizbullah; Ishtiaq, Muhammad; Khan, Sardar; Waqas, Muhammad; Wei, Luo; Wang, Tieyu

    2013-08-01

    This study assessed the concentrations of heavy metals such as cadmium (Cd), chromium (Cr), copper (Cu), manganese (Mn), nickel (Ni) and zinc (Zn) in agricultural soils and crops (fruits, grains and vegetable) and their possible human health risk in Swat District, northern Pakistan. Cd concentration was found higher than the limit (0.05 mg/kg) set by world health organization in 95% fruit and 100% vegetable samples. Moreover, the concentrations of Cr, Cu, Mn, Ni and Zn in the soils were shown significant correlations with those in the crops. The metal transfer factor (MTF) was found highest for Cd followed by Cr>Ni>Zn>Cu>Mn, while the health risk assessment revealed that there was no health risk for most of the heavy metals except Cd, which showed a high level of health risk index (HRI⩾10E-1) that would pose a potential health risk to the consumers. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Assessing ways to combat eutrophication in a Chinese drinking water reservoir using SWAT

    DEFF Research Database (Denmark)

    Nielsen, Anders; Trolle, Dennis; Me, W

    2013-01-01

    Across China, nutrient losses associated with agricultural production and domestic sewage have triggered eutrophication, and local managers are challenged to comply with drinking water quality requirements. Evidently, the improvement of water quality should be targeted holistically and encompass...... both point sources and surface activities within the watershed of a reservoir. We expanded the ordinary Soil Water Assessment Tool – (SWAT) with a widely used empirical equation to estimate total phosphorus (TP) concentrations in lakes and reservoirs. Subsequently, we examined the effects of changes...... in land and livestock management and sewage treatment on nutrient export and derived consequences for water quality in the Chinese subtropical Kaiping (Dashahe) drinking water reservoir (supplying 0.4 million people). The critical load of TP was estimated to 13.5 tonnes yr–1 in order to comply...

  9. Poor Physical Performance Predicts Future Onset of Depression in Elderly People: Progetto Veneto Anziani Longitudinal Study.

    Science.gov (United States)

    Veronese, Nicola; Stubbs, Brendon; Trevisan, Caterina; Bolzetta, Francesco; De Rui, Marina; Solmi, Marco; Sartori, Leonardo; Musacchio, Estella; Zambon, Sabina; Perissinotto, Egle; Baggio, Giovannella; Crepaldi, Gaetano; Manzato, Enzo; Maggi, Stefania; Sergi, Guiseppe

    2017-06-01

    Reduced physical performance is predictive of deleterious outcomes in older adults. Data considering objective physical performance and incident depression are sparse. The objective of this study was to investigate during a 4-year study whether objective physical performance can predict incident depression among older adults who do not have depression at the baseline. This was a longitudinal study. From 3,099 older people initially enrolled in the Progetto Veneto Anziani study, 970 participants without depression at the baseline were included (mean age = 72.5 years; 54.6% women). Physical performance measures included the Short Physical Performance Battery, 4-m gait speed, Five-Times Sit-to-Stand test, leg extension and flexion, handgrip strength, and 6-minute walk test, categorized in sex-specific tertiles. Depression was classified on the basis of the Geriatric Depression Scale and a diagnosis from a geriatric psychiatrist. Area under the curve and logistic regression analyses were conducted. At the baseline, participants developing depression during the follow-up (n = 207) scored significantly worse across all physical performance measures than those who did not develop depression. The area under the curve and predictive power were similar for all of the physical performance tests assessed. In the logistic regression analysis, after adjustment for 14 potential confounders, worse physical performance across all tests increased the risk of depression. Participants in the lowest tertile of the Short Physical Performance Battery were at notable odds of developing depression (odds ratio = 1.79; 95% CI = 1.18-2.71). The association between poor physical performance and depression was typically stronger in women than in men, except for 4-m gait speed. No gold standard was used for a depression diagnosis; oxidative stress and inflammatory markers were not included; and there was a high rate of missing data at the follow-up. Low physical performance appeared to be an

  10. Prediction of 6-minute walk performance in patients with peripheral artery disease.

    Science.gov (United States)

    Chen, Xi; Stoner, Julie A; Montgomery, Polly S; Casanegra, Ana I; Silva-Palacios, Federico; Chen, Sixia; Janitz, Amanda E; Gardner, Andrew W

    2017-10-01

    Peripheral artery disease (PAD) is a highly prevalent disease that impairs walking ability. Walking tests, such as the 6-minute walk test (6MWT) and 4-meter walk test, are commonly used to assess exercise endurance and ambulatory function over a short distance, respectively. The 6MWT performance is predictive of PAD severity and disease outcomes, but it is not feasible in many clinical settings because it requires a long walkway to serve as the test route and lengthens clinic visits. As an alternative, the 4-meter walk test is convenient, inexpensive, and repeatable, but whether it accurately predicts endurance performance in the long-distance 6MWT is not known. The goal of this study was to develop a statistical model to predict 6MWT gait speed from 4-meter walk test results and clinical characteristics among patients with PAD. Measures of 6MWT gait speed were derived from 183 patients with symptomatic PAD who were evaluated at the University of Oklahoma Health Sciences Center (2004-2012). The testing procedures and research personnel remained constant throughout the duration of the study. Independent variables included demographic and clinical information and 4-meter walk test gait speed. Fivefold cross validation and manual backward selection were used for model selection. Adjusted R 2 and corrected Akaike information criterion were applied to quantify the predictive performance of the regression models. A total of 183 people (54% male; mean age, 65 [standard deviation (SD), 10] years) with moderate PAD severity (ankle-brachial index [ABI]; mean, 0.72 [SD, 0.24]) performed the walking tests. Participants covered an average distance of 335 (SD, 97) m distance in the 6MWT. The 4-meter walk gait speed, ABI, and dyspnea were independent predictors of 6MWT speed in the multivariate model (adjusted R 2  = 0.55). The model resulted in 95% prediction interval widths of 30 m for mean and 260 m for individual predicted 6MWT distance measures. Slower 4-meter walking

  11. Prediction of maize single-cross performance by mixed linear models with microsatellite marker information.

    Science.gov (United States)

    Balestre, M; Von Pinho, R G; Souza, J C

    2010-06-11

    We evaluated the potential of the best linear unbiased predictor (BLUP) along with the relationship coefficient for predicting the performance of untested maize single-cross hybrids. Ninety S(0:2) progenies arising from three single-cross hybrids were used. The 90 progenies were genotyped with 25 microsatellite markers, with nine markers linked to quantitative trait loci for grain yield. Based on genetic similarities, 17 partial inbred lines were selected and crossed in a partial diallel design. Similarity and relationship coefficients were used to construct the additive and dominance genetic matrices; along with BLUP, they provided predictions for untested single-crosses. Five degrees of imbalance were simulated (5, 10, 20, 30, and 40 hybrids). The correlation values between the predicted genotypic values and the observed phenotypic means varied from 0.55 to 0.70, depending on the degree of imbalance. A similar result was observed for the specific combining ability predictions; they varied from 0.61 to 0.70. It was also found that the relationship coefficient based on BLUP provided more accurate predictions than similarity-in-state predictions. We conclude that BLUP methodology is a viable alternative for the prediction of untested crosses in early progenies.

  12. CFD Predictions for Transonic Performance of the ERA Hybrid Wing-Body Configuration

    Science.gov (United States)

    Deere, Karen A.; Luckring, James M.; McMillin, S. Naomi; Flamm, Jeffrey D.; Roman, Dino

    2016-01-01

    A computational study was performed for a Hybrid Wing Body configuration that was focused at transonic cruise performance conditions. In the absence of experimental data, two fully independent computational fluid dynamics analyses were conducted to add confidence to the estimated transonic performance predictions. The primary analysis was performed by Boeing with the structured overset-mesh code OVERFLOW. The secondary analysis was performed by NASA Langley Research Center with the unstructured-mesh code USM3D. Both analyses were performed at full-scale flight conditions and included three configurations customary to drag buildup and interference analysis: a powered complete configuration, the configuration with the nacelle/pylon removed, and the powered nacelle in isolation. The results in this paper are focused primarily on transonic performance up to cruise and through drag rise. Comparisons between the CFD results were very good despite some minor geometric differences in the two analyses.

  13. 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.

  14. Calibration of SWAT model for woody plant encroachment using paired experimental watershed data

    Science.gov (United States)

    Qiao, Lei; Zou, Chris B.; Will, Rodney E.; Stebler, Elaine

    2015-04-01

    Globally, rangeland has been undergoing a transition from herbaceous dominated grasslands into tree or shrub dominated woodlands with great uncertainty of associated changes in water budget. Previous modeling studies simulated the impact of woody plant encroachment on hydrological processes using models calibrated and constrained primarily by historic streamflow from intermediate sized watersheds. In this study, we calibrated the Soil and Water Assessment Tool (SWAT model), a widely used model for cropping and grazing systems, for a prolifically encroaching juniper species, eastern redcedar (Juniperus virginiana), in the south-central Great Plains using species-specific biophysical and hydrological parameters and in situ meteorological forcing from three pairs of experimental watersheds (grassland versus eastern redcedar woodland) for a period of 3-years covering a dry-to-wet cycle. The multiple paired watersheds eliminated the potentially confounding edaphic and topographic influences from changes in hydrological processes related to woody encroachment. The SWAT model was optimized with the Shuffled complexes with Principal component analysis (SP-UCI) algorithm developed from the Shuffled Complexes Evolution (SCE_UA). The mean Nash-Sutcliff coefficient (NSCE) values of the calibrated model for daily and monthly runoff from experimental watersheds reached 0.96 and 0.97 for grassland, respectively, and 0.90 and 0.84 for eastern redcedar woodland, respectively. We then validated the calibrated model with a nearby, larger watershed undergoing rapid eastern redcedar encroachment. The NSCE value for monthly streamflow over a period of 22 years was 0.79. We provide detailed biophysical and hydrological parameters for tallgrass prairie under moderate grazing and eastern redcedar, which can be used to calibrate any model for further validation and application by the hydrologic modeling community.

  15. Assessment of Flood Frequency Alteration by Dam Construction via SWAT Simulation

    Directory of Open Access Journals (Sweden)

    Jeong Eun Lee

    2017-04-01

    Full Text Available The purpose of this study is to evaluate the impacts of the upstream Soyanggang and Chungju multi-purpose dams on the frequency of downstream floods in the Han River basin, South Korea. A continuous hydrological model, SWAT (Soil and Water Assessment Tool, was used to individually simulate regulated and unregulated daily streamflows entering the Paldang Dam, which is located at the outlet of the basin of interest. The simulation of the regulated flows by the Soyanggang and Chungju dams was calibrated with observed inflow data to the Paldang Dam. The estimated daily flood peaks were used for a frequency analysis, using the extreme Type-I distribution, for which the parameters were estimated via the L-moment method. This novel approach was applied to the study area to assess the effects of the dams on downstream floods. From the results, the two upstream dams were found to be able to reduce downstream floods by approximately 31% compared to naturally occurring floods without dam regulation. Furthermore, an approach to estimate the flood frequency based on the hourly extreme peak flow data, obtained by combining SWAT simulation and Sangal’s method, was proposed and then verified by comparison with the observation-based results. The increased percentage of floods estimated with hourly simulated data for the three scenarios of dam regulation ranged from 16.1% to 44.1%. The reduced percentages were a little higher than those for the daily-based flood frequency estimates. The developed approach allowed for better understanding of flood frequency, as influenced by dam regulation on a relatively large watershed scale.

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

    Energy Technology Data Exchange (ETDEWEB)

    Lawless, M.T.; Laughery, K.R. [Micro Analysis and Design, Inc., Boulder, CO (United States); Persenky, J.J. [Nuclear Regulatory Commission, Washington, DC (United States)

    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 procedures{close_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 conditions{close_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.

  17. 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.

  18. 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

  19. Passing a Technical Skills Examination in the First Year of Surgical Residency Can Predict Future Performance.

    Science.gov (United States)

    de Montbrun, Sandra; Louridas, Marisa; Grantcharov, Teodor

    2017-06-01

    The ability of an assessment to predict performance would be of major benefit to residency programs, allowing for early identification of residents at risk. We sought to establish whether passing the Objective Structured Assessment of Technical Skills (OSATS) examination in postgraduate year 1 (PGY-1) predicts future performance. Between 2002 and 2012, 133 PGY-1 surgery residents at the University of Toronto (Toronto, Ontario, Canada) completed an 8-station, simulated OSATS examination as a component of training. With recently set passing scores, residents were assigned a pass/fail status using 3 standards setting methods (contrasting groups, borderline group, and borderline regression). Future in-training performance was compared between residents who had passed and those who failed the OSATS, using in-training evaluation reports from resident files. A Mann-Whitney U test compared performance among groups at PGY-2 and PGY-4 levels. Residents who passed the OSATS examination outperformed those who failed, when compared during PGY-2 across all 3 standard setting methodologies (P technical skills examination was associated with future performance on in-training evaluation reports in later years. This provides validity evidence for the current PGY-1 pass/fail score, and suggests that this technical skills examination may be used to predict performance and to identify residents who require remediation.

  20. The Validity of Selection and Classification Procedures for Predicting Job Performance.

    Science.gov (United States)

    1987-04-01

    direct lineal descendant of the Army Alpha of 1917, the services are now more active than ever before in seeking improvements in the Battery. Several...regression equationa An algebraic equation used to predict criterion performance from predictor scores. relevancea The extent to which a criterion measure

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

    CSIR Research Space (South Africa)

    Berman, Robert J

    2016-11-01

    Full Text Available combinations. The model considers vehicle geometry, suspension parameters and payload properties as variable inputs and is able to predict the high-speed PBS performance with an average error of less than 1% for four of the five standards and less than 5...

  2. 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.

  3. Predictive Modeling of Student Performances for Retention and Academic Support in a Diagnostic Medical Sonography Program

    Science.gov (United States)

    Borghese, Peter; Lacey, Sandi

    2014-01-01

    As part of a retention and academic support program, data was collected to develop a predictive model of student performances in core classes in a Diagnostic Medical Sonography (DMS) program. The research goal was to identify students likely to have difficulty with coursework and provide supplemental tutorial support. The focus was on the…

  4. Thermoelectrically cooled cloud physics expansion chamber. [systems engineering and performance prediction

    Science.gov (United States)

    Buist, R. J.

    1977-01-01

    The design and fabrication of a thermoelectric chiller for use in chilling a liquid reservoir is described. Acceptance test results establish the accuracy of the thermal model and predict the unit performance under various conditions required by the overall spacelab program.

  5. 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…

  6. 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.

  7. 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…

  8. 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 =…

  9. Somatic Complaints in Children with Anxiety Disorders and Their Unique Prediction of Poorer Academic Performance

    Science.gov (United States)

    Hughes, Alicia A.; Lourea-Waddell, Brittany; Kendall, Philip C.

    2008-01-01

    The present study aimed to examine somatic complaints in children with anxiety disorders compared to non-anxious control children and whether somatic complaints predict poorer academic performance. The sample consisted of 108 children and adolescents (aged 8-14 years) assessed by a structured diagnostic interview: 69 with a principal (i.e., most…

  10. Beyond the "High-Tech" Suits: Predicting 2012 Olympic Swim Performances

    Science.gov (United States)

    Brammer, Chris L.; Stager, Joel M.; Tanner, Dave A.

    2012-01-01

    The purpose of the authors in this study was to predict the mean swim time of the top eight swimmers in swim events at the 2012 Olympic Games based upon prior Olympic performances from 1972 through 2008. Using the mean top eight time across all years, a best fit power curve [time = a x year[superscript b

  11. 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…

  12. Model predictive control as a tool for improving the process operation performance of MSW combustion plants

    NARCIS (Netherlands)

    Leskens, M.; Kessel, L.B.M. van; Bosgra, O.H.

    2003-01-01

    In this paper a feasibility study is presented on the application of the advanced control strategy called model predictive control (MPC) as a tool for obtaining an improved operation performance for municipal solid waste (MSW) combustion plants. The paper starts with a motivation for applying MPC to

  13. Biological lifestyle factors in adult distance education: Predicting cognitive and learning performance

    NARCIS (Netherlands)

    Gijselaers, Jérôme

    2017-01-01

    The aim of this dissertation was to explore the characteristics of different student groups (i.e., successful, non-successful, and non-starting). The second aim was to examine whether biological lifestyle factors (e.g. physical activity, sleep, and nutrition) predicted learning performance. Third,

  14. Selfish-LRU: Preemption-Aware Caching for Predictability and Performance

    NARCIS (Netherlands)

    Reineke, J.; Altmeyer, S.; Grund, D.; Hahn, S.; Maiza, C.

    2014-01-01

    We introduce Selfish-LRU, a variant of the LRU (least recently used) cache replacement policy that improves performance and predictability in preemptive scheduling scenarios. In multitasking systems with conventional caches, a single memory access by a preempting task can trigger a chain reaction

  15. The Development of MST Test Information for the Prediction of Test Performances

    Science.gov (United States)

    Park, Ryoungsun; Kim, Jiseon; Chung, Hyewon; Dodd, Barbara G.

    2017-01-01

    The current study proposes novel methods to predict multistage testing (MST) performance without conducting simulations. This method, called MST test information, is based on analytic derivation of standard errors of ability estimates across theta levels. We compared standard errors derived analytically to the simulation results to demonstrate the…

  16. 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

  17. Predictive performance of eleven pharmacokinetic models for propofol infusion in children for long-duration anaesthesia

    NARCIS (Netherlands)

    Hara, M.; Masui, K.; Eleveld, D. J.; Struys, M. M. R. F.; Uchida, O.

    Background. Predictive performance of eleven published propofol pharmacokinetic models was evaluated for long-duration propofol infusion in children. Methods. Twenty-one aged three-11 yr ASA I-II patients were included. Anaesthesia was induced with propofol or sevoflurane, and maintained with

  18. A multidimensional approach to performance prediction in Olympic distance cross-country mountain bikers.

    Science.gov (United States)

    Novak, Andrew R; Bennett, Kyle J M; Fransen, Job; Dascombe, Ben J

    2018-01-01

    This study adopted a multidimensional approach to performance prediction within Olympic distance cross-country mountain biking (XCO-MTB). Twelve competitive XCO-MTB cyclists (VO2max 60.8 ± 6.7 ml · kg-1 · min-1) completed an incremental cycling test, maximal hand grip strength test, cycling power profile (maximal efforts lasting 6-600 s), decision-making test and an individual XCO-MTB time-trial (34.25 km). A hierarchical approach using multiple linear regression analyses was used to develop predictive models of performance across 10 circuit subsections and the total time-trial. The strongest model to predict overall time-trial performance achieved prediction accuracy of 127.1 s across 6246.8 ± 452.0 s (adjusted R2 = 0.92; P < 0.01). This model included VO2max relative to total cycling mass, maximal mean power across 5 and 30 s, peak left hand grip strength, and response time for correct decisions in the decision-making task. A range of factors contributed to the models for each individual subsection of the circuit with varying predictive strength (adjusted R2: 0.62-0.97; P < 0.05). The high prediction accuracy for the total time-trial supports that a multidimensional approach should be taken to develop XCO-MTB performance. Additionally, individual models for circuit subsections may help guide training practices relative to the specific trail characteristics of various XCO-MTB circuits.

  19. 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…

  20. 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.

  1. Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth.

    Science.gov (United States)

    Valindria, Vanya V; Lavdas, Ioannis; Bai, Wenjia; Kamnitsas, Konstantinos; Aboagye, Eric O; Rockall, Andrea G; Rueckert, Daniel; Glocker, Ben

    2017-08-01

    When integrating computational tools, such as automatic segmentation, into clinical practice, it is of utmost importance to be able to assess the level of accuracy on new data and, in particular, to detect when an automatic method fails. However, this is difficult to achieve due to the absence of ground truth. Segmentation accuracy on clinical data might be different from what is found through cross validation, because validation data are often used during incremental method development, which can lead to overfitting and unrealistic performance expectations. Before deployment, performance is quantified using different metrics, for which the predicted segmentation is compared with a reference segmentation, often obtained manually by an expert. But little is known about the real performance after deployment when a reference is unavailable. In this paper, we introduce the concept of reverse classification accuracy (RCA) as a framework for predicting the performance of a segmentation method on new data. In RCA, we take the predicted segmentation from a new image to train a reverse classifier, which is evaluated on a set of reference images with available ground truth. The hypothesis is that if the predicted segmentation is of good quality, then the reverse classifier will perform well on at least some of the reference images. We validate our approach on multi-organ segmentation with different classifiers and segmentation methods. Our results indicate that it is indeed possible to predict the quality of individual segmentations, in the absence of ground truth. Thus, RCA is ideal for integration into automatic processing pipelines in clinical routine and as a part of large-scale image analysis studies.

  2. Off-Ice Anaerobic Power Does Not Predict On-Ice Repeated Shift Performance in Hockey.

    Science.gov (United States)

    Peterson, Ben J; Fitzgerald, John S; Dietz, Calvin C; Ziegler, Kevin S; Baker, Sarah E; Snyder, Eric M

    2016-09-01

    Peterson, BJ, Fitzgerald, JS, Dietz, CC, Ziegler, KS, Baker, SE, and Snyder, EM. Off-ice anaerobic power does not predict on-ice repeated shift performance in hockey. J Strength Cond Res 30(9): 2375-2381, 2016-Anaerobic power is a significant predictor of acceleration and top speed in team sport athletes. Historically, these findings have been applied to ice hockey although recent research has brought their validity for this sport into question. As ice hockey emphasizes the ability to repeatedly produce power, single bout anaerobic power tests should be examined to determine their ability to predict on-ice performance. We tested whether conventional off-ice anaerobic power tests could predict on-ice acceleration, top speed, and repeated shift performance. Forty-five hockey players, aged 18-24 years, completed anthropometric, off-ice, and on-ice tests. Anthropometric and off-ice testing included height, weight, body composition, vertical jump, and Wingate tests. On-ice testing consisted of acceleration, top speed, and repeated shift fatigue tests. Vertical jump (VJ) (r = -0.42; r = -0.58), Wingate relative peak power (WRPP) (r = -0.32; r = -0.43), and relative mean power (WRMP) (r = -0.34; r = -0.48) were significantly correlated (p ≤ 0.05) to on-ice acceleration and top speed, respectively. Conversely, none of the off-ice tests correlated with on-ice repeated shift performance, as measured by first gate, second gate, or total course fatigue; VJ (r = 0.06; r = 0.13; r = 0.09), WRPP (r = 0.06; r = 0.14; r = 0.10), or WRMP (r = -0.10; r = -0.01; r = -0.01). Although conventional off-ice anaerobic power tests predict single bout on-ice acceleration and top speed, they neither predict the repeated shift ability of the player, nor are good markers for performance in ice hockey.

  3. Universality, limits and predictability of gold-medal performances at the olympic games.

    Directory of Open Access Journals (Sweden)

    Filippo Radicchi

    Full Text Available Inspired by the Games held in ancient Greece, modern Olympics represent the world's largest pageant of athletic skill and competitive spirit. Performances of athletes at the Olympic Games mirror, since 1896, human potentialities in sports, and thus provide an optimal source of information for studying the evolution of sport achievements and predicting the limits that athletes can reach. Unfortunately, the models introduced so far for the description of athlete performances at the Olympics are either sophisticated or unrealistic, and more importantly, do not provide a unified theory for sport performances. Here, we address this issue by showing that relative performance improvements of medal winners at the Olympics are normally distributed, implying that the evolution of performance values can be described in good approximation as an exponential approach to an a priori unknown limiting performance value. This law holds for all specialties in athletics-including running, jumping, and throwing-and swimming. We present a self-consistent method, based on normality hypothesis testing, able to predict limiting performance values in all specialties. We further quantify the most likely years in which athletes will breach challenging performance walls in running, jumping, throwing, and swimming events, as well as the probability that new world records will be established at the next edition of the Olympic Games.

  4. 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.

  5. Universality, limits and predictability of winners' performances at the Olympic Games

    CERN Document Server

    Radicchi, Filippo

    2012-01-01

    Inspired by the legendary Games held in ancient Greece, modern Olympics represent the world's largest pageant of athletic skill and competitive spirit. Athletes' performances at the Olympic Games mirror, since more than a century, human potentialities in sports, and thus provide an optimal source of information for studying the evolution of sport achievements and predicting the limits that athletes can reach. Unfortunately, the models introduced so far for the description of athletes' performances are either sophisticated or unrealistic, and more importantly, do not provide a unified theory for sport performances. Here, we address this issue by showing that relative performance improvements of medal winners at the Olympics are normally distributed, implying that the evolution of performance values can be simply described as an exponential approach to an a priori unknown limiting performance value. This law holds for all specialties in athletics - including running, jumping and throwing - and swimming. We pres...

  6. Progress and prediction of occupational performance in women with distal radius fractures

    DEFF Research Database (Denmark)

    Nielsen, Tove Lise; Dekkers, Merete Klindt

    2013-01-01

    , a number of ‡10 performance problems at 12 months could be predicted in women with ‡20 performance problems (RR 2.41) or with a pain intensity described as “moderate” or worse (RR 3.71). The findings of this study suggest that occupational therapy services might still be of relevance perhaps as follow......To describe the occupational performance and pain during the first year after a distal radius fracture, an observational follow-up study was performed among 37 mainly elderly Danish women. They were assessed at cast removal and reassessed at three and 12 months post-injury with COPM, DASH...... in occupational performance and disability took place within the first three months. Pain decreased significantly during the follow-up period. In spite of these positive results, at 12 months 78% of the women still had performance problems and 62% still had some degree of pain due to the fracture. At cast removal...

  7. 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

  8. How obstacles and facilitators predict academic performance: the mediating role of study burnout and engagement.

    Science.gov (United States)

    Salanova, Marisa; Schaufeli, Wilmar; Martinez, Isabel; Breso, Edgar

    2010-01-01

    Most people would agree with the maxim that "success breeds success." However, this is not the whole story. The current study investigated the additional impact of psychosocial factors (i.e., performance obstacles and facilitators) as well as psychological well-being (i.e., burnout and engagement) on success (i.e., academic performance). More specifically, our purpose was to show that, instead of directly affecting future performance, obstacles and facilitators exert an indirect effect via well-being. A total of 527 university students comprised the sample and filled out a questionnaire. We obtained their previous and future academic performance Grade Point Average (GPA) from the university's records. Structural equations modeling showed that the best predictor of future performance was the students' previous performance. As expected, study engagement mediated the relationship between performance obstacles and facilitators on the one hand, and future performance on the other. Contrary to expectations, burnout did not predict future performance, although, it is significantly associated with the presence of obstacles and the absence of facilitators. Our results illustrate that, although "success breeds success" (i.e., the best predictor of future performance is past performance), positive psychological states like study engagement are also important in explaining future performance, at least more so than negative states like study burnout.

  9. Static and Dynamic Measures of Human Brain Connectivity Predict Complementary Aspects of Human Cognitive Performance

    Directory of Open Access Journals (Sweden)

    Aurora I. Ramos-Nuñez

    2017-08-01

    Full Text Available In cognitive network neuroscience, the connectivity and community structure of the brain network is related to measures of cognitive performance, like attention and memory. Research in this emerging discipline has largely focused on two measures of connectivity—modularity and flexibility—which, for the most part, have been examined in isolation. The current project investigates the relationship between these two measures of connectivity and how they make separable contribution to predicting individual differences in performance on cognitive tasks. Using resting state fMRI data from 52 young adults, we show that flexibility and modularity are highly negatively correlated. We use a Brodmann parcellation of the fMRI data and a sliding window approach for calculation of the flexibility. We also demonstrate that flexibility and modularity make unique contributions to explain task performance, with a clear result showing that modularity, not flexibility, predicts performance for simple tasks and that flexibility plays a greater role in predicting performance on complex tasks that require cognitive control and executive functioning. The theory and results presented here allow for stronger links between measures of brain network connectivity and cognitive processes.

  10. Static and Dynamic Measures of Human Brain Connectivity Predict Complementary Aspects of Human Cognitive Performance

    Science.gov (United States)

    Ramos-Nuñez, Aurora I.; Fischer-Baum, Simon; Martin, Randi C.; Yue, Qiuhai; Ye, Fengdan; Deem, Michael W.

    2017-01-01

    In cognitive network neuroscience, the connectivity and community structure of the brain network is related to measures of cognitive performance, like attention and memory. Research in this emerging discipline has largely focused on two measures of connectivity—modularity and flexibility—which, for the most part, have been examined in isolation. The current project investigates the relationship between these two measures of connectivity and how they make separable contribution to predicting individual differences in performance on cognitive tasks. Using resting state fMRI data from 52 young adults, we show that flexibility and modularity are highly negatively correlated. We use a Brodmann parcellation of the fMRI data and a sliding window approach for calculation of the flexibility. We also demonstrate that flexibility and modularity make unique contributions to explain task performance, with a clear result showing that modularity, not flexibility, predicts performance for simple tasks and that flexibility plays a greater role in predicting performance on complex tasks that require cognitive control and executive functioning. The theory and results presented here allow for stronger links between measures of brain network connectivity and cognitive processes. PMID:28883789

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

    Energy Technology Data Exchange (ETDEWEB)

    Lye, T.C.; Creasey, H.; Kril, J.J. [University of Sydney and Concord Hospital, Centre for Education and Research on Ageing, Sydney, New South Wales (Australia); Grayson, D.A. [University of Sydney, School of Psychology, Sydney (Australia); Piguet, O. [University of Sydney and Concord Hospital, Centre for Education and Research on Ageing, Sydney, New South Wales (Australia); Prince of Wales Medical Research Institute and the University of New South Wales, Sydney (Australia); Bennett, H.P. [Prince of Wales Medical Research Institute and the University of New South Wales, Sydney (Australia); Ridley, L.J. [Concord Hospital, Department of Radiology, Sydney (Australia); Broe, G.A. [Prince of Wales Medical Research Institute and the University of New South Wales, Sydney (Australia); Prince of Wales Hospital, Sydney (Australia)

    2006-02-15

    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.)

  12. Brain activity during a visuospatial working memory task predicts arithmetical performance 2 years later.

    Science.gov (United States)

    Dumontheil, Iroise; Klingberg, Torkel

    2012-05-01

    Visuospatial working memory (WM) capacity is highly correlated with mathematical reasoning abilities and can predict future development of arithmetical performance. Activity in the intraparietal sulcus (IPS) during visuospatial WM tasks correlates with interindividual differences in WM capacity. This region has also been implicated in numerical representation, and its structure and activity reflect arithmetical performance impairments (e.g., dyscalculia). We collected behavioral (N = 246) and neuroimaging data (N = 46) in a longitudinal sample to test whether IPS activity during a visuospatial WM task could provide more information than psychological testing alone and predict arithmetical performance 2 years later in healthy participants aged 6-16 years. Nonverbal reasoning and verbal and visuospatial WM measures were found to be independent predictors of arithmetical outcome. In addition, WM activation in the left IPS predicted arithmetical outcome independently of behavioral measures. A logistic model including both behavioral and imaging data showed improved sensitivity by correctly classifying more than twice as many children as poor arithmetical performers after 2 years than a model with behavioral measures only. These results demonstrate that neuroimaging data can provide useful information in addition to behavioral assessments and be used to improve the identification of individuals at risk of future low academic performance.

  13. A Systematic Review of Submaximal Cycle Tests to Predict, Monitor, and Optimize Cycling Performance.

    Science.gov (United States)

    Capostagno, Benoit; Lambert, Michael I; Lamberts, Robert P

    2016-09-01

    Finding the optimal balance between high training loads and recovery is a constant challenge for cyclists and their coaches. Monitoring improvements in performance and levels of fatigue is recommended to correctly adjust training to ensure optimal adaptation. However, many performance tests require a maximal or exhaustive effort, which reduces their real-world application. The purpose of this review was to investigate the development and use of submaximal cycling tests that can be used to predict and monitor cycling performance and training status. Twelve studies met the inclusion criteria, and 3 separate submaximal cycling tests were identified from within those 12. Submaximal variables including gross mechanical efficiency, oxygen uptake (VO2), heart rate, lactate, predicted time to exhaustion (pTE), rating of perceived exertion (RPE), power output, and heart-rate recovery (HRR) were the components of the 3 tests. pTE, submaximal power output, RPE, and HRR appear to have the most value for monitoring improvements in performance and indicate a state of fatigue. This literature review shows that several submaximal cycle tests have been developed over the last decade with the aim to predict, monitor, and optimize cycling performance. To be able to conduct a submaximal test on a regular basis, the test needs to be short in duration and as noninvasive as possible. In addition, a test should capture multiple variables and use multivariate analyses to interpret the submaximal outcomes correctly and alter training prescription if needed.

  14. Localization in reverberation with cochlear implants: predicting performance from basic psychophysical measures.

    Science.gov (United States)

    Kerber, Stefan; Seeber, Bernhard U

    2013-06-01

    Users of bilateral cochlear implants (CIs) experience difficulties localizing sounds in reverberant rooms, even in rooms where normal-hearing listeners would hardly notice the reverberation. We measured the localization ability of seven bilateral CI users listening with their own devices in anechoic space and in a simulated reverberant room. To determine factors affecting performance in reverberant space we measured the sensitivity to interaural time differences (ITDs), interaural level differences (ILDs), and forward masking in the same participants using direct computer control of the electric stimulation in their CIs. Localization performance, quantified by the coefficient of determination r(2) and the root mean squared error, was significantly worse in the reverberant room than in anechoic conditions. Localization performance in the anechoic room, expressed as r(2), was best predicted by subject's sensitivity to ILDs. However, the decrease in localization performance caused by reverberation was better predicted by the sensitivity to envelope ITDs measured on single electrode pairs, with a correlation coefficient of 0.92. The CI users who were highly sensitive to envelope ITDs also better maintained their localization ability in reverberant space. Results in the forward masking task added only marginally to the predictions of localization performance in both environments. The results indicate that envelope ITDs provided by CI processors support localization in reverberant space. Thus, methods that improve perceptual access to envelope ITDs could help improve localization with bilateral CIs in everyday listening situations.

  15. Prediction of the Styrene Butadiene Rubber Performance by Emulsion Polymerization Using Backpropagation Neural Network

    Directory of Open Access Journals (Sweden)

    Yan-jiang Jin

    2013-01-01

    Full Text Available The effect of the amounts of initiator, emulsifier, and molecular weight regulator on the styrene butadiene rubber performance was investigated, based on the industrial original formula. It was found that the polymerization rate was increased with the increased dosage of initiator and emulsifier, and together with replenishing molecular weight regulator will make the Mooney viscosity of rubber meet the national standard when the conversion rate reaches 70%. The backpropagation neural network was trained by the original formula and ameliorated formula on the basis of Levenberg-Marquardt algorithm, and the relative error between the simulation results and experimental data is less than 1%. The good consistency shows that the BP neural network could predict the product performances in different formula conditions. It would pave the way for adjustment of the SBR formulation and prediction of the product performances.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. The performance of immune-based neural network with financial time series prediction

    Directory of Open Access Journals (Sweden)

    Dhiya Al-Jumeily

    2015-12-01

    Full Text Available This paper presents the use of immune-based neural networks that include multilayer perceptron (MLP and functional neural network for the prediction of financial time series signals. Extensive simulations for the prediction of one- and five-steps-ahead of stationary and non-stationary time series were performed which indicate that immune-based neural networks in most cases demonstrated advantages in capturing chaotic movement in the financial signals with an improvement in the profit return and rapid convergence over MLPs.

  1. 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.

  2. 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.

  3. 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.

  4. Application of regression and neural models to predict competitive swimming performance.

    Science.gov (United States)

    Maszczyk, Adam; Roczniok, Robert; Waśkiewicz, Zbigniew; Czuba, Miłosz; Mikołajec, Kazimierz; Zajac, Adam; Stanula, Arkadiusz

    2012-04-01

    This research problem was indirectly but closely connected with the optimization of an athlete-selection process, based on predictions viewed as determinants of future successes. The research project involved a group of 249 competitive swimmers (age 12 yr., SD = 0.5) who trained and competed for four years. Measures involving fitness (e.g., lung capacity), strength (e.g., standing long jump), swimming technique (turn, glide, distance per stroke cycle), anthropometric variables (e.g., hand and foot size), as well as specific swimming measures (speeds in particular distances), were used. The participants (n = 189) trained from May 2008 to May 2009, which involved five days of swimming workouts per week, and three additional 45-min. sessions devoted to measurements necessary for this study. In June 2009, data from two groups of 30 swimmers each (n = 60) were used to identify predictor variables. Models were then constructed from these variables to predict final swimming performance in the 50 meter and 800 meter crawl events. Nonlinear regression models and neural models were built for the dependent variable of sport results (performance at 50m and 800m). In May 2010, the swimmers' actual race times for these events were compared to the predictions created a year prior to the beginning of the experiment. Results for the nonlinear regression models and perceptron networks structured as 8-4-1 and 4-3-1 indicated that the neural models overall more accurately predicted final swimming performance from initial training, strength, fitness, and body measurements. Differences in the sum of absolute error values were 4:11.96 (n = 30 for 800m) and 20.39 (n = 30 for 50m), for models structured as 8-4-1 and 4-3-1, respectively, with the neural models being more accurate. It seems possible that such models can be used to predict future performance, as well as in the process of recruiting athletes for specific styles and distances in swimming.

  5. 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.

  6. An Anatomy Pre-Course Predicts Student Performance in a Professional Veterinary Anatomy Curriculum.

    Science.gov (United States)

    McNulty, Margaret A; Lazarus, Michelle D

    2018-01-18

    Little to no correlation has been identified between previous related undergraduate coursework or outcomes on standardized tests and performance in a veterinary curriculum, including anatomy coursework. Therefore, a relatively simplistic method to predict student performance before entrance would be advantageous to many. The purpose of this study was to evaluate whether there is a correlation between performance in a veterinary anatomy pre-course and subsequent performance within a professional anatomy curriculum. Incoming first-year veterinary students at the Louisiana State University School of Veterinary Medicine were asked to participate in a free weeklong pre-course, before the start of the semester. The pre-course covered the musculoskeletal anatomy of the canine thoracic limb using dissection-based methods. Student performance, as evaluated by test grades in the pre-course, did indeed correlate with test grades in professional veterinary anatomy courses. A significant and positive correlation was identified between pre-course final exam performance and performance on examinations in each of 3 professional anatomy courses. Qualitative analyses of student comments pertaining to their experience within the pre-course indicated differences in the perceived benefits of the pre-course between high-, middle-, and low-performing students. These varied perceptions may provide predictive feedback as well as guidance for supporting lower performing students. Together, these results indicate that performance in a weeklong pre-course covering only a small portion of canine anatomy is a strong predictor of performance within a professional anatomy curriculum. In addition, the pre-course differentially affected student perceptions of their learning experience.

  7. Predictive validity of the UKCAT for medical school undergraduate performance: a national prospective cohort study.

    Science.gov (United States)

    Tiffin, Paul A; Mwandigha, Lazaro M; Paton, Lewis W; Hesselgreaves, H; McLachlan, John C; Finn, Gabrielle M; Kasim, Adetayo S

    2016-09-26

    The UK Clinical Aptitude Test (UKCAT) has been shown to have a modest but statistically significant ability to predict aspects of academic performance throughout medical school. Previously, this ability has been shown to be incremental to conventional measures of educational performance for the first year of medical school. This study evaluates whether this predictive ability extends throughout the whole of undergraduate medical study and explores the potential impact of using the test as a selection screening tool. This was an observational prospective study, linking UKCAT scores, prior educational attainment and sociodemographic variables with subsequent academic outcomes during the 5 years of UK medical undergraduate training. The participants were 6812 entrants to UK medical schools in 2007-8 using the UKCAT. The main outcome was academic performance at each year of medical school. A receiver operating characteristic (ROC) curve analysis was also conducted, treating the UKCAT as a screening test for a negative academic outcome (failing at least 1 year at first attempt). All four of the UKCAT scale scores significantly predicted performance in theory- and skills-based exams. After adjustment for prior educational achievement, the UKCAT scale scores remained significantly predictive for most years. Findings from the ROC analysis suggested that, if used as a sole screening test, with the mean applicant UKCAT score as the cut-off, the test could be used to reject candidates at high risk of failing at least 1 year at first attempt. However, the 'number needed to reject' value would be high (at 1.18), with roughly one candidate who would have been likely to pass all years at first sitting being rejected for every higher risk candidate potentially declined entry on this basis. The UKCAT scores demonstrate a statistically significant but modest degree of incremental predictive validity throughout undergraduate training. Whilst the UKCAT could be considered a fairly

  8. Predictive Validity and Time Dependency of Self-Efficacy, Self-Esteem, Personal Goals, and Academic Performance.

    Science.gov (United States)

    Mone, Mark A.; And Others

    1995-01-01

    Relationships among self-efficacy, self-esteem, personal goals, and performance over multiple performance trials were examined for 215 college students. Self-efficacy was significantly predictive of personal goals and performance, but self-esteem was not. Results indicate that the more task-specific the measure, the better the prediction. (SLD)

  9. Even after Thirteen Class Exams, Students Are Still Overconfident: The Role of Memory for Past Exam Performance in Student Predictions

    Science.gov (United States)

    Foster, Nathaniel L.; Was, Christopher A.; Dunlosky, John; Isaacson, Randall M.

    2017-01-01

    Students often are overconfident when they predict their performance on classroom examinations, and their accuracy often does not improve across exams. One contributor to overconfidence may be that students did not have enough experience, and another is that students may under-use their knowledge of prior exam performance to predict performance on…

  10. Cognitive performance predicts treatment decisional abilities in mild to moderate dementia.

    Science.gov (United States)

    Gurrera, R J; Moye, J; Karel, M J; Azar, A R; Armesto, J C

    2006-05-09

    To examine the contribution of neuropsychological test performance to treatment decision-making capacity in community volunteers with mild to moderate dementia. The authors recruited volunteers (44 men, 44 women) with mild to moderate dementia from the community. Subjects completed a battery of 11 neuropsychological tests that assessed auditory and visual attention, logical memory, language, and executive function. To measure decision making capacity, the authors administered the Capacity to Consent to Treatment Interview, the Hopemont Capacity Assessment Interview, and the MacCarthur Competence Assessment Tool--Treatment. Each of these instruments individually scores four decisional abilities serving capacity: understanding, appreciation, reasoning, and expression of choice. The authors used principal components analysis to generate component scores for each ability across instruments, and to extract principal components for neuropsychological performance. Multiple linear regression analyses demonstrated that neuropsychological performance significantly predicted all four abilities. Specifically, it predicted 77.8% of the common variance for understanding, 39.4% for reasoning, 24.6% for appreciation, and 10.2% for expression of choice. Except for reasoning and appreciation, neuropsychological predictor (beta) profiles were unique for each ability. Neuropsychological performance substantially and differentially predicted capacity for treatment decisions in individuals with mild to moderate dementia. Relationships between elemental cognitive function and decisional capacity may differ in individuals whose decisional capacity is impaired by other disorders, such as mental illness.

  11. 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.

  12. 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.

  13. 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.

  14. Model for Predicting the Performance of Planetary Suit Hip Bearing Designs

    Science.gov (United States)

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

    2012-01-01

    Designing a space suit is very complex and often requires difficult trade-offs between performance, cost, mass, and system complexity. During the development period of the suit numerous design iterations need to occur before the hardware meets human performance requirements. Using computer models early in the design phase of hardware development is advantageous, by allowing virtual prototyping to take place. A virtual design environment allows designers to think creatively, exhaust design possibilities, and study design impacts on suit and human performance. A model of the rigid components of the Mark III Technology Demonstrator Suit (planetary-type space suit) and a human manikin were created and tested in a virtual environment. The performance of the Mark III hip bearing model was first developed and evaluated virtually by comparing the differences in mobility performance between the nominal bearing configurations and modified bearing configurations. Suited human performance was then simulated with the model and compared to actual suited human performance data using the same bearing configurations. The Mark III hip bearing model was able to visually represent complex bearing rotations and the theoretical volumetric ranges of motion in three dimensions. The model was also able to predict suited human hip flexion and abduction maximums to within 10% of the actual suited human subject data, except for one modified bearing condition in hip flexion which was off by 24%. Differences between the model predictions and the human subject performance data were attributed to the lack of joint moment limits in the model, human subject fitting issues, and the limited suit experience of some of the subjects. The results demonstrate that modeling space suit rigid segments is a feasible design tool for evaluating and optimizing suited human performance. Keywords: space suit, design, modeling, performance

  15. 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.

  16. Using Predictive Uncertainty Analysis to Assess Hydrologic Model Performance for a Watershed in Oregon

    Science.gov (United States)

    Brannan, K. M.; Somor, A.

    2016-12-01

    A variety of statistics are used to assess watershed model performance but these statistics do not directly answer the question: what is the uncertainty of my prediction. Understanding predictive uncertainty is important when using a watershed model to develop a Total Maximum Daily Load (TMDL). TMDLs are a key component of the US Clean Water Act and specify the amount of a pollutant that can enter a waterbody when the waterbody meets water quality criteria. TMDL developers use watershed models to estimate pollutant loads from nonpoint sources of pollution. We are developing a TMDL for bacteria impairments in a watershed in the Coastal Range of Oregon. We setup an HSPF model of the watershed and used the calibration software PEST to estimate HSPF hydrologic parameters and then perform predictive uncertainty analysis of stream flow. We used Monte-Carlo simulation to run the model with 1,000 different parameter sets and assess predictive uncertainty. In order to reduce the chance of specious parameter sets, we accounted for the relationships among parameter values by using mathematically-based regularization techniques and an estimate of the parameter covariance when generating random parameter sets. We used a novel approach to select flow data for predictive uncertainty analysis. We set aside flow data that occurred on days that bacteria samples were collected. We did not use these flows in the estimation of the model parameters. We calculated a percent uncertainty for each flow observation based 1,000 model runs. We also used several methods to visualize results with an emphasis on making the data accessible to both technical and general audiences. We will use the predictive uncertainty estimates in the next phase of our work, simulating bacteria fate and transport in the watershed.

  17. 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.

  18. Yo-Yo IR1 vs. incremental continuous running test for prediction of 3000-m performance.

    Science.gov (United States)

    Schmitz, Boris; Klose, Andreas; Schelleckes, Katrin; Jekat, Charlotte M; Krüger, Michael; Brand, Stefan-Martin

    2017-11-01

    This study aimed to compare physiological responses during the Yo-Yo intermittent recovery level 1 (Yo-Yo IR1) Test and an incremental continuous running field Test (ICRT) and to analyze their predictive value on 3000-m running performance. Forty moderately trained individuals (18 females) performed the ICRT and Yo-Yo IR1 Test to exhaustion. The ICRT was performed as graded running test with an increase of 2.0 km·h-1 after each 3 min interval for lactate diagnostic. In both tests, blood lactate levels were determined after the test and at 2 and 5 min of recovery. Heart rate (HR) was recorded to monitor differences in HR slopes and HR recovery. Comparison revealed a correlation between ICRT and Yo-Yo IR1 Test performance (R2=0.83, Prunning time (R2=0.77, Prunning performances such as 3000-m runs but maximum HR and blood lactate values differ significantly. The ICRT may have higher predictive power for middle- to long- distance running performance such as 3000-m runs offering a reliable test for coaches in the recruitment of athletes or supervision of training concepts.

  19. Evaluating the performance of thermal sensation prediction with a biophysical model.

    Science.gov (United States)

    Schweiker, M; Kingma, B R M; Wagner, A

    2017-09-01

    Neutral thermal sensation is expected for a human body in heat balance in near-steady-state thermal environments. The physiological thermoneutral zone (TNZ) is defined as the range of operative temperatures where the body can maintain such heat balance by actively adjusting body tissue insulation, but without regulatory increases in metabolic rate or sweating. These basic principles led to the hypothesis that thermal sensation relates to the operative temperature distance from the thermoneutral centroid (dTNZop ). This hypothesis was confirmed by data from respiratory climate chamber experiments. This paper explores the potential of such biophysical model for the prediction of thermal sensation under increased contextual variance. Data (798 votes, 47 participants) from a controlled office environment were used to analyze the predictive performance of the dTNZop model. The results showed a similar relationship between dTNZop and thermal sensation between the dataset used here and the previously used dataset. The predictive performance had the same magnitude as that of the PMV model; however, potential benefits of using a biophysical model are discussed. In conclusion, these findings confirm the potential of the biophysical model with regard to the understanding and prediction of human thermal sensation. Further work remains to make benefit of its full potential. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  20. Uncertainty quantification (UQ) techniques to improve predictions of laser beam control performance

    Science.gov (United States)

    Carreras, Richard A.

    2017-05-01

    Uncertainty quantification (UQ) is the study of the effects of uncertainty on the values of analytical results and the predictions of scientific models. Sources of uncertainty include imprecise knowledge of the exact values of parameters, lack of confidence in the physical models, use of imperfectly calibrated models, and irreducible uncertainties due to physical characteristics. The Air Force Research Laboratory has undertaken the challenge of understanding, developing and analyzing the techniques of UQ as they apply to Laser Beam Control. This paper proposes a simple methodology and simple results with our first attempt of applying UQ as a new analysis tool. The software toolkit which was chosen was an analytical group of algorithms from a Sandia National Laboratory (SNL) package called DAKOTA (Design Analysis Kit for Optimization and Terascale Applications). The specific application of interest to the Air Force Research Laboratory (AFRL) is the analytical prediction of the performance of a Laser Beam Control systems under various scenarios, conditions, and missions. The application of rigorous UQ techniques to the models used to predict beam control performance could greatly improve our confidence in these predictions and also improve the acceptance of advanced Laser Beam Control systems within the science and engineering communities1,2. The proposed work would follow a multi-step approach, analyzing the more easily quantified sources of uncertainty, and then including increasingly complicated physical phenomena as the work progresses. Will present the initial results, and the first steps in the incorporation of UQ into our Laser Beam Control Modeling and Simulation environments.

  1. Issues in performance evaluation for host-pathogen protein interaction prediction.

    Science.gov (United States)

    Abbasi, Wajid Arshad; Minhas, Fayyaz Ul Amir Afsar

    2016-06-01

    The study of interactions between host and pathogen proteins is important for understanding the underlying mechanisms of infectious diseases and for developing novel therapeutic solutions. Wet-lab techniques for detecting protein-protein interactions (PPIs) can benefit from computational predictions. Machine learning is one of the computational approaches that can assist biologists by predicting promising PPIs. A number of machine learning based methods for predicting host-pathogen interactions (HPI) have been proposed in the literature. The techniques used for assessing the accuracy of such predictors are of critical importance in this domain. In this paper, we question the effectiveness of K-fold cross-validation for estimating the generalization ability of HPI prediction for proteins with no known interactions. K-fold cross-validation does not model this scenario, and we demonstrate a sizable difference between its performance and the performance of an alternative evaluation scheme called leave one pathogen protein out (LOPO) cross-validation. LOPO is more effective in modeling the real world use of HPI predictors, specifically for cases in which no information about the interacting partners of a pathogen protein is available during training. We also point out that currently used metrics such as areas under the precision-recall or receiver operating characteristic curves are not intuitive to biologists and propose simpler and more directly interpretable metrics for this purpose.

  2. Application of SWAT99.2 to sensitivity analysis of water balance components in unique plots in a hilly region

    Directory of Open Access Journals (Sweden)

    Jun-feng Dai

    2017-07-01

    Full Text Available Although many sensitivity analyses using the soil and water assessment tool (SWAT in a complex watershed have been conducted, little attention has been paid to the application potential of the model in unique plots. In addition, sensitivity analysis of percolation and evapotranspiration with SWAT has seldom been undertaken. In this study, SWAT99.2 was calibrated to simulate water balance components for unique plots in Southern China from 2000 to 2001, which included surface runoff, percolation, and evapotranspiration. Twenty-one parameters classified into four categories, including meteorological conditions, topographical characteristics, soil properties, and vegetation attributes, were used for sensitivity analysis through one-at-a-time (OAT sampling to identify the factor that contributed most to the variance in water balance components. The results were shown to be different for different plots, with parameter sensitivity indices and ranks varying for different water balance components. Water balance components in the broad-leaved forest and natural grass plots were most sensitive to meteorological conditions, less sensitive to vegetation attributes and soil properties, and least sensitive to topographical characteristics. Compared to those in the natural grass plot, water balance components in the broad-leaved forest plot demonstrated higher sensitivity to the maximum stomatal conductance (GSI and maximum leaf area index (BLAI.

  3. Performance of blend sign in predicting hematoma expansion in intracerebral hemorrhage: A meta-analysis.

    Science.gov (United States)

    Yu, Zhiyuan; Zheng, Jun; Guo, Rui; Ma, Lu; Li, Mou; Wang, Xiaoze; Lin, Sen; Li, Hao; You, Chao

    2017-12-01

    Hematoma expansion is independently associated with poor outcome in intracerebral hemorrhage (ICH). Blend sign is a simple predictor for hematoma expansion on non-contrast computed tomography. However, its accuracy for predicting hematoma expansion is inconsistent in previous studies. This meta-analysis is aimed to systematically assess the performance of blend sign in predicting hematoma expansion in ICH. A systematic literature search was conducted. Original studies about predictive accuracy of blend sign for hematoma expansion in ICH were included. Pooled sensitivity, specificity, positive and negative likelihood ratios were calculated. Summary receiver operating characteristics curve was constructed. Publication bias was assessed by Deeks' funnel plot asymmetry test. A total of 5 studies with 2248 patients were included in this meta-analysis. The pooled sensitivity, specificity, positive and negative likelihood ratios of blend sign for predicting hematoma expansion were 0.28, 0.92, 3.4 and 0.78, respectively. The area under the curve (AUC) was 0.85. No significant publication bias was found. This meta-analysis demonstrates that blend sign is a useful predictor with high specificity for hematoma expansion in ICH. Further studies with larger sample size are still necessary to verify the accuracy of blend sign for predicting hematoma expansion. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Concepts within reach: Action performance predicts action language processing in stroke.

    Science.gov (United States)

    Desai, Rutvik H; Herter, Troy; Riccardi, Nicholas; Rorden, Chris; Fridriksson, Julius

    2015-05-01

    The relationship between the brain's conceptual or semantic and sensory-motor systems remains controversial. Here, we tested manual and conceptual abilities of 41 chronic stroke patients in order to examine their relationship. Manual abilities were assed through a reaching task using an exoskeleton robot. Semantic abilities were assessed with implicit as well as explicit semantic tasks, for both verbs and nouns. The results show that that the degree of selective impairment for action word processing was predicted by the degree of impairment in reaching performance. Moreover, the implicit semantic measures showed a correlation with a global reaching parameter, while the explicit semantic similarity judgment task predicted performance in action initiation. These results suggest that action concepts are dynamically grounded through motoric simulations, and that more details are simulated for more explicit semantic tasks. This is evidence for a close and causal relationship between sensory-motor and conceptual systems of the brain. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. 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.

  6. Performance Prediction of Double-Binary Turbo Codes with High Order Modulations in AWGN Channel

    Directory of Open Access Journals (Sweden)

    BALTA, H.

    2014-11-01

    Full Text Available In this paper, we present a method for turbo codes (TC performance prediction, in terms of bit error rate (BER and frame error rate (FER versus signal to noise ratio (SNR, when they are used with high-order modulations (HOM. The method is based on two simplifying hypotheses and assumes that the BER/FER vs. SNR performance, in the case of BPSK modulation, is known. For the simulations we have chosen the double-binary turbo codes (DBTC used in the DVB-RCS standard. The experimental results confirm the good accuracy of the proposed prediction method and validate our assumptions. The method has been applied in the case of 16-Quadrature Amplitude Modulation (16-QAM, but it can be easily extended to any other type of modulation.

  7. 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...... operating characteristic [ROC] curve), and goodness-of-fit statistics for calibration.Several new measures have recently been proposed that can be seen as refinements of discrimination measures, including variants of the c statistic for survival, reclassification tables, net reclassification improvement...... (NRI), and integrated discrimination improvement (IDI). Moreover, decision-analytic measures have been proposed, including decision curves to plot the net benefit achieved by making decisions based on model predictions.We aimed to define the role of these relatively novel approaches in the evaluation...

  8. Effects of data anonymization by cell suppression on descriptive statistics and predictive modeling performance.

    Science.gov (United States)

    Ohno-Machado, L; Vinterbo, S A; Dreiseitl, S

    2001-01-01

    Protecting individual data in disclosed databases is essential. Data anonymization strategies can produce table ambiguation by suppression of selected cells. Using table ambiguation, different degrees of anonymization can be achieved, depending on the number of individuals that a particular case must become indistinguishable from. This number defines the level of anonymization. Anonymization by cell suppression does not necessarily prevent inferences from being made from the disclosed data. Preventing inferences may be important to preserve confidentiality. We show that anonymized data sets can preserve descriptive characteristics of the data, but might also be used for making inferences on particular individuals, which is a feature that may not be desirable. The degradation of predictive performance is directly proportional to the degree of anonymity. As an example, we report the effect of anonymization on the predictive performance of a model constructed to estimate the probability of disease given clinical findings.

  9. Predicted and experimental performance of large-bore high-speed ball and roller bearings

    Science.gov (United States)

    Coe, H. H.

    1983-01-01

    The values of inner and outer race temperature, cage speed, and heat transferred to the lubricant or bearing power loss, calculated using the computer programs Shaberth and Cybean, with the corresponding experimental data for the large bore ball and roller bearings were compared. After the development of computer program, it is important that values calculated using such program are compared with actual bearing performance data to assess the programs predictive capability. Several comprehensive computer programs currently in use are capable of predicting rolling bearing operating and performance characteristics. These programs accept input data of bearing internal geometry, bearing material and lubricant properties, and bearing operating conditions. The programs solve several sets of equations that characterize rolling element bearings. The output produced typically consists of rolling element loads and Hertz stresses, operating contact angles, component speed, heat generation, local temperatures, bearing fatigue life, and power loss. Two of these programs, Shaberth and Cybean were developed.

  10. 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.

  11. Predicting performance on the Columbia Card Task: effects of personality characteristics, mood, and executive functions.

    Science.gov (United States)

    Buelow, Melissa T

    2015-04-01

    Behavioral measures of risky decision making are frequently used by researchers and clinicians; however, most of these measures are strongly associated with personality characteristics and state mood. The present study sought to examine personality, mood, and executive function predictors of performance on a newer measure of decision making, the Columbia Card Task (CCT). Participants were 489 undergraduate students who completed either the hot or cold version of the CCT as well as measures of state mood, impulsive sensation seeking, behavioral inhibition and activation systems, and executive functions (Wisconsin Card Sort Task; Digit Span). Results indicated that performance on the CCT-cold was predicted by Wisconsin Card Sort Task errors, and Digit Span predicted the CCT-hot. In addition, significant correlations were found between the CCT information use variables and the predictor variables. Implications for the utility of the CCT as a clinical instrument and its relationship with other measures of decision making are discussed. © The Author(s) 2014.

  12. Predicting episodic memory performance in dementia: is severity all there is?

    Science.gov (United States)

    Bäckman, L; Hill, R D; Herlitz, A; Fratiglioni, L; Winblad, B

    1994-12-01

    Whether individual differences in demographic, psychometric, and biological domains can predict episodic memory in dementia was investigated. Mildly to moderately demented very old persons performed episodic memory tasks (free recall and recognition of slowly and rapidly presented random words, free and cued recall of organizable words, and recognition of dated and contemporary famous faces). A factor analysis of the memory measures yielded 2 factors, 1 indexing recall and 1 recognition. Controlling for severity of dementia, only 2 predictors contributed to performance: (a) Block Design (a marker of fluid intelligence) was positively related to recall, and (b) age was negatively related to recognition. Although these results are similar to data reported on predictors of episodic memory in normal aging, (a) the number of predictive variables appears to be reduced in dementia, and (b) age seems to affect recall and recognition differentially in normal aging and dementia.

  13. Predicting performance in Canadian dental schools: the new CDA structured interview, a new personality assessment, and the DAT.

    Science.gov (United States)

    Poole, Amanda; Catano, Victor M; Cunningham, D P

    2007-05-01

    Using a sample of dental students (N=373) from four Canadian dental schools, this longitudinal study determined whether the new Canadian Dental Association (CDA) structured interview was a predictor of clinical and academic performance. The new interview predicted clinical performance in the third and fourth years of dental school, but not academic performance. The Canadian Dental Aptitude Test (DAT) continued to predict first- and second-year academic performance, but not clinical performance in the senior years. A personality factor, "Conscientiousness," predicted clinical and academic performance to various degrees across the four years of dental school. A second personality factor, "Openness to Experience," predicted third-year academic performance. The results suggest that a combination of scores from the DAT, a valid measure of personality, and a well-designed structured interview will provide the best prediction of those applicants who will do well in both the academic and clinical aspects of dental school.

  14. Performance Prediction and Simulation of Gas Turbine Engine Operation for Aircraft, Marine, Vehicular, and Power Generation

    Science.gov (United States)

    2007-02-01

    Overall performances of an LM6000 type gas turbine are shown in this figure, where comparison of predictions to manufacturer published data is shown. The...of Engineering for Gas Turbine and Power, July 1987, Vol. 109. Anon., “ LM6000 Control Solutions Benefit Operations”, Woodward Governor Company...Organowski, G., “GE LM6000 Development of the First 40% Thermal Efficiency Gas Turbine”, GE Marine & Industrial Engine and Service Division”. Meher Homji

  15. Understanding and predicting physiological performance of organisms in fluctuating and multifactorial environments

    OpenAIRE

    Koussoroplis, Apostolos-Manuel; Pincebourde, Sylvain; Wacker, Alexander

    2017-01-01

    International audience; Understanding how variance in environmental factors affects physiological performance , population growth, and persistence is central in ecology. Despite recent interest in the effects of variance in single biological drivers, such as temperature, we have lacked a comprehensive framework for predicting how the variances and covariances between multiple environmental factors will affect physiological rates. Here, we integrate current theory on variance effects with co-l...

  16. The National Football League (NFL) combine: does normalized data better predict performance in the NFL draft?

    Science.gov (United States)

    Robbins, Daniel W

    2010-11-01

    The objective of this study was to investigate the predictive ability of National Football League (NFL) combine physical test data to predict draft order over the years 2005-2009. The NFL combine provides a setting in which NFL personnel can evaluate top draft prospects. The predictive ability of combine data in its raw form and when normalized in both a ratio and allometric manner was examined for 17 positions. Data from 8 combine physical performance tests were correlated with draft order to determine the direction and strength of relationship between the various combine measures and draft order. Players invited to the combine and subsequently drafted in the same year (n = 1,155) were included in the study. The primary finding was that performance in the combine physical test battery, whether normalized or not, has little association with draft success. In terms of predicting draft order from outcomes of the 8 tests making up the combine battery, normalized data provided no advantage over raw data. Of the 8 performance measures investigated, straight sprint time and jumping ability seem to hold the most weight with NFL personnel responsible for draft decisions. The NFL should consider revising the combine test battery to reflect the physical characteristics it deems important. It may be that NFL teams are more interested in attributes other than the purely physical traits reflected in the combine test battery. Players with aspirations of entering the NFL may be well advised to develop mental and technical skills in addition to developing the physical characteristics necessary to optimize performance.

  17. A framework for the measurement and prediction of an individual scientist's performance

    CERN Document Server

    Poder, Endel

    2015-01-01

    Quantitative bibliometric indicators are widely used to evaluate the performance of scientists. However, traditional indicators are not much based on the analysis of the processes intended to measure and the practical goals of the measurement. In this study, I propose a simple framework to measure and predict an individual researcher's scientific performance that takes into account the main regularities of publication and citation processes and the requirements of practical tasks. Statistical properties of the new indicator - a scientist's personal impact rate - are illustrated by its application to a sample of Estonian researchers.

  18. Performance prediction and parametric analysis of two stage stirling cycle cryocooler

    Science.gov (United States)

    Natu, P. V.; Narayankhedkar, K. G.

    The lowest temperature that can be achieved inStirling cycle cryocooler is governed by various losses. This paper presents performance prediction of Two Stage Stirling Cryocooler(for 20K as the second stage temperature) by using second order analysis which calculates the ideal refrigerating effect at intermediate and final stage temperatures and the ideal power input. The losses are found out for both the stages to determine the actual refrigerating effects and power input. The results obtained are in good agreement with reported values. The performance of the cryocooler is governed by various operating and geometric parameters. Parametric analysis is carried.

  19. Thermal Conductivity of UO2 Fuel: Predicting Fuel Performance from Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Phillpot, Simon R.; El-Azab, Anter; Chernatynskiy, Aleksandr; Tulenko, James S.

    2011-08-19

    Recent progress in understanding the thermal-transport properties of UO₂ for fission reactors is reviewed from the perspective of computer simulations. A path to incorporating more accurate materials models into fuel performance codes is outlined. In particular, it is argued that a judiciously integrated program of atomic-level simulations and mesoscale simulations offers the possibility of both better predicting the thermal-transport properties of UO₂ in light-water reactors and enabling the assessment of the thermal performances of novel fuel systems for which extensive experimental databases are not available.

  20. A Data Driven Approach to Bioretention Cell Performance: Prediction and Design

    Directory of Open Access Journals (Sweden)

    Jianxun He

    2013-01-01

    Full Text Available Bioretention cells are an urban stormwater management technology used to address both water quality and quantity concerns. A lack of region-specific design guidelines has limited the widespread implementation of bioretention cells, particularly in cold climates. In this paper, experimental data are used to construct a multiple linear regression model to predict hydrological performance of bioretention cells. Nine different observed parameters are considered as candidates for regressors, of which inlet runoff volume and duration, and initial soil moisture were chosen. These three variables are used to construct six different regression models, which are tested against the observations. Statistical analysis showed that the amount of runoff captured by a bioretention cell can be successfully predicted by the inlet runoff volume and event duration. Historical data is then used to calculate runoff volume for a given duration, in different catchment types. This data is used in the regression model to predict bioretention cell performance. The results are then used to create a design tool which can assist in estimating bioretention cell size to meet different performance goals in southern Alberta. Examples on the functionality of the design tool are provided.