Capabilities, innovation, and overall performance in Brazilian export firms.

Directory of Open Access Journals (Sweden)

José Ednilson de Oliveira Cabral

2015-06-01

Full Text Available This article extends the current research on innovation by investigating the relationship between innovative capabilities and export firms’ overall performance. From the perspectives of the resource-based view (RBV and dynamic capability, we examine the differential and interactive effects of exploration and exploitation capabilities in product innovation for external markets and overall performance (direct and mediated by a new product. In addition, we test the moderating effect of market dynamism and the controlling effect of firm size on these relationships. Hence, the main contribution of this article is developing and empirically testing an original model, by combining these constructs that address new relationships, in an emerging country. This model was tested with data from 498 Brazilian export firms, distributed throughout all Brazilian manufacturing sectors, by firm size, and in states. The analysis was made with application of the structural equation modeling (SEM. As a result, we found support for the assumptions that exploitation capabilities influence product innovation and overall performance, whereas exploration capabilities and their interaction to exploitation capabilities influence overall performance, but not product innovation. Additionally, the relationship between exploitation capabilities and overall performance is mediated by product innovation. Unlike hypothesized, market dynamism does not moderate the relationship between product innovation and overall performance. Furthermore, firm size works as a controlling variable in the relationships analyzed. Regarding the implications for theory, this study contributes to grasp that exploitation capabilities influences a firm’s overall performance, both directly and indirectly (via product innovation, and highlights the various direct and mediatory effects of innovation on overall performance. These insights show the importance of considering the role of mediating and

The Impact of Knowledge Management Capability, Organizational Learning, and Supply Chain Management Practices on Organizational Performance

Directory of Open Access Journals (Sweden)

Ingy Essam Eldin Salama

2017-03-01

Full Text Available The focus of this research is developing and examining a conceptual framework relating resource-based organizational capabilities and inter-organizational practices with organizational performance. Specifically, it investigates the relationship between knowledge management capability, organizational learning, supply chain management practices and organizational performance. Such a study is important as it contributes to the growing body of literature that links organizational capabilities and practices with organizational performance. In addition, it also contributes to empirical knowledge by applying the proposed conceptual framework in the Egyptian context, which is currently under-researched. The research approach adopted in this research includes empirical examination of the hypothesized relationships among research variables applied on 63 factories with more than 100 employees located at New Borg Al-Arab industrial city using self-administrated questionnaires. The findings of this research provide evidence that knowledge management capability has an impact on organizational learning as well as on supply chain management practices. However, none of the research variables; i.e. knowledge management capability, organizational learning and supply chain management practices have an impact on organizational performance. The main conclusion drawn from this study is that knowledge management capability may be useful to managers for predicting organizational learning and coordinating supply chain management practices between supply chain members. In addition, it could be concluded that organizational performance, in the factories under study, is affected by variables other than knowledge management capability, organizational learning and supply chain management practices.

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

National Research Council Canada - National Science Library

Christensen, Kathryn

1998-01-01

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

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)

Assessing the Predictive Capability of the LIFEIV Nuclear Fuel Performance Code using Sequential Calibration

International Nuclear Information System (INIS)

Stull, Christopher J.; Williams, Brian J.; Unal, Cetin

2012-01-01

This report considers the problem of calibrating a numerical model to data from an experimental campaign (or series of experimental tests). The issue is that when an experimental campaign is proposed, only the input parameters associated with each experiment are known (i.e. outputs are not known because the experiments have yet to be conducted). Faced with such a situation, it would be beneficial from the standpoint of resource management to carefully consider the sequence in which the experiments are conducted. In this way, the resources available for experimental tests may be allocated in a way that best 'informs' the calibration of the numerical model. To address this concern, the authors propose decomposing the input design space of the experimental campaign into its principal components. Subsequently, the utility (to be explained) of each experimental test to the principal components of the input design space is used to formulate the sequence in which the experimental tests will be used for model calibration purposes. The results reported herein build on those presented and discussed in (1,2) wherein Verification and Validation and Uncertainty Quantification (VU) capabilities were applied to the nuclear fuel performance code LIFEIV. In addition to the raw results from the sequential calibration studies derived from the above, a description of the data within the context of the Predictive Maturity Index (PMI) will also be provided. The PMI (3,4) is a metric initiated and developed at Los Alamos National Laboratory to quantitatively describe the ability of a numerical model to make predictions in the absence of experimental data, where it is noted that 'predictions in the absence of experimental data' is not synonymous with extrapolation. This simply reflects the fact that resources do not exist such that each and every execution of the numerical model can be compared against experimental data. If such resources existed, the justification for numerical models

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.

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.

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

Building a Predictive Capability for Decision-Making that Supports MultiPEM

Energy Technology Data Exchange (ETDEWEB)

Carmichael, Joshua Daniel [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-11-20

Multi-phenomenological explosion monitoring (multiPEM) is a developing science that uses multiple geophysical signatures of explosions to better identify and characterize their sources. MultiPEM researchers seek to integrate explosion signatures together to provide stronger detection, parameter estimation, or screening capabilities between different sources or processes. This talk will address forming a predictive capability for screening waveform explosion signatures to support multiPEM.

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

Simulating urban-scale air pollutants and their predicting capabilities over the Seoul metropolitan area.

Science.gov (United States)

Park, Il-Soo; Lee, Suk-Jo; Kim, Cheol-Hee; Yoo, Chul; Lee, Yong-Hee

2004-06-01

Urban-scale air pollutants for sulfur dioxide, nitrogen dioxide, particulate matter with aerodynamic diameter > or = 10 microm, and ozone (O3) were simulated over the Seoul metropolitan area, Korea, during the period of July 2-11, 2002, and their predicting capabilities were discussed. The Air Pollution Model (TAPM) and the highly disaggregated anthropogenic and the biogenic gridded emissions (1 km x 1 km) recently prepared by the Korean Ministry of Environment were applied. Wind fields with observational nudging in the prognostic meteorological model TAPM are optionally adopted to comparatively examine the meteorological impact on the prediction capabilities of urban-scale air pollutants. The result shows that the simulated concentrations of secondary air pollutant largely agree with observed levels with an index of agreement (IOA) of >0.6, whereas IOAs of approximately 0.4 are found for most primary pollutants in the major cities, reflecting the quality of emission data in the urban area. The observationally nudged wind fields with higher IOAs have little effect on the prediction for both primary and secondary air pollutants, implying that the detailed wind field does not consistently improve the urban air pollution model performance if emissions are not well specified. However, the robust highest concentrations are better described toward observations by imposing observational nudging, suggesting the importance of wind fields for the predictions of extreme concentrations such as robust highest concentrations, maximum levels, and >90th percentiles of concentrations for both primary and secondary urban-scale air pollutants.

Predictive Measures of Locomotor Performance on an Unstable Walking Surface

Science.gov (United States)

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

Determinants of Marketing Performance: Innovation, Market Capabilities and Marketing Performance

Directory of Open Access Journals (Sweden)

Naili Farida

2016-04-01

Full Text Available This research aim to analyze causality influence between innovations, market capability, social modal, entrepreneurs oriented into marketing performance. Organizational innovations is a basic focus on Total  Quality Management. Innovation has a role to technological development and competitive economy environment. The sample technique used is Purpusive sampling amount 58 respondent owner of Batik Small Medium Enterprise known as UKM.  Small businesses have small medium or medium can grow and develop so that it is able to increase its product and sustainability efforts on the creative industry. The technique analysis used is Parsial Least Square (PLS, this result shows entrepreneur orientation doesn’t influence into market capability and social modal, innovation has positive influence and significance into market capability and marketing performance. This results shows innovation has important role in advantaging market capability while influencing to increase marketing performance of Small Medium Enterprise known as UKM. Penelitian ini bertujuan untuk menganalisis pengaruh kausalitas antara inovasi, kemampuan pasar, modal sosial, pengusaha berorientasi ke kinerja pemasaran. Inovasi organisasi adalah dasar TQM. Inovasi mempunyai peran pentinga dalam pengembangan teknologi dan lingkungan yang penuh persaingan. Teknik sampel yang digunakan adalah Purposive Sampling jumlah 58 pemilik responden dari Batik Kecil Menengah dikenal sebagai UKM. UKM dapat tumbuh dan berkembang melalui industri kreatif. Teknik analisis yang digunakan adalah Parsial Least Square (PLS, hasil ini menunjukkan orientasi entrepreneur tidak mempengaruhi ke kemampuan pasar dan modal sosial, inovasi berpengaruh positif dan signifikan dalam kemampuan pasar dan kinerja pemasaran. Hal ini menyebabkan menunjukkan inovasi memiliki peran penting dalam advantaging kemampuan pasar sementara yang mempengaruhi untuk meningkatkan kinerja pemasaran Kecil Menengah dikenal sebagai UKM.

A Process for Assessing NASA's Capability in Aircraft Noise Prediction Technology

Science.gov (United States)

Dahl, Milo D.

2008-01-01

An acoustic assessment is being conducted by NASA that has been designed to assess the current state of the art in NASA s capability to predict aircraft related noise and to establish baselines for gauging future progress in the field. The process for determining NASA s current capabilities includes quantifying the differences between noise predictions and measurements of noise from experimental tests. The computed noise predictions are being obtained from semi-empirical, analytical, statistical, and numerical codes. In addition, errors and uncertainties are being identified and quantified both in the predictions and in the measured data to further enhance the credibility of the assessment. The content of this paper contains preliminary results, since the assessment project has not been fully completed, based on the contributions of many researchers and shows a select sample of the types of results obtained regarding the prediction of aircraft noise at both the system and component levels. The system level results are for engines and aircraft. The component level results are for fan broadband noise, for jet noise from a variety of nozzles, and for airframe noise from flaps and landing gear parts. There are also sample results for sound attenuation in lined ducts with flow and the behavior of acoustic lining in ducts.

A Study on the Impact of Marketing Capability, Operations Capability, Environmental Capability and Diversification Strategy on the Performance of Hotel Industry in the UK

OpenAIRE

ZHANG, YUBO

2009-01-01

Hotel industry has been an increasingly significant service industry across the whole world. The performance measurement method is crucial for hotels’ operations. This study examines the impacts of marketing capability, operations capability, environmental capability and diversification strategy on the business performance of hotel industry in the UK. Based on the financial archival data in the database and information obtained in the firm websites from 2004 to 2007, the investigation is carr...

Predictive capability of average Stokes polarimetry for simulation of phase multilevel elements onto LCoS devices.

Science.gov (United States)

Martínez, Francisco J; Márquez, Andrés; Gallego, Sergi; Ortuño, Manuel; Francés, Jorge; Pascual, Inmaculada; Beléndez, Augusto

2015-02-20

Parallel-aligned (PA) liquid-crystal on silicon (LCoS) microdisplays are especially appealing in a wide range of spatial light modulation applications since they enable phase-only operation. Recently we proposed a novel polarimetric method, based on Stokes polarimetry, enabling the characterization of their linear retardance and the magnitude of their associated phase fluctuations or flicker, exhibited by many LCoS devices. In this work we apply the calibrated values obtained with this technique to show their capability to predict the performance of spatially varying phase multilevel elements displayed onto the PA-LCoS device. Specifically we address a series of multilevel phase blazed gratings. We analyze both their average diffraction efficiency ("static" analysis) and its associated time fluctuation ("dynamic" analysis). Two different electrical configuration files with different degrees of flicker are applied in order to evaluate the actual influence of flicker on the expected performance of the diffractive optical elements addressed. We obtain a good agreement between simulation and experiment, thus demonstrating the predictive capability of the calibration provided by the average Stokes polarimetric technique. Additionally, it is obtained that for electrical configurations with less than 30° amplitude for the flicker retardance, they may not influence the performance of the blazed gratings. In general, we demonstrate that the influence of flicker greatly diminishes when the number of quantization levels in the optical element increases.

Assessing the predictive capability of randomized tree-based ensembles in streamflow modelling

Science.gov (United States)

Galelli, S.; Castelletti, A.

2013-07-01

Combining randomization methods with ensemble prediction is emerging as an effective option to balance accuracy and computational efficiency in data-driven modelling. In this paper, we investigate the prediction capability of extremely randomized trees (Extra-Trees), in terms of accuracy, explanation ability and computational efficiency, in a streamflow modelling exercise. Extra-Trees are a totally randomized tree-based ensemble method that (i) alleviates the poor generalisation property and tendency to overfitting of traditional standalone decision trees (e.g. CART); (ii) is computationally efficient; and, (iii) allows to infer the relative importance of the input variables, which might help in the ex-post physical interpretation of the model. The Extra-Trees potential is analysed on two real-world case studies - Marina catchment (Singapore) and Canning River (Western Australia) - representing two different morphoclimatic contexts. The evaluation is performed against other tree-based methods (CART and M5) and parametric data-driven approaches (ANNs and multiple linear regression). Results show that Extra-Trees perform comparatively well to the best of the benchmarks (i.e. M5) in both the watersheds, while outperforming the other approaches in terms of computational requirement when adopted on large datasets. In addition, the ranking of the input variable provided can be given a physically meaningful interpretation.

ORGANISATIONAL CAPABILITIES, COMPETITIVE ADVANTAGE AND PERFORMANCE IN SUPPORTING INDUSTRIES IN VIETNAM

Directory of Open Access Journals (Sweden)

Nham Phong Tuan

2010-01-01

Full Text Available This paper focuses on applying the resource-based view (RBV of firms to explain performance in supporting industries in Vietnam. Specifically, we based our research on the comprehensive framework of RBV and reviewed previous empirical researches before deciding on adopting a dynamic capabilities approach to test relationships among organisational capabilities, competitive advantage and performance. A multivariate analysis of survey responses of 102 firms belonging to supporting industries in Vietnam indicates that the organisational capabilities are related to the competitive advantage, that the competitive advantage is related to performance, and that the competitive advantage mediates the relationship between organizational capabilities and performance. These findings have considerable implications for academics as well as practitioners. Finally, this study also provides directions for future research.

BIG DATA RESOURCES, MARKETING CAPABILITIES, AND FIRM PERFORMANCE.

OpenAIRE

Suoniemi, Samppa; Meyer-Waarden, Lars; Munzel, Andreas

2017-01-01

RESEARCH QUESTION Big data may significantly improve the efficiency and effectiveness of the firm's marketing capabilities. However, firms must overcome technological, skill-based and organisational challenges to become data-driven. Academic research has not empirically investigated how strategic big data resources, and to what extent, influence strategic marketing capabilities and, by extension, firm performance. The primary objective of this research is to remedy this crucial knowledge ...

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

Energy Technology Data Exchange (ETDEWEB)

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

1981-09-01

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

Development of a fourth generation predictive capability maturity model.

Energy Technology Data Exchange (ETDEWEB)

Hills, Richard Guy; Witkowski, Walter R.; Urbina, Angel; Rider, William J.; Trucano, Timothy Guy

2013-09-01

The Predictive Capability Maturity Model (PCMM) is an expert elicitation tool designed to characterize and communicate completeness of the approaches used for computational model definition, verification, validation, and uncertainty quantification associated for an intended application. The primary application of this tool at Sandia National Laboratories (SNL) has been for physics-based computational simulations in support of nuclear weapons applications. The two main goals of a PCMM evaluation are 1) the communication of computational simulation capability, accurately and transparently, and 2) the development of input for effective planning. As a result of the increasing importance of computational simulation to SNLs mission, the PCMM has evolved through multiple generations with the goal to provide more clarity, rigor, and completeness in its application. This report describes the approach used to develop the fourth generation of the PCMM.

How Relational Capabilities Matter? Organizational Context and Performance of Internationally Oriented SMEs

Directory of Open Access Journals (Sweden)

Mariola Ciszewska-Mlinarič

2012-12-01

Full Text Available The article sheds light on the organizational context enhancing development of relational capabilities and examines the significance of relational capabilities for SMEs’ financial and non-financial performance. The firm relational capability is measured separately in customers’ and suppliers’ networks. The research results reveal that fostering internal social capital coupled with the usage of economic motivators augment a firm relational capability in a supplier network, which in turn is associated with better performance results, both financial and non-financial. The results on relational capability in a customer network with respect to performance are less conclusive, indicating that vertical ties that internationally oriented SMEs develop (with suppliers and customers are not of equal importance.

Alliance capability as a mediator between experience and alliance performance

DEFF Research Database (Denmark)

Heimeriks, Koen; Duysters, Geert

This study centers around the way in which firms can enhance alliance performance through the development of alliance capabilities. Whereas most research has focused on inter-firm antecedents of alliance performance, research on intra-firm antecedents pointing to prior experience and internal...... alliance managers and Vice-Presidents of 151 firms. The survey covers over 2600 alliances for the period 1997-2001. This study not only finds that alliance capabilities partially mediate between alliance experience and alliance performance, but also yields novel insights into the micro-level building...

Judgmental Forecasting of Operational Capabilities

DEFF Research Database (Denmark)

Hallin, Carina Antonia; Tveterås, Sigbjørn; Andersen, Torben Juul

This paper explores a new judgmental forecasting indicator, the Employee Sensed Operational Capabilities (ESOC). The purpose of the ESOC is to establish a practical prediction tool that can provide early signals about changes in financial performance by gauging frontline employees’ sensing...... of changes in the firm’s operational capabilities. We present the first stage of the development of ESOC by applying a formative measurement approach to test the index in relation to financial performance and against an organizational commitment scale. We use distributed lag models to test whether the ESOC...

Learning Capability and Business Performance: A Non-Financial and Financial Assessment

Science.gov (United States)

Ma Prieto, Isabel; Revilla, Elena

2006-01-01

Purpose: There has been little research that includes reliable deductions about the positive influence of learning capability on business performance. For this reason, the main objective of the present study is to empirically explore the link between learning capability in organizations and business performance evaluated in both financial and…

Associations between structural capabilities of primary care practices and performance on selected quality measures.

Science.gov (United States)

Friedberg, Mark W; Coltin, Kathryn L; Safran, Dana Gelb; Dresser, Marguerite; Zaslavsky, Alan M; Schneider, Eric C

2009-10-06

Recent proposals to reform primary care have encouraged physician practices to adopt such structural capabilities as performance feedback and electronic health records. Whether practices with these capabilities have higher performance on measures of primary care quality is unknown. To measure associations between structural capabilities of primary care practices and performance on commonly used quality measures. Cross-sectional analysis. Massachusetts. 412 primary care practices. During 2007, 1 physician from each participating primary care practice (median size, 4 physicians) was surveyed about structural capabilities of the practice (responses representing 308 practices were obtained). Data on practice structural capabilities were linked to multipayer performance data on 13 Healthcare Effectiveness Data and Information Set (HEDIS) process measures in 4 clinical areas: screening, diabetes, depression, and overuse. Frequently used multifunctional electronic health records were associated with higher performance on 5 HEDIS measures (3 in screening and 2 in diabetes), with statistically significant differences in performance ranging from 3.1 to 7.6 percentage points. Frequent meetings to discuss quality were associated with higher performance on 3 measures of diabetes care (differences ranging from 2.3 to 3.1 percentage points). Physician awareness of patient experience ratings was associated with higher performance on screening for breast cancer and cervical cancer (1.9 and 2.2 percentage points, respectively). No other structural capabilities were associated with performance on more than 1 measure. No capabilities were associated with performance on depression care or overuse. Structural capabilities of primary care practices were assessed by physician survey. Among the investigated structural capabilities of primary care practices, electronic health records were associated with higher performance across multiple HEDIS measures. Overall, the modest magnitude and

Predictive modeling capabilities from incident powder and laser to mechanical properties for laser directed energy deposition

Science.gov (United States)

Shin, Yung C.; Bailey, Neil; Katinas, Christopher; Tan, Wenda

2018-01-01

This paper presents an overview of vertically integrated comprehensive predictive modeling capabilities for directed energy deposition processes, which have been developed at Purdue University. The overall predictive models consist of vertically integrated several modules, including powder flow model, molten pool model, microstructure prediction model and residual stress model, which can be used for predicting mechanical properties of additively manufactured parts by directed energy deposition processes with blown powder as well as other additive manufacturing processes. Critical governing equations of each model and how various modules are connected are illustrated. Various illustrative results along with corresponding experimental validation results are presented to illustrate the capabilities and fidelity of the models. The good correlations with experimental results prove the integrated models can be used to design the metal additive manufacturing processes and predict the resultant microstructure and mechanical properties.

Predictive modeling capabilities from incident powder and laser to mechanical properties for laser directed energy deposition

Science.gov (United States)

Shin, Yung C.; Bailey, Neil; Katinas, Christopher; Tan, Wenda

2018-05-01

This paper presents an overview of vertically integrated comprehensive predictive modeling capabilities for directed energy deposition processes, which have been developed at Purdue University. The overall predictive models consist of vertically integrated several modules, including powder flow model, molten pool model, microstructure prediction model and residual stress model, which can be used for predicting mechanical properties of additively manufactured parts by directed energy deposition processes with blown powder as well as other additive manufacturing processes. Critical governing equations of each model and how various modules are connected are illustrated. Various illustrative results along with corresponding experimental validation results are presented to illustrate the capabilities and fidelity of the models. The good correlations with experimental results prove the integrated models can be used to design the metal additive manufacturing processes and predict the resultant microstructure and mechanical properties.

Performance Analysis of the Capability Assessment Tool for Sustainable Manufacturing

Directory of Open Access Journals (Sweden)

Enda Crossin

2013-08-01

Full Text Available This paper explores the performance of a novel capability assessment tool, developed to identify capability gaps and associated training and development requirements across the supply chain for environmentally-sustainable manufacturing. The tool was developed to assess 170 capabilities that have been clustered with respect to key areas of concern such as managing energy, water, material resources, carbon emissions and waste as well as environmental management practices for sustainability. Two independent expert teams used the tool to assess a sample group of five first and second tier sports apparel and footwear suppliers within the supply chain of a global sporting goods manufacturer in Asia. The paper addresses the reliability and robustness of the developed assessment method by formulating the expected links between the assessment results. The management practices of the participating suppliers were shown to be closely connected to their performance in managing their resources and emissions. The companies’ initiatives in implementing energy efficiency measures were found to be generally related to their performance in carbon emissions management. The suppliers were also asked to undertake a self-assessment by using a short questionnaire. The large gap between the comprehensive assessment and these in-house self-assessments revealed the suppliers’ misconceptions about their capabilities.

Determinants of Marketing Performance: Innovation, Market Capabilities and Marketing Performance

OpenAIRE

Naili Farida

2016-01-01

This research aim to analyze causality influence between innovations, market capability, social modal, entrepreneurs oriented into marketing performance. Organizational innovations is a basic focus on Total  Quality Management. Innovation has a role to technological development and competitive economy environment. The sample technique used is Purpusive sampling amount 58 respondent owner of Batik Small Medium Enterprise known as UKM.  Small businesses have small medium or medium can grow and ...

Investigation for GOTHIC-3D prediction capability for the local hydrogen behavior analysis in the NPP containment

International Nuclear Information System (INIS)

Lee, Un-jang; Park, Goon-cherl

2002-01-01

Under a severe accident condition, hydrogen can be generated mainly from the reaction of zirconium cladding with hot steam and flammable hydrogen/air/steam mixtures can be formed. Thus hydrogen analysis is needed for a variety of reasons in the containment building; to predict the global containment response against the threat potential by hydrogen; to address certain safety issues such as the safety feature survivability due to global burning or explosion of hydrogen; or for designing and positioning of the hydrogen controller. In this study an analytical tool was used to predict the local hydrogen behavior in a small compartment and its analytical capability was examined through verification tests, which have been performed in SNU hydrogen mixing facilities. The analytical tool that was employed is the code GOTHIC which is a 3D three-fields (vapor, liquid and droplets) code specially developed for the containment analysis, and has the additional capability of modeling a number of different gases as well as air. The comparison between experimental and analytical tests results showed that the GOTHIC code is not applicable for the analysis of local hydrogen behavior in the highly transient condition and/or in small size compartment. (authors)

Relationship between innovation capability, innovation type, and firm performance

Directory of Open Access Journals (Sweden)

R.P. Jayani Rajapathirana

2018-01-01

Full Text Available Insurers are well versed in the litany of challenging conditions facing the sector. These challenges are economic, political, regulatory, legal, social, and technological. As a result of those pressures, the industry is experiencing increasing competition, muted growth, and an excess of capital. The increased connectivity among household and workplace devices, the development of autonomous vehicle and the rising threat of cyber attacks are transforming the way people live and risk they need to mitigate with insurance products. Insurers need to adopt their business models address the changes which can be threatening to the growth of the industry (Deloitte, 2017. Innovation is widely regarded as pinnacle success factor in highly competitive and global economy. An innovation perspective draws a clear picture of future opportunities that lie ahead. The main purpose of this paper is to explore the relationship among innovations capability, innovation type and on the different aspect of firm performance including innovation, market and financial performance based on an empirical study covering insurance industry in Sri Lanka. The research framework developed in this study was tested 379 senior managers of insurance companies. The empirical verification of assumption of this model has given evidence to confirm the relationship between innovation capabilities; innovation efforts and firm performance are significant and strong. The results of this study could lead effective management of innovation capability which helps to deliver more effective innovations outcomes to generate better performance and it would be benefits for management of the insurance companies.

Building Micro-Foundations for the Routines, Capabilities, and Performance Links

DEFF Research Database (Denmark)

Abell, Peter; Felin, Teppo; Foss, Nicolai Juul

2007-01-01

a neglect of micro-foundations - is incomplete. There are no mechanisms that work solely on the macro-level, directly connecting routines and capabilities to firm-level outcomes. While routines and capabilities are useful shorthand for complicated patterns of individual action and interaction, ultimately...... they are best understood at the micro-level. Second, we provide a formal model that shows precisely why macro explanation is incomplete and which exemplifies how explicit micro-foundations may be built for notions of routines and capabilities and for how these impact firm performance....

Applying a multi-replication framework to support dynamic situation assessment and predictive capabilities

Science.gov (United States)

Lammers, Craig; McGraw, Robert M.; Steinman, Jeffrey S.

2005-05-01

Technological advances and emerging threats reduce the time between target detection and action to an order of a few minutes. To effectively assist with the decision-making process, C4I decision support tools must quickly and dynamically predict and assess alternative Courses Of Action (COAs) to assist Commanders in anticipating potential outcomes. These capabilities can be provided through the faster-than-real-time predictive simulation of plans that are continuously re-calibrating with the real-time picture. This capability allows decision-makers to assess the effects of re-tasking opportunities, providing the decision-maker with tremendous freedom to make time-critical, mid-course decisions. This paper presents an overview and demonstrates the use of a software infrastructure that supports DSAP capabilities. These DSAP capabilities are demonstrated through the use of a Multi-Replication Framework that supports (1) predictivie simulations using JSAF (Joint Semi-Automated Forces); (2) real-time simulation, also using JSAF, as a state estimation mechanism; and, (3) real-time C4I data updates through TBMCS (Theater Battle Management Core Systems). This infrastructure allows multiple replications of a simulation to be executed simultaneously over a grid faster-than-real-time, calibrated with live data feeds. A cost evaluator mechanism analyzes potential outcomes and prunes simulations that diverge from the real-time picture. In particular, this paper primarily serves to walk a user through the process for using the Multi-Replication Framework providing an enhanced decision aid.

Relationships and Predictive Capabilities of Jump Assessments to Soccer-Specific Field Test Performance in Division I Collegiate Players.

Science.gov (United States)

Lockie, Robert G; Stage, Alyssa A; Stokes, John J; Orjalo, Ashley J; Davis, DeShaun L; Giuliano, Dominic V; Moreno, Matthew R; Risso, Fabrice G; Lazar, Adrina; Birmingham-Babauta, Samantha A; Tomita, Tricia M

2016-12-03

Leg power is an important characteristic for soccer, and jump tests can measure this capacity. Limited research has analyzed relationships between jumping and soccer-specific field test performance in collegiate male players. Nineteen Division I players completed tests of: leg power (vertical jump (VJ), standing broad jump (SBJ), left- and right-leg triple hop (TH)); linear (30 m sprint; 0⁻5 m, 5⁻10 m, 0⁻10, 0⁻30 m intervals) and change-of-direction (505) speed; soccer-specific fitness (Yo-Yo Intermittent Recovery Test Level 2); and 7 × 30-m sprints to measure repeated-sprint ability (RSA; total time (TT), performance decrement (PD)). Pearson's correlations ( r ) determined jump and field test relationships; stepwise regression ascertained jump predictors of the tests ( p jumps correlated with the 0⁻5, 0⁻10, and 0⁻30 m sprint intervals ( r = -0.65⁻-0.90). VJ, SBJ, and left- and right-leg TH correlated with RSA TT ( r = -0.51⁻-0.59). Right-leg TH predicted the 0⁻5 and 0⁻10 m intervals (R² = 0.55⁻0.81); the VJ predicted the 0⁻30 m interval and RSA TT (R² = 0.41⁻0.84). Between-leg TH asymmetry correlated with and predicted left-leg 505 and RSA PD ( r = -0.68⁻0.62; R² = 0.39⁻0.46). Improvements in jumping ability could contribute to faster speed and RSA performance in collegiate soccer players.

Relationships and Predictive Capabilities of Jump Assessments to Soccer-Specific Field Test Performance in Division I Collegiate Players

Directory of Open Access Journals (Sweden)

Robert G. Lockie

2016-12-01

Full Text Available Leg power is an important characteristic for soccer, and jump tests can measure this capacity. Limited research has analyzed relationships between jumping and soccer-specific field test performance in collegiate male players. Nineteen Division I players completed tests of: leg power (vertical jump (VJ, standing broad jump (SBJ, left- and right-leg triple hop (TH; linear (30 m sprint; 0–5 m, 5–10 m, 0–10, 0–30 m intervals and change-of-direction (505 speed; soccer-specific fitness (Yo-Yo Intermittent Recovery Test Level 2; and 7 × 30-m sprints to measure repeated-sprint ability (RSA; total time (TT, performance decrement (PD. Pearson’s correlations (r determined jump and field test relationships; stepwise regression ascertained jump predictors of the tests (p < 0.05. All jumps correlated with the 0–5, 0–10, and 0–30 m sprint intervals (r = −0.65–−0.90. VJ, SBJ, and left- and right-leg TH correlated with RSA TT (r = −0.51–−0.59. Right-leg TH predicted the 0–5 and 0–10 m intervals (R2 = 0.55–0.81; the VJ predicted the 0–30 m interval and RSA TT (R2 = 0.41–0.84. Between-leg TH asymmetry correlated with and predicted left-leg 505 and RSA PD (r = −0.68–0.62; R2 = 0.39–0.46. Improvements in jumping ability could contribute to faster speed and RSA performance in collegiate soccer players.

Cadmium-emitter self-powered thermal neutron detector performance characterization & reactor power tracking capability experiments performed in ZED-2

Energy Technology Data Exchange (ETDEWEB)

LaFontaine, M.W., E-mail: physics@execulink.com [LaFontaine Consulting, Kitchener, Ontario (Canada); Zeller, M.B. [Canadian Nuclear Laboratories, Chalk River, Ontario (Canada); Nielsen, K. [Royal Military College of Canada, SLOWPOKE-2 Reactor, Kingston, Ontario (Canada)

2014-07-01

Cadmium-emitter self-powered thermal neutron flux detectors (SPDs), are typically used for flux monitoring and control applications in low temperature, test reactors such as the SLOWPOKE-2. A collaborative program between Atomic Energy of Canada, academia (Royal Military College of Canada (RMCC)) and industry (LaFontaine Consulting) was initiated to characterize the incore performance of a typical Cd-emitter SPD; and to obtain a definitive measure of the capability of the detector to track changes in reactor power in real time. Prior to starting the experiment proper, Chalk River Laboratories' ZED-2 was operated at low power (5 watts nominal) to verify the predicted moderator critical height. Test measurements were then performed with the vertical center of the SPD emitter positioned at the vertical mid-plane of the ZED-2 reactor core. Measurements were taken with the SPD located at lattice position L0 (near center), and repeated at lattice position P0 (in D{sub 2}O reflector). An ionization chamber (part of the ZED-2 control instrumentation) monitored reactor power at a position located on the south side of the outside wall of the reactor's calandria. These experiments facilitated measurement of the absolute thermal neutron sensitivity of the subject Cd-emitter SPD, and validated the power tracking capability of said SPD. Procedural details of the experiments, data, calculations and associated graphs, are presented and discussed. (author)

Assessment of Prediction Capabilities of COCOSYS and CFX Code for Simplified Containment

Directory of Open Access Journals (Sweden)

Jia Zhu

2016-01-01

Full Text Available The acceptable accuracy for simulation of severe accident scenarios in containments of nuclear power plants is required to investigate the consequences of severe accidents and effectiveness of potential counter measures. For this purpose, the actual capability of CFX tool and COCOSYS code is assessed in prototypical geometries for simplified physical process-plume (due to a heat source under adiabatic and convection boundary condition, respectively. Results of the comparison under adiabatic boundary condition show that good agreement is obtained among the analytical solution, COCOSYS prediction, and CFX prediction for zone temperature. The general trend of the temperature distribution along the vertical direction predicted by COCOSYS agrees with the CFX prediction except in dome, and this phenomenon is predicted well by CFX and failed to be reproduced by COCOSYS. Both COCOSYS and CFX indicate that there is no temperature stratification inside dome. CFX prediction shows that temperature stratification area occurs beneath the dome and away from the heat source. Temperature stratification area under adiabatic boundary condition is bigger than that under convection boundary condition. The results indicate that the average temperature inside containment predicted with COCOSYS model is overestimated under adiabatic boundary condition, while it is underestimated under convection boundary condition compared to CFX prediction.

Evaluation of icing drag coefficient correlations applied to iced propeller performance prediction

Science.gov (United States)

Miller, Thomas L.; Shaw, R. J.; Korkan, K. D.

1987-01-01

Evaluation of three empirical icing drag coefficient correlations is accomplished through application to a set of propeller icing data. The various correlations represent the best means currently available for relating drag rise to various flight and atmospheric conditions for both fixed-wing and rotating airfoils, and the work presented here ilustrates and evaluates one such application of the latter case. The origins of each of the correlations are discussed, and their apparent capabilities and limitations are summarized. These correlations have been made to be an integral part of a computer code, ICEPERF, which has been designed to calculate iced propeller performance. Comparison with experimental propeller icing data shows generally good agreement, with the quality of the predicted results seen to be directly related to the radial icing extent of each case. The code's capability to properly predict thrust coefficient, power coefficient, and propeller efficiency is shown to be strongly dependent on the choice of correlation selected, as well as upon proper specificatioon of radial icing extent.

IT-enabled dynamic capability on performance: An empirical study of BSC model

Directory of Open Access Journals (Sweden)

Adilson Carlos Yoshikuni

2017-05-01

Full Text Available ew studies have investigated the influence of “information capital,” through IT-enabled dynamic capability, on corporate performance, particularly in economic turbulence. Our study investigates the causal relationship between performance perspectives of the balanced scorecard using partial least squares path modeling. Using data on 845 Brazilian companies, we conduct a quantitative empirical study of firms during an economic crisis and observe the following interesting results. Operational and analytical IT-enabled dynamic capability had positive effects on business process improvement and corporate performance. Results pertaining to mediation (endogenous variables and moderation (control variables clarify IT’s role in and benefits for corporate performance.

Small Firm Adaptive Capability, Competitive Strategy and Performance Outcomes: Competing Mediation vs Moderation Perspectives

OpenAIRE

Chryssochoidis, George; Dousios, Dimitrios; Tzokas, Nikolaos

2016-01-01

In small firms, adaptive capability exercises a handling grip on competitive strategy for superior performance primarily acting as a mediator and may offset, through attenuation, the adverse impact of limited resources. Besides exercising a handling grip on competitive strategy adaptive capability is more important than competitive strategy per se for superior performance. Adaptive capability simultaneously undertakes additional secondary roles reinforcing innovation competitive strategy for ...

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

Directory of Open Access Journals (Sweden)

Senol Celik

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

Power capability evaluation for lithium iron phosphate batteries based on multi-parameter constraints estimation

Science.gov (United States)

Wang, Yujie; Pan, Rui; Liu, Chang; Chen, Zonghai; Ling, Qiang

2018-01-01

The battery power capability is intimately correlated with the climbing, braking and accelerating performance of the electric vehicles. Accurate power capability prediction can not only guarantee the safety but also regulate driving behavior and optimize battery energy usage. However, the nonlinearity of the battery model is very complex especially for the lithium iron phosphate batteries. Besides, the hysteresis loop in the open-circuit voltage curve is easy to cause large error in model prediction. In this work, a multi-parameter constraints dynamic estimation method is proposed to predict the battery continuous period power capability. A high-fidelity battery model which considers the battery polarization and hysteresis phenomenon is presented to approximate the high nonlinearity of the lithium iron phosphate battery. Explicit analyses of power capability with multiple constraints are elaborated, specifically the state-of-energy is considered in power capability assessment. Furthermore, to solve the problem of nonlinear system state estimation, and suppress noise interference, the UKF based state observer is employed for power capability prediction. The performance of the proposed methodology is demonstrated by experiments under different dynamic characterization schedules. The charge and discharge power capabilities of the lithium iron phosphate batteries are quantitatively assessed under different time scales and temperatures.

ISOPHOT - Capabilities and performance

DEFF Research Database (Denmark)

Lemke, D.; Klaas, U.; Abolins, J.

1996-01-01

ISOPHOT covers the largest wavelength range on ISO from 2.5 to 240 mu m. Its scientific capabilities include multi filter and multi-aperture photometry, polarimetry, imaging and spectrophotometry. All modes can optionally include a focal plane chopper. The backbone of the photometric calibration...

Analysis of the performance capability of an infrared interior intrusion detector

International Nuclear Information System (INIS)

Dunn, D.R.

1977-01-01

Component performances are required by the LLL assessment procedure for material control and accounting (MC and A) systems. Monitors are an example of an MC and A component whose functions are to process measurements or observations for purposes of detecting abnormalities. This report develops a methodology for characterizing the performance of a class of infrared (IR) interior intrusion monitors or detectors. The methodology is developed around a specific commercial IR detector, the InfrAlarm, manufactured by Barnes Engineering Company (Models 19-124 and 19-115A). Statistical detection models for computing probabilities of detection and false alarms were derived, and the performance capability of the InfrAlarm IR detector was shown using these measures. The results obtained in the performance analysis show that the detection capability of the InfrAlarm is excellent (approx. 1), with very low false alarm rates, for a wide range in target characteristics. These results should be representative and particularly for non-hostile environments

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.

Towards the Next Generation of Space Environment Prediction Capabilities.

Science.gov (United States)

Kuznetsova, M. M.

2015-12-01

Since its establishment more than 15 years ago, the Community Coordinated Modeling Center (CCMC, http://ccmc.gsfc.nasa.gov) is serving as an assess point to expanding collection of state-of-the-art space environment models and frameworks as well as a hub for collaborative development of next generation space weather forecasting systems. In partnership with model developers and international research and operational communities the CCMC integrates new data streams and models from diverse sources into end-to-end space weather impacts predictive systems, identifies week links in data-model & model-model coupling and leads community efforts to fill those gaps. The presentation will highlight latest developments, progress in CCMC-led community-wide projects on testing, prototyping, and validation of models, forecasting techniques and procedures and outline ideas on accelerating implementation of new capabilities in space weather operations.

Predicting emergency diesel starting performance

International Nuclear Information System (INIS)

DeBey, T.M.

1989-01-01

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

Landscape capability models as a tool to predict fine-scale forest bird occupancy and abundance

Science.gov (United States)

Loman, Zachary G.; DeLuca, William; Harrison, Daniel J.; Loftin, Cynthia S.; Rolek, Brian W.; Wood, Petra B.

2018-01-01

ContextSpecies-specific models of landscape capability (LC) can inform landscape conservation design. Landscape capability is “the ability of the landscape to provide the environment […] and the local resources […] needed for survival and reproduction […] in sufficient quantity, quality and accessibility to meet the life history requirements of individuals and local populations.” Landscape capability incorporates species’ life histories, ecologies, and distributions to model habitat for current and future landscapes and climates as a proactive strategy for conservation planning.ObjectivesWe tested the ability of a set of LC models to explain variation in point occupancy and abundance for seven bird species representative of spruce-fir, mixed conifer-hardwood, and riparian and wooded wetland macrohabitats.MethodsWe compiled point count data sets used for biological inventory, species monitoring, and field studies across the northeastern United States to create an independent validation data set. Our validation explicitly accounted for underestimation in validation data using joint distance and time removal sampling.ResultsBlackpoll warbler (Setophaga striata), wood thrush (Hylocichla mustelina), and Louisiana (Parkesia motacilla) and northern waterthrush (P. noveboracensis) models were validated as predicting variation in abundance, although this varied from not biologically meaningful (1%) to strongly meaningful (59%). We verified all seven species models [including ovenbird (Seiurus aurocapilla), blackburnian (Setophaga fusca) and cerulean warbler (Setophaga cerulea)], as all were positively related to occupancy data.ConclusionsLC models represent a useful tool for conservation planning owing to their predictive ability over a regional extent. As improved remote-sensed data become available, LC layers are updated, which will improve predictions.

EPRI MOV performance prediction program

International Nuclear Information System (INIS)

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

1994-01-01

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

Reactivity Insertion Accident (RIA) Capability Status in the BISON Fuel Performance Code

Energy Technology Data Exchange (ETDEWEB)

Williamson, Richard L. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Folsom, Charles Pearson [Idaho National Lab. (INL), Idaho Falls, ID (United States); Pastore, Giovanni [Idaho National Lab. (INL), Idaho Falls, ID (United States); Veeraraghavan, Swetha [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2016-05-01

One of the Challenge Problems being considered within CASL relates to modelling and simulation of Light Water Reactor LWR) fuel under Reactivity Insertion Accident (RIA) conditions. BISON is the fuel performance code used within CASL for LWR fuel under both normal operating and accident conditions, and thus must be capable of addressing the RIA challenge problem. This report outlines required BISON capabilities for RIAs and describes the current status of the code. Information on recent accident capability enhancements, application of BISON to a RIA benchmark exercise, and plans for validation to RIA behavior are included.

Comparing performances of clements, box-cox, Johnson methods with weibull distributions for assessing process capability

Directory of Open Access Journals (Sweden)

Ozlem Senvar

2016-08-01

Full Text Available Purpose: This study examines Clements’ Approach (CA, Box-Cox transformation (BCT, and Johnson transformation (JT methods for process capability assessments through Weibull-distributed data with different parameters to figure out the effects of the tail behaviours on process capability and compares their estimation performances in terms of accuracy and precision. Design/methodology/approach: Usage of process performance index (PPI Ppu is handled for process capability analysis (PCA because the comparison issues are performed through generating Weibull data without subgroups. Box plots, descriptive statistics, the root-mean-square deviation (RMSD, which is used as a measure of error, and a radar chart are utilized all together for evaluating the performances of the methods. In addition, the bias of the estimated values is important as the efficiency measured by the mean square error. In this regard, Relative Bias (RB and the Relative Root Mean Square Error (RRMSE are also considered. Findings: The results reveal that the performance of a method is dependent on its capability to fit the tail behavior of the Weibull distribution and on targeted values of the PPIs. It is observed that the effect of tail behavior is more significant when the process is more capable. Research limitations/implications: Some other methods such as Weighted Variance method, which also give good results, were also conducted. However, we later realized that it would be confusing in terms of comparison issues between the methods for consistent interpretations. Practical implications: Weibull distribution covers a wide class of non-normal processes due to its capability to yield a variety of distinct curves based on its parameters. Weibull distributions are known to have significantly different tail behaviors, which greatly affects the process capability. In quality and reliability applications, they are widely used for the analyses of failure data in order to understand how

Firm Performance and Alliance Capability: The mediating role of culture

NARCIS (Netherlands)

de Man, A.P.; Luvison, D.

2015-01-01

Purpose – Extant literature has looked at the effect of alliance capability and organizational culture on alliance portfolio performance, but the relationship between the two has not been explored. The purpose of this paper is to explore the hypothesis that an alliance supportive culture is not only

Complexity factors and prediction of performance

International Nuclear Information System (INIS)

Braarud, Per Oeyvind

1998-03-01

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

A Field Research on Organizational Learning, Crisis Management Capability and Firm Performance

Directory of Open Access Journals (Sweden)

Cemal Zehir

2016-01-01

Full Text Available Turkey has experienced a series of crises in 1994, 1999 and 2001, which induced remarkable damage in Turkish economy. Thus crisis management has been the main topic in Turkish agenda so many years. Besides crisis management, organizational learning also has been focused as an affective crisis management mean. Crisis preparedness process which is a part of crisis management is vital for any organization’s existence because the emergence of crises is inevitable. Therefore the crisis preparedness has been a topic of increasing importance for organizations seeking an effective way to fight against potential crises. In this context, this research aim to investigate the relationship among the crisis preparedness capability, organizational learning capability and organizational performance.  This survey is conducted on 400 managers of 114 firms operating in the Marmara region.  SPSS 15.0 statistics package program was used to analyze the data obtained from 400 questionnaires. Factor analysis, and reliability analysis have been executed to reveal the reliability of scale, and correlation and regression analyses have been executed to reveal the relationship among the crisis preparedness capability, organizational learning capability, and organizational performance.

A Field Research on Organizational Learning, Crisis Management Capability and Firm Performance

Directory of Open Access Journals (Sweden)

Cemal Zehir

2014-07-01

Full Text Available Turkey has experienced a series of crises in 1994, 1999 and 2001, which induced remarkable damage in Turkish economy. Thus crisis management has been the main topic in Turkish agenda so many years. Besides crisis management, organizational learning also has been focused as an affective crisis management mean. Crisis preparedness process which is a part of crisis management is vital for any organization’s existence because the emergence of crises is inevitable. Therefore the crisis preparedness has been a topic of increasing importance for organizations seeking an effective way to fight against potential crises. In this context, this research aim to investigate the relationship among the crisis preparedness capability, organizational learning capability and organizational performance. This survey is conducted on 400 managers of 114 firms operating in the Marmara region.  SPSS 15.0 statistics package program was used to analyze the data obtained from 400 questionnaires. Factor analysis, and reliability analysis have been executed to reveal the reliability of scale, and correlation and regression analyses have been executed to reveal the relationship among the crisis preparedness capability, organizational learning capability, and organizational performance.

Moving the Hazard Prediction and Assessment Capability to a Distributed, Portable Architecture

Energy Technology Data Exchange (ETDEWEB)

Lee, RW

2002-09-05

The Hazard Prediction and Assessment Capability (HPAC) has been re-engineered from a Windows application with tight binding between computation and a graphical user interface (GUI) to a new distributed object architecture. The key goals of this new architecture are platform portability, extensibility, deployment flexibility, client-server operations, easy integration with other systems, and support for a new map-based GUI. Selection of Java as the development and runtime environment is the major factor in achieving each of the goals, platform portability in particular. Portability is further enforced by allowing only Java components in the client. Extensibility is achieved via Java's dynamic binding and class loading capabilities and a design by interface approach. HPAC supports deployment on a standalone host, as a heavy client in client-server mode with data stored on the client but calculations performed on the server host, and as a thin client with data and calculations on the server host. The principle architectural element supporting deployment flexibility is the use of Universal Resource Locators (URLs) for all file references. Java WebStart{trademark} is used for thin client deployment. Although there were many choices for the object distribution mechanism, the Common Object Request Broker Architecture (CORBA) was chosen to support HPAC client server operation. HPAC complies with version 2.0 of the CORBA standard and does not assume support for pass-by-value method arguments. Execution in standalone mode is expedited by having most server objects run in the same process as client objects, thereby bypassing CORBA object transport. HPAC provides four levels for access by other tools and systems, starting with a Windows library providing transport and dispersion (T&D) calculations and output generation, detailed and more abstract sets of CORBA services, and reusable Java components.

The discriminatory capability of existing scores to predict advanced colorectal neoplasia: a prospective colonoscopy study of 5,899 screening participants.

Science.gov (United States)

Wong, Martin C S; Ching, Jessica Y L; Ng, Simpson; Lam, Thomas Y T; Luk, Arthur K C; Wong, Sunny H; Ng, Siew C; Ng, Simon S M; Wu, Justin C Y; Chan, Francis K L; Sung, Joseph J Y

2016-02-03

We evaluated the performance of seven existing risk scoring systems in predicting advanced colorectal neoplasia in an asymptomatic Chinese cohort. We prospectively recruited 5,899 Chinese subjects aged 50-70 years in a colonoscopy screening programme(2008-2014). Scoring systems under evaluation included two scoring tools from the US; one each from Spain, Germany, and Poland; the Korean Colorectal Screening(KCS) scores; and the modified Asia Pacific Colorectal Screening(APCS) scores. The c-statistics, sensitivity, specificity, positive predictive values(PPVs), and negative predictive values(NPVs) of these systems were evaluated. The resources required were estimated based on the Number Needed to Screen(NNS) and the Number Needed to Refer for colonoscopy(NNR). Advanced neoplasia was detected in 364 (6.2%) subjects. The German system referred the least proportion of subjects (11.2%) for colonoscopy, whilst the KCS scoring system referred the highest (27.4%). The c-statistics of all systems ranged from 0.56-0.65, with sensitivities ranging from 0.04-0.44 and specificities from 0.74-0.99. The modified APCS scoring system had the highest c-statistics (0.65, 95% C.I. 0.58-0.72). The NNS (12-19) and NNR (5-10) were similar among the scoring systems. The existing scoring systems have variable capability to predict advanced neoplasia among asymptomatic Chinese subjects, and further external validation should be performed.

A Comparison of Hazard Prediction and Assessment Capability (HPAC) Software Dose-Rate Contour Plots to a Sample of Local Fallout Data From Test Detonations in the Continental United States, 1945 - 1962

National Research Council Canada - National Science Library

Chancellor, Richard W

2005-01-01

A comparison of Hazard Prediction and Assessment Capability (HPAC) software dose-rate contour plots to a sample of local nuclear fallout data from test detonations in the continental United States, 1945 - 1962, is performed...

Exploring the Mediation Between KM Infrastructure Capabilities and Organisational Performance: The Penetration of Learning by KM Practices

OpenAIRE

Meng-Lin Shih; Shu-Hui Chuang; Chechen Liao

2009-01-01

Previous studies have examined the relationship between knowledge management (KM) infrastructure capabilities and organisational performance. However, most studies neglect the mediating effect of organisational learning by KM practices (OLKMP) in the relationship between KM infrastructure capabilities and organisational performance. This study uses the survey method to discuss the relationships governing KM infrastructure capabilities, OLKMP and organisational performance. Results of the anal...

Predictive capabilities of a two-dimensional model in the ground water transport of radionuclides

International Nuclear Information System (INIS)

Gureghian, A.B.; Beskid, N.J.; Marmer, G.J.

1978-01-01

The discharge of low-level radioactive waste into tailings ponds is a potential source of ground water contamination. The estimation of the radiological hazards related to the ground water transport of radionuclides from tailings retention systems depends on reasonably accurate estimates of the movement of both water and solute. A two-dimensional mathematical model having predictive capability for ground water flow and solute transport has been developed. The flow equation has been solved under steady-state conditions and the mass transport equation under transient conditions. The simultaneous solution of both equations is achieved through the finite element technique using isoparametric elements, based on the Galerkin formulation. However, in contrast to the flow equation solution, the weighting functions used in the solution of the mass transport equation have a non-symmetric form. The predictive capability of the model is demonstrated using an idealized case based on analyses of field data obtained from the sites of operating uranium mills. The pH of the solution, which regulates the variation of the distribution coefficient (K/sub d/) in a particular site, appears to be the most important factor in the assessment of the rate of migration of the elements considered herein

The Impact of Organizational Learning Capability on Product Innovation Performance: Evidence from the Turkish Manufacturing Sector

Directory of Open Access Journals (Sweden)

Özlem Yaşar Uğurlu

2016-02-01

Full Text Available This study aims to examine the effect of organizational learning capability on product innovation performance in the manufacturing sector using empirical data. A survey was conducted with 120 firms that were on the list of Top 1000 Firms of Turkey and registered with the Istanbul Chamber of Industry, to examine the relationship between the dimensions of organizational learning capability and the dimensions of product innovation performance. The findings of the study indicate a positive relationship between organizational learning capability and product innovation performance.

Advancing Environmental Prediction Capabilities for the Polar Regions and Beyond during The Year of Polar Prediction

Science.gov (United States)

Werner, Kirstin; Goessling, Helge; Hoke, Winfried; Kirchhoff, Katharina; Jung, Thomas

2017-04-01

Environmental changes in polar regions open up new opportunities for economic and societal operations such as vessel traffic related to scientific, fishery and tourism activities, and in the case of the Arctic also enhanced resource development. The availability of current and accurate weather and environmental information and forecasts will therefore play an increasingly important role in aiding risk reduction and safety management around the poles. The Year of Polar Prediction (YOPP) has been established by the World Meteorological Organization's World Weather Research Programme as the key activity of the ten-year Polar Prediction Project (PPP; see more on www.polarprediction.net). YOPP is an internationally coordinated initiative to significantly advance our environmental prediction capabilities for the polar regions and beyond, supporting improved weather and climate services. Scheduled to take place from mid-2017 to mid-2019, the YOPP core phase covers an extended period of intensive observing, modelling, prediction, verification, user-engagement and education activities in the Arctic and Antarctic, on a wide range of time scales from hours to seasons. The Year of Polar Prediction will entail periods of enhanced observational and modelling campaigns in both polar regions. With the purpose to close the gaps in the conventional polar observing systems in regions where the observation network is sparse, routine observations will be enhanced during Special Observing Periods for an extended period of time (several weeks) during YOPP. This will allow carrying out subsequent forecasting system experiments aimed at optimizing observing systems in the polar regions and providing insight into the impact of better polar observations on forecast skills in lower latitudes. With various activities and the involvement of a wide range of stakeholders, YOPP will contribute to the knowledge base needed to managing the opportunities and risks that come with polar climate change.

Technological Innovation Capabilities and Firm Performance

OpenAIRE

Richard C.M. Yam; William Lo; Esther P.Y. Tang; Antonio; K.W. Lau

2010-01-01

Technological innovation capability (TIC) is defined as a comprehensive set of characteristics of a firm that facilities and supports its technological innovation strategies. An audit to evaluate the TICs of a firm may trigger improvement in its future practices. Such an audit can be used by the firm for self assessment or third-party independent assessment to identify problems of its capability status. This paper attempts to develop such an auditing framework that can...

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.

Comparing performances of clements, box-cox, Johnson methods with weibull distributions for assessing process capability

Energy Technology Data Exchange (ETDEWEB)

Senvar, O.; Sennaroglu, B.

2016-07-01

This study examines Clements’ Approach (CA), Box-Cox transformation (BCT), and Johnson transformation (JT) methods for process capability assessments through Weibull-distributed data with different parameters to figure out the effects of the tail behaviours on process capability and compares their estimation performances in terms of accuracy and precision. Design/methodology/approach: Usage of process performance index (PPI) Ppu is handled for process capability analysis (PCA) because the comparison issues are performed through generating Weibull data without subgroups. Box plots, descriptive statistics, the root-mean-square deviation (RMSD), which is used as a measure of error, and a radar chart are utilized all together for evaluating the performances of the methods. In addition, the bias of the estimated values is important as the efficiency measured by the mean square error. In this regard, Relative Bias (RB) and the Relative Root Mean Square Error (RRMSE) are also considered. Findings: The results reveal that the performance of a method is dependent on its capability to fit the tail behavior of the Weibull distribution and on targeted values of the PPIs. It is observed that the effect of tail behavior is more significant when the process is more capable. Research limitations/implications: Some other methods such as Weighted Variance method, which also give good results, were also conducted. However, we later realized that it would be confusing in terms of comparison issues between the methods for consistent interpretations... (Author)

Towards a National Space Weather Predictive Capability

Science.gov (United States)

Fox, N. J.; Ryschkewitsch, M. G.; Merkin, V. G.; Stephens, G. K.; Gjerloev, J. W.; Barnes, R. J.; Anderson, B. J.; Paxton, L. J.; Ukhorskiy, A. Y.; Kelly, M. A.; Berger, T. E.; Bonadonna, L. C. M. F.; Hesse, M.; Sharma, S.

2015-12-01

National needs in the area of space weather informational and predictive tools are growing rapidly. Adverse conditions in the space environment can cause disruption of satellite operations, communications, navigation, and electric power distribution grids, leading to a variety of socio-economic losses and impacts on our security. Future space exploration and most modern human endeavors will require major advances in physical understanding and improved transition of space research to operations. At present, only a small fraction of the latest research and development results from NASA, NOAA, NSF and DoD investments are being used to improve space weather forecasting and to develop operational tools. The power of modern research and space weather model development needs to be better utilized to enable comprehensive, timely, and accurate operational space weather tools. The mere production of space weather information is not sufficient to address the needs of those who are affected by space weather. A coordinated effort is required to support research-to-applications transition efforts and to develop the tools required those who rely on this information. In this presentation we will review the space weather system developed for the Van Allen Probes mission, together with other datasets, tools and models that have resulted from research by scientists at JHU/APL. We will look at how these, and results from future missions such as Solar Probe Plus, could be applied to support space weather applications in coordination with other community assets and capabilities.

Space Environmental Effects (SEE) Testing Capability: NASA/Marshall Space Flight Center

Science.gov (United States)

DeWittBurns, H.; Crave, Paul; Finckenor, Miria; Finchum, Charles; Nehls, Mary; Schneider, Todd; Vaughn, Jason

2012-01-01

Understanding the effects of the space environment on materials and systems is fundamental and essential for mission success. If not properly understood and designed for, the space environment can lead to materials degradation, reduction of functional lifetime, and system failure. Ground based testing is critical in predicting performance NASA/MSFC's expertise and capabilities make up the most complete SEE testing capability available.

Comparison of in-plant performance test data with analytic prediction of reactor safety system injection transient (U)

International Nuclear Information System (INIS)

Roy, B.N.; Neill, C.H. Jr.

1993-01-01

This paper compares the performance test data from injection transients for both of the subsystems of the Supplementary Safety System of the Savannah River Site production reactor with analytical predictions from an in-house thermal hydraulic computer code. The code was initially developed for design validation of the new Supplementary Safety System subsystem, but is shown to be equally capable of predicting the performance of the Supplementary Safety System existing subsystem even though the two subsystem transient injections have marked differences. The code itself was discussed and its validation using prototypic tests with simulated fluids was reported in an earlier paper (Roy and Nomm 1991)

The Relationship between Learning Capability and Organizational Performance: A Meta-Analytic Examination

Science.gov (United States)

Goh, Swee C.; Elliott, Catherine; Quon, Tony K.

2012-01-01

Purpose: The purpose of this paper is to present a meta-analysis of a subset of published empirical research papers that measure learning capability and link it to organizational performance. It also seeks to examine both financial and non-financial performance. Design/methodology/approach: In a search of published research on learning capability…

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

Directory of Open Access Journals (Sweden)

Amy S. Nowacki

2013-08-01

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

Capability Assessment and Performance Metrics for the Titan Multispectral Mapping Lidar

Directory of Open Access Journals (Sweden)

Juan Carlos Fernandez-Diaz

2016-11-01

Full Text Available In this paper we present a description of a new multispectral airborne mapping light detection and ranging (lidar along with performance results obtained from two years of data collection and test campaigns. The Titan multiwave lidar is manufactured by Teledyne Optech Inc. (Toronto, ON, Canada and emits laser pulses in the 1550, 1064 and 532 nm wavelengths simultaneously through a single oscillating mirror scanner at pulse repetition frequencies (PRF that range from 50 to 300 kHz per wavelength (max combined PRF of 900 kHz. The Titan system can perform simultaneous mapping in terrestrial and very shallow water environments and its multispectral capability enables new applications, such as the production of false color active imagery derived from the lidar return intensities and the automated classification of target and land covers. Field tests and mapping projects performed over the past two years demonstrate capabilities to classify five land covers in urban environments with an accuracy of 90%, map bathymetry under more than 15 m of water, and map thick vegetation canopies at sub-meter vertical resolutions. In addition to its multispectral and performance characteristics, the Titan system is designed with several redundancies and diversity schemes that have proven to be beneficial for both operations and the improvement of data quality.

Summary of the Blind Test Campaign to predict the High Reynolds number performance of DU00-W-210 airfoil

DEFF Research Database (Denmark)

Yilmaz, Özlem Ceyhan; Pires, Oscar; Munduate, Xabier

2017-01-01

This paper summarizes the results of a blind test campaign organized in the AVATAR project to predict the high Reynolds number performance of a wind turbine airfoil for wind turbine applications. The DU00-W-210 airfoil was tested in the DNW-HDG pressurized wind tunnel in order to investigate...... the flow at high Reynolds number range from 3 to 15 million which is the operating condition of the future large 10MW+ offshore wind turbine rotors. The results of the experiment was used in a blind test campaign to test the prediction capability of the CFD tools used in the wind turbine rotor simulations....... As a result of the blind test campaign it was found that although the codes are in general capable of predicting increased max lift and decreased minimum drag with Re number, the Re trend predictions in particular the glide ratio (lift over drag) need further improvement. In addition to that, the significant...

Dynamic Capabilities

DEFF Research Database (Denmark)

Grünbaum, Niels Nolsøe; Stenger, Marianne

2013-01-01

The findings reveal a positive relationship between dynamic capabilities and innovation performance in the case enterprises, as we would expect. It was, however, not possible to establish a positive relationship between innovation performance and profitability. Nor was there any positive...... relationship between dynamic capabilities and profitability....

RETRAN's role in the development of Northeast Utilities' analytical capabilities

International Nuclear Information System (INIS)

Bonaca, M.V.; Gharakhani, A.; Sterner, R.W.

1983-01-01

The RETRAN code plays an important role in Northeast Utilities' (NUSCO's) safety analysis capabilities. Its ability to predict plant response to operational transients has been shown by several benchmarking efforts. Additionally, it has been utilized in performing both design-basis and bestestimate analyses for NUSCO's operating plants. The decision to use RETRAN as a major contributor to reload analysis efforts at NUSCO was justified by the results of numerous analyses proving RETRAN's capabilities and credibility

Improving environmental performance through unit-level organizational citizenship behaviors for the environment: A capability perspective.

Science.gov (United States)

Alt, Elisa; Spitzeck, Heiko

2016-11-01

Organizational citizenship behaviors for the environment (OCBEs) are increasingly advocated as a means of complementing formal practices in improving environmental performance. Adopting a capability perspective, we propose that a firm's employee involvement capability translates into environmental performance through the manifestation of unit-level OCBEs, and that this relationship is amplified by a shared vision capability. In a cross-country and multi-industry sample of 170 firms, we find support for our hypotheses, shedding light on contextual determinants of OCBEs, and on how firms may engender a positive relationship between top-down environmental initiatives and bottom-up behaviors. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

Ickes, Jacob C.

of improved peak/trough magnitude prediction, better phase prediction of these locations, and a predicted signal with a frequency content more like the flight test data than the CSD code acting alone. Additionally, a tight coupling analysis was performed as a demonstration of the capability and unique aspects of such an analysis. This work shows that away from the center of the flight envelope, the aerodynamic modeling of the CSD code can be replaced with a more accurate set of predictions from a CFD code with an improvement in the aerodynamic results. The better predictions come at substantially increased computational costs between 1,000 and 10,000 processor-hours.

Network Communication as a Service-Oriented Capability

Energy Technology Data Exchange (ETDEWEB)

Johnston, William; Johnston, William; Metzger, Joe; Collins, Michael; Burrescia, Joseph; Dart, Eli; Gagliardi, Jim; Guok, Chin; Oberman, Kevin; O' Conner, Mike

2008-01-08

In widely distributed systems generally, and in science-oriented Grids in particular, software, CPU time, storage, etc., are treated as"services" -- they can be allocated and used with service guarantees that allows them to be integrated into systems that perform complex tasks. Network communication is currently not a service -- it is provided, in general, as a"best effort" capability with no guarantees and only statistical predictability. In order for Grids (and most types of systems with widely distributed components) to be successful in performing the sustained, complex tasks of large-scale science -- e.g., the multi-disciplinary simulation of next generation climate modeling and management and analysis of the petabytes of data that will come from the next generation of scientific instrument (which is very soon for the LHC at CERN) -- networks must provide communication capability that is service-oriented: That is it must be configurable, schedulable, predictable, and reliable. In order to accomplish this, the research and education network community is undertaking a strategy that involves changes in network architecture to support multiple classes of service; development and deployment of service-oriented communication services, and; monitoring and reporting in a form that is directly useful to the application-oriented system so that it may adapt to communications failures. In this paper we describe ESnet's approach to each of these -- an approach that is part of an international community effort to have intra-distributed system communication be based on a service-oriented capability.

The Real World Significance of Performance Prediction

Science.gov (United States)

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

2012-01-01

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

Organizational capabilities and bottom line performance : The relationship between organizational architecture and strategic performance of business units in Dutch headquartered multinationals

NARCIS (Netherlands)

Eikelenboom, B.L.

2005-01-01

This study addresses a key question in business: do organizational capabilities relate to bottom line performance? It is a hard struggle to assess intangible, organizational capabilities, but due to web-based technology, serious advances have been made to measure organizational architecture, a

Advanced Simulation Capability for Environmental Management: Development and Demonstrations - 12532

Energy Technology Data Exchange (ETDEWEB)

Freshley, Mark D.; Freedman, Vicky; Gorton, Ian [Pacific Northwest National Laboratory, MSIN K9-33, P.O. Box 999, Richland, WA 99352 (United States); Hubbard, Susan S. [Lawrence Berkeley National Laboratory, 1 Cyclotron Road, MS 50B-4230, Berkeley, CA 94720 (United States); Moulton, J. David; Dixon, Paul [Los Alamos National Laboratory, MS B284, P.O. Box 1663, Los Alamos, NM 87544 (United States)

2012-07-01

The U.S. Department of Energy Office of Environmental Management (EM), Technology Innovation and Development is supporting development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is a state-of-the-art scientific tool and approach for understanding and predicting contaminant fate and transport in natural and engineered systems. The modular and open source high-performance computing tool facilitates integrated approaches to modeling and site characterization that enable robust and standardized assessments of performance and risk for EM cleanup and closure activities. The ASCEM project continues to make significant progress in development of capabilities, which are organized into Platform and Integrated Tool-sets and a High-Performance Computing Multi-process Simulator. The Platform capabilities target a level of functionality to allow end-to-end model development, starting with definition of the conceptual model and management of data for model input. The High-Performance Computing capabilities target increased functionality of process model representations, tool-sets for interaction with Platform, and verification and model confidence testing. The new capabilities are demonstrated through working groups, including one focused on the Hanford Site Deep Vadose Zone. The ASCEM program focused on planning during the first year and executing a prototype tool-set for an early demonstration of individual components. Subsequently, ASCEM has focused on developing and demonstrating an integrated set of capabilities, making progress toward a version of the capabilities that can be used to engage end users. Demonstration of capabilities continues to be implemented through working groups. Three different working groups, one focused on EM problems in the deep vadose zone, another investigating attenuation mechanisms for metals and radionuclides, and a third focusing on waste tank performance assessment, continue to make progress. The project

Human resource strategies and organizational performance in the hotel sector: the role of organizational capabilities

Directory of Open Access Journals (Sweden)

Leilianne Michelle Trindade da Silva Barreto

2014-09-01

Full Text Available The general objective of this research was to establish relationships among the settings of human resource strategies, organizational capabilities and organizational performance in the hotel sector. A descriptive and relational study, with a quantitative approach, was developed in hotels of the principal tourist destinations of four states in the Northeast Region of Brazil. The relationships discovered confirm the super positioning proposed by Cameron and Quinn (2006 between the human resource strategies of the Competing Values Model and the organizational capabilities of Ulrich’s (1998 Multiple Roles Model. Complementary analyses present testimony that hotels that are able to develop the four organizational capabilities in a equilibrated form, manage to reach higher performance.

Integration of meanline and one-dimensional methods for prediction of pulsating performance of a turbocharger turbine

International Nuclear Information System (INIS)

Chiong, M.S.; Rajoo, S.; Romagnoli, A.; Costall, A.W.; Martinez-Botas, R.F.

2014-01-01

Highlights: • Unsteady turbine performance prediction by integrating the 1-D and meanline models. • The optimum discretization length/diameter ratio is identified. • No improvement is gained by increasing the number of rotor entries. • The predicted instantaneous mass flow and output power are analysed in detail. - Abstract: Stringent emission regulations are driving engine manufacturers to increase investment into enabling technologies to achieve better specific fuel consumption, thermal efficiency and most importantly carbon reduction. Engine downsizing is seen as a key enabler to successfully achieve all of these requirements. Boosting through turbocharging is widely regarded as one of the most promising technologies for engine downsizing. However, the wide range of engine speeds and loads requires enhanced quality of engine-turbocharger matching, compared to the conventional approach which considers only the full load condition. Thus, development of computational models capable of predicting the unsteady behaviour of a turbocharger turbine is crucial to the overall matching process. A purely one-dimensional (1D) turbine model is capable of good unsteady swallowing capacity predictions, however it has not been fully exploited to predict instantaneous turbine power. On the contrary, meanline models (zero-dimensional) are regarded as a good tool to determine turbine efficiency in steady state but they do not include any information about the pressure wave action occurring within the turbine. This paper explores an alternative methodology to predict instantaneous turbine power and swallowing capacity by integrating one-dimensional and meanline models. A single entry mixed-flow turbine is modelled using a 1D gas dynamic code to solve the unsteady flow state in the volute, consequently used as the input for a meanline model to evaluate the instantaneous turbine power. The key in the effectiveness of this methodology relies on the synchronisation of the flow

Leak detection capability in CANDU reactors

Energy Technology Data Exchange (ETDEWEB)

Azer, N.; Barber, D.H.; Boucher, P.J. [and others

1997-04-01

This paper addresses the moisture leak detection capability of Ontario Hydro CANDU reactors which has been demonstrated by performing tests on the reactor. The tests confirmed the response of the annulus gas system (AGS) to the presence of moisture injected to simulate a pressure tube leak and also confirmed the dew point response assumed in leak before break assessments. The tests were performed on Bruce A Unit 4 by injecting known and controlled rates of heavy water vapor. To avoid condensation during test conditions, the amount of moisture which could be injected was small (2-3.5 g/hr). The test response demonstrated that the AGS is capable of detecting and annunciating small leaks. Thus confidence is provided that it would alarm for a growing pressure tube leak where the leak rate is expected to increase to kg/hr rapidly. The measured dew point response was close to that predicted by analysis.

Leak detection capability in CANDU reactors

International Nuclear Information System (INIS)

Azer, N.; Barber, D.H.; Boucher, P.J.

1997-01-01

This paper addresses the moisture leak detection capability of Ontario Hydro CANDU reactors which has been demonstrated by performing tests on the reactor. The tests confirmed the response of the annulus gas system (AGS) to the presence of moisture injected to simulate a pressure tube leak and also confirmed the dew point response assumed in leak before break assessments. The tests were performed on Bruce A Unit 4 by injecting known and controlled rates of heavy water vapor. To avoid condensation during test conditions, the amount of moisture which could be injected was small (2-3.5 g/hr). The test response demonstrated that the AGS is capable of detecting and annunciating small leaks. Thus confidence is provided that it would alarm for a growing pressure tube leak where the leak rate is expected to increase to kg/hr rapidly. The measured dew point response was close to that predicted by analysis

Understanding the origin of radon indoors: Building a predictive capability

International Nuclear Information System (INIS)

Sextro, R.G.

1985-12-01

Indoor radon concentrations one to two orders of magnitude higher than the US average of ∼60 Bq m -3 (∼1.5 pCi L -1 ) are not uncommon, and concentrations greater than 4000 Bq m -3 have been observed in houses in areas with no known artificially-enhanced radon sources. In general, source categories for indoor radon are well known: soil, domestic water, building materials, outdoor air, and natural gas. Soil is thought to be a major source of indoor radon, either through molecular diffusion (usually a minor component) or convective flow of soil gas. While soil gas flow into residences has been demonstrated, no detailed understanding of the important factors affecting the source strength of radon from soil has yet emerged. Preliminary work in this area has identified a number of likely issues, including the concentration of radium in the soil, the emanating fraction, soil type, soil moisture content, and other factors that would influence soil permeability and soil gas transport. Because a significant number of dwellings are expected to have indoor radon concentrations above guideline levels, a predictive capability is needed that would help identify geographical areas having the potential for high indoor concentrations. This paper reviews the preliminary work that has been done to identify important soil and building characteristics that influence the migration of radon and outlines the areas of further research necessary for development of a predictive method. 32 refs., 4 figs

Stakeholder Management Capability and Performance in Brazilian Cooperatives

Directory of Open Access Journals (Sweden)

Yeda Maria Pereira Pavão

2015-09-01

Full Text Available Objective – The aim of this paper is to relate Stakeholder Management Capability (SMC to economic-financial and social-environmental performance. Design/methodology/approach – Data collection occurred in 26 states and the Federal District of Brazil. There was validation of 171 questionnaires answered at the strategic and tactical levels in the context of cooperatives in 13 sectors of Brazil’s economy. Structural equation modeling was used as an application to verify the data with the use of exploratory and confirmatory factor analysis. Findings – The results made it possible to verify the relationship between SMC and the social and environmental performance. The coefficient found for the relationship between SMC and economicfinancial performance also had a positive effect. Practical implications – The research results provide evidence that SMC is directly related to the economic-financial and socialenvironmental performance of cooperative organizations. SMC may also contribute to the analytical process of organizations from the statistical dimension and an applied empirical structure. Originality/value – The model reached support in both relationships with significant values, demonstrating that the dimensions and scales used to measure it were satisfactory, validating the proposed model. This finding demonstrates that these organizations have the skills to meet the requirements of and manage stakeholders, even if one person plays different roles, i.e. the cooperative member, which is basically the owner, supplier, consumer and customer.

The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability

Science.gov (United States)

Theurich, Gerhard; DeLuca, C.; Campbell, T.; Liu, F.; Saint, K.; Vertenstein, M.; Chen, J.; Oehmke, R.; Doyle, J.; Whitcomb, T.;

Co-Marketing Capability and its Impact on Marketing Allinace Performance

OpenAIRE

Schögel, Marcus; Herhausen, Dennis

2010-01-01

The aim of this paper is to conceptualize co-marketing capability (CMC) and to explore its relationship to marketing alliance performance. Drawing on a literature review, in-depth interviews with marketing alliance managers and consulting experience concerning co-marketing alliances, we established a multidimensional model of CMC. Using data from 287 chief marketing officers, we empirically show that the identified CMC is an important source of competitive advantage in terms of marketing alli...

Demonstration of a repository performance assessment capability at the US Nuclear Regulatory Commission

International Nuclear Information System (INIS)

Codell, R.; Eisenberg, N.; McCartin, T.; Park, J.

1991-01-01

In order to better review licensing submittals for a High-Level Waste Repository, the US Nuclear Regulatory Commission staff has expanded and improved its capability to conduct performance assessments. A demonstration of this capability used the limited data from Yucca Mountain, Nevada to investigate a small set of scenario classes. Models of release and transport of radionuclides from a repository via the groundwater and direct release pathways provided preliminary estimates of releases to the accessible environment for a 10,000 year simulation time. Latin hypercube sampling of input parameters was used to express results as distributions and to investigate model sensitivities. This methodology demonstration should not be interpreted as an estimate of performance of the proposed repository at Yucca Mountain, Nevada

Improving Performance of LVRT Capability in Single-phase Grid-tied PV Inverters by a Model Predictive Controller

DEFF Research Database (Denmark)

Zangeneh Bighash, Esmaeil; Sadeghzadeh, Seyed Mohammad; Ebrahimzadeh, Esmaeil

2018-01-01

dynamic response and stability. To fill in this gap, this paper presents a fast and robust current controller based on a Model-Predictive Control (MPC) for single-phase PV inverters in other to deal with the LVRT operation. In order to confirm the effectiveness of the proposed controller, results...... the voltage sag period is short, a fast dynamic performance along with a soft behavior of the controller is the most important issue in the LVRT duration. Recently, some methods like Proportional Resonant (PR) controllers, have been presented to control the single phase PV systems in LVRT mode. However......, these methods have had uncertainties in respect their contribution in LVRT mode. In PR controllers, a fast dynamic response can be obtained by tuning the gains of PR controllers for a high bandwidth, but typically the phase margin is decreased. Therefore, the design of PR controllers needs a tradeoff between...

NASA's Evolutionary Xenon Thruster (NEXT) Project Qualification Propellant Throughput Milestone: Performance, Erosion, and Thruster Service Life Prediction After 450 kg

Science.gov (United States)

Herman, Daniel A.

2010-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is tasked with significantly improving and extending the capabilities of current state-of-the-art NSTAR thruster. The service life capability of the NEXT ion thruster is being assessed by thruster wear test and life-modeling of critical thruster components, such as the ion optics and cathodes. The NEXT Long-Duration Test (LDT) was initiated to validate and qualify the NEXT thruster propellant throughput capability. The NEXT thruster completed the primary goal of the LDT; namely to demonstrate the project qualification throughput of 450 kg by the end of calendar year 2009. The NEXT LDT has demonstrated 28,500 hr of operation and processed 466 kg of xenon throughput--more than double the throughput demonstrated by the NSTAR flight-spare. Thruster performance changes have been consistent with a priori predictions. Thruster erosion has been minimal and consistent with the thruster service life assessment, which predicts the first failure mode at greater than 750 kg throughput. The life-limiting failure mode for NEXT is predicted to be loss of structural integrity of the accelerator grid due to erosion by charge-exchange ions.

Exploiting the capabilities of the Sentinel-2 multi spectral instrument for predicting growing stock volume in forest ecosystems

Science.gov (United States)

Mura, Matteo; Bottalico, Francesca; Giannetti, Francesca; Bertani, Remo; Giannini, Raffaello; Mancini, Marco; Orlandini, Simone; Travaglini, Davide; Chirici, Gherardo

2018-04-01

The spatial prediction of growing stock volume is one of the most frequent application of remote sensing for supporting the sustainable management of forest ecosystems. For such a purpose data from active or passive sensors are used as predictor variables in combination with measures taken in the field in sampling plots. The Sentinel-2 (S2) satellites are equipped with a Multi Spectral Instrument (MSI) capable of acquiring 13 bands in the visible and infrared domains with a spatial resolution varying between 10 and 60 m. The present study aimed at evaluating the performance of the S2-MSI imagery for estimating the growing stock volume of forest ecosystems. To do so we used 240 plots measured in two study areas in Italy. The imputation was carried out with eight k-Nearest Neighbours (k-NN) methods available in the open source YaImpute R package. In order to evaluate the S2-MSI performance we repeated the experimental protocol also with two other sets of images acquired by two well-known satellites equipped with multi spectral instruments: Landsat 8 OLI and RapidEye scanner. We found that S2 worked better than Landsat in 37.5% of the cases and in 62.5% of the cases better than RapidEye. In one study area the best performance was obtained with Landsat OLI (RMSD = 6.84%) and in the other with S2 (RMSD = 22.94%), both with the k-NN system based on a distance matrix calculated with the Random Forest algorithm. The results confirmed that S2 images are suitable for predicting growing stock volume obtaining good performances (average RMSD for both the test areas of less than 19%).

Assessment of Process Capability: the case of Soft Drinks Processing Unit

Science.gov (United States)

Sri Yogi, Kottala

2018-03-01

The process capability studies have significant impact in investigating process variation which is important in achieving product quality characteristics. Its indices are to measure the inherent variability of a process and thus to improve the process performance radically. The main objective of this paper is to understand capability of the process being produced within specification of the soft drinks processing unit, a premier brands being marketed in India. A few selected critical parameters in soft drinks processing: concentration of gas volume, concentration of brix, torque of crock has been considered for this study. Assessed some relevant statistical parameters: short term capability, long term capability as a process capability indices perspective. For assessment we have used real time data of soft drinks bottling company which is located in state of Chhattisgarh, India. As our research output suggested reasons for variations in the process which is validated using ANOVA and also predicted Taguchi cost function, assessed also predicted waste monetarily this shall be used by organization for improving process parameters. This research work has substantially benefitted the organization in understanding the various variations of selected critical parameters for achieving zero rejection.

Pulse Power Capability Estimation of Lithium Titanate Oxide-based Batteries

DEFF Research Database (Denmark)

Stroe, Ana-Irina; Swierczynski, Maciej Jozef; Stroe, Daniel Loan

2016-01-01

The pulse power capability (PPC) represents one of the parameters that describe the performance behavior of Lithium-ion batteries independent on the application. Consequently, extended information about the Li-ion battery PPC and its dependence on the operating conditions become necessary. Thus......, this paper analyzes the power capability characteristic of a 13Ah high power Lithium Titanate Oxide-based battery and its dependence on temperature, load current and state-of-charge. Furthermore, a model to predict the discharging PPC of the battery cell at different temperatures and load currents for three...

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.

Development of a generally applicable morphokinetic algorithm capable of predicting the implantation potential of embryos transferred on Day 3

Science.gov (United States)

Petersen, Bjørn Molt; Boel, Mikkel; Montag, Markus; Gardner, David K.

2016-01-01

curve (AUC) to establish the predictive strength of the algorithm. MAIN RESULTS AND THE ROLE OF CHANCE By applying the here developed algorithm (KIDScore), which was based on six annotations (the number of pronuclei equals 2 at the 1-cell stage, time from insemination to pronuclei fading at the 1-cell stage, time from insemination to the 2-cell stage, time from insemination to the 3-cell stage, time from insemination to the 5-cell stage and time from insemination to the 8-cell stage) and ranking the embryos in five groups, the implantation potential of the embryos was predicted with an AUC of 0.650. On Day 3 the KIDScore algorithm was capable of predicting blastocyst development with an AUC of 0.745 and blastocyst quality with an AUC of 0.679. In a comparison of blastocyst prediction including six other published algorithms and KIDScore, only KIDScore and one more algorithm surpassed an algorithm constructed on conventional Alpha/ESHRE consensus timings in terms of predictive power. LIMITATIONS, REASONS FOR CAUTION Some morphological assessments were not available and consequently three of the algorithms in the comparison were not used in full and may therefore have been put at a disadvantage. Algorithms based on implantation data from Day 3 embryo transfers require adjustments to be capable of predicting the implantation potential of Day 5 embryo transfers. The current study is restricted by its retrospective nature and absence of live birth information. Prospective Randomized Controlled Trials should be used in future studies to establish the value of time-lapse technology and morphokinetic evaluation. WIDER IMPLICATIONS OF THE FINDINGS Algorithms applicable to different culture conditions can be developed if based on large data sets of heterogeneous origin. STUDY FUNDING/COMPETING INTEREST(S) This study was funded by Vitrolife A/S, Denmark and Vitrolife AB, Sweden. B.M.P.’s company BMP Analytics is performing consultancy for Vitrolife A/S. M.B. is employed at

Assessment of predictive capability of REFLA/TRAC code for large break LOCA transient in PWR using LOFT L2-5 test data

International Nuclear Information System (INIS)

Akimoto, Hajime; Ohnuki, Akira; Murao, Yoshio

1994-03-01

The REFLA/TRAC code is a best estimate code developed at Japan Atomic Energy Research Institute (JAERI) to provide advanced predictions of thermal hydraulic transient in light water reactors (LWRs). The REFLA/TRAC code uses the TRAC-PF1/MOD1 code as the framework of the code. The REFLA/TRAC code is expected to be used for the calibration of licensing codes, accident analysis, accident simulation of LWRs, and design of advanced LWRs. Several models have been implemented to the TRAC-PF1/MOD1 code at JAERI including reflood model, condensation model, interfacial and wall friction models, etc. These models have been verified using data from various separate effect tests. This report describes an assessment result of the REFLA/TRAC code, which was performed to assess the predictive capability for integral system behavior under large break loss of coolant accident (LBLOCA) using data from the LOFT L2-5 test. The assessment calculation confirmed that the REFLA/TRAC code can predict break mass flow rate, emergency core cooling water bypass and clad temperature excellently in the LOFT L2-5 test. The CPU time of the REFLA/TRAC code was about 1/3 of the TRAC-PF1/MOD1 code. The REFLA/TRAC code can perform stable and fast simulation of thermal hydraulic behavior in PWR LBLOCA with enough accuracy for practical use. (author)

Simulation Study on the Effect of Reduced Inputs of Artificial Neural Networks on the Predictive Performance of the Solar Energy System

Directory of Open Access Journals (Sweden)

Wahiba Yaïci

2017-08-01

Full Text Available In recent years, there has been a strong growth in solar power generation industries. The need for highly efficient and optimised solar thermal energy systems, stand-alone or grid connected photovoltaic systems, has substantially increased. This requires the development of efficient and reliable performance prediction capabilities of solar heat and power production over the day. This contribution investigates the effect of the number of input variables on both the accuracy and the reliability of the artificial neural network (ANN method for predicting the performance parameters of a solar energy system. This paper describes the ANN models and the optimisation process in detail for predicting performance. Comparison with experimental data from a solar energy system tested in Ottawa, Canada during two years under different weather conditions demonstrates the good prediction accuracy attainable with each of the models using reduced input variables. However, it is likely true that the degree of model accuracy would gradually decrease with reduced inputs. Overall, the results of this study demonstrate that the ANN technique is an effective approach for predicting the performance of highly non-linear energy systems. The suitability of the modelling approach using ANNs as a practical engineering tool in renewable energy system performance analysis and prediction is clearly demonstrated.

Capability and opportunity in hot shooting performance: Evidence from top-scoring NBA leaders.

Science.gov (United States)

Chang, Shun-Chuan

2018-01-01

In basketball games, whenever players successfully shoot in streaks, they are expected to demonstrate heightened performance for a stretch of time. Streak shooting in basketball has been debated for more than three decades, but most studies have provided little significant statistical evidence and have labeled random subjective judgments the "hot hand fallacy." To obtain a broader perspective of the hot hand phenomenon and its accompanying influences on the court, this study uses field goal records and optical tracking data from the official NBA database for the entire 2015-2016 season to analyze top-scoring leaders' shooting performances. We first reflect on the meaning of "hot hand" and the "Matthew effect" in actual basketball competition. Second, this study employs statistical models to integrate three different shooting perspectives (field goal percentage, points scored, and attempts). This study's findings shed new light not only on the existence or nonexistence of streaks, but on the roles of capability and opportunity in NBA hot shooting. Furthermore, we show how hot shooting performances resulting from capability and opportunity lead to actual differences for teams.

Capability and opportunity in hot shooting performance: Evidence from top-scoring NBA leaders.

Directory of Open Access Journals (Sweden)

Shun-Chuan Chang

Full Text Available In basketball games, whenever players successfully shoot in streaks, they are expected to demonstrate heightened performance for a stretch of time. Streak shooting in basketball has been debated for more than three decades, but most studies have provided little significant statistical evidence and have labeled random subjective judgments the "hot hand fallacy." To obtain a broader perspective of the hot hand phenomenon and its accompanying influences on the court, this study uses field goal records and optical tracking data from the official NBA database for the entire 2015-2016 season to analyze top-scoring leaders' shooting performances. We first reflect on the meaning of "hot hand" and the "Matthew effect" in actual basketball competition. Second, this study employs statistical models to integrate three different shooting perspectives (field goal percentage, points scored, and attempts. This study's findings shed new light not only on the existence or nonexistence of streaks, but on the roles of capability and opportunity in NBA hot shooting. Furthermore, we show how hot shooting performances resulting from capability and opportunity lead to actual differences for teams.

The new MCNP6 depletion capability

International Nuclear Information System (INIS)

Fensin, M. L.; James, M. R.; Hendricks, J. S.; Goorley, J. T.

2012-01-01

The first MCNP based in-line Monte Carlo depletion capability was officially released from the Radiation Safety Information and Computational Center as MCNPX 2.6.0. Both the MCNP5 and MCNPX codes have historically provided a successful combinatorial geometry based, continuous energy, Monte Carlo radiation transport solution for advanced reactor modeling and simulation. However, due to separate development pathways, useful simulation capabilities were dispersed between both codes and not unified in a single technology. MCNP6, the next evolution in the MCNP suite of codes, now combines the capability of both simulation tools, as well as providing new advanced technology, in a single radiation transport code. We describe here the new capabilities of the MCNP6 depletion code dating from the official RSICC release MCNPX 2.6.0, reported previously, to the now current state of MCNP6. NEA/OECD benchmark results are also reported. The MCNP6 depletion capability enhancements beyond MCNPX 2.6.0 reported here include: (1) new performance enhancing parallel architecture that implements both shared and distributed memory constructs; (2) enhanced memory management that maximizes calculation fidelity; and (3) improved burnup physics for better nuclide prediction. MCNP6 depletion enables complete, relatively easy-to-use depletion calculations in a single Monte Carlo code. The enhancements described here help provide a powerful capability as well as dictate a path forward for future development to improve the usefulness of the technology. (authors)

The New MCNP6 Depletion Capability

International Nuclear Information System (INIS)

Fensin, Michael Lorne; James, Michael R.; Hendricks, John S.; Goorley, John T.

2012-01-01

The first MCNP based inline Monte Carlo depletion capability was officially released from the Radiation Safety Information and Computational Center as MCNPX 2.6.0. Both the MCNP5 and MCNPX codes have historically provided a successful combinatorial geometry based, continuous energy, Monte Carlo radiation transport solution for advanced reactor modeling and simulation. However, due to separate development pathways, useful simulation capabilities were dispersed between both codes and not unified in a single technology. MCNP6, the next evolution in the MCNP suite of codes, now combines the capability of both simulation tools, as well as providing new advanced technology, in a single radiation transport code. We describe here the new capabilities of the MCNP6 depletion code dating from the official RSICC release MCNPX 2.6.0, reported previously, to the now current state of MCNP6. NEA/OECD benchmark results are also reported. The MCNP6 depletion capability enhancements beyond MCNPX 2.6.0 reported here include: (1) new performance enhancing parallel architecture that implements both shared and distributed memory constructs; (2) enhanced memory management that maximizes calculation fidelity; and (3) improved burnup physics for better nuclide prediction. MCNP6 depletion enables complete, relatively easy-to-use depletion calculations in a single Monte Carlo code. The enhancements described here help provide a powerful capability as well as dictate a path forward for future development to improve the usefulness of the technology.

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.

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

Science.gov (United States)

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

2013-09-01

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

Information Technology Managerial Capabilities and Customer Service Performance Among Insurance Firms in Nigeria

Directory of Open Access Journals (Sweden)

Sunday Adekunle Aduloju

2014-12-01

Full Text Available The potential of information technology (IT as an enabler of customer service process continues to generate interest, which is reflected in the large number of IT-related studies. In spite of the significant progress made in this area, research findings have been mixed and inconsistent. Also, the underlying mechanisms by which IT can affect customer service process remain underexamined. The aim of this study was to find out whether IT investments and IT managerial capabilities can account for variations in customer service performance among insurance companies in Nigeria. Using survey research design, the three formulated hypotheses were tested with data gathered from 402 staff at the managerial level drawn from the selected insurance companies in Nigeria, which have been among the largest investors in IT, and where customer service is widely perceived as strategically important. Responses were analyzed using linear regression. A major finding of this study is that IT is a necessary, but not sufficient, condition for sustainable competitive advantage in customer service. Results show that the interaction of IT investments and tacit, path-dependent, and firm-specific IT managerial capabilities significantly explains variations in customer service performance. Consequently, this study recommends that to realize IT-business value, investments in IT should be accompanied by building and developing IT managerial capabilities.

Developing Flexible, High Performance Polymers with Self-Healing Capabilities

Science.gov (United States)

Jolley, Scott T.; Williams, Martha K.; Gibson, Tracy L.; Caraccio, Anne J.

2011-01-01

Flexible, high performance polymers such as polyimides are often employed in aerospace applications. They typically find uses in areas where improved physical characteristics such as fire resistance, long term thermal stability, and solvent resistance are required. It is anticipated that such polymers could find uses in future long duration exploration missions as well. Their use would be even more advantageous if self-healing capability or mechanisms could be incorporated into these polymers. Such innovative approaches are currently being studied at the NASA Kennedy Space Center for use in high performance wiring systems or inflatable and habitation structures. Self-healing or self-sealing capability would significantly reduce maintenance requirements, and increase the safety and reliability performance of the systems into which these polymers would be incorporated. Many unique challenges need to be overcome in order to incorporate a self-healing mechanism into flexible, high performance polymers. Significant research into the incorporation of a self-healing mechanism into structural composites has been carried out over the past decade by a number of groups, notable among them being the University of I1linois [I]. Various mechanisms for the introduction of self-healing have been investigated. Examples of these are: 1) Microcapsule-based healant delivery. 2) Vascular network delivery. 3) Damage induced triggering of latent substrate properties. Successful self-healing has been demonstrated in structural epoxy systems with almost complete reestablishment of composite strength being achieved through the use of microcapsulation technology. However, the incorporation of a self-healing mechanism into a system in which the material is flexible, or a thin film, is much more challenging. In the case of using microencapsulation, healant core content must be small enough to reside in films less than 0.1 millimeters thick, and must overcome significant capillary and surface

Multivariate performance reliability prediction in real-time

International Nuclear Information System (INIS)

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

2001-01-01

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

Predicting Performance in Higher Education Using Proximal Predictors

Science.gov (United States)

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

2016-01-01

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

Center-TRACON Automation System (CTAS) En Route Trajectory Predictor Requirements and Capabilities

Science.gov (United States)

Vivona, Robert; Cate, Karen Tung

2013-01-01

This requirements framework document is designed to support the capture of requirements and capabilities for state-of-the-art trajectory predictors (TPs). This framework has been developed to assist TP experts in capturing a clear, consistent, and cross-comparable set of requirements and capabilities. The goal is to capture capabilities (types of trajectories that can be built), functional requirements (including inputs and outputs), non-functional requirements (including prediction accuracy and computational performance), approaches for constraint relaxation, and input uncertainties. The sections of this framework are based on the Common Trajectory Predictor structure developed by the FAA/Eurocontrol Cooperative R&D Action Plan 16 Committee on Common Trajectory Prediction. It is assumed that the reader is familiar with the Common TP Structure.1 This initial draft is intended as a first cut capture of the En Route TS Capabilities and Requirements. As such, it contains many annotations indicating possible logic errors in the CTAS code or in the description provided. It is intended to work out the details of the annotations with NASA and to update this document at a later time.

Investigating the effects of intellectual capital on organizational performance measurement through organizational learning capabilities

Directory of Open Access Journals (Sweden)

Nabi ollah Nejatizadeh

2013-01-01

Full Text Available During the past few years, there have been growing interests on intellectual capital due to industrial changes on the market. Thus, identifying different ways to create, manage, and evaluate the impact of intellectual capital has remained an open area of research. One of the most important organizational capabilities, which could help organizations create and share knowledge is to effectively use knowledge to create competitive advantage. The primary objective of this study is to investigate the effects of intellectual capital on other components and their impacts on organizational learning capability. The statistical population includes 500 employees of an Iranian organization. The study uses a sample size including 273 people using Morgan statistical table and Cronbach's alpha is calculated as 0.838. The results of this survey indicate that human capital, relational capital and learning capabilities have positive impact on organizational performance. In addition, relational capital positively impacts learning capability and human capital influences positively on relational capital.

HST/WFC3: new capabilities, improved IR detector calibrations, and long-term performance stability

Science.gov (United States)

MacKenty, John W.; Baggett, Sylvia M.; Brammer, Gabriel; Hilbert, Bryan; Long, Knox S.; McCullough, Peter; Riess, Adam G.

2014-08-01

Wide Field Camera 3 (WFC3) is the most used instrument on board the Hubble Space Telescope. Providing a broad range of high quality imaging capabilities from 200 to 1700mn using Silicon CCD and HgCdTe IR detectors, WFC3 is fulfilling both our expectations and its formal requirements. With the re-establishment of the observatory level "spatial scan" capability, we have extended the scientific potential ofWFC3 in multiple directions. These controlled scans, often in combination with low resolution slit-less spectroscopy, enable extremely high precision differential photometric measurements of transiting exo-planets and direct measurement of sources considerably brighter than originally anticipated. In addition, long scans permit the measurement of the separation of star images to accuracies approaching 25 micro-arc seconds (a factor of 10 better than prior FGS or imaging measurements) enables direct parallax observations out to 4 kilo-parsecs. In addition, we have employed this spatial scan capability to both assess and improve the mid­ spatial frequency flat field calibrations. WFC3 uses a Teledyne HgCdTe 1014xl014 pixel Hawaii-lR infrared detector array developed for this mission. One aspect of this detector with implications for many types of science observations is the localized trapping of charge. This manifests itself as both image persistence lasting several hours and as an apparent response variation with photon arrival rate over a large dynamic range. Beyond a generally adopted observing strategy of obtaining multiple observations with small spatial offsets, we have developed a multi-parameter model that accounts for source flux, accumulated signal level, and decay time to predict image persistence at the pixel level. Using a running window through the entirety of the acquired data, we now provide observers with predictions for each individual exposure within several days of its acquisition. Ongoing characterization of the sources on infrared background and

Capability and opportunity in hot shooting performance: Evidence from top-scoring NBA leaders

Science.gov (United States)

2018-01-01

In basketball games, whenever players successfully shoot in streaks, they are expected to demonstrate heightened performance for a stretch of time. Streak shooting in basketball has been debated for more than three decades, but most studies have provided little significant statistical evidence and have labeled random subjective judgments the “hot hand fallacy.” To obtain a broader perspective of the hot hand phenomenon and its accompanying influences on the court, this study uses field goal records and optical tracking data from the official NBA database for the entire 2015–2016 season to analyze top-scoring leaders’ shooting performances. We first reflect on the meaning of “hot hand” and the “Matthew effect” in actual basketball competition. Second, this study employs statistical models to integrate three different shooting perspectives (field goal percentage, points scored, and attempts). This study’s findings shed new light not only on the existence or nonexistence of streaks, but on the roles of capability and opportunity in NBA hot shooting. Furthermore, we show how hot shooting performances resulting from capability and opportunity lead to actual differences for teams. PMID:29432458

Quantifying predictive capability of electronic health records for the most harmful breast cancer

Science.gov (United States)

Wu, Yirong; Fan, Jun; Peissig, Peggy; Berg, Richard; Tafti, Ahmad Pahlavan; Yin, Jie; Yuan, Ming; Page, David; Cox, Jennifer; Burnside, Elizabeth S.

2018-03-01

Improved prediction of the "most harmful" breast cancers that cause the most substantive morbidity and mortality would enable physicians to target more intense screening and preventive measures at those women who have the highest risk; however, such prediction models for the "most harmful" breast cancers have rarely been developed. Electronic health records (EHRs) represent an underused data source that has great research and clinical potential. Our goal was to quantify the value of EHR variables in the "most harmful" breast cancer risk prediction. We identified 794 subjects who had breast cancer with primary non-benign tumors with their earliest diagnosis on or after 1/1/2004 from an existing personalized medicine data repository, including 395 "most harmful" breast cancer cases and 399 "least harmful" breast cancer cases. For these subjects, we collected EHR data comprised of 6 components: demographics, diagnoses, symptoms, procedures, medications, and laboratory results. We developed two regularized prediction models, Ridge Logistic Regression (Ridge-LR) and Lasso Logistic Regression (Lasso-LR), to predict the "most harmful" breast cancer one year in advance. The area under the ROC curve (AUC) was used to assess model performance. We observed that the AUCs of Ridge-LR and Lasso-LR models were 0.818 and 0.839 respectively. For both the Ridge-LR and LassoLR models, the predictive performance of the whole EHR variables was significantly higher than that of each individual component (pbreast cancer, providing the possibility to personalize care for those women at the highest risk in clinical practice.

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.

COMPETITIVENESS, MARKETING ACCESS, AND NETWORK CAPABILITY AND ITS IMPACTS ON MARKETING PERFORMANCE

Directory of Open Access Journals (Sweden)

Teguh Iman Sayekti

2016-12-01

Full Text Available This study is to determine what factors influencingthe performance of SMEs. The population in this study is SMEs in the Central Java. Sample collection was conducted with a purposive sampling method. Criteriaused to take into accountis the SMEs that are already running at leastfortwo years. The sample in this study is intended as the representative of total population,67 (sixty seven. The data were processed and analyzed by computer program of SPSS 20 for Windows. Based on the results of regression analysis, it can be concluded that competitiveness has positive and significant impact on marketing performance marketing access has positive and significant impact on marketing performance. It means that the higher competitiveness and marketing access, the higher its performance. Competitiveness and marketing access have influence on SMEs’ performance through network capability.   

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.

Iowa calibration of MEPDG performance prediction models.

Science.gov (United States)

2013-06-01

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

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

DEFF Research Database (Denmark)

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

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

Simulation and high performance computing-Building a predictive capability for fusion

International Nuclear Information System (INIS)

Strand, P.I.; Coelho, R.; Coster, D.; Eriksson, L.-G.; Imbeaux, F.; Guillerminet, Bernard

2010-01-01

The Integrated Tokamak Modelling Task Force (ITM-TF) is developing an infrastructure where the validation needs, as being formulated in terms of multi-device data access and detailed physics comparisons aiming for inclusion of synthetic diagnostics in the simulation chain, are key components. As the activity and the modelling tools are aimed for general use, although focused on ITER plasmas, a device independent approach to data transport and a standardized approach to data management (data structures, naming, and access) is being developed in order to allow cross-validation between different fusion devices using a single toolset. Extensive work has already gone into, and is continuing to go into, the development of standardized descriptions of the data (Consistent Physical Objects). The longer term aim is a complete simulation platform which is expected to last and be extended in different ways for the coming 30 years. The technical underpinning is therefore of vital importance. In particular the platform needs to be extensible and open-ended to be able to take full advantage of not only today's most advanced technologies but also be able to marshal future developments. As a full level comprehensive prediction of ITER physics rapidly becomes expensive in terms of computing resources, the simulation framework needs to be able to use both grid and HPC computing facilities. Hence data access and code coupling technologies are required to be available for a heterogeneous, possibly distributed, environment. The developments in this area are pursued in a separate project-EUFORIA (EU Fusion for ITER Applications) which is providing about 15 professional person year (ppy) per annum from 14 different institutes. The range and size of the activity is not only technically challenging but is providing some unique management challenges in that a large and geographically distributed team (a truly pan-European set of researchers) need to be coordinated on a fairly detailed

Developing Materials Processing to Performance Modeling Capabilities and the Need for Exascale Computing Architectures (and Beyond)

Energy Technology Data Exchange (ETDEWEB)

Schraad, Mark William [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Physics and Engineering Models; Luscher, Darby Jon [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Advanced Simulation and Computing

2016-09-06

Additive Manufacturing techniques are presenting the Department of Energy and the NNSA Laboratories with new opportunities to consider novel component production and repair processes, and to manufacture materials with tailored response and optimized performance characteristics. Additive Manufacturing technologies already are being applied to primary NNSA mission areas, including Nuclear Weapons. These mission areas are adapting to these new manufacturing methods, because of potential advantages, such as smaller manufacturing footprints, reduced needs for specialized tooling, an ability to embed sensing, novel part repair options, an ability to accommodate complex geometries, and lighter weight materials. To realize the full potential of Additive Manufacturing as a game-changing technology for the NNSA’s national security missions; however, significant progress must be made in several key technical areas. In addition to advances in engineering design, process optimization and automation, and accelerated feedstock design and manufacture, significant progress must be made in modeling and simulation. First and foremost, a more mature understanding of the process-structure-property-performance relationships must be developed. Because Additive Manufacturing processes change the nature of a material’s structure below the engineering scale, new models are required to predict materials response across the spectrum of relevant length scales, from the atomistic to the continuum. New diagnostics will be required to characterize materials response across these scales. And not just models, but advanced algorithms, next-generation codes, and advanced computer architectures will be required to complement the associated modeling activities. Based on preliminary work in each of these areas, a strong argument for the need for Exascale computing architectures can be made, if a legitimate predictive capability is to be developed.

Fuzzy Predictions for Strategic Decision Making

DEFF Research Database (Denmark)

Hallin, Carina Antonia; Andersen, Torben Juul; Tveterås, Sigbjørn

This article theorizes a new way to predict firm performance based on aggregation of sensing among frontline employees about changes in operational capabilities to update strategic action plans. We frame the approach in the context of first- and second-generation prediction markets and outline it...

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

A Compact Methodology to Understand, Evaluate, and Predict the Performance of Automatic Target Recognition

Science.gov (United States)

Li, Yanpeng; Li, Xiang; Wang, Hongqiang; Chen, Yiping; Zhuang, Zhaowen; Cheng, Yongqiang; Deng, Bin; Wang, Liandong; Zeng, Yonghu; Gao, Lei

2014-01-01

This paper offers a compacted mechanism to carry out the performance evaluation work for an automatic target recognition (ATR) system: (a) a standard description of the ATR system's output is suggested, a quantity to indicate the operating condition is presented based on the principle of feature extraction in pattern recognition, and a series of indexes to assess the output in different aspects are developed with the application of statistics; (b) performance of the ATR system is interpreted by a quality factor based on knowledge of engineering mathematics; (c) through a novel utility called “context-probability” estimation proposed based on probability, performance prediction for an ATR system is realized. The simulation result shows that the performance of an ATR system can be accounted for and forecasted by the above-mentioned measures. Compared to existing technologies, the novel method can offer more objective performance conclusions for an ATR system. These conclusions may be helpful in knowing the practical capability of the tested ATR system. At the same time, the generalization performance of the proposed method is good. PMID:24967605

Gate valve performance prediction

International Nuclear Information System (INIS)

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

1994-01-01

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

A predictive model of nuclear power plant crew decision-making and performance in a dynamic simulation environment

Science.gov (United States)

Coyne, Kevin Anthony

The safe operation of complex systems such as nuclear power plants requires close coordination between the human operators and plant systems. In order to maintain an adequate level of safety following an accident or other off-normal event, the operators often are called upon to perform complex tasks during dynamic situations with incomplete information. The safety of such complex systems can be greatly improved if the conditions that could lead operators to make poor decisions and commit erroneous actions during these situations can be predicted and mitigated. The primary goal of this research project was the development and validation of a cognitive model capable of simulating nuclear plant operator decision-making during accident conditions. Dynamic probabilistic risk assessment methods can improve the prediction of human error events by providing rich contextual information and an explicit consideration of feedback arising from man-machine interactions. The Accident Dynamics Simulator paired with the Information, Decision, and Action in a Crew context cognitive model (ADS-IDAC) shows promise for predicting situational contexts that might lead to human error events, particularly knowledge driven errors of commission. ADS-IDAC generates a discrete dynamic event tree (DDET) by applying simple branching rules that reflect variations in crew responses to plant events and system status changes. Branches can be generated to simulate slow or fast procedure execution speed, skipping of procedure steps, reliance on memorized information, activation of mental beliefs, variations in control inputs, and equipment failures. Complex operator mental models of plant behavior that guide crew actions can be represented within the ADS-IDAC mental belief framework and used to identify situational contexts that may lead to human error events. This research increased the capabilities of ADS-IDAC in several key areas. The ADS-IDAC computer code was improved to support additional

Use of the Hazard Prediction and Assessment Capability (HPAC) at the Savannah River Site

International Nuclear Information System (INIS)

BUCKLEY, ROBERT

2004-01-01

This report provides background information on the implementation of the Hazard Prediction and Assessment Capability (HPAC) software package at the Savannah River Site for atmospheric modeling. Developed by the Defense Threat Reduction Agency (DTRA), HPAC is actually a suite of models that allows for various modes of release of radiological, chemical and biological agents, generates interpolated meteorological data fields based on inputted meteorology, and transports the material using a tested transport and diffusion model. A discussion of meteorological data availability for direct use by HPAC is given, and is important for applications to emergency response. An evaluation of the data input methodology for a release from SRS is examined, as well as an application to the World Trade Center attacks in New York City in September 2001. Benefits of the newer versions of HPAC now in use are then discussed. These include access to more meteorological data sources and improved graphical cap abilities. The HPAC software package is another tool to help the Atmospheric Technologies Group (ATG) provide atmospheric transport and dispersion predictions in the event of hazardous atmospheric releases

Reliable predictions of waste performance in a geologic repository

International Nuclear Information System (INIS)

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

1985-08-01

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

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.

Capability and Technology Performance Goals for the Next Step in Affordable Human Exploration of Space

Science.gov (United States)

Linne, Diane L.; Sanders, Gerald B.; Taminger, Karen M.

2015-01-01

The capability for living off the land, commonly called in-situ resource utilization, is finally gaining traction in space exploration architectures. Production of oxygen from the Martian atmosphere is called an enabling technology for human return from Mars, and a flight demonstration to be flown on the Mars 2020 robotic lander is in development. However, many of the individual components still require technical improvements, and system-level trades will be required to identify the best combination of technology options. Based largely on work performed for two recent roadmap activities, this paper defines the capability and technology requirements that will need to be achieved before this game-changing capability can reach its full potential.

Developing Alliance Capabilities

DEFF Research Database (Denmark)

Heimeriks, Koen H.; Duysters, Geert; Vanhaverbeke, Wim

This paper assesses the differential performance effects of learning mechanisms on the development of alliance capabilities. Prior research has suggested that different capability levels could be identified in which specific intra-firm learning mechanisms are used to enhance a firm's alliance...

Mechanism of supply chain coordination cased on dynamic capability framework-the mediating role of manufacturing capabilities

Directory of Open Access Journals (Sweden)

Tiantian Gao

2014-10-01

Full Text Available Purpose: A critical issue has been absent from the conversation on supply chain coordination: how supply chain coordination influence the enterprise performance. This research proposes a new vision to research the performance mechanism of supply chain coordination capability as a dynamic capability. Manufacturing capabilities are existed as mediating role. Design/methodology/approach: Data from International Manufacturing Strategy Survey in 2009 is used to verify the mediating model by hierarchical regression analysis. Findings: The results show that supply chain coordination impacts the enterprise performance positively and indirect impacts the enterprise performance through quality, cost, flexibility. Research implications: This study presents an overview of the impact of supply chain coordination and manufacturing capabilities on enterprise performance, giving grasp for further research of the relationships that exist between them. Originality/value: This finding integrates insights from previous research in dynamic capability framework and supply chain management into a generalization and extension of the performance mechanism in manufacturing enterprises.

Predictive performance models and multiple task performance

Science.gov (United States)

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

1989-01-01

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

A systems engineering cost analysis capability for use in assessing nuclear waste management system cost performance

International Nuclear Information System (INIS)

Shay, M.R.

1990-04-01

The System Engineering Cost Analysis (SECA) capability has been developed by the System Integration Branch of the US Department of Energy's Office of Civilian Radioactive Waste Management for use in assessing the cost performance of alternative waste management system configurations. The SECA capability is designed to provide rapid cost estimates of the waste management system for a given operational scenario and to permit aggregate or detailed cost comparisons for alternative waste system configurations. This capability may be used as an integral part of the System Integration Modeling System (SIMS) or, with appropriate input defining a scenario, as a separate cost analysis model

The psychology of voice and performance capabilities in masculine and feminine cultures and contexts

NARCIS (Netherlands)

Van den Bos, K.; Brockner, J.; Stein, J.H.; Steiner, D.D.; van Yperen, N.W.; Dekker, D.

2010-01-01

In this article, we examine the hypothesis that in masculine cultures or in other contexts that emphasize competitive achievement, those with higher performance capabilities will feel empowered to have input in decisions and, hence, will desire opportunities to voice their opinions about decisions

Performance prediction method for a multi-stage Knudsen pump

Science.gov (United States)

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

2017-12-01

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

Calibration of PMIS pavement performance prediction models.

Science.gov (United States)

2012-02-01

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

CASL Dakota Capabilities Summary

Energy Technology Data Exchange (ETDEWEB)

Adams, Brian M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Simmons, Chris [Univ. of Texas, Austin, TX (United States); Williams, Brian J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-10-10

The Dakota software project serves the mission of Sandia National Laboratories and supports a worldwide user community by delivering state-of-the-art research and robust, usable software for optimization and uncertainty quantification. These capabilities enable advanced exploration and riskinformed prediction with a wide range of computational science and engineering models. Dakota is the verification and validation (V&V) / uncertainty quantification (UQ) software delivery vehicle for CASL, allowing analysts across focus areas to apply these capabilities to myriad nuclear engineering analyses.

Organizational learning capability, firm innovativeness, and firm performance: A meta-analysis

DEFF Research Database (Denmark)

Schlägel, Christopher; Reichel, Lisa-Marie; Richter, Nicole Franziska

In the last twenty years a growing number of empirical studies tested the association be-tween organizational learning capability (OLC) and various economic outcomes. While these studies have provided a better understanding of these relationships, the literature is characterized by the use...... different measures. Based on 53 studies (13,663 firms), we (a) provide a systematic overview of the most commonly used OLC measures, (b) use meta-analytic techniques to highlight the relevance of OLC for firm innovativeness (ruc = .39) and firm perfor-mance (ruc = .41), and (c) explore the unique and common...

'Red Flag' Predictions

DEFF Research Database (Denmark)

Hallin, Carina Antonia; Andersen, Torben Juul; Tveterås, Sigbjørn

-generation prediction markets and outline its unique features as a third-generation prediction market. It is argued that frontline employees gain deep insights when they execute operational activities on an ongoing basis in the organization. The experiential learning from close interaction with internal and external......This conceptual article introduces a new way to predict firm performance based on aggregation of sensing among frontline employees about changes in operational capabilities to update strategic action plans and generate innovations. We frame the approach in the context of first- and second...

Predicting Performance Ratings Using Motivational Antecedents

National Research Council Canada - National Science Library

Zazania, Michelle

1998-01-01

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

Statistical and Machine Learning Models to Predict Programming Performance

OpenAIRE

Bergin, Susan

2006-01-01

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

Are the Performance Based Logistics Prophets Using Science or Alchemy to Create Life-Cycle Affordability? Using Theory to Predict the Efficacy of Performance Based Logistics

Science.gov (United States)

2013-10-01

certain PBL ecosystems , their suppliers, customers, and integrator, can efficiently adapt to environmental changes, and thus predict competitive...capability = budget – cost. An effective entrepreneurial program leader will increase capability (i.e., lethality, maintainability, and/or

Exploring the impact of dynamic capabilities on sustainable supply chain firm's performance using Grey-Analytical Hierarchy Process

DEFF Research Database (Denmark)

Govindan, Kannan; Mathivathanan, Deepak; Haq, A. Noorul

2017-01-01

Dynamic capabilities (DCs) are the inherent capabilities developed by firms through the implementation of Sustainable Supply Chain practices. These DCs serve as a backbone for the firms to achieve competitive advantages in contemporary ever-changing markets. The present study focuses on exploring...... industrial managers to identify specific influential DCs for each performance measure category by overcoming the limitations of few experts through the application of the grey multi criteria decision making system. Identifying and prioritizing performance-specific DCs allow sustainable supply chain oriented...... performance measures identified from the literature. First, through a questionnaire survey with industrial experts from south India as respondents, the initial list of 77 DCs is confined to a list of 40 essential DCs. Second, the shortlisted 40 DCs are grouped under six performance measures; a logical...

How to come to military platforms that are capable to perform the anticipated tasks and missions

NARCIS (Netherlands)

Smit, C.S.; Rijn, T.P.J. van

2010-01-01

A programme has been performed in the Netherlands to realise a framework to support the armed forces during the procurement of (land based) platforms. The aim is to procure platforms that are capable to perform the anticipated tasks and missions. The support comprises two aspects: formulation of

Prediction of Job Performance: Review of Military Studies

Science.gov (United States)

1982-03-01

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

10 CFR 73.25 - Performance capabilities for physical protection of strategic special nuclear material in transit.

Science.gov (United States)

2010-01-01

... strategic special nuclear material in transit. 73.25 Section 73.25 Energy NUCLEAR REGULATORY COMMISSION... Transit § 73.25 Performance capabilities for physical protection of strategic special nuclear material in transit. (a) To meet the general performance objective and requirements of § 73.20 an in-transit physical...

Predictive Capability of the Compressible MRG Equation for an Explosively Driven Particle with Validation

Science.gov (United States)

Garno, Joshua; Ouellet, Frederick; Koneru, Rahul; Balachandar, Sivaramakrishnan; Rollin, Bertrand

2017-11-01

An analytic model to describe the hydrodynamic forces on an explosively driven particle is not currently available. The Maxey-Riley-Gatignol (MRG) particle force equation generalized for compressible flows is well-studied in shock-tube applications, and captures the evolution of particle force extracted from controlled shock-tube experiments. In these experiments only the shock-particle interaction was examined, and the effects of the contact line were not investigated. In the present work, the predictive capability of this model is considered for the case where a particle is explosively ejected from a rigid barrel into ambient air. Particle trajectory information extracted from simulations is compared with experimental data. This configuration ensures that both the shock and contact produced by the detonation will influence the motion of the particle. The simulations are carried out using a finite volume, Euler-Lagrange code using the JWL equation of state to handle the explosive products. This work was supported by the U.S. Department of Energy, National Nuclear Security Administration, Advanced Simulation and Computing Program, as a Cooperative Agreement under the Predictive Science Academic Alliance Program,under Contract No. DE-NA0002378.

Off-Gas Adsorption Model Capabilities and Recommendations

Energy Technology Data Exchange (ETDEWEB)

Lyon, Kevin L. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Welty, Amy K. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Law, Jack [Idaho National Lab. (INL), Idaho Falls, ID (United States); Ladshaw, Austin [Georgia Inst. of Technology, Atlanta, GA (United States); Yiacoumi, Sotira [Georgia Inst. of Technology, Atlanta, GA (United States); Tsouris, Costas [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2016-03-01

Off-gas treatment is required to reduce emissions from aqueous fuel reprocessing. Evaluating the products of innovative gas adsorption research requires increased computational simulation capability to more effectively transition from fundamental research to operational design. Early modeling efforts produced the Off-Gas SeParation and REcoverY (OSPREY) model that, while efficient in terms of computation time, was of limited value for complex systems. However, the computational and programming lessons learned in development of the initial model were used to develop Discontinuous Galerkin OSPREY (DGOSPREY), a more effective model. Initial comparisons between OSPREY and DGOSPREY show that, while OSPREY does reasonably well to capture the initial breakthrough time, it displays far too much numerical dispersion to accurately capture the real shape of the breakthrough curves. DGOSPREY is a much better tool as it utilizes a more stable set of numerical methods. In addition, DGOSPREY has shown the capability to capture complex, multispecies adsorption behavior, while OSPREY currently only works for a single adsorbing species. This capability makes DGOSPREY ultimately a more practical tool for real world simulations involving many different gas species. While DGOSPREY has initially performed very well, there is still need for improvement. The current state of DGOSPREY does not include any micro-scale adsorption kinetics and therefore assumes instantaneous adsorption. This is a major source of error in predicting water vapor breakthrough because the kinetics of that adsorption mechanism is particularly slow. However, this deficiency can be remedied by building kinetic kernels into DGOSPREY. Another source of error in DGOSPREY stems from data gaps in single species, such as Kr and Xe, isotherms. Since isotherm data for each gas is currently available at a single temperature, the model is unable to predict adsorption at temperatures outside of the set of data currently

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

Science.gov (United States)

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

2012-08-01

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

ADVANCED SIMULATION CAPABILITY FOR ENVIRONMENTAL MANAGEMENT- CURRENT STATUS AND PHASE II DEMONSTRATION RESULTS

Energy Technology Data Exchange (ETDEWEB)

Seitz, R.

2013-02-26

The U.S. Department of Energy (USDOE) Office of Environmental Management (EM), Office of Soil and Groundwater, is supporting development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is a state-of-the-art scientific tool and approach for understanding and predicting contaminant fate and transport in natural and engineered systems. The modular and open source high-performance computing tool facilitates integrated approaches to modeling and site characterization that enable robust and standardized assessments of performance and risk for EM cleanup and closure activities. The ASCEM project continues to make significant progress in development of computer software capabilities with an emphasis on integration of capabilities in FY12. Capability development is occurring for both the Platform and Integrated Toolsets and High-Performance Computing (HPC) Multiprocess Simulator. The Platform capabilities provide the user interface and tools for end-to-end model development, starting with definition of the conceptual model, management of data for model input, model calibration and uncertainty analysis, and processing of model output, including visualization. The HPC capabilities target increased functionality of process model representations, toolsets for interaction with Platform, and verification and model confidence testing. The Platform and HPC capabilities are being tested and evaluated for EM applications in a set of demonstrations as part of Site Applications Thrust Area activities. The Phase I demonstration focusing on individual capabilities of the initial toolsets was completed in 2010. The Phase II demonstration completed in 2012 focused on showcasing integrated ASCEM capabilities. For Phase II, the Hanford Site deep vadose zone (BC Cribs) served as an application site for an end-to-end demonstration of capabilities, with emphasis on integration and linkages between the Platform and HPC components. Other demonstrations

Mean streamline analysis for performance prediction of cross-flow fans

International Nuclear Information System (INIS)

Kim, Jae Won; Oh, Hyoung Woo

2004-01-01

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

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

OpenAIRE

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

2008-01-01

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

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.

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.

The influence of entrepreneurial orientation and family business’s resources and capabilities on marketing performances

OpenAIRE

Charupongsopon, Wittaya; Puriwat, Wilert

2017-01-01

This paper uses data from the Successful Transgenerational Entrepreneurship Practices Project (STEP Project) to investigate the influence of entrepreneurial orientation (EO) and family business’s resources and capabilities towards marketing performance. Previous researches represent an evidence of a relationship between EO and firm performance. Nevertheless, there are limited studies to investigate both psychological and physical aspects of family business like EO and family business’s resour...

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.

The evolution of alliance capabilities

NARCIS (Netherlands)

Heimeriks, K.H.; Duysters, G.M.; Vanhaverbeke, W.P.M.

2004-01-01

This paper assesses the effectiveness and differential performance effects of learning mechanisms on the evolution of alliance capabilities. Relying on the concept of capability lifecycles, prior research has suggested that different capability levels could be identified in which different

A Study Effects Architectural Marketing Capabilities on Performance Marketing unit Based on: Morgan et al case: Past Industry in Tehran

OpenAIRE

Mohammad Reza Dalvi; Robabe Seifi

2014-01-01

Over a period of time architectural marketing capabilities combination of knowledge and skills develop in to capabilities. These architectural marketing capabilities have been identified as one of the important ways firms can achieve a competitive advantage The following research tests effects architectural marketing capabilities on performance marketing unit Based on a survey .a structural equation model was developed to test our hypotheses. the study develops a structural model linking arch...

Investigation on prediction capability of nuclear design parameters for gap configuration in ITER through analysis of the FNS gap streaming experiment

International Nuclear Information System (INIS)

Maekawa, Fujio; Konno, Chikara; Kasugai, Yoshimi; Oyama, Yukio; Uno, Yoshitomo; Maekawa, Hiroshi; Ikeda, Yujiro

2000-01-01

As an R and D Task of shielding neutronics experiment under the Engineering Design Activities of the International Thermonuclear Experimental Reactor (ITER), streaming experiments with simulating a gap configuration formed by two neighboring blanket modules of ITER were carried out at the FNS (Fusion Neutron Source) facility. In this work, prediction capability of various nuclear design parameters was investigated through analysis of the experiments. The Monte Carlo transport calculation code MCNP-4A and the FENDL/E-1.0 and JENDL Fusion File cross section data libraries were used for the analysis with detailed modeling of the experimental conditions. As a result, all the measured quantities were reproduced within about ±30% by the calculations. It was concluded that these calculation tools were capable of predicting nuclear design parameters, such as helium production rates at connection legs of blanket modules to the back plate and nuclear responses in toroidal field coils, with uncertainty of ±30% for the geometry where gap-streaming effect was significant. (author)

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.

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.

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

Science.gov (United States)

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

2018-01-01

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

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.

The influence of ligament modelling strategies on the predictive capability of finite element models of the human knee joint.

Science.gov (United States)

Naghibi Beidokhti, Hamid; Janssen, Dennis; van de Groes, Sebastiaan; Hazrati, Javad; Van den Boogaard, Ton; Verdonschot, Nico

2017-12-08

In finite element (FE) models knee ligaments can represented either by a group of one-dimensional springs, or by three-dimensional continuum elements based on segmentations. Continuum models closer approximate the anatomy, and facilitate ligament wrapping, while spring models are computationally less expensive. The mechanical properties of ligaments can be based on literature, or adjusted specifically for the subject. In the current study we investigated the effect of ligament modelling strategy on the predictive capability of FE models of the human knee joint. The effect of literature-based versus specimen-specific optimized material parameters was evaluated. Experiments were performed on three human cadaver knees, which were modelled in FE models with ligaments represented either using springs, or using continuum representations. In spring representation collateral ligaments were each modelled with three and cruciate ligaments with two single-element bundles. Stiffness parameters and pre-strains were optimized based on laxity tests for both approaches. Validation experiments were conducted to evaluate the outcomes of the FE models. Models (both spring and continuum) with subject-specific properties improved the predicted kinematics and contact outcome parameters. Models incorporating literature-based parameters, and particularly the spring models (with the representations implemented in this study), led to relatively high errors in kinematics and contact pressures. Using a continuum modelling approach resulted in more accurate contact outcome variables than the spring representation with two (cruciate ligaments) and three (collateral ligaments) single-element-bundle representations. However, when the prediction of joint kinematics is of main interest, spring ligament models provide a faster option with acceptable outcome. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessment of Equipment Capability to Perform Reliably under Severe Accident Conditions

International Nuclear Information System (INIS)

2017-07-01

The experience from the last 40 years has shown that severe accidents can subject electrical and instrumentation and control (I&C) equipment to environmental conditions exceeding the equipment’s original design basis assumptions. Severe accident conditions can then cause rapid degradation or damage to various degrees up to complete failure of such equipment. This publication provides the technical basis to consider when assessing the capability of electrical and I&C equipment to perform reliably during a severe accident. It provides examples of calculation tools to determine the environmental parameters as well as examples and methods that Member States can apply to assess equipment reliability.

Plant corrosion: prediction of materials performance

International Nuclear Information System (INIS)

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

1987-01-01

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

A unified tool for performance modelling and prediction

International Nuclear Information System (INIS)

Gilmore, Stephen; Kloul, Leila

2005-01-01

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

Dynamic Simulation of Human Gait Model With Predictive Capability.

Science.gov (United States)

Sun, Jinming; Wu, Shaoli; Voglewede, Philip A

2018-03-01

In this paper, it is proposed that the central nervous system (CNS) controls human gait using a predictive control approach in conjunction with classical feedback control instead of exclusive classical feedback control theory that controls based on past error. To validate this proposition, a dynamic model of human gait is developed using a novel predictive approach to investigate the principles of the CNS. The model developed includes two parts: a plant model that represents the dynamics of human gait and a controller that represents the CNS. The plant model is a seven-segment, six-joint model that has nine degrees-of-freedom (DOF). The plant model is validated using data collected from able-bodied human subjects. The proposed controller utilizes model predictive control (MPC). MPC uses an internal model to predict the output in advance, compare the predicted output to the reference, and optimize the control input so that the predicted error is minimal. To decrease the complexity of the model, two joints are controlled using a proportional-derivative (PD) controller. The developed predictive human gait model is validated by simulating able-bodied human gait. The simulation results show that the developed model is able to simulate the kinematic output close to experimental data.

Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

Science.gov (United States)

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

2014-01-01

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

Advanced Simulation Capability for Environmental Management - Current Status and Phase II Demonstration Results - 13161

Energy Technology Data Exchange (ETDEWEB)

Seitz, Roger R.; Flach, Greg [Savannah River National Laboratory, Savannah River Site, Bldg 773-43A, Aiken, SC 29808 (United States); Freshley, Mark D.; Freedman, Vicky; Gorton, Ian [Pacific Northwest National Laboratory, MSIN K9-33, P.O. Box 999, Richland, WA 99352 (United States); Dixon, Paul; Moulton, J. David [Los Alamos National Laboratory, MS B284, P.O. Box 1663, Los Alamos, NM 87544 (United States); Hubbard, Susan S.; Faybishenko, Boris; Steefel, Carl I.; Finsterle, Stefan [Lawrence Berkeley National Laboratory, 1 Cyclotron Road, MS 50B-4230, Berkeley, CA 94720 (United States); Marble, Justin [Department of Energy, 19901 Germantown Road, Germantown, MD 20874-1290 (United States)

2013-07-01

The U.S. Department of Energy (US DOE) Office of Environmental Management (EM), Office of Soil and Groundwater, is supporting development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is a state-of-the-art scientific tool and approach for understanding and predicting contaminant fate and transport in natural and engineered systems. The modular and open source high-performance computing tool facilitates integrated approaches to modeling and site characterization that enable robust and standardized assessments of performance and risk for EM cleanup and closure activities. The ASCEM project continues to make significant progress in development of computer software capabilities with an emphasis on integration of capabilities in FY12. Capability development is occurring for both the Platform and Integrated Tool-sets and High-Performance Computing (HPC) Multi-process Simulator. The Platform capabilities provide the user interface and tools for end-to-end model development, starting with definition of the conceptual model, management of data for model input, model calibration and uncertainty analysis, and processing of model output, including visualization. The HPC capabilities target increased functionality of process model representations, tool-sets for interaction with Platform, and verification and model confidence testing. The Platform and HPC capabilities are being tested and evaluated for EM applications in a set of demonstrations as part of Site Applications Thrust Area activities. The Phase I demonstration focusing on individual capabilities of the initial tool-sets was completed in 2010. The Phase II demonstration completed in 2012 focused on showcasing integrated ASCEM capabilities. For Phase II, the Hanford Site deep vadose zone (BC Cribs) served as an application site for an end-to-end demonstration of capabilities, with emphasis on integration and linkages between the Platform and HPC components. Other demonstrations

Advanced Simulation Capability for Environmental Management - Current Status and Phase II Demonstration Results - 13161

International Nuclear Information System (INIS)

Seitz, Roger R.; Flach, Greg; Freshley, Mark D.; Freedman, Vicky; Gorton, Ian; Dixon, Paul; Moulton, J. David; Hubbard, Susan S.; Faybishenko, Boris; Steefel, Carl I.; Finsterle, Stefan; Marble, Justin

2013-01-01

The U.S. Department of Energy (US DOE) Office of Environmental Management (EM), Office of Soil and Groundwater, is supporting development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is a state-of-the-art scientific tool and approach for understanding and predicting contaminant fate and transport in natural and engineered systems. The modular and open source high-performance computing tool facilitates integrated approaches to modeling and site characterization that enable robust and standardized assessments of performance and risk for EM cleanup and closure activities. The ASCEM project continues to make significant progress in development of computer software capabilities with an emphasis on integration of capabilities in FY12. Capability development is occurring for both the Platform and Integrated Tool-sets and High-Performance Computing (HPC) Multi-process Simulator. The Platform capabilities provide the user interface and tools for end-to-end model development, starting with definition of the conceptual model, management of data for model input, model calibration and uncertainty analysis, and processing of model output, including visualization. The HPC capabilities target increased functionality of process model representations, tool-sets for interaction with Platform, and verification and model confidence testing. The Platform and HPC capabilities are being tested and evaluated for EM applications in a set of demonstrations as part of Site Applications Thrust Area activities. The Phase I demonstration focusing on individual capabilities of the initial tool-sets was completed in 2010. The Phase II demonstration completed in 2012 focused on showcasing integrated ASCEM capabilities. For Phase II, the Hanford Site deep vadose zone (BC Cribs) served as an application site for an end-to-end demonstration of capabilities, with emphasis on integration and linkages between the Platform and HPC components. Other demonstrations

Nitrate reduction in geologically heterogeneous catchments — A framework for assessing the scale of predictive capability of hydrological models

International Nuclear Information System (INIS)

Refsgaard, Jens Christian; Auken, Esben; Bamberg, Charlotte A.; Christensen, Britt S.B.; Clausen, Thomas; Dalgaard, Esben; Effersø, Flemming; Ernstsen, Vibeke; Gertz, Flemming; Hansen, Anne Lausten; He, Xin; Jacobsen, Brian H.; Jensen, Karsten Høgh; Jørgensen, Flemming; Jørgensen, Lisbeth Flindt; Koch, Julian; Nilsson, Bertel; Petersen, Christian; De Schepper, Guillaume; Schamper, Cyril

2014-01-01

In order to fulfil the requirements of the EU Water Framework Directive nitrate load from agricultural areas to surface water in Denmark needs to be reduced by about 40%. The regulations imposed until now have been uniform, i.e. the same restrictions for all areas independent of the subsurface conditions. Studies have shown that on a national basis about 2/3 of the nitrate leaching from the root zone is reduced naturally, through denitrification, in the subsurface before reaching the streams. Therefore, it is more cost-effective to identify robust areas, where nitrate leaching through the root zone is reduced in the saturated zone before reaching the streams, and vulnerable areas, where no subsurface reduction takes place, and then only impose regulations/restrictions on the vulnerable areas. Distributed hydrological models can make predictions at grid scale, i.e. at much smaller scale than the entire catchment. However, as distributed models often do not include local scale hydrogeological heterogeneities, they are typically not able to make accurate predictions at scales smaller than they are calibrated. We present a framework for assessing nitrate reduction in the subsurface and for assessing at which spatial scales modelling tools have predictive capabilities. A new instrument has been developed for airborne geophysical measurements, Mini-SkyTEM, dedicated to identifying geological structures and heterogeneities with horizontal and lateral resolutions of 30–50 m and 2 m, respectively, in the upper 30 m. The geological heterogeneity and uncertainty are further analysed by use of the geostatistical software TProGS by generating stochastic geological realisations that are soft conditioned against the geophysical data. Finally, the flow paths within the catchment are simulated by use of the MIKE SHE hydrological modelling system for each of the geological models generated by TProGS and the prediction uncertainty is characterised by the variance between the

Nitrate reduction in geologically heterogeneous catchments — A framework for assessing the scale of predictive capability of hydrological models

Energy Technology Data Exchange (ETDEWEB)

Refsgaard, Jens Christian, E-mail: jcr@geus.dk [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Auken, Esben [Department of Earth Sciences, Aarhus University (Denmark); Bamberg, Charlotte A. [City of Aarhus (Denmark); Christensen, Britt S.B. [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Clausen, Thomas [DHI, Hørsholm (Denmark); Dalgaard, Esben [Department of Earth Sciences, Aarhus University (Denmark); Effersø, Flemming [SkyTEM Aps, Beder (Denmark); Ernstsen, Vibeke [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Gertz, Flemming [Knowledge Center for Agriculture, Skejby (Denmark); Hansen, Anne Lausten [Department of Geosciences and Natural Resource Management, University of Copenhagen (Denmark); He, Xin [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Jacobsen, Brian H. [Department of Food and Resource Economics, University of Copenhagen (Denmark); Jensen, Karsten Høgh [Department of Geosciences and Natural Resource Management, University of Copenhagen (Denmark); Jørgensen, Flemming; Jørgensen, Lisbeth Flindt [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Koch, Julian [Department of Geosciences and Natural Resource Management, University of Copenhagen (Denmark); Nilsson, Bertel [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Petersen, Christian [City of Odder (Denmark); De Schepper, Guillaume [Université Laval, Québec (Canada); Schamper, Cyril [Department of Earth Sciences, Aarhus University (Denmark); and others

2014-01-01

In order to fulfil the requirements of the EU Water Framework Directive nitrate load from agricultural areas to surface water in Denmark needs to be reduced by about 40%. The regulations imposed until now have been uniform, i.e. the same restrictions for all areas independent of the subsurface conditions. Studies have shown that on a national basis about 2/3 of the nitrate leaching from the root zone is reduced naturally, through denitrification, in the subsurface before reaching the streams. Therefore, it is more cost-effective to identify robust areas, where nitrate leaching through the root zone is reduced in the saturated zone before reaching the streams, and vulnerable areas, where no subsurface reduction takes place, and then only impose regulations/restrictions on the vulnerable areas. Distributed hydrological models can make predictions at grid scale, i.e. at much smaller scale than the entire catchment. However, as distributed models often do not include local scale hydrogeological heterogeneities, they are typically not able to make accurate predictions at scales smaller than they are calibrated. We present a framework for assessing nitrate reduction in the subsurface and for assessing at which spatial scales modelling tools have predictive capabilities. A new instrument has been developed for airborne geophysical measurements, Mini-SkyTEM, dedicated to identifying geological structures and heterogeneities with horizontal and lateral resolutions of 30–50 m and 2 m, respectively, in the upper 30 m. The geological heterogeneity and uncertainty are further analysed by use of the geostatistical software TProGS by generating stochastic geological realisations that are soft conditioned against the geophysical data. Finally, the flow paths within the catchment are simulated by use of the MIKE SHE hydrological modelling system for each of the geological models generated by TProGS and the prediction uncertainty is characterised by the variance between the

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

Science.gov (United States)

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

2012-01-01

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

Advance simulation capability for environmental management (ASCEM) - 59065

International Nuclear Information System (INIS)

Dixon, Paul; Keating, Elizabeth; Moulton, David; Williamson, Mark; Collazo, Yvette; Gerdes, Kurt; Freshley, Mark; Gorton, Ian; Meza, Juan

2012-01-01

The United States Department Energy (DOE) Office of Environmental Management (EM) determined that uniform application of advanced modeling in the subsurface could help reduce the cost and risks associated with its environmental cleanup mission. In response to this determination, the EM Office of Technology Innovation and Development (OTID), Groundwater and Soil Remediation (GW and S) began the program Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is a state-of-the-art scientific tool and approach for integrating data and scientific understanding to enable prediction of contaminant fate and transport in natural and engineered systems. This initiative supports the reduction of uncertainties and risks associated with EM?s environmental cleanup and closure programs through better understanding and quantifying the subsurface flow and contaminant transport behavior in complex geological systems. This involves the long-term performance of engineered components, including cementitious materials in nuclear waste disposal facilities that may be sources for future contamination of the subsurface. This paper describes the ASCEM tools and approach and the ASCEM programmatic accomplishments completed in 2010 including recent advances and technology transfer. The US Department of Energy Office of Environmental Management has begun development of an Advanced Simulation Capability for Environmental Management, (ASCEM). This program will provide predictions of the end states of contaminated areas allowing for cost and risk reduction of EM remedial activities. ASCEM will provide the tools and approaches necessary to standardize risk and performance assessments across the DOE complex. Through its Phase One demonstration, the ASCEM team has shown value to the EM community in the areas of High Performance Computing, Data Management, Visualization, and Uncertainty Quantification. In 2012, ASCEM will provide an initial limited release of a community code for

IMPACT OF CO-CREATION ON INNOVATION CAPABILITY AND FIRM PERFORMANCE: A STRUCTURAL EQUATION MODELING

Directory of Open Access Journals (Sweden)

FATEMEH HAMIDI

Full Text Available ABSTRACT Traditional firms used to design products, evaluate marketing messages and control product distribution channels with no costumer interface. With the advancements in interaction technologies, however, users can easily make impacts on firms; the interaction between costumers and firms is now in peak condition in comparison to the past and is no longer controlled by firms. Customers are playing two roles of value creators and consumers simultaneously. We examine the role of co-creation on the influences of innovation capability and firm performance. We develop hypotheses and test them using researcher survey data. The results suggest that implement of co-creation partially mediate the effect of process innovation capability. We discuss the implications of these findings for research and practice on the depict and implement of unique value co-creation model.

Using Machine Learning to Predict Student Performance

OpenAIRE

Pojon, Murat

2017-01-01

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

Micro-Vibration Performance Prediction of SEPTA24 Using SMeSim (RUAG Space Mechanism Simulator Tool)

Science.gov (United States)

Omiciuolo, Manolo; Lang, Andreas; Wismer, Stefan; Barth, Stephan; Szekely, Gerhard

2013-09-01

Scientific space missions are currently challenging the performances of their payloads. The performances can be dramatically restricted by micro-vibration loads generated by any moving parts of the satellites, thus by Solar Array Drive Assemblies too. Micro-vibration prediction of SADAs is therefore very important to support their design and optimization in the early stages of a programme. The Space Mechanism Simulator (SMeSim) tool, developed by RUAG, enhances the capability of analysing the micro-vibration emissivity of a Solar Array Drive Assembly (SADA) under a specified set of boundary conditions. The tool is developed in the Matlab/Simulink® environment throughout a library of blocks simulating the different components a SADA is made of. The modular architecture of the blocks, assembled by the user, and the set up of the boundary conditions allow time-domain and frequency-domain analyses of a rigid multi-body model with concentrated flexibilities and coupled- electronic control of the mechanism. SMeSim is used to model the SEPTA24 Solar Array Drive Mechanism and predict its micro-vibration emissivity. SMeSim and the return of experience earned throughout its development and use can now support activities like verification by analysis of micro-vibration emissivity requirements and/or design optimization to minimize the micro- vibration emissivity of a SADA.

Evaluation of remote-sensing-based rainfall products through predictive capability in hydrological runoff modelling

DEFF Research Database (Denmark)

Stisen, Simon; Sandholt, Inge

2010-01-01

SRFEs, Climate Prediction Center MORPHing technique (CMORPH), Tropical Rainfall Measuring Mission (TRMM) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). The best performing SRFE, CPC-FEWS, produced good results with values of R2NS between 0...

Risk Management Capability Maturity and Performance of Complex Product and System (CoPS Projects with an Asian Perspective

Directory of Open Access Journals (Sweden)

Ren, Y.

2014-07-01

Full Text Available Complex Products and Systems (CoPS are high value, technology and engineering-intensive capital goods. The motivation of this study is the persistent high failure rate of CoPS projects, Asian CoPS provider’s weak capability and lack of specific research on CoPS risk management. This paper evaluates risk management maturity level of CoPS projects against a general CoPS risk management capability maturity model (RM-CMM developed by the authors. An Asian based survey was conducted to investigate the value of RM to project performance, and Asian (non-Japanese CoPS implementers’ perceived application of RM practices, their strengths and weaknesses. The survey result shows that higher RM maturity level leads to higher CoPS project performance. It also shows project complexity and uncertainty moderates the relationship between some RM practices and project performance, which implies that a contingency approach should be adopted to manage CoPS risks effectively. In addition, it shows that Asian CoPS implementers are weak in RM process and there are also rooms for improvement in the softer aspects of organizational capabilities and robustness.

Enhancing Foreign Consumer Acceptance The Role of Capabilities of Creating Export-Market Oriented Products in Small and Medium-Sized Enterprises (SMEs

Directory of Open Access Journals (Sweden)

Firmanzah Firmanzah

2008-06-01

Full Text Available The main purpose of this paper is to measure the effects of SMEs capabilities on their export performance. This paper offers a model to test the effects of the capabilities of creating export-market oriented products (EMOPs on increasing SMEs’ export performance. Six hypotheses are developed to analyze causal effects of variables. Using 387 Indonesian SMEs as sample, hypotheses testing highlight the importance of SMEs’ capabilities of building export-market oriented products, which highly follow foreign (export market standards. Hence, these kinds of products increase foreign consumer acceptance. In general, this paper offers a possible explanation to predict the determinants of how SMEs’ can perform in the export market.

Performance Prediction of Constrained Waveform Design for Adaptive Radar

Science.gov (United States)

2016-11-01

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

Application of the aberration ring test (ARTEMIS) to determine lens quality and predict its lithographic performance

Science.gov (United States)

Moers, Marco H. P.; van der Laan, Hans; Zellenrath, Mark; de Boeij, Wim; Beaudry, Neil A.; Cummings, Kevin D.; van Zwol, Adriaan; Brecht, Arthur; Willekers, Rob

2001-09-01

ARTEMISTM (Aberration Ring Test Exposed at Multiple Illumination Settings) is a technique to determine in-situ, full-field, low and high order lens aberrations. In this paper we are analyzing the ARTEMISTM data of PAS5500/750TM DUV Step & Scan systems and its use as a lithographic prediction tool. ARTEMISTM is capable of determining Zernike coefficients up to Z25 with a 3(sigma) reproducibility range from 1.5 to 4.5 nm depending on the aberration type. 3D electric field simulations, that take the extended geometry of the phase shift feature into account, have been used for an improved treatment of the extraction of the spherical Zernike coefficients. Knowledge of the extracted Zernike coefficients allows an accurate prediction of the lithographic performance of the scanner system. This ability is demonstrated for a two bar pattern and an isolation pattern. The RMS difference between the ARTEMISTM-based lithographic prediction and the lithographic measurement is 2.5 nm for the two bar pattern and 3 nm for the isolation pattern. The 3(sigma) reproducibility of the prediction for the two bar pattern is 2.5 nm and 1 nm for the isolation pattern. This is better than the reproducibility of the lithographic measurements themselves.

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.

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

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...

A human capital predictive model for agent performance in contact centres

Directory of Open Access Journals (Sweden)

Chris Jacobs

2011-10-01

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

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

Science.gov (United States)

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

2018-05-01

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

PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes.

Science.gov (United States)

Yu, Nancy Y; Wagner, James R; Laird, Matthew R; Melli, Gabor; Rey, Sébastien; Lo, Raymond; Dao, Phuong; Sahinalp, S Cenk; Ester, Martin; Foster, Leonard J; Brinkman, Fiona S L

2010-07-01

PSORTb has remained the most precise bacterial protein subcellular localization (SCL) predictor since it was first made available in 2003. However, the recall needs to be improved and no accurate SCL predictors yet make predictions for archaea, nor differentiate important localization subcategories, such as proteins targeted to a host cell or bacterial hyperstructures/organelles. Such improvements should preferably be encompassed in a freely available web-based predictor that can also be used as a standalone program. We developed PSORTb version 3.0 with improved recall, higher proteome-scale prediction coverage, and new refined localization subcategories. It is the first SCL predictor specifically geared for all prokaryotes, including archaea and bacteria with atypical membrane/cell wall topologies. It features an improved standalone program, with a new batch results delivery system complementing its web interface. We evaluated the most accurate SCL predictors using 5-fold cross validation plus we performed an independent proteomics analysis, showing that PSORTb 3.0 is the most accurate but can benefit from being complemented by Proteome Analyst predictions. http://www.psort.org/psortb (download open source software or use the web interface). psort-mail@sfu.ca Supplementary data are available at Bioinformatics online.

Enhancing pavement performance prediction models for the Illinois Tollway System

OpenAIRE

Laxmikanth Premkumar; William R. Vavrik

2016-01-01

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

Goal Setting and Expectancy Theory Predictions of Effort and Performance.

Science.gov (United States)

Dossett, Dennis L.; Luce, Helen E.

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

Measuring and Predicting Sleep and Performance During Military Operations

Science.gov (United States)

2012-08-23

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

Porflow Capabilities, Usage, History, and Testing

International Nuclear Information System (INIS)

Collard, L.B.

1998-05-01

To support closure of the Savannah River Site High Level Waste tanks, the PORFLOW computer program is being applied to predict long term movement of residual contaminants from the tanks. The PORFLOW program has greater capabilities than simpler programs that have been used previously, and PORFLOW results have been accepted by state and federal regulators throughout the United States. This document briefly discusses the PORFLOW capabilities and presents lists of reports showing PORFLOW's usage history and testing

Enhancing pavement performance prediction models for the Illinois Tollway System

Directory of Open Access Journals (Sweden)

Laxmikanth Premkumar

2016-01-01

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

Performance Prediction for Large-Scale Nuclear Waste Repositories: Final Report

International Nuclear Information System (INIS)

Glassley, W E; Nitao, J J; Grant, W; Boulos, T N; Gokoffski, M O; Johnson, J W; Kercher, J R; Levatin, J A; Steefel, C I

2001-01-01

The goal of this project was development of a software package capable of utilizing terascale computational platforms for solving subsurface flow and transport problems important for disposal of high level nuclear waste materials, as well as for DOE-complex clean-up and stewardship efforts. We sought to develop a tool that would diminish reliance on abstracted models, and realistically represent the coupling between subsurface fluid flow, thermal effects and chemical reactions that both modify the physical framework of the rock materials and which change the rock mineralogy and chemistry of the migrating fluid. Providing such a capability would enhance realism in models and increase confidence in long-term predictions of performance. Achieving this goal also allows more cost-effective design and execution of monitoring programs needed to evaluate model results. This goal was successfully accomplished through the development of a new simulation tool (NUFT-C). This capability allows high resolution modeling of complex coupled thermal-hydrological-geochemical processes in the saturated and unsaturated zones of the Earth's crust. The code allows consideration of virtually an unlimited number of chemical species and minerals in a multi-phase, non-isothermal environment. Because the code is constructed to utilize the computational power of the tera-scale IBM ASCI computers, simulations that encompass large rock volumes and complex chemical systems can now be done without sacrificing spatial or temporal resolution. The code is capable of doing one-, two-, and three-dimensional simulations, allowing unprecedented evaluation of the evolution of rock properties and mineralogical and chemical change as a function of time. The code has been validated by comparing results of simulations to laboratory-scale experiments, other benchmark codes, field scale experiments, and observations in natural systems. The results of these exercises demonstrate that the physics and chemistry

Capabilities, performance, and future possibilities of high frequency polyphase resonant converters

International Nuclear Information System (INIS)

Reass, W.A.; Baca, D.M.; Bradley, J.T. III; Hardek, T.W.; Kwon, S.I.; Lynch, M.T.; Rees, D.E.

2004-01-01

High Frequency Polyphase Resonant Power Conditioning (PRPC) techniques developed at Los Alamos National Laboratory (LANL) are now being utilized for the Oak Ridge National Laboratory (ORNL) Spallation Neutron Source (SNS) accelerator klystron RF amplifier power systems. Three different styles of polyphase resonant converter modulators were developed for the SNS application. The various systems operate up to 140 kV, or 11 MW pulses, or up to 1.1 MW average power, all from a DC input of +/- 1.2 kV. Component improvements realized with the SNS effort coupled with new applied engineering techniques have resulted in dramatic changes in RF power conditioning topology. As an example, the high-voltage transformers are over 100 times smaller and lighter than equivalent 60 Hz versions. With resonant conversion techniques, load protective networks are not required. A shorted load de-tunes the resonance and little power transfer can occur. This provides for power conditioning systems that are inherently self-protective, with automatic fault 'ride-through' capabilities. By altering the Los Alamos design, higher power and CW power conditioning systems can be realized without further demands of the individual component voltage or current capabilities. This has led to designs that can accommodate 30 MW long pulse applications and megawatt class CW systems with high efficiencies. The same PRPC techniques can also be utilized for lower average power systems (∼250 kW). This permits the use of significantly higher frequency conversion techniques that result in extremely compact systems with short pulse (10 to 100 us) capabilities. These lower power PRPC systems may be suitable for medical Linacs and mobile RF systems. This paper will briefly review the performance achieved for the SNS accelerator and examine designs for high efficiency megawatt class CW systems and 30 MW peak power applications. The devices and designs for compact higher frequency converters utilized for short pulse

Identification of New Tools to Predict Surgical Performance of Novices using a Plastic Surgery Simulator.

Science.gov (United States)

Kazan, Roy; Viezel-Mathieu, Alex; Cyr, Shantale; Hemmerling, Thomas M; Lin, Samuel J; Gilardino, Mirko S

2018-04-09

To identify new tools capable of predicting surgical performance of novices on an augmentation mammoplasty simulator. The pace of technical skills acquisition varies between residents and may necessitate more time than that allotted by residency training before reaching competence. Identifying applicants with superior innate technical abilities might shorten learning curves and the time to reach competence. The objective of this study is to identify new tools that could predict surgical performance of novices on a mammoplasty simulator. We recruited 14 medical students and recorded their performance in 2 skill-games: Mikado and Perplexus Epic, and in 2 video games: Star War Racer (Sony Playstation 3) and Super Monkey Ball 2 (Nintendo Wii). Then, each participant performed an augmentation mammoplasty procedure on a Mammoplasty Part-task Trainer, which allows the simulation of the essential steps of the procedure. The average age of participants was 25.4 years. Correlation studies showed significant association between Perplexus Epic, Star Wars Racer, Super Monkey Ball scores and the modified OSATS score with r s = 0.8491 (p 41 (p = 0.005), and r s = 0.7309 (p < 0.003), but not with the Mikado score r s = -0.0255 (p = 0.9). Linear regressions were strongest for Perplexus Epic and Super Monkey Ball scores with coefficients of determination of 0.59 and 0.55, respectively. A combined score (Perplexus/Super-Monkey-Ball) was computed and showed a significant correlation with the modified OSATS score having an r s = 0.8107 (p < 0.001) and R 2 = 0.75, respectively. This study identified a combination of skill games that correlated to better performance of novices on a surgical simulator. With refinement, such tools could serve to help screen plastic surgery applicants and identify those with higher surgical performance predictors. Copyright © 2018 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

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

Evaluation of the Predictive Capabilities of a Phenomenological Combustion Model for Natural Gas SI Engine

Directory of Open Access Journals (Sweden)

Toman Rastislav

2017-12-01

Full Text Available The current study evaluates the predictive capabilities of a new phenomenological combustion model, available as a part of the GT-Suite software package. It is comprised of two main sub-models: 0D model of in-cylinder flow and turbulence, and turbulent SI combustion model. The 0D in-cylinder flow model (EngCylFlow uses a combined K-k-ε kinetic energy cascade approach to predict the evolution of the in-cylinder charge motion and turbulence, where K and k are the mean and turbulent kinetic energies, and ε is the turbulent dissipation rate. The subsequent turbulent combustion model (EngCylCombSITurb gives the in-cylinder burn rate; based on the calculation of flame speeds and flame kernel development. This phenomenological approach reduces significantly the overall computational effort compared to the 3D-CFD, thus allowing the computation of full engine operating map and the vehicle driving cycles. Model was calibrated using a full map measurement from a turbocharged natural gas SI engine, with swirl intake ports. Sensitivity studies on different calibration methods, and laminar flame speed sub-models were conducted. Validation process for both the calibration and sensitivity studies was concerning the in-cylinder pressure traces and burn rates for several engine operation points achieving good overall results.

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

International Nuclear Information System (INIS)

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

2011-01-01

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

Hanford grout: predicting long-term performance

International Nuclear Information System (INIS)

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

1987-01-01

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

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.

A study on the prediction capability of GOTHIC and HYCA3D code for local hydrogen concentrations

International Nuclear Information System (INIS)

Choi, Y. S.; Lee, W. J.; Lee, J. J.; Park, K. C.

2002-01-01

In this study the prediction capability of GOTHIC and HYCA3D code for local hydrogen concentrations was verified with experimental results. Among the experiments, executed by SNU and other organization inside and outside of the country, the fast transient and the obstacle cases are selected. In case of large subcompartment both the code show good agreement with the experimental data. But in case of small and complex geometry or fast transient the results of GOTHIC code have the large difference from experimental ones. This represents that GOTHIC code is unsuitable for these cases. On the contrary HTCA3D code agrees well with all the experimental data

Predicting space telerobotic operator training performance from human spatial ability assessment

Science.gov (United States)

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

2013-11-01

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

Transforming organizational capabilities in strategizing

DEFF Research Database (Denmark)

Jørgensen, Claus; Friis, Ole Uhrskov; Koch, Christian

2014-01-01

Offshored and networked enterprises are becoming an important if not leading organizational form and this development seriously challenges their organizational capabilities. More specifically, over the last years, SMEs have commenced entering these kinds of arrangements. As the organizational...... capabilities of SMEs are limited at the outset, even more emphasis is needed regarding the issues of developing relevant organizational capabilities. This paper aims at investigating how capabilities evolve during an offshoring process of more than 5 years in two Danish SMEs, i.e. not only short- but long......-term evolvements within the companies. We develop our framework of understanding organizational capabilities drawing on dynamic capability, relational capability and strategy as practice concepts, appreciating the performative aspects of developing new routines. Our two cases are taken from one author’s Ph...

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

Science.gov (United States)

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

2016-01-01

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

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

Science.gov (United States)

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

2015-11-19

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

Geometry and gravity influences on strength capability

Science.gov (United States)

Poliner, Jeffrey; Wilmington, Robert P.; Klute, Glenn K.

1994-01-01

Strength, defined as the capability of an individual to produce an external force, is one of the most important determining characteristics of human performance. Knowledge of strength capabilities of a group of individuals can be applied to designing equipment and workplaces, planning procedures and tasks, and training individuals. In the manned space program, with the high risk and cost associated with spaceflight, information pertaining to human performance is important to ensuring mission success and safety. Knowledge of individual's strength capabilities in weightlessness is of interest within many areas of NASA, including workplace design, tool development, and mission planning. The weightless environment of space places the human body in a completely different context. Astronauts perform a variety of manual tasks while in orbit. Their ability to perform these tasks is partly determined by their strength capability as demanded by that particular task. Thus, an important step in task planning, development, and evaluation is to determine the ability of the humans performing it. This can be accomplished by utilizing quantitative techniques to develop a database of human strength capabilities in weightlessness. Furthermore, if strength characteristics are known, equipment and tools can be built to optimize the operators' performance. This study examined strength in performing a simple task, specifically, using a tool to apply a torque to a fixture.

Dynamic Capabilities and Firm Performance: A Case of Two SMEs in Pakistan

Directory of Open Access Journals (Sweden)

Qazi Muhammad Moinuddin Abro

2011-07-01

Full Text Available This paper investigates the inter-relationship among entrepreneurship, dynamic capabilities and innovation. Entrepreneur\\'s foresights and insights of ICT (Information and Communication Technologies tend to affect their choices of resources and development of dynamic capabilities, leading to different results of innovation. Based on the literature of business innovation and dynamic capabilities, this paper provides a model addressing the links between leadership, with insights and foresights for technology exploration and exploitation, and organizational capabilities of resource integration, learning and transformation to accelerate innovation. A comparative analysis of the two textile manufacturers in Pakistan revealed a cyclical process between the leadership decisions and dynamic capabilities of leveraging ICT for sustained competitiveness in these two SMEs (Small and Medium Sized Enterprises. The result suggests that to build strong capabilities for continuous innovation in today\\'s dynamic business environment, firms need to have leadership with both the attitude and behavior of entrepreneurship, combining the foresight to capture opportunities through ICT and the insight to guide and manage internal resources to achieve ICT-enabled innovation.

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

Directory of Open Access Journals (Sweden)

Patrick Ring

2016-11-01

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

Campus Capability Plan

Energy Technology Data Exchange (ETDEWEB)

Adams, C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Arsenlis, T. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Bailey, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Bergman, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Brase, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Brenner, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Camara, L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Carlton, H. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Cheng, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Chrzanowski, P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Colson, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); East, D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Farrell, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ferranti, L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Gursahani, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hansen, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Helms, L. L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hernandez, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Jeffries, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Larson, D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Lu, K. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); McNabb, D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Mercer, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Skeate, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sueksdorf, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Zucca, B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Le, D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ancria, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Scott, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Leininger, L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Gagliardi, F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Gash, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Bronson, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Chung, B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hobson, B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Meeker, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sanchez, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Zagar, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Quivey, B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sommer, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Atherton, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2017-06-06

Lawrence Livermore National Laboratory Campus Capability Plan for 2018-2028. Lawrence Livermore National Laboratory (LLNL) is one of three national laboratories that are part of the National Nuclear Security Administration. LLNL provides critical expertise to strengthen U.S. security through development and application of world-class science and technology that: Ensures the safety, reliability, and performance of the U.S. nuclear weapons stockpile; Promotes international nuclear safety and nonproliferation; Reduces global danger from weapons of mass destruction; Supports U.S. leadership in science and technology. Essential to the execution and continued advancement of these mission areas are responsive infrastructure capabilities. This report showcases each LLNL capability area and describes the mission, science, and technology efforts enabled by LLNL infrastructure, as well as future infrastructure plans.

Key Future Engineering Capabilities for Human Capital Retention

Science.gov (United States)

Sivich, Lorrie

Projected record retirements of Baby Boomer generation engineers have been predicted to result in significant losses of mission-critical knowledge in space, national security, and future scientific ventures vital to high-technology corporations. No comprehensive review or analysis of engineering capabilities has been performed to identify threats related to the specific loss of mission-critical knowledge posed by the increasing retirement of tenured engineers. Archival data from a single diversified Fortune 500 aerospace manufacturing engineering company's engineering career database were analyzed to ascertain whether relationships linking future engineering capabilities, engineering disciplines, and years of engineering experience could be identified to define critical knowledge transfer models. Chi square, logistic, and linear regression analyses were used to map patterns of discipline-specific, mission-critical knowledge using archival data of engineers' perceptions of engineering capabilities, key developmental experiences, and knowledge learned from their engineering careers. The results from the study were used to document key engineering future capabilities. The results were then used to develop a proposed human capital retention plan to address specific key knowledge gaps of younger engineers as veteran engineers retire. The potential for social change from this study involves informing leaders of aerospace engineering corporations on how to build better quality mentoring or succession plans to fill the void of lost knowledge from retiring engineers. This plan can secure mission-critical knowledge for younger engineers for current and future product development and increased global competitiveness in the technology market.

Atmospheric release advisory capability

International Nuclear Information System (INIS)

Sullivan, T.J.

1981-01-01

The ARAC system (Atmospheric Release Advisory Capability) is described. The system is a collection of people, computers, computer models, topographic data and meteorological input data that together permits a calculation of, in a quasi-predictive sense, where effluent from an accident will migrate through the atmosphere, where it will be deposited on the ground, and what instantaneous and integrated dose an exposed individual would receive

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

Directory of Open Access Journals (Sweden)

Magdalena Ewa Król

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

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

Science.gov (United States)

Król, Magdalena Ewa; Król, Michał

2017-01-01

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

Sandia QIS Capabilities.

Energy Technology Data Exchange (ETDEWEB)

Muller, Richard P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-07-01

Sandia National Laboratories has developed a broad set of capabilities in quantum information science (QIS), including elements of quantum computing, quantum communications, and quantum sensing. The Sandia QIS program is built atop unique DOE investments at the laboratories, including the MESA microelectronics fabrication facility, the Center for Integrated Nanotechnologies (CINT) facilities (joint with LANL), the Ion Beam Laboratory, and ASC High Performance Computing (HPC) facilities. Sandia has invested $75 M of LDRD funding over 12 years to develop unique, differentiating capabilities that leverage these DOE infrastructure investments.

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

Science.gov (United States)

Lee, Ming; Vermillion, Michelle

2018-02-01

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

Package testing capabilities at the Pacific Northwest Laboratory

International Nuclear Information System (INIS)

Taylor, J.M.

1993-01-01

The purpose of this paper is to describe the package testing capabilities at the Pacific Northwest Laboratory (PNL). In the past all of the package testing that was performed at PNL was done on prototype or mocked up radioactive material packaging. Presently, we are developing the capability to perform testing on non-radioactive material packaging. The testing on the non-radioactive material packaging will be done to satisfy the new performance oriented packaging requirements (DOT Docket HM-181, 1991). This paper describes the equipment used to perform the performance oriented packaging tests and also describes some testing capability for testing radioactive material packaging

Predicting the performance of fingerprint similarity searching.

Science.gov (United States)

Vogt, Martin; Bajorath, Jürgen

2011-01-01

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

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

Science.gov (United States)

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

2018-04-10

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

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

CSIR Research Space (South Africa)

Berman, Robert J

2016-11-01

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

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

Space Logistics: Launch Capabilities

Science.gov (United States)

Furnas, Randall B.

1989-01-01

The current maximum launch capability for the United States are shown. The predicted Earth-to-orbit requirements for the United States are presented. Contrasting the two indicates the strong National need for a major increase in Earth-to-orbit lift capability. Approximate weights for planned payloads are shown. NASA is studying the following options to meet the need for a new heavy-lift capability by mid to late 1990's: (1) Shuttle-C for near term (include growth versions); and (2) the Advanced Lauching System (ALS) for the long term. The current baseline two-engine Shuttle-C has a 15 x 82 ft payload bay and an expected lift capability of 82,000 lb to Low Earth Orbit. Several options are being considered which have expanded diameter payload bays. A three-engine Shuttle-C with an expected lift of 145,000 lb to LEO is being evaluated as well. The Advanced Launch System (ALS) is a potential joint development between the Air Force and NASA. This program is focused toward long-term launch requirements, specifically beyond the year 2000. The basic approach is to develop a family of vehicles with the same high reliability as the Shuttle system, yet offering a much greater lift capability at a greatly reduced cost (per pound of payload). The ALS unmanned family of vehicles will provide a low end lift capability equivalent to Titan IV, and a high end lift capability greater than the Soviet Energia if requirements for such a high-end vehicle are defined.In conclusion, the planning of the next generation space telescope should not be constrained to the current launch vehicles. New vehicle designs will be driven by the needs of anticipated heavy users.

How dynamic capabilities drive performance in the Indian IT industry

DEFF Research Database (Denmark)

Holzweber, Markus; Mattsson, Jan; Chadee, Doren

2012-01-01

This study examines key issues and effects of capability management on a fast-growing area of knowledge-intensive global business services – IT outsourcing and offshoring. An exploratory study of Indian companies providing complex process-oriented offshore IT services to their global customers...... is undertaken. The analysis of the data related to the service provider side shows that developing dynamic capabilities is strongly driven by management and top-clients and results in the development of business processes and in establishing a strategic partnership with the client organization. Key findings...

Current limiting capability of diffused resistors

International Nuclear Information System (INIS)

Shedd, W.; Cappelli, J.

1979-01-01

An experimental evaluation of the current limiting capability of dielectrically isolated diffused resistors at transient ionizing dose rates up to 6*10 12 rads(Si)/sec is presented. Existing theoretical predictions of the transient response of diffused resistors are summarized and compared to the experimentally measured values. The test resistors used allow the effects of sheet resistance and geometry on the transient response to be determined. The experimental results show that typical dielectrically isolated diffused resistors maintain adequate current limiting capability for use in radiation hardened integrated circuits

Outcomes of Domestic Standard Problem-03 : Scaling Capability of Facility Data

Energy Technology Data Exchange (ETDEWEB)

Park, Yusun; Youn, Bumsu; Lee, Seung-won; Kim, Won-tae; Kang, Kyoung-ho; Choi, Ki-yong [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2015-10-15

The Domestic Standard Problem (DSP) previous two DSPs provided good research opportunities to many nuclear organizations to understand the capability of the current system-scale safety analysis codes and to find a way for further code development area. Thus, the third DSP program was launched in the 2nd half of the year 2012. As the third DSP exercise (DSP-03), a double-ended guillotine break of the main steam line at an 8% power without loss of off-site power (LOOP) was decided a target scenario. Seventeen domestic organizations joined this DSP exercise. This DSP exercise was performed in an open calculation environment similar to the previous ones. In the present DSP-03, taking into accounts the different levels of code experiences and expertise, three sub-topics were suggested by operating agency. Among them, the investigation on scaling capability of facility data which was the topic of Group A will be discussed in this paper. Agreed participants should perform two calculations with the ATLAS model and the APR1400 model. By comparing major and detailed local parameters from both calculation models, scaling capability of the facility data was investigated. The 38.6 mm MSLB in ATLAS test facility was calculated using SPACE and MARS-KS code. To analyze the effect of scaling on the system behavior, MSLB in APR-1400 was also simulated in this study and following results were obtained. - The code predicted appropriately the overall MSLB experimental data obtained from ATLAS test facility. - The break flow calculated by code was lower than that of experimental data. - And the difference between calculated value and measured value was attributed to the measurement of mass from break flow. - The temperatures of core inlet and outlet of ATLAS test facility were predicted lower than those of experimental data.

Standardizing the performance evaluation of short-term wind prediction models

DEFF Research Database (Denmark)

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

2005-01-01

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

Radiography Capabilities for Matter-Radiation Interactions in Extremes

Energy Technology Data Exchange (ETDEWEB)

Walstrom, Peter Lowell [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Garnett, Robert William [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Chapman, Catherine A. B [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Salazar, Harry Richard [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Otoole, Joseph Alfred [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Barber, Ronald L. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Gomez, Tony Simon [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2015-04-28

The Matter-Radiation Interactions in Extremes (MaRIE) experimental facility will be used to discover and design the advanced materials needed to meet 21st century national security and energy security challenges. This new facility will provide the new tools scientists need to develop next-generation materials that will perform predictably and on-demand for currently unattainable lifetimes in extreme environments. The MaRIE facility is based on upgrades to the existing LANSCE 800-MeV proton linac and a new 12-GeV electron linac and associated X-ray FEL to provide simultaneous multiple probe beams, and new experimental areas. In addition to the high-energy photon probe beam, both electron and proton radiography capabilities will be available at the MaRIE facility. Recently, detailed radiography system studies have been performed to develop conceptual layouts of high-magnification electron and proton radiography systems that can meet the experimental requirements for the expected first experiments to be performed at the facility. A description of the radiography systems, their performance requirements, and a proposed facility layout are presented.

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.

Effect of Marketing Knowledge Competency and Entrepreneurship Orientation on Marketing Capabilities and Marketing Performance of Fishery Smes in Malang City, East Java

OpenAIRE

Charir, Nur Azizah; Primyastanto, Mimit; Abidin, Zainal

2017-01-01

Fishery SMEs of in Malang city is increasing, these SMEs owner face up the challenge of confronting competitor's product. Fishery SMEs can improve their competitiveness through marketing knowledge competency, entrepreneurial orientation (EO) and need to grow the marketing capabilities and improving marketing performance. This study aimed to analyze the effect of marketing knowledge competency on marketing capabilities, EO on marketing capabilities, marketing knowledge competency on marketing ...

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.

Web-based turbine cycle performance analysis for nuclear power plants

International Nuclear Information System (INIS)

Heo, Gyun Young; Lee, Sung Jin; Chang, Soon Heung; Choi, Seong Soo

2000-01-01

As an approach to improve the economical efficiency of operating nuclear power plants, a thermal performance analysis tool for steam turbine cycle has been developed. For the validation and the prediction of the signals used in thermal performance analysis, a few statistical signal processing techniques are integrated. The developed tool provides predicted performance calculation capability that is steady-state wet steam turbine cycle simulation, and measurement performance calculation capability which determines component- and cycle-level performance indexes. Web-based interface with all performance analysis is implemented, so even remote users can achieve performance analysis. Comparing to ASME PTC6 (Performance Test Code 6), the focusing point of the developed tool is historical performance analysis rather than single accurate performance test. The proposed signal processing techniques are validated using actual plant signals, and turbine cycle models are tested by benchmarking with a commercial thermal analysis tool

Predictive testing of performance of metals in HTR service environments

International Nuclear Information System (INIS)

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

1982-01-01

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

A business analytics capability framework

Directory of Open Access Journals (Sweden)

Ranko Cosic

2015-09-01

Full Text Available Business analytics (BA capabilities can potentially provide value and lead to better organisational performance. This paper develops a holistic, theoretically-grounded and practically relevant business analytics capability framework (BACF that specifies, defines and ranks the capabilities that constitute an organisational BA initiative. The BACF was developed in two phases. First, an a priori conceptual framework was developed based on the Resource-Based View theory of the firm and a thematic content analysis of the BA literature. Second, the conceptual framework was further developed and refined using a three round Delphi study involving 16 BA experts. Changes from the Delphi study resulted in a refined and confirmed framework including detailed capability definitions, together with a ranking of the capabilities based on importance. The BACF will help academic researchers and industry practitioners to better understand the capabilities that constitute an organisational BA initiative and their relative importance. In future work, the capabilities in the BACF will be operationalised to measure their as-is status, thus enabling organisations to identify key areas of strength and weakness and prioritise future capability improvement efforts.

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

NARCIS (Netherlands)

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

2014-01-01

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

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).

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

African Journals Online (AJOL)

olayemitoyin

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

Comparing theories' performance in predicting violence.

Science.gov (United States)

Haas, Henriette; Cusson, Maurice

2015-01-01

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

Evaluating the habitat capability model for Merriam's turkeys

Science.gov (United States)

Mark A. Rumble; Stanley H. Anderson

1995-01-01

Habitat capability (HABCAP) models for wildlife assist land managers in predicting the consequences of their management decisions. Models must be tested and refined prior to using them in management planning. We tested the predicted patterns of habitat selection of the R2 HABCAP model using observed patterns of habitats selected by radio-marked Merriam’s turkey (

Entity versus incremental theories predict older adults' memory performance.

Science.gov (United States)

Plaks, Jason E; Chasteen, Alison L

2013-12-01

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

A Performance Evaluation for IT/IS Implementation in Organisation: Preliminary New IT/IS Capability Evaluation (NICE Model

Directory of Open Access Journals (Sweden)

Hafez Salleh

2011-12-01

Full Text Available Most of the traditional IT/IS performance measures are based on productivity and process, which mainly focus on method of investment appraisal. There is a need to produce alternative holistic measurement models that enable soft and hard issues to be measured qualitatively. A New IT/IS Capability Evaluation (NICE framework has been designed to measure the capability of organisations to'successfully implement IT systems' and it is applicable across industries.The idea is to provide managers with measurement tools to enable them to identify where improvements are required within their organisations and to indicate their readiness prior to IT investment. The NICE framework investigates four organisational key elements: IT, Environment, Process and People, and is composed of six progressive stages of maturity that a company can achieve its IT/IS capabilities. For each maturity stage, the NICE framework describes a set of critical success factors that must be in place for the company to achieve each stage.

Marketing Capability in Strategy Research

DEFF Research Database (Denmark)

Ritter, Thomas; Distel, Andreas Philipp

Following the call for a demand-side perspective of strategic management (e.g., Priem et al., 2012), a firm’s marketing capability, i.e. its ability to interact with down-stream stakeholders, becomes a pivotal element in explaining a firm’s competitiveness. While marketing capability is recognized...... in the strategic management literature as an important driver of firm performance, our review of 86 articles reveals a lack of a generally accepted definition of marketing capability, a lack of a common conceptualization as well as differences in the measurement of marketing capability. In order to build a common...... ground for advancing marketing capability research and thus supporting the demand-side perspective in strategic management, we develop an integrative framework to explain the differences and propose a research agenda for developing the field....

Building Alliance Capability: Management Techniques for Superior Alliance Performance

NARCIS (Netherlands)

J.A.J. Draulans (Johan); A-P. de Man (Ard-Pieter); H.W. Volberda (Henk)

2003-01-01

textabstractDespite the fact that they represent a growing element of business strategy, alliances between organisations quite often result in failure. This is partly due to the fact that firms have not built up adequate capabilities to manage alliances. Special management techniques have to be

Hybrid ANN–PLS approach to scroll compressor thermodynamic performance prediction

International Nuclear Information System (INIS)

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

2015-01-01

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

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.

A study of the external cooling capability for the prevention of reactor vessel failure

Energy Technology Data Exchange (ETDEWEB)

Chang, S H; Baek, W P; Moon, S K; Yang, S H; Kim, S H [Korea Advanced Institute of Science Technology, Daejeon (Korea, Republic of)

1994-07-15

This study (a 3-year program) aims to perform a comprehensive assessment of the feasibility of external vessel flooding with respect to advanced pressurized water reactor plants to be built in Korea. During the first year, review of the relevant phenomena and preliminary assessment of the concept have been performed. Also performed is a review of heat transfer correlations for the computer program that will be developed for assessment of the cooling capability of external vessel flooding. Important phenomena that determine the cooling capability of external vessel flooding are (a) the initial transient before formation of molten corium pool, (b) natural convection of in-vessel molten corium pool, (c) radiative heat exchange between the molten corium pool and the upper vessel structures, (d) thermal hydraulics outside the vessel, (e) structural integrity consideration, and (f) long-term phenomena. The adoption of the concept should be decided by considering several factors such as (a) vessel submergence procedure, (b) cooling requirements, (c) vessel design features, (d) steam production, (e) instrumentation needs, and (f) an overall accident management strategy. The external vessel cooling concept looks to be promising. However, further study is required for a reliable decision making. Several correlations are available for the prediction of cooling capability of the present concept. However, it is difficult to define a sufficiently reliable set of correlations; sensitivity studies would be required in assessing the cooling capability with the computer program.

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

Hybrid modeling approach to improve the forecasting capability for the gaseous radionuclide in a nuclear site

International Nuclear Information System (INIS)

Jeong, Hyojoon; Hwang, Wontae; Kim, Eunhan; Han, Moonhee

2012-01-01

Highlights: ► This study is to improve the reliability of air dispersion modeling. ► Tracer experiments assumed gaseous radionuclides were conducted at a nuclear site. ► The performance of a hybrid modeling combined ISC with ANFIS was investigated.. ► Hybrid modeling approach shows better performance rather than a single ISC model. - Abstract: Predicted air concentrations of radioactive materials are important for an environmental impact assessment for the public health. In this study, the performance of a hybrid modeling combined with the industrial source complex (ISC) model and an adaptive neuro-fuzzy inference system (ANFIS) for predicting tracer concentrations was investigated. Tracer dispersion experiments were performed to produce the field data assuming the accidental release of radioactive material. ANFIS was trained in order that the outputs of the ISC model are similar to the measured data. Judging from the higher correlation coefficients between the measured and the calculated ones, the hybrid modeling approach could be an appropriate technique for an improvement of the modeling capability to predict the air concentrations for radioactive materials.

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

Science.gov (United States)

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

2015-01-01

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

Building alliance capability : management techniques for superior alliance performance

NARCIS (Netherlands)

Draulans, J.; Man, de A.P.; Volberda, H.W.

2003-01-01

Despite the fact that they represent a growing element of business strategy, alliances between organisations quite often result in failure. This is partly due to the fact that firms have not built up adequate capabilities to manage alliances. Special management techniques have to be implemented in

Determining Mean Predicted Performance for Army Job Families

National Research Council Canada - National Science Library

Zeidner, Joseph

2003-01-01

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

Using Genome-scale Models to Predict Biological Capabilities

DEFF Research Database (Denmark)

O’Brien, Edward J.; Monk, Jonathan M.; Palsson, Bernhard O.

2015-01-01

Constraint-based reconstruction and analysis (COBRA) methods at the genome scale have been under development since the first whole-genome sequences appeared in the mid-1990s. A few years ago, this approach began to demonstrate the ability to predict a range of cellular functions, including cellul...

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

Science.gov (United States)

Lowmaster, Sara E; Morey, Leslie C

2012-01-01

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

Predicting Document Retrieval System Performance: An Expected Precision Measure.

Science.gov (United States)

Losee, Robert M., Jr.

1987-01-01

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

Design to Process Capabilities: challenges for the use of Process Capability Databases (PCDBs) in development

DEFF Research Database (Denmark)

Eifler, Tobias; Göhler, Simon Moritz; Howard, Thomas J.

2014-01-01

capabilities may lead to low yields and a cost/time overrun, conservatively underestimated capabilities affect quality through the reduced design space, or through increased play, rattle/noise, size or weight. A possibility to overcome the subjective assessment of variation in development projects is a Process...... and Maiti (2012), Breyfogle (2003)]. At the same time, information on the achievable manufacturing accuracy or the supplier’s performance is usually inaccurate and largely qualitative in early development stages. Design decisions as well as the choice of manufacturing processes, therefore, often rely...... Capability Data Base (PCDB) offering valuable insight into the actual or expected performance of production processes (Tata and Thornton, 1999). But although the potential benefits as well as initial challenges for the use of PCDBs have been addressed in earlier research, e. g. by Delaney and Phelan (2008...

Geologic CO2 Sequestration: Predicting and Confirming Performance in Oil Reservoirs and Saline Aquifers

Science.gov (United States)

Johnson, J. W.; Nitao, J. J.; Newmark, R. L.; Kirkendall, B. A.; Nimz, G. J.; Knauss, K. G.; Ziagos, J. P.

2002-05-01

Reducing anthropogenic CO2 emissions ranks high among the grand scientific challenges of this century. In the near-term, significant reductions can only be achieved through innovative sequestration strategies that prevent atmospheric release of large-scale CO2 waste streams. Among such strategies, injection into confined geologic formations represents arguably the most promising alternative; and among potential geologic storage sites, oil reservoirs and saline aquifers represent the most attractive targets. Oil reservoirs offer a unique "win-win" approach because CO2 flooding is an effective technique of enhanced oil recovery (EOR), while saline aquifers offer immense storage capacity and widespread distribution. Although CO2-flood EOR has been widely used in the Permian Basin and elsewhere since the 1980s, the oil industry has just recently become concerned with the significant fraction of injected CO2 that eludes recycling and is therefore sequestered. This "lost" CO2 now has potential economic value in the growing emissions credit market; hence, the industry's emerging interest in recasting CO2 floods as co-optimized EOR/sequestration projects. The world's first saline aquifer storage project was also catalyzed in part by economics: Norway's newly imposed atmospheric emissions tax, which spurred development of Statoil's unique North Sea Sleipner facility in 1996. Successful implementation of geologic sequestration projects hinges on development of advanced predictive models and a diverse set of remote sensing, in situ sampling, and experimental techniques. The models are needed to design and forecast long-term sequestration performance; the monitoring techniques are required to confirm and refine model predictions and to ensure compliance with environmental regulations. We have developed a unique reactive transport modeling capability for predicting sequestration performance in saline aquifers, and used it to simulate CO2 injection at Sleipner; we are now

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-09-01

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

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

International Nuclear Information System (INIS)

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

2001-01-01

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

Post Irradiation Capabilities at the Idaho National Laboratory

International Nuclear Information System (INIS)

Schulthess, J.L.; Rosenberg, K.E.

2011-01-01

The U.S. Department of Energy (DOE), Office of Nuclear Energy (NE) oversees the efforts to ensure nuclear energy remains a viable option for the United States. A significant portion of these efforts are related to post-irradiation examinations (PIE) of highly activated fuel and materials that are subject to the extreme environment inside a nuclear reactor. As the lead national laboratory, Idaho National Laboratory (INL) has a rich history, experience, workforce and capabilities for performing PIE. However, new advances in tools and techniques for performing PIE now enable understanding the performance of fuels and materials at the nano-scale and smaller level. Examination at this level is critical since this is the scale at which irradiation damage occurs. The INL is on course to adopt these advanced tools and techniques to develop a comprehensive nuclear fuels and materials characterization capability that is unique in the world. Because INL has extensive PIE capabilities currently in place, a strong foundation exist to build upon as new capabilities are implemented and work load increases. In the recent past, INL has adopted significant capability to perform advanced PIE characterization. Looking forward, INL is planning for the addition of two facilities that will be built to meet the stringent demands of advanced tools and techniques for highly activated fuels and materials characterization. Dubbed the Irradiated Materials Characterization Laboratory (IMCL) and Advanced Post Irradiation Examination Capability, these facilities are next generation PIE laboratories designed to perform the work of PIE that cannot be performed in current DOE facilities. In addition to physical capabilities, INL has recently added two significant contributors to the Advanced Test Reactor-National Scientific User Facility (ATR-NSUF), Oak Ridge National Laboratory and University of California, Berkeley.

Performance reliability prediction for thermal aging based on kalman filtering

International Nuclear Information System (INIS)

Ren Shuhong; Wen Zhenhua; Xue Fei; Zhao Wensheng

2015-01-01

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

The prediction of swimming performance in competition from behavioral information.

Science.gov (United States)

Rushall, B S; Leet, D

1979-06-01

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

Essays on predictability of emerging markets growth and financial performance

OpenAIRE

Banegas, Maria Ayelen

2011-01-01

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

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.

The reliability of test results from simple test samples in predicting the fatigue performance of automotive components

International Nuclear Information System (INIS)

Fourlaris, G.; Ellwood, R.; Jones, T.B.

2007-01-01

The use of high strength steels (HSS) in automotive components is steadily increasing as automotive designers use modern steel grades to improve structural performance, reduce vehicle weight and enhance crash performance. Weight reduction can be achieved by substituting mild steel with a thinner gauge HSS, however, it must be ensured that no deterioration in performance including fatigue capability occurs. In this study, tests have been carried out to determine the effects that gauge and material strength have on the fatigue performance of a fusion welded automotive suspension arm. Current finite element (FE) modelling and fatigue prediction techniques have been evaluated to determine their reliability when used for thin strip steels. Results have shown the fatigue performance of welded components to be independent of the strength of the parent material for the steel grades studied, with material thickness and joining process the key features determining the fatigue performance. The correlation between the fatigue performance of simple welded samples under uniaxial, constant amplitude loading and complex components under biaxial in service road load data, has been shown to be unreliable. This study also indicates that with the application of modern technologies, such as tailor-welded blanks (TWB), significant weight savings can be achieved. This is demonstrated by a 19% weight reduction with no detrimental effect on the fatigue performance

STUDENT ACADEMIC PERFORMANCE PREDICTION USING SUPPORT VECTOR MACHINE

OpenAIRE

S.A. Oloruntoba1 ,J.L.Akinode2

2017-01-01

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

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.

Predicted performance of an integrated modular engine system

Science.gov (United States)

Binder, Michael; Felder, James L.

1993-01-01

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

Improved thermal source term generation capability for use in performance assessment and system studies

International Nuclear Information System (INIS)

King, J.; Rhodes, C.

1994-01-01

This paper describes work performed by the Civilian Radioactive Waste Management System (CRWMS) Management and Operating (M ampersand O) Contractor to improve spent nuclear fuel (SNF) waste stream characterization for system studies. It discusses how these new capabilities may be exploited for thermal source term generation for use in repository performance assessment modeling. SNF historical discharges have been exhaustively tracked, and significant effort has gone into capturing, verifying, and electronically managing spent fuel inventory data. Future discharge projections are produced annually by the Energy Information Administration (EIA) using sophisticated computer models. The output of these models is coupled with annually updated SNF historical discharges to produce what is referred to as the open-quotes reactor database.close quotes This database and related data are published in a variety of ways including on magnetic media for consistent use by analysts or other interested parties

Mastery and Performance Goals Predict Epistemic and Relational Conflict Regulation

Science.gov (United States)

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

2006-01-01

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

Performance Prediction of Centrifugal Compressor for Drop-In Testing Using Low Global Warming Potential Alternative Refrigerants and Performance Test Codes

Directory of Open Access Journals (Sweden)

Joo Hoon Park

2017-12-01

Full Text Available As environmental regulations to stall global warming are strengthened around the world, studies using newly developed low global warming potential (GWP alternative refrigerants are increasing. In this study, substitute refrigerants, R-1234ze (E and R-1233zd (E, were used in the centrifugal compressor of an R-134a 2-stage centrifugal chiller with a fixed rotational speed. Performance predictions and thermodynamic analyses of the centrifugal compressor for drop-in testing were performed. A performance prediction method based on the existing ASME PTC-10 performance test code was proposed. The proposed method yielded the expected operating area and operating point of the centrifugal compressor with alternative refrigerants. The thermodynamic performance of the first and second stages of the centrifugal compressor was calculated as the polytropic state. To verify the suitability of the proposed method, the drop-in test results of the two alternative refrigerants were compared. The predicted operating range based on the permissible deviation of ASME PTC-10 confirmed that the temperature difference was very small at the same efficiency. Because the drop-in test of R-1234ze (E was performed within the expected operating range, the centrifugal compressor using R-1234ze (E is considered well predicted. However, the predictions of the operating point and operating range of R-1233zd (E were lower than those of the drop-in test. The proposed performance prediction method will assist in understanding thermodynamic performance at the expected operating point and operating area of a centrifugal compressor using alternative gases based on limited design and structure information.

Real-time Tsunami Inundation Prediction Using High Performance Computers

Science.gov (United States)

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

2014-12-01

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

Capabilities of a remote work vehicle

International Nuclear Information System (INIS)

Whittaker, W.L.; Champeny, L.

1987-01-01

The remote work vehicle (RWV) is a mobile work system for recovery operations in radiological environments. A teleoperated, electrohydraulically powered system, the RWV features omnidirectional locomotion, a telescoping boom with a seven meter reach, a master/slave manipulator, ten cameras, a tether for sustained power, and an offboard console where three operators control vehicle functions. (The RWV is more fully described elsewhere see bibliography; capability is emphasized here). Capabilities of the base vehicle and specialized tooling allow the RWV to perform accident recovery tasks, including demolishing concrete and steel structures, decontaminating and sealing surfaces, removing water and sediment from flooded areas, emplacing shields, packaging and transporting materials, and performing general inspections. Aspirations for reliability have made the RWV an order of magnitude more complex than its predecessor recovery robots, and ambitions for task performance have made it two orders of magnitude more capable. In addition to nuclear recovery work, the RWV is a viable candidate for other remote work applications, including nuclear facility maintenance and decommissioning

Optimal artificial neural network architecture selection for performance prediction of compact heat exchanger with the EBaLM-OTR technique

Energy Technology Data Exchange (ETDEWEB)

Wijayasekara, Dumidu, E-mail: wija2589@vandals.uidaho.edu [Department of Computer Science, University of Idaho, 1776 Science Center Drive, Idaho Falls, ID 83402 (United States); Manic, Milos [Department of Computer Science, University of Idaho, 1776 Science Center Drive, Idaho Falls, ID 83402 (United States); Sabharwall, Piyush [Idaho National Laboratory, Idaho Falls, ID (United States); Utgikar, Vivek [Department of Chemical Engineering, University of Idaho, Idaho Falls, ID 83402 (United States)

2011-07-15

Highlights: > Performance prediction of PCHE using artificial neural networks. > Evaluating artificial neural network performance for PCHE modeling. > Selection of over-training resilient artificial neural networks. > Artificial neural network architecture selection for modeling problems with small data sets. - Abstract: Artificial Neural Networks (ANN) have been used in the past to predict the performance of printed circuit heat exchangers (PCHE) with satisfactory accuracy. Typically published literature has focused on optimizing ANN using a training dataset to train the network and a testing dataset to evaluate it. Although this may produce outputs that agree with experimental results, there is a risk of over-training or over-learning the network rather than generalizing it, which should be the ultimate goal. An over-trained network is able to produce good results with the training dataset but fails when new datasets with subtle changes are introduced. In this paper we present EBaLM-OTR (error back propagation and Levenberg-Marquardt algorithms for over training resilience) technique, which is based on a previously discussed method of selecting neural network architecture that uses a separate validation set to evaluate different network architectures based on mean square error (MSE), and standard deviation of MSE. The method uses k-fold cross validation. Therefore in order to select the optimal architecture for the problem, the dataset is divided into three parts which are used to train, validate and test each network architecture. Then each architecture is evaluated according to their generalization capability and capability to conform to original data. The method proved to be a comprehensive tool in identifying the weaknesses and advantages of different network architectures. The method also highlighted the fact that the architecture with the lowest training error is not always the most generalized and therefore not the optimal. Using the method the testing

Optimal artificial neural network architecture selection for performance prediction of compact heat exchanger with the EBaLM-OTR technique

International Nuclear Information System (INIS)

Wijayasekara, Dumidu; Manic, Milos; Sabharwall, Piyush; Utgikar, Vivek

2011-01-01

Highlights: → Performance prediction of PCHE using artificial neural networks. → Evaluating artificial neural network performance for PCHE modeling. → Selection of over-training resilient artificial neural networks. → Artificial neural network architecture selection for modeling problems with small data sets. - Abstract: Artificial Neural Networks (ANN) have been used in the past to predict the performance of printed circuit heat exchangers (PCHE) with satisfactory accuracy. Typically published literature has focused on optimizing ANN using a training dataset to train the network and a testing dataset to evaluate it. Although this may produce outputs that agree with experimental results, there is a risk of over-training or over-learning the network rather than generalizing it, which should be the ultimate goal. An over-trained network is able to produce good results with the training dataset but fails when new datasets with subtle changes are introduced. In this paper we present EBaLM-OTR (error back propagation and Levenberg-Marquardt algorithms for over training resilience) technique, which is based on a previously discussed method of selecting neural network architecture that uses a separate validation set to evaluate different network architectures based on mean square error (MSE), and standard deviation of MSE. The method uses k-fold cross validation. Therefore in order to select the optimal architecture for the problem, the dataset is divided into three parts which are used to train, validate and test each network architecture. Then each architecture is evaluated according to their generalization capability and capability to conform to original data. The method proved to be a comprehensive tool in identifying the weaknesses and advantages of different network architectures. The method also highlighted the fact that the architecture with the lowest training error is not always the most generalized and therefore not the optimal. Using the method the

Axisymmetric thrust-vectoring nozzle performance prediction

International Nuclear Information System (INIS)

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

1998-01-01

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

Predicting Performance in Higher Education Using Proximal Predictors

NARCIS (Netherlands)

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

2016-01-01

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

Are Hydrostatic Models Still Capable of Simulating Oceanic Fronts

Science.gov (United States)

2016-11-10

Hydrostatic Models Still Capable of Simulating Oceanic Fronts Yalin Fan Zhitao Yu Ocean Dynamics and Prediction Branch Oceanography Division FengYan Shi...OF PAGES 17. LIMITATION OF ABSTRACT Are Hydrostatic Models Still Capable of Simulating Oceanic Fronts? Yalin Fan, Zhitao Yu, and, Fengyan Shi1 Naval...mixed layer and thermocline simulations as well as large scale circulations. Numerical experiments are conducted using hydrostatic (HY) and

Customizing Countermeasure Prescriptions using Predictive Measures of Sensorimotor Adaptability

Science.gov (United States)

Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Miller, C. A.; Batson, C. D.; Wood, S. J.; Guined, J. R.; Cohen, H. S.; Buccello-Stout, R.; DeDios, Y. E.;

Study on new energy development planning and absorptive capability of Xinjiang in China considering resource characteristics and demand prediction

Science.gov (United States)

Shao, Hai; Miao, Xujuan; Liu, Jinpeng; Wu, Meng; Zhao, Xuehua

2018-02-01

Xinjiang, as the area where wind energy and solar energy resources are extremely rich, with good resource development characteristics, can provide a support for regional power development and supply protection. This paper systematically analyzes the new energy resource and development characteristics of Xinjiang and carries out the demand prediction and excavation of load characteristics of Xinjiang power market. Combing the development plan of new energy of Xinjiang and considering the construction of transmission channel, it analyzes the absorptive capability of new energy. It provides certain reference for the comprehensive planning of new energy development in Xinjiang and the improvement of absorptive capacity of new energy.

Predicting BCI subject performance using probabilistic spatio-temporal filters.

Directory of Open Access Journals (Sweden)

Heung-Il Suk

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

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

Science.gov (United States)

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

2017-07-04

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

Prediction of topographic and bathymetric measurement performance of airborne low-SNR lidar systems

Science.gov (United States)

Cossio, Tristan

Low signal-to-noise ratio (LSNR) lidar (light detection and ranging) is an alternative paradigm to traditional lidar based on the detection of return signals at the single photoelectron level. The objective of this work was to predict low altitude (600 m) LSNR lidar system performance with regards to elevation measurement and target detection capability in topographic (dry land) and bathymetric (shallow water) scenarios. A modular numerical sensor model has been developed to provide data for further analysis due to the dearth of operational low altitude LSNR lidar systems. This simulator tool is described in detail, with consideration given to atmospheric effects, surface conditions, and the effects of laser phenomenology. Measurement performance analysis of the simulated topographic data showed results comparable to commercially available lidar systems, with a standard deviation of less than 12 cm for calculated elevation values. Bathymetric results, although dependent largely on water turbidity, were indicative of meter-scale horizontal data spacing for sea depths less than 5 m. The high prevalence of noise in LSNR lidar data introduces significant difficulties in data analysis. Novel algorithms to reduce noise are described, with particular focus on their integration into an end-to-end target detection classifier for both dry and submerged targets (cube blocks, 0.5 m to 1.0 m on a side). The key characteristic exploited to discriminate signal and noise is the temporal coherence of signal events versus the random distribution of noise events. Target detection performance over dry earth was observed to be robust, reliably detecting over 90% of targets with a minimal false alarm rate. Comparable results were observed in waters of high clarity, where the investigated system was generally able to detect more than 70% of targets to a depth of 5 m. The results of the study show that CATS, the University of Florida's LSNR lidar prototype, is capable of high fidelity

Code Verification Capabilities and Assessments in Support of ASC V&V Level 2 Milestone #6035

Energy Technology Data Exchange (ETDEWEB)

Doebling, Scott William [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Budzien, Joanne Louise [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Ferguson, Jim Michael [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Harwell, Megan Louise [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hickmann, Kyle Scott [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Israel, Daniel M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Magrogan, William Richard III [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Singleton, Jr., Robert [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Srinivasan, Gowri [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Walter, Jr, John William [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Woods, Charles Nathan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-09-26

This document provides a summary of the code verification activities supporting the FY17 Level 2 V&V milestone entitled “Deliver a Capability for V&V Assessments of Code Implementations of Physics Models and Numerical Algorithms in Support of Future Predictive Capability Framework Pegposts.” The physics validation activities supporting this milestone are documented separately. The objectives of this portion of the milestone are: 1) Develop software tools to support code verification analysis; 2) Document standard definitions of code verification test problems; and 3) Perform code verification assessments (focusing on error behavior of algorithms). This report and a set of additional standalone documents serve as the compilation of results demonstrating accomplishment of these objectives.

Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks.

Science.gov (United States)

Chande, Ruchi D; Hargraves, Rosalyn Hobson; Ortiz-Robinson, Norma; Wayne, Jennifer S

2017-01-01

Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue properties are implemented from literature data, when available. We sought to improve the predictive capability of a computational foot/ankle model by optimizing its ligament stiffness inputs using feedforward and radial basis function neural networks. While the former demonstrated better performance than the latter per mean square error, both networks provided reasonable stiffness predictions for implementation into the computational model.

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

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

Science.gov (United States)

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

2018-01-01

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

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

Science.gov (United States)

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

2016-01-01

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

ANN Model for Predicting the Impact of Submerged Aquatic Weeds Existence on the Hydraulic Performance of Branched Open Channel System Accompanied by Water Structures

International Nuclear Information System (INIS)

Abdeen, Mostafa A. M.; Abdin, Alla E.

2007-01-01

The existence of hydraulic structures in a branched open channel system urges the need for considering the gradually varied flow criterion in evaluating the different hydraulic characteristics in this type of open channel system. Computations of hydraulic characteristics such as flow rates and water surface profiles in branched open channel system with hydraulic structures require tremendous numerical effort especially when the flow cannot be assumed uniform. In addition, the existence of submerged aquatic weeds in this branched open channel system adds to the complexity of the evaluation of the different hydraulic characteristics for this system. However, this existence of aquatic weeds can not be neglected since it is very common in Egyptian open channel systems. Artificial Neural Network (ANN) has been widely utilized in the past decade in civil engineering applications for the simulation and prediction of the different physical phenomena and has proven its capabilities in the different fields. The present study aims towards introducing the use of ANN technique to model and predict the impact of submerged aquatic weeds existence on the hydraulic performance of branched open channel system. Specifically the current paper investigates a branched open channel system that consists of main channel supplies water to two branch channels that are infested by submerged aquatic weeds and have water structures such as clear over fall weirs and sluice gates. The results of this study showed that ANN technique was capable, with small computational effort and high accuracy, of predicting the impact of different infestation percentage for submerged aquatic weeds on the hydraulic performance of branched open channel system with two different hydraulic structures

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'…

Initial demonstration of the NRC`s capability to conduct a performance assessment for a High-Level Waste Repository

Energy Technology Data Exchange (ETDEWEB)

Codell, R.; Eisenberg, N.; Fehringer, D.; Ford, W.; Margulies, T.; McCartin, T.; Park, J.; Randall, J.

1992-05-01

In order to better review licensing submittals for a High-Level Waste Repository, the US Nuclear Regulatory Commission staff has expanded and improved its capability to conduct performance assessments. This report documents an initial demonstration of this capability. The demonstration made use of the limited data from Yucca Mountain, Nevada to investigate a small set of scenario classes. Models of release and transport of radionuclides from a repository via the groundwater and direct release pathways provided preliminary estimates of releases to the accessible environment for a 10,000 year simulation time. Latin hypercube sampling of input parameters was used to express results as distributions and to investigate model sensitivities. This methodology demonstration should not be interpreted as an estimate of performance of the proposed repository at Yucca Mountain, Nevada. By expanding and developing the NRC staff capability to conduct such analyses, NRC would be better able to conduct an independent technical review of the US Department of Energy (DOE) licensing submittals for a high-level waste (HLW) repository. These activities were divided initially into Phase 1 and Phase 2 activities. Additional phases may follow as part of a program of iterative performance assessment at the NRC. The NRC staff conducted Phase 1 activities primarily in CY 1989 with minimal participation from NRC contractors. The Phase 2 activities were to involve NRC contractors actively and to provide for the transfer of technology. The Phase 2 activities are scheduled to start in CY 1990, to allow Sandia National Laboratories to complete development and transfer of computer codes and the Center for Nuclear Waste Regulatory Analyses (CNWRA) to be in a position to assist in the acquisition of the codes.

Comparison of High Performance Network Options: EDR InfiniBand vs.100Gb RDMA Capable Ethernet

Energy Technology Data Exchange (ETDEWEB)

Kachelmeier, Luke Anthony [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Univ. of New Mexico, Albuquerque, NM (United States); Van Wig, Faith Virginia [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Missouri Univ. of Science and Technology, Rolla, MO (United States); Erickson, Kari Natania [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); New Mexico Inst. of Mining and Technology, Socorro, NM (United States)

2016-08-08

These are the slides for a presentation at the HPC Mini Showcase. This is a comparison of two different high performance network options: EDR InfiniBand and 100Gb RDMA capable ethernet. The conclusion of this comparison is the following: there is good potential, as shown with the direct results; 100Gb technology is too new and not standardized, thus deployment effort is complex for both options; different companies are not necessarily compatible; if you want 100Gb/s, you must get it all from one place.

On predicting student performance using low-rank matrix factorization techniques

DEFF Research Database (Denmark)

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

2017-01-01

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

Predicting the performance of a high head Francis turbine using a fully implicit mixing plane

International Nuclear Information System (INIS)

Amstutz, O; Aakti, B; Casartelli, E; Mangani, L; Hanimann, L

2015-01-01

In the present paper numerical investigations of a complete high head Francis turbine comprehensive of a spiral casing, stay and guide vanes and draft tube have been performed at three operating conditions, namely at part load (PL), best efficiency point (BEP), and high load (HL). The main target of the investigations is to assess the prediction accuracy of a reduced domain of the complete turbine using a novel mixing-plane formulation. The computational domain is simplified simulating one single passage of the runner, thus assuming rotational periodicity and steady state conditions. The results were compared with experimental data published by the workshop organization. All CFD simulations were performed at model scale with an in-house adapted, 3D, unstructured, object-oriented finite volume code based on the OpenFOAM-V2.2 framework and designed to solve steady-state incompressible RANS-Equations. The pressure-based solver uses a SIMPLE-C like algorithm and is capable of handling multiple references of frame (MRF). The influence of the turbulence has been considered applying the shear-stress transport model (SST). Full second order upwind scheme for advection discretization has been used for all computations

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

Science.gov (United States)

Porter, J; Galfano, V J

1987-01-01

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

Prediction of Human Performance Using Electroencephalography under Different Indoor Room Temperatures

Science.gov (United States)

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

2018-01-01

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

Modeling the prediction of business intelligence system effectiveness.

Science.gov (United States)

Weng, Sung-Shun; Yang, Ming-Hsien; Koo, Tian-Lih; Hsiao, Pei-I

2016-01-01

Although business intelligence (BI) technologies are continually evolving, the capability to apply BI technologies has become an indispensable resource for enterprises running in today's complex, uncertain and dynamic business environment. This study performed pioneering work by constructing models and rules for the prediction of business intelligence system effectiveness (BISE) in relation to the implementation of BI solutions. For enterprises, effectively managing critical attributes that determine BISE to develop prediction models with a set of rules for self-evaluation of the effectiveness of BI solutions is necessary to improve BI implementation and ensure its success. The main study findings identified the critical prediction indicators of BISE that are important to forecasting BI performance and highlighted five classification and prediction rules of BISE derived from decision tree structures, as well as a refined regression prediction model with four critical prediction indicators constructed by logistic regression analysis that can enable enterprises to improve BISE while effectively managing BI solution implementation and catering to academics to whom theory is important.

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

International Nuclear Information System (INIS)

Kneifel, Joshua; Webb, David

2016-01-01

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

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

Science.gov (United States)

Sato, Naoyuki; Yamaguchi, Yoko

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

An estimator-based distributed voltage-predictive control strategy for ac islanded microgrids

DEFF Research Database (Denmark)

Wang, Yanbo; Chen, Zhe; Wang, Xiongfei

2015-01-01

This paper presents an estimator-based voltage predictive control strategy for AC islanded microgrids, which is able to perform voltage control without any communication facilities. The proposed control strategy is composed of a network voltage estimator and a voltage predictive controller for each...... and has a good capability to reject uncertain perturbations of islanded microgrids....

Structure life prediction at high temperature: present and future capabilities

International Nuclear Information System (INIS)

Chaboche, J.L.

1987-01-01

The life prediction techniques for high temperature conditions include several aspects which are considered successively in this article. Crack initiation criteria themselves, defined for the isolated volume element (the tension-compression specimen for example), including parametric relationships and continuous damage approaches and calculation of local stress and strain fields in the structure and their evolution under cyclic plasticity, which poses several difficult problems to obtain stabilized cyclic solutions are examined. The use of crack initiation criteria or damage rules from the result of the cyclic inelastic analysis and the prediction of crack growth in the structure are considered. Different levels are considered for the predictive tools: the classical approach, future methods presently under development and intermediate rules, which are already in use. Several examples are given on materials and components used either in the nuclear industry or in gas turbine engines. (author)

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.

Do physiological measures predict selected CrossFit® benchmark performance?

Science.gov (United States)

Butcher, Scotty J; Neyedly, Tyler J; Horvey, Karla J; Benko, Chad R

2015-01-01

Purpose CrossFit® is a new but extremely popular method of exercise training and competition that involves constantly varied functional movements performed at high intensity. Despite the popularity of this training method, the physiological determinants of CrossFit performance have not yet been reported. The purpose of this study was to determine whether physiological and/or muscle strength measures could predict performance on three common CrossFit “Workouts of the Day” (WODs). Materials and methods Fourteen CrossFit Open or Regional athletes completed, on separate days, the WODs “Grace” (30 clean and jerks for time), “Fran” (three rounds of thrusters and pull-ups for 21, 15, and nine repetitions), and “Cindy” (20 minutes of rounds of five pull-ups, ten push-ups, and 15 bodyweight squats), as well as the “CrossFit Total” (1 repetition max [1RM] back squat, overhead press, and deadlift), maximal oxygen consumption (VO2max), and Wingate anaerobic power/capacity testing. Results Performance of Grace and Fran was related to whole-body strength (CrossFit Total) (r=−0.88 and −0.65, respectively) and anaerobic threshold (r=−0.61 and −0.53, respectively); however, whole-body strength was the only variable to survive the prediction regression for both of these WODs (R2=0.77 and 0.42, respectively). There were no significant associations or predictors for Cindy. Conclusion CrossFit benchmark WOD performance cannot be predicted by VO2max, Wingate power/capacity, or either respiratory compensation or anaerobic thresholds. Of the data measured, only whole-body strength can partially explain performance on Grace and Fran, although anaerobic threshold also exhibited association with performance. Along with their typical training, CrossFit athletes should likely ensure an adequate level of strength and aerobic endurance to optimize performance on at least some benchmark WODs. PMID:26261428

Investigating the Effects of Information Technology on the Capabilities and Performance of the Supply Chain of Dairy Companies in Fars Province: A Multiple Case Study

Directory of Open Access Journals (Sweden)

Ali Mohammadi

2011-09-01

Full Text Available Nowadays all organizations are somehow involved with information technology revolutions and the applicable aspects of information technology are evident in any field of supply chain, from the relationship with suppliers and producers to the relationship with the customers. In other words, the application of information technology is influential in the improvement of the supply chain. In this study, the effect of information technology tools on the capabilities and performance of the supply chain in the dairy companies of Fars province is investigated. In this research, in information technology sets of tools ,supply chain communication system (SCCS, electronic data interchange (EDI, electronic mail (Email, bar-coding, and radio frequency identification (RFID, in supply chain capabilities, four dimensions including information exchange, coordination, interfirm activity integration, and supply chain responsiveness, and in performance of supply chain, two variables of performance including marketing performance and financial performance will be examined. The results indicate that using information technology tools is effective on the capabilities and hence performance of the supply chain.

The Prediction Performance of Asset Pricing Models and Their Capability of Capturing the Effects of Economic Crises: The Case of Istanbul Stock Exchange

Directory of Open Access Journals (Sweden)

Erol Muzır

2010-09-01

Full Text Available This paper is prepared to test the common opinion that the multifactor asset pricing models produce superior predictions as compared to the single factor models and to evaluate the performance of Arbitrage Pricing Theory (APT and Capital Asset Pricing Model (CAPM. For this purpose, the monthly return data from January 1996 and December 2004 of the stocks of 45 firms listed at Istanbul Stock Exchange were used. Our factor analysis results show that 68,3 % of the return variation can be explained by five factors. Although the APT model has generated a low coefficient of determination, 28,3 %, it proves to be more competent in explaining stock return changes when compared to CAPM which has an inferior explanation power, 5,4 %. Furthermore, we have observed that APT is more robust also in capturing the effects of any economic crisis on return variations.

Artificial Knee Joints Actuators with Energy Recovery Capabilities: A Comparison of Performance

Directory of Open Access Journals (Sweden)

Roberta Alò

2016-01-01

Full Text Available The human knee absorbs more energy than it expends in level ground walking. For this reason it would be useful if the actuation system of a wearable robot for lower limbs was able to recover energy thus improving portability. Presently, we recognize three promising technologies with energy recovery capabilities already available in the literature: the Series Elastic Actuator (SEA, the Clutchable Series Elastic Actuator (C-SEA, and the flywheel Infinitely Variable Transmission (F-IVT actuator. In this paper, a simulation model based comparison of the performance of these actuators is presented. The focus is on two performance indexes: the energy consumed by the electric motor per gait and the peak torque/power requested to the electric motor. Both quantities are related to the portability of the device: the former affects the size of the batteries for a given desired range; the latter affects the size and the weight of the electric motor. The results show that, besides some well-explained limitations of the presented methodology, the C-SEA is the most energy efficient whereas the F-IVT allows cutting down the motor torque/peak power strongly. The analysis also leads to defining how it is possible to improve the F-IVT to achieve a reduction of the energy consumption.

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

Science.gov (United States)

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

2016-10-01

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

Implementation of Premixed Equilibrium Chemistry Capability in OVERFLOW

Science.gov (United States)

Olsen, Mike E.; Liu, Yen; Vinokur, M.; Olsen, Tom

2004-01-01

An implementation of premixed equilibrium chemistry has been completed for the OVERFLOW code, a chimera capable, complex geometry flow code widely used to predict transonic flowfields. The implementation builds on the computational efficiency and geometric generality of the solver.

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...

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.

Predicting work Performance through selection interview ratings and Psychological assessment

Directory of Open Access Journals (Sweden)

Liziwe Nzama

2008-11-01

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

MSFC Turbine Performance Optimization (TPO) Technology Verification Status

Science.gov (United States)

Griffin, Lisa W.; Dorney, Daniel J.; Snellgrove, Lauren M.; Zoladz, Thomas F.; Stroud, Richard T.; Turner, James E. (Technical Monitor)

2002-01-01

Capability to optimize for turbine performance and accurately predict unsteady loads will allow for increased reliability, Isp, and thrust-to-weight. The development of a fast, accurate, validated aerodynamic design, analysis, and optimization system is required.

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

Science.gov (United States)

Belu, Radian

2010-11-01

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

Capitalizing on capabilities.

Science.gov (United States)

Ulrich, Dave; Smallwood, Norm

2004-06-01

By making the most of organizational capabilities--employees' collective skills and fields of expertise--you can dramatically improve your company's market value. Although there is no magic list of proficiencies that every organization needs in order to succeed, the authors identify 11 intangible assets that well-managed companies tend to have: talent, speed, shared mind-set and coherent brand identity, accountability, collaboration, learning, leadership, customer connectivity, strategic unity, innovation, and efficiency. Such companies typically excel in only three of these capabilities while maintaining industry parity in the other areas. Organizations that fall below the norm in any of the 11 are likely candidates for dysfunction and competitive disadvantage. So you can determine how your company fares in these categories (or others, if the generic list doesn't suit your needs), the authors explain how to conduct a "capabilities audit," describing in particular the experiences and findings of two companies that recently performed such audits. In addition to highlighting which intangible assets are most important given the organization's history and strategy, this exercise will gauge how well your company delivers on its capabilities and will guide you in developing an action plan for improvement. A capabilities audit can work for an entire organization, a business unit, or a region--indeed, for any part of a company that has a strategy to generate financial or customer-related results. It enables executives to assess overall company strengths and weaknesses, senior leaders to define strategy, midlevel managers to execute strategy, and frontline leaders to achieve tactical results. In short, it helps turn intangible assets into concrete strengths.

Has Athletic Performance Reached its Peak?

Science.gov (United States)

Berthelot, Geoffroy; Sedeaud, Adrien; Marck, Adrien; Antero-Jacquemin, Juliana; Schipman, Julien; Saulière, Guillaume; Marc, Andy; Desgorces, François-Denis; Toussaint, Jean-François

2015-09-01

Limits to athletic performance have long been a topic of myth and debate. However, sport performance appears to have reached a state of stagnation in recent years, suggesting that the physical capabilities of humans and other athletic species, such as greyhounds and thoroughbreds, cannot progress indefinitely. Although the ultimate capabilities may be predictable, the exact path for the absolute maximal performance values remains difficult to assess and relies on technical innovations, sport regulation, and other parameters that depend on current societal and economic conditions. The aim of this literature review was to assess the possible plateau of top physical capabilities in various events and detail the historical backgrounds and sociocultural, anthropometrical, and physiological factors influencing the progress and regression of athletic performance. Time series of performances in Olympic disciplines, such as track and field and swimming events, from 1896 to 2012 reveal a major decrease in performance development. Such a saturation effect is simultaneous in greyhound, thoroughbred, and frog performances. The genetic condition, exhaustion of phenotypic pools, economic context, and the depletion of optimal morphological traits contribute to the observed limitation of physical capabilities. Present conditions prevailing, we approach absolute physical limits and endure a continued period of world record scarcity. Optional scenarios for further improvements will mostly depend on sport technology and modification competition rules.

Predicting the performance of molecularly imprinted polymers: Selective extraction of caffeine by molecularly imprinted solid phase extraction

Energy Technology Data Exchange (ETDEWEB)

Farrington, Keith [School of Chemical Sciences, Dublin City University, Glasnevin, Dublin 9 (Ireland); Magner, Edmond [Materials and Surface Science Institute, Chemical and Environmental Sciences Department, University of Limerick, Limerick (Ireland); Regan, Fiona [School of Chemical Sciences, Dublin City University, Glasnevin, Dublin 9 (Ireland)]. E-mail: fiona.regan@dcu.ie

2006-04-27

A rational design approach was taken to the planning and synthesis of a molecularly imprinted polymer capable of extracting caffeine (the template molecule) from a standard solution of caffeine and further from a food sample containing caffeine. Data from NMR titration experiments in conjunction with a molecular modelling approach was used in predicting the relative ratios of template to functional monomer and furthermore determined both the choice of solvent (porogen) and the amount used for the study. In addition the molecular modelling program yielded information regarding the thermodynamic stability of the pre-polymerisation complex. Post-polymerisation analysis of the polymer itself by analysis of the pore size distribution by BET yielded significant information regarding the nature of the size and distribution of the pores within the polymer matrix. Here is proposed a stepwise procedure for the development and testing of a molecularly imprinted polymer using a well-studied compound-caffeine as a model system. It is shown that both the physical characteristics of a molecularly imprinted polymer (MIP) and the analysis of the pre-polymerisation complex can yield vital information, which can predict how well a given MIP will perform.

Predicting the performance of molecularly imprinted polymers: Selective extraction of caffeine by molecularly imprinted solid phase extraction

International Nuclear Information System (INIS)

Farrington, Keith; Magner, Edmond; Regan, Fiona

2006-01-01

A rational design approach was taken to the planning and synthesis of a molecularly imprinted polymer capable of extracting caffeine (the template molecule) from a standard solution of caffeine and further from a food sample containing caffeine. Data from NMR titration experiments in conjunction with a molecular modelling approach was used in predicting the relative ratios of template to functional monomer and furthermore determined both the choice of solvent (porogen) and the amount used for the study. In addition the molecular modelling program yielded information regarding the thermodynamic stability of the pre-polymerisation complex. Post-polymerisation analysis of the polymer itself by analysis of the pore size distribution by BET yielded significant information regarding the nature of the size and distribution of the pores within the polymer matrix. Here is proposed a stepwise procedure for the development and testing of a molecularly imprinted polymer using a well-studied compound-caffeine as a model system. It is shown that both the physical characteristics of a molecularly imprinted polymer (MIP) and the analysis of the pre-polymerisation complex can yield vital information, which can predict how well a given MIP will perform

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

Science.gov (United States)

Fayol, Michel; Barrouillet, Pierre; Marinthe, Catherine

1998-01-01

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

Performance Evaluation of WiMAX Broadband from High Altitude Platform Cellular System and Terrestrial Coexistence Capability

Directory of Open Access Journals (Sweden)

Yang Z

2008-01-01

Full Text Available The performance obtained from providing worldwide interoperability for microwave access (WiMAX from high altitude platforms (HAPs with multiple antenna payloads is investigated, and the coexistence capability with multiple-operator terrestrial WiMAX deployments is examined. A scenario composed of a single HAP and coexisting multiple terrestrial WiMAX base stations deployed inside the HAP coverage area (with radius of 30 km to provide services to fixed users with the antenna mounted on the roof with a directive antenna to receive signals from HAPs is proposed. A HAP cellular configuration with different possible reuse patterns is established. The coexistence performance is assessed in terms of HAP downlink and uplink performance, interfered by terrestrial WiMAX deployment. Simulation results show that it is effective to deliver WiMAX via HAPs and share the spectrum with terrestrial systems.

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.

What predicts performance during clinical psychology training?

OpenAIRE

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

2013-01-01

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

Capability of the "Ball-Berry" model for predicting stomatal conductance and water use efficiency of potato leaves under different irrigation regimes

DEFF Research Database (Denmark)

Liu, Fulai; Andersen, Mathias N.; Jensen, Christian Richardt

2009-01-01

was used for model parameterization, where measurements of midday leaf gas exchange of potted potatoes were done during progressive soil drying for 2 weeks at tuber initiation and earlier bulking stages. The measured photosynthetic rate (An) was used as an input for the model. To account for the effects......The capability of the ‘Ball-Berry' model (BB-model) in predicting stomatal conductance (gs) and water use efficiency (WUE) of potato (Solanum tuberosum L.) leaves under different irrigation regimes was tested using data from two independent pot experiments in 2004 and 2007. Data obtained from 2004...... of soil water deficits on gs, a simple equation modifying the slope (m) based on the mean soil water potential (Ψs) in the soil columns was incorporated into the original BB-model. Compared with the original BB-model, the modified BB-model showed better predictability for both gs and WUE of potato leaves...

Predicting Performance on MOOC Assessments using Multi-Regression Models

OpenAIRE

Ren, Zhiyun; Rangwala, Huzefa; Johri, Aditya

2016-01-01

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

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

International Nuclear Information System (INIS)

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

1983-01-01

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

Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Ruchi D. Chande

2017-01-01

Full Text Available Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue properties are implemented from literature data, when available. We sought to improve the predictive capability of a computational foot/ankle model by optimizing its ligament stiffness inputs using feedforward and radial basis function neural networks. While the former demonstrated better performance than the latter per mean square error, both networks provided reasonable stiffness predictions for implementation into the computational model.

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.

Materials capability review Los Alamos National Laboratory, May 3-6, 2010

Energy Technology Data Exchange (ETDEWEB)

Taylor, Antoinette [Los Alamos National Laboratory

2010-01-01

, environment for conducting science, technology and engineering. The specific charge for the Materials Capability Review is to assess the Los Alamos Laboratory Directed Research and Development project titled, 'First Principles Predictive Capabilities for Transuranic Materials: Mott Insulators to Correlated Metals' using the criteria performance, quality, and relevance for the current status of the project. The committee is requested to provide advice on future direction of the project.

The Search Performance Evaluation and Prediction in Exploratory Search

OpenAIRE

LIU, FEI

2016-01-01

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

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.

Multiprocessor performance modeling with ADAS

Science.gov (United States)

Hayes, Paul J.; Andrews, Asa M.

1989-01-01

A graph managing strategy referred to as the Algorithm to Architecture Mapping Model (ATAMM) appears useful for the time-optimized execution of application algorithm graphs in embedded multiprocessors and for the performance prediction of graph designs. This paper reports the modeling of ATAMM in the Architecture Design and Assessment System (ADAS) to make an independent verification of ATAMM's performance prediction capability and to provide a user framework for the evaluation of arbitrary algorithm graphs. Following an overview of ATAMM and its major functional rules are descriptions of the ADAS model of ATAMM, methods to enter an arbitrary graph into the model, and techniques to analyze the simulation results. The performance of a 7-node graph example is evaluated using the ADAS model and verifies the ATAMM concept by substantiating previously published performance results.

NARX prediction of some rare chaotic flows: Recurrent fuzzy functions approach

International Nuclear Information System (INIS)

Goudarzi, Sobhan; Jafari, Sajad; Moradi, Mohammad Hassan; Sprott, J.C.

2016-01-01

The nonlinear and dynamic accommodating capability of time domain models makes them a useful representation of chaotic time series for analysis, modeling and prediction. This paper is devoted to the modeling and prediction of chaotic time series with hidden attractors using a nonlinear autoregressive model with exogenous inputs (NARX) based on a novel recurrent fuzzy functions (RFFs) approach. Case studies of recently introduced chaotic systems with hidden attractors plus classical chaotic systems demonstrate that the proposed modeling methodology exhibits better prediction performance from different viewpoints (short term and long term) compared to some other existing methods. - Highlights: • A new method is proposed for prediction of chaotic time series. • This method is based on novel recurrent fuzzy functions (RFFs) approach. • Some rare chaotic flows are used as test systems. • The new method shows proper performance in short-term prediction. • It also shows proper performance in prediction of attractor's topology.

NARX prediction of some rare chaotic flows: Recurrent fuzzy functions approach

Energy Technology Data Exchange (ETDEWEB)

Goudarzi, Sobhan [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Jafari, Sajad, E-mail: sajadjafari@aut.ac.ir [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Moradi, Mohammad Hassan [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Sprott, J.C. [Department of Physics, University of Wisconsin–Madison, Madison, WI 53706 (United States)

2016-02-15

The nonlinear and dynamic accommodating capability of time domain models makes them a useful representation of chaotic time series for analysis, modeling and prediction. This paper is devoted to the modeling and prediction of chaotic time series with hidden attractors using a nonlinear autoregressive model with exogenous inputs (NARX) based on a novel recurrent fuzzy functions (RFFs) approach. Case studies of recently introduced chaotic systems with hidden attractors plus classical chaotic systems demonstrate that the proposed modeling methodology exhibits better prediction performance from different viewpoints (short term and long term) compared to some other existing methods. - Highlights: • A new method is proposed for prediction of chaotic time series. • This method is based on novel recurrent fuzzy functions (RFFs) approach. • Some rare chaotic flows are used as test systems. • The new method shows proper performance in short-term prediction. • It also shows proper performance in prediction of attractor's topology.

Predicting Story Goodness Performance from Cognitive Measures Following Traumatic Brain Injury

Science.gov (United States)

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

2012-01-01

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

Introduction of an Evaluation Tool to Predict the Probability of Success of Companies: The Innovativeness, Capabilities and Potential Model (ICP

Directory of Open Access Journals (Sweden)

Michael Lewrick

2009-05-01

Full Text Available Successful innovation requires management and in this paper a model to help manage the innovation process is presented. This model can be used to audit the management capability to innovate and to monitor how sales increase is related to innovativeness. The model was developed from a study of companies in the high technology cluster around Munich and validated using statistical procedures. The model was found to be effective at predicting the success or otherwise of the innovation strategy pursued by the company. The use of this model and how it can be used to identify areas for improvement are documented in this paper.

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.

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.

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

Science.gov (United States)

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

2011-02-01

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

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

Cloud-Based Numerical Weather Prediction for Near Real-Time Forecasting and Disaster Response

Science.gov (United States)

Molthan, Andrew; Case, Jonathan; Venners, Jason; Schroeder, Richard; Checchi, Milton; Zavodsky, Bradley; Limaye, Ashutosh; O'Brien, Raymond

2015-01-01

The use of cloud computing resources continues to grow within the public and private sector components of the weather enterprise as users become more familiar with cloud-computing concepts, and competition among service providers continues to reduce costs and other barriers to entry. Cloud resources can also provide capabilities similar to high-performance computing environments, supporting multi-node systems required for near real-time, regional weather predictions. Referred to as "Infrastructure as a Service", or IaaS, the use of cloud-based computing hardware in an on-demand payment system allows for rapid deployment of a modeling system in environments lacking access to a large, supercomputing infrastructure. Use of IaaS capabilities to support regional weather prediction may be of particular interest to developing countries that have not yet established large supercomputing resources, but would otherwise benefit from a regional weather forecasting capability. Recently, collaborators from NASA Marshall Space Flight Center and Ames Research Center have developed a scripted, on-demand capability for launching the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS), which includes pre-compiled binaries of the latest version of the Weather Research and Forecasting (WRF) model. The WRF-EMS provides scripting for downloading appropriate initial and boundary conditions from global models, along with higher-resolution vegetation, land surface, and sea surface temperature data sets provided by the NASA Short-term Prediction Research and Transition (SPoRT) Center. This presentation will provide an overview of the modeling system capabilities and benchmarks performed on the Amazon Elastic Compute Cloud (EC2) environment. In addition, the presentation will discuss future opportunities to deploy the system in support of weather prediction in developing countries supported by NASA's SERVIR Project, which provides capacity building

Sensitive quantitative predictions of peptide-MHC binding by a 'Query by Committee' artificial neural network approach

DEFF Research Database (Denmark)

Buus, S.; Lauemoller, S.L.; Worning, Peder

2003-01-01

We have generated Artificial Neural Networks (ANN) capable of performing sensitive, quantitative predictions of peptide binding to the MHC class I molecule, HLA-A*0204. We have shown that such quantitative ANN are superior to conventional classification ANN, that have been trained to predict...

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.

Structural Capability of an Organization toward Innovation Capability

DEFF Research Database (Denmark)

Nielsen, Susanne Balslev; Momeni, Mostafa

2016-01-01

The scholars in the field of strategic management have developed two major approaches for attainment of competitive advantage: an approach based on environmental opportunities, and another one based on internal capabilities of an organization. Some investigations in the last two decades have...... indicated that the advantages relying on the internal capabilities of organizations may determine the competitive position of organizations better than environmental opportunities do. Characteristics of firms shows that one of the most internal capabilities that lead the organizations to the strongest...... competitive advantage in the organizations is the innovation capability. The innovation capability is associated with other organizational capabilities, and many organizations have focused on the need to identify innovation capabilities.This research focuses on recognition of the structural aspect...

An Overview of Facilities and Capabilities to Support the Development of Nuclear Thermal Propulsion

Energy Technology Data Exchange (ETDEWEB)

James Werner; Sam Bhattacharyya; Mike Houts

2011-02-01

Abstract. The future of American space exploration depends on the ability to rapidly and economically access locations of interest throughout the solar system. There is a large body of work (both in the US and the Former Soviet Union) that show that Nuclear Thermal Propulsion (NTP) is the most technically mature, advanced propulsion system that can enable this rapid and economical access by its ability to provide a step increase above what is a feasible using a traditional chemical rocket system. For an NTP system to be deployed, the earlier measurements and recent predictions of the performance of the fuel and the reactor system need to be confirmed experimentally prior to launch. Major fuel and reactor system issues to be addressed include fuel performance at temperature, hydrogen compatibility, fission product retention, and restart capability. The prime issue to be addressed for reactor system performance testing involves finding an affordable and environmentally acceptable method to test a range of engine sizes using a combination of nuclear and non-nuclear test facilities. This paper provides an assessment of some of the capabilities and facilities that are available or will be needed to develop and test the nuclear fuel, and reactor components. It will also address briefly options to take advantage of the greatly improvement in computation/simulation and materials processing capabilities that would contribute to making the development of an NTP system more affordable. Keywords: Nuclear Thermal Propulsion (NTP), Fuel fabrication, nuclear testing, test facilities.

NGNP Component Test Capability Design Code of Record

Energy Technology Data Exchange (ETDEWEB)

S.L. Austad; D.S. Ferguson; L.E. Guillen; C.W. McKnight; P.J. Petersen

2009-09-01

The Next Generation Nuclear Plant Project is conducting a trade study to select a preferred approach for establishing a capability whereby NGNP technology development testing—through large-scale, integrated tests—can be performed for critical HTGR structures, systems, and components (SSCs). The mission of this capability includes enabling the validation of interfaces, interactions, and performance for critical systems and components prior to installation in the NGNP prototype.

Advanced Simulation Capability for Environmental Management (ASCEM) Phase II Demonstration

Energy Technology Data Exchange (ETDEWEB)

Freshley, M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hubbard, S. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Flach, G. [Savannah River National Lab. (SRNL), Aiken, SC (United States); Freedman, V. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Agarwal, D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Andre, B. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bott, Y. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Chen, X. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Davis, J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Faybishenko, B. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Gorton, I. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Murray, C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Moulton, D. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Meyer, J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Rockhold, M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Shoshani, A. [LBNL; Steefel, C. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wainwright, H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Waichler, S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2012-09-28

In 2009, the National Academies of Science (NAS) reviewed and validated the U.S. Department of Energy Office of Environmental Management (EM) Technology Program in its publication, Advice on the Department of Energy’s Cleanup Technology Roadmap: Gaps and Bridges. The NAS report outlined prioritization needs for the Groundwater and Soil Remediation Roadmap, concluded that contaminant behavior in the subsurface is poorly understood, and recommended further research in this area as a high priority. To address this NAS concern, the EM Office of Site Restoration began supporting the development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is a state-of-the-art scientific approach that uses an integration of toolsets for understanding and predicting contaminant fate and transport in natural and engineered systems. The ASCEM modeling toolset is modular and open source. It is divided into three thrust areas: Multi-Process High Performance Computing (HPC), Platform and Integrated Toolsets, and Site Applications. The ASCEM toolsets will facilitate integrated approaches to modeling and site characterization that enable robust and standardized assessments of performance and risk for EM cleanup and closure activities. During fiscal year 2012, the ASCEM project continued to make significant progress in capabilities development. Capability development occurred in both the Platform and Integrated Toolsets and Multi-Process HPC Simulator areas. The new Platform and Integrated Toolsets capabilities provide the user an interface and the tools necessary for end-to-end model development that includes conceptual model definition, data management for model input, model calibration and uncertainty analysis, and model output processing including visualization. The new HPC Simulator capabilities target increased functionality of process model representations, toolsets for interaction with the Platform, and model confidence testing and verification for

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

Directory of Open Access Journals (Sweden)

Roland Stöggl, Erich Müller, Thomas Stöggl

2017-09-01

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

Performance Evaluation of WiMAX Broadband from High Altitude Platform Cellular System and Terrestrial Coexistence Capability

Directory of Open Access Journals (Sweden)

T. Hult

2008-12-01

Full Text Available The performance obtained from providing worldwide interoperability for microwave access (WiMAX from high altitude platforms (HAPs with multiple antenna payloads is investigated, and the coexistence capability with multiple-operator terrestrial WiMAX deployments is examined. A scenario composed of a single HAP and coexisting multiple terrestrial WiMAX base stations deployed inside the HAP coverage area (with radius of 30 km to provide services to fixed users with the antenna mounted on the roof with a directive antenna to receive signals from HAPs is proposed. A HAP cellular configuration with different possible reuse patterns is established. The coexistence performance is assessed in terms of HAP downlink and uplink performance, interfered by terrestrial WiMAX deployment. Simulation results show that it is effective to deliver WiMAX via HAPs and share the spectrum with terrestrial systems.

Improved understanding of physics processes in pedestal structure, leading to improved predictive capability for ITER

International Nuclear Information System (INIS)

Groebner, R.J.; Snyder, P.B.; Leonard, A.W.; Chang, C.S.; Maingi, R.; Boyle, D.P.; Diallo, A.; Hughes, J.W.; Davis, E.M.; Ernst, D.R.; Landreman, M.; Xu, X.Q.; Boedo, J.A.; Cziegler, I.; Diamond, P.H.; Eldon, D.P.; Callen, J.D.; Canik, J.M.; Elder, J.D.; Fulton, D.P.

2013-01-01

Joint experiment/theory/modelling research has led to increased confidence in predictions of the pedestal height in ITER. This work was performed as part of a US Department of Energy Joint Research Target in FY11 to identify physics processes that control the H-mode pedestal structure. The study included experiments on C-Mod, DIII-D and NSTX as well as interpretation of experimental data with theory-based modelling codes. This work provides increased confidence in the ability of models for peeling–ballooning stability, bootstrap current, pedestal width and pedestal height scaling to make correct predictions, with some areas needing further work also being identified. A model for pedestal pressure height has made good predictions in existing machines for a range in pressure of a factor of 20. This provides a solid basis for predicting the maximum pedestal pressure height in ITER, which is found to be an extrapolation of a factor of 3 beyond the existing data set. Models were studied for a number of processes that are proposed to play a role in the pedestal n e and T e profiles. These processes include neoclassical transport, paleoclassical transport, electron temperature gradient turbulence and neutral fuelling. All of these processes may be important, with the importance being dependent on the plasma regime. Studies with several electromagnetic gyrokinetic codes show that the gradients in and on top of the pedestal can drive a number of instabilities. (paper)

Advanced simulation capability for environmental management - current status and future applications

Energy Technology Data Exchange (ETDEWEB)

Freshley, Mark; Scheibe, Timothy [Pacific Northwest National Laboratory, Richland, Washington (United States); Robinson, Bruce; Moulton, J. David; Dixon, Paul [Los Alamos National Laboratory, Los Alamos, New Mexico (United States); Marble, Justin; Gerdes, Kurt [U.S. Department of Energy, Office of Environmental Management, Washington DC (United States); Stockton, Tom [Neptune and Company, Inc, Los Alamos, New Mexico (United States); Seitz, Roger [Savannah River National Laboratory, Aiken, South Carolina (United States); Black, Paul [Neptune and Company, Inc, Lakewood, Colorado (United States)

2013-07-01

The U.S. Department of Energy (US DOE) Office of Environmental Management (EM), Office of Soil and Groundwater (EM-12), is supporting development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is a state-of-the-art scientific tool and approach that is currently aimed at understanding and predicting contaminant fate and transport in natural and engineered systems. ASCEM is a modular and open source high-performance computing tool. It will be used to facilitate integrated approaches to modeling and site characterization, and provide robust and standardized assessments of performance and risk for EM cleanup and closure activities. The ASCEM project continues to make significant progress in development of capabilities, with current emphasis on integration of capabilities in FY12. Capability development is occurring for both the Platform and Integrated Tool-sets and High-Performance Computing (HPC) multi-process simulator. The Platform capabilities provide the user interface and tools for end-to-end model development, starting with definition of the conceptual model, management of data for model input, model calibration and uncertainty analysis, and processing of model output, including visualization. The HPC capabilities target increased functionality of process model representations, tool-sets for interaction with Platform, and verification and model confidence testing. The integration of the Platform and HPC capabilities were tested and evaluated for EM applications in a set of demonstrations as part of Site Applications Thrust Area activities in 2012. The current maturity of the ASCEM computational and analysis capabilities has afforded the opportunity for collaborative efforts to develop decision analysis tools to support and optimize radioactive waste disposal. Recent advances in computerized decision analysis frameworks provide the perfect opportunity to bring this capability into ASCEM. This will allow radioactive waste

Wind turbine control with constraint handling: a model predictive control approach

DEFF Research Database (Denmark)

Henriksen, Lars Christian; Hansen, Morten Hartvig; Poulsen, Niels Kjølstad

2012-01-01

on model predictive control, a control method well suited for constraint handling. The performance of the presented controller during an extreme operating gust is compared to that of a proportional-integral controller with integrator anti-windup. Furthermore, the presented controller-s capability...

Westinghouse Hanford Company package testing capabilities

International Nuclear Information System (INIS)

Hummer, J.H.; Mercado, M.S.

1993-07-01

The Department of Energy's Hanford Site is a 1,450-km 2 (560-mi 2 ) installation located in southeastern Washington State. Established in 1943 as a plutonium production facility, Hanford's role has evolved into one of environmental restoration and remediation. Many of these environmental restoration and remediation activities involve transportation of radioactive/hazardous materials. Packagings used for the transportation of radioactive/hazardous materials must be capable of meeting certain normal transport and hypothetical accident performance criteria. Evaluations of performance to these criteria typically involve a combination of analysis and testing. Required tests may include the free drop, puncture, penetration, compression, thermal, heat, cold, vibration, water spray, water immersion, reduced pressure, and increased pressure tests. The purpose of this paper is to outline the Hanford capabilities for performing each of these tests

Update of super-speed ground transportation technology development status and performance capabilities. CIGGT report No. 89-16

Energy Technology Data Exchange (ETDEWEB)

Hayes, W F

1990-01-01

This report presents an update of the Phase II assessment of development status and performance capabilities for four candidate super-speed ground transportation system alternatives for the Las Vegas-Southern California corridor. The four alternatives considered are the TGV wheel-on-rail technology, the Transrapid TR- 07 long-stator Electromagnetic Maglev (EMS) technology, the Japan Railways MLU Electrodynamic Maglev (EDS) technology, and the HSST Corp. HSST-400 short-stator Electromagnetic Maglev technology.

The capability concept – On how to define and describe capability in relation to risk, vulnerability and resilience

International Nuclear Information System (INIS)

Lindbom, Hanna; Tehler, Henrik; Eriksson, Kerstin; Aven, Terje

2015-01-01

Capabilities-based planning and capability assessment are high on the agendas of several countries and organisations as part of their risk management and emergency preparedness. Despite this, few definitions of capability exist, and they are not easily related to concepts such as risk, vulnerability and resilience. The aim of the present study was thus to broaden the scientific basis of the risk field to also include the concept of capability. The proposed definition is based on a recently developed risk framework, and we define capability as the uncertainty about and the severity of the consequences of an activity given the occurrence of the initiating event and the performed task. We provide examples of how the response capability for a fictive scenario can be described using this definition, and illustrate how our definition can be used to analyse capability assessments prepared according to the Swedish crisis management system. We have analysed the content of 25 capability assessments produced in 2011 by stakeholders on local, regional and national level. It was concluded that none addressed uncertainty to any appreciable extent, and only a third described capability in terms of consequences and task, making it difficult to relate these capability assessments to risk assessments. - Highlights: • Few definitions of capability relate to definitions of risk, vulnerability and resilience. • We relate capability to risk, vulnerability and resilience. • We define capability using the components uncertainty, consequences, event and task

Conceptualizing innovation capabilities: A contingency perspective

Directory of Open Access Journals (Sweden)

Tor Helge Aas

2017-01-01

Full Text Available Empirical research has confirmed that a positive relationship exists between the implementation of innovation activities and the future performance of organizations. Firms utilize resources and capabilities to develop innovations in the form of new products, services or processes. Some firms prove to be better at reproducing innovation success than others, and the capacity to do so is referred to as innovation capability. However, the term innovation capability is ambiguously treated in extant literature. There are several different definitions of the concept and the distinction between innovation capabilities and other types of capabilities, such as dynamic capabilities, is neither explicitly stated, nor is the relationship between the concept and other resource- and capability-based concepts within strategy theory established. Although innovation is increasingly identified as crucial for a firm’s sustainable competitiveness in contemporary volatile and complex markets, the strategy-innovation link is underdeveloped in extant research. To overcome this challenge this paper raises the following research question: What type of innovation capabilities are required to innovate successfully? Due to the status of the extant research, we chose a conceptual research design to answer our research question and the paper contributes with a conceptual framework to discuss what innovation capabilities firms need to reproduce innovation success. Based on careful examination of current literature on innovation capability specifically, and the strategy-innovation link in general, we suggest that innovation capability must be viewed along two dimensions – innovation novelty and market characteristics. This framework enables the identification of four different contexts for innovation capabilities in a two-bytwo matrix. We discuss the types of innovation capabilities necessary within the four different contexts. This novel framework contributes to the

NRC iterative performance assessment Phase 2. Development of capabilities for review of a performance assessment for a high-level waste repository

International Nuclear Information System (INIS)

Wescott, R.G.; Lee, M.P.; Eisenberg, N.A.; Baca, R.G.

1995-10-01

In order to better review a potential license application to construct and operate a geologic repository for spent nuclear fuel and high-level radioactive waste (HLW), the Nuclear Regulatory Commission staff (and its contractor) has expanded and improved its capability to conduct performance assessments. This report documents the demonstration of the second phase of this capability. The demonstration made use of the scenario selection procedure developed by Sandia National Laboratories to provide a set of scenarios, with corresponding probabilities, for use in the consequence analysis of a potential HLW disposal site in unsaturated tuff. Models of release of radionuclides from the waste form and transport in ground water, air and by direct pathways provided preliminary estimates of releases to the accessible environment for a 10,000 year period. The input values of parameters necessary for the consequence models were sampled numerous times using Latin Hypercube Sampling from assumed probability distributions. The results from the consequence models were then used to generate Complementary Cumulative Distribution Functions (CCDFs) for either release to the accessible environment or effective dose equivalents to a target population. CCDFs were calculated for probabilistically significant combinations (scenarios) of four disruptive events; drilling, pluvial climate, seismicity and magmatism. Sensitivity and uncertainty analyses of the calculated releases and effective dose equivalents were also used to determine the importance of the parameters. Because of the preliminary nature of the analysis and the lack of an adequate data base, the results and conclusions presented in this report should be carefully interpreted. They should not be misconstrued to represent the actual performance of the proposed Yucca Mountain repository nor serve as an endorsement of the methods used

Technological Capability's Predictor Variables

Directory of Open Access Journals (Sweden)

Fernanda Maciel Reichert

2011-03-01

Full Text Available The aim of this study was to identify the factors that influence in configuration of the technological capability of companies in sectors with medium-low technological intensity. To achieve the goal proposed in this article a survey was carried out. Based on the framework developed by Lall (1992 which classifies firms in basic, intermediate and advanced level of technological capability; it was found that the predominant technological capability is intermediate, with 83.7% of respondent companies (plastics companies in Brazil. It is believed that the main contribution of this study is the finding that the dependent variable named “Technological Capability” can be explained at a rate of 65% by six variables: development of new processes; selection of the best equipment supplier; sales of internally developed new technology to third parties; design and manufacture of equipment; study of the work methods and perform inventory control; and improvement of product quality.

Decline curve based models for predicting natural gas well performance

Directory of Open Access Journals (Sweden)

Arash Kamari

2017-06-01

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

Review of fluorescence guided surgery systems: identification of key performance capabilities beyond indocyanine green imaging

Science.gov (United States)

DSouza, Alisha V.; Lin, Huiyun; Henderson, Eric R.; Samkoe, Kimberley S.; Pogue, Brian W.

2016-01-01

Abstract. There is growing interest in using fluorescence imaging instruments to guide surgery, and the leading options for open-field imaging are reviewed here. While the clinical fluorescence-guided surgery (FGS) field has been focused predominantly on indocyanine green (ICG) imaging, there is accelerated development of more specific molecular tracers. These agents should help advance new indications for which FGS presents a paradigm shift in how molecular information is provided for resection decisions. There has been a steady growth in commercially marketed FGS systems, each with their own differentiated performance characteristics and specifications. A set of desirable criteria is presented to guide the evaluation of instruments, including: (i) real-time overlay of white-light and fluorescence images, (ii) operation within ambient room lighting, (iii) nanomolar-level sensitivity, (iv) quantitative capabilities, (v) simultaneous multiple fluorophore imaging, and (vi) ergonomic utility for open surgery. In this review, United States Food and Drug Administration 510(k) cleared commercial systems and some leading premarket FGS research systems were evaluated to illustrate the continual increase in this performance feature base. Generally, the systems designed for ICG-only imaging have sufficient sensitivity to ICG, but a fraction of the other desired features listed above, with both lower sensitivity and dynamic range. In comparison, the emerging research systems targeted for use with molecular agents have unique capabilities that will be essential for successful clinical imaging studies with low-concentration agents or where superior rejection of ambient light is needed. There is no perfect imaging system, but the feature differences among them are important differentiators in their utility, as outlined in the data and tables here. PMID:27533438

Review of fluorescence guided surgery systems: identification of key performance capabilities beyond indocyanine green imaging

Science.gov (United States)

DSouza, Alisha V.; Lin, Huiyun; Henderson, Eric R.; Samkoe, Kimberley S.; Pogue, Brian W.

2016-08-01

There is growing interest in using fluorescence imaging instruments to guide surgery, and the leading options for open-field imaging are reviewed here. While the clinical fluorescence-guided surgery (FGS) field has been focused predominantly on indocyanine green (ICG) imaging, there is accelerated development of more specific molecular tracers. These agents should help advance new indications for which FGS presents a paradigm shift in how molecular information is provided for resection decisions. There has been a steady growth in commercially marketed FGS systems, each with their own differentiated performance characteristics and specifications. A set of desirable criteria is presented to guide the evaluation of instruments, including: (i) real-time overlay of white-light and fluorescence images, (ii) operation within ambient room lighting, (iii) nanomolar-level sensitivity, (iv) quantitative capabilities, (v) simultaneous multiple fluorophore imaging, and (vi) ergonomic utility for open surgery. In this review, United States Food and Drug Administration 510(k) cleared commercial systems and some leading premarket FGS research systems were evaluated to illustrate the continual increase in this performance feature base. Generally, the systems designed for ICG-only imaging have sufficient sensitivity to ICG, but a fraction of the other desired features listed above, with both lower sensitivity and dynamic range. In comparison, the emerging research systems targeted for use with molecular agents have unique capabilities that will be essential for successful clinical imaging studies with low-concentration agents or where superior rejection of ambient light is needed. There is no perfect imaging system, but the feature differences among them are important differentiators in their utility, as outlined in the data and tables here.

Analytical prediction of thermal performance of hypervapotron and its application to ITER

International Nuclear Information System (INIS)

Baxi, C.B.; Falter, H.

1992-09-01

A hypervapotron (HV) is a water cooled device made of high thermal conductivity material such as copper. A surface heat flux of up to 30 MW/m 2 has been achieved in copper hypervapotrans cooled by water at a velocity of 10 m/s and at a pressure of six bar. Hypervapotrons have been used in the past as beam dumps at the Joint European Torus (JET). It is planned to use them for diverter cooling during Mark II upgrade of the JET. Although a large amount of experimental data has been collected on these devices, an analytical performance prediction has not been done before due to the complexity of the heat transfer mechanisms. A method to analytically predict the thermal performance of the hypervapotron is described. The method uses a combination of a number of thermal hydraulic correlations and a finite element analysis. The analytical prediction shows an excellent agreement with experimental results over a wide range of velocities, pressures, subcooling, and geometries. The method was used to predict the performance of hypervapotron made of beryllium. Merits for the use of hypervapotrons for International Thermonuclear Experimental Reactor (ITER) and Tokamak Physics Experiment (TPX) are discussed

Neural network for prediction of superheater fireside corrosion

Energy Technology Data Exchange (ETDEWEB)

Makkonen, P [Foster Wheeler Energia Oy, Karhula R and D Center, Karhula (Finland)

1999-12-31

Superheater corrosion causes vast annual losses to the power companies. If the corrosion could be reliably predicted, new power plants could be designed accordingly, and knowledge of fuel selection and determination of process conditions could be utilized to minimize superheater corrosion. If relations between inputs and the output are poorly known, conventional models depending on corrosion theories will fail. A prediction model based on a neural network is capable of learning from errors and improving its performance as the amount of data increases. The neural network developed during this study predicts superheater corrosion with 80 % accuracy at early stage of the project. (orig.) 10 refs.

Neural network for prediction of superheater fireside corrosion

Energy Technology Data Exchange (ETDEWEB)

Makkonen, P. [Foster Wheeler Energia Oy, Karhula R and D Center, Karhula (Finland)

1998-12-31

Superheater corrosion causes vast annual losses to the power companies. If the corrosion could be reliably predicted, new power plants could be designed accordingly, and knowledge of fuel selection and determination of process conditions could be utilized to minimize superheater corrosion. If relations between inputs and the output are poorly known, conventional models depending on corrosion theories will fail. A prediction model based on a neural network is capable of learning from errors and improving its performance as the amount of data increases. The neural network developed during this study predicts superheater corrosion with 80 % accuracy at early stage of the project. (orig.) 10 refs.

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%.

Technological innovation capability in Malaysian-owned resource-based manufacturing companies: Early findings

Science.gov (United States)

Razali, Nur Fhathyhah; Mohd Suradi, Nur Riza; Ahmad Shahabuddin, Faridatul Azna; Ismail, Wan Rosmanira; Abidin, Norkisme Zainal; Ahmad, Nor Amalina; Mustafa, Zainol

2013-04-01

This study aims to identify the determinants of technological innovation capability of Malaysian-owned companies in the resources-based manufacturing, to identify the relationship between technological innovation capability (TIC) and technological innovation performance (TIP) for the resource-based manufacturing. Furthermore, this study also aims to identify innovation capability factors that need more emphasis and improvements from the respective authority. The scope of the study covers four industries which are petrochemical industries, pharmaceutical industries, palm oil-based industries and food processing industries which are located in the state of Selangor. Descriptive analysis, correlation analysis and performance capability analysis were used in this study. It was found that, technological innovation capabilities (TIC) for companies in the resource-based manufacturing are moderate. Factors such as policies capability, human resources capability and facilities capability have a positive relationship with the performance of technological innovation (TIP). These findings will help the government in making decisions and better implementation of policies to strengthen the competitiveness of the company, particularly in resource-based manufacturing.

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.

SCANAIR a transient fuel performance code Part two: Assessment of modelling capabilities

Energy Technology Data Exchange (ETDEWEB)

Georgenthum, Vincent, E-mail: vincent.georgenthum@irsn.fr; Moal, Alain; Marchand, Olivier

2014-12-15

Highlights: • The SCANAIR code is devoted to the study of irradiated fuel rod behaviour during RIA. • The paper deals with the status of the code validation for PWR rods. • During the PCMI stage there is a good agreement between calculations and experiments. • The boiling crisis occurrence is rather well predicted. • The code assessment during the boiling crisis has still to be improved. - Abstract: In the frame of their research programmes on fuel safety, the French Institut de Radioprotection et de Sûreté Nucléaire develops the SCANAIR code devoted to the study of irradiated fuel rod behaviour during reactivity initiated accident. A first paper was focused on detailed modellings and code description. This second paper deals with the status of the code validation for pressurised water reactor rods performed thanks to the available experimental results. About 60 integral tests carried out in CABRI and NSRR experimental reactors and 24 separated tests performed in the PATRICIA facility (devoted to the thermal-hydraulics study) have been recalculated and compared to experimental data. During the first stage of the transient, the pellet clad mechanical interaction phase, there is a good agreement between calculations and experiments: the clad residual elongation and hoop strain of non failed tests but also the failure occurrence and failure enthalpy of failed tests are correctly calculated. After this first stage, the increase of cladding temperature can lead to the Departure from Nucleate Boiling. During the film boiling regime, the clad temperature can reach a very high temperature (>700 °C). If the boiling crisis occurrence is rather well predicted, the calculation of the clad temperature and the clad hoop strain during this stage have still to be improved.

Capabilities of Future Training Support Packages

National Research Council Canada - National Science Library

Burnside, Billy

2004-01-01

.... This report identifies and analyzes five key capabilities needed in future TSPs: rapid tailoring or modification, reach, simulated operating environment, performance measurement, and pretests/selection criteria...

Predicting Cavitation on Marine and Hydrokinetic Turbine Blades with AeroDyn V15.04

Energy Technology Data Exchange (ETDEWEB)

Murray, Robynne [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-09-14

Cavitation is an important consideration in the design of marine and hydrokinetic (MHK) turbines. The National Renewable Energy Laboratory's AeroDyn performance code was originally developed for horizontal-axis wind turbines and did not have the capability to predict cavitation inception. Therefore, AeroDyn has been updated to include the ability to predict cavitation on MHK turbines based on user-specified vapor pressure and submerged depth. This report outlines a verification of the AeroDyn V15.04 performance code for MHK turbines through a comparison to publicly available performance data.

Baseline Assessment and Prioritization Framework for IVHM Integrity Assurance Enabling Capabilities

Science.gov (United States)

Cooper, Eric G.; DiVito, Benedetto L.; Jacklin, Stephen A.; Miner, Paul S.

2009-01-01

Fundamental to vehicle health management is the deployment of systems incorporating advanced technologies for predicting and detecting anomalous conditions in highly complex and integrated environments. Integrated structural integrity health monitoring, statistical algorithms for detection, estimation, prediction, and fusion, and diagnosis supporting adaptive control are examples of advanced technologies that present considerable verification and validation challenges. These systems necessitate interactions between physical and software-based systems that are highly networked with sensing and actuation subsystems, and incorporate technologies that are, in many respects, different from those employed in civil aviation today. A formidable barrier to deploying these advanced technologies in civil aviation is the lack of enabling verification and validation tools, methods, and technologies. The development of new verification and validation capabilities will not only enable the fielding of advanced vehicle health management systems, but will also provide new assurance capabilities for verification and validation of current generation aviation software which has been implicated in anomalous in-flight behavior. This paper describes the research focused on enabling capabilities for verification and validation underway within NASA s Integrated Vehicle Health Management project, discusses the state of the art of these capabilities, and includes a framework for prioritizing activities.

Incremental Validity of Personality Measures in Predicting Underwater Performance and Adaptation.

Science.gov (United States)

Colodro, Joaquín; Garcés-de-Los-Fayos, Enrique J; López-García, Juan J; Colodro-Conde, Lucía

2015-03-17

Intelligence and personality traits are currently considered effective predictors of human behavior and job performance. However, there are few studies about their relevance in the underwater environment. Data from a sample of military personnel performing scuba diving courses were analyzed with regression techniques, testing the contribution of individual differences and ascertaining the incremental validity of the personality in an environment with extreme psychophysical demands. The results confirmed the incremental validity of personality traits (ΔR 2 = .20, f 2 = .25) over the predictive contribution of general mental ability (ΔR 2 = .07, f 2 = .08) in divers' performance. Moreover, personality (R(L)2 = .34) also showed a higher validity to predict underwater adaptation than general mental ability ( R(L)2 = .09). The ROC curve indicated 86% of the maximum possible discrimination power for the prediction of underwater adaptation, AUC = .86, p personality traits as predictors of an effective response to the changing circumstances of military scuba diving. They also may improve the understanding of the behavioral effects and psychophysiological complications of diving and can also provide guidance for psychological intervention and prevention of risk in this extreme environment.

Predictive modeling of reactive wetting and metal joining.

Energy Technology Data Exchange (ETDEWEB)

van Swol, Frank B.

2013-09-01

The performance, reproducibility and reliability of metal joints are complex functions of the detailed history of physical processes involved in their creation. Prediction and control of these processes constitutes an intrinsically challenging multi-physics problem involving heating and melting a metal alloy and reactive wetting. Understanding this process requires coupling strong molecularscale chemistry at the interface with microscopic (diffusion) and macroscopic mass transport (flow) inside the liquid followed by subsequent cooling and solidification of the new metal mixture. The final joint displays compositional heterogeneity and its resulting microstructure largely determines the success or failure of the entire component. At present there exists no computational tool at Sandia that can predict the formation and success of a braze joint, as current capabilities lack the ability to capture surface/interface reactions and their effect on interface properties. This situation precludes us from implementing a proactive strategy to deal with joining problems. Here, we describe what is needed to arrive at a predictive modeling and simulation capability for multicomponent metals with complicated phase diagrams for melting and solidification, incorporating dissolutive and composition-dependent wetting.

A comparison of SAR ATR performance with information theoretic predictions

Science.gov (United States)

Blacknell, David

2003-09-01

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

Trait impulsivity predicts D-KEFS tower test performance in university students.

Science.gov (United States)

Lyvers, Michael; Basch, Vanessa; Duff, Helen; Edwards, Mark S

2015-01-01

The present study examined a widely used self-report index of trait impulsiveness in relation to performance on a well-known neuropsychological executive function test in 70 university undergraduate students (50 women, 20 men) aged 18 to 24 years old. Participants completed the Barratt Impulsiveness Scale (BIS-11) and the Frontal Systems Behavior Scale (FrSBe), after which they performed the Tower Test of the Delis-Kaplan Executive Function System. Hierarchical linear regression showed that after controlling for gender, current alcohol consumption, age at onset of weekly alcohol use, and FrSBe scores, BIS-11 significantly predicted Tower Test Achievement scores, β = -.44, p impulsiveness is associated with poorer executive cognitive performance even in a sample likely to be characterized by relatively high general cognitive functioning (i.e., university students). The results also support the role of inhibition as a key aspect of executive task performance. Elevated scores on the BIS-11 and FrSBe are known to be linked to risky drinking in young adults as confirmed in this sample; however, only BIS-11 predicted Tower Test performance.

Do physiological measures predict selected CrossFit® benchmark performance?

Directory of Open Access Journals (Sweden)

Butcher SJ

2015-07-01

Full Text Available Scotty J Butcher,1,2 Tyler J Neyedly,3 Karla J Horvey,1 Chad R Benko2,41Physical Therapy, University of Saskatchewan, 2BOSS Strength Institute, 3Physiology, University of Saskatchewan, 4Synergy Strength and Conditioning, Saskatoon, SK, CanadaPurpose: CrossFit® is a new but extremely popular method of exercise training and competition that involves constantly varied functional movements performed at high intensity. Despite the popularity of this training method, the physiological determinants of CrossFit performance have not yet been reported. The purpose of this study was to determine whether physiological and/or muscle strength measures could predict performance on three common CrossFit "Workouts of the Day" (WODs.Materials and methods: Fourteen CrossFit Open or Regional athletes completed, on separate days, the WODs "Grace" (30 clean and jerks for time, "Fran" (three rounds of thrusters and pull-ups for 21, 15, and nine repetitions, and "Cindy" (20 minutes of rounds of five pull-ups, ten push-ups, and 15 bodyweight squats, as well as the "CrossFit Total" (1 repetition max [1RM] back squat, overhead press, and deadlift, maximal oxygen consumption (VO2max, and Wingate anaerobic power/capacity testing.Results: Performance of Grace and Fran was related to whole-body strength (CrossFit Total (r=-0.88 and -0.65, respectively and anaerobic threshold (r=-0.61 and -0.53, respectively; however, whole-body strength was the only variable to survive the prediction regression for both of these WODs (R2=0.77 and 0.42, respectively. There were no significant associations or predictors for Cindy.Conclusion: CrossFit benchmark WOD performance cannot be predicted by VO2max, Wingate power/capacity, or either respiratory compensation or anaerobic thresholds. Of the data measured, only whole-body strength can partially explain performance on Grace and Fran, although anaerobic threshold also exhibited association with performance. Along with their typical training

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.

Canadian national nuclear forensics capability project

International Nuclear Information System (INIS)

Ball, J.; Dimayuga, I.; Summerell, I.; Totland, M.; Jonkmans, G.; Whitlock, J.; El-jaby, A.; Inrig, E.

2015-01-01

Following the 2010 Nuclear Security Summit, Canada expanded its existing capability for nuclear forensics by establishing a national nuclear forensics laboratory network, which would include a capability to perform forensic analysis on nuclear and other radioactive material, as well as on traditional evidence contaminated with radioactive material. At the same time, the need for a national nuclear forensics library of signatures of nuclear and radioactive materials under Canadian regulatory control was recognized. The Canadian Safety and Security Program, administered by Defence Research and Development Canada's Centre for Security Science (DRDC CSS), funds science and technology initiatives to enhance Canada's preparedness for prevention of and response to potential threats. DRDC CSS, with assistance from Canadian Nuclear Laboratories, formerly Atomic Energy of Canada Limited, is leading the Canadian National Nuclear Forensics Capability Project to develop a coordinated, comprehensive, and timely national nuclear forensics capability. (author)

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

International Nuclear Information System (INIS)

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

2006-01-01

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

PENGELOLAAN KNOWLEDGE MANAGEMENT CAPABILITY DALAM MEMEDIASI DUKUNGAN INFORMATION TECHNOLOGY RELATEDNESS TERHADAP KINERJA PERUSAHAAN

Directory of Open Access Journals (Sweden)

Luluk Muhimatul Ifada

2011-06-01

Full Text Available The study examines whether or not and how information technology (IT relatedness influences corporate performance. This study proposes that knowledge management (KM is a critical organizational capability through which IT influences firm performance. Measurement of IT relatedness and KM capability uses a reflective second-order factor modeling approach for capturing complementarities among the four dimensions of IT relatedness (IT strategy making processes, IT vendor management processes, IT human resource management processes and IT infrastructure and for capturing complementarities among the three dimensions of KM capability (product KM capability, customer KM capability, and managerial KM capability. A survey was conducted among 93 branch managers of banking in Central Java. Structural Equation Model (SEM was used to analyze the data using the software program of SmartPLS (Partial Least Square. The findings support for the hypotheses of the study. IT relatedness of business units enhances the cross unit KM capability of the corporate. The KM capability creates and exploits cross-unit synergies from the product, customer, and managerial knowledge resources of the corporate. These synergies increase the corporate performance. IT relatedness of business units positively influences corporate performance. IT relatedness also has significant indirect effects on corporate performance through the mediation of KM capability.

Graphical Visualization of Human Exploration Capabilities

Science.gov (United States)

Rodgers, Erica M.; Williams-Byrd, Julie; Arney, Dale C.; Simon, Matthew A.; Williams, Phillip A.; Barsoum, Christopher; Cowan, Tyler; Larman, Kevin T.; Hay, Jason; Burg, Alex

2016-01-01

NASA's pioneering space strategy will require advanced capabilities to expand the boundaries of human exploration on the Journey to Mars (J2M). The Evolvable Mars Campaign (EMC) architecture serves as a framework to identify critical capabilities that need to be developed and tested in order to enable a range of human exploration destinations and missions. Agency-wide System Maturation Teams (SMT) are responsible for the maturation of these critical exploration capabilities and help formulate, guide and resolve performance gaps associated with the EMC-identified capabilities. Systems Capability Organization Reporting Engine boards (SCOREboards) were developed to integrate the SMT data sets into cohesive human exploration capability stories that can be used to promote dialog and communicate NASA's exploration investments. Each SCOREboard provides a graphical visualization of SMT capability development needs that enable exploration missions, and presents a comprehensive overview of data that outlines a roadmap of system maturation needs critical for the J2M. SCOREboards are generated by a computer program that extracts data from a main repository, sorts the data based on a tiered data reduction structure, and then plots the data according to specified user inputs. The ability to sort and plot varying data categories provides the flexibility to present specific SCOREboard capability roadmaps based on customer requests. This paper presents the development of the SCOREboard computer program and shows multiple complementary, yet different datasets through a unified format designed to facilitate comparison between datasets. Example SCOREboard capability roadmaps are presented followed by a discussion of how the roadmaps are used to: 1) communicate capability developments and readiness of systems for future missions, and 2) influence the definition of NASA's human exploration investment portfolio through capability-driven processes. The paper concludes with a description

On line performance monitoring for predictive maintenance [Paper No.: VIA - 2

International Nuclear Information System (INIS)

Gupta, R.K.; Chandra, Rajesh

1981-01-01

There will always be progressive deterioration in the performance of dynamic equipment due to normal inevitable wear, malfunctions, failures and other reasons. In most cases it is possible to monitor some parameters of a system which would get progressively affected with the deterioration in the health of the system. By on-line monitoring of such predetermined parameters, compared with preset base data generated for a healthy system earlier, would prove very helpful in avoiding breakdowns and in proper planning of preventive and predictive maintenance. With increasing use of on-line computerised controls the generation of design base data and also the in-built self checking feature of monitoring the equipment health can be achieved by incorporating suitable software. This type of system will be helpful in: (a) predicting the life of component, (b) prewarning the operator about impending malfunctions, (c) establishing a maintenance schedule and spare inventory, and (d) analysing the failures. This type of centralised predictive maintenance is increasingly becoming important where: (a) the number of equipments are large, (b) the operation of equipment is critical from safety criteria, and (c) the minimum safety margin in the performance of the component is to be maintained. Keeping this in mind, the Fuel Handling System of Narora Atomic Power Project and the future power plants having computerised controls will have facility for on-line performance monitoring for predictive maintenance. The paper also describes methodology of the technique in detail, with a few representative cases. (author)

Application of analytical capability to predict rapid cladding cooling and quench during the blowdown phase of a large break loss-of-coolant accident

International Nuclear Information System (INIS)

Aksan, S.N.; Tolman, E.L.; Nelson, R.A.

1983-01-01

Large-break Experiments L2-2 and L2-3 conducted in the Loss-of-Fluid Test (LOFT) facility experienced core-wide rapid quenches early in the blowdown transients. To further investigate rapid cladding quenches, separate effects experiments using Semiscale solid-type electric heater rods were conducted in the LOFT Test Support Facility (LTSF) over a wide range of inlet coolant conditions. The analytical capability to predict the cladding temperature response from selected LTSF experiments estimated to bound the hydraulic conditions causing the LOFT early blowdown quenches was investigated using the RELAP4 computer code and was shown to be acceptable over the film boiling cooldown phase. This analytical capability was then used to investigate the behavior of nuclear fuel rods under the same hydraulic conditions. The calculations show that, under rapid cooling conditions, the behaviors of nuclear and electrical heater rods are significantly different because the nuclear rods are conduction limited, while the electrical rods are convection limited

Methods of ecological capability evaluation of forest

International Nuclear Information System (INIS)

Hosseini, M.; Makhdoum, M.F.; Akbarnia, M.; Saghebtalebi, Kh.

2000-01-01

In this research common methods of ecological capability evaluation of forests were reviewed and limitations for performance were analysed. Ecological capability of forests is an index that show site potential in several role of wood production, soil conservation, flood control, biodiversity, conservation and water supply. This index is related to ecological characteristics of land, such as soil, micro climate, elevation, slope and aspect that affect potential of sites. Suitable method of ecological capability evaluation must be chosen according to the objective of forestry. Common methods for ecological capability evaluation include plant and animal diversity, site index curve, soil and land form, inter branches, index plants, leave analyses, analyses regeneration and ecological mapping

Optimizing Blasting’s Air Overpressure Prediction Model using Swarm Intelligence

Science.gov (United States)

Nur Asmawisham Alel, Mohd; Ruben Anak Upom, Mark; Asnida Abdullah, Rini; Hazreek Zainal Abidin, Mohd

2018-04-01

Air overpressure (AOp) resulting from blasting can cause damage and nuisance to nearby civilians. Thus, it is important to be able to predict AOp accurately. In this study, 8 different Artificial Neural Network (ANN) were developed for the purpose of prediction of AOp. The ANN models were trained using different variants of Particle Swarm Optimization (PSO) algorithm. AOp predictions were also made using an empirical equation, as suggested by United States Bureau of Mines (USBM), to serve as a benchmark. In order to develop the models, 76 blasting operations in Hulu Langat were investigated. All the ANN models were found to outperform the USBM equation in three performance metrics; root mean square error (RMSE), mean absolute percentage error (MAPE) and coefficient of determination (R2). Using a performance ranking method, MSO-Rand-Mut was determined to be the best prediction model for AOp with a performance metric of RMSE=2.18, MAPE=1.73% and R2=0.97. The result shows that ANN models trained using PSO are capable of predicting AOp with great accuracy.

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

International Nuclear Information System (INIS)

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

2007-01-01

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

Research for new UAV capabilities

Energy Technology Data Exchange (ETDEWEB)

Canavan, G.H.; Leadabrand, R.

1996-07-01

This paper discusses research for new Unmanned Aerial Vehicles (UAV) capabilities. Findings indicate that UAV performance could be greatly enhanced by modest research. Improved sensors and communications enhance near term cost effectiveness. Improved engines, platforms, and stealth improve long term effectiveness.

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)

Using a Simple Binomial Model to Assess Improvement in Predictive Capability: Sequential Bayesian Inference, Hypothesis Testing, and Power Analysis

Energy Technology Data Exchange (ETDEWEB)

Sigeti, David E. [Los Alamos National Laboratory; Pelak, Robert A. [Los Alamos National Laboratory

2012-09-11

We present a Bayesian statistical methodology for identifying improvement in predictive simulations, including an analysis of the number of (presumably expensive) simulations that will need to be made in order to establish with a given level of confidence that an improvement has been observed. Our analysis assumes the ability to predict (or postdict) the same experiments with legacy and new simulation codes and uses a simple binomial model for the probability, {theta}, that, in an experiment chosen at random, the new code will provide a better prediction than the old. This model makes it possible to do statistical analysis with an absolute minimum of assumptions about the statistics of the quantities involved, at the price of discarding some potentially important information in the data. In particular, the analysis depends only on whether or not the new code predicts better than the old in any given experiment, and not on the magnitude of the improvement. We show how the posterior distribution for {theta} may be used, in a kind of Bayesian hypothesis testing, both to decide if an improvement has been observed and to quantify our confidence in that decision. We quantify the predictive probability that should be assigned, prior to taking any data, to the possibility of achieving a given level of confidence, as a function of sample size. We show how this predictive probability depends on the true value of {theta} and, in particular, how there will always be a region around {theta} = 1/2 where it is highly improbable that we will be able to identify an improvement in predictive capability, although the width of this region will shrink to zero as the sample size goes to infinity. We show how the posterior standard deviation may be used, as a kind of 'plan B metric' in the case that the analysis shows that {theta} is close to 1/2 and argue that such a plan B should generally be part of hypothesis testing. All the analysis presented in the paper is done with a

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.

Capabilities and diagnostics of the Sandia Pelletron-raster system

International Nuclear Information System (INIS)

Buckalew, W.H.; Lockwood, G.J.; Luker, S.M.; Ruggles, L.E.; Wyant, F.J.

1984-07-01

The radiation capabilities of the PELLETRON Electron Beam Accelerator have been expanded to include a controllable, variable dimension, beam diffusion option. This rastered beam option has been studied in detail. Beam characteristics have been determined as a function of incident electron beam energy, current, and deflection system parameters. The beam diagnostics required to define any given diffuse beam pattern are accurate and predictable. Recently, utility of this added PELLETRON capability was demonstrated by simulating the effects of complex nuclear reactor accident electron environments on electrical insulation materials similar to those used in nuclear power plants

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.

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

Science.gov (United States)

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

2008-01-01

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

ACCEPT: Introduction of the Adverse Condition and Critical Event Prediction Toolbox

Science.gov (United States)

Martin, Rodney A.; Santanu, Das; Janakiraman, Vijay Manikandan; Hosein, Stefan

2015-01-01

The prediction of anomalies or adverse events is a challenging task, and there are a variety of methods which can be used to address the problem. In this paper, we introduce a generic framework developed in MATLAB (sup registered mark) called ACCEPT (Adverse Condition and Critical Event Prediction Toolbox). ACCEPT is an architectural framework designed to compare and contrast the performance of a variety of machine learning and early warning algorithms, and tests the capability of these algorithms to robustly predict the onset of adverse events in any time-series data generating systems or processes.

Development of a model capable of predicting the performance of piston ring-cylinder liner-like tribological interfaces

DEFF Research Database (Denmark)

Felter, C.L.; Vølund, A.; Imran, Tajammal

2010-01-01

Friction in the piston ring package (piston, piston rings, and liner) is a major source of power consumption in large two-stroke marine diesel engines. In order to improve the frictional and wear performance, knowledge about the tribological interface between piston rings and liner is needed...

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