WorldWideScience

Sample records for positive predictive power

  1. The Power of Positive Emotions

    Science.gov (United States)

    ... Safe Videos for Educators Search English Español The Power of Positive Emotions KidsHealth / For Teens / The Power ... great one. 2. Practice Positivity Every Day Building habits that encourage us to feel more positive emotions ...

  2. Wind power prediction models

    Science.gov (United States)

    Levy, R.; Mcginness, H.

    1976-01-01

    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  3. Felt power explains the link between position power and experienced emotions.

    Science.gov (United States)

    Bombari, Dario; Schmid Mast, Marianne; Bachmann, Manuel

    2017-02-01

    The approach/inhibition theory by Keltner, Gruenfeld, and Anderson (2003) predicts that powerful people should feel more positive and less negative emotions. To date, results of studies investigating this prediction are inconsistent. We fill this gap with four studies in which we investigated the role of different conceptualizations of power: felt power and position power. In Study 1, participants were made to feel more or less powerful and we tested how their felt power was related to different emotional states. In Studies 2, 3, and 4, participants were assigned to either a high or a low power role and engaged in an interaction with a virtual human, after which participants reported on how powerful they felt and the emotions they experienced during the interaction. We meta-analytically combined the results of the four studies and found that felt power was positively related to positive emotions (happiness and serenity) and negatively to negative emotions (fear, anger, and sadness), whereas position power did not show any significant overall relation with any of the emotional states. Importantly, felt power mediated the relationship between position power and emotion. In summary, we show that how powerful a person feels in a given social interaction is the driving force linking the person's position power to his or her emotional states. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  4. IFE Target Injection Tracking and Position Prediction Update

    International Nuclear Information System (INIS)

    Petzoldt, Ronald W.; Jonestrask, Kevin

    2005-01-01

    To achieve high gain in an inertial fusion energy power plant, driver beams must hit direct drive targets with ±20 μm accuracy (±100 μm for indirect drive). Targets will have to be tracked with even greater accuracy. The conceptual design for our tracking system, which predicts target arrival position and timing based on position measurements outside of the reaction chamber was previously described. The system has been built and has begun tracking targets at the first detector station. Additional detector stations are being modified for increased field of view. After three tracking stations are operational, position predictions at the final station will be compared to position measurements at that station as a measure of target position prediction accuracy.The as-installed design will be described together with initial target tracking and position prediction accuracy results. Design modifications that allow for improved accuracy and/or in-chamber target tracking will also be presented

  5. Reward positivity: Reward prediction error or salience prediction error?

    Science.gov (United States)

    Heydari, Sepideh; Holroyd, Clay B

    2016-08-01

    The reward positivity is a component of the human ERP elicited by feedback stimuli in trial-and-error learning and guessing tasks. A prominent theory holds that the reward positivity reflects a reward prediction error signal that is sensitive to outcome valence, being larger for unexpected positive events relative to unexpected negative events (Holroyd & Coles, 2002). Although the theory has found substantial empirical support, most of these studies have utilized either monetary or performance feedback to test the hypothesis. However, in apparent contradiction to the theory, a recent study found that unexpected physical punishments also elicit the reward positivity (Talmi, Atkinson, & El-Deredy, 2013). The authors of this report argued that the reward positivity reflects a salience prediction error rather than a reward prediction error. To investigate this finding further, in the present study participants navigated a virtual T maze and received feedback on each trial under two conditions. In a reward condition, the feedback indicated that they would either receive a monetary reward or not and in a punishment condition the feedback indicated that they would receive a small shock or not. We found that the feedback stimuli elicited a typical reward positivity in the reward condition and an apparently delayed reward positivity in the punishment condition. Importantly, this signal was more positive to the stimuli that predicted the omission of a possible punishment relative to stimuli that predicted a forthcoming punishment, which is inconsistent with the salience hypothesis. © 2016 Society for Psychophysiological Research.

  6. Positive year for Alberta power pool

    International Nuclear Information System (INIS)

    Reid-Carlson, D.

    1997-01-01

    The electricity power pool in Alberta completed its first year under deregulation. Results to date indicate that the competitive market has operated as intended. The effects of electricity pricing on the oil industry following deregulation were described, given the fact that electricity prices represent the second largest cost item to the oil industry after labour. The peculiarities of the mechanism of electricity pricing (based on hourly matching of supply offers to demand bids) were explained, highlighting the opportunities and risks to the oil industry caused by the hourly price variations and the difficulties involved in accurately forecasting on-peak and off-peak prices a full year in advance. In 1996 predicted average price was $14 to $17/MWh. The actual average price was $13.40/MWh. The general conclusion was that Alberta continues to have a surplus of electricity generation and is well positioned to to take advantage of its low generating costs, at least over the longer term. Short term bidding practices, however, may results in slightly higher system marginal prices

  7. Positivity of linear maps under tensor powers

    Energy Technology Data Exchange (ETDEWEB)

    Müller-Hermes, Alexander, E-mail: muellerh@ma.tum.de; Wolf, Michael M., E-mail: m.wolf@tum.de [Zentrum Mathematik, Technische Universität München, 85748 Garching (Germany); Reeb, David, E-mail: reeb.qit@gmail.com [Zentrum Mathematik, Technische Universität München, 85748 Garching (Germany); Institute for Theoretical Physics, Leibniz Universität Hannover, 30167 Hannover (Germany)

    2016-01-15

    We investigate linear maps between matrix algebras that remain positive under tensor powers, i.e., under tensoring with n copies of themselves. Completely positive and completely co-positive maps are trivial examples of this kind. We show that for every n ∈ ℕ, there exist non-trivial maps with this property and that for two-dimensional Hilbert spaces there is no non-trivial map for which this holds for all n. For higher dimensions, we reduce the existence question of such non-trivial “tensor-stable positive maps” to a one-parameter family of maps and show that an affirmative answer would imply the existence of non-positive partial transpose bound entanglement. As an application, we show that any tensor-stable positive map that is not completely positive yields an upper bound on the quantum channel capacity, which for the transposition map gives the well-known cb-norm bound. We, furthermore, show that the latter is an upper bound even for the local operations and classical communications-assisted quantum capacity, and that moreover it is a strong converse rate for this task.

  8. Positivity of linear maps under tensor powers

    International Nuclear Information System (INIS)

    Müller-Hermes, Alexander; Wolf, Michael M.; Reeb, David

    2016-01-01

    We investigate linear maps between matrix algebras that remain positive under tensor powers, i.e., under tensoring with n copies of themselves. Completely positive and completely co-positive maps are trivial examples of this kind. We show that for every n ∈ ℕ, there exist non-trivial maps with this property and that for two-dimensional Hilbert spaces there is no non-trivial map for which this holds for all n. For higher dimensions, we reduce the existence question of such non-trivial “tensor-stable positive maps” to a one-parameter family of maps and show that an affirmative answer would imply the existence of non-positive partial transpose bound entanglement. As an application, we show that any tensor-stable positive map that is not completely positive yields an upper bound on the quantum channel capacity, which for the transposition map gives the well-known cb-norm bound. We, furthermore, show that the latter is an upper bound even for the local operations and classical communications-assisted quantum capacity, and that moreover it is a strong converse rate for this task

  9. Staying Power of Churn Prediction Models

    NARCIS (Netherlands)

    Risselada, Hans; Verhoef, Peter C.; Bijmolt, Tammo H. A.

    In this paper, we study the staying power of various churn prediction models. Staying power is defined as the predictive performance of a model in a number of periods after the estimation period. We examine two methods, logit models and classification trees, both with and without applying a bagging

  10. Conditional prediction intervals of wind power generation

    DEFF Research Database (Denmark)

    Pinson, Pierre; Kariniotakis, Georges

    2010-01-01

    A generic method for the providing of prediction intervals of wind power generation is described. Prediction intervals complement the more common wind power point forecasts, by giving a range of potential outcomes for a given probability, their so-called nominal coverage rate. Ideally they inform...... on the characteristics of prediction errors for providing conditional interval forecasts. By simultaneously generating prediction intervals with various nominal coverage rates, one obtains full predictive distributions of wind generation. Adapted resampling is applied here to the case of an onshore Danish wind farm...... to the case of a large number of wind farms in Europe and Australia among others is finally discussed....

  11. Composable and Predictable Power Management

    NARCIS (Netherlands)

    Nelson, A.T.

    2014-01-01

    The functionality of embedded systems is ever growing. The computational power of embedded systems is growing to match this demand, with embedded multiprocessor systems becoming more common. The limitations of embedded systems are not always related to chip size but are commonly due to energy and/or

  12. Positional accommodative intraocular lens power error induced by the estimation of the corneal power and the effective lens position

    Directory of Open Access Journals (Sweden)

    David P Piñero

    2015-01-01

    Full Text Available Purpose: To evaluate the predictability of the refractive correction achieved with a positional accommodating intraocular lenses (IOL and to develop a potential optimization of it by minimizing the error associated with the keratometric estimation of the corneal power and by developing a predictive formula for the effective lens position (ELP. Materials and Methods: Clinical data from 25 eyes of 14 patients (age range, 52-77 years and undergoing cataract surgery with implantation of the accommodating IOL Crystalens HD (Bausch and Lomb were retrospectively reviewed. In all cases, the calculation of an adjusted IOL power (P IOLadj based on Gaussian optics considering the residual refractive error was done using a variable keratometric index value (n kadj for corneal power estimation with and without using an estimation algorithm for ELP obtained by multiple regression analysis (ELP adj . P IOLadj was compared to the real IOL power implanted (P IOLReal , calculated with the SRK-T formula and also to the values estimated by the Haigis, HofferQ, and Holladay I formulas. Results: No statistically significant differences were found between P IOLReal and P IOLadj when ELP adj was used (P = 0.10, with a range of agreement between calculations of 1.23 D. In contrast, P IOLReal was significantly higher when compared to P IOLadj without using ELP adj and also compared to the values estimated by the other formulas. Conclusions: Predictable refractive outcomes can be obtained with the accommodating IOL Crystalens HD using a variable keratometric index for corneal power estimation and by estimating ELP with an algorithm dependent on anatomical factors and age.

  13. Wind Power Prediction using Ensembles

    DEFF Research Database (Denmark)

    Giebel, Gregor; Badger, Jake; Landberg, Lars

    2005-01-01

    offshore wind farm and the whole Jutland/Funen area. The utilities used these forecasts for maintenance planning, fuel consumption estimates and over-the-weekend trading on the Leipzig power exchange. Othernotable scientific results include the better accuracy of forecasts made up from a simple...... superposition of two NWP provider (in our case, DMI and DWD), an investigation of the merits of a parameterisation of the turbulent kinetic energy within thedelivered wind speed forecasts, and the finding that a “naïve” downscaling of each of the coarse ECMWF ensemble members with higher resolution HIRLAM did...

  14. Wind Power Prediction Considering Nonlinear Atmospheric Disturbances

    Directory of Open Access Journals (Sweden)

    Yagang Zhang

    2015-01-01

    Full Text Available This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance are put forward in this study. Firstly, we define the form of the Lorenz disturbance variable and the wind speed perturbation formula. Then, different artificial neural network models are used to verify the new idea and obtain better wind speed predictions. Finally we separately use the original and improved wind speed series to predict the related wind power. This proves that the corrected wind speed provides higher precision wind power predictions. This research presents a totally new direction in the wind prediction field and has profound theoretical research value and practical guiding significance.

  15. Position control of a floating nuclear power plant

    International Nuclear Information System (INIS)

    Motohashi, K.; Hamamoto, T.; Sasaki, R.; Kojima, M.

    1993-01-01

    In spite of the increasing demand of electricity in Japan, the sites of nuclear power plants suitable for conventional seismic regulations become severely limited. Under these circumstances, several types of advanced siting technology have been developed. Among them, floating power plants have a great advantage of seismic isolation that leads to the seismic design standardization and factory fabrication. The feasibility studies or preliminary designs of floating power plants enclosed by breakwaters in the shallow sea have been carried out last two decades in U.S. and Japan. On the other hand, there are few investigations on the dynamic behavior of floating power plants in the deep sea. The offshore floating nuclear power plants have an additional advantage in that large breakwaters are not required, although the safety checking is inevitable against wind-induced waves. The tension-leg platforms which have been constructed for oil drilling in the deep sea seem to be a promising offshore siting technology of nuclear power plants. The tension-leg mooring system can considerably restrain the heave and pitch of a floating power plant because of significant stiffness in the vertical direction. Different from seismic effects, wind-induced waves may be predicted in advance by making use of ocean weather forecasts using artificial satellites. According to the wave prediction, the position of the floating plant may be controlled by adjusting the water content in ballast tanks and the length of tension-legs before the expected load arrives. The position control system can reduce the wave force acting on the plant and to avoid the unfavorable response behavior of the plant. In this study a semi-submerged circular cylinder with tension-legs is considered as a mathematical model. The configuration of circular cylinder is effective because the dynamic behavior does not depend on incident wave directions. It is also unique in that it can obtain the closed-form solution of

  16. Short-term wind power prediction

    DEFF Research Database (Denmark)

    Joensen, Alfred K.

    2003-01-01

    , and to implement these models and methods in an on-line software application. The economical value of having predictions available is also briefly considered. The summary report outlines the background and motivation for developing wind power prediction models. The meteorological theory which is relevant......The present thesis consists of 10 research papers published during the period 1997-2002 together with a summary report. The objective of the work described in the thesis is to develop models and methods for calculation of high accuracy predictions of wind power generated electricity...

  17. Simulators predict power plant operation

    Energy Technology Data Exchange (ETDEWEB)

    Peltier, R.

    2002-07-01

    Mix the complexity of a new construction or major retrofit project with today's 'do more with less', a pinch of 'personnel inexperience,' and a dash of 'unintended consequences', and you have got a recipe for insomnia. Advanced simulation tools, however, can help you wring out your design train your operators before the first wire is terminated and just may be get a good night's rest. The article describes several examples of uses of simulation tools. Esscor recently completed a simulation project for a major US utility exploring the potential for furnace/duct implosion that could result from adding higher volumetric flow induced-draft fans and selective catalytic reduction to a 650-MW coal-fired plant. CAF Electronics Inc. provided a full-scope simulator for Alstom's KA24-1 combined-cycle power plant in Paris, France. Computational fluid dynamics (CFD) tools are being used by the Gas Technology Institute to simulate the performance of the next generation of pulverized coal combustors. 5 figs.

  18. Free positioning for inductive wireless power system

    NARCIS (Netherlands)

    Waffenschmidt, E.

    2012-01-01

    In inductive wireless power transmission system a lateral displacement of the receiver coil to the transmitter coil leads to a change ofthe coupling factor and thus an unwanted variation of the power transfer. Here, an algorithm to determine the turn distribution to achieve homogeneous coupling

  19. Improved techniques for predicting spacecraft power

    International Nuclear Information System (INIS)

    Chmielewski, A.B.

    1987-01-01

    Radioisotope Thermoelectric Generators (RTGs) are going to supply power for the NASA Galileo and Ulysses spacecraft now scheduled to be launched in 1989 and 1990. The duration of the Galileo mission is expected to be over 8 years. This brings the total RTG lifetime to 13 years. In 13 years, the RTG power drops more than 20 percent leaving a very small power margin over what is consumed by the spacecraft. Thus it is very important to accurately predict the RTG performance and be able to assess the magnitude of errors involved. The paper lists all the error sources involved in the RTG power predictions and describes a statistical method for calculating the tolerance

  20. Can slide positivity rates predict malaria transmission?

    Directory of Open Access Journals (Sweden)

    Bi Yan

    2012-04-01

    Full Text Available Abstract Background Malaria is a significant threat to population health in the border areas of Yunnan Province, China. How to accurately measure malaria transmission is an important issue. This study aimed to examine the role of slide positivity rates (SPR in malaria transmission in Mengla County, Yunnan Province, China. Methods Data on annual malaria cases, SPR and socio-economic factors for the period of 1993 to 2008 were obtained from the Center for Disease Control and Prevention (CDC and the Bureau of Statistics, Mengla, China. Multiple linear regression models were conducted to evaluate the relationship between socio-ecologic factors and malaria incidence. Results The results show that SPR was significantly positively associated with the malaria incidence rates. The SPR (β = 1.244, p = 0.000 alone and combination (SPR, β = 1.326, p  Conclusion SPR is a strong predictor of malaria transmission, and can be used to improve the planning and implementation of malaria elimination programmes in Mengla and other similar locations. SPR might also be a useful indicator of malaria early warning systems in China.

  1. Blind prediction of interfacial water positions in CAPRI

    NARCIS (Netherlands)

    Lensink, Marc F; Moal, Iain H; Bates, Paul A; Kastritis, Panagiotis L; Melquiond, Adrien S J; Karaca, Ezgi; Schmitz, Christophe; van Dijk, Marc; Bonvin, Alexandre M J J; Eisenstein, Miriam; Jiménez-García, Brian; Grosdidier, Solène; Solernou, Albert; Pérez-Cano, Laura; Pallara, Chiara; Fernández-Recio, Juan; Xu, Jianqing; Muthu, Pravin; Praneeth Kilambi, Krishna; Gray, Jeffrey J; Grudinin, Sergei; Derevyanko, Georgy; Mitchell, Julie C; Wieting, John; Kanamori, Eiji; Tsuchiya, Yuko; Murakami, Yoichi; Sarmiento, Joy; Standley, Daron M; Shirota, Matsuyuki; Kinoshita, Kengo; Nakamura, Haruki; Chavent, Matthieu; Ritchie, David W; Park, Hahnbeom; Ko, Junsu; Lee, Hasup; Seok, Chaok; Shen, Yang; Kozakov, Dima; Vajda, Sandor; Kundrotas, Petras J; Vakser, Ilya A; Pierce, Brian G; Hwang, Howook; Vreven, Thom; Weng, Zhiping; Buch, Idit; Farkash, Efrat; Wolfson, Haim J; Zacharias, Martin; Qin, Sanbo; Zhou, Huan-Xiang; Huang, Shen-You; Zou, Xiaoqin; Wojdyla, Justyna A; Kleanthous, Colin; Wodak, Shoshana J

    We report the first assessment of blind predictions of water positions at protein-protein interfaces, performed as part of the critical assessment of predicted interactions (CAPRI) community-wide experiment. Groups submitting docking predictions for the complex of the DNase domain of colicin E2 and

  2. The wind power prediction research based on mind evolutionary algorithm

    Science.gov (United States)

    Zhuang, Ling; Zhao, Xinjian; Ji, Tianming; Miao, Jingwen; Cui, Haina

    2018-04-01

    When the wind power is connected to the power grid, its characteristics of fluctuation, intermittent and randomness will affect the stability of the power system. The wind power prediction can guarantee the power quality and reduce the operating cost of power system. There were some limitations in several traditional wind power prediction methods. On the basis, the wind power prediction method based on Mind Evolutionary Algorithm (MEA) is put forward and a prediction model is provided. The experimental results demonstrate that MEA performs efficiently in term of the wind power prediction. The MEA method has broad prospect of engineering application.

  3. Uncertainties in predicting solar panel power output

    Science.gov (United States)

    Anspaugh, B.

    1974-01-01

    The problem of calculating solar panel power output at launch and during a space mission is considered. The major sources of uncertainty and error in predicting the post launch electrical performance of the panel are considered. A general discussion of error analysis is given. Examples of uncertainty calculations are included. A general method of calculating the effect on the panel of various degrading environments is presented, with references supplied for specific methods. A technique for sizing a solar panel for a required mission power profile is developed.

  4. Automation of Aditya tokamak plasma position control DC power supply

    Energy Technology Data Exchange (ETDEWEB)

    Arambhadiya, Bharat, E-mail: bharat@ipr.res.in; Raj, Harshita; Tanna, R.L.; Edappala, Praveenlal; Rajpal, Rachana; Ghosh, Joydeep; Chattopadhyay, P.K.; Kalal, M.B.

    2016-11-15

    Highlights: • Plasma position control is very essential for obtaining repeatable high temperature, high-density discharges of longer durations in tokomak. • The present capacitor bank has limitations of maximum current capacity and position control beyond 200 ms. • The installation of a separate set of coils and a DC power supply can control the plasma position beyond 200 ms. • A high power thyristor (T588N1200) triggers for DC current pulse of 300 A fires precisely at required positions to modify plasma position. • The commissioning is done for the automated in-house, quick and reliable solution. - Abstract: Plasma position control is essential for obtaining repeatable high temperature, high-density discharges of longer duration in tokamaks. Recently, a set of external coils is installed in the vertical field mode configuration to control the radial plasma position in ADITYA tokamak. The existing capacitor bank cannot provide the required current pulse beyond 200 ms for position control. This motivated to have a DC power supply of 500 A to provide current pulse beyond 200 ms for the position control. The automatization of the DC power supply mandated interfaces with the plasma control system, Aditya Pulse Power supply, and Data acquisition system for coordinated discharge operation. A high current thyristor circuit and a timer circuit have been developed for controlling the power supply automatically for charging vertical field coils of Aditya tokamak. Key protection interlocks implemented in the development ensure machine and occupational safety. Fiber-optic trans-receiver isolates the power supply with other subsystems, while analog channel is optically isolated. Commissioning and testing established proper synchronization of the power supply with tokamak operation. The paper discusses the automation of the DC power supply with main circuit components, timing control, and testing results.

  5. Feature Selection and ANN Solar Power Prediction

    Directory of Open Access Journals (Sweden)

    Daniel O’Leary

    2017-01-01

    Full Text Available A novel method of solar power forecasting for individuals and small businesses is developed in this paper based on machine learning, image processing, and acoustic classification techniques. Increases in the production of solar power at the consumer level require automated forecasting systems to minimize loss, cost, and environmental impact for homes and businesses that produce and consume power (prosumers. These new participants in the energy market, prosumers, require new artificial neural network (ANN performance tuning techniques to create accurate ANN forecasts. Input masking, an ANN tuning technique developed for acoustic signal classification and image edge detection, is applied to prosumer solar data to improve prosumer forecast accuracy over traditional macrogrid ANN performance tuning techniques. ANN inputs tailor time-of-day masking based on error clustering in the time domain. Results show an improvement in prediction to target correlation, the R2 value, lowering inaccuracy of sample predictions by 14.4%, with corresponding drops in mean average error of 5.37% and root mean squared error of 6.83%.

  6. Model output statistics applied to wind power prediction

    Energy Technology Data Exchange (ETDEWEB)

    Joensen, A; Giebel, G; Landberg, L [Risoe National Lab., Roskilde (Denmark); Madsen, H; Nielsen, H A [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)

    1999-03-01

    Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.

  7. Potential predictive factors of positive prostate biopsy in the Chinese ...

    African Journals Online (AJOL)

    Yomi

    2012-01-16

    Jan 16, 2012 ... Therefore, it might be inappropriate that we apply these western models to the. Chinese population that has a lower incidence of PCa. Therefore, this retrospective study aimed to determine predictive factors for a positive prostate biopsy in Chinese men. Our ultimate goal is to develop a simple model for ...

  8. Nomogram for predicting the probability of the positive outcome of ...

    African Journals Online (AJOL)

    F.A. Yeboah

    Abstract. Introduction and objectives: Several existing models have been developed to predict positive prostate biopsy among men undergoing evaluation for prostate cancer (PCa). However, most of these models have come from industrialized countries. We therefore, developed a prostate disease nomogram model to ...

  9. Safety prediction technique for nuclear power plants

    International Nuclear Information System (INIS)

    Henry, C.D. III; Anderson, R.T.

    1985-01-01

    This paper presents a safety prediction technique (SPT) developed by Reliability Technology Associates (RTA) for nuclear power plants. It is based on a technique applied by RTA to assess the flight safety of US Air Force aircraft. The purpose of SPT is to provide a computerized technique for objective measurement of the effect on nuclear plant safety of component failure or procedural, software, or human error. A quantification is determined, called criticality, which is proportional to the probability that a given component or procedural-human action will cause the plant to operate in a hazardous mode. A hazardous mode is characterized by the fact that there has been a failure/error and the plant, its operating crew, and the public are exposed to danger. Whether the event results in an accident, an incident, or merely the exposure to danger is dependent on the skill and reaction of the operating crew as well as external influences. There are three major uses of SPT: (a) to predict unsafe situations so that corrective action can be taken before accidents occur, (b) to quantify the impact of equipment malfunction or procedural, software, or human error on safety and thereby establish priorities for proposed modifications, and (c) to provide a means of evaluating proposed changes for their impact on safety prior to implementation and to provide a method of tracking implemented changes

  10. Buyer-Supplier Relationships and Power Position: Interchaining

    Directory of Open Access Journals (Sweden)

    Hebatollah Morsy

    2017-02-01

    Full Text Available According to several studies, power and interdependence play a considerable role in understanding the buyer–supplier relationships, yet, empirical research is still limited. Also, the nature of the buyer-supplier relationship and managing them might vary based on the power position of buyers and suppliers. Few studies focused on the reason behind this interrelation and strong influence of power on the buyer-supplier relationships. Thus, the purpose of this study is to gain better understanding and try to identify how power position and buyer-supplier relationships are interrelated, and whether there are common determinants and/or characteristics behind this strong bond between the two concepts. Both transaction cost analysis theory and social exchange theory were integrated in building the argument. Regarding the methodology, qualitative exploratory research design was employed by using multiple-case study as the main research method, where three multinational Egyptian organizations were selected. Moreover, data was collected using individual in-depth interviews, and analyzed through coding and cross case analysis techniques. The results showed that there are common factors that influence both buyer-supplier relationship characteristics and power position attributes. And according, the findings helped in pointing out a new lens of discussing and investigating the bond between buyer-supplier relationships ad power in research.

  11. Low power predictable memory and processing architectures

    OpenAIRE

    Chen, Jiaoyan

    2013-01-01

    Great demand in power optimized devices shows promising economic potential and draws lots of attention in industry and research area. Due to the continuously shrinking CMOS process, not only dynamic power but also static power has emerged as a big concern in power reduction. Other than power optimization, average-case power estimation is quite significant for power budget allocation but also challenging in terms of time and effort. In this thesis, we will introduce a methodology to support mo...

  12. Positive-Unlabeled Learning for Pupylation Sites Prediction

    Directory of Open Access Journals (Sweden)

    Ming Jiang

    2016-01-01

    Full Text Available Pupylation plays a key role in regulating various protein functions as a crucial posttranslational modification of prokaryotes. In order to understand the molecular mechanism of pupylation, it is important to identify pupylation substrates and sites accurately. Several computational methods have been developed to identify pupylation sites because the traditional experimental methods are time-consuming and labor-sensitive. With the existing computational methods, the experimentally annotated pupylation sites are used as the positive training set and the remaining nonannotated lysine residues as the negative training set to build classifiers to predict new pupylation sites from the unknown proteins. However, the remaining nonannotated lysine residues may contain pupylation sites which have not been experimentally validated yet. Unlike previous methods, in this study, the experimentally annotated pupylation sites were used as the positive training set whereas the remaining nonannotated lysine residues were used as the unlabeled training set. A novel method named PUL-PUP was proposed to predict pupylation sites by using positive-unlabeled learning technique. Our experimental results indicated that PUL-PUP outperforms the other methods significantly for the prediction of pupylation sites. As an application, PUL-PUP was also used to predict the most likely pupylation sites in nonannotated lysine sites.

  13. Predicting Positive and Negative Relationships in Large Social Networks.

    Directory of Open Access Journals (Sweden)

    Guan-Nan Wang

    Full Text Available In a social network, users hold and express positive and negative attitudes (e.g. support/opposition towards other users. Those attitudes exhibit some kind of binary relationships among the users, which play an important role in social network analysis. However, some of those binary relationships are likely to be latent as the scale of social network increases. The essence of predicting latent binary relationships have recently began to draw researchers' attention. In this paper, we propose a machine learning algorithm for predicting positive and negative relationships in social networks inspired by structural balance theory and social status theory. More specifically, we show that when two users in the network have fewer common neighbors, the prediction accuracy of the relationship between them deteriorates. Accordingly, in the training phase, we propose a segment-based training framework to divide the training data into two subsets according to the number of common neighbors between users, and build a prediction model for each subset based on support vector machine (SVM. Moreover, to deal with large-scale social network data, we employ a sampling strategy that selects small amount of training data while maintaining high accuracy of prediction. We compare our algorithm with traditional algorithms and adaptive boosting of them. Experimental results of typical data sets show that our algorithm can deal with large social networks and consistently outperforms other methods.

  14. Predicting Positive and Negative Relationships in Large Social Networks.

    Science.gov (United States)

    Wang, Guan-Nan; Gao, Hui; Chen, Lian; Mensah, Dennis N A; Fu, Yan

    2015-01-01

    In a social network, users hold and express positive and negative attitudes (e.g. support/opposition) towards other users. Those attitudes exhibit some kind of binary relationships among the users, which play an important role in social network analysis. However, some of those binary relationships are likely to be latent as the scale of social network increases. The essence of predicting latent binary relationships have recently began to draw researchers' attention. In this paper, we propose a machine learning algorithm for predicting positive and negative relationships in social networks inspired by structural balance theory and social status theory. More specifically, we show that when two users in the network have fewer common neighbors, the prediction accuracy of the relationship between them deteriorates. Accordingly, in the training phase, we propose a segment-based training framework to divide the training data into two subsets according to the number of common neighbors between users, and build a prediction model for each subset based on support vector machine (SVM). Moreover, to deal with large-scale social network data, we employ a sampling strategy that selects small amount of training data while maintaining high accuracy of prediction. We compare our algorithm with traditional algorithms and adaptive boosting of them. Experimental results of typical data sets show that our algorithm can deal with large social networks and consistently outperforms other methods.

  15. Power load prediction based on GM (1,1)

    Science.gov (United States)

    Wu, Di

    2017-05-01

    Currently, Chinese power load prediction is highly focused; the paper deeply studies grey prediction and applies it to Chinese electricity consumption during the recent 14 years; through after-test test, it obtains grey prediction which has good adaptability to medium and long-term power load.

  16. Switzerland - its position within a liberalised European power market

    International Nuclear Information System (INIS)

    Kiener, E.

    2005-01-01

    This article takes a look at the situation in Switzerland shortly before parliamentary discussions on the liberalisation of Switzerland's electricity market. In particular the interconnection of Switzerland's electricity supply system with that of the rest of Europe is discussed. The power black-out that occurred in Italy in September 2003 is looked at. In particular, its relevance to power supply infrastructures is discussed and the fast-changing international configurations that are resulting from the liberalisation of electricity markets are looked at. Questions of international power transfer capacities and their allocation are looked at in detail in the light of the occurrences in 2003. The lessons that must be learned from the blackout are discussed and Switzerland's geographical position as an important hub of the European power transfer system are considered

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1998-12-31

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

  18. Model Predictive Voltage Control of Wind Power Plants

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei

    2018-01-01

    the efficacy of the proposed WFVC, two case scenarios were designed: the wind farm is under normal operating conditions and the internal wind power fluctuation is considered; and besides internal power fluctuation, the impact of the external grid on the wind farm is considered.......This chapter proposes an autonomous wind farm voltage controller (WFVC) based on model predictive control (MPC). It also introduces the analytical expressions for the voltage sensitivity to tap positions of a transformer. The chapter then describes the discrete models for the wind turbine...... generators (WTGs) and static var compensators (SVCs)/static var generators (SVGs). Next, it describes the implementation of the on‐load tap changing (OLTC) in the MPC. Furthermore, the chapter examines the cost function as well as the constraints of the MPC‐based WFVC for both control modes. In order to test...

  19. Does area V3A predict positions of moving objects?

    Directory of Open Access Journals (Sweden)

    Gerrit W Maus

    2010-11-01

    Full Text Available A gradually fading moving object is perceived to disappear at positions beyond its luminance detection threshold, whereas abrupt offsets are usually localised accurately. What role does retinotopic activity in visual cortex play in this motion-induced mislocalization of the endpoint of fading objects? Using functional magnetic resonance imaging (fMRI, we localised regions of interest (ROIs in retinotopic maps abutting the trajectory endpoint of a bar moving either towards or away from this position while gradually decreasing or increasing in luminance. Area V3A showed predictive activity, with stronger fMRI responses for motion towards versus away from the ROI. This effect was independent of the change in luminance. In Area V1 we found higher activity for high-contrast onsets and offsets near the ROI, but no significant differences between motion directions. We suggest that perceived final positions of moving objects are based on an interplay of predictive position representations in higher motion-sensitive retinotopic areas and offset transients in primary visual cortex.

  20. Sludge pipe flow pressure drop prediction using composite power ...

    African Journals Online (AJOL)

    Sludge pipe flow pressure drop prediction using composite power-law friction ... Water SA. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue ... When predicting pressure gradients for the flow of sludges in pipes, the ...

  1. Positioning Nuclear Power in the Low-Carbon Electricity Transition

    Directory of Open Access Journals (Sweden)

    Aviel Verbruggen

    2017-01-01

    Full Text Available Addressing climate change requires de-carbonizing future energy supplies in an increasingly energy-dependent world. The IEA and the IPCC (2014 mention the following as low-carbon energy supply options: ‘renewable energy, nuclear power and fossil fuels with carbon capture and storage’. Positioning nuclear power in the decarbonization transition is a problematic issue and is overridden by ill-conceived axioms. Before probing these axioms, we provide an overview of five major, postwar energy-related legacies and some insight into who is engaged in nuclear activities. We check whether low-carbon nuclear power passes the full sustainability test and whether it is compatible with the unfettered deployment of variable renewable power sourced from the sun and from wind and water currents, which delivers two negative answers. We show that the best approach of the sustainable energy transition was Germany’s 2011 decision to phase out nuclear power for a fast development and full deployment of renewable power. This is the best approach for the sustainable energy transition. We offer five practical suggestions to strengthen and accelerate carbon- and nuclear-free transitions. They are related to institutional issues like the role of cost-benefit analysis and the mission of the International Atomic Energy Agency, to the costs of nuclear risks and catastrophes, and to the historical record of nuclear technology and business.

  2. Does Andrews facial analysis predict esthetic sagittal maxillary position?

    Science.gov (United States)

    Resnick, Cory M; Daniels, Kimberly M; Vlahos, Maryann

    2018-04-01

    Cephalometric analyses have limited utility in planning maxillary sagittal position for orthognathic surgery. In Six Elements of Orofacial Harmony, Andrews quantified maxillary position relative to forehead projection and angulation and proposed an ideal relationship. The purpose of this study was to investigate the ability of this technique to predict esthetic sagittal maxillary position. Survey study including a male and female with straight facial profiles, normal maxillary incisor angulations, and Angle's Class I. Maxillary position was modified on lateral photographs to create 5 images for each participant with incisor-goal anterior limit line (GALL) distances of -4, -2, 0, +2, and +4 mm. A series of health care professionals and laypeople were asked to rate each photo in order of attractiveness. A total of 100 complete responses were received. Incisor-GALL distances of +4 mm (41%) and +2 mm (40%) were most commonly considered "most esthetic" for the female volunteer (P < .001). For the male volunteer, there were 2 peak "most esthetic" responses: incisor-GALL distances of 0 mm (37%) and -4 mm (32%) (P < .001). Respondents considered maxillary incisor position 2 to 4 mm anterior to GALL most attractive in a woman and 0 to 4 mm posterior to GALL most esthetic in a man. Using these modified target distances, this analysis may be useful for orthognathic surgery planning. Copyright © 2018 Elsevier Inc. All rights reserved.

  3. Predicting Player Position for Talent Identification in Association Football

    Science.gov (United States)

    Razali, Nazim; Mustapha, Aida; Yatim, Faiz Ahmad; Aziz, Ruhaya Ab

    2017-08-01

    This paper is set to introduce a new framework from the perspective of Computer Science for identifying talents in the sport of football based on the players’ individual qualities; physical, mental, and technical. The combination of qualities as assessed by coaches are then used to predict the players’ position in a match that suits the player the best in a particular team formation. Evaluation of the proposed framework is two-fold; quantitatively via classification experiments to predict player position, and qualitatively via a Talent Identification Site developed to achieve the same goal. Results from the classification experiments using Bayesian Networks, Decision Trees, and K-Nearest Neighbor have shown an average of 98% accuracy, which will promote consistency in decision-making though elimination of personal bias in team selection. The positive reviews on the Football Identification Site based on user acceptance evaluation also indicates that the framework is sufficient to serve as the basis of developing an intelligent team management system in different sports, whereby growth and performance of sport players can be monitored and identified.

  4. Feature Selection and ANN Solar Power Prediction

    OpenAIRE

    O’Leary, Daniel; Kubby, Joel

    2017-01-01

    A novel method of solar power forecasting for individuals and small businesses is developed in this paper based on machine learning, image processing, and acoustic classification techniques. Increases in the production of solar power at the consumer level require automated forecasting systems to minimize loss, cost, and environmental impact for homes and businesses that produce and consume power (prosumers). These new participants in the energy market, prosumers, require new artificial neural...

  5. Protein complex prediction via dense subgraphs and false positive analysis.

    Directory of Open Access Journals (Sweden)

    Cecilia Hernandez

    Full Text Available Many proteins work together with others in groups called complexes in order to achieve a specific function. Discovering protein complexes is important for understanding biological processes and predict protein functions in living organisms. Large-scale and throughput techniques have made possible to compile protein-protein interaction networks (PPI networks, which have been used in several computational approaches for detecting protein complexes. Those predictions might guide future biologic experimental research. Some approaches are topology-based, where highly connected proteins are predicted to be complexes; some propose different clustering algorithms using partitioning, overlaps among clusters for networks modeled with unweighted or weighted graphs; and others use density of clusters and information based on protein functionality. However, some schemes still require much processing time or the quality of their results can be improved. Furthermore, most of the results obtained with computational tools are not accompanied by an analysis of false positives. We propose an effective and efficient mining algorithm for discovering highly connected subgraphs, which is our base for defining protein complexes. Our representation is based on transforming the PPI network into a directed acyclic graph that reduces the number of represented edges and the search space for discovering subgraphs. Our approach considers weighted and unweighted PPI networks. We compare our best alternative using PPI networks from Saccharomyces cerevisiae (yeast and Homo sapiens (human with state-of-the-art approaches in terms of clustering, biological metrics and execution times, as well as three gold standards for yeast and two for human. Furthermore, we analyze false positive predicted complexes searching the PDBe (Protein Data Bank in Europe database in order to identify matching protein complexes that have been purified and structurally characterized. Our analysis shows

  6. Positive Disposition in the Prediction of Strategic Independence among Millennials

    Directory of Open Access Journals (Sweden)

    Robert Konopaske

    2017-11-01

    Full Text Available Research on the dispositional traits of Millennials (born in 1980–2000 finds that this generation, compared to earlier generations, tends to be more narcissistic, hold themselves in higher regard and feel more entitled to rewards. The purpose of this intragenerational study is to counter balance extant research by exploring how the positive dispositional traits of proactive personality, core self-evaluation, grit and self-control predict strategic independence in a sample of 311 young adults. Strategic independence is a composite variable measuring a person’s tendency to make plans and achieve long-term goals. A confirmatory factor analysis and hierarchical regression found evidence of discriminant validity across the scales and that three of the four independent variables were statistically significant and positive predictors of strategic independence in the study. The paper discusses research and practical implications, strengths and limitations and areas for future research.

  7. Power Admission Control with Predictive Thermal Management in Smart Buildings

    DEFF Research Database (Denmark)

    Yao, Jianguo; Costanzo, Giuseppe Tommaso; Zhu, Guchuan

    2015-01-01

    This paper presents a control scheme for thermal management in smart buildings based on predictive power admission control. This approach combines model predictive control with budget-schedulability analysis in order to reduce peak power consumption as well as ensure thermal comfort. First...

  8. Mentoring Support and Power: A Three Year Predictive Field Study on Protege Networking and Career Success

    Science.gov (United States)

    Blickle, Gerhard; Witzki, Alexander H.; Schneider, Paula B.

    2009-01-01

    Career success of early employees was analyzed from a power perspective and a developmental network perspective. In a predictive field study with 112 employees mentoring support and mentors' power were assessed in the first wave, employees' networking was assessed after two years, and career success (i.e. income and hierarchical position) and…

  9. Competitive positioning of power generation plants in a deregulated market

    International Nuclear Information System (INIS)

    Stephens, J.

    1998-01-01

    As industrialized countries deregulate their electric power industries, there is a fundamental shift from guaranteed cost recovery to open market competition on a deregulated grid. Utilities generally competitively bid into a power exchange where the lowest cost power providers are dispatched first. Therefore, the competitiveness of utilities determines their profitability. This commercial structure compels power generators to seek out ways of improving their equipment and plant performance. The inevitability of this trend is demonstrated by a look at the installed base in the US where the move toward deregulation is gaining momentum. More than half of the generating plants in the US are over 20 years old. The average thermal efficiency nation-wide is 33%. In contrast, contemporary coal-and gas-fired plants can operate at efficiency levels up to 45 percent and 55 to 60%, respectfully. With new facilities coming on-line, existing plants will need to make improvements to be dispatched. When deregulation fully envelopes the US market, utilities will not all fit into one pattern; their strategies and actions will depend on a multiple set of factors. Their success will be based on their ability to change landscapes from guaranteed cost recovery to competitive bidding. This paper discussers technical and commercial options available to power producers to improve their competitive positions in a deregulated market as well as software for determining the competitiveness of specific power plants and the location-based market prices of electricity. Examples of the application of alternatives will be cited along with expected payback and impact on cents per kilowatt-hour production costs

  10. Development and design of photovoltaic power prediction system

    Science.gov (United States)

    Wang, Zhijia; Zhou, Hai; Cheng, Xu

    2018-02-01

    In order to reduce the impact of power grid safety caused by volatility and randomness of the energy produced in photovoltaic power plants, this paper puts forward a construction scheme on photovoltaic power generation prediction system, introducing the technical requirements, system configuration and function of each module, and discussing the main technical features of the platform software development. The scheme has been applied in many PV power plants in the northwest of China. It shows that the system can produce reasonable prediction results, providing a right guidance for dispatching and efficient running for PV power plant.

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

    DEFF Research Database (Denmark)

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

    2008-01-01

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

  12. Prediction of nucleosome positioning based on transcription factor binding sites.

    Directory of Open Access Journals (Sweden)

    Xianfu Yi

    Full Text Available BACKGROUND: The DNA of all eukaryotic organisms is packaged into nucleosomes, the basic repeating units of chromatin. The nucleosome consists of a histone octamer around which a DNA core is wrapped and the linker histone H1, which is associated with linker DNA. By altering the accessibility of DNA sequences, the nucleosome has profound effects on all DNA-dependent processes. Understanding the factors that influence nucleosome positioning is of great importance for the study of genomic control mechanisms. Transcription factors (TFs have been suggested to play a role in nucleosome positioning in vivo. PRINCIPAL FINDINGS: Here, the minimum redundancy maximum relevance (mRMR feature selection algorithm, the nearest neighbor algorithm (NNA, and the incremental feature selection (IFS method were used to identify the most important TFs that either favor or inhibit nucleosome positioning by analyzing the numbers of transcription factor binding sites (TFBSs in 53,021 nucleosomal DNA sequences and 50,299 linker DNA sequences. A total of nine important families of TFs were extracted from 35 families, and the overall prediction accuracy was 87.4% as evaluated by the jackknife cross-validation test. CONCLUSIONS: Our results are consistent with the notion that TFs are more likely to bind linker DNA sequences than the sequences in the nucleosomes. In addition, our results imply that there may be some TFs that are important for nucleosome positioning but that play an insignificant role in discriminating nucleosome-forming DNA sequences from nucleosome-inhibiting DNA sequences. The hypothesis that TFs play a role in nucleosome positioning is, thus, confirmed by the results of this study.

  13. Eyeball Position in Facial Approximation: Accuracy of Methods for Predicting Globe Positioning in Lateral View.

    Science.gov (United States)

    Zednikova Mala, Pavla; Veleminska, Jana

    2018-01-01

    This study measured the accuracy of traditional and validated newly proposed methods for globe positioning in lateral view. Eighty lateral head cephalograms of adult subjects from Central Europe were taken, and the actual and predicted dimensions were compared. The anteroposterior eyeball position was estimated as the most accurate method based on the proportion of the orbital height (SEE = 1.9 mm) and was followed by the "tangent to the iris method" showing SEE = 2.4 mm. The traditional "tangent to the cornea method" underestimated the eyeball projection by SEE = 5.8 mm. Concerning the superoinferior eyeball position, the results showed a deviation from a central to a more superior position by 0.3 mm, on average, and the traditional method of central positioning of the globe could not be rejected as inaccurate (SEE = 0.3 mm). Based on regression analyzes or proportionality of the orbital height, the SEE = 2.1 mm. © 2017 American Academy of Forensic Sciences.

  14. Predicting Drug-Target Interactions Based on Small Positive Samples.

    Science.gov (United States)

    Hu, Pengwei; Chan, Keith C C; Hu, Yanxing

    2018-01-01

    A basic task in drug discovery is to find new medication in the form of candidate compounds that act on a target protein. In other words, a drug has to interact with a target and such drug-target interaction (DTI) is not expected to be random. Significant and interesting patterns are expected to be hidden in them. If these patterns can be discovered, new drugs are expected to be more easily discoverable. Currently, a number of computational methods have been proposed to predict DTIs based on their similarity. However, such as approach does not allow biochemical features to be directly considered. As a result, some methods have been proposed to try to discover patterns in physicochemical interactions. Since the number of potential negative DTIs are very high both in absolute terms and in comparison to that of the known ones, these methods are rather computationally expensive and they can only rely on subsets, rather than the full set, of negative DTIs for training and validation. As there is always a relatively high chance for negative DTIs to be falsely identified and as only partial subset of such DTIs is considered, existing approaches can be further improved to better predict DTIs. In this paper, we present a novel approach, called ODT (one class drug target interaction prediction), for such purpose. One main task of ODT is to discover association patterns between interacting drugs and proteins from the chemical structure of the former and the protein sequence network of the latter. ODT does so in two phases. First, the DTI-network is transformed to a representation by structural properties. Second, it applies a oneclass classification algorithm to build a prediction model based only on known positive interactions. We compared the best AUROC scores of the ODT with several state-of-art approaches on Gold standard data. The prediction accuracy of the ODT is superior in comparison with all the other methods at GPCRs dataset and Ion channels dataset. Performance

  15. Control rod position and temperature coefficients in HTTR power-rise tests. Interim report

    International Nuclear Information System (INIS)

    Fujimoto, Nozomu; Nojiri, Naoki; Takada, Eiji; Saito, Kenji; Kobayashi, Shoichi; Sawahata, Hiroaki; Kokusen, Sigeru

    2001-03-01

    Power-rise tests of the High Temperature Engineering Test Reactor (HTTR) have been carried out aiming to achieve 100% power. So far, 50% of power operation and many tests have been carried out. In the HTTR, temperature change in core is so large to achieve the outlet coolant temperature of 950degC. To improve the calculation accuracy of the HTTR reactor physics characteristics, control rod positions at criticality and temperature coefficients were measured at each step to achieve 50% power level. The calculations were carried out using Monte Carlo code and diffusion theory with temperature distributions in the core obtained by reciprocal calculation of thermo-hydraulic code and diffusion theory. Control rod positions and temperature coefficients were calculated by diffusion theory and Monte Carlo method. The test results were compared to calculation results. The control rod positions at criticality showed good agreement with calculation results by Monte Carlo method with error of 50 mm. The control position at criticality at 100% was predicted around 2900mm. Temperature coefficients showed good agreement with calculation results by diffusion theory. The improvement of calculation will be carried out comparing the measured results up to 100% power level. (author)

  16. 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.

  17. False positive reduction in protein-protein interaction predictions using gene ontology annotations

    Directory of Open Access Journals (Sweden)

    Lin Yen-Han

    2007-07-01

    Full Text Available Abstract Background Many crucial cellular operations such as metabolism, signalling, and regulations are based on protein-protein interactions. However, the lack of robust protein-protein interaction information is a challenge. One reason for the lack of solid protein-protein interaction information is poor agreement between experimental findings and computational sets that, in turn, comes from huge false positive predictions in computational approaches. Reduction of false positive predictions and enhancing true positive fraction of computationally predicted protein-protein interaction datasets based on highly confident experimental results has not been adequately investigated. Results Gene Ontology (GO annotations were used to reduce false positive protein-protein interactions (PPI pairs resulting from computational predictions. Using experimentally obtained PPI pairs as a training dataset, eight top-ranking keywords were extracted from GO molecular function annotations. The sensitivity of these keywords is 64.21% in the yeast experimental dataset and 80.83% in the worm experimental dataset. The specificities, a measure of recovery power, of these keywords applied to four predicted PPI datasets for each studied organisms, are 48.32% and 46.49% (by average of four datasets in yeast and worm, respectively. Based on eight top-ranking keywords and co-localization of interacting proteins a set of two knowledge rules were deduced and applied to remove false positive protein pairs. The 'strength', a measure of improvement provided by the rules was defined based on the signal-to-noise ratio and implemented to measure the applicability of knowledge rules applying to the predicted PPI datasets. Depending on the employed PPI-predicting methods, the strength varies between two and ten-fold of randomly removing protein pairs from the datasets. Conclusion Gene Ontology annotations along with the deduced knowledge rules could be implemented to partially

  18. Model predictive control for wind power gradients

    DEFF Research Database (Denmark)

    Hovgaard, Tobias Gybel; Boyd, Stephen; Jørgensen, John Bagterp

    2015-01-01

    We consider the operation of a wind turbine and a connected local battery or other electrical storage device, taking into account varying wind speed, with the goal of maximizing the total energy generated while respecting limits on the time derivative (gradient) of power delivered to the grid. We...... ranges. The system dynamics are quite non-linear, and the constraints and objectives are not convex functions of the control inputs, so the resulting optimal control problem is difficult to solve globally. In this paper, we show that by a novel change of variables, which focuses on power flows, we can...... wind data and modern wind forecasting methods. The simulation results using real wind data demonstrate the ability to reject the disturbances from fast changes in wind speed, ensuring certain power gradients, with an insignificant loss in energy production....

  19. Peak Source Power Associated with Positive Narrow Bipolar Lightning Pulses

    Science.gov (United States)

    Bandara, S. A.; Marshall, T. C.; Karunarathne, S.; Karunarathne, N. D.; Siedlecki, R. D., II; Stolzenburg, M.

    2017-12-01

    During the summer of 2016, we deployed a lightning sensor array in and around Oxford Mississippi, USA. The array system comprised seven lightning sensing stations in a network approximately covering an area of 30 km × 30 km. Each station is equipped with four sensors: Fast antenna (10 ms decay time), Slow antenna (1.0 s decay time)), field derivative sensor (dE/dt) and Log-RF antenna (bandwidth 187-192 MHz). We have observed 319 Positive NBPs and herein we report on comparisons of the NBP properties measured from the Fast antenna data with the Log-RF antenna data. These properties include 10-90% rise time, full width at half maximum, zero cross time, and range-normalized amplitude at 100 km. NBPs were categorized according to the fine structure of the electric field wave shapes into Types A-D, as in Karunarathne et al. [2015]. The source powers of NBPs in each category were determined using single station Log-RF data. Furthermore, we also categorized the NBPs in three other groups: initial event of an IC flash, isolated, and not-isolated (according to their spatiotemporal relationship with other lightning activity). We compared the source powers within each category. Karunarathne, S., T. C. Marshall, M. Stolzenburg, and N. Karunarathna (2015), Observations of positive narrow bipolar pulses, J. Geophys. Res. Atmos., 120, doi:10.1002/2015JD023150.

  20. Magnetic storm effects in electric power systems and prediction needs

    Science.gov (United States)

    Albertson, V. D.; Kappenman, J. G.

    1979-01-01

    Geomagnetic field fluctuations produce spurious currents in electric power systems. These currents enter and exit through points remote from each other. The fundamental period of these currents is on the order of several minutes which is quasi-dc compared to the normal 60 Hz or 50 Hz power system frequency. Nearly all of the power systems problems caused by the geomagnetically induced currents result from the half-cycle saturation of power transformers due to simultaneous ac and dc excitation. The effects produced in power systems are presented, current research activity is discussed, and magnetic storm prediction needs of the power industry are listed.

  1. Attentional Bias towards Positive Emotion Predicts Stress Resilience.

    Science.gov (United States)

    Thoern, Hanna A; Grueschow, Marcus; Ehlert, Ulrike; Ruff, Christian C; Kleim, Birgit

    2016-01-01

    There is extensive evidence for an association between an attentional bias towards emotionally negative stimuli and vulnerability to stress-related psychopathology. Less is known about whether selective attention towards emotionally positive stimuli relates to mental health and stress resilience. The current study used a modified Dot Probe task to investigate if individual differences in attentional biases towards either happy or angry emotional stimuli, or an interaction between these biases, are related to self-reported trait stress resilience. In a nonclinical sample (N = 43), we indexed attentional biases as individual differences in reaction time for stimuli preceded by either happy or angry (compared to neutral) face stimuli. Participants with greater attentional bias towards happy faces (but not angry faces) reported higher trait resilience. However, an attentional bias towards angry stimuli moderated this effect: The attentional bias towards happy faces was only predictive for resilience in those individuals who also endorsed an attentional bias towards angry stimuli. An attentional bias towards positive emotional stimuli may thus be a protective factor contributing to stress resilience, specifically in those individuals who also endorse an attentional bias towards negative emotional stimuli. Our findings therefore suggest a novel target for prevention and treatment interventions addressing stress-related psychopathology.

  2. Power Load Prediction Based on Fractal Theory

    OpenAIRE

    Jian-Kai, Liang; Cattani, Carlo; Wan-Qing, Song

    2015-01-01

    The basic theories of load forecasting on the power system are summarized. Fractal theory, which is a new algorithm applied to load forecasting, is introduced. Based on the fractal dimension and fractal interpolation function theories, the correlation algorithms are applied to the model of short-term load forecasting. According to the process of load forecasting, the steps of every process are designed, including load data preprocessing, similar day selecting, short-term load forecasting, and...

  3. VT Predicted Mean Wind Power - 50 meter height

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) Wind power predictions at 50m are generated by a numerical model that simulates weather conditions over a 15-year period, taking into account...

  4. Univariate Time Series Prediction of Solar Power Using a Hybrid Wavelet-ARMA-NARX Prediction Method

    Energy Technology Data Exchange (ETDEWEB)

    Nazaripouya, Hamidreza; Wang, Yubo; Chu, Chi-Cheng; Pota, Hemanshu; Gadh, Rajit

    2016-05-02

    This paper proposes a new hybrid method for super short-term solar power prediction. Solar output power usually has a complex, nonstationary, and nonlinear characteristic due to intermittent and time varying behavior of solar radiance. In addition, solar power dynamics is fast and is inertia less. An accurate super short-time prediction is required to compensate for the fluctuations and reduce the impact of solar power penetration on the power system. The objective is to predict one step-ahead solar power generation based only on historical solar power time series data. The proposed method incorporates discrete wavelet transform (DWT), Auto-Regressive Moving Average (ARMA) models, and Recurrent Neural Networks (RNN), while the RNN architecture is based on Nonlinear Auto-Regressive models with eXogenous inputs (NARX). The wavelet transform is utilized to decompose the solar power time series into a set of richer-behaved forming series for prediction. ARMA model is employed as a linear predictor while NARX is used as a nonlinear pattern recognition tool to estimate and compensate the error of wavelet-ARMA prediction. The proposed method is applied to the data captured from UCLA solar PV panels and the results are compared with some of the common and most recent solar power prediction methods. The results validate the effectiveness of the proposed approach and show a considerable improvement in the prediction precision.

  5. WPPT, a tool for on-line wind power prediction

    Energy Technology Data Exchange (ETDEWEB)

    Skov Nielsen, T. [Dept. of Mathematical Modelling (IMM-DTU), Kgs. Lyngby (Denmark); Madsen, H. [Dept. of Mathematical Modelling (IMM-DTU) Kgs. Lyngby (Denmark); Toefting, J. [Elsam, Fredericia (Denmark)

    2004-07-01

    This paper dsecribes VPPT (Wind Power Prediction Tool), an application for assessing the future available wind power up to 36 hours ahead in time. WPPT has been installed in the Eltra/Elsam central dispatch center since October 1997. The paper describes the prediction model used, the actual implementation of WPPT as well as the experience gained by the operators in the dispatch center (au)

  6. Prediction of Wind Energy Resources (PoWER) Users Guide

    Science.gov (United States)

    2016-01-01

    ARL-TR-7573● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER) User’s Guide by David P Sauter...manufacturer’s or trade names does not constitute an official endorsement or approval of the use thereof. Destroy this report when it is no longer needed. Do...not return it to the originator. ARL-TR-7573 ● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER

  7. Evaluation of peak power prediction equations in male basketball players.

    Science.gov (United States)

    Duncan, Michael J; Lyons, Mark; Nevill, Alan M

    2008-07-01

    This study compared peak power estimated using 4 commonly used regression equations with actual peak power derived from force platform data in a group of adolescent basketball players. Twenty-five elite junior male basketball players (age, 16.5 +/- 0.5 years; mass, 74.2 +/- 11.8 kg; height, 181.8 +/- 8.1 cm) volunteered to participate in the study. Actual peak power was determined using a countermovement vertical jump on a force platform. Estimated peak power was determined using countermovement jump height and body mass. All 4 prediction equations were significantly related to actual peak power (all p jump prediction equations, 12% for the Canavan and Vescovi equation, and 6% for the Sayers countermovement jump equation. In all cases peak power was underestimated.

  8. Wind Power Plant Prediction by Using Neural Networks: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Z.; Gao, W.; Wan, Y. H.; Muljadi, E.

    2012-08-01

    This paper introduces a method of short-term wind power prediction for a wind power plant by training neural networks based on historical data of wind speed and wind direction. The model proposed is shown to achieve a high accuracy with respect to the measured data.

  9. Hybrid robust predictive optimization method of power system dispatch

    Science.gov (United States)

    Chandra, Ramu Sharat [Niskayuna, NY; Liu, Yan [Ballston Lake, NY; Bose, Sumit [Niskayuna, NY; de Bedout, Juan Manuel [West Glenville, NY

    2011-08-02

    A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.

  10. Skill forecasting from ensemble predictions of wind power

    DEFF Research Database (Denmark)

    Pinson, Pierre; Nielsen, Henrik Aalborg; Madsen, Henrik

    2009-01-01

    Optimal management and trading of wind generation calls for the providing of uncertainty estimates along with the commonly provided short-term wind power point predictions. Alternative approaches for the use of probabilistic forecasting are introduced. More precisely, focus is given to prediction...... risk indices aiming to give a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the spread of ensemble forecasts (i.e. a set...... of alternative scenarios for the coming period) for a single prediction horizon or over a took-ahead period. It is shown on the test case of a Danish offshore wind farm how these prediction risk indices may be related to several levels of forecast uncertainty (and potential energy imbalances). Wind power...

  11. Operational results from a physical power prediction model

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L [Risoe National Lab., Meteorology and Wind Energy Dept., Roskilde (Denmark)

    1999-03-01

    This paper will describe a prediction system which predicts the expected power output of a number of wind farms. The system is automatic and operates on-line. The paper will quantify the accuracy of the predictions and will also give examples of the performance for specific storm events. An actual implementation of the system will be described and the robustness demonstrated. (au) 11 refs.

  12. Local Geomagnetic Indices and the Prediction of Auroral Power

    Science.gov (United States)

    Newell, P. T.; Gjerloev, J. W.

    2014-12-01

    As the number of magnetometer stations and data processing power increases, just how auroral power relates to geomagnetic observations becomes a quantitatively more tractable question. This paper compares Polar UVI auroral power observations during 1997 with a variety of geomagnetic indices. Local time (LT) versions of the SuperMAG auroral electojet (SME) are introduced and examined, along with the corresponding upper and lower envelopes (SMU and SML). Also, the East-West component, BE, is investigated. We also consider whether using any of the local indices is actually better at predicting local auroral power than a single global index. Each index is separated into 24 LT indices based on a sliding 3-h MLT window. The ability to predict - or better reconstruct - auroral power varies greatly with LT, peaking at 1900 MLT, where about 75% of the variance (r2) can be predicted at 1-min cadence. The aurora is fairly predictable from 1700 MLT - 0400 MLT, roughly the region in which substorms occur. Auroral power is poorly predicted from auroral electrojet indices from 0500 MLT - 1500 MLT, with the minima at 1000-1300 MLT. In the region of high predictability, the local variable which works best is BE, in contrast to long-standing expectations. However using global SME is better than any local variable. Auroral power is best predicted by combining global SME with a local index: BE from 1500-0200 MLT, and either SMU or SML from 0300-1400 MLT. In the region of the diffuse aurora, it is better to use a 30 min average than the cotemporaneous 1-min SME value, while from 1500-0200 MLT the cotemporaneous 1-min SME works best, suggesting a more direct physical relationship with the auroral circuit. These results suggest a significant role for discrete auroral currents closing locally with Pedersen currents.

  13. Position-insensitive long range inductive power transfer

    International Nuclear Information System (INIS)

    Kwan, Christopher H; Lawson, James; Yates, David C; Mitcheson, Paul D

    2014-01-01

    This paper presents results of an improved inductive wireless power transfer system for reliable long range powering of sensors with milliwatt-level consumption. An ultra-low power flyback impedance emulator operating in open loop is used to present the optimal load to the receiver's resonant tank. Transmitter power modulation is implemented in order to maintain constant receiver power and to prevent damage to the receiver electronics caused by excessive received voltage. Received power is steady up to 3 m at around 30 mW. The receiver electronics and feedback system consumes 3.1 mW and so with a transmitter input power of 163.3 W the receiver becomes power neutral at 4.75 m. Such an IPT system can provide a reliable alternative to energy harvesters for supplying power concurrently to multiple remote sensors

  14. Integrated Solid Oxide Fuel Cell Power System Characteristics Prediction

    Directory of Open Access Journals (Sweden)

    Marian GAICEANU

    2009-07-01

    Full Text Available The main objective of this paper is to deduce the specific characteristics of the CHP 100kWe Solid Oxide Fuel Cell (SOFC Power System from the steady state experimental data. From the experimental data, the authors have been developed and validated the steady state mathematical model. From the control room the steady state experimental data of the SOFC power conditioning are available and using the developed steady state mathematical model, the authors have been obtained the characteristic curves of the system performed by Siemens-Westinghouse Power Corporation. As a methodology the backward and forward power flow analysis has been employed. The backward power flow makes possible to obtain the SOFC power system operating point at different load levels, resulting as the load characteristic. By knowing the fuel cell output characteristic, the forward power flow analysis is used to predict the power system efficiency in different operating points, to choose the adequate control decision in order to obtain the high efficiency operation of the SOFC power system at different load levels. The CHP 100kWe power system is located at Gas Turbine Technologies Company (a Siemens Subsidiary, TurboCare brand in Turin, Italy. The work was carried out through the Energia da Ossidi Solidi (EOS Project. The SOFC stack delivers constant power permanently in order to supply the electric and thermal power both to the TurboCare Company and to the national grid.

  15. Prediction of lacking control power in power plants using statistical models

    DEFF Research Database (Denmark)

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

    2007-01-01

    Prediction of the performance of plants like power plants is of interest, since the plant operator can use these predictions to optimize the plant production. In this paper the focus is addressed on a special case where a combination of high coal moisture content and a high load limits the possible...... plant load, meaning that the requested plant load cannot be met. The available models are in this case uncertain. Instead statistical methods are used to predict upper and lower uncertainty bounds on the prediction. Two different methods are used. The first relies on statistics of recent prediction...... errors; the second uses operating point depending statistics of prediction errors. Using these methods on the previous mentioned case, it can be concluded that the second method can be used to predict the power plant performance, while the first method has problems predicting the uncertain performance...

  16. A new ensemble model for short term wind power prediction

    DEFF Research Database (Denmark)

    Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan

    2012-01-01

    As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re-search...... of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset...

  17. Testing the predictive power of nuclear mass models

    International Nuclear Information System (INIS)

    Mendoza-Temis, J.; Morales, I.; Barea, J.; Frank, A.; Hirsch, J.G.; Vieyra, J.C. Lopez; Van Isacker, P.; Velazquez, V.

    2008-01-01

    A number of tests are introduced which probe the ability of nuclear mass models to extrapolate. Three models are analyzed in detail: the liquid drop model, the liquid drop model plus empirical shell corrections and the Duflo-Zuker mass formula. If predicted nuclei are close to the fitted ones, average errors in predicted and fitted masses are similar. However, the challenge of predicting nuclear masses in a region stabilized by shell effects (e.g., the lead region) is far more difficult. The Duflo-Zuker mass formula emerges as a powerful predictive tool

  18. Potentiality Prediction of Electric Power Replacement Based on Power Market Development Strategy

    Science.gov (United States)

    Miao, Bo; Yang, Shuo; Liu, Qiang; Lin, Jingyi; Zhao, Le; Liu, Chang; Li, Bin

    2017-05-01

    The application of electric power replacement plays an important role in promoting the development of energy conservation and emission reduction in our country. To exploit the potentiality of regional electric power replacement, the regional GDP (gross domestic product) and energy consumption are taken as potentiality evaluation indicators. The principal component factors are extracted with PCA (principal component analysis), and the integral potentiality analysis is made to the potentiality of electric power replacement in the national various regions; a region is taken as a research object, and the potentiality of electric power replacement is defined and quantified. The analytical model for the potentiality of multi-scenario electric power replacement is developed, and prediction is made to the energy consumption with the grey prediction model. The relevant theoretical research is utilized to realize prediction analysis on the potentiality amount of multi-scenario electric power replacement.

  19. Predicting Harmonic Distortion of Multiple Converters in a Power System

    Directory of Open Access Journals (Sweden)

    P. M. Ivry

    2017-01-01

    Full Text Available Various uncertainties arise in the operation and management of power systems containing Renewable Energy Sources (RES that affect the systems power quality. These uncertainties may arise due to system parameter changes or design parameter choice. In this work, the impact of uncertainties on the prediction of harmonics in a power system containing multiple Voltage Source Converters (VSCs is investigated. The study focuses on the prediction of harmonic distortion level in multiple VSCs when some system or design parameters are only known within certain constraints. The Univariate Dimension Reduction (UDR method was utilized in this study as an efficient predictive tool for the level of harmonic distortion of the VSCs measured at the Point of Common Coupling (PCC to the grid. Two case studies were considered and the UDR technique was also experimentally validated. The obtained results were compared with that of the Monte Carlo Simulation (MCS results.

  20. On the universality of power laws for tokamak plasma predictions

    Science.gov (United States)

    Garcia, J.; Cambon, D.; Contributors, JET

    2018-02-01

    Significant deviations from well established power laws for the thermal energy confinement time, obtained from extensive databases analysis as the IPB98(y,2), have been recently reported in dedicated power scans. In order to illuminate the adequacy, validity and universality of power laws as tools for predicting plasma performance, a simplified analysis has been carried out in the framework of a minimal modeling for heat transport which is, however, able to account for the interplay between turbulence and collinear effects with the input power known to play a role in experiments with significant deviations from such power laws. Whereas at low powers, the usual scaling laws are recovered with little influence of other plasma parameters, resulting in a robust power low exponent, at high power it is shown how the exponents obtained are extremely sensitive to the heating deposition, the q-profile or even the sampling or the number of points considered due to highly non-linear behavior of the heat transport. In particular circumstances, even a minimum of the thermal energy confinement time with the input power can be obtained, which means that the approach of the energy confinement time as a power law might be intrinsically invalid. Therefore plasma predictions with a power law approximation with a constant exponent obtained from a regression of a broad range of powers and other plasma parameters which can non-linearly affect and suppress heat transport, can lead to misleading results suggesting that this approach should be taken cautiously and its results continuously compared with modeling which can properly capture the underline physics, as gyrokinetic simulations.

  1. Wind power prediction based on genetic neural network

    Science.gov (United States)

    Zhang, Suhan

    2017-04-01

    The scale of grid connected wind farms keeps increasing. To ensure the stability of power system operation, make a reasonable scheduling scheme and improve the competitiveness of wind farm in the electricity generation market, it's important to accurately forecast the short-term wind power. To reduce the influence of the nonlinear relationship between the disturbance factor and the wind power, the improved prediction model based on genetic algorithm and neural network method is established. To overcome the shortcomings of long training time of BP neural network and easy to fall into local minimum and improve the accuracy of the neural network, genetic algorithm is adopted to optimize the parameters and topology of neural network. The historical data is used as input to predict short-term wind power. The effectiveness and feasibility of the method is verified by the actual data of a certain wind farm as an example.

  2. Training for vigilance: using predictive power to evaluate feedback effectiveness.

    Science.gov (United States)

    Szalma, James L; Hancock, Peter A; Warm, Joel S; Dember, William N; Parsons, Kelley S

    2006-01-01

    We examined the effects of knowledge of results (KR) on vigilance accuracy and report the first use of positive and negative predictive power (PPP and NPP) to assess vigilance training effectiveness. Training individuals to detect infrequent signals among a plethora of nonsignals is critical to success in many failure-intolerant monitoring technologies. KR has been widely used for vigilance training, but the effect of the schedule of KR presentation on accuracy has been neglected. Previous research on training for vigilance has used signal detection metrics or hits and false alarms. In this study diagnosticity measures were applied to augment traditional analytic methods. We examined the effects of continuous KR and a partial-KR regimen versus a no-KR control on decision diagnosticity. Signal detection theory (SDT) analysis indicated that KR induced conservatism in responding but did not enhance sensitivity. However, KR in both forms equally enhanced PPP while selectively impairing NPP. There is a trade-off in the effectiveness of KR in reducing false alarms and misses. Together, SDT and PPP/NPP measures provide a more complete portrait of performance effects. PPP and NPP together provide another assessment technique for vigilance performance, and as additional diagnostic tools, these measures are potentially useful to the human factors community.

  3. Using machine learning to predict wind turbine power output

    International Nuclear Information System (INIS)

    Clifton, A; Kilcher, L; Lundquist, J K; Fleming, P

    2013-01-01

    Wind turbine power output is known to be a strong function of wind speed, but is also affected by turbulence and shear. In this work, new aerostructural simulations of a generic 1.5 MW turbine are used to rank atmospheric influences on power output. Most significant is the hub height wind speed, followed by hub height turbulence intensity and then wind speed shear across the rotor disk. These simulation data are used to train regression trees that predict the turbine response for any combination of wind speed, turbulence intensity, and wind shear that might be expected at a turbine site. For a randomly selected atmospheric condition, the accuracy of the regression tree power predictions is three times higher than that from the traditional power curve methodology. The regression tree method can also be applied to turbine test data and used to predict turbine performance at a new site. No new data are required in comparison to the data that are usually collected for a wind resource assessment. Implementing the method requires turbine manufacturers to create a turbine regression tree model from test site data. Such an approach could significantly reduce bias in power predictions that arise because of the different turbulence and shear at the new site, compared to the test site. (letter)

  4. Does Spontaneous Favorability to Power (vs. Universalism) Values Predict Spontaneous Prejudice and Discrimination?

    Science.gov (United States)

    Souchon, Nicolas; Maio, Gregory R; Hanel, Paul H P; Bardin, Brigitte

    2017-10-01

    We conducted five studies testing whether an implicit measure of favorability toward power over universalism values predicts spontaneous prejudice and discrimination. Studies 1 (N = 192) and 2 (N = 86) examined correlations between spontaneous favorability toward power (vs. universalism) values, achievement (vs. benevolence) values, and a spontaneous measure of prejudice toward ethnic minorities. Study 3 (N = 159) tested whether conditioning participants to associate power values with positive adjectives and universalism values with negative adjectives (or inversely) affects spontaneous prejudice. Study 4 (N = 95) tested whether decision bias toward female handball players could be predicted by spontaneous attitude toward power (vs. universalism) values. Study 5 (N = 123) examined correlations between spontaneous attitude toward power (vs. universalism) values, spontaneous importance toward power (vs. universalism) values, and spontaneous prejudice toward Black African people. Spontaneous positivity toward power (vs. universalism) values was associated with spontaneous negativity toward minorities and predicted gender bias in a decision task, whereas the explicit measures did not. These results indicate that the implicit assessment of evaluative responses attached to human values helps to model value-attitude-behavior relations. © 2016 The Authors. Journal of Personality Published by Wiley Periodicals, Inc.

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

    DEFF Research Database (Denmark)

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

    2008-01-01

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

  6. Prediction of power-ramp defects in CANDU fuel

    International Nuclear Information System (INIS)

    Gillespie, P.; Wadsworth, S.; Daniels, T.

    2010-01-01

    Power ramps result in fuel pellet expansion and can lead to fuel sheath failures by fission product induced stress corrosion cracking (SCC). Historically, empirical models fit to experimental test data were used to predict the onset of power-ramp failures in CANDU fuel. In 1988, a power-ramped fuel defect event at PNGS-1 led to the refinement of these empirical models. This defect event has recently been re-analyzed and the empirical model updated. The empirical model is supported by a physically based model which can be used to extrapolate to fuel conditions (density, burnup) outside of the 1988 data set. (author)

  7. Thermal Storage Power Balancing with Model Predictive Control

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus; Poulsen, Niels Kjølstad; Madsen, Henrik

    2013-01-01

    The method described in this paper balances power production and consumption with a large number of thermal loads. Linear controllers are used for the loads to track a temperature set point, while Model Predictive Control (MPC) and model estimation of the load behavior are used for coordination....... The total power consumption of all loads is controlled indirectly through a real-time price. The MPC incorporates forecasts of the power production and disturbances that influence the loads, e.g. time-varying weather forecasts, in order to react ahead of time. A simulation scenario demonstrates...

  8. A model to predict the power output from wind farms

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L. [Riso National Lab., Roskilde (Denmark)

    1997-12-31

    This paper will describe a model that can predict the power output from wind farms. To give examples of input the model is applied to a wind farm in Texas. The predictions are generated from forecasts from the NGM model of NCEP. These predictions are made valid at individual sites (wind farms) by applying a matrix calculated by the sub-models of WASP (Wind Atlas Application and Analysis Program). The actual wind farm production is calculated using the Riso PARK model. Because of the preliminary nature of the results, they will not be given. However, similar results from Europe will be given.

  9. Predictive Smart Grid Control with Exact Aggregated Power Constraints

    DEFF Research Database (Denmark)

    Trangbæk, K; Petersen, Mette Højgaard; Bendtsen, Jan Dimon

    2012-01-01

    of autonomous consumers. The control system is tasked with balancing electric power production and consumption within the smart grid, and makes active use of the flexibility of a large number of power producing and/or power consuming units. The load variations on the grid arise on one hand from varying......This chapter deals with hierarchical model predictive control (MPC) of smart grid systems. The design consists of a high-level MPC controller, a second level of so-called aggregators,which reduces the computational and communication related load on the high-level control, and a lower level...... consumption, and on the other hand from natural variations in power production from e.g. wind turbines. The consumers represent energy-consuming units such as heat pumps, car batteries etc. These units obviously have limits on how much power and energy they can consume at any given time, which impose...

  10. When Power Shapes Interpersonal Behavior: Low Relationship Power Predicts Men’s Aggressive Responses to Low Situational Power

    Science.gov (United States)

    Overall, Nickola C.; Hammond, Matthew D.; McNulty, James K.; Finkel, Eli J.

    2016-01-01

    When does power in intimate relationships shape important interpersonal behaviors, such as psychological aggression? Five studies tested whether possessing low relationship power was associated with aggressive responses, but (1) only within power-relevant relationship interactions when situational power was low, and (2) only by men because masculinity (but not femininity) involves the possession and demonstration of power. In Studies 1 and 2, men lower in relationship power exhibited greater aggressive communication during couples’ observed conflict discussions, but only when they experienced low situational power because they were unable to influence their partner. In Study 3, men lower in relationship power reported greater daily aggressive responses toward their partner, but only on days when they experienced low situational power because they were either (a) unable to influence their partner or (b) dependent on their partner for support. In Study 4, men who possessed lower relationship power exhibited greater aggressive responses during couples’ support-relevant discussions, but only when they had low situational power because they needed high levels of support. Study 5 provided evidence for the theoretical mechanism underlying men’s aggressive responses to low relationship power. Men who possessed lower relationship power felt less manly on days they faced low situational power because their partner was unwilling to change to resolve relationship problems, which in turn predicted greater aggressive responses to their partner. These results demonstrate that fully understanding when and why power is associated with interpersonal behavior requires differentiating between relationship and situational power. PMID:27442766

  11. Skill forecasting from different wind power ensemble prediction methods

    International Nuclear Information System (INIS)

    Pinson, Pierre; Nielsen, Henrik A; Madsen, Henrik; Kariniotakis, George

    2007-01-01

    This paper presents an investigation on alternative approaches to the providing of uncertainty estimates associated to point predictions of wind generation. Focus is given to skill forecasts in the form of prediction risk indices, aiming at giving a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the dispersion of ensemble members for a single prediction horizon, or over a set of successive look-ahead times. It is shown on the test case of a Danish offshore wind farm how prediction risk indices may be related to several levels of forecast uncertainty (and energy imbalances). Wind power ensemble predictions are derived from the transformation of ECMWF and NCEP ensembles of meteorological variables to power, as well as by a lagged average approach alternative. The ability of risk indices calculated from the various types of ensembles forecasts to resolve among situations with different levels of uncertainty is discussed

  12. Electrical predictive maintenance at Trillo I Nuclear Power Plant

    International Nuclear Information System (INIS)

    Vicente, L. R.; Fernandez de la Mata, R.; Cano Gonzalez, J. C.

    1998-01-01

    An electrical predictive maintenance plan is currently being put into effect at Trillo I Nuclear Power Plant which is initially being applied to three types of equipment: motors, transformers and motor-driven valves. This paper describes the different phases considered in the implementation of the Predictive Maintenance Plan: study of existing techniques for such equipment (tangoδ, spectral analysis of stator current, chromatographic analysis of gases, spectral analysis of the axial stray magnetic flux, etc), study of the special characteristics of the electrical equipment at Trillo NPP, analysis of applicable techniques (characteristic parameters, alert-alarm values, experience with such techniques, etc), analysis of machine history records, study of the optimum preventive-predictive case, study of applicable frequencies and definition of the computerised predictive maintenance management tool. With the exception of the computerised predictive maintenance management applications which are presently being implemented, all the activities described above have been carried out on the three types of equipment mentioned. (Author)

  13. MDEP Common Position CP-STC-02. Common Position Addressing Fukushima Daiichi Nuclear Power Accident

    International Nuclear Information System (INIS)

    2016-09-01

    Following the nuclear accident in Japan as a consequence of the earthquake and tsunami, the MDEP Members provide the following information, based on initial information available, to ensure adequate safety of new reactor design activities being undertaken pursuant to the MDEP program of work. Due to the extensive nature of the magnitude and duration of the Fukushima Daiichi NPP accident, it is important to consider lessons learnt at an early stage of the design. In this context, the extensive work done by the IAEA, the International Atomic Energy Agency, is also acknowledged. Vendors, licensees and applicants involved in New Design activities should examine the implications of the Fukushima Daiichi NPP accident and identify relevant issues to be taken into account to strengthen defense in depth. Those lessons learnt should include, but not be limited to, plans to assess the following: - Provisions taken in the design basis concerning flooding, earthquake, other extreme natural phenomena and combinations of external event hazards appropriate to each country, - The robustness of the plant to maintain its safety functions beyond the design basis hazards, - The capability of the plant to withstand extended loss of all electrical power supplies as well as prolonged loss of ultimate heat sink and other essential supplies, and - The capability of the plant to cope with such extreme situations, including provisions to manage severe accidents (such as combustible gas management). In assessing these areas, the effect of multiple units and nuclear fuel storages should be considered. The MDEP regulators will strive to harmonize approaches to incorporate lessons learnt in their ongoing national safety reviews of new reactors. Based on the design-specific common positions, this paper identifies the approaches to address potential safety improvements for several designs as related to lessons learned from the Fukushima Daiichi NPP accident or related issues. Designs being

  14. Nomogram for predicting the probability of the positive outcome of ...

    African Journals Online (AJOL)

    F.A. Yeboah

    distribution, the median and inter quartile (IQR) values were used. ... Crude or adjusted odds ratios and ... model, the estimated probability of a positive biopsy was calcu- ..... Gratitude goes to workers at Department of Surgery (Urology Unit).

  15. Forecasting Electricity Spot Prices Accounting for Wind Power Predictions

    DEFF Research Database (Denmark)

    Jónsson, Tryggvi; Pinson, Pierre; Nielsen, Henrik Aalborg

    2013-01-01

    A two-step methodology for forecasting of electricity spot prices is introduced, with focus on the impact of predicted system load and wind power generation. The nonlinear and nonstationary influence of these explanatory variables is accommodated in a first step based on a nonparametric and time...

  16. Prediction of future dispute concerning nuclear power generation

    International Nuclear Information System (INIS)

    1981-04-01

    This investigation is the third research on the public acceptance of nuclear power generation by the National Congress on Social Economics. In this study, how the energy dispute including that concerning nuclear power generation will develop in 1980s and 1990s, how the form of dispute and the point of controversy will change, were predicted. Though the maintenance of the concord of groups strongly regulates the behavior of people, recently they have become to exercise individual rights frequently. The transition to the society of dispute is the natural result of the modernization of society and the increase of richness. The proper prediction of social problems and the planning and execution of proper countermeasures are very important. The background, objective, basic viewpoint, range and procedure of this investigation, the change of social dispute, the history of the dispute concerning nuclear power generation, the basic viewpoint in the prediction of the dispute concerning nuclear power generation, the social situation in 1980s, the prediction and avoidance of the dispute in view of social and energy situations, and the fundamental strategy for seeking a clue to the solution in 1980s and 1990s are described. The establishment of neutral mediation organs and the flexible technologies of nuclear reactors are necessary. (Kako, I.)

  17. Model predictive control for Z-source power converter

    DEFF Research Database (Denmark)

    Mo, W.; Loh, P.C.; Blaabjerg, Frede

    2011-01-01

    This paper presents Model Predictive Control (MPC) of impedance-source (commonly known as Z-source) power converter. Output voltage control and current control for Z-source inverter are analyzed and simulated. With MPC's ability of multi- system variables regulation, load current and voltage...

  18. Connecting Positive Psychology and Organizational Behavior Management: Achievement Motivation and the Power of Positive Reinforcement

    Science.gov (United States)

    Wiegand, Douglas M.; Geller, E. Scott

    2005-01-01

    Positive psychology is becoming established as a reputable sub-discipline in psychology despite having neglected the role of positive reinforcement in enhancing quality of life. The authors discuss the relevance of positive reinforcement for positive psychology, with implications for broadening the content of organizational behavior management.…

  19. Predictive power of the grace score in population with diabetes.

    Science.gov (United States)

    Baeza-Román, Anna; de Miguel-Balsa, Eva; Latour-Pérez, Jaime; Carrillo-López, Andrés

    2017-12-01

    Current clinical practice guidelines recommend risk stratification in patients with acute coronary syndrome (ACS) upon admission to hospital. Diabetes mellitus (DM) is widely recognized as an independent predictor of mortality in these patients, although it is not included in the GRACE risk score. The objective of this study is to validate the GRACE risk score in a contemporary population and particularly in the subgroup of patients with diabetes, and to test the effects of including the DM variable in the model. Retrospective cohort study in patients included in the ARIAM-SEMICYUC registry, with a diagnosis of ACS and with available in-hospital mortality data. We tested the predictive power of the GRACE score, calculating the area under the ROC curve. We assessed the calibration of the score and the predictive ability based on type of ACS and the presence of DM. Finally, we evaluated the effect of including the DM variable in the model by calculating the net reclassification improvement. The GRACE score shows good predictive power for hospital mortality in the study population, with a moderate degree of calibration and no significant differences based on ACS type or the presence of DM. Including DM as a variable did not add any predictive value to the GRACE model. The GRACE score has an appropriate predictive power, with good calibration and clinical applicability in the subgroup of diabetic patients. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

  20. Model Predictive Control of Grid Connected Modular Multilevel Converter for Integration of Photovoltaic Power Systems

    DEFF Research Database (Denmark)

    Hajizadeh, Amin; Shahirinia, Amir

    2017-01-01

    Investigation of an advanced control structure for integration of Photovoltaic Power Systems through Grid Connected-Modular Multilevel Converter (GC-MMC) is proposed in this paper. To achieve this goal, a non-linear model of MMC regarding considering of negative and positive sequence components has...... been presented. Then, due to existence of unbalance voltage faults in distribution grid, non-linarites and uncertainties in model, model predictive controller which is developed for GC-MMC. They are implemented based upon positive and negative components of voltage and current to mitigate the power...

  1. Predictive Maintenance: One key to improved power plant availability

    International Nuclear Information System (INIS)

    Mobley; Allen, J.W.

    1986-01-01

    Recent developments in microprocessor technology has provided the ability to routinely monitor the actual mechanical condition of all rotating and reciprocating machinery and process variables (i.e. pressure, temperature, flow, etc.) of other process equipment within an operating electric power generating plant. This direct correlation between frequency domain vibration and actual mechanical condition of machinery and trending process variables of non-rotating equipment can provide the ''key'' to improving the availability and reliability, thermal efficiency and provide the baseline information necessary for developing a realistic plan for extending the useful life of power plants. The premise of utilizing microprocessor-based Predictive Maintenance to improve power plant operation has been proven by a number of utilities. This paper provides a comprehensive discussion of the TEC approach to Predictive Maintenance and examples of successful programs

  2. Model Predictive Control of Integrated Gasification Combined Cycle Power Plants

    Energy Technology Data Exchange (ETDEWEB)

    B. Wayne Bequette; Priyadarshi Mahapatra

    2010-08-31

    The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.

  3. The power of extraverts: testing positive and negative mood regulation

    Directory of Open Access Journals (Sweden)

    Gonzalo Hervas

    Full Text Available Extraversion is a personality trait which has been systematically related to positive affect and well-being. One of the mechanisms that may account for these positive outcomes is the ability to regulate the responses to positive, as well as negative, moods. Prior research has found that extraverts' higher positive mood maintenance could explain their higher levels of positive affect. However, research exploring differences between extraverts and introverts in negative mood regulation has yielded mixed results. The aim of the current study was explore the role of different facets of mood regulation displayed by extraverts, ambiverts, and introverts. After been exposed to a sad vs. happy mood induction, participants underwent a mood regulation task. Extraverts and ambiverts exhibited higher positive mood regulation than introverts, but similar mood repair. Thus, this research highlights the importance of positive mood regulation in the psychological functioning of extraverts, and opens new conceptualizations for developing interventions for introverts to improve their positive mood regulation and, hence, overall positive affect and well-being.

  4. Predicting positional error of MLC using volumetric analysis

    International Nuclear Information System (INIS)

    Hareram, E.S.

    2008-01-01

    IMRT normally using multiple beamlets (small width of the beam) for a particular field to deliver so that it is imperative to maintain the positional accuracy of the MLC in order to deliver integrated computed dose accurately. Different manufacturers have reported high precession on MLC devices with leaf positional accuracy nearing 0.1 mm but measuring and rectifying the error in this accuracy is very difficult. Various methods are used to check MLC position and among this volumetric analysis is one of the technique. Volumetric approach was adapted in our method using primus machine and 0.6cc chamber at 5 cm depth In perspex. MLC of 1 mm error introduces an error of 20%, more sensitive to other methods

  5. Effect of accuracy of wind power prediction on power system operator

    Science.gov (United States)

    Schlueter, R. A.; Sigari, G.; Costi, T.

    1985-01-01

    This research project proposed a modified unit commitment that schedules connection and disconnection of generating units in response to load. A modified generation control is also proposed that controls steam units under automatic generation control, fast responding diesels, gas turbines and hydro units under a feedforward control, and wind turbine array output under a closed loop array control. This modified generation control and unit commitment require prediction of trend wind power variation one hour ahead and the prediction of error in this trend wind power prediction one half hour ahead. An improved meter for predicting trend wind speed variation is developed. Methods for accurately simulating the wind array power from a limited number of wind speed prediction records was developed. Finally, two methods for predicting the error in the trend wind power prediction were developed. This research provides a foundation for testing and evaluating the modified unit commitment and generation control that was developed to maintain operating reliability at a greatly reduced overall production cost for utilities with wind generation capacity.

  6. Positive affect and markers of inflammation: discrete positive emotions predict lower levels of inflammatory cytokines.

    Science.gov (United States)

    Stellar, Jennifer E; John-Henderson, Neha; Anderson, Craig L; Gordon, Amie M; McNeil, Galen D; Keltner, Dacher

    2015-04-01

    Negative emotions are reliably associated with poorer health (e.g., Kiecolt-Glaser, McGuire, Robles, & Glaser, 2002), but only recently has research begun to acknowledge the important role of positive emotions for our physical health (Fredrickson, 2003). We examine the link between dispositional positive affect and one potential biological pathway between positive emotions and health-proinflammatory cytokines, specifically levels of interleukin-6 (IL-6). We hypothesized that greater trait positive affect would be associated with lower levels of IL-6 in a healthy sample. We found support for this hypothesis across two studies. We also explored the relationship between discrete positive emotions and IL-6 levels, finding that awe, measured in two different ways, was the strongest predictor of lower levels of proinflammatory cytokines. These effects held when controlling for relevant personality and health variables. This work suggests a potential biological pathway between positive emotions and health through proinflammatory cytokines. (c) 2015 APA, all rights reserved).

  7. Using meteorological forecasts in on-line predictions of wind power

    DEFF Research Database (Denmark)

    Nielsen, Torben Skov; Nielsen, Henrik Aalborg; Madsen, Henrik

    1999-01-01

    This report describes a model investigation into wind power prediction model as well as a tool for predicting the power production from wind turbines in an area - the Wind Power Prediction Tool (WPPT). The predictions are based on on-line measurements of power production for a selected set...

  8. Empirical Information Metrics for Prediction Power and Experiment Planning

    Directory of Open Access Journals (Sweden)

    Christopher Lee

    2011-01-01

    Full Text Available In principle, information theory could provide useful metrics for statistical inference. In practice this is impeded by divergent assumptions: Information theory assumes the joint distribution of variables of interest is known, whereas in statistical inference it is hidden and is the goal of inference. To integrate these approaches we note a common theme they share, namely the measurement of prediction power. We generalize this concept as an information metric, subject to several requirements: Calculation of the metric must be objective or model-free; unbiased; convergent; probabilistically bounded; and low in computational complexity. Unfortunately, widely used model selection metrics such as Maximum Likelihood, the Akaike Information Criterion and Bayesian Information Criterion do not necessarily meet all these requirements. We define four distinct empirical information metrics measured via sampling, with explicit Law of Large Numbers convergence guarantees, which meet these requirements: Ie, the empirical information, a measure of average prediction power; Ib, the overfitting bias information, which measures selection bias in the modeling procedure; Ip, the potential information, which measures the total remaining information in the observations not yet discovered by the model; and Im, the model information, which measures the model’s extrapolation prediction power. Finally, we show that Ip + Ie, Ip + Im, and Ie — Im are fixed constants for a given observed dataset (i.e. prediction target, independent of the model, and thus represent a fundamental subdivision of the total information contained in the observations. We discuss the application of these metrics to modeling and experiment planning.    

  9. Power system dynamic state estimation using prediction based evolutionary technique

    International Nuclear Information System (INIS)

    Basetti, Vedik; Chandel, Ashwani K.; Chandel, Rajeevan

    2016-01-01

    In this paper, a new robust LWS (least winsorized square) estimator is proposed for dynamic state estimation of a power system. One of the main advantages of this estimator is that it has an inbuilt bad data rejection property and is less sensitive to bad data measurements. In the proposed approach, Brown's double exponential smoothing technique has been utilised for its reliable performance at the prediction step. The state estimation problem is solved as an optimisation problem using a new jDE-self adaptive differential evolution with prediction based population re-initialisation technique at the filtering step. This new stochastic search technique has been embedded with different state scenarios using the predicted state. The effectiveness of the proposed LWS technique is validated under different conditions, namely normal operation, bad data, sudden load change, and loss of transmission line conditions on three different IEEE test bus systems. The performance of the proposed approach is compared with the conventional extended Kalman filter. On the basis of various performance indices, the results thus obtained show that the proposed technique increases the accuracy and robustness of power system dynamic state estimation performance. - Highlights: • To estimate the states of the power system under dynamic environment. • The performance of the EKF method is degraded during anomaly conditions. • The proposed method remains robust towards anomalies. • The proposed method provides precise state estimates even in the presence of anomalies. • The results show that prediction accuracy is enhanced by using the proposed model.

  10. Network position and related power : how they affect and are affected by network management and outcomes

    NARCIS (Netherlands)

    Oukes, Tamara

    2018-01-01

    In network position and related power you learn more about how network position and related power affect and are affected by network management and outcomes. First, I expand our present understanding of how startups with a fragile network position manage business relationships by taking an

  11. Optimism predicts positive health in repatriated prisoners of war.

    Science.gov (United States)

    Segovia, Francine; Moore, Jeffrey L; Linnville, Steven E; Hoyt, Robert E

    2015-05-01

    "Positive health," defined as a state beyond the mere absence of disease, was used as a model to examine factors for enhancing health despite extreme trauma. The study examined the United States' longest detained American prisoners of war, those held in Vietnam in the 1960s through early 1970s. Positive health was measured using a physical and a psychological composite score for each individual, based on 9 physical and 9 psychological variables. Physical and psychological health was correlated with optimism obtained postrepatriation (circa 1973). Linear regressions were employed to determine which variables contributed most to health ratings. Optimism was the strongest predictor of physical health (β = -.33, t = -2.73, p = .008), followed by fewer sleep complaints (β = -.29, t = -2.52, p = .01). This model accounted for 25% of the variance. Optimism was also the strongest predictor of psychological health (β = -.41, t = -2.87, p = .006), followed by Minnesota Multiphasic Personality Inventory-Psychopathic Deviate (MMPI-PD; McKinley & Hathaway, 1944) scores (β = -.23, t = -1.88, p = .07). This model strongly suggests that optimism is a significant predictor of positive physical and psychological health, and optimism also provides long-term protective benefits. These findings and the utility of this model suggest a promising area for future research and intervention. (c) 2015 APA, all rights reserved).

  12. The power of Nutrition Impact and Positive Practice (NIPP) Circles

    African Journals Online (AJOL)

    family members we identify existing, positive behaviours of mothers or caretakers in ..... foods is practice to reinforce that idea. In order to help the volunteer ... exercises are only covered in theory, whereas the women's groups need to practice ...

  13. Bimanual coordination positively predicts episodic memory: A combined behavioral and MRI investigation.

    Science.gov (United States)

    Lyle, Keith B; Dombroski, Brynn A; Faul, Leonard; Hopkins, Robin F; Naaz, Farah; Switala, Andrew E; Depue, Brendan E

    2017-11-01

    Some people remember events more completely and accurately than other people, but the origins of individual differences in episodic memory are poorly understood. One way to advance understanding is by identifying characteristics of individuals that reliably covary with memory performance. Recent research suggests motor behavior is related to memory performance, with individuals who consistently use a single preferred hand for unimanual actions performing worse than individuals who make greater use of both hands. This research has relied on self-reports of behavior. It is unknown whether objective measures of motor behavior also predict memory performance. Here, we tested the predictive power of bimanual coordination, an important form of manual dexterity. Bimanual coordination, as measured objectively on the Purdue Pegboard Test, was positively related to correct recall on the California Verbal Learning Test-II and negatively related to false recall. Furthermore, MRI data revealed that cortical surface area in right lateral prefrontal regions was positively related to correct recall. In one of these regions, cortical thickness was negatively related to bimanual coordination. These results suggest that individual differences in episodic memory may partially reflect morphological variation in right lateral prefrontal cortex and suggest a relationship between neural correlates of episodic memory and motor behavior. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Positive predictive value of cholescintigraphy in common bile duct obstruction

    International Nuclear Information System (INIS)

    Lecklitner, M.L.; Austin, A.R.; Benedetto, A.R.; Growcock, G.W.

    1986-01-01

    Technetium-99m DISIDA imaging was employed in 400 patients to differentiate obstruction of the common bile duct from medical and other surgical causes of hyperbilirubinemia. Sequential anterior images demonstrated variable degrees of liver uptake, yet there was no evidence of intrabiliary or extrabiliary radioactivity for at least 4 hr after injection in 25 patients. Twenty-three patients were surgically documented to have complete obstruction of the common bile duct. One patient had hepatitis, and another had sickle cell crisis without bile duct obstruction. The remaining patients had either partial or no obstruction of the common bile duct. We conclude that the presence of liver uptake without evident biliary excretion by 4 hr on cholescintigraphy is highly sensitive and predictive of total obstruction of the common bile duct

  15. Applying model predictive control to power system frequency control

    OpenAIRE

    Ersdal, AM; Imsland, L; Cecilio, IM; Fabozzi, D; Thornhill, NF

    2013-01-01

    16.07.14 KB Ok to add accepted version to Spiral Model predictive control (MPC) is investigated as a control method which may offer advantages in frequency control of power systems than the control methods applied today, especially in presence of increased renewable energy penetration. The MPC includes constraints on both generation amount and generation rate of change, and it is tested on a one-area system. The proposed MPC is tested against a conventional proportional-integral (PI) cont...

  16. Pre-stimulus thalamic theta power predicts human memory formation.

    Science.gov (United States)

    Sweeney-Reed, Catherine M; Zaehle, Tino; Voges, Jürgen; Schmitt, Friedhelm C; Buentjen, Lars; Kopitzki, Klaus; Richardson-Klavehn, Alan; Hinrichs, Hermann; Heinze, Hans-Jochen; Knight, Robert T; Rugg, Michael D

    2016-09-01

    Pre-stimulus theta (4-8Hz) power in the hippocampus and neocortex predicts whether a memory for a subsequent event will be formed. Anatomical studies reveal thalamus-hippocampal connectivity, and lesion, neuroimaging, and electrophysiological studies show that memory processing involves the dorsomedial (DMTN) and anterior thalamic nuclei (ATN). The small size and deep location of these nuclei have limited real-time study of their activity, however, and it is unknown whether pre-stimulus theta power predictive of successful memory formation is also found in these subcortical structures. We recorded human electrophysiological data from the DMTN and ATN of 7 patients receiving deep brain stimulation for refractory epilepsy. We found that greater pre-stimulus theta power in the right DMTN was associated with successful memory encoding, predicting both behavioral outcome and post-stimulus correlates of successful memory formation. In particular, significant correlations were observed between right DMTN theta power and both frontal theta and right ATN gamma (32-50Hz) phase alignment, and frontal-ATN theta-gamma cross-frequency coupling. We draw the following primary conclusions. Our results provide direct electrophysiological evidence in humans of a role for the DMTN as well as the ATN in memory formation. Furthermore, prediction of subsequent memory performance by pre-stimulus thalamic oscillations provides evidence that post-stimulus differences in thalamic activity that index successful and unsuccessful encoding reflect brain processes specifically underpinning memory formation. Finally, the findings broaden the understanding of brain states that facilitate memory encoding to include subcortical as well as cortical structures. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. An adaptive predictive controller and its applications in power stations

    Energy Technology Data Exchange (ETDEWEB)

    Yang Zhiyuan; Lu Huiming; Zhang Xinggao [North China Electric Power University, Beijing (China); Song Chunping [Tsinghua University, Beijing (China). Dept. of Thermal Energy Engineering

    1999-07-01

    Based on the objective function in the form of integration of generalized model error, a globally convergent model reference adaptive predictive control algorithm (MRAPC) containing inertia-time compensators is presented in this paper. MRAPC has been successfully applied to control important thermal process of more than 20 units in many Chinese power stations. In this paper three representative examples are described. Continual operation results for years demonstrate that MRAPC is a successful attempt for the practical applications of adaptive control techniques. (author)

  18. True self-alienation positively predicts reports of mindwandering.

    Science.gov (United States)

    Vess, Matthew; Leal, Stephanie A; Hoeldtke, Russell T; Schlegel, Rebecca J; Hicks, Joshua A

    2016-10-01

    Two studies assessed the relationship between feelings of uncertainty about who one truly is (i.e., true self-alienation) and self-reported task-unrelated thoughts (i.e., mindwandering) during performance tasks. Because true self-alienation is conceptualized as the subjective disconnect between conscious awareness and actual experience, we hypothesized that greater feelings of true self-alienation would positively relate to subjective reports of mindwandering. Two convergent studies supported this hypothesis. Moreover, this relationship could not consistently be accounted for by the independent influence of other aspects of authenticity, negative mood, mindfulness, or broad personality dimensions. These findings suggest that individual differences in true self-alienation are reliably associated with subjective reports of mindwandering. The implications of these findings for the true self-alienation construct, the ways that personality relates to mindwandering, and future research directions focused on curtailing mindwandering and improving performance and achievement are discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Error analysis of short term wind power prediction models

    International Nuclear Information System (INIS)

    De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco

    2011-01-01

    The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction. (author)

  20. Error analysis of short term wind power prediction models

    Energy Technology Data Exchange (ETDEWEB)

    De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco [Dipartimento di Ingegneria dell' Innovazione, Universita del Salento, Via per Monteroni, 73100 Lecce (Italy)

    2011-04-15

    The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction. (author)

  1. Predicting Output Power for Nearshore Wave Energy Harvesting

    Directory of Open Access Journals (Sweden)

    Henock Mamo Deberneh

    2018-04-01

    Full Text Available Energy harvested from a Wave Energy Converter (WEC varies greatly with the location of its installation. Determining an optimal location that can result in maximum output power is therefore critical. In this paper, we present a novel approach to predicting the output power of a nearshore WEC by characterizing ocean waves using floating buoys. We monitored the movement of the buoys using an Arduino-based data collection module, including a gyro-accelerometer sensor and a wireless transceiver. The collected data were utilized to train and test prediction models. The models were developed using machine learning algorithms: SVM, RF and ANN. The results of the experiments showed that measurements from the data collection module can yield a reliable predictor of output power. Furthermore, we found that the predictors work better when the regressors are combined with a classifier. The accuracy of the proposed prediction model suggests that it could be extremely useful in both locating optimal placement for wave energy harvesting plants and designing the shape of the buoys used by them.

  2. The Power of Montessori's Positive Psychology in an Expanding Universe.

    Science.gov (United States)

    Haines, Annette

    1999-01-01

    Relates Montessori theory of development with the concept of connection to the universe and natural world, noting Montessori education's role in nurturing reestablished connection with the natural world. Describes events leading to a fulfilled life as part of psychological normalization, noting the importance of identifying positive tendencies of…

  3. Prediction of Chiller Power Consumption: An Entropy Generation Approach

    KAUST Repository

    Saththasivam, Jayaprakash

    2016-06-21

    Irreversibilities in each component of vapor compression chillers contribute to additional power consumption in chillers. In this study, chiller power consumption was predicted by computing the Carnot reversible work and entropy generated in every component of the chiller. Thermodynamic properties namely enthalpy and entropy of the entire refrigerant cycle were obtained by measuring the pressure and temperature at the inlet and outlet of each primary component of a 15kW R22 water cooled scroll chiller. Entropy generation of each component was then calculated using the First and Second Laws of Thermodynamics. Good correlation was found between the measured and computed chiller power consumption. This irreversibility analysis can be also effectively used as a performance monitoring tool in vapor compression chillers as higher entropy generation is anticipated during faulty operations.

  4. Predicting the emissive power of hydrocarbon pool fires

    International Nuclear Information System (INIS)

    Munoz, Miguel; Planas, Eulalia; Ferrero, Fabio; Casal, Joaquim

    2007-01-01

    The emissive power (E) of a flame depends on the size of the fire and the type of fuel. In fact, it changes significantly over the flame surface: the zones of luminous flame have high emittance, while those covered by smoke have low E values. The emissive power of each zone (that is, the luminous or clear flame and the non-luminous or smoky flame) and the portion of total flame area they occupy must be assessed when a two-zone model is used. In this study, data obtained from an experimental set-up were used to estimate the emissive power of fires and its behaviour as a function of pool size. The experiments were performed using gasoline and diesel oil as fuel. Five concentric circular pools (1.5, 3, 4, 5 and 6 m in diameter) were used. Appropriate instruments were employed to determine the main features of the fires. By superimposing IR and VHS images it was possible to accurately identify the luminous and non-luminous zones of the fire. Mathematical expressions were obtained that give a more accurate prediction of E lum , E soot and the average emissive power of a fire as a function of its luminous and smoky zones. These expressions can be used in a two-zone model to obtain a better prediction of the thermal radiation. The value of the radiative fraction was determined from the thermal flux measured with radiometers. An expression is also proposed for estimating the radiative fraction

  5. COSMIC EMULATION: FAST PREDICTIONS FOR THE GALAXY POWER SPECTRUM

    Energy Technology Data Exchange (ETDEWEB)

    Kwan, Juliana; Heitmann, Katrin; Habib, Salman; Frontiere, Nicholas; Pope, Adrian [High Energy Physics Division, Argonne National Laboratory, Lemont, IL 60439 (United States); Padmanabhan, Nikhil [Department of Physics, Yale University, 260 Whitney Ave., New Haven, CT 06520 (United States); Lawrence, Earl [Statistical Sciences, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Finkel, Hal [Argonne Leadership Computing Facility, Argonne National Laboratory, Lemont, IL 60439 (United States)

    2015-09-01

    The halo occupation distribution (HOD) approach has proven to be an effective method for modeling galaxy clustering and bias. In this approach, galaxies of a given type are probabilistically assigned to individual halos in N-body simulations. In this paper, we present a fast emulator for predicting the fully nonlinear galaxy–galaxy auto and galaxy–dark matter cross power spectrum and correlation function over a range of freely specifiable HOD modeling parameters. The emulator is constructed using results from 100 HOD models run on a large ΛCDM N-body simulation, with Gaussian Process interpolation applied to a PCA-based representation of the galaxy power spectrum. The total error is currently ∼1% in the auto correlations and ∼2% in the cross correlations from z = 1 to z = 0, over the considered parameter range. We use the emulator to investigate the accuracy of various analytic prescriptions for the galaxy power spectrum, parametric dependencies in the HOD model, and the behavior of galaxy bias as a function of HOD parameters. Additionally, we obtain fully nonlinear predictions for tangential shear correlations induced by galaxy–galaxy lensing from our galaxy–dark matter cross power spectrum emulator. All emulation products are publicly available at http://www.hep.anl.gov/cosmology/CosmicEmu/emu.html.

  6. Synapse:neural network for predict power consumption: users guide

    Energy Technology Data Exchange (ETDEWEB)

    Muller, C; Mangeas, M; Perrot, N

    1994-08-01

    SYNAPSE is forecasting tool designed to predict power consumption in metropolitan France on the half hour time scale. Some characteristics distinguish this forecasting model from those which already exist. In particular, it is composed of numerous neural networks. The idea for using many neural networks arises from past tests. These tests showed us that a single neural network is not able to solve the problem correctly. From this result, we decided to perform unsupervised classification of the 24 consumption curves. From this classification, six classes appeared, linked with the weekdays: Mondays, Tuesdays, Wednesdays, Thursdays, Fridays, Saturdays, Sundays, holidays and bridge days. For each class and for each half hour, two multilayer perceptrons are built. The two of them forecast the power for one particular half hour, and for a day including one of the determined class. The input of these two network are different: the first one (short time forecasting) includes the powers for the most recent half hour and relative power of the previous day; the second (medium time forecasting) includes only the relative power of the previous day. A process connects the results of every networks and allows one to forecast more than one half-hour in advance. In this process, short time forecasting networks and medium time forecasting networks are used differently. The first kind of neural networks gives good results on the scale of one day. The second one gives good forecasts for the next predicted powers. In this note, the organization of the SYNAPSE program is detailed, and the user`s menu is described. This first version of synapse works and should allow the APC group to evaluate its utility. (authors). 6 refs., 2 appends.

  7. Controlled test for predictive power of Lyapunov exponents: their inability to predict epileptic seizures.

    Science.gov (United States)

    Lai, Ying-Cheng; Harrison, Mary Ann F; Frei, Mark G; Osorio, Ivan

    2004-09-01

    Lyapunov exponents are a set of fundamental dynamical invariants characterizing a system's sensitive dependence on initial conditions. For more than a decade, it has been claimed that the exponents computed from electroencephalogram (EEG) or electrocorticogram (ECoG) signals can be used for prediction of epileptic seizures minutes or even tens of minutes in advance. The purpose of this paper is to examine the predictive power of Lyapunov exponents. Three approaches are employed. (1) We present qualitative arguments suggesting that the Lyapunov exponents generally are not useful for seizure prediction. (2) We construct a two-dimensional, nonstationary chaotic map with a parameter slowly varying in a range containing a crisis, and test whether this critical event can be predicted by monitoring the evolution of finite-time Lyapunov exponents. This can thus be regarded as a "control test" for the claimed predictive power of the exponents for seizure. We find that two major obstacles arise in this application: statistical fluctuations of the Lyapunov exponents due to finite time computation and noise from the time series. We show that increasing the amount of data in a moving window will not improve the exponents' detective power for characteristic system changes, and that the presence of small noise can ruin completely the predictive power of the exponents. (3) We report negative results obtained from ECoG signals recorded from patients with epilepsy. All these indicate firmly that, the use of Lyapunov exponents for seizure prediction is practically impossible as the brain dynamical system generating the ECoG signals is more complicated than low-dimensional chaotic systems, and is noisy. Copyright 2004 American Institute of Physics

  8. Mobile Robot Positioning with 433-MHz Wireless Motes with Varying Transmission Powers and a Particle Filter.

    Science.gov (United States)

    Canedo-Rodriguez, Adrian; Rodriguez, Jose Manuel; Alvarez-Santos, Victor; Iglesias, Roberto; Regueiro, Carlos V

    2015-04-30

    In wireless positioning systems, the transmitter's power is usually fixed. In this paper, we explore the use of varying transmission powers to increase the performance of a wireless localization system. To this extent, we have designed a robot positioning system based on wireless motes. Our motes use an inexpensive, low-power sub-1-GHz system-on-chip (CC1110) working in the 433-MHz ISM band. Our localization algorithm is based on a particle filter and infers the robot position by: (1) comparing the power received with the expected one; and (2) integrating the robot displacement. We demonstrate that the use of transmitters that vary their transmission power over time improves the performance of the wireless positioning system significantly, with respect to a system that uses fixed power transmitters. This opens the door for applications where the robot can localize itself actively by requesting the transmitters to change their power in real time.

  9. Mobile Robot Positioning with 433-MHz Wireless Motes with Varying Transmission Powers and a Particle Filter

    Directory of Open Access Journals (Sweden)

    Adrian Canedo-Rodriguez

    2015-04-01

    Full Text Available In wireless positioning systems, the transmitter’s power is usually fixed. In this paper, we explore the use of varying transmission powers to increase the performance of a wireless localization system. To this extent, we have designed a robot positioning system based on wireless motes. Our motes use an inexpensive, low-power sub-1-GHz system-on-chip (CC1110 working in the 433-MHz ISM band. Our localization algorithm is based on a particle filter and infers the robot position by: (1 comparing the power received with the expected one; and (2 integrating the robot displacement. We demonstrate that the use of transmitters that vary their transmission power over time improves the performance of the wireless positioning system significantly, with respect to a system that uses fixed power transmitters. This opens the door for applications where the robot can localize itself actively by requesting the transmitters to change their power in real time.

  10. Corporate brand positioning : searching for a new position - case Metso Power

    OpenAIRE

    KUURU, TIINA-KAISA

    2013-01-01

    Tutkielmasta TamPubissa rajattu versio. Täydellinen versio luettavissa Tampereen yliopiston Linna-kirjastossa. This is a limited version of the Master's thesis. The complete version can be viewed in print at Tampere University Library The purpose of this study is to describe and analyse the process of corporate brand positioning. Study is focused on B2B market, precisely on industrial brands. Corporate brand positioning is defined as a process of searching and finding a...

  11. Power and religion: Geertz position of present-day Bali

    Directory of Open Access Journals (Sweden)

    Ni Wayan Radita Novi Puspitasari

    2017-05-01

    Full Text Available This article analyzes the changes of religious - political power relations from the mid of 1950’s to present-day Bali. Anthropologist Geertz stated that Balinese Hinduism is a “superstition”, “rhetoric” and “state cult” that had been applied in the Negara as a theatre state. Within the conception of Hinduism by referring to the relation between the Divine God -Tri Murti and Tri Hita Karana, the Balinese society is believed in the relation between Gods, the people and its environment. Although in the post-colonial era, Balinese people are maintaining the power existence of the local kingdoms, mainly the system of warna. Through the accumulation of charisma, Geertz provided a concept that Negara was basically a state created by honor and ceremony. Thus, the democratic governmental system of Indonesia hardly reach the political arena within the Balinese society. As a result, through the self-awareness and the notion on equality, the Sudra could establish their role as an influential Balinese personage.

  12. Predicting College Students' Positive Psychology Associated Traits with Executive Functioning Dimensions

    Science.gov (United States)

    Marshall, Seth

    2016-01-01

    More research is needed that investigates how positive psychology-associated traits are predicted by neurocognitive processes. Correspondingly, the purpose of this study was to ascertain how, and to what extent, four traits, namely, grit, optimism, positive affect, and life satisfaction were predicted by the executive functioning (EF) dimensions…

  13. Predicting Power Outages Using Multi-Model Ensemble Forecasts

    Science.gov (United States)

    Cerrai, D.; Anagnostou, E. N.; Yang, J.; Astitha, M.

    2017-12-01

    Power outages affect every year millions of people in the United States, affecting the economy and conditioning the everyday life. An Outage Prediction Model (OPM) has been developed at the University of Connecticut for helping utilities to quickly restore outages and to limit their adverse consequences on the population. The OPM, operational since 2015, combines several non-parametric machine learning (ML) models that use historical weather storm simulations and high-resolution weather forecasts, satellite remote sensing data, and infrastructure and land cover data to predict the number and spatial distribution of power outages. A new methodology, developed for improving the outage model performances by combining weather- and soil-related variables using three different weather models (WRF 3.7, WRF 3.8 and RAMS/ICLAMS), will be presented in this study. First, we will present a performance evaluation of each model variable, by comparing historical weather analyses with station data or reanalysis over the entire storm data set. Hence, each variable of the new outage model version is extracted from the best performing weather model for that variable, and sensitivity tests are performed for investigating the most efficient variable combination for outage prediction purposes. Despite that the final variables combination is extracted from different weather models, this ensemble based on multi-weather forcing and multi-statistical model power outage prediction outperforms the currently operational OPM version that is based on a single weather forcing variable (WRF 3.7), because each model component is the closest to the actual atmospheric state.

  14. Ranking low, feeling high: How hierarchical position and experienced power promote prosocial behavior in response to procedural justice.

    Science.gov (United States)

    van Dijke, Marius; De Cremer, David; Langendijk, Gerben; Anderson, Cameron

    2018-02-01

    Research shows that power can lead to prosocial behavior by facilitating the behavioral expression of dispositional prosocial motivation. However, it is not clear how power may facilitate responses to contextual factors that promote prosocial motivation. Integrating fairness heuristic theory and the situated focus theory of power, we argue that in particular, organization members in lower (vs. higher) hierarchical positions who simultaneously experience a high (vs. low) sense of power respond with prosocial behavior to 1 important antecedent of prosocial motivation, that is, the enactment of procedural justice. The results from a multisource survey among employees and their leaders from various organizations (Study 1) and an experiment using a public goods dilemma (Study 2) support this prediction. Three subsequent experiments (Studies 3-5) show that this effect is mediated by perceptions of authority trustworthiness. Taken together, this research (a) helps resolve the debate regarding whether power promotes or undermines prosocial behavior, (b) demonstrates that hierarchical position and the sense of power can have very different effects on processes that are vital to the functioning of an organization, and (c) helps solve ambiguity regarding the roles of hierarchical position and power in fairness heuristic theory. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  15. Analysis and experimental evaluation of shunt active power filter for power quality improvement based on predictive direct power control.

    Science.gov (United States)

    Aissa, Oualid; Moulahoum, Samir; Colak, Ilhami; Babes, Badreddine; Kabache, Nadir

    2017-10-12

    This paper discusses the use of the concept of classical and predictive direct power control for shunt active power filter function. These strategies are used to improve the active power filter performance by compensation of the reactive power and the elimination of the harmonic currents drawn by non-linear loads. A theoretical analysis followed by a simulation using MATLAB/Simulink software for the studied techniques has been established. Moreover, two test benches have been carried out using the dSPACE card 1104 for the classic and predictive DPC control to evaluate the studied methods in real time. Obtained results are presented and compared in this paper to confirm the superiority of the predictive technique. To overcome the pollution problems caused by the consumption of fossil fuels, renewable energies are the alternatives recommended to ensure green energy. In the same context, the tested predictive filter can easily be supplied by a renewable energy source that will give its impact to enhance the power quality.

  16. On the impact of NWP model resolution and power source disaggregation on photovoltaic power prediction

    Czech Academy of Sciences Publication Activity Database

    Eben, Kryštof; Juruš, Pavel; Resler, Jaroslav; Pelikán, Emil; Krč, Pavel

    2011-01-01

    Roč. 8, - (2011), EMS2011-667-4 [EMS Annual Meeting /11./ and European Conference on Applications of Meteorology /10./. 12.09.2011-16.09.2011, Berlin] Institutional research plan: CEZ:AV0Z10300504 Keywords : photovoltaic power prediction * NWP * numerical model parameterization Subject RIV: DG - Athmosphere Sciences, Meteorology

  17. Contribution of inner shell electrons to position-dependent stopping powers of a crystal surface

    International Nuclear Information System (INIS)

    Narumi, Kazumasa; Fujii, Yoshikazu; Kishine, Keiji; Kurakake, Hiroshi; Kimura, Kenji; Mannami, Michi-hiko

    1994-01-01

    Position-dependent stopping powers of the (001) surface of SnTe single crystal for specularly reflected 15 - 200 keV H + ions are studied. The position dependence of the experimental stopping powers varies with the energy of ions. From the comparison with the theoretical stopping powers based on both the single ion-electron collision and the collective excitation of the valence electrons, it is concluded that the observed change in the position-dependent stopping powers with energy of H + is due to the variation of contribution of inner shell electrons to stopping. (author)

  18. A machine learning approach to the accurate prediction of multi-leaf collimator positional errors

    Science.gov (United States)

    Carlson, Joel N. K.; Park, Jong Min; Park, So-Yeon; In Park, Jong; Choi, Yunseok; Ye, Sung-Joon

    2016-03-01

    Discrepancies between planned and delivered movements of multi-leaf collimators (MLCs) are an important source of errors in dose distributions during radiotherapy. In this work we used machine learning techniques to train models to predict these discrepancies, assessed the accuracy of the model predictions, and examined the impact these errors have on quality assurance (QA) procedures and dosimetry. Predictive leaf motion parameters for the models were calculated from the plan files, such as leaf position and velocity, whether the leaf was moving towards or away from the isocenter of the MLC, and many others. Differences in positions between synchronized DICOM-RT planning files and DynaLog files reported during QA delivery were used as a target response for training of the models. The final model is capable of predicting MLC positions during delivery to a high degree of accuracy. For moving MLC leaves, predicted positions were shown to be significantly closer to delivered positions than were planned positions. By incorporating predicted positions into dose calculations in the TPS, increases were shown in gamma passing rates against measured dose distributions recorded during QA delivery. For instance, head and neck plans with 1%/2 mm gamma criteria had an average increase in passing rate of 4.17% (SD  =  1.54%). This indicates that the inclusion of predictions during dose calculation leads to a more realistic representation of plan delivery. To assess impact on the patient, dose volumetric histograms (DVH) using delivered positions were calculated for comparison with planned and predicted DVHs. In all cases, predicted dose volumetric parameters were in closer agreement to the delivered parameters than were the planned parameters, particularly for organs at risk on the periphery of the treatment area. By incorporating the predicted positions into the TPS, the treatment planner is given a more realistic view of the dose distribution as it will truly be

  19. What good are positive emotions for treatment? Trait positive emotionality predicts response to Cognitive Behavioral Therapy for anxiety.

    Science.gov (United States)

    Taylor, Charles T; Knapp, Sarah E; Bomyea, Jessica A; Ramsawh, Holly J; Paulus, Martin P; Stein, Murray B

    2017-06-01

    Cognitive behavioral therapy (CBT) is empirically supported for the treatment of anxiety disorders; however, not all individuals achieve recovery following CBT. Positive emotions serve a number of functions that theoretically should facilitate response to CBT - they promote flexible patterns of information processing and assimilation of new information, encourage approach-oriented behavior, and speed physiological recovery from negative emotions. We conducted a secondary analysis of an existing clinical trial dataset to test the a priori hypothesis that individual differences in trait positive emotions would predict CBT response for anxiety. Participants meeting diagnostic criteria for panic disorder (n = 28) or generalized anxiety disorder (n = 31) completed 10 weekly individual CBT sessions. Trait positive emotionality was assessed at pre-treatment, and severity of anxiety symptoms and associated impairment was assessed throughout treatment. Participants who reported a greater propensity to experience positive emotions at pre-treatment displayed the largest reduction in anxiety symptoms as well as fewer symptoms following treatment. Positive emotions remained a robust predictor of change in symptoms when controlling for baseline depression severity. Initial evidence supports the predictive value of trait positive emotions as a prognostic indicator for CBT outcome in a GAD and PD sample. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Scaffolding reflective journal writing - negotiating power, play and position.

    Science.gov (United States)

    Harris, M

    2008-04-01

    A three-year qualitative study based on an action-research design, framed within the critical genre and using a multi-method approach, was used to establish how a model of critical reflective practice [Van Aswegen, E.J., Brink, H.I., Steyn, P.J., 2000. A model for facilitation of critical reflective practice: Part I- Introductory discussion and explanation of the phases followed to construct the model. Part ll - Conceptual analysis within the context of constructing the model. Part III - Description of the model. Curationis 23 (4), 117-135.] could be implemented. Reflective journals were introduced as one of the educational strategies within the model to support and sustain 'deep' transformatory learning. A component of this larger study focused on how scaffolding deep learning through reflective writing is enhanced by supportive structures. These include critiquing (feedback), a mutually developed self-evaluation strategy, as well as an awareness of and sensitivity to the need for student/writer-responder negotiation. Three student groups of part-time post-basic, practicing South African nurses engaged in reflective writing over the period of an academic year. This article is based on their perceptions, mid-way through their writing, of these strategies. It reflects the story of assumptions made by educators, and challenges for change. Students find reflective writing difficult, and although they are willing to accept its value and engage in the process, they require a regular, specific and sensitive critical response from their writer-responder and follow-up supportive contact. Self-evaluation for the purposes of 'owning' their own ideas is difficult, and requires constant support and validation. Transformatory learning comes at a cost, and a revisiting of the balance of power between student and educator is in order.

  1. Power flow prediction in vibrating systems via model reduction

    Science.gov (United States)

    Li, Xianhui

    This dissertation focuses on power flow prediction in vibrating systems. Reduced order models (ROMs) are built based on rational Krylov model reduction which preserve power flow information in the original systems over a specified frequency band. Stiffness and mass matrices of the ROMs are obtained by projecting the original system matrices onto the subspaces spanned by forced responses. A matrix-free algorithm is designed to construct ROMs directly from the power quantities at selected interpolation frequencies. Strategies for parallel implementation of the algorithm via message passing interface are proposed. The quality of ROMs is iteratively refined according to the error estimate based on residual norms. Band capacity is proposed to provide a priori estimate of the sizes of good quality ROMs. Frequency averaging is recast as ensemble averaging and Cauchy distribution is used to simplify the computation. Besides model reduction for deterministic systems, details of constructing ROMs for parametric and nonparametric random systems are also presented. Case studies have been conducted on testbeds from Harwell-Boeing collections. Input and coupling power flow are computed for the original systems and the ROMs. Good agreement is observed in all cases.

  2. A mathematical look at a physical power prediction model

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L. [Riso National Lab., Roskilde (Denmark)

    1997-12-31

    This paper takes a mathematical look at a physical model used to predict the power produced from wind farms. The reason is to see whether simple mathematical expressions can replace the original equations, and to give guidelines as to where the simplifications can be made and where they can not. This paper shows that there is a linear dependence between the geostrophic wind and the wind at the surface, but also that great care must be taken in the selection of the models since physical dependencies play a very important role, e.g. through the dependence of the turning of the wind on the wind speed.

  3. A mathematical look at a physical power prediction model

    DEFF Research Database (Denmark)

    Landberg, L.

    1998-01-01

    This article takes a mathematical look at a physical model used to predict the power produced from wind farms. The reason is to see whether simple mathematical expressions can replace the original equations and to give guidelines as to where simplifications can be made and where they cannot....... The article shows that there is a linear dependence between the geostrophic wind and the local wind at the surface, but also that great care must be taken in the selection of the simple mathematical models, since physical dependences play a very important role, e.g. through the dependence of the turning...

  4. Model Predictive Control of a Wave Energy Converter with Discrete Fluid Power Power Take-Off System

    DEFF Research Database (Denmark)

    Hansen, Anders Hedegaard; Asmussen, Magnus Færing; Bech, Michael Møller

    2018-01-01

    Wave power extraction algorithms for wave energy converters are normally designed without taking system losses into account leading to suboptimal power extraction. In the current work, a model predictive power extraction algorithm is designed for a discretized power take of system. It is shown how...... the quantized nature of a discrete fluid power system may be included in a new model predictive control algorithm leading to a significant increase in the harvested power. A detailed investigation of the influence of the prediction horizon and the time step is reported. Furthermore, it is shown how...

  5. Positive Predictive Value of True Bacteremia according to the Number of Positive Culture Sets in Adult Patients.

    Science.gov (United States)

    Kitaura, Tsuyoshi; Chikumi, Hiroki; Fujiwara, Hiromitsu; Okada, Kensaku; Hayabuchi, Tatsuya; Nakamoto, Masaki; Takata, Miyako; Yamasaki, Akira; Igishi, Tadashi; Burioka, Naoto; Shimizu, Eiji

    2014-12-01

    Performing multiple blood culture sets simultaneously is a standard blood culture methodology, although it is often difficult to distinguish true bacteremia from contamination when only one of several blood culture sets is positive. This study clarified the relationship between the number of positive blood culture sets and clinical significance in patients with positive blood culture. Patients aged 18 years and over with at least 1 positive blood culture were enrolled. Positive blood culture episodes were categorized from clinical records as true bacteremia, contamination, or unknown clinical significance. The associations among episodes of true bacteremia, isolated bacteria, the number of positive blood culture sets from among the performed sets, and the clinical background of patients were analyzed. Among a total of 407 episodes, 262, 67 and 78 were true bacteremia, contamination and unknown clinical significance, respectively. The positive predictive values (PPVs) of 1 out of 1, 1 out of 2 and 2 out of 2 positive sets in cases of Staphylococcus aureus, were 81.3%, 50% and 100% respectively; those in cases of coagulase-negative Staphylococci were 20.5%, 10.8% and 63.5%, respectively. Almost all cases of Escherichia coli, Pseudomonas aeruginosa, Klebsiella species and Candida species were true bacteremia. The probability of true bacteremia was strongly associated with recent surgery in multivariate analysis (P sets from among the performed sets varies by microorganism. Therefore, PPVs calculated using this method may help physicians distinguish true bacteremia from contamination.

  6. Model Predictive Control of a Wave Energy Converter with Discrete Fluid Power Power Take-Off System

    Directory of Open Access Journals (Sweden)

    Anders Hedegaard Hansen

    2018-03-01

    Full Text Available Wave power extraction algorithms for wave energy converters are normally designed without taking system losses into account leading to suboptimal power extraction. In the current work, a model predictive power extraction algorithm is designed for a discretized power take of system. It is shown how the quantized nature of a discrete fluid power system may be included in a new model predictive control algorithm leading to a significant increase in the harvested power. A detailed investigation of the influence of the prediction horizon and the time step is reported. Furthermore, it is shown how the inclusion of a loss model may increase the energy output. Based on the presented results it is concluded that power extraction algorithms based on model predictive control principles are both feasible and favorable for use in a discrete fluid power power take-off system for point absorber wave energy converters.

  7. Epileptic seizure prediction based on a bivariate spectral power methodology.

    Science.gov (United States)

    Bandarabadi, Mojtaba; Teixeira, Cesar A; Direito, Bruno; Dourado, Antonio

    2012-01-01

    The spectral power of 5 frequently considered frequency bands (Alpha, Beta, Gamma, Theta and Delta) for 6 EEG channels is computed and then all the possible pairwise combinations among the 30 features set, are used to create a 435 dimensional feature space. Two new feature selection methods are introduced to choose the best candidate features among those and to reduce the dimensionality of this feature space. The selected features are then fed to Support Vector Machines (SVMs) that classify the cerebral state in preictal and non-preictal classes. The outputs of the SVM are regularized using a method that accounts for the classification dynamics of the preictal class, also known as "Firing Power" method. The results obtained using our feature selection approaches are compared with the ones obtained using minimum Redundancy Maximum Relevance (mRMR) feature selection method. The results in a group of 12 patients of the EPILEPSIAE database, containing 46 seizures and 787 hours multichannel recording for out-of-sample data, indicate the efficiency of the bivariate approach as well as the two new feature selection methods. The best results presented sensitivity of 76.09% (35 of 46 seizures predicted) and a false prediction rate of 0.15(-1).

  8. Testing the Predictive Power of Coulomb Stress on Aftershock Sequences

    Science.gov (United States)

    Woessner, J.; Lombardi, A.; Werner, M. J.; Marzocchi, W.

    2009-12-01

    Empirical and statistical models of clustered seismicity are usually strongly stochastic and perceived to be uninformative in their forecasts, since only marginal distributions are used, such as the Omori-Utsu and Gutenberg-Richter laws. In contrast, so-called physics-based aftershock models, based on seismic rate changes calculated from Coulomb stress changes and rate-and-state friction, make more specific predictions: anisotropic stress shadows and multiplicative rate changes. We test the predictive power of models based on Coulomb stress changes against statistical models, including the popular Short Term Earthquake Probabilities and Epidemic-Type Aftershock Sequences models: We score and compare retrospective forecasts on the aftershock sequences of the 1992 Landers, USA, the 1997 Colfiorito, Italy, and the 2008 Selfoss, Iceland, earthquakes. To quantify predictability, we use likelihood-based metrics that test the consistency of the forecasts with the data, including modified and existing tests used in prospective forecast experiments within the Collaboratory for the Study of Earthquake Predictability (CSEP). Our results indicate that a statistical model performs best. Moreover, two Coulomb model classes seem unable to compete: Models based on deterministic Coulomb stress changes calculated from a given fault-slip model, and those based on fixed receiver faults. One model of Coulomb stress changes does perform well and sometimes outperforms the statistical models, but its predictive information is diluted, because of uncertainties included in the fault-slip model. Our results suggest that models based on Coulomb stress changes need to incorporate stochastic features that represent model and data uncertainty.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  10. Characterizing and predicting the robustness of power-law networks

    International Nuclear Information System (INIS)

    LaRocca, Sarah; Guikema, Seth D.

    2015-01-01

    Power-law networks such as the Internet, terrorist cells, species relationships, and cellular metabolic interactions are susceptible to node failures, yet maintaining network connectivity is essential for network functionality. Disconnection of the network leads to fragmentation and, in some cases, collapse of the underlying system. However, the influences of the topology of networks on their ability to withstand node failures are poorly understood. Based on a study of the response of 2000 randomly-generated power-law networks to node failures, we find that networks with higher nodal degree and clustering coefficient, lower betweenness centrality, and lower variability in path length and clustering coefficient maintain their cohesion better during such events. We also find that network robustness, i.e., the ability to withstand node failures, can be accurately predicted a priori for power-law networks across many fields. These results provide a basis for designing new, more robust networks, improving the robustness of existing networks such as the Internet and cellular metabolic pathways, and efficiently degrading networks such as terrorist cells. - Highlights: • Examine relationship between network topology and robustness to failures. • Relationship is statistically significant for scale-free networks. • Use statistical models to estimate robustness to failures for real-world networks

  11. Predicting Power Output of Upper Body using the OMNI-RES Scale

    Directory of Open Access Journals (Sweden)

    Bautista Iker J.

    2014-12-01

    Full Text Available The main aim of this study was to determine the optimal training zone for maximum power output. This was to be achieved through estimating mean bar velocity of the concentric phase of a bench press using a prediction equation. The values for the prediction equation would be obtained using OMNI-RES scale values of different loads of the bench press exercise. Sixty males ( voluntarily participated in the study and were tested using an incremental protocol on a Smith machine to determine one repetition maximum (1RM in the bench press exercise. A linear regression analysis produced a strong correlation (r = -0.94 between rating of perceived exertion (RPE and mean bar velocity (Velmean. The Pearson correlation analysis between real power output (PotReal and estimated power (PotEst showed a strong correlation coefficient of r = 0.77, significant at a level of p = 0.01. Therefore, the OMNI-RES scale can be used to predict Velmean in the bench press exercise to control the intensity of the exercise. The positive relationship between PotReal and PotEst allowed for the identification of a maximum power-training zone.

  12. Predicting Power Output of Upper Body using the OMNI-RES Scale.

    Science.gov (United States)

    Bautista, Iker J; Chirosa, Ignacio J; Tamayo, Ignacio Martín; González, Andrés; Robinson, Joseph E; Chirosa, Luis J; Robertson, Robert J

    2014-12-09

    The main aim of this study was to determine the optimal training zone for maximum power output. This was to be achieved through estimating mean bar velocity of the concentric phase of a bench press using a prediction equation. The values for the prediction equation would be obtained using OMNI-RES scale values of different loads of the bench press exercise. Sixty males (age 23.61 2.81 year; body height 176.29 6.73 cm; body mass 73.28 4.75 kg) voluntarily participated in the study and were tested using an incremental protocol on a Smith machine to determine one repetition maximum (1RM) in the bench press exercise. A linear regression analysis produced a strong correlation (r = -0.94) between rating of perceived exertion (RPE) and mean bar velocity (Velmean). The Pearson correlation analysis between real power output (PotReal) and estimated power (PotEst) showed a strong correlation coefficient of r = 0.77, significant at a level of p = 0.01. Therefore, the OMNI-RES scale can be used to predict Velmean in the bench press exercise to control the intensity of the exercise. The positive relationship between PotReal and PotEst allowed for the identification of a maximum power-training zone.

  13. Method for Prediction of the Power Output from Photovoltaic Power Plant under Actual Operating Conditions

    Science.gov (United States)

    Obukhov, S. G.; Plotnikov, I. A.; Surzhikova, O. A.; Savkin, K. D.

    2017-04-01

    Solar photovoltaic technology is one of the most rapidly growing renewable sources of electricity that has practical application in various fields of human activity due to its high availability, huge potential and environmental compatibility. The original simulation model of the photovoltaic power plant has been developed to simulate and investigate the plant operating modes under actual operating conditions. The proposed model considers the impact of the external climatic factors on the solar panel energy characteristics that improves accuracy in the power output prediction. The data obtained through the photovoltaic power plant operation simulation enable a well-reasoned choice of the required capacity for storage devices and determination of the rational algorithms to control the energy complex.

  14. Positive predictive value of infective endocarditis in the Danish National Patient Registry: a validation study.

    Science.gov (United States)

    Østergaard, Lauge; Adelborg, Kasper; Sundbøll, Jens; Pedersen, Lars; Loldrup Fosbøl, Emil; Schmidt, Morten

    2018-05-30

    The positive predictive value of an infective endocarditis diagnosis is approximately 80% in the Danish National Patient Registry. However, since infective endocarditis is a heterogeneous disease implying long-term intravenous treatment, we hypothesiszed that the positive predictive value varies by length of hospital stay. A total of 100 patients with first-time infective endocarditis in the Danish National Patient Registry were identified from January 2010 - December 2012 at the University hospital of Aarhus and regional hospitals of Herning and Randers. Medical records were reviewed. We calculated the positive predictive value according to admission length, and separately for patients with a cardiac implantable electronic device and a prosthetic heart valve using the Wilson score method. Among the 92 medical records available for review, the majority of the patients had admission length ⩾2 weeks. The positive predictive value increased with length of admission. In patients with admission length value was 65% while it was 90% for admission length ⩾2 weeks. The positive predictive value was 81% for patients with a cardiac implantable electronic device and 87% for patients with a prosthetic valve. The positive predictive value of the infective endocarditis diagnosis in the Danish National Patient Registry is high for patients with admission length ⩾2 weeks. Using this algorithm, the Danish National Patient Registry provides a valid source for identifying infective endocarditis for research.

  15. Role and position of Nuclear Power Plants Research Institute in nuclear power industry

    International Nuclear Information System (INIS)

    Metke, E.

    1984-01-01

    The Nuclear Power Plants Research Institute carries out applied and experimental research of the operating states of nuclear power plants, of new methods of surveillance and diagnosis of technical equipment, it prepares training of personnel, carries out tests, engineering and technical consultancy and the research of automated control systems. The main research programme of the Institute is the rationalization of raising the safety and operating reliability of WWER nuclear power plants. The Institute is also concerned with quality assurance of selected equipment of nuclear power plants and assembly works, with radioactive waste disposal and the decommissioning of nuclear power plants as well as with the preparation and implementation of the nuclear power plant start-up. The Research Institute is developing various types of equipment, such as equipment for the decontamination of the primary part of the steam generator, a continuous analyzer of chloride levels in water, a gas monitoring instrument, etc. The prospects are listed of the Research Institute and its cooperation with other CMEA member countries. (M.D.)

  16. Centrality of positive and negative deployment memories predicts posttraumatic growth in danish veterans

    DEFF Research Database (Denmark)

    Staugaard, Søren Risløv; Johannessen, Kim Berg; Thomsen, Yvonne Duval

    2015-01-01

    OBJECTIVE: The purpose of the present study was to examine theoretically motivated predictors for the development of positive changes following potentially traumatic experiences (i.e., posttraumatic growth). Specifically, we wanted to examine the prediction that memories of highly negative......-sectional analyses of the data. RESULTS: The main findings were that the centrality of highly emotional memories from deployment predicted growth alongside openness to experience, combat exposure, and social support. Importantly, the centrality of both positive and negative memories predicted growth equally well...

  17. Testing predictive models of positive and negative affect with psychosocial, acculturation, and coping variables in a multiethnic undergraduate sample.

    Science.gov (United States)

    Kuo, Ben Ch; Kwantes, Catherine T

    2014-01-01

    Despite the prevalence and popularity of research on positive and negative affect within the field of psychology, there is currently little research on affect involving the examination of cultural variables and with participants of diverse cultural and ethnic backgrounds. To the authors' knowledge, currently no empirical studies have comprehensively examined predictive models of positive and negative affect based specifically on multiple psychosocial, acculturation, and coping variables as predictors with any sample populations. Therefore, the purpose of the present study was to test the predictive power of perceived stress, social support, bidirectional acculturation (i.e., Canadian acculturation and heritage acculturation), religious coping and cultural coping (i.e., collective, avoidance, and engagement coping) in explaining positive and negative affect in a multiethnic sample of 301 undergraduate students in Canada. Two hierarchal multiple regressions were conducted, one for each affect as the dependent variable, with the above described predictors. The results supported the hypotheses and showed the two overall models to be significant in predicting affect of both kinds. Specifically, a higher level of positive affect was predicted by a lower level of perceived stress, less use of religious coping, and more use of engagement coping in dealing with stress by the participants. Higher level of negative affect, however, was predicted by a higher level of perceived stress and more use of avoidance coping in responding to stress. The current findings highlight the value and relevance of empirically examining the stress-coping-adaptation experiences of diverse populations from an affective conceptual framework, particularly with the inclusion of positive affect. Implications and recommendations for advancing future research and theoretical works in this area are considered and presented.

  18. Correlation to predict heat transfer characteristics of a radially rotating heat pipe at vertical position

    Energy Technology Data Exchange (ETDEWEB)

    Waowaew, N.; Terdtoon, P.; Kamonpet, P.; Klongpanich, W. [Chiang Mai University (Thailand). Dept. of Mechanical Engineering; Maezawa, S. [Seikei University (Japan). Dept. of Mechanical Engineering

    2003-06-01

    The heat transfer characteristics of a radially rotating heat pipe (RRHP) depend on a number of parameters. This paper is a study of the effects of these parameters. They are the inner diameter of the tube, aspect ratio, rotational acceleration, working fluid and the dimensionless parameters of heat transfer. RRHPs, made of copper tubes with inner diameters of 11, 26, and 50.4 mm, were used in the experiments. The aspect ratios were 5, 10, 20 and 40 respectively. The selected working fluids were water, ethanol and R123 (CHCI{sub 2}CF{sub 3}) with a filling ratio of 60% of evaporator volume. The experiments were conducted at inclination angles of 0-90{sup o} from horizontal axis and the rotational accelerations were lower, higher and equal to gravitational acceleration. The working temperature was 90{sup o}C. The evaporator section was heated by electric power while heat in the condenser section was removed naturally by air. The evaporator and adiabatic section of the RRHP were well insulated with ceramic fibers. The experimental results showed that the heat flux decreases with an increasing inner diameter, and decreases with an increasing aspect ratio. The heat flux increases with an increasing rotational acceleration and decreases with an increasing liquid density of the working fluid. A correlation to predict the heat transfer rate at vertical position can be established. Further research will investigate a visual study of internal flow pattern and the formulation of a mathematical model. (author)

  19. Monte Carlo simulation techniques for predicting annual power production

    International Nuclear Information System (INIS)

    Cross, J.P.; Bulandr, P.J.

    1991-01-01

    As the owner and operator of a number of small to mid-sized hydroelectric sites, STS HydroPower has been faced with the need to accurately predict anticipated hydroelectric revenues over a period of years. The typical approach to this problem has been to look at each site from a mathematical deterministic perspective and evaluate the annual production from historic streamflows. Average annual production is simply taken to be the area under the flow duration curve defined by the operating and design characteristics of the selected turbines. Minimum annual production is taken to be a historic dry year scenario and maximum production is viewed as power generated under the most ideal of conditions. Such an approach creates two problems. First, in viewing the characteristics of a single site, it does not take into account the probability of such an event occurring. Second, in viewing all sites in a single organization's portfolio together, it does not reflect the varying flow conditions at the different sites. This paper attempts to address the first of these two concerns, that being the creation of a simulation model utilizing the Monte Carlo method at a single site. The result of the analysis is a picture of the production at the site that is both a better representation of anticipated conditions and defined probabilistically

  20. Prediction of lung tumour position based on spirometry and on abdominal displacement: Accuracy and reproducibility

    International Nuclear Information System (INIS)

    Hoisak, Jeremy D.P.; Sixel, Katharina E.; Tirona, Romeo; Cheung, Patrick C.F.; Pignol, Jean-Philippe

    2006-01-01

    Background and purpose: A simulation investigating the accuracy and reproducibility of a tumour motion prediction model over clinical time frames is presented. The model is formed from surrogate and tumour motion measurements, and used to predict the future position of the tumour from surrogate measurements alone. Patients and methods: Data were acquired from five non-small cell lung cancer patients, on 3 days. Measurements of respiratory volume by spirometry and abdominal displacement by a real-time position tracking system were acquired simultaneously with X-ray fluoroscopy measurements of superior-inferior tumour displacement. A model of tumour motion was established and used to predict future tumour position, based on surrogate input data. The calculated position was compared against true tumour motion as seen on fluoroscopy. Three different imaging strategies, pre-treatment, pre-fraction and intrafractional imaging, were employed in establishing the fitting parameters of the prediction model. The impact of each imaging strategy upon accuracy and reproducibility was quantified. Results: When establishing the predictive model using pre-treatment imaging, four of five patients exhibited poor interfractional reproducibility for either surrogate in subsequent sessions. Simulating the formulation of the predictive model prior to each fraction resulted in improved interfractional reproducibility. The accuracy of the prediction model was only improved in one of five patients when intrafractional imaging was used. Conclusions: Employing a prediction model established from measurements acquired at planning resulted in localization errors. Pre-fractional imaging improved the accuracy and reproducibility of the prediction model. Intrafractional imaging was of less value, suggesting that the accuracy limit of a surrogate-based prediction model is reached with once-daily imaging

  1. The Emotional Landscapes of Literacy Coaching: Issues of Identity, Power, and Positioning

    Science.gov (United States)

    Hunt, Carolyn S.; Handsfield, Lara J.

    2013-01-01

    In this article, the researchers use positioning theory and de Certeau's theoretical insights into cultural production in everyday life to examine how first-year literacy coaches negotiate issues of power, positioning, and identity during their professional development. Data were collected during a yearlong qualitative study of literacy coaches…

  2. Improved design for vibration-proof platinum RTD in special position of nuclear power plant

    International Nuclear Information System (INIS)

    Liu Zhuo; Ma Jinna; Wu Bin

    2014-01-01

    In accordance with the actual situation for the vibration of violence in a special position of nuclear power plant, an improved design for platinum RTD was proposed. The structure design is verified to meet the measure requirement in the special position. (authors)

  3. Job analysis of the instrument and control technician position for the nuclear power plant maintenance personnel reliability model

    International Nuclear Information System (INIS)

    Siegel, A.I.; Bartter, W.D.; Federman, P.J.

    1983-08-01

    This report is one of a series that is planned to describe the results of a program undertaken by the Oak Ridge National Laboratory (ORNL) for the US Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, to define, develop, validate, and disseminate a methodology for the quantitative prediction of human reliability in the conduct of maintenance tasks in nuclear power plants (NPPs). ORNL has subcontracted portions of this effort to Applied Psychological Services, Inc. This report on the job analysis of the Instrument and Control technician (NUREG/CR-3274) and a report on the job analysis of the electrician position (NUREG/CR-3275) comprise a part of the initial efforts of the development phase of this program. With the publication of the job analysis of the electrician position, the series of job analyses reports addressing nuclear power plant maintenance personnel will be complete. Subsequent reports addressing model development and validation are planned

  4. Intrapersonal positive future thinking predicts repeat suicide attempts in hospital-treated suicide attempters.

    Science.gov (United States)

    O'Connor, Rory C; Smyth, Roger; Williams, J Mark G

    2015-02-01

    Although there is clear evidence that low levels of positive future thinking (anticipation of positive experiences in the future) and hopelessness are associated with suicide risk, the relationship between the content of positive future thinking and suicidal behavior has yet to be investigated. This is the first study to determine whether the positive future thinking-suicide attempt relationship varies as a function of the content of the thoughts and whether positive future thinking predicts suicide attempts over time. A total of 388 patients hospitalized following a suicide attempt completed a range of clinical and psychological measures (depression, hopelessness, suicidal ideation, suicidal intent and positive future thinking). Fifteen months later, a nationally linked database was used to determine who had been hospitalized again after a suicide attempt. During follow-up, 25.6% of linked participants were readmitted to hospital following a suicide attempt. In univariate logistic regression analyses, previous suicide attempts, suicidal ideation, hopelessness, and depression-as well as low levels of achievement, low levels of financial positive future thoughts, and high levels of intrapersonal (thoughts about the individual and no one else) positive future thoughts predicted repeat suicide attempts. However, only previous suicide attempts, suicidal ideation, and high levels of intrapersonal positive future thinking were significant predictors in multivariate analyses. Positive future thinking has predictive utility over time; however, the content of the thinking affects the direction and strength of the positive future thinking-suicidal behavior relationship. Future research is required to understand the mechanisms that link high levels of intrapersonal positive future thinking to suicide risk and how intrapersonal thinking should be targeted in treatment interventions. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

  5. Incremental validity of positive orientation: predictive efficiency beyond the five-factor model

    Directory of Open Access Journals (Sweden)

    Łukasz Roland Miciuk

    2016-05-01

    Full Text Available Background The relation of positive orientation (a basic predisposition to think positively of oneself, one’s life and one’s future and personality traits is still disputable. The purpose of the described research was to verify the hypothesis that positive orientation has predictive efficiency beyond the five-factor model. Participants and procedure One hundred and thirty participants (at the mean age M = 24.84 completed the following questionnaires: the Self-Esteem Scale (SES, the Satisfaction with Life Scale (SWLS, the Life Orientation Test-Revised (LOT-R, the Positivity Scale (P-SCALE, the NEO Five Factor Inventory (NEO-FFI, the Self-Concept Clarity Scale (SCC, the Generalized Self-Efficacy Scale (GSES and the Life Engagement Test (LET. Results The introduction of positive orientation as an additional predictor in the second step of regression analyses led to better prediction of the following variables: purpose in life, self-concept clarity and generalized self-efficacy. This effect was the strongest for predicting purpose in life (i.e. 14% increment of the explained variance. Conclusions The results confirmed our hypothesis that positive orientation can be characterized by incremental validity – its inclusion in the regression model (in addition to the five main factors of personality increases the amount of explained variance. These findings may provide further evidence for the legitimacy of measuring positive orientation and personality traits separately.

  6. The determination of contribution of emotional intelligence and parenting styles components to predicts positive psychological components

    Directory of Open Access Journals (Sweden)

    hosein Ebrahimi moghadam

    2015-05-01

    Full Text Available Background: Since the essential of positive psychological components, as compliment of deficiency oriented approaches, has begun in recent days,we decided to take into account this new branch of psychology which scientifically considers studying forces of human, as well as because of the importance of this branch of psychology, we also tried to search the contribution of emotional intelligence and parenting styles components to predict positive psychological components. Materials and Methods:In this cross sectional study 200 psychological students of Azad university (Rudehen branch selected using cluster sampling method. Then they were estimated by Bradbery and Grivers emotional intelligence questionnaire , Bamrind parenting styles and Rajayi et al positive psychological components questionnaire. Research data was analyzed using descriptive statistics (mean and standard deviation, inferential statistics (multiple regression and Pierson correlation coefficient and SPSS software. Results:Among the components of emotional intelligence, the component of emotional self consciousness (β=0.464 had the greatest predictable , and reaction leadership showed no predictability in this research between parenting styles , authority parenting styles had positive significance relationship with positive psychological components. And no significant relationship was found between despot parenting styles and positive psychological components. Conclusion: Regarding the results of this research and importance of positive psychological components, it is suggested to treat the emotional intelligence from childhood and to learn it to parents and remind them the parenting way to decrease the satisfaction of individuals which leads to promotion of society mental health.

  7. Geometrical prediction of maximum power point for photovoltaics

    International Nuclear Information System (INIS)

    Kumar, Gaurav; Panchal, Ashish K.

    2014-01-01

    Highlights: • Direct MPP finding by parallelogram constructed from geometry of I–V curve of cell. • Exact values of V and P at MPP obtained by Lagrangian interpolation exploration. • Extensive use of Lagrangian interpolation for implementation of proposed method. • Method programming on C platform with minimum computational burden. - Abstract: It is important to drive solar photovoltaic (PV) system to its utmost capacity using maximum power point (MPP) tracking algorithms. This paper presents a direct MPP prediction method for a PV system considering the geometry of the I–V characteristic of a solar cell and a module. In the first step, known as parallelogram exploration (PGE), the MPP is determined from a parallelogram constructed using the open circuit (OC) and the short circuit (SC) points of the I–V characteristic and Lagrangian interpolation. In the second step, accurate values of voltage and power at the MPP, defined as V mp and P mp respectively, are decided by the Lagrangian interpolation formula, known as the Lagrangian interpolation exploration (LIE). Specifically, this method works with a few (V, I) data points instead most of the MPP algorithms work with (P, V) data points. The performance of the method is examined by several PV technologies including silicon, copper indium gallium selenide (CIGS), copper zinc tin sulphide selenide (CZTSSe), organic, dye sensitized solar cell (DSSC) and organic tandem cells’ data previously reported in literatures. The effectiveness of the method is tested experimentally for a few silicon cells’ I–V characteristics considering variation in the light intensity and the temperature. At last, the method is also employed for a 10 W silicon module tested in the field. To testify the preciseness of the method, an absolute value of the derivative of power (P) with respect to voltage (V) defined as (dP/dV) is evaluated and plotted against V. The method estimates the MPP parameters with high accuracy for any

  8. A 3-Year Study of Predictive Factors for Positive and Negative Appendicectomies.

    Science.gov (United States)

    Chang, Dwayne T S; Maluda, Melissa; Lee, Lisa; Premaratne, Chandrasiri; Khamhing, Srisongham

    2018-03-06

    Early and accurate identification or exclusion of acute appendicitis is the key to avoid the morbidity of delayed treatment for true appendicitis or unnecessary appendicectomy, respectively. We aim (i) to identify potential predictive factors for positive and negative appendicectomies; and (ii) to analyse the use of ultrasound scans (US) and computed tomography (CT) scans for acute appendicitis. All appendicectomies that took place at our hospital from the 1st of January 2013 to the 31st of December 2015 were retrospectively recorded. Test results of potential predictive factors of acute appendicitis were recorded. Statistical analysis was performed using Fisher exact test, logistic regression analysis, sensitivity, specificity, and positive and negative predictive values calculation. 208 patients were included in this study. 184 patients had histologically proven acute appendicitis. The other 24 patients had either nonappendicitis pathology or normal appendix. Logistic regression analysis showed statistically significant associations between appendicitis and white cell count, neutrophil count, C-reactive protein, and bilirubin. Neutrophil count was the test with the highest sensitivity and negative predictive values, whereas bilirubin was the test with the highest specificity and positive predictive values (PPV). US and CT scans had high sensitivity and PPV for diagnosing appendicitis. No single test was sufficient to diagnose or exclude acute appendicitis by itself. Combining tests with high sensitivity (abnormal neutrophil count, and US and CT scans) and high specificity (raised bilirubin) may predict acute appendicitis more accurately.

  9. New approach for control rod position indication system for light water power reactor

    International Nuclear Information System (INIS)

    Bahuguna, Sushil; Dhage, Sangeeta; Nawaj, S.; Salek, C.; Lahiri, S.K.; Marathe, P.P.; Mukhopadhyay, S.; Taly, Y.K.

    2015-01-01

    Control rod position indication system is an important system in a nuclear power plant to monitor and display control rod position in all regimes of reactor operation. A new approach to design a control rod position indication system for sensing absolute position of control rod in Light Water Power Reactor has been undertaken. The proposed system employs an inductive type, hybrid measurement strategy providing both analog position as well as digital zone indication with built-in temperature compensation. The new design approach meets single failure criterion through redundancy in design without sacrificing measurement resolution. It also provides diversity in measurement technique by indirect position sensing based on analysis of drive coil current signature. Prototype development and qualification at room temperature of the control rod position indication system (CRPIS) has been demonstrated. The article presents the design philosophy of control rod position indication system, the new measurement strategy for sensing absolute position of control rod, position estimation algorithm for both direct and indirect sensing and a brief account associated processing electronics. (author)

  10. Predicting Positive Education Outcomes for Emerging Adults in Mental Health Systems of Care.

    Science.gov (United States)

    Brennan, Eileen M; Nygren, Peggy; Stephens, Robert L; Croskey, Adrienne

    2016-10-01

    Emerging adults who receive services based on positive youth development models have shown an ability to shape their own life course to achieve positive goals. This paper reports secondary data analysis from the Longitudinal Child and Family Outcome Study including 248 culturally diverse youth ages 17 through 22 receiving mental health services in systems of care. After 12 months of services, school performance was positively related to youth ratings of school functioning and service participation and satisfaction. Regression analysis revealed ratings of young peoples' perceptions of school functioning, and their experience in services added to the significant prediction of satisfactory school performance, even controlling for sex and attendance. Finally, in addition to expected predictors, participation in planning their own services significantly predicted enrollment in higher education for those who finished high school. Findings suggest that programs and practices based on positive youth development approaches can improve educational outcomes for emerging adults.

  11. Replicability and 40-Year Predictive Power of Childhood ARC Types

    Science.gov (United States)

    Chapman, Benjamin P.; Goldberg, Lewis R.

    2011-01-01

    We examined three questions surrounding the Undercontrolled, Overcontrolled, and Resilient--or Asendorpf-Robins-Caspi (ARC)--personality types originally identified by Block (1971). In analyses of the teacher personality assessments of over 2,000 children in 1st through 6th grade in 1959-1967, and follow-up data on general and cardiovascular health outcomes in over 1,100 adults recontacted 40 years later, we found: (1) Bootstrapped internal replication clustering suggested that Big Five scores were best characterized by a tripartite cluster structure corresponding to the ARC types; (2) this cluster structure was fuzzy, rather than discrete, indicating that ARC constructs are best represented as gradients of similarity to three prototype Big Five profiles; and (3) ARC types and degrees of ARC prototypicality showed associations with multiple health outcomes 40 years later. ARC constructs were more parsimonious, but neither better nor more consistent predictors than the dimensional Big Five traits. Forty-year incident cases of heart disease could be correctly identified with 68% accuracy by personality information alone, a figure approaching the 12-year accuracy of a leading medical cardiovascular risk model. Findings support the theoretical validity of ARC constructs, their treatment as continua of prototypicality rather than discrete categories, and the need for further understanding the robust predictive power of childhood personality traits for mid-life health. PMID:21744975

  12. Positive Skin Test or Specific IgE to Penicillin Does Not Reliably Predict Penicillin Allergy.

    Science.gov (United States)

    Tannert, Line Kring; Mortz, Charlotte Gotthard; Skov, Per Stahl; Bindslev-Jensen, Carsten

    According to guidelines, patients are diagnosed with penicillin allergy if skin test (ST) result or specific IgE (s-IgE) to penicillin is positive. However, the true sensitivity and specificity of these tests are presently not known. To investigate the clinical relevance of a positive ST result and positive s-IgE and to study the reproducibility of ST and s-IgE. A sample of convenience of 25 patients with positive penicillin ST results, antipenicillin s-IgE results, or both was challenged with their culprit penicillin. Further 19 patients were not challenged, but deemed allergic on the basis of a recent anaphylactic reaction or delayed reactions to skin testing. Another sample of convenience of 18 patients, 17 overlapping with the 25 challenged, with initial skin testing and s-IgE (median, 25; range, 3-121), months earlier (T -1 ), was repeat skin tested and had s-IgE measured (T 0 ), and then skin tested and had s-IgE measured 4 weeks later (T 1 ). Only 9 (36%) of 25 were challenge positive. There was an increased probability of being penicillin allergic if both ST result and s-IgE were positive at T 0 . Positive ST result or positive s-IgE alone did not predict penicillin allergy. Among the 18 patients repeatedly tested, 46.2% (12 of 25) of positive ST results at T -1 were reproducibly positive at T 0 . For s-IgE, 54.2% (14 of 24) positive measurements were still positive at T 0 and 7 converted to positive at T 1 . The best predictor for a clinically significant (IgE-mediated) penicillin allergy is a combination of a positive case history with simultaneous positive ST result and s-IgE or a positive challenge result. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

  13. The determination of contribution of emotional intelligence and parenting styles components to predicts positive psychological components

    OpenAIRE

    hosein Ebrahimi moghadam; mahin Fekraty

    2015-01-01

    Background: Since the essential of positive psychological components, as compliment of deficiency oriented approaches, has begun in recent days,we decided to take into account this new branch of psychology which scientifically considers studying forces of human, as well as because of the importance of this branch of psychology, we also tried to search the contribution of emotional intelligence and parenting styles components to predict positive psychological components. Materials and Methods:...

  14. Emotion dysregulation and social competence: stability, change and predictive power.

    Science.gov (United States)

    Berkovits, L D; Baker, B L

    2014-08-01

    Social difficulties are closely linked to emotion dysregulation among children with typical development (TD). Children with developmental delays (DD) are at risk for poor social outcomes, but the relationship between social and emotional development within this population is not well understood. The current study examines the extent to which emotion dysregulation is related to social problems across middle childhood among children with TD or DD. Children with TD (IQ ≥ 85, n = 113) and children with DD (IQ ≤ 75, n = 61) participated in a longitudinal study. Annual assessments were completed at ages 7, 8 and 9 years. At each assessment, mothers reported on children's emotion dysregulation, and both mothers and teachers reported on children's social difficulties. Children with DD had higher levels of emotion dysregulation and social problems at each age than those with TD. Emotion dysregulation and social problems were significantly positively correlated within both TD and DD groups using mother report of social problems, and within the TD group using teacher report of social problems. Among children with TD, emotion dysregulation consistently predicted change in social problems from one year to the next. However, among children with DD, emotion dysregulation offered no unique prediction value above and beyond current social problems. Results suggested that the influence of emotion regulation abilities on social development may be a less salient pathway for children with DD. These children may have more influences, beyond emotion regulation, on their social behaviour, highlighting the importance of directly targeting social skill deficits among children with DD in order to ameliorate their social difficulties. © 2013 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

  15. The Positive Effect of Authoritarian Leadership on Employee Performance: The Moderating Role of Power Distance

    Science.gov (United States)

    Wang, Honglei; Guan, Bichen

    2018-01-01

    Based on goal setting theory, this study explores the positive effect and influencing process of authoritarian leadership on employee performance, as well as the moderating role of individual power distance in this process. Data from 211 supervisor-subordinate dyads in Chinese organizations indicates that authoritarian leadership is positively associated with employee performance, and learning goal orientation mediates this relationship. Furthermore, power distance moderates the effect of authoritarian leadership on learning goal orientation, such that the effect was stronger when individual power distance was higher. The indirect effect of authoritarian leadership on employee performance via learning goal orientation is also moderated by power distance. Theoretical and managerial implications and future directions are also discussed. PMID:29628902

  16. The Positive Effect of Authoritarian Leadership on Employee Performance: The Moderating Role of Power Distance.

    Science.gov (United States)

    Wang, Honglei; Guan, Bichen

    2018-01-01

    Based on goal setting theory, this study explores the positive effect and influencing process of authoritarian leadership on employee performance, as well as the moderating role of individual power distance in this process. Data from 211 supervisor-subordinate dyads in Chinese organizations indicates that authoritarian leadership is positively associated with employee performance, and learning goal orientation mediates this relationship. Furthermore, power distance moderates the effect of authoritarian leadership on learning goal orientation, such that the effect was stronger when individual power distance was higher. The indirect effect of authoritarian leadership on employee performance via learning goal orientation is also moderated by power distance. Theoretical and managerial implications and future directions are also discussed.

  17. Preserving the nuclear option: The AIAA position paper on space nuclear power

    International Nuclear Information System (INIS)

    Allen, D.M.; Bennett, G.L.; El-Genk, M.S.; Newhouse, A.R.; Rose, M.F.; Rovang, R.D.

    1996-01-01

    In response to published reports about the decline in funding for space nuclear power, the Board of Directors of the American Institute of Aeronautics and Astronautics (AIAA) approved a position paper in March 1995 that recommends (1) development and support of an integrated space nuclear power program by DOE, NASA and DoD; (2) Congressional support for the program; (3) advocacy of the program by government and industry leaders; and (4) continuation of cooperation between the U.S. and other countries to advance nuclear power source technology and to promote safety. This position paper has been distributed to various people having oversight of the U.S. space nuclear power program. copyright 1996 American Institute of Physics

  18. Optically powered and interrogated rotary position sensor for aircraft engine control applications

    Science.gov (United States)

    Spillman, W. B.; Crowne, D. H.; Woodward, D. W.

    A throttle level angle (TLA) sensing system is described that utilizes a capacitance based rotary position transducer that is powered and interrogated via light from a single multimode optical fiber. The system incorporates a unique GaAs device that serves as both a power converter and optical data transmitter. Design considerations are discussed, and the fabrication and performance of the sensor system are detailed.

  19. Analysis of variability and predictability challenges of wind and solar power

    NARCIS (Netherlands)

    Haan, de J.E.S.; Virag, A.; Kling, W.L.

    2013-01-01

    In power systems, reserves are essential to ensure system security, certainly when challenges of predictability (inaccurate forecast) and variability (imperfect correlation of renewable generation and system load) are causing power imbalances. Different techniques can be used to size and allocate

  20. A process for providing positive primary control power by wind turbines

    Science.gov (United States)

    Marschner, V.; Michael, J.; Liersch, J.

    2014-12-01

    Due to the increasing share of wind energy in electricity generation, wind turbines have to fulfil additional requirements in the context of grid integration. The paper examines to which extent wind turbines can provide positive control power following the related grid code. The additional power has to be obtained from the rotating flywheel mass of the wind turbine's rotor. A simple physical model is developed that allows to draw conclusions about appropriate concepts by means of a dynamic simulation of the variables rotational speed, torque, power output and rotor power. The paper discusses scenarios to provide control power. The supply of control power at partial load is examined in detail using simulations. Under partial load conditions control power can be fed into the grid for a short time. Thereby the rotational speed drops so that aerodynamic efficiency decreases and feed-in power is below the initial value after the control process. In this way an unfavourable situation for the grid control is produced, therefore the paper proposes a modified partial load condition with a higher rotational speed. By providing primary control power the rotor is delayed to the optimum rotational speed so that more rotational energy can be fed in and fed-in power can be increased persistently. However, as the rotor does not operate at optimum speed, a small amount of the energy yield is lost. Finally, the paper shows that a wind farm can combine these two concepts: A part of the wind turbines work under modified partial load conditions can compensate the decrease of power of the wind turbines working under partial load conditions. Therefore the requested control power is provided and afterwards the original value of power is maintained.

  1. Predicting the short-term risk of diabetes in HIV-positive patients

    DEFF Research Database (Denmark)

    Petoumenos, Kathy; Worm, Signe W; Fontas, Eric

    2012-01-01

    HIV-positive patients receiving combination antiretroviral therapy (cART) frequently experience metabolic complications such as dyslipidemia and insulin resistance, as well as lipodystrophy, increasing the risk of cardiovascular disease (CVD) and diabetes mellitus (DM). Rates of DM and other...... glucose-associated disorders among HIV-positive patients have been reported to range between 2 and 14%, and in an ageing HIV-positive population, the prevalence of DM is expected to continue to increase. This study aims to develop a model to predict the short-term (six-month) risk of DM in HIV...

  2. The Role of Perceived Social Support and Coping Styles in Predicting Adolescents' Positivity

    Science.gov (United States)

    Çevik, Gülsen Büyüksahin; Yildiz, Mehmet Ali

    2017-01-01

    The current research aims to examine the perceived social support and coping styles predicting positivity. Research participants included 268 adolescents, attending high school, with 147 females (54.9%) and 121 males (45.1%). Adolescents participating in the research were 14 to 18 years old and their average age was 16.12 with SD = 1.01. Research…

  3. Explicit Generalized Predictive Control of Speed and Position of PMSM Drives

    Czech Academy of Sciences Publication Activity Database

    Belda, Květoslav; Vošmik, D.

    2016-01-01

    Roč. 63, č. 6 (2016), s. 3889-3896 ISSN 0278-0046 Institutional support: RVO:67985556 Keywords : current limitation * field weakening * motion control * permanent magnet synchronous motors * position control * predictive control * speed control Subject RIV: BC - Control Systems Theory Impact factor: 7.168, year: 2016 http://library.utia.cas.cz/separaty/2016/AS/belda-0457259.pdf

  4. Evaluation of two methods of predicting MLC leaf positions using EPID measurements

    International Nuclear Information System (INIS)

    Parent, Laure; Seco, Joao; Evans, Phil M.; Dance, David R.; Fielding, Andrew

    2006-01-01

    In intensity modulated radiation treatments (IMRT), the position of the field edges and the modulation within the beam are often achieved with a multileaf collimator (MLC). During the MLC calibration process, due to the finite accuracy of leaf position measurements, a systematic error may be introduced to leaf positions. Thereafter leaf positions of the MLC depend on the systematic error introduced on each leaf during MLC calibration and on the accuracy of the leaf position control system (random errors). This study presents and evaluates two methods to predict the systematic errors on the leaf positions introduced during the MLC calibration. The two presented methods are based on a series of electronic portal imaging device (EPID) measurements. A comparison with film measurements showed that the EPID could be used to measure leaf positions without introducing any bias. The first method, referred to as the 'central leaf method', is based on the method currently used at this center for MLC leaf calibration. It mimics the manner in which leaf calibration parameters are specified in the MLC control system and consequently is also used by other centers. The second method, a new method proposed by the authors and referred to as the ''individual leaf method,'' involves the measurement of two positions for each leaf (-5 and +15 cm) and the interpolation and extrapolation from these two points to any other given position. The central leaf method and the individual leaf method predicted leaf positions at prescribed positions of -11, 0, 5, and 10 cm within 2.3 and 1.0 mm, respectively, with a standard deviation (SD) of 0.3 and 0.2 mm, respectively. The individual leaf method provided a better prediction of the leaf positions than the central leaf method. Reproducibility tests for leaf positions of -5 and +15 cm were performed. The reproducibility was within 0.4 mm on the same day and 0.4 mm six weeks later (1 SD). Measurements at gantry angles of 0 deg., 90 deg., and 270 deg

  5. vmPFC activation during a stressor predicts positive emotions during stress recovery

    Science.gov (United States)

    Yang, Xi; Garcia, Katelyn M; Jung, Youngkyoo; Whitlow, Christopher T; McRae, Kateri; Waugh, Christian E

    2018-01-01

    Abstract Despite accruing evidence showing that positive emotions facilitate stress recovery, the neural basis for this effect remains unclear. To identify the underlying mechanism, we compared stress recovery for people reflecting on a stressor while in a positive emotional context with that for people in a neutral context. While blood–oxygen-level dependent data were being collected, participants (N = 43) performed a stressful anagram task, which was followed by a recovery period during which they reflected on the stressor while watching a positive or neutral video. Participants also reported positive and negative emotions throughout the task as well as retrospective thoughts about the task. Although there was no effect of experimental context on emotional recovery, we found that ventromedial prefrontal cortex (vmPFC) activation during the stressor predicted more positive emotions during recovery, which in turn predicted less negative emotions during recovery. In addition, the relationship between vmPFC activation and positive emotions during recovery was mediated by decentering—the meta-cognitive detachment of oneself from one’s feelings. In sum, successful recovery from a stressor seems to be due to activation of positive emotion-related regions during the stressor itself as well as to their downstream effects on certain cognitive forms of emotion regulation. PMID:29462404

  6. Power capability prediction for lithium-ion batteries based on multiple constraints analysis

    International Nuclear Information System (INIS)

    Pan, Rui; Wang, Yujie; Zhang, Xu; Yang, Duo; Chen, Zonghai

    2017-01-01

    Highlights: • Multiple constraints for peak power capability prediction are deeply analyzed. • Multi-limited method is proposed for the peak power capability prediction of LIBs. • The EKF is used for the model based peak power capability prediction. • The FUDS and UDDS profiles are executed to evaluate the proposed method. - Abstract: The power capability of the lithium-ion battery is a key performance indicator for electric vehicle, and it is intimately correlated with the acceleration, regenerative braking and gradient climbing power requirements. Therefore, an accurate power capability or state-of-power prediction is critical to a battery management system, which can help the battery to work in suitable area and prevent the battery from over-charging and over-discharging. However, the power capability is easily affected by dynamic load, voltage variation and temperature. In this paper, three different constraints in power capability prediction are introduced, and the advantages and disadvantages of the three methods are deeply analyzed. Furthermore, a multi-limited approach for the power capability prediction is proposed, which can overcome the drawbacks of the three methods. Subsequently, the extended Kalman filter algorithm is employed for model based state-of-power prediction. In order to verify the proposed method, diverse experiments are executed to explore the efficiency, robustness, and precision. The results indicate that the proposed method can improve the precision and robustness obviously.

  7. Strength, power, speed, and agility of women basketball players according to playing position.

    Science.gov (United States)

    Delextrat, Anne; Cohen, Daniel

    2009-10-01

    The aim of the present study was to investigate the effect of playing position on strength, power, speed, and agility performances of women basketball players. Thirty subjects playing at national level participated in this study. They were divided into 3 groups according to playing position: guards (positions 1 and 2), forwards (positions 3 and 4), and centers (position 5). Each subject performed 8 tests presented in a random order: The 30-second Wingate Anaerobic test (WAnT), isokinetic testing of the knee extensors, 2 types of jump tests, a 20-m sprint, the agility T-test, a suicide run, and a basketball chest pass. Statistical differences between playing positions were assessed using a 1-way analysis of variance (ANOVA) and Scheffe post hoc analyses. Results showed that guards performed significantly better than centers for the relative peak and mean power achieved during the WAnT (+13% and +16.9%, respectively), relative peak torque of knee extensors (+19.5%), single-leg jump (+21.8), suicide run (+7.5%), and agility T-test (+6.4%, p training must be undertaken according to playing position. The ability to perform the suicide run, the single-leg jump, and the different movements involved in the agility T-test must be developed in guards. In contrast, speed over short distances and strength development of lower body and upper body should be performed by all playing positions.

  8. Predicting the short-term risk of diabetes in HIV-positive patients

    DEFF Research Database (Denmark)

    Petoumenos, Kathy; Worm, Signe Westring; Fontas, Eric

    2012-01-01

    Introduction: HIV-positive patients receiving combination antiretroviral therapy (cART) frequently experience metabolic complications such as dyslipidemia and insulin resistance, as well as lipodystrophy, increasing the risk of cardiovascular disease (CVD) and diabetes mellitus (DM). Rates of DM ......). Factors predictive of DM included higher glucose, body mass index (BMI) and triglyceride levels, and older age. Among HIV-related factors, recent CD4 counts of...... and other glucose-associated disorders among HIV-positive patients have been reported to range between 2 and 14%, and in an ageing HIV-positive population, the prevalence of DM is expected to continue to increase. This study aims to develop a model to predict the short-term (six-month) risk of DM in HIV...

  9. A New Weighted Injury Severity Scoring System: Better Predictive Power for Pediatric Trauma Mortality.

    Science.gov (United States)

    Shi, Junxin; Shen, Jiabin; Caupp, Sarah; Wang, Angela; Nuss, Kathryn E; Kenney, Brian; Wheeler, Krista K; Lu, Bo; Xiang, Henry

    2018-05-02

    An accurate injury severity measurement is essential for the evaluation of pediatric trauma care and outcome research. The traditional Injury Severity Score (ISS) does not consider the differential risks of the Abbreviated Injury Scale (AIS) from different body regions nor is it pediatric specific. The objective of this study was to develop a weighted injury severity scoring (wISS) system for pediatric blunt trauma patients with better predictive power than ISS. Based on the association between mortality and AIS from each of the six ISS body regions, we generated different weights for the component AIS scores used in the calculation of ISS. The weights and wISS were generated using the National Trauma Data Bank (NTDB). The Nationwide Emergency Department Sample (NEDS) was used to validate our main results. Pediatric blunt trauma patients less than 16 years were included, and mortality was the outcome. Discrimination (areas under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, concordance) and calibration (Hosmer-Lemeshow statistic) were compared between the wISS and ISS. The areas under the receiver operating characteristic curves from the wISS and ISS are 0.88 vs. 0.86 in ISS=1-74 and 0.77 vs. 0.64 in ISS=25-74 (ppredictive value, negative predictive value, and concordance when they were compared at similar levels of sensitivity. The wISS had better calibration (smaller Hosmer-Lemeshow statistic) than the ISS (11.6 versus 19.7 for ISS=1-74 and 10.9 versus 12.6 for ISS= 25-74). The wISS showed even better discrimination with the NEDS. By weighting the AIS from different body regions, the wISS had significantly better predictive power for mortality than the ISS, especially in critically injured children.Level of Evidence and study typeLevel IV Prognostic/Epidemiological.

  10. An updated prediction model of the global risk of cardiovascular disease in HIV-positive persons

    DEFF Research Database (Denmark)

    Friis-Møller, Nina; Ryom, Lene; Smith, Colette

    2016-01-01

    ,663 HIV-positive persons from 20 countries in Europe and Australia, who were free of CVD at entry into the Data-collection on Adverse Effects of Anti-HIV Drugs (D:A:D) study. Cox regression models (full and reduced) were developed that predict the risk of a global CVD endpoint. The predictive performance...... significantly predicted risk more accurately than the recalibrated Framingham model (Harrell's c-statistic of 0.791, 0.783 and 0.766 for the D:A:D full, D:A:D reduced, and Framingham models respectively; p models also more accurately predicted five-year CVD-risk for key prognostic subgroups...... to quantify risk and to guide preventive care....

  11. Situational Motivation and Perceived Intensity: Their Interaction in Predicting Changes in Positive Affect from Physical Activity

    Directory of Open Access Journals (Sweden)

    Eva Guérin

    2012-01-01

    Full Text Available There is evidence that affective experiences surrounding physical activity can contribute to the proper self-regulation of an active lifestyle. Motivation toward physical activity, as portrayed by self-determination theory, has been linked to positive affect, as has the intensity of physical activity, especially of a preferred nature. The purpose of this experimental study was to examine the interaction between situational motivation and intensity [i.e., ratings of perceived exertion (RPE] in predicting changes in positive affect following an acute bout of preferred physical activity, namely, running. Fourty-one female runners engaged in a 30-minute self-paced treadmill run in a laboratory context. Situational motivation for running, pre- and post-running positive affect, and RPE were assessed via validated self-report questionnaires. Hierarchical regression analyses revealed a significant interaction effect between RPE and introjection (P<.05 but not between RPE and identified regulation or intrinsic motivation. At low levels of introjection, the influence of RPE on the change in positive affect was considerable, with higher RPE ratings being associated with greater increases in positive affect. The implications of the findings in light of SDT principles as well as the potential contingencies between the regulations and RPE in predicting positive affect among women are discussed.

  12. Situational motivation and perceived intensity: their interaction in predicting changes in positive affect from physical activity.

    Science.gov (United States)

    Guérin, Eva; Fortier, Michelle S

    2012-01-01

    There is evidence that affective experiences surrounding physical activity can contribute to the proper self-regulation of an active lifestyle. Motivation toward physical activity, as portrayed by self-determination theory, has been linked to positive affect, as has the intensity of physical activity, especially of a preferred nature. The purpose of this experimental study was to examine the interaction between situational motivation and intensity [i.e., ratings of perceived exertion (RPE)] in predicting changes in positive affect following an acute bout of preferred physical activity, namely, running. Fourty-one female runners engaged in a 30-minute self-paced treadmill run in a laboratory context. Situational motivation for running, pre- and post-running positive affect, and RPE were assessed via validated self-report questionnaires. Hierarchical regression analyses revealed a significant interaction effect between RPE and introjection (P positive affect was considerable, with higher RPE ratings being associated with greater increases in positive affect. The implications of the findings in light of SDT principles as well as the potential contingencies between the regulations and RPE in predicting positive affect among women are discussed.

  13. ELMO model predicts the price of electric power

    International Nuclear Information System (INIS)

    Antila, H.

    2001-01-01

    Electrowatt-Ekono has developed a new model, by which it is possible to make long-term prognoses on the development of electricity prices in the Nordic Countries. The ELMO model can be used as an analysis service of the electricity markets and estimation of the profitability of long-term power distribution contracts with different scenarios. It can also be applied for calculation of technical and economical fundamentals for new power plants, and for estimation of the effects of different taxation models on the emissions of power generation. The model describes the whole power generation system, the power and heat consumption and transmission. The Finnish power generation system is based on the Electrowatt-Ekono's boiler database by combining different data elements. Calculation is based on the assumption that the Nordic power generation system is used optimally, and that the production costs are minimised. In practise the effectively operated electricity markets ensure the optimal use of the production system. The market area to be described consists of Finland and Sweden. The spot prices have long been the same. Norway has been treated as a separate market area. The most potential power generation system, the power consumption and the power transmission system are presumed for the target year during a normal rainfall situation. The basic scenario is calculated on the basis of the preconditional data. The calculation is carried out on hourly basis, which enables the estimation of the price variation of electric power between different times during the day and seasons. The system optimises the power generation on the basis of electricity and heat consumption curves and fuel prices. The result is an hourly limit price for electric power. Estimates are presented as standard form reports. Prices are presented as average annuals, in the seasonal base, and in hourly or daily basis for different seasons

  14. Integrating the ICF with positive psychology: Factors predicting role participation for mothers with multiple sclerosis.

    Science.gov (United States)

    Farber, Ruth S; Kern, Margaret L; Brusilovsky, Eugene

    2015-05-01

    Being a mother has become a realizable life role for women with disabilities and chronic illnesses, including multiple sclerosis (MS). Identifying psychosocial factors that facilitate participation in important life roles-including motherhood-is essential to help women have fuller lives despite the challenge of their illness. By integrating the International Classification of Functioning, Disability, and Health (ICF) and a positive psychology perspective, this study examined how environmental social factors and positive personal factors contribute to daily role participation and satisfaction with parental participation. One hundred and 11 community-dwelling mothers with MS completed Ryff's Psychological Well-Being Scales, the Medical Outcome Study Social Support Survey, the Short Form-36, and the Parental Participation Scale. Hierarchical regression analyses examined associations between social support and positive personal factors (environmental mastery, self-acceptance, purpose in life) with daily role participation (physical and emotional) and satisfaction with parental participation. One-way ANOVAs tested synergistic combinations of social support and positive personal factors. Social support predicted daily role participation (fewer limitations) and greater satisfaction with parental participation. Positive personal factors contributed additional unique variance. Positive personal factors and social support synergistically predicted better function and greater satisfaction than either alone. Integrating components of the ICF and positive psychology provides a useful model for understanding how mothers with MS can thrive despite challenge or impairment. Both positive personal factors and environmental social factors were important contributors to positive role functioning. Incorporating these paradigms into treatment may help mothers with MS participate more fully in meaningful life roles. (c) 2015 APA, all rights reserved).

  15. Positive Skin Test or Specific IgE to Penicillin Does Not Reliably Predict Penicillin Allergy

    DEFF Research Database (Denmark)

    Tannert, Line Kring; Mørtz, Charlotte G; Skov, Per Stahl

    2017-01-01

    INTRODUCTION: According to guidelines, patients are diagnosed with penicillin allergy if skin test (ST) result or specific IgE (s-IgE) to penicillin is positive. However, the true sensitivity and specificity of these tests are presently not known. OBJECTIVE: To investigate the clinical relevance...... of a positive ST result and positive s-IgE and to study the reproducibility of ST and s-IgE. METHODS: A sample of convenience of 25 patients with positive penicillin ST results, antipenicillin s-IgE results, or both was challenged with their culprit penicillin. Further 19 patients were not challenged......-IgE measured (T0), and then skin tested and had s-IgE measured 4 weeks later (T1). RESULTS: Only 9 (36%) of 25 were challenge positive. There was an increased probability of being penicillin allergic if both ST result and s-IgE were positive at T0. Positive ST result or positive s-IgE alone did not predict...

  16. Suspicion of Motives Predicts Minorities' Responses to Positive Feedback in Interracial Interactions.

    Science.gov (United States)

    Major, Brenda; Kunstman, Jonathan W; Malta, Brenna D; Sawyer, Pamela J; Townsend, Sarah S M; Mendes, Wendy Berry

    2016-01-01

    Strong social and legal norms in the United States discourage the overt expression of bias against ethnic and racial minorities, increasing the attributional ambiguity of Whites' positive behavior to ethnic minorities. Minorities who suspect that Whites' positive overtures toward minorities are motivated more by their fear of appearing racist than by egalitarian attitudes may regard positive feedback they receive from Whites as disingenuous. This may lead them to react to such feedback with feelings of uncertainty and threat. Three studies examined how suspicion of motives relates to ethnic minorities' responses to receiving positive feedback from a White peer or same-ethnicity peer (Experiment 1), to receiving feedback from a White peer that was positive or negative (Experiment 2), and to receiving positive feedback from a White peer who did or did not know their ethnicity (Experiment 3). As predicted, the more suspicious Latinas were of Whites' motives for behaving positively toward minorities in general, the more they regarded positive feedback from a White peer who knew their ethnicity as disingenuous and the more they reacted with cardiovascular reactivity characteristic of threat/avoidance, increased feelings of stress, heightened uncertainty, and decreased self-esteem. We discuss the implications for intergroup interactions of perceptions of Whites' motives for nonprejudiced behavior.

  17. Suspicion of Motives Predicts Minorities’ Responses to Positive Feedback in Interracial Interactions

    Science.gov (United States)

    Major, Brenda; Kunstman, Jonathan W.; Malta, Brenna D.; Sawyer, Pamela J.; Townsend, Sarah S. M.; Mendes, Wendy Berry

    2015-01-01

    Strong social and legal norms in the United States discourage the overt expression of bias against ethnic and racial minorities, increasing the attributional ambiguity of Whites’ positive behavior to ethnic minorities. Minorities who suspect that Whites’ positive overtures toward minorities are motivated more by their fear of appearing racist than by egalitarian attitudes may regard positive feedback they receive from Whites as disingenuous. This may lead them to react to such feedback with feelings of uncertainty and threat. Three studies examined how suspicion of motives relates to ethnic minorities’ responses to receiving positive feedback from a White peer or same-ethnicity peer (Experiment 1), to receiving feedback from a White peer that was positive or negative (Experiment 2), and to receiving positive feedback from a White peer who did or did not know their ethnicity (Experiment 3). As predicted, the more suspicious Latinas were of Whites’ motives for behaving positively toward minorities in general, the more they regarded positive feedback from a White peer who knew their ethnicity as disingenuous and the more they reacted with cardiovascular reactivity characteristic of threat/avoidance, increased feelings of stress, heightened uncertainty, and decreased self-esteem. We discuss the implications for intergroup interactions of perceptions of Whites’ motives for nonprejudiced behavior. PMID:26688594

  18. Job analysis of the electrician position for the nuclear power plant maintenance personnel reliability model

    International Nuclear Information System (INIS)

    Federman, P.J.; Bartter, W.D.; Siegel, A.I.

    1984-02-01

    This report presents the methods, procedures, and results of the fourth and final of a series of job analytic studies which characterize maintenance positions in nuclear power plants. The electrician position is the subject of the present report. The characterization of the electrician position takes the form of detailed information about: (1) the frequency of performing various tasks, (2) the time required for performing each task, (3) the training required for adequate performance of each task, and (4) the perceived consequences resulting from inadequate task performance. Additionally, information is presented about the intellective and the perceptual-motor loading imposed by each task. This information contributes to job design and training requirements derivation as well as to the assessment of human performance reliability in nuclear power plants

  19. Study of eddy current power loss from outer-winding coils of a magnetic position sensor

    International Nuclear Information System (INIS)

    Liu, C.-P.; Lin, T.-K.; Chang, Y.-H.; Yu, C.-S.; Wu, K.-T.; Wang, S.-J.; Ying, T.-F.; Huang, D.-R.

    2000-01-01

    The present analysis is concerned with eddy current power loss of a magnetic position sensor, which arises from a non-uniform flux linkage distribution between magnetic material and position sensor. In the paper, a magnetic position sensor system is simplified to be an outer-winding coil along the axial direction of a low carbon steel bar, and developed a numerical model to compute the electrical characteristics by an excited current source. According to the simulated and measured data in this proposed model from 2.52 to 11.37 Oes, eddy current power losses of conducting material have a variation of 6.1% and 9.77%, respectively. Finally, the phases of waveform of the induced output voltage will also be obtained in the conducting material, and have a variation of 3.68% obtained by using the current source in the proposed model

  20. Study of eddy current power loss from outer-winding coils of a magnetic position sensor

    CERN Document Server

    Liu, C P; Chang, Y H; Yu, C S; Wu, K T; Wang, S J; Ying, T F; Huang, D R

    2000-01-01

    The present analysis is concerned with eddy current power loss of a magnetic position sensor, which arises from a non-uniform flux linkage distribution between magnetic material and position sensor. In the paper, a magnetic position sensor system is simplified to be an outer-winding coil along the axial direction of a low carbon steel bar, and developed a numerical model to compute the electrical characteristics by an excited current source. According to the simulated and measured data in this proposed model from 2.52 to 11.37 Oes, eddy current power losses of conducting material have a variation of 6.1% and 9.77%, respectively. Finally, the phases of waveform of the induced output voltage will also be obtained in the conducting material, and have a variation of 3.68% obtained by using the current source in the proposed model.

  1. Positive thinking about the future in newspaper reports and presidential addresses predicts economic downturn.

    Science.gov (United States)

    Sevincer, A Timur; Wagner, Greta; Kalvelage, Johanna; Oettingen, Gabriele

    2014-04-01

    Previous research has shown that positive thinking, in the form of fantasies about an idealized future, predicts low effort and poor performance. In the studies reported here, we used computerized content analysis of historical documents to investigate the relation between positive thinking about the future and economic development. During the financial crisis from 2007 to 2009, the more weekly newspaper articles in the economy page of USA Today contained positive thinking about the future, the more the Dow Jones Industrial Average declined in the subsequent week and 1 month later. In addition, between the New Deal era and the present time, the more presidential inaugural addresses contained positive thinking about the future, the more the gross domestic product and the employment rate declined in the presidents' subsequent tenures. These counterintuitive findings may help reveal the psychological processes that contribute to an economic crisis.

  2. Fuzzy-predictive direct power control implementation of a grid connected photovoltaic system, associated with an active power filter

    International Nuclear Information System (INIS)

    Ouchen, Sabir; Betka, Achour; Abdeddaim, Sabrina; Menadi, Abdelkrim

    2016-01-01

    Highlights: • An implementation on dSPACE 1104 of a double stage grid connected photovoltaic system, associated with an active power filter. • A fuzzy logic controller for maximum power point tracking of photovoltaic generator using a boost converter. • Predictive direct power control almost eliminates the effect of harmonics under a unite power factor. • The robustness of control strategies was examined in different irradiance level conditions. - Abstract: The present paper proposes a real time implementation of an optimal operation of a double stage grid connected photovoltaic system, associated with a shunt active power filter. On the photovoltaic side, a fuzzy logic based maximum power point taking control is proposed to track permanently the optimum point through an adequate tuning of a boost converter regardless the solar irradiance variations; whereas, on the grid side, a model predictive direct power control is applied, to ensure both supplying a part of the load demand with the extracted photovoltaic power, and a compensation of undesirable harmonic contents of the grid current, under a unity power factor operation. The implementation of the control strategies is conducted on a small scale photovoltaic system, controlled via a dSPACE 1104 single card. The obtained experimental results show on one hand, that the proposed Fuzzy logic based maximum power taking point technique provides fast and high performances under different irradiance levels while compared with a sliding mode control, and ensures 1.57% more in efficiency. On the other hand, the predictive power control ensures a flexible settlement of active power amounts exchanges with the grid, under a unity power functioning. Furthermore, the grid current presents a sinusoidal shape with a tolerable total harmonic distortion coefficient 4.71%.

  3. Positive predictive value of abnormal mammographic findings and role of assessment procedures

    International Nuclear Information System (INIS)

    Menna, S.; Marra, V.; Di Virgilio, M.R.; Macchia, G.; Frigerio, A.

    1999-01-01

    To investigate the positive predictive value for cancer of abnormal mammographic findings and the role of assessment, the authors reviewed a series of 962 patients recalled and examined in the first breast screening center of Turin (Italy), out of 18996 women aged 50-59 from 1991 to 1995, within a population-based mammography program. The results of this study confirm the accuracy of mammography in the early detection of breast cancer and the different role of assessment procedures in the various abnormal mammographic findings. The improvement in positive predictive value for screening demonstrates the importance of the learning curve within the screening team. Most of this improvement could be referred to refined diagnostic criteria for calcifications [it

  4. Breast calcifications. A standardized mammographic reporting and data system to improve positive predictive value

    International Nuclear Information System (INIS)

    Perugini, G.; Bonzanini, B.; Valentino, C.

    1999-01-01

    The purpose of this work is to investigate the usefulness of a standardized reporting and data system in improving the positive predictive value of mammography in breast calcifications. Using the Breast Imaging Reporting and Data System lexicon developed by the American College of Radiology, it is defined 5 descriptive categories of breast calcifications and classified diagnostic suspicion of malignancy on a 3-grade scale (low, intermediate and high). Two radiologists reviewed 117 mammographic studies selected from those of the patients submitted to surgical biopsy for mammographically detected calcifications from January 1993 to December 1997, and classified them according to the above criteria. The positive predictive value was calculated for all examinations and for the stratified groups. Defining a standardized system for assessing and describing breast calcifications helps improve the diagnostic accuracy of mammography in clinical practice [it

  5. Performance Feedback Processing Is Positively Biased As Predicted by Attribution Theory.

    Directory of Open Access Journals (Sweden)

    Christoph W Korn

    Full Text Available A considerable literature on attribution theory has shown that healthy individuals exhibit a positivity bias when inferring the causes of evaluative feedback on their performance. They tend to attribute positive feedback internally (e.g., to their own abilities but negative feedback externally (e.g., to environmental factors. However, all empirical demonstrations of this bias suffer from at least one of the three following drawbacks: First, participants directly judge explicit causes for their performance. Second, participants have to imagine events instead of experiencing them. Third, participants assess their performance only after receiving feedback and thus differences in baseline assessments cannot be excluded. It is therefore unclear whether the classically reported positivity bias generalizes to setups without these drawbacks. Here, we aimed at establishing the relevance of attributions for decision-making by showing an attribution-related positivity bias in a decision-making task. We developed a novel task, which allowed us to test how participants changed their evaluations in response to positive and negative feedback about performance. Specifically, we used videos of actors expressing different facial emotional expressions. Participants were first asked to evaluate the actors' credibility in expressing a particular emotion. After this initial rating, participants performed an emotion recognition task and did--or did not--receive feedback on their veridical performance. Finally, participants re-rated the actors' credibility, which provided a measure of how they changed their evaluations after feedback. Attribution theory predicts that participants change their evaluations of the actors' credibility toward the positive after receiving positive performance feedback and toward the negative after negative performance feedback. Our results were in line with this prediction. A control condition without feedback showed that correct or

  6. Performance Feedback Processing Is Positively Biased As Predicted by Attribution Theory.

    Science.gov (United States)

    Korn, Christoph W; Rosenblau, Gabriela; Rodriguez Buritica, Julia M; Heekeren, Hauke R

    2016-01-01

    A considerable literature on attribution theory has shown that healthy individuals exhibit a positivity bias when inferring the causes of evaluative feedback on their performance. They tend to attribute positive feedback internally (e.g., to their own abilities) but negative feedback externally (e.g., to environmental factors). However, all empirical demonstrations of this bias suffer from at least one of the three following drawbacks: First, participants directly judge explicit causes for their performance. Second, participants have to imagine events instead of experiencing them. Third, participants assess their performance only after receiving feedback and thus differences in baseline assessments cannot be excluded. It is therefore unclear whether the classically reported positivity bias generalizes to setups without these drawbacks. Here, we aimed at establishing the relevance of attributions for decision-making by showing an attribution-related positivity bias in a decision-making task. We developed a novel task, which allowed us to test how participants changed their evaluations in response to positive and negative feedback about performance. Specifically, we used videos of actors expressing different facial emotional expressions. Participants were first asked to evaluate the actors' credibility in expressing a particular emotion. After this initial rating, participants performed an emotion recognition task and did--or did not--receive feedback on their veridical performance. Finally, participants re-rated the actors' credibility, which provided a measure of how they changed their evaluations after feedback. Attribution theory predicts that participants change their evaluations of the actors' credibility toward the positive after receiving positive performance feedback and toward the negative after negative performance feedback. Our results were in line with this prediction. A control condition without feedback showed that correct or incorrect performance

  7. Genome-scale detection of positive selection in nine primates predicts human-virus evolutionary conflicts.

    Science.gov (United States)

    van der Lee, Robin; Wiel, Laurens; van Dam, Teunis J P; Huynen, Martijn A

    2017-10-13

    Hotspots of rapid genome evolution hold clues about human adaptation. We present a comparative analysis of nine whole-genome sequenced primates to identify high-confidence targets of positive selection. We find strong statistical evidence for positive selection in 331 protein-coding genes (3%), pinpointing 934 adaptively evolving codons (0.014%). Our new procedure is stringent and reveals substantial artefacts (20% of initial predictions) that have inflated previous estimates. The final 331 positively selected genes (PSG) are strongly enriched for innate and adaptive immunity, secreted and cell membrane proteins (e.g. pattern recognition, complement, cytokines, immune receptors, MHC, Siglecs). We also find evidence for positive selection in reproduction and chromosome segregation (e.g. centromere-associated CENPO, CENPT), apolipoproteins, smell/taste receptors and mitochondrial proteins. Focusing on the virus-host interaction, we retrieve most evolutionary conflicts known to influence antiviral activity (e.g. TRIM5, MAVS, SAMHD1, tetherin) and predict 70 novel cases through integration with virus-human interaction data. Protein structure analysis further identifies positive selection in the interaction interfaces between viruses and their cellular receptors (CD4-HIV; CD46-measles, adenoviruses; CD55-picornaviruses). Finally, primate PSG consistently show high sequence variation in human exomes, suggesting ongoing evolution. Our curated dataset of positive selection is a rich source for studying the genetics underlying human (antiviral) phenotypes. Procedures and data are available at https://github.com/robinvanderlee/positive-selection. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  8. The positioning of Iberdrola Ingenieria y Construccion in the market for new electric power plants

    International Nuclear Information System (INIS)

    Garnica, E.; Cubain, B.; Chimeno, M. A.; Ortego, A.

    2009-01-01

    IBERDROLA Ingeneria y Contruccion carrying out a wide plant of activities oriented to position the company in the emerging marketplace of new nuclear power plants whose expectation for the next years is highly promising. Obviously, the plan is focused in their technicians, which include people that are very knowledgeable and others younger, both strongly committed with the managerial project. During the las years, the gained experience in nuclear projects, together with other successfully generation projects (combined cycles gas turbine and renewable) allow warranty the success in the challenge of building new nuclear power plants for the next years. (Author)

  9. Short-term wind power prediction based on LSSVM–GSA model

    International Nuclear Information System (INIS)

    Yuan, Xiaohui; Chen, Chen; Yuan, Yanbin; Huang, Yuehua; Tan, Qingxiong

    2015-01-01

    Highlights: • A hybrid model is developed for short-term wind power prediction. • The model is based on LSSVM and gravitational search algorithm. • Gravitational search algorithm is used to optimize parameters of LSSVM. • Effect of different kernel function of LSSVM on wind power prediction is discussed. • Comparative studies show that prediction accuracy of wind power is improved. - Abstract: Wind power forecasting can improve the economical and technical integration of wind energy into the existing electricity grid. Due to its intermittency and randomness, it is hard to forecast wind power accurately. For the purpose of utilizing wind power to the utmost extent, it is very important to make an accurate prediction of the output power of a wind farm under the premise of guaranteeing the security and the stability of the operation of the power system. In this paper, a hybrid model (LSSVM–GSA) based on the least squares support vector machine (LSSVM) and gravitational search algorithm (GSA) is proposed to forecast the short-term wind power. As the kernel function and the related parameters of the LSSVM have a great influence on the performance of the prediction model, the paper establishes LSSVM model based on different kernel functions for short-term wind power prediction. And then an optimal kernel function is determined and the parameters of the LSSVM model are optimized by using GSA. Compared with the Back Propagation (BP) neural network and support vector machine (SVM) model, the simulation results show that the hybrid LSSVM–GSA model based on exponential radial basis kernel function and GSA has higher accuracy for short-term wind power prediction. Therefore, the proposed LSSVM–GSA is a better model for short-term wind power prediction

  10. Incremental validity of positive and negative valence in predicting personality disorder.

    Science.gov (United States)

    Simms, Leonard J; Yufik, Tom; Gros, Daniel F

    2010-04-01

    The Big Seven model of personality includes five dimensions similar to the Big Five model as well as two evaluative dimensions—Positive Valence (PV) and Negative Valence (NV)—which reflect extremely positive and negative person descriptors, respectively. Recent theory and research have suggested that PV and NV predict significant variance in personality disorder (PD) above that predicted by the Big Five, but firm conclusions have not been possible because previous studies have been limited to only single measures of PV, NV, and the Big Five traits. In the present study, we replicated and extended previous findings using three markers of all key constructs—including PV, NV, and the Big Five—in a diverse sample of 338 undergraduates. Results of hierarchical multiple regression analyses revealed that PV incrementally predicted Narcissistic and Histrionic PDs above the Big Five and that NV nonspecifically incremented the prediction of most PDs. Implications for dimensional models of personality pathology are discussed. PsycINFO Database Record (c) 2010 APA, all rights reserved.

  11. Stochastic Short-term High-resolution Prediction of Solar Irradiance and Photovoltaic Power Output

    Energy Technology Data Exchange (ETDEWEB)

    Melin, Alexander M. [ORNL; Olama, Mohammed M. [ORNL; Dong, Jin [ORNL; Djouadi, Seddik M. [ORNL; Zhang, Yichen [University of Tennessee, Knoxville (UTK), Department of Electrical Engineering and Computer Science

    2017-09-01

    The increased penetration of solar photovoltaic (PV) energy sources into electric grids has increased the need for accurate modeling and prediction of solar irradiance and power production. Existing modeling and prediction techniques focus on long-term low-resolution prediction over minutes to years. This paper examines the stochastic modeling and short-term high-resolution prediction of solar irradiance and PV power output. We propose a stochastic state-space model to characterize the behaviors of solar irradiance and PV power output. This prediction model is suitable for the development of optimal power controllers for PV sources. A filter-based expectation-maximization and Kalman filtering mechanism is employed to estimate the parameters and states in the state-space model. The mechanism results in a finite dimensional filter which only uses the first and second order statistics. The structure of the scheme contributes to a direct prediction of the solar irradiance and PV power output without any linearization process or simplifying assumptions of the signal’s model. This enables the system to accurately predict small as well as large fluctuations of the solar signals. The mechanism is recursive allowing the solar irradiance and PV power to be predicted online from measurements. The mechanism is tested using solar irradiance and PV power measurement data collected locally in our lab.

  12. Modelling of physical properties - databases, uncertainties and predictive power

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    in the estimated/predicted property values, how to assess the quality and reliability of the estimated/predicted property values? The paper will review a class of models for prediction of physical and thermodynamic properties of organic chemicals and their mixtures based on the combined group contribution – atom......Physical and thermodynamic property in the form of raw data or estimated values for pure compounds and mixtures are important pre-requisites for performing tasks such as, process design, simulation and optimization; computer aided molecular/mixture (product) design; and, product-process analysis...

  13. Reactive Power Impact on Lifetime Prediction of Two-level Wind Power Converter

    DEFF Research Database (Denmark)

    Zhou, Dao; Blaabjerg, Frede; Lau, M.

    2013-01-01

    The influence of reactive power injection on the dominating two-level wind power converter is investigated and compared in terms of power loss and thermal behavior. Then the lifetime of both the partial-scale and full-scale power converter is estimated based on the widely used Coffin-Manson model...

  14. Optimization of maintenance for power system equipment using a predictive health model

    NARCIS (Netherlands)

    Bajracharya, G.; Koltunowicz, T.; Negenborn, R.R.; Papp, Z.; Djairam, D.; Schutter, B.D. de; Smit, J.J.

    2009-01-01

    In this paper, a model-predictive control based framework is proposed for modeling and optimization of the health state of power system equipment. In the framework, a predictive health model is proposed that predicts the health state of the equipment based on its usage and maintenance actions. Based

  15. Adaptability and Prediction of Anticipatory Muscular Activity Parameters to Different Movements in the Sitting Position.

    Science.gov (United States)

    Chikh, Soufien; Watelain, Eric; Faupin, Arnaud; Pinti, Antonio; Jarraya, Mohamed; Garnier, Cyril

    2016-08-01

    Voluntary movement often causes postural perturbation that requires an anticipatory postural adjustment to minimize perturbation and increase the efficiency and coordination during execution. This systematic review focuses specifically on the relationship between the parameters of anticipatory muscular activities and movement finality in sitting position among adults, to study the adaptability and predictability of anticipatory muscular activities parameters to different movements and conditions in sitting position in adults. A systematic literature search was performed using PubMed, Science Direct, Web of Science, Springer-Link, Engineering Village, and EbscoHost. Inclusion and exclusion criteria were applied to retain the most rigorous and specific studies, yielding 76 articles, Seventeen articles were excluded at first reading, and after the application of inclusion and exclusion criteria, 23 were retained. In a sitting position, central nervous system activity precedes movement by diverse anticipatory muscular activities and shows the ability to adapt anticipatory muscular activity parameters to the movement direction, postural stability, or charge weight. In addition, these parameters could be adapted to the speed of execution, as found for the standing position. Parameters of anticipatory muscular activities (duration, order, and amplitude of muscle contractions constituting the anticipatory muscular activity) could be used as a predictive indicator of forthcoming movement. In addition, this systematic review may improve methodology in empirical studies and assistive technology for people with disabilities. © The Author(s) 2016.

  16. Position of nuclear power generation in the public and further enhancement of safe and stable operation

    International Nuclear Information System (INIS)

    Miyazaki, Yozo

    1996-01-01

    In Japan, the first commercial light water reactor (LWR) started operation in 1970 when the International Exposition was held in Osaka, and now 50 nuclear power plants supply about 30 % of the total electricity and nuclear power plays the important role as a 'major power source'. Meanwhile, with the international transportation of plutonium and return shipment of vitrified HLW reprocessed abroad, nuclear power has closer relationship with the public in these days. We will review the history of nuclear power generation in Japan from the viewpoint of the safety culture and consider the safety culture under the present situation. The team of 'safety Charlotte's fixed its position since the occurrence of Chernobyl accident though the concept existed as expressed in words such as 'safety-first principle' and 'enhancement of morale'. The safety culture is a concept: high level 'safety Culture' cab be expected when 'the management of the organization' and 'individual consciousness concerning safety' are well balanced. The 'safety culture' has experienced various changes along with the development of nuclear power in Japan: at the initial period of the development, the management side invested excellent talents and funds to the nuclear division based on the 'safety-first principle' from the beginning. At the same time, the world of atom filled with dream appealed to those who had enthusiasm as pioneers and they were engaged in the development with enhanced morale

  17. Classical fluoroscopy criteria poorly predict right ventricular lead septal positioning by comparison with echocardiography.

    Science.gov (United States)

    Squara, Fabien; Scarlatti, Didier; Riccini, Philippe; Garret, Gauthier; Moceri, Pamela; Ferrari, Emile

    2018-03-13

    Fluoroscopic criteria have been described for the documentation of septal right ventricular (RV) lead positioning, but their accuracy remains questioned. Consecutive patients undergoing pacemaker or defibrillator implantation were prospectively included. RV lead was positioned using postero-anterior and left anterior oblique 40° incidences, and right anterior oblique 30° to rule out coronary sinus positioning when suspected. RV lead positioning using fluoroscopy was compared to true RV lead positioning as assessed by transthoracic echocardiography (TTE). Precise anatomical localizations were determined with both modalities; then, RV lead positioning was ultimately dichotomized into two simple clinically relevant categories: RV septal or RV free wall. Accuracy of fluoroscopy for RV lead positioning was then assessed by comparison with TTE. We included 100 patients. On TTE, 66/100 had a septal RV lead and 34/100 had a free wall RV lead. Fluoroscopy had moderate agreement with TTE for precise anatomical localization of RV lead (k = 0.53), and poor agreement for septal/free wall localization (k = 0.36). For predicting septal RV lead positioning, classical fluoroscopy criteria had a high sensitivity (95.5%; 63/66 patients having a septal RV lead on TTE were correctly identified by fluoroscopy) but a very low specificity (35.3%; only 12/34 patients having a free wall RV lead on TTE were correctly identified by fluoroscopy). Classical fluoroscopy criteria have a poor accuracy for identifying RV free wall leads, which are most of the time misclassified as septal. This raises important concerns about the efficacy and safety of RV lead positioning using classical fluoroscopy criteria.

  18. Sludge pipe flow pressure drop prediction using composite power ...

    African Journals Online (AJOL)

    2011-09-30

    Sep 30, 2011 ... 3Department of Chemical Engineering, IIT Kanpur, India. Abstract. When predicting pressure gradients for the flow of sludges in pipes, the rheology of the fluid ..... implicit in the stability analysis of Ryan and Johnson (1959).

  19. Fuzzy model predictive control algorithm applied in nuclear power plant

    International Nuclear Information System (INIS)

    Zuheir, Ahmad

    2006-01-01

    The aim of this paper is to design a predictive controller based on a fuzzy model. The Takagi-Sugeno fuzzy model with an Adaptive B-splines neuro-fuzzy implementation is used and incorporated as a predictor in a predictive controller. An optimization approach with a simplified gradient technique is used to calculate predictions of the future control actions. In this approach, adaptation of the fuzzy model using dynamic process information is carried out to build the predictive controller. The easy description of the fuzzy model and the easy computation of the gradient sector during the optimization procedure are the main advantages of the computation algorithm. The algorithm is applied to the control of a U-tube steam generation unit (UTSG) used for electricity generation. (author)

  20. Upgrading to lead firm position via international acquisition: learning from the global biomass power plant industry

    DEFF Research Database (Denmark)

    Hansen, Ulrich Elmer; Fold, Niels; Hansen, Teis

    2016-01-01

    This article examines the case of a Chinese firm that has upgraded to lead firm position in the global biomass power plant industry mainly through acquisitions of technological frontier firms in Denmark. Sustaining the lead firm position was, however, challenged by difficulties in developing...... innovative capability. Drawing on the literature on (i) firm-level technological capability and (ii) knowledge transfer in international acquisitions, we explain the reasons for insufficient innovative capability building. Based on these empirical findings, we suggest maintaining the existing upgrading...

  1. nuMap: a web platform for accurate prediction of nucleosome positioning.

    Science.gov (United States)

    Alharbi, Bader A; Alshammari, Thamir H; Felton, Nathan L; Zhurkin, Victor B; Cui, Feng

    2014-10-01

    Nucleosome positioning is critical for gene expression and of major biological interest. The high cost of experimentally mapping nucleosomal arrangement signifies the need for computational approaches to predict nucleosome positions at high resolution. Here, we present a web-based application to fulfill this need by implementing two models, YR and W/S schemes, for the translational and rotational positioning of nucleosomes, respectively. Our methods are based on sequence-dependent anisotropic bending that dictates how DNA is wrapped around a histone octamer. This application allows users to specify a number of options such as schemes and parameters for threading calculation and provides multiple layout formats. The nuMap is implemented in Java/Perl/MySQL and is freely available for public use at http://numap.rit.edu. The user manual, implementation notes, description of the methodology and examples are available at the site. Copyright © 2014 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

  2. nuMap: A Web Platform for Accurate Prediction of Nucleosome Positioning

    Directory of Open Access Journals (Sweden)

    Bader A. Alharbi

    2014-10-01

    Full Text Available Nucleosome positioning is critical for gene expression and of major biological interest. The high cost of experimentally mapping nucleosomal arrangement signifies the need for computational approaches to predict nucleosome positions at high resolution. Here, we present a web-based application to fulfill this need by implementing two models, YR and W/S schemes, for the translational and rotational positioning of nucleosomes, respectively. Our methods are based on sequence-dependent anisotropic bending that dictates how DNA is wrapped around a histone octamer. This application allows users to specify a number of options such as schemes and parameters for threading calculation and provides multiple layout formats. The nuMap is implemented in Java/Perl/MySQL and is freely available for public use at http://numap.rit.edu. The user manual, implementation notes, description of the methodology and examples are available at the site.

  3. Predictive IP controller for robust position control of linear servo system.

    Science.gov (United States)

    Lu, Shaowu; Zhou, Fengxing; Ma, Yajie; Tang, Xiaoqi

    2016-07-01

    Position control is a typical application of linear servo system. In this paper, to reduce the system overshoot, an integral plus proportional (IP) controller is used in the position control implementation. To further improve the control performance, a gain-tuning IP controller based on a generalized predictive control (GPC) law is proposed. Firstly, to represent the dynamics of the position loop, a second-order linear model is used and its model parameters are estimated on-line by using a recursive least squares method. Secondly, based on the GPC law, an optimal control sequence is obtained by using receding horizon, then directly supplies the IP controller with the corresponding control parameters in the real operations. Finally, simulation and experimental results are presented to show the efficiency of proposed scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  4. Basic tuning of hydrogen powered car and artificial intelligent prediction of hydrogen engine characteristics

    Energy Technology Data Exchange (ETDEWEB)

    Ho, Tien [School of Engineering, University of Tasmania, GPO Box 252-65, Hobart, Tasmania, 7001 (Australia); Karri, Vishy [Australian College of Kuwait, P.O. Box 1411, Safat 13015 (Kuwait)

    2010-09-15

    Many studies of renewable energy have shown hydrogen is one of the major green energy in the future. This has lead to the development of many automotive application of using hydrogen as a fuel especially in internal combustion engine. Nonetheless, there has been a slow growth and less knowledge details in building up the prototype and control methodology of the hydrogen internal combustion engine. In this paper, The Toyota Corolla 4 cylinder, 1.8l engine running on petrol was systematically modified in such a way that it could be operated on either gasoline or hydrogen at the choice of the driver. Within the scope of this project, several ancillary instruments such as a new inlet manifold, hydrogen fuel injection, storage system and leak detection safety system were implemented. Attention is directed towards special characteristics related to the basic tuning of hydrogen engine such as: air to fuel ratio operating conditions, ignition timing and injection timing in terms of different engine speed and throttle position. Based on the experimental data, a suite of neural network models were tested to accurately predict the effect of different engine operating conditions (speed and throttle position) on the hydrogen powered car engine characteristics. Predictions were found to be {+-}3% to the experimental values for all of case studies. This work provided better understanding of the effect of hydrogen engine characteristic parameters on different engine operating conditions. (author)

  5. Artful Women in Positions of Power: Three Examples from Tirso de Molina

    Directory of Open Access Journals (Sweden)

    David Hildner

    2017-05-01

    Full Text Available The present study examines three plays by Tirso de Molina (Amar por señas, El castigo del penséque and Quien calla otorga in which female protagonists in positions of power (or as relatives of those in power use their authority to confuse and deceive the male protagonists, who is a foreigner in their lands. Their position allows them to go beyond the typical deceptions of Tirso’s intrigue comedies (e. g., Don Gil de las calzas verdes. Concretely, they manage to detain the young man physically, to torment him without revealing their identity and to send ambiguous message that keep the male character in uncertainty. However, they are constrained by their sense of honor and it is implied that, after the traditional wedding that ends these plays, the women will no longer have the authority to continue their manipulation.

  6. A study on the characteristics, predictions and policies of China’s eight main power grids

    International Nuclear Information System (INIS)

    Wang, Jianzhou; Dong, Yao; Jiang, He

    2014-01-01

    Highlights: • Indian blackout is analyzed as a warning for China’s power system. • Issues and recommendations of China’s eight power grids are presented. • Five models are employed for scenario analysis on power generation and consumption. • The optimized combined model outperforms other models. • Methods towards balancing power generation and environmental impacts are proposed. - Abstract: Electricity is an indispensable energy source for modern social and economic development. However, large-scale blackouts can cause incalculable loss to society. In 2012, three major Indian power grids collapsed, resulting in the interruption of the electricity supply to over 600 million people. To avoid an event like that, China needs to forecast the power generation and consumption of eight power grids effectively. This paper first analyzes the characteristics of eight power grids and then proposes a combined model based on three improved grey models optimized by a differential evolution algorithm to predict electricity production and consumption of each power grid. The optimized combined forecasting model provides a better prediction than other models, and it is also the most workable and satisfactory model. Experiment results show electricity production and consumption would increase. In consideration of the real situation and existing problems, some suggestions are proposed. The government could decrease thermal power and exploit renewable energy power, like hydroelectric power, wind power and solar power, to ensure the safe and reliable operation of China’s major power grids and protect environment

  7. Comparison of the Anaerobic Power of Brazilian Professional Football Players Grouped by Tactical Position

    Directory of Open Access Journals (Sweden)

    Renan Renato Cruz dos Santos

    2014-09-01

    Full Text Available Football is characterized as a predominately aerobic modality, however, during a match; the most important actions performed by the players are in short duration and high intensity. In addition, this sport presents to have some particularities, such as, highlights differences of each tactical position. Thus, this study aimed to compare the anaerobic power of professional football players grouped by different tactical positions. Thirty professional football players separated in three groups, goal¬keep¬ers+fullbacks, sideways+DMF (defensive middlefields and OMF (offensive middlefields+forwards, performed two anaerobic po¬wer tests, Running anaerobic sprint test and Sargent jump test Goalkeepers+fullbacks showed higher values of body mass index and absolute anaerobic power (w, using Sargent jump test than the others, but when analyzed the RAST results, this same group presented lower values (p<0.05 of relative AP (w∙kg-1. OMF+forwards showed to have the best Pmed and Pmax values (p<0.05, when compared with defensive players. These results suggest the use of running anaerobic sprint test and sargent jump test toge¬ther when is proposed to measure the anaerobic power of football players, and also a anthropometric evaluation, so the training can be more specific e efficient to each tactical position and athlete.

  8. Employing Tropospheric Numerical Weather Prediction Model for High-Precision GNSS Positioning

    Science.gov (United States)

    Alves, Daniele; Gouveia, Tayna; Abreu, Pedro; Magário, Jackes

    2014-05-01

    In the past few years is increasing the necessity of realizing high accuracy positioning. In this sense, the spatial technologies have being widely used. The GNSS (Global Navigation Satellite System) has revolutionized the geodetic positioning activities. Among the existent methods one can emphasize the Precise Point Positioning (PPP) and network-based positioning. But, to get high accuracy employing these methods, mainly in real time, is indispensable to realize the atmospheric modeling (ionosphere and troposphere) accordingly. Related to troposphere, there are the empirical models (for example Saastamoinen and Hopfield). But when highly accuracy results (error of few centimeters) are desired, maybe these models are not appropriated to the Brazilian reality. In order to minimize this limitation arises the NWP (Numerical Weather Prediction) models. In Brazil the CPTEC/INPE (Center for Weather Prediction and Climate Studies / Brazilian Institute for Spatial Researches) provides a regional NWP model, currently used to produce Zenithal Tropospheric Delay (ZTD) predictions (http://satelite.cptec.inpe.br/zenital/). The actual version, called eta15km model, has a spatial resolution of 15 km and temporal resolution of 3 hours. In this paper the main goal is to accomplish experiments and analysis concerning the use of troposphere NWP model (eta15km model) in PPP and network-based positioning. Concerning PPP it was used data from dozens of stations over the Brazilian territory, including Amazon forest. The results obtained with NWP model were compared with Hopfield one. NWP model presented the best results in all experiments. Related to network-based positioning it was used data from GNSS/SP Network in São Paulo State, Brazil. This network presents the best configuration in the country to realize this kind of positioning. Actually the network is composed by twenty stations (http://www.fct.unesp.br/#!/pesquisa/grupos-de-estudo-e-pesquisa/gege//gnss-sp-network2789/). The

  9. Reduction of wind power induced reserve requirements by advanced shortest-term forecasts and prediction intervals

    Energy Technology Data Exchange (ETDEWEB)

    Dobschinski, Jan; Wessel, Arne; Lange, Bernhard; Bremen, Lueder von [Fraunhofer Institut fuer Windenergie und Energiesystemtechnik (IWES), Kassel (Germany)

    2009-07-01

    In electricity systems with large penetration of wind power, the limited predictability of the wind power generation leads to an increase in reserve and balancing requirements. At first the present study concentrates on the capability of dynamic day-ahead prediction intervals to reduce the wind power induced reserve and balancing requirements. Alternatively the reduction of large forecast errors of the German wind power generation by using advanced shortest-term predictions has been evaluated in a second approach. With focus on the allocation of minute reserve power the aim is to estimate the maximal remaining uncertainty after trading activities on the intraday market. Finally both approaches were used in a case study concerning the reserve requirements induced by the total German wind power expansion in 2007. (orig.)

  10. Communal and Agentic Interpersonal and Intergroup Motives Predict Preferences for Status Versus Power.

    Science.gov (United States)

    Locke, Kenneth D; Heller, Sonja

    2017-01-01

    Seven studies involving 1,343 participants showed how circumplex models of social motives can help explain individual differences in preferences for status (having others' admiration) versus power (controlling valuable resources). Studies 1 to 3 and 7 concerned interpersonal motives in workplace contexts, and found that stronger communal motives (to have mutual trust, support, and cooperation) predicted being more attracted to status (but not power) and achieving more workplace status, while stronger agentic motives (to be firm, decisive, and influential) predicted being more attracted to and achieving more workplace power, and experiencing a stronger connection between workplace power and job satisfaction. Studies 4 to 6 found similar effects for intergroup motives: Stronger communal motives predicted wanting one's ingroup (e.g., country) to have status-but not power-relative to other groups. Finally, most people preferred status over power, and this was especially true for women, which was partially explained by women having stronger communal motives.

  11. Lifetime prediction of high-power press-pack IGBTs in wind power applications

    DEFF Research Database (Denmark)

    Busca, Cristian

    The Wind Turbine (WT) industry is advancing at a rapid pace and the power rating of new WTs is continuously growing. The next generation large WTs are likely to be realized with full-scale power converters due to the advantages they offer in terms of grid code compliance, power density and decoup......The Wind Turbine (WT) industry is advancing at a rapid pace and the power rating of new WTs is continuously growing. The next generation large WTs are likely to be realized with full-scale power converters due to the advantages they offer in terms of grid code compliance, power density...... and decoupling of the generator and grid sides. Press-Pack (PP) Insulated Gate Bipolar Transistors (IGBTs) are promising semiconductor devices for the next generation large WTs due to the advantages they offer in terms of power capability, power density and thermal cycling capability. PP IGBTs require proper...

  12. Power shifts track serial position and modulate encoding in human episodic memory.

    Science.gov (United States)

    Serruya, Mijail D; Sederberg, Per B; Kahana, Michael J

    2014-02-01

    The first events in a series exert a powerful influence on cognition and behavior in both humans and animals. This is known as the law of primacy. Here, we analyze the neural correlates of primacy in humans by analyzing electrocorticographic recordings in 84 neurosurgical patients as they studied and subsequently recalled lists of common words. We found that spectral power in the gamma frequency band (28-100 Hz) was elevated at the start of the list and gradually subsided, whereas lower frequency (2-8 Hz) delta and theta band power exhibited the opposite trend. This gradual shift in the power spectrum was found across a widespread network of brain regions. The degree to which the subsequent memory effect was modulated by list (serial) position was most pronounced in medial temporal lobe structures. These results suggest that globally increased gamma and decreased delta-theta spectral powers reflect a brain state that predisposes medial temporal lobe structures to enhance the encoding and maintenance of early list items.

  13. Power maximization of a point absorber wave energy converter using improved model predictive control

    Science.gov (United States)

    Milani, Farideh; Moghaddam, Reihaneh Kardehi

    2017-08-01

    This paper considers controlling and maximizing the absorbed power of wave energy converters for irregular waves. With respect to physical constraints of the system, a model predictive control is applied. Irregular waves' behavior is predicted by Kalman filter method. Owing to the great influence of controller parameters on the absorbed power, these parameters are optimized by imperialist competitive algorithm. The results illustrate the method's efficiency in maximizing the extracted power in the presence of unknown excitation force which should be predicted by Kalman filter.

  14. Prediction on corrosion rate of pipe in nuclear power system based on optimized grey theory

    International Nuclear Information System (INIS)

    Chen Yonghong; Zhang Dafa; Chen Dengke; Jiang Wei

    2007-01-01

    For the prediction of corrosion rate of pipe in nuclear power system, the pre- diction error from the grey theory is greater, so a new method, optimized grey theory was presented in the paper. A comparison among predicted results from present and other methods was carried out, and it is seem that optimized grey theory is correct and effective for the prediction of corrosion rate of pipe in nuclear power system, and it provides a fundamental basis for the maintenance of pipe in nuclear power system. (authors)

  15. Disentangling evolutionary signals: conservation, specificity determining positions and coevolution. Implication for catalytic residue prediction

    DEFF Research Database (Denmark)

    Teppa, Elin; Wilkins, Angela D.; Nielsen, Morten

    2012-01-01

    Background: A large panel of methods exists that aim to identify residues with critical impact on protein function based on evolutionary signals, sequence and structure information. However, it is not clear to what extent these different methods overlap, and if any of the methods have higher...... predictive potential compared to others when it comes to, in particular, the identification of catalytic residues (CR) in proteins. Using a large set of enzymatic protein families and measures based on different evolutionary signals, we sought to break up the different components of the information content......-value Evolutionary Trace (rvET) methods and conservation, another containing mutual information (MI) methods, and the last containing methods designed explicitly for the identification of specificity determining positions (SDPs): integer-value Evolutionary Trace (ivET), SDPfox, and XDET. In terms of prediction of CR...

  16. Positive Predictive Value of BI-RADS Categorization in an Asian Population

    Directory of Open Access Journals (Sweden)

    Yah-Yuen Tan

    2004-07-01

    Full Text Available The Breast Imaging Reporting And Data System (BI-RADS categorization of mammograms is useful in estimating the risk of malignancy, thereby guiding management decisions. However, in Asian women, in whom breast density is increased, the sensitivity of mammography is correspondingly lower. We sought to determine the positive predictive value of BI-RADS categorization for malignancy in our Asian population and, hence, its value in helping us to choose between the various modalities for breast biopsy. We retrospectively reviewed all patients with occult breast lesions detected on mammography or ultrasound who underwent needle-localization open breast biopsy (NLOB in our institution over a 6-year period. There were 470 biopsies in 427 patients; 16% of lesions were malignant. The positive predictive value of BI-RADS 4 and 5 lesions for cancer was 0.27 and 0.84, respectively. While most BI-RADS 5 mass lesions were invasive cancers, the majority of calcifications in this category were in situ carcinomas. We conclude that BI-RADS remains useful in aiding decision-making for biopsy in our Asian population. Based on positive predictive values, we recommend percutaneous breast biopsy for initial evaluation of lesions categorized as BI-RADS 4 or less. For BI-RADS 5 lesions with microcalcifications, open surgical biopsy as a diagnostic and therapeutic procedure may be more appropriate. In the case of a BI-RADS 5 lesion associated with a mass, initial percutaneous biopsy may be useful for diagnosis, followed by a planned single-stage surgical procedure as necessary.

  17. Basic study on dynamic reactive-power control method with PV output prediction for solar inverter

    Directory of Open Access Journals (Sweden)

    Ryunosuke Miyoshi

    2016-01-01

    Full Text Available To effectively utilize a photovoltaic (PV system, reactive-power control methods for solar inverters have been considered. Among the various methods, the constant-voltage control outputs less reactive power compared with the other methods. We have developed a constant-voltage control to reduce the reactive-power output. However, the developed constant-voltage control still outputs unnecessary reactive power because the control parameter is constant in every waveform of the PV output. To reduce the reactive-power output, we propose a dynamic reactive-power control method with a PV output prediction. In the proposed method, the control parameter is varied according to the properties of the predicted PV waveform. In this study, we performed numerical simulations using a distribution system model, and we confirmed that the proposed method reduces the reactive-power output within the voltage constraint.

  18. Predicting uptake of continuous positive airway pressure (CPAP) therapy in obstructive sleep apnoea (OSA)

    DEFF Research Database (Denmark)

    Skinner, Timothy; McNeil, Lindsay; Olaithe, Michelle

    2013-01-01

    diagnosed with OSA. Epworth sleepiness scale (ESS), Fatigue Severity Scale, Depression Anxiety Stress Scale and Illness Perception Questionnaire-Revised (IPQ-R) were administered at time of sleep study. These, patient demographics and sleep study variables were used to determine factors predicting patient......Purpose: Obstructive sleep apnoea (OSA) is a common disorder, for which continuous positive airway pressure (CPAP) therapy is a standard treatment. Despite its well-established efficacy, many patients choose not to initiate CPAP treatment. The present study investigated the degree to which...

  19. Reality television predicts both positive and negative outcomes for adolescent girls.

    Science.gov (United States)

    Ferguson, Christopher J; Salmond, Kimberlee; Modi, Kamla

    2013-06-01

    To assess the influence of media, specifically reality television, on adolescent behavior. A total of 1141 preteen and adolescent girls (age range 11-17) answered questions related to their reality television viewing, personality, self-esteem, relational aggression, appearance focus, and desire for fame. Our results indicated that the influence of reality television on adolescent behavior is complex and potentially related to the adolescents' intended uses and gratifications for using reality television. Reality television viewing was positively related to increased self-esteem and expectations of respect in dating relationships. However, watching reality television also was related to an increased focus on appearance and willingness to compromise other values for fame. Reality television viewing did not predict relational aggression. The potential influences of reality television use on adolescent girls are both positive and negative, defying easy categorization. Copyright © 2013 Mosby, Inc. All rights reserved.

  20. Risk score predicts high-grade prostate cancer in DNA-methylation positive, histopathologically negative biopsies.

    Science.gov (United States)

    Van Neste, Leander; Partin, Alan W; Stewart, Grant D; Epstein, Jonathan I; Harrison, David J; Van Criekinge, Wim

    2016-09-01

    Prostate cancer (PCa) diagnosis is challenging because efforts for effective, timely treatment of men with significant cancer typically result in over-diagnosis and repeat biopsies. The presence or absence of epigenetic aberrations, more specifically DNA-methylation of GSTP1, RASSF1, and APC in histopathologically negative prostate core biopsies has resulted in an increased negative predictive value (NPV) of ∼90% and thus could lead to a reduction of unnecessary repeat biopsies. Here, it is investigated whether, in methylation-positive men, DNA-methylation intensities could help to identify those men harboring high-grade (Gleason score ≥7) PCa, resulting in an improved positive predictive value. Two cohorts, consisting of men with histopathologically negative index biopsies, followed by a positive or negative repeat biopsy, were combined. EpiScore, a methylation intensity algorithm was developed in methylation-positive men, using area under the curve of the receiver operating characteristic as metric for performance. Next, a risk score was developed combining EpiScore with traditional clinical risk factors to further improve the identification of high-grade (Gleason Score ≥7) cancer. Compared to other risk factors, detection of DNA-methylation in histopathologically negative biopsies was the most significant and important predictor of high-grade cancer, resulting in a NPV of 96%. In methylation-positive men, EpiScore was significantly higher for those with high-grade cancer detected upon repeat biopsy, compared to those with either no or low-grade cancer. The risk score resulted in further improvement of patient risk stratification and was a significantly better predictor compared to currently used metrics as PSA and the prostate cancer prevention trial (PCPT) risk calculator (RC). A decision curve analysis indicated strong clinical utility for the risk score as decision-making tool for repeat biopsy. Low DNA-methylation levels in PCa-negative biopsies led

  1. What is the Predictive Power of Market Orientation?

    NARCIS (Netherlands)

    F. Langerak (Fred)

    2002-01-01

    textabstractThe majority of studies on market orientation claim that compelling evidence exists that market orientation has a positive effect on business performance. This study takes a closer look at forty studies that have addressed the relationship between market orientation and business

  2. Poor Positive Predictive Value of Lyme Disease Serologic Testing in an Area of Low Disease Incidence.

    Science.gov (United States)

    Lantos, Paul M; Branda, John A; Boggan, Joel C; Chudgar, Saumil M; Wilson, Elizabeth A; Ruffin, Felicia; Fowler, Vance; Auwaerter, Paul G; Nigrovic, Lise E

    2015-11-01

    Lyme disease is diagnosed by 2-tiered serologic testing in patients with a compatible clinical illness, but the significance of positive test results in low-prevalence regions has not been investigated. We reviewed the medical records of patients who tested positive for Lyme disease with standardized 2-tiered serologic testing between 2005 and 2010 at a single hospital system in a region with little endemic Lyme disease. Based on clinical findings, we calculated the positive predictive value of Lyme disease serology. Next, we reviewed the outcome of serologic testing in patients with select clinical syndromes compatible with disseminated Lyme disease (arthritis, cranial neuropathy, or meningitis). During the 6-year study period 4723 patients were tested for Lyme disease, but only 76 (1.6%) had positive results by established laboratory criteria. Among 70 seropositive patients whose medical records were available for review, 12 (17%; 95% confidence interval, 9%-28%) were found to have Lyme disease (6 with documented travel to endemic regions). During the same time period, 297 patients with a clinical illness compatible with disseminated Lyme disease underwent 2-tiered serologic testing. Six of them (2%; 95% confidence interval, 0.7%-4.3%) were seropositive, 3 with documented travel and 1 who had an alternative diagnosis that explained the clinical findings. In this low-prevalence cohort, fewer than 20% of positive Lyme disease tests are obtained from patients with clinically likely Lyme disease. Positive Lyme disease test results may have little diagnostic value in this setting. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  3. Predicting residue contacts using pragmatic correlated mutations method: reducing the false positives

    Directory of Open Access Journals (Sweden)

    Alexov Emil G

    2006-11-01

    Full Text Available Abstract Background Predicting residues' contacts using primary amino acid sequence alone is an important task that can guide 3D structure modeling and can verify the quality of the predicted 3D structures. The correlated mutations (CM method serves as the most promising approach and it has been used to predict amino acids pairs that are distant in the primary sequence but form contacts in the native 3D structure of homologous proteins. Results Here we report a new implementation of the CM method with an added set of selection rules (filters. The parameters of the algorithm were optimized against fifteen high resolution crystal structures with optimization criterion that maximized the confidentiality of the predictions. The optimization resulted in a true positive ratio (TPR of 0.08 for the CM without filters and a TPR of 0.14 for the CM with filters. The protocol was further benchmarked against 65 high resolution structures that were not included in the optimization test. The benchmarking resulted in a TPR of 0.07 for the CM without filters and to a TPR of 0.09 for the CM with filters. Conclusion Thus, the inclusion of selection rules resulted to an overall improvement of 30%. In addition, the pair-wise comparison of TPR for each protein without and with filters resulted in an average improvement of 1.7. The methodology was implemented into a web server http://www.ces.clemson.edu/compbio/recon that is freely available to the public. The purpose of this implementation is to provide the 3D structure predictors with a tool that can help with ranking alternative models by satisfying the largest number of predicted contacts, as well as it can provide a confidence score for contacts in cases where structure is known.

  4. Wireless online position monitoring of manual valve types for plant configuration management in nuclear power plants

    International Nuclear Information System (INIS)

    Agarwal, Vivek; Buttles, John W.; Beaty, Lawrence H.; Naser, Joseph; Hallbert, Bruce P.

    2016-01-01

    In the current competitive energy market, the nuclear industry is committed to lower the operations and maintenance cost; increase productivity and efficiency while maintaining safe and reliable operation. The present operating model of nuclear power plants is dependent on large technical staffs that put the nuclear industry at long-term economic disadvantage. Technology can play a key role in nuclear power plant configuration management in offsetting labor costs by automating manually performed plant activities. The technology being developed, tested, and demonstrated in this paper will enable the continued safe operation of today’s fleet of light water reactors by providing the technical means to monitor components in plants today that are only routinely monitored through manual activities. The wireless enabled valve position indicators that are the subject of this paper are able to provide a valid position indication available continuously, rather than only periodically. As a result, a real-time (online) availability of valve positions using an affordable technologies are vital to plant configuration when compared with long-term labor rates, and provide information that can be used for a variety of plant engineering, maintenance, and management applications.

  5. Development of Bundle Position-Wise Linear Model for Predicting the Pressure Tube Diametral Creep in CANDU Reactors

    International Nuclear Information System (INIS)

    Lee, Jae Yong; Na, Man Gyun

    2011-01-01

    Diametral creep of the pressure tube (PT) is one of the principal aging mechanisms governing the heat transfer and hydraulic degradation of a heat transport system. PT diametral creep leads to diametral expansion that affects the thermal hydraulic characteristics of the coolant channels and the critical heat flux. Therefore, it is essential to predict the PT diametral creep in CANDU reactors, which is caused mainly by fast neutron irradiation, reactor coolant temperature and so forth. The currently used PT diametral creep prediction model considers the complex interactions between the effects of temperature and fast neutron flux on the deformation of PT zirconium alloys. The model assumes that long-term steady-state deformation consists of separable, additive components from thermal creep, irradiation creep and irradiation growth. This is a mechanistic model based on measured data. However, this model has high prediction uncertainty. Recently, a statistical error modeling method was developed using plant inspection data from the Bruce B CANDU reactor. The aim of this study was to develop a bundle position-wise linear model (BPLM) to predict PT diametral creep employing previously measured PT diameters and HTS operating conditions. There are twelve bundles in a fuel channel and for each bundle, a linear model was developed by using the dependent variables, such as the fast neutron fluxes and the bundle temperatures. The training data set was selected using the subtractive clustering method. The data of 39 channels that consist of 80 percent of a total of 49 measured channels from Units 2, 3 and 4 were used to develop the BPLM models. The remaining 10 channels' data were used to test the developed BPLM models. The BPLM was optimized by the maximum likelihood estimation method. The developed BPLM to predict PT diametral creep was verified using the operating data gathered from the Units 2,3 and 4 in Korea. Two error components for the BPLM, which are the epistemic

  6. Nuclear power renaissance in Brazil - the need for a positive agenda

    International Nuclear Information System (INIS)

    Villar, Heldio P.

    2007-01-01

    After having promised electricity 'too cheap to meter' and being hailed as a viable alternative to the oil shocks of the 1970s, nuclear power is having one more chance - and most probably the last. Prices are competitive, environmentalists now favour it and concerns over global warming are fast overcoming nuclear power's risks, though the vast majority of the population has no clear idea of which they are. Yet, most countries are reluctant to embrace this technology, even those rich in uranium. Brazil, a uranium-rich, energy-hungry country, is still debating if it is not more appropriate to build power plants that use imported gas or - which is probably worse - Brazilian coal. This paper deals with the current situation, taking Brazil as a model. lt is then suggested that the nuclear sector changes its attitude, thus establishing for itself a positive agenda. Instead of stressing safety as its most important feature, the sector must sell nuclear technology as clean, innovative and affordable. Proposals include a good use of the media and, most of all, the introduction of nuclear topics in schools. This will ensure that nuclear power can have a prominent role in bridging the gap between present and future energy sources. (author)

  7. Design and implementation of predictive filtering system for current reference generation of active power filter

    Energy Technology Data Exchange (ETDEWEB)

    Kilic, Tomislav; Milun, Stanko; Petrovic, Goran [FESB University of Split, Faculty of Electrical Engineering, Machine Engineering and Naval Architecture, R. Boskovica bb, 21000, Split (Croatia)

    2007-02-15

    The shunt active power filters are used to attenuate the harmonic currents in power systems by injecting equal but opposite compensating currents. Successful control of the active filters requires an accurate current reference. In this paper the current reference determination based on predictive filtering structure is presented. Current reference was obtained by taking the difference of load current and its fundamental harmonic. For fundamental harmonic determination with no time delay a combination of digital predictive filter and low pass filter is used. The proposed method was implemented on a laboratory prototype of a three-phase active power filter. The algorithm for current reference determination was adapted and implemented on DSP controller. Simulation and experimental results show that the active power filter with implemented predictive filtering structure gives satisfactory performance in power system harmonic attenuation. (author)

  8. Improving nuclear power plant reliability through predictive maintenance

    International Nuclear Information System (INIS)

    Geilhausen, R.; Kunze, U.

    1996-01-01

    Maintenance strategies can be assigned to one of three categories: failure maintenance, periodic maintenance or condition-oriented maintenance. The optimum maintenance scheme can be selected on the basis of a cost-benefit analysis but the safety of life and limb or the political climate for NPP can hardly expressed in numbers. The implementation of preventive maintenance needs two preconditions: high-performance instrumentation in the form of stationary and mobile monitoring systems for the determination of the condition of the nuclear power plant components and provision of a tool that can handle both the organization of the work and the evaluation of the results obtained. (authors)

  9. Ordinal convolutional neural networks for predicting RDoC positive valence psychiatric symptom severity scores.

    Science.gov (United States)

    Rios, Anthony; Kavuluru, Ramakanth

    2017-11-01

    The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) provided a set of 1000 neuropsychiatric notes to participants as part of a competition to predict psychiatric symptom severity scores. This paper summarizes our methods, results, and experiences based on our participation in the second track of the shared task. Classical methods of text classification usually fall into one of three problem types: binary, multi-class, and multi-label classification. In this effort, we study ordinal regression problems with text data where misclassifications are penalized differently based on how far apart the ground truth and model predictions are on the ordinal scale. Specifically, we present our entries (methods and results) in the N-GRID shared task in predicting research domain criteria (RDoC) positive valence ordinal symptom severity scores (absent, mild, moderate, and severe) from psychiatric notes. We propose a novel convolutional neural network (CNN) model designed to handle ordinal regression tasks on psychiatric notes. Broadly speaking, our model combines an ordinal loss function, a CNN, and conventional feature engineering (wide features) into a single model which is learned end-to-end. Given interpretability is an important concern with nonlinear models, we apply a recent approach called locally interpretable model-agnostic explanation (LIME) to identify important words that lead to instance specific predictions. Our best model entered into the shared task placed third among 24 teams and scored a macro mean absolute error (MMAE) based normalized score (100·(1-MMAE)) of 83.86. Since the competition, we improved our score (using basic ensembling) to 85.55, comparable with the winning shared task entry. Applying LIME to model predictions, we demonstrate the feasibility of instance specific prediction interpretation by identifying words that led to a particular decision. In this paper, we present a method that successfully uses wide features and

  10. THE PREDICTIVE POWER OF RELIGIOUS ORIENTATION TYPES ON AMBIVALENT SEXISM

    Directory of Open Access Journals (Sweden)

    Fatih Ozdemir

    2016-07-01

    Full Text Available The purpose of the present study was to predict ambivalent sexism (including hostile sexism and benevolent sexism with religious orientation types as intrinsic religiosity, extrinsic religiosity and quest religiosity. In addition, the effect of demographic variables (including age, gender, education on sexist attitudes was tested. 583 (N_female= 318; N_male= 265 university students who study in different universities of Ankara/Turkey (M_age= 22.10; SD = 2.33 completed Ambivalent Sexism Inventory, and Religious Orientation Scale. Findings indicated significant gender differences on study variables and significant associations between ambivalent sexism and religious orientation types within university students sample in Turkey.

  11. On-line test of power distribution prediction system for boiling water reactors

    International Nuclear Information System (INIS)

    Nishizawa, Y.; Kiguchi, T.; Kobayashi, S.; Takumi, K.; Tanaka, H.; Tsutsumi, R.; Yokomi, M.

    1982-01-01

    A power distribution prediction system for boiling water reactors has been developed and its on-line performance test has proceeded at an operating commercial reactor. This system predicts the power distribution or thermal margin in advance of control rod operations and core flow rate change. This system consists of an on-line computer system, an operator's console with a color cathode-ray tube, and plant data input devices. The main functions of this system are present power distribution monitoring, power distribution prediction, and power-up trajectory prediction. The calculation method is based on a simplified nuclear thermal-hydraulic calculation, which is combined with a method of model identification to the actual reactor core state. It has been ascertained by the on-line test that the predicted power distribution (readings of traversing in-core probe) agrees with the measured data within 6% root-mean-square. The computing time required for one prediction calculation step is less than or equal to 1.5 min by an HIDIC-80 on-line computer

  12. The predictive power of Japanese candlestick charting in Chinese stock market

    Science.gov (United States)

    Chen, Shi; Bao, Si; Zhou, Yu

    2016-09-01

    This paper studies the predictive power of 4 popular pairs of two-day bullish and bearish Japanese candlestick patterns in Chinese stock market. Based on Morris' study, we give the quantitative details of definition of long candlestick, which is important in two-day candlestick pattern recognition but ignored by several previous researches, and we further give the quantitative definitions of these four pairs of two-day candlestick patterns. To test the predictive power of candlestick patterns on short-term price movement, we propose the definition of daily average return to alleviate the impact of correlation among stocks' overlap-time returns in statistical tests. To show the robustness of our result, two methods of trend definition are used for both the medium-market-value and large-market-value sample sets. We use Step-SPA test to correct for data snooping bias. Statistical results show that the predictive power differs from pattern to pattern, three of the eight patterns provide both short-term and relatively long-term prediction, another one pair only provide significant forecasting power within very short-term period, while the rest three patterns present contradictory results for different market value groups. For all the four pairs, the predictive power drops as predicting time increases, and forecasting power is stronger for stocks with medium market value than those with large market value.

  13. Wealth and happiness across the world: material prosperity predicts life evaluation, whereas psychosocial prosperity predicts positive feeling.

    Science.gov (United States)

    Diener, Ed; Ng, Weiting; Harter, James; Arora, Raksha

    2010-07-01

    The Gallup World Poll, the first representative sample of planet Earth, was used to explore the reasons why happiness is associated with higher income, including the meeting of basic needs, fulfillment of psychological needs, increasing satisfaction with one's standard of living, and public goods. Across the globe, the association of log income with subjective well-being was linear but convex with raw income, indicating the declining marginal effects of income on subjective well-being. Income was a moderately strong predictor of life evaluation but a much weaker predictor of positive and negative feelings. Possessing luxury conveniences and satisfaction with standard of living were also strong predictors of life evaluation. Although the meeting of basic and psychological needs mediated the effects of income on life evaluation to some degree, the strongest mediation was provided by standard of living and ownership of conveniences. In contrast, feelings were most associated with the fulfillment of psychological needs: learning, autonomy, using one's skills, respect, and the ability to count on others in an emergency. Thus, two separate types of prosperity-economic and social psychological-best predict different types of well-being.

  14. Extremum seeking x-ray position feedback using power line harmonic leakage as the perturbation

    Directory of Open Access Journals (Sweden)

    S. Zohar

    2016-09-01

    Full Text Available Small x-ray beam sizes necessary for probing nanoscale phenomena require exquisite stability to prevent data corruption by noise. One source of instability at synchrotron radiation x-ray beamlines is the slow detuning of x-ray optics to marginal alignment where the onset of clipping increases the beam’s susceptibility to higher frequency position oscillations. In this article, we show that a 1  μm amplitude horizontal x-ray beam oscillation driven by power line harmonic leakage into the electron storage ring can be used as perturbation for horizontal position extremum seeking feedback. Feedback performance is characterized by convergence to 1.5% away from maximum intensity at optimal alignment.

  15. Positive-unlabeled learning for the prediction of conformational B-cell epitopes

    Science.gov (United States)

    2015-01-01

    Background The incomplete ground truth of training data of B-cell epitopes is a demanding issue in computational epitope prediction. The challenge is that only a small fraction of the surface residues of an antigen are confirmed as antigenic residues (positive training data); the remaining residues are unlabeled. As some of these uncertain residues can possibly be grouped to form novel but currently unknown epitopes, it is misguided to unanimously classify all the unlabeled residues as negative training data following the traditional supervised learning scheme. Results We propose a positive-unlabeled learning algorithm to address this problem. The key idea is to distinguish between epitope-likely residues and reliable negative residues in unlabeled data. The method has two steps: (1) identify reliable negative residues using a weighted SVM with a high recall; and (2) construct a classification model on the positive residues and the reliable negative residues. Complex-based 10-fold cross-validation was conducted to show that this method outperforms those commonly used predictors DiscoTope 2.0, ElliPro and SEPPA 2.0 in every aspect. We conducted four case studies, in which the approach was tested on antigens of West Nile virus, dihydrofolate reductase, beta-lactamase, and two Ebola antigens whose epitopes are currently unknown. All the results were assessed on a newly-established data set of antigen structures not bound by antibodies, instead of on antibody-bound antigen structures. These bound structures may contain unfair binding information such as bound-state B-factors and protrusion index which could exaggerate the epitope prediction performance. Source codes are available on request. PMID:26681157

  16. Prediction of speech intelligibility based on a correlation metric in the envelope power spectrum domain

    DEFF Research Database (Denmark)

    Relano-Iborra, Helia; May, Tobias; Zaar, Johannes

    A powerful tool to investigate speech perception is the use of speech intelligibility prediction models. Recently, a model was presented, termed correlation-based speechbased envelope power spectrum model (sEPSMcorr) [1], based on the auditory processing of the multi-resolution speech-based Envel...

  17. The prediction and prevention of voltage collapse in the Finnish power system

    Energy Technology Data Exchange (ETDEWEB)

    Bastman, J; Lakervi, E [Tampere Univ. of Tech. (Finland); Hirvonen, R; Kuronen, P; Hagman, E [IVO Group (Finland)

    1994-12-31

    The Finnish power system is a part of the Nordic power system (NORDEL), which includes Finland, Sweden, Norway and the eastern part of Denmark. In NORDEL the transmission distances are long, which implies that the power transmission capacities are determined by stability criteria . The methods to prevent and predict the voltage collapse during severe disturbances are studied using advances simulation program. Results are presented. (author) 10 figs., 1 tab.

  18. Positive parenting predicts the development of adolescent brain structure: A longitudinal study

    Directory of Open Access Journals (Sweden)

    Sarah Whittle

    2014-04-01

    Full Text Available Little work has been conducted that examines the effects of positive environmental experiences on brain development to date. The aim of this study was to prospectively investigate the effects of positive (warm and supportive maternal behavior on structural brain development during adolescence, using longitudinal structural MRI. Participants were 188 (92 female adolescents, who were part of a longitudinal adolescent development study that involved mother–adolescent interactions and MRI scans at approximately 12 years old, and follow-up MRI scans approximately 4 years later. FreeSurfer software was used to estimate the volume of limbic-striatal regions (amygdala, hippocampus, caudate, putamen, pallidum, and nucleus accumbens and the thickness of prefrontal regions (anterior cingulate and orbitofrontal cortices across both time points. Higher frequency of positive maternal behavior during the interactions predicted attenuated volumetric growth in the right amygdala, and accelerated cortical thinning in the right anterior cingulate (males only and left and right orbitofrontal cortices, between baseline and follow up. These results have implications for understanding the biological mediators of risk and protective factors for mental disorders that have onset during adolescence.

  19. Positive parenting predicts the development of adolescent brain structure: a longitudinal study.

    Science.gov (United States)

    Whittle, Sarah; Simmons, Julian G; Dennison, Meg; Vijayakumar, Nandita; Schwartz, Orli; Yap, Marie B H; Sheeber, Lisa; Allen, Nicholas B

    2014-04-01

    Little work has been conducted that examines the effects of positive environmental experiences on brain development to date. The aim of this study was to prospectively investigate the effects of positive (warm and supportive) maternal behavior on structural brain development during adolescence, using longitudinal structural MRI. Participants were 188 (92 female) adolescents, who were part of a longitudinal adolescent development study that involved mother-adolescent interactions and MRI scans at approximately 12 years old, and follow-up MRI scans approximately 4 years later. FreeSurfer software was used to estimate the volume of limbic-striatal regions (amygdala, hippocampus, caudate, putamen, pallidum, and nucleus accumbens) and the thickness of prefrontal regions (anterior cingulate and orbitofrontal cortices) across both time points. Higher frequency of positive maternal behavior during the interactions predicted attenuated volumetric growth in the right amygdala, and accelerated cortical thinning in the right anterior cingulate (males only) and left and right orbitofrontal cortices, between baseline and follow up. These results have implications for understanding the biological mediators of risk and protective factors for mental disorders that have onset during adolescence. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

  20. Predicting body appreciation in young women: An integrated model of positive body image.

    Science.gov (United States)

    Andrew, Rachel; Tiggemann, Marika; Clark, Levina

    2016-09-01

    This study examined a range of predictors, based on previous theoretical models, of positive body image in young adult women. Participants were 266 women who completed an online questionnaire measuring body appreciation, activity participation, media consumption, perceived body acceptance by others, self-compassion, and autonomy. Potential mechanisms in predicting body appreciation assessed were self-objectification, social appearance comparison, and thin-ideal internalisation. Results indicated that greater perceived body acceptance by others and self-compassion, and lower appearance media consumption, self-objectification, social comparison, and thin-ideal internalisation were related to greater body appreciation. An integrated model showed that appearance media (negatively) and non-appearance media and self-compassion (positively) were associated with lower self-objectification, social comparison, and thin-ideal internalisation, which in turn related to greater body appreciation. Additionally, perceived body acceptance by others was directly associated with body appreciation. The results contribute to an understanding of potential pathways of positive body image development, thereby highlighting possible intervention targets. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Androgen receptor positive triple negative breast cancer: Clinicopathologic, prognostic, and predictive features.

    Directory of Open Access Journals (Sweden)

    Kristine Astvatsaturyan

    Full Text Available Overexpression of the androgen receptor (AR characterizes a distinct molecular subset of triple negative breast carcinomas (TNBC. The role of AR as a prognostic/predictive biomarker in TNBC is controversial, but increasing evidence suggests that this subset may respond to therapeutic agents targeting AR. Evaluation of AR has not been standardized, and criteria for selection of patients for antiandrogen therapy remain controversial. In this study we determine the appropriate threshold of AR immunoreactivity to define AR positive (AR+ TNBC, describe the clinicopathologic features of AR+ TNBC, and discuss the utility of AR positivity as a prognostic and predictive marker in TNBC.135 invasive TNBC processed in accordance with ASCO/CAP guidelines, were immunostained for AR. Clinicopathologic features of AR+ TNBC were analyzed and compared to AR negative (AR- TNBC. Patients' age, tumor size, tumor grade, lymph node status, proliferation rate, immunopositivity for EGFR, CK5/6, Ki-67, and disease free survival (DFS were evaluated statistically.A 1% cutpoint was confirmed as the appropriate threshold for AR positivity. Using this cutpoint 41% of 135 TNBC were AR+. AR+ TNBC occurred in older women, were larger, had lower mean proliferation rate and increased incidence of axillary metastasis than AR- TNBC. 76% of TNBC with apocrine morphology were AR+. A subset of AR+TNBC expressed basal markers (EGFR and CK5/6. A prognostic model was created.AR identifies a heterogeneous group of TNBC. Additional evaluation of EGFR expression allowed us to stratify TNBCs into 3 risk groups with significant differences in DFS and therapeutic implications: low-risk (AR+ EGFR- which represents the LAR molecular subtype with the best prognosis and may benefit the most from anti-androgen therapies; high-risk (AR- EGFR+ which represents the basal molecular subtype with the worst prognosis and may benefit the most from chemotherapy regimens; intermediate-risk (AR+EGFR+ and AR

  2. Positive predictive value of the infant respiratory distress syndrome diagnosis in the Danish National Patient Registry

    Directory of Open Access Journals (Sweden)

    Thygesen SK

    2013-08-01

    Full Text Available Sandra Kruchov Thygesen, Morten Olsen, Christian Fynbo ChristiansenDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus, DenmarkBackground: Infant respiratory distress syndrome (IRDS is the most common respiratory disease in preterm infants, and is associated with considerable morbidity and mortality. Valid data on IRDS are important in clinical epidemiological research.Objectives: The objective of this study was to estimate the positive predictive value (PPV of the IRDS diagnosis registered in the population-based Danish National Patient Registry according to the International Classification of Diseases, 8th and 10th revisions.Methods: Between January 1, 1977 and December 31, 2008, we randomly selected three patients per year, 96 in total, who were registered with an IRDS diagnosis in the Danish National Patient Registry and living in the northern part of Denmark. Data on the infants included information on the presence of predefined clinical symptoms. We defined IRDS as the presence of at least two of four clinical symptoms (tachypnea, retractions or nasal flaring, grunting, and central cyanosis, which had to be present for more than 30 minutes. Using medical record review as the reference standard, we computed the positive predictive value of the registered IRDS diagnosis including 95% confidence intervals (CIs.Results: We located the medical record for 90 of the 96 patients (94%, and found an overall PPV of the IRDS diagnosis of 81% (95% CI 72%–88%. This did not vary substantially between primary and secondary diagnoses. The PPV was higher, at 89% (95% CI 80%–95%, for preterm infants born before 37 weeks of gestation.Conclusion: The PPV of the IRDS diagnosis in the Danish National Patient Registry is reasonable when compared with symptoms described in the corresponding medical records. The Danish National Patient Registry is a useful data source for studies of IRDS, particularly if restricted to preterm infants

  3. A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

    International Nuclear Information System (INIS)

    Pousinho, H.M.I.; Mendes, V.M.F.; Catalao, J.P.S.

    2011-01-01

    The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

  4. A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

    Energy Technology Data Exchange (ETDEWEB)

    Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal); Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)

    2011-01-15

    The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches. (author)

  5. Synchrophasor-Assisted Prediction of Stability/Instability of a Power System

    Science.gov (United States)

    Saha Roy, Biman Kumar; Sinha, Avinash Kumar; Pradhan, Ashok Kumar

    2013-05-01

    This paper presents a technique for real-time prediction of stability/instability of a power system based on synchrophasor measurements obtained from phasor measurement units (PMUs) at generator buses. For stability assessment the technique makes use of system severity indices developed using bus voltage magnitude obtained from PMUs and generator electrical power. Generator power is computed using system information and PMU information like voltage and current phasors obtained from PMU. System stability/instability is predicted when the indices exceeds a threshold value. A case study is carried out on New England 10-generator, 39-bus system to validate the performance of the technique.

  6. Robust Correlation Analyses: False Positive and Power Validation Using a New Open Source Matlab Toolbox

    Science.gov (United States)

    Pernet, Cyril R.; Wilcox, Rand; Rousselet, Guillaume A.

    2012-01-01

    Pearson’s correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab(R) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand. PMID:23335907

  7. Robust correlation analyses: false positive and power validation using a new open source matlab toolbox.

    Science.gov (United States)

    Pernet, Cyril R; Wilcox, Rand; Rousselet, Guillaume A

    2012-01-01

    Pearson's correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab((R)) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand.

  8. Improving tokamak vertical position control in the presence of power supply voltage saturation

    International Nuclear Information System (INIS)

    Favez, J-Y; Lister, J B; Muellhaupt, Ph; Srinivasan, B

    2005-01-01

    The control of the current, position and shape of an elongated cross-section tokamak plasma is complicated by the so-called instability of the current vertical position. Linearized models all share the feature of a single unstable eigenmode, attributable to this vertical instability of the plasma equilibrium movement, and a large number of stable or marginally stable eigenmodes, attributable to zero or positive resistance in all other model circuit equations. Due to the size and therefore cost of the ITER tokamak, there will naturally be smaller margins in the poloidal field coil power supplies, implying that the feedback control will experience actuator saturation during large transients due to a variety of plasma disturbances. Current saturation is relatively benign, due to the integrating nature of the tokamak, resulting in a reasonable time horizon for strategically handling the approach to saturation which leads to the loss of one degree of freedom in the feedback control for each saturated coil. On the other hand, voltage saturation is produced by the feedback controller itself, with no intrinsic delay. This paper presents a feedback controller design approach which explicitly takes saturation of the power supply voltage into account when producing the power supply demand signals. We consider the vertically stabilizing part of the ITER controller (fast controller) with one power supply and therefore a single saturated input. We consider an existing ITER controller and enlarge its region of attraction to the full null controllable region by adding a continuous nonlinearity into the control. In a system with a single unstable eigenmode and a single stable eigenmode we have already provided a proof of the asymptotical stability of the closed loop system, and we have examined the performance of this new continuous nonlinear controller. We have subsequently extended this analysis to a system with a single eigenmode and multiple stable eigenmodes. The method

  9. Char characterization and DTF assays as tools to predict burnout of coal blends in power plants

    Energy Technology Data Exchange (ETDEWEB)

    C. Ulloa; A.G. Borrego; S. Helle; A.L. Gordon; X. Garcia [Universidad de Concepcion, Concepcion (Chile). Departamento de Ingenieria Quimica

    2005-02-01

    The aim of this study is to predict efficiency deviations in the combustion of coal blends in power plants. Combustion of blends, as compared to its single coals, shows that for some blends the behavior is non-additive in nature. Samples of coal feed and fly ashes from combustion of blends at two power plants, plus chars of the parent coals generated in a drop-tube furnace (DTF) at temperatures and heating rates similar to those found in the industrial boilers were used. Intrinsic kinetic parameters, burning profiles and petrographic characteristics of these chars correlated well with the burnout in power plants and DTF experiments. The blend combustion in a DTF reproduces both positive and negative burnout deviations from the expected weighted average. These burnout deviations have been previously attributed to parallel or parallel-series pathways of competition for oxygen. No deviations were found for blends of low rank coals of similar characteristics yielding chars close in morphology, optical texture and reactivity. Negative deviations were found for blends of coals differing moderately in rank and were interpreted as associated with long periods of competition. In this case, fly-ashes were enriched in material derived from the least reactive char, but also unburnt material attributed to the most reactive char was identified. Improved burnout compared to the weighted average was observed for blends of coals very different in rank, and interpreted as the result of a short interaction period, followed by a period where the less reactive char burns under conditions that are more favorable to its combustion. In this case, only unburned material from the least reactive char was identified in the fly-ashes. 20 refs., 9 figs., 5 tabs.

  10. THE PREDICTIVE POWER OF RELIGIOUS ORIENTATION TYPES ON AMBIVALENT SEXISM

    Directory of Open Access Journals (Sweden)

    Gul Ulubayram

    2016-07-01

    Full Text Available Objective: The purpose of this study is to examine stress and stress related factors in tuberculosis patients. In addition, to determine the impact of socio-demographic variables such as age, gender and educational level over stress symptoms hereby comprises a further objective of this study. Method: The study included totally 129 tuberculosis patients and 161 non-patients (normal group participants. Tuberculosis patients registered in Ankara Tuberculosis Dispensary No.4, and Atatürk Chest Diseases and Chest Surgery Hospital. There are 75 Pulmonary Tuberculosis (AC TB and 54 Extra- Pulmonary Tuberculosis (AD TB patients. As regards data collection tools; Demographic Information Form, Brief Symptom Inventory, Stress Symptoms Scale, Stress Vulnerability Scale, and Stress Coping Scale were used. Results: Within the context of diagnosis groups; it was found that; stress symptoms of tuberculosis patients are higher than the normal group, they use their ineffective coping ways more and their life satisfactions are lower. There exists no gender and diagnosis group main effect in terms of the psychological symptoms of stress, however “gender x diagnosis group” interaction effect draws attention herein. In tuberculosis patients, ineffective coping the stress and relation pleasure variables are confronted as joint variables which are predicting both the psychological and physical health. Another point which draws attention in regression analyzes is that; “education” variable takes place among the variables which predict the psychological symptoms of stress in tuberculosis patients. Conclusion: Under the light of these findings, tuberculosis patients, during their treatment processes, may be encouraged to attend various training programs prepared for stress management and effective dealing strategies with stress. By increasing the patients’ motivation towards the treatment, these programs may provide supplementary benefits to the treatment by

  11. Power consumption in positive ion beam converter with electrostatic electron suppressor

    International Nuclear Information System (INIS)

    Hashimoto, Kiyoshi; Sugawara, Tohru

    1985-01-01

    The power recovery characteristics of an in-line direct beam converter provided with electrostatic electron suppressor were studied numerically by tracing the orbits of fast primary ions and secondary charged particles generated along their beam path by collision with background gas molecules. It is shown that, in reference to the electrostatic field potential at the point of impact, the energy distribution of secondary ions impinging on the suppressor has two peaks-one corresponding to a zone of high positive potential surrounding the collector and the other to one of slightly negative potential around the electron suppressor. Secondary electron emission from the suppressor is ascribed mainly to the latter peak, associated with impingement of slower secondary ions. Far much power consumed in secondary particle acceleration is spent for emitting electrons from the suppressor than for secondary ions generated by beam-gas collision. The upper limit of background pressure is discussed on the basis of criteria prescribed for restricting the power consumed in this secondary particle acceleration, as for practical convenience of electrode cooling. Numerical examples are given of calculations based on particle trajectory analysis of both primary ions and secondary particles, for the case of a 100 keV-proton sheet beam 10 cm thick of 35 mA/cm 2 current density. (author)

  12. Predicting Likelihood of Having Four or More Positive Nodes in Patient With Sentinel Lymph Node-Positive Breast Cancer: A Nomogram Validation Study

    International Nuclear Information System (INIS)

    Unal, Bulent; Gur, Akif Serhat; Beriwal, Sushil; Tang Gong; Johnson, Ronald; Ahrendt, Gretchen; Bonaventura, Marguerite; Soran, Atilla

    2009-01-01

    Purpose: Katz suggested a nomogram for predicting having four or more positive nodes in sentinel lymph node (SLN)-positive breast cancer patients. The findings from this formula might influence adjuvant radiotherapy decisions. Our goal was to validate the accuracy of the Katz nomogram. Methods and Materials: We reviewed the records of 309 patients with breast cancer who had undergone completion axillary lymph node dissection. The factors associated with the likelihood of having four or more positive axillary nodes were evaluated in patients with one to three positive SLNs. The nomogram developed by Katz was applied to our data set. The area under the curve of the corresponding receiver operating characteristics curve was calculated for the nomogram. Results: Of the 309 patients, 80 (25.9%) had four or more positive axillary lymph nodes. On multivariate analysis, the number of positive SLNs (p < .0001), overall metastasis size (p = .019), primary tumor size (p = .0001), and extracapsular extension (p = .01) were significant factors predicting for four or more positive nodes. For patients with <5% probability, 90.3% had fewer than four positive nodes and 9.7% had four or more positive nodes. The negative predictive value was 91.7%, and sensitivity was 80%. The nomogram was accurate and discriminating (area under the curve, .801). Conclusion: The probability of four or more involved nodes is significantly greater in patients who have an increased number of positive SLNs, increased overall metastasis size, increased tumor size, and extracapsular extension. The Katz nomogram was validated in our patients. This nomogram will be helpful to clinicians making adjuvant treatment recommendations to their patients.

  13. ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

    Science.gov (United States)

    Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

    2013-01-01

    Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application. PMID:23955435

  14. Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

    Science.gov (United States)

    Mohammed, E.; Wang, S.; Yu, J.

    2017-05-01

    This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

  15. ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

    Directory of Open Access Journals (Sweden)

    Milos Bogdanovic

    2013-08-01

    Full Text Available Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.

  16. ESB-based Sensor Web integration for the prediction of electric power supply system vulnerability.

    Science.gov (United States)

    Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

    2013-08-15

    Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.

  17. A new wind power prediction method based on chaotic theory and Bernstein Neural Network

    International Nuclear Information System (INIS)

    Wang, Cong; Zhang, Hongli; Fan, Wenhui; Fan, Xiaochao

    2016-01-01

    The accuracy of wind power prediction is important for assessing the security and economy of the system operation when wind power connects to the grids. However, multiple factors cause a long delay and large errors in wind power prediction. Hence, efficient wind power forecasting approaches are still required for practical applications. In this paper, a new wind power forecasting method based on Chaos Theory and Bernstein Neural Network (BNN) is proposed. Firstly, the largest Lyapunov exponent as a judgment for wind power system's chaotic behavior is made. Secondly, Phase Space Reconstruction (PSR) is used to reconstruct the wind power series' phase space. Thirdly, the prediction model is constructed using the Bernstein polynomial and neural network. Finally, the weights and thresholds of the model are optimized by Primal Dual State Transition Algorithm (PDSTA). The practical hourly data of wind power generation in Xinjiang is used to test this forecaster. The proposed forecaster is compared with several current prominent research findings. Analytical results indicate that the forecasting error of PDSTA + BNN is 3.893% for 24 look-ahead hours, and has lower errors obtained compared with the other forecast methods discussed in this paper. The results of all cases studying confirm the validity of the new forecast method. - Highlights: • Lyapunov exponent is used to verify chaotic behavior of wind power series. • Phase Space Reconstruction is used to reconstruct chaotic wind power series. • A new Bernstein Neural Network to predict wind power series is proposed. • Primal dual state transition algorithm is chosen as the training strategy of BNN.

  18. A variable capacitance based modeling and power capability predicting method for ultracapacitor

    Science.gov (United States)

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

    2018-01-01

    Methods of accurate modeling and power capability predicting for ultracapacitors are of great significance in management and application of lithium-ion battery/ultracapacitor hybrid energy storage system. To overcome the simulation error coming from constant capacitance model, an improved ultracapacitor model based on variable capacitance is proposed, where the main capacitance varies with voltage according to a piecewise linear function. A novel state-of-charge calculation approach is developed accordingly. After that, a multi-constraint power capability prediction is developed for ultracapacitor, in which a Kalman-filter-based state observer is designed for tracking ultracapacitor's real-time behavior. Finally, experimental results verify the proposed methods. The accuracy of the proposed model is verified by terminal voltage simulating results under different temperatures, and the effectiveness of the designed observer is proved by various test conditions. Additionally, the power capability prediction results of different time scales and temperatures are compared, to study their effects on ultracapacitor's power capability.

  19. Wind Turbine Generator Efficiency Based on Powertrain Combination and Annual Power Generation Prediction

    Directory of Open Access Journals (Sweden)

    Dongmyung Kim

    2018-05-01

    Full Text Available Wind turbine generators are eco-friendly generators that produce electric energy using wind energy. In this study, wind turbine generator efficiency is examined using a powertrain combination and annual power generation prediction, by employing an analysis model. Performance testing was conducted in order to analyze the efficiency of a hydraulic pump and a motor, which are key components, and so as to verify the analysis model. The annual wind speed occurrence frequency for the expected installation areas was used to predict the annual power generation of the wind turbine generators. It was found that the parallel combination of the induction motors exhibited a higher efficiency when the wind speed was low and the serial combination showed higher efficiency when wind speed was high. The results of predicting the annual power generation considering the regional characteristics showed that the power generation was the highest when the hydraulic motors were designed in parallel and the induction motors were designed in series.

  20. Application of clustering analysis in the prediction of photovoltaic power generation based on neural network

    Science.gov (United States)

    Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

    2017-11-01

    In order to select effective samples in the large number of data of PV power generation years and improve the accuracy of PV power generation forecasting model, this paper studies the application of clustering analysis in this field and establishes forecasting model based on neural network. Based on three different types of weather on sunny, cloudy and rainy days, this research screens samples of historical data by the clustering analysis method. After screening, it establishes BP neural network prediction models using screened data as training data. Then, compare the six types of photovoltaic power generation prediction models before and after the data screening. Results show that the prediction model combining with clustering analysis and BP neural networks is an effective method to improve the precision of photovoltaic power generation.

  1. Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation

    Energy Technology Data Exchange (ETDEWEB)

    Abbas, Nikhar [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Tom, Nathan M [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-06-03

    Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalman filter and autoregressive model to evaluate model predictive control performance.

  2. Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Abbas, Nikhar; Tom, Nathan

    2017-09-01

    Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalman filter and autoregressive model to evaluate model predictive control performance.

  3. Positive predictive value and effectiveness of measles case-based surveillance in Uganda, 2012-2015.

    Directory of Open Access Journals (Sweden)

    Fred Nsubuga

    Full Text Available Disease surveillance is a critical component in the control and elimination of vaccine preventable diseases. The Uganda National Expanded Program on Immunization strives to have a sensitive surveillance system within the Integrated Disease Surveillance and Response (IDSR framework. We analyzed measles surveillance data to determine the effectiveness of the measles case-based surveillance system and estimate its positive predictive value in order to inform policy and practice.An IDSR alert was defined as ≥1 suspected measles case reported by a district in a week, through the electronic Health Management Information System. We defined an alert in the measles case-based surveillance system (CBS as ≥1 suspected measles case with a blood sample collected for confirmation during the corresponding week in a particular district. Effectiveness of CBS was defined as having ≥80% of IDSR alerts with a blood sample collected for laboratory confirmation. Positive predictive value was defined as the proportion of measles case-patients who also had a positive measles serological result (IgM +. We reviewed case-based surveillance data with laboratory confirmation and measles surveillance data from the electronic Health Management Information System from 2012-2015.A total of 6,974 suspected measles case-persons were investigated by the measles case-based surveillance between 2012 and 2015. Of these, 943 (14% were measles specific IgM positive. The median age of measles case-persons between 2013 and 2015 was 4.0 years. Between 2013 and 2015, 72% of the IDSR alerts reported in the electronic Health Management Information System, had blood samples collected for laboratory confirmation. This was however less than the WHO recommended standard of ≥80%. The PPV of CBS between 2013 and 2015 was 8.6%.In conclusion, the effectiveness of measles case-based surveillance was sub-optimal, while the PPV showed that true measles cases have significantly reduced in Uganda

  4. Significant change of predictions related to the future of nuclear power

    International Nuclear Information System (INIS)

    Dumitrache, Ion

    2002-01-01

    During the last two decades of the 20th century, nuclear power contribution increased slowly in the world. This trend was mainly determined by the commissioning of new nuclear power plants, NPP, in the non-developed countries, except for Japan and South Korea. Almost all the forecasts offered the image of the stagnant nuclear power business. Sweden, Germany, Holland and Belgium Governments made clear the intention to stop the production of electricity based on fission. Recently, despite the negative effects on nuclear power of the terrorism events of September 11, 2001, the predictions related to the nuclear power future become much more optimistic. USA, Japan, South Korea and Canada made clear that new NPPs will offer their significant electricity contribution several decades, even after years 2020-2030. Moreover, several old NPP from USA obtained the license for an additional 20 years period of operation. The analysis indicated that most of the existing NPP in USA may increase the level of the maximum global power defined by the initial design. In the European Union the situation is much more complicated. About 35% of the electricity is based now on fission. Several countries, like Sweden and Germany, maintain the position of phasing out the NPPs, as soon as the licensed life-time is over. Finland decided to build a new power plant. France is very favorable to nuclear power, but does not need more energy. In the UK several very old NPP will be shut down, and companies like BNFL and British Energy intend to build new NPP, based on Westinghouse or AECL-Canada advanced reactors. Switzerland and Spain are favorable to the future use of nuclear power. In the eastern part of Europe, almost all the countries intend to base their electricity production on coal, fission, hydro and gas, nuclear contribution being significant. The most impressive increases of nuclear power output are related to Asia; in China, from 2.2 Gwe in 1999, to 18.7 Gwe in 2020, reference case, or 10

  5. Recent advances in prediction of emission of hazardous air pollutants from coal-fired power plants

    International Nuclear Information System (INIS)

    Senior, C.L.; Helble, J.J.; Sarofim, A.F.

    2000-01-01

    Coal-fired power plants are a primary source of mercury discharge into the atmosphere along with fine particulates containing arsenic, selenium, cadmium, and other hazardous air pollutants. Information regarding the speciation of these toxic metals is necessary to accurately predict their atmospheric transport and fate in the environment. New predictive tools have been developed to allow utilities to better estimate the emissions of toxic metals from coal-fired power plants. These prediction equations are based on fundamental physics and chemistry and can be applied to a wide variety of fuel types and combustion conditions. The models have significantly improved the ability to predict the emissions of air toxic metals in fine particulate and gas-phase mercury. In this study, the models were successfully tested using measured mercury speciation and mass balance information collected from coal-fired power plants

  6. Effects of Positioning Uncertainty and Breathing on Dose Delivery and Radiation Pneumonitis Prediction in Breast Cancer

    International Nuclear Information System (INIS)

    Mavroidis, Panayiotis; Axelsson, Sofie; Hyoedynmaa, Simo; Rajala, Juha; Pitkaenen, Maunu A.; Lind, Bengt K.; Brahme, Anders

    2002-01-01

    complication probabilities than the original plans. This means that the true expected complications are often underestimated in clinical practice. The lung density variation during breathing is calculated from the maximal change in average density during tidal breathing. The change in density in the lung due to breathing is shown to have almost no influence on the dose distribution in the lung. The proposed treatment-plan adjustments taking positioning uncertainty and breathing effects into account indicate significant deviations in the dose delivery and the predicted lung complications

  7. CT colonography without cathartic preparation: positive predictive value and patient experience in clinical practice

    Energy Technology Data Exchange (ETDEWEB)

    Zueco Zueco, Carmen; Sobrido Sampedro, Carolina; Corroto, Juan D.; Rodriguez Fernandez, Paula; Fontanillo Fontanillo, Manuela [Complexo Hospitalario Universitario de Vigo - CHUVI, Vigo, Pontevedra (Spain)

    2012-06-15

    To determine the positive predictive value (PPV) for polyps {>=}6 mm detected at CT colonography (CTC) performed without cathartic preparation, with low-dose iodine faecal tagging regimen and to evaluate patient experience. 1920 average-risk patients underwent CTC without cathartic preparation. Faecal tagging was performed by diatrizoate meglumine and diatrizoate sodium at a total dose of 60 ml (22.2 g of iodine).The standard interpretation method was primary 3D with 2D problem solving. We calculated per-patient and per-polyp PPV in relation to size and morphology. All colonic segments were evaluated for image quality (faecal tagging, amount of liquid and solid residual faeces and luminal distension). Patients completed a questionnaire before and after CTC to assess preparation and examination experience. Per-polyp PPV for detected lesions of {>=}6 mm, 6-9 mm, {>=}10 mm and {>=}30 mm were 94.3%, 93.1%, 94.7% and 98%, respectively. Per-polyp PPV, according to lesion morphology, was 94.6%, 97.3% and 85.1% for sessile, pedunculated and flat polyps, respectively. Per-patient PPV was 92.8%. Preparation without frank cathartics was reported to cause minimal discomfort by 78.9% of patients. CTC without cathartic preparation and low-dose iodine faecal tagging may yield high PPVs for lesions {>=}6 mm and is well accepted by patients. circle Computed tomographic colonography (CTC) without cathartic preparation is well accepted by patients circle Cathartic-free faecal tagging CTC yields high positive predictive values circle CTC without cathartic preparation could improve uptake of colorectal cancer screening. (orig.)

  8. Positive technology–A powerful partnership between positive psychology and interactive technology. A discussion of potential and challenges.

    Directory of Open Access Journals (Sweden)

    Sarah Diefenbach

    2017-11-01

    Full Text Available Under the umbrella term "positive computing" concepts of positive psychology are transferred to the domain of human-computer interaction (HCI. In an interdisciplinary community psychologist, computer scientists, designers and others are exploring promising ways how to utilize interactive technology to support wellbeing and human flourishing. Along with this, the recent popularity of smartphone apps aiming at the improvement of health behavior, mindfulness and positive routines, suggests the general acceptance of technology as a facilitator of personal development. Given this, there generally seems a high potential for a technology mediated trigger of positive behavior change, especially in context of positive psychology and resource oriented approaches such as solution-focused coaching. At the same time, there is still a lack of well-founded approaches to design such technology which consider its responsible role as an "interactive coach" and systematically integrate the needed expertise of different disciplines. The present article discusses the general potential and particular challenges to support the goals of positive psychology and human desire for self-improvement through interactive technology and highlights critical steps for a successful partnership between both.

  9. Nurse-Administered, Gut-Directed Hypnotherapy in IBS: Efficacy and Factors Predicting a Positive Response.

    Science.gov (United States)

    Lövdahl, Jenny; Ringström, Gisela; Agerforz, Pia; Törnblom, Hans; Simrén, Magnus

    2015-07-01

    Hypnotherapy is an effective treatment in irritable bowel syndrome (IBS). It is often delivered by a psychotherapist and is costly and time consuming. Nurse-administered hypnotherapy could increase availability and reduce costs. In this study the authors evaluate the effectiveness of nurse-administered, gut-directed hypnotherapy and identify factors predicting treatment outcome. Eighty-five patients were included in the study. Participants received hypnotherapy by a nurse once/week for 12 weeks. Patients reported marked improvement in gastrointestinal (GI) and extra-colonic symptoms after treatment, as well as a reduction in GI-specific anxiety, general anxiety, and depression. Fifty-eight percent were responders after the 12 weeks treatment period, and of these 82% had a favorable clinical response already at week 6. Women were more likely than men to respond favorably to the treatment. Nurse-administered hypnotherapy is an effective treatment for IBS. Being female and reporting a favorable response to treatment by week 6 predicted a positive treatment response at the end of the 12 weeks treatment period.

  10. Critical power prediction by CATHARE2 of the OECD/NRC BFBT benchmark

    Energy Technology Data Exchange (ETDEWEB)

    Lutsanych, Sergii, E-mail: s.lutsanych@ing.unipi.it [San Piero a Grado Nuclear Research Group (GRNSPG), University of Pisa, Via Livornese 1291, 56122, San Piero a Grado, Pisa (Italy); Sabotinov, Luben, E-mail: luben.sabotinov@irsn.fr [Institut for Radiological Protection and Nuclear Safety (IRSN), 31 avenue de la Division Leclerc, 92262 Fontenay-aux-Roses (France); D’Auria, Francesco, E-mail: francesco.dauria@dimnp.unipi.it [San Piero a Grado Nuclear Research Group (GRNSPG), University of Pisa, Via Livornese 1291, 56122, San Piero a Grado, Pisa (Italy)

    2015-03-15

    Highlights: • We used CATHARE code to calculate the critical power exercises of the OECD/NRC BFBT benchmark. • We considered both steady-state and transient critical power tests of the benchmark. • We used both the 1D and 3D features of the CATHARE code to simulate the experiments. • Acceptable prediction of the critical power and its location in the bundle is obtained using appropriate modelling. - Abstract: This paper presents an application of the French best estimate thermal-hydraulic code CATHARE 2 to calculate the critical power and departure from nucleate boiling (DNB) exercises of the International OECD/NRC BWR Fuel Bundle Test (BFBT) benchmark. The assessment activity is performed comparing the code calculation results with available in the framework of the benchmark experimental data from Japanese Nuclear Power Engineering Corporation (NUPEC). Two-phase flow calculations on prediction of the critical power have been carried out both in steady state and transient cases, using one-dimensional and three-dimensional modelling. Results of the steady-state critical power tests calculation have shown the ability of CATHARE code to predict reasonably the critical power and its location, using appropriate modelling.

  11. Innovative optical power detection array system for relative positioning of inner-formation flying system

    Science.gov (United States)

    Hou, Zhendong; Wang, Zhaokui; Zhang, Yulin

    2016-09-01

    The Inner-formation flying system (IFFS) is conceived to feature a spherical proof mass falling freely within a large cavity for space gravity detection, of which first application focuses on the Earth's gravity field recovery. For the IFFS, it is the relative position of the proof mass to its surrounding cavity that is feedback into thrusters for tracking control, even as part of data to detect gravity. Since the demonstration and verification of demanding technologies using small satellite platforms is a very sensible choice prior to detection mission, an optical power detection array system (OPDAS) is proposed to measure the relative position with advantages of low cost and high adaptability. Besides that, its large dynamic range can reduce the requirement for satellite platform and releasing mechanism, which is also an attracting trait for small satellite application. The concept of the OPDAS is firstly presented, followed by the algorithm to position the proof mass. Then the radiation pressure caused by the measuring beam is modeled, and its disturbance on the proof mass is simulated. The experimental system to test the performance of a prototype of the OPDAS is established, and the preliminary results show that a precision of less than 0.4 mm across a dynamic range of several centimeters can be reached by the prototype of the OPDAS.

  12. Using data-driven approach for wind power prediction: A comparative study

    International Nuclear Information System (INIS)

    Taslimi Renani, Ehsan; Elias, Mohamad Fathi Mohamad; Rahim, Nasrudin Abd.

    2016-01-01

    Highlights: • Double exponential smoothing is the most accurate model in wind speed prediction. • A two-stage feature selection method is proposed to select most important inputs. • Direct prediction illustrates better accuracy than indirect prediction. • Adaptive neuro fuzzy inference system outperforms data mining algorithms. • Random forest performs the worst compared to other data mining algorithm. - Abstract: Although wind energy is intermittent and stochastic in nature, it is increasingly important in the power generation due to its sustainability and pollution-free. Increased utilization of wind energy sources calls for more robust and efficient prediction models to mitigate uncertainties associated with wind power. This research compares two different approaches in wind power forecasting which are indirect and direct prediction methods. In indirect method, several times series are applied to forecast the wind speed, whereas the logistic function with five parameters is then used to forecast the wind power. In this study, backtracking search algorithm with novel crossover and mutation operators is employed to find the best parameters of five-parameter logistic function. A new feature selection technique, combining the mutual information and neural network is proposed in this paper to extract the most informative features with a maximum relevancy and minimum redundancy. From the comparative study, the results demonstrate that, in the direct prediction approach where the historical weather data are used to predict the wind power generation directly, adaptive neuro fuzzy inference system outperforms five data mining algorithms namely, random forest, M5Rules, k-nearest neighbor, support vector machine and multilayer perceptron. Moreover, it is also found that the mean absolute percentage error of the direct prediction method using adaptive neuro fuzzy inference system is 1.47% which is approximately less than half of the error obtained with the

  13. New England observed and predicted August stream/river temperature maximum positive daily rate of change points

    Data.gov (United States)

    U.S. Environmental Protection Agency — The shapefile contains points with associated observed and predicted August stream/river temperature maximum positive daily rate of change in New England based on a...

  14. New England observed and predicted July stream/river temperature maximum positive daily rate of change points

    Data.gov (United States)

    U.S. Environmental Protection Agency — The shapefile contains points with associated observed and predicted July stream/river temperature maximum positive daily rate of change in New England based on a...

  15. Robust Distributed Model Predictive Load Frequency Control of Interconnected Power System

    Directory of Open Access Journals (Sweden)

    Xiangjie Liu

    2013-01-01

    Full Text Available Considering the load frequency control (LFC of large-scale power system, a robust distributed model predictive control (RDMPC is presented. The system uncertainty according to power system parameter variation alone with the generation rate constraints (GRC is included in the synthesis procedure. The entire power system is composed of several control areas, and the problem is formulated as convex optimization problem with linear matrix inequalities (LMI that can be solved efficiently. It minimizes an upper bound on a robust performance objective for each subsystem. Simulation results show good dynamic response and robustness in the presence of power system dynamic uncertainties.

  16. Predictive power of theoretical modelling of the nuclear mean field: examples of improving predictive capacities

    Science.gov (United States)

    Dedes, I.; Dudek, J.

    2018-03-01

    We examine the effects of the parametric correlations on the predictive capacities of the theoretical modelling keeping in mind the nuclear structure applications. The main purpose of this work is to illustrate the method of establishing the presence and determining the form of parametric correlations within a model as well as an algorithm of elimination by substitution (see text) of parametric correlations. We examine the effects of the elimination of the parametric correlations on the stabilisation of the model predictions further and further away from the fitting zone. It follows that the choice of the physics case and the selection of the associated model are of secondary importance in this case. Under these circumstances we give priority to the relative simplicity of the underlying mathematical algorithm, provided the model is realistic. Following such criteria, we focus specifically on an important but relatively simple case of doubly magic spherical nuclei. To profit from the algorithmic simplicity we chose working with the phenomenological spherically symmetric Woods–Saxon mean-field. We employ two variants of the underlying Hamiltonian, the traditional one involving both the central and the spin orbit potential in the Woods–Saxon form and the more advanced version with the self-consistent density-dependent spin–orbit interaction. We compare the effects of eliminating of various types of correlations and discuss the improvement of the quality of predictions (‘predictive power’) under realistic parameter adjustment conditions.

  17. PREDICTION OF POWER GENERATION OF SMALL SCALE VERTICAL AXIS WIND TURBINE USING FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    Altab Hossain

    2009-01-01

    Full Text Available Renewable energy from the wind turbine has been focused for the alternative source of power generation due to the following advances of the of the wind turbine. Firstly, the wind turbine is highly efficient and eco-friendly. Secondly, the turbine has the ability to response for the changeable power generation based on the wind velocity and structural framework. However, the competitive efficiency of the wind turbine is necessary to successfully alternate the conventional power sources. The most relevant factor which affects the overall efficiency of the wind turbine is the wind velocity and the relative turbine dimensions. Artificial intelligence systems are widely used technology that can learn from examples and are able to deal with non-linear problems. Compared with traditional approach, fuzzy logic approach is more efficient for the representation, manipulation and utilization. Therefore, the primary purpose of this work was to investigate the relationship between wind turbine power generation and wind velocity, and to illustrate how fuzzy expert system might play an important role in prediction of wind turbine power generation. The main purpose of the measurement over the small scaled prototype vertical axis wind turbine for the wind velocity is to predict the performance of full scaled H-type vertical axis wind turbine. Prediction of power generation at the different wind velocities has been tested at the Thermal Laboratory of Faculty of Engineering, Universiti Industri Selangor (UNISEL and results concerning the daily prediction have been obtained.

  18. PREDICTION OF POWER GENERATION OF SMALL SCALE VERTICAL AXIS WIND TURBINE USING FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    Altab Md. Hossain

    2009-12-01

    Full Text Available Renewable energy from the wind turbine has been focused for the alternative source of power generation due to the following advances of the of the wind turbine. Firstly, the wind turbine is highly efficient and eco-friendly. Secondly, the turbine has the ability to response for the changeable power generation based on the wind velocity and structural framework. However, the competitive efficiency of the wind turbine is necessary to successfully alternate the conventional power sources. The most relevant factor which affects the overall efficiency of the wind turbine is the wind velocity and the relative turbine dimensions. Artificial intelligence systems are widely used technology that can learn from examples and are able to deal with non-linear problems. Compared with traditional approach, fuzzy logic approach is more efficient for the representation, manipulation and utilization. Therefore, the primary purpose of this work was to investigate the relationship between wind turbine power generation and wind velocity, and to illustrate how fuzzy expert system might play an important role in prediction of wind turbine power generation. The main purpose of the measurement over the small scaled prototype vertical axis wind turbine for the wind velocity is to predict the performance of full scaled H-type vertical axis wind turbine. Prediction of power generation at the different wind velocities has been tested at the Thermal Laboratory of Faculty of Engineering, Universiti Industri Selangor (UNISEL and results concerning the daily prediction have been obtained.

  19. Prognostic and Predictive Value of the 21-Gene Recurrence Score Assay in a Randomized Trial of Chemotherapy for Postmenopausal, Node-Positive, Estrogen Receptor-Positive Breast Cancer

    Science.gov (United States)

    Albain, Kathy S.; Barlow, William E.; Shak, Steven; Hortobagyi, Gabriel N.; Livingston, Robert B.; Yeh, I-Tien; Ravdin, Peter; Bugarini, Roberto; Baehner, Frederick L.; Davidson, Nancy E.; Sledge, George W.; Winer, Eric P.; Hudis, Clifford; Ingle, James N.; Perez, Edith A.; Pritchard, Kathleen I.; Shepherd, Lois; Gralow, Julie R.; Yoshizawa, Carl; Allred, D. Craig; Osborne, C. Kent; Hayes, Daniel F.

    2010-01-01

    SUMMARY Background The 21-gene Recurrence Score assay (RS) is prognostic for women with node-negative, estrogen receptor (ER)-positive breast cancer (BC) treated with tamoxifen. A low RS predicts little benefit of chemotherapy. For node-positive BC, we investigated whether RS was prognostic in women treated with tamoxifen alone and whether it identified those who might not benefit from anthracycline-based chemotherapy, despite higher recurrence risks. Methods The phase III trial S8814 for postmenopausal women with node-positive, ER-positive BC showed that CAF chemotherapy prior to tamoxifen (CAF-T) added survival benefit to tamoxifen alone. Optional tumor banking yielded specimens for RS determination by RT-PCR. We evaluated the effect of RS on disease-free survival (DFS) by treatment group (tamoxifen versus CAF-T) using Cox regression adjusting for number of positive nodes. Findings There were 367 specimens (40% of parent trial) with sufficient RNA (tamoxifen, 148; CAF-T, 219). The RS was prognostic in the tamoxifen arm (p=0.006). There was no CAF benefit in the low RS group (logrank p=0.97; HR=1.02, 95% CI (0.54,1.93)), but major DFS improvement for the high RS subset (logrank p=.03; HR=0.59, 95% CI (0.35, 1.01)), adjusting for number of positive nodes. The RS-by-treatment interaction was significant in the first 5 years (p=0.029), with no additional prediction beyond 5 years (p=0.58), though the cumulative benefit remained at 10 years. Results were similar for overall survival and BC-specific survival. Interpretation In this retrospective analysis, the RS is prognostic for tamoxifen-treated patients with positive nodes and predicts significant CAF benefit in tumors with a high RS. A low RS identifies women who may not benefit from anthracycline-based chemotherapy despite positive nodes. PMID:20005174

  20. K-Line Patterns’ Predictive Power Analysis Using the Methods of Similarity Match and Clustering

    Directory of Open Access Journals (Sweden)

    Lv Tao

    2017-01-01

    Full Text Available Stock price prediction based on K-line patterns is the essence of candlestick technical analysis. However, there are some disputes on whether the K-line patterns have predictive power in academia. To help resolve the debate, this paper uses the data mining methods of pattern recognition, pattern clustering, and pattern knowledge mining to research the predictive power of K-line patterns. The similarity match model and nearest neighbor-clustering algorithm are proposed for solving the problem of similarity match and clustering of K-line series, respectively. The experiment includes testing the predictive power of the Three Inside Up pattern and Three Inside Down pattern with the testing dataset of the K-line series data of Shanghai 180 index component stocks over the latest 10 years. Experimental results show that (1 the predictive power of a pattern varies a great deal for different shapes and (2 each of the existing K-line patterns requires further classification based on the shape feature for improving the prediction performance.

  1. Wind Power Ramp Events Prediction with Hybrid Machine Learning Regression Techniques and Reanalysis Data

    Directory of Open Access Journals (Sweden)

    Laura Cornejo-Bueno

    2017-11-01

    Full Text Available Wind Power Ramp Events (WPREs are large fluctuations of wind power in a short time interval, which lead to strong, undesirable variations in the electric power produced by a wind farm. Its accurate prediction is important in the effort of efficiently integrating wind energy in the electric system, without affecting considerably its stability, robustness and resilience. In this paper, we tackle the problem of predicting WPREs by applying Machine Learning (ML regression techniques. Our approach consists of using variables from atmospheric reanalysis data as predictive inputs for the learning machine, which opens the possibility of hybridizing numerical-physical weather models with ML techniques for WPREs prediction in real systems. Specifically, we have explored the feasibility of a number of state-of-the-art ML regression techniques, such as support vector regression, artificial neural networks (multi-layer perceptrons and extreme learning machines and Gaussian processes to solve the problem. Furthermore, the ERA-Interim reanalysis from the European Center for Medium-Range Weather Forecasts is the one used in this paper because of its accuracy and high resolution (in both spatial and temporal domains. Aiming at validating the feasibility of our predicting approach, we have carried out an extensive experimental work using real data from three wind farms in Spain, discussing the performance of the different ML regression tested in this wind power ramp event prediction problem.

  2. State-space model predictive control method for core power control in pressurized water reactor nuclear power stations

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Guo Xu; Wu, Jie; Zeng, Bifan; Wu, Wangqiang; Ma, Xiao Qian [School of Electric Power, South China University of Technology, Guangzhou (China); Xu, Zhibin [Electric Power Research Institute of Guangdong Power Grid Corporation, Guangzhou (China)

    2017-02-15

    A well-performed core power control to track load changes is crucial in pressurized water reactor (PWR) nuclear power stations. It is challenging to keep the core power stable at the desired value within acceptable error bands for the safety demands of the PWR due to the sensitivity of nuclear reactors. In this paper, a state-space model predictive control (MPC) method was applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, the MPC model, and quadratic programming (QP). The mathematical models of the reactor core were based on neutron dynamic models, thermal hydraulic models, and reactivity models. The MPC model was presented in state-space model form, and QP was introduced for optimization solution under system constraints. Simulations of the proposed state-space MPC control system in PWR were designed for control performance analysis, and the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.

  3. A novel method for predicting the power outputs of wave energy converters

    Science.gov (United States)

    Wang, Yingguang

    2018-03-01

    This paper focuses on realistically predicting the power outputs of wave energy converters operating in shallow water nonlinear waves. A heaving two-body point absorber is utilized as a specific calculation example, and the generated power of the point absorber has been predicted by using a novel method (a nonlinear simulation method) that incorporates a second order random wave model into a nonlinear dynamic filter. It is demonstrated that the second order random wave model in this article can be utilized to generate irregular waves with realistic crest-trough asymmetries, and consequently, more accurate generated power can be predicted by subsequently solving the nonlinear dynamic filter equation with the nonlinearly simulated second order waves as inputs. The research findings demonstrate that the novel nonlinear simulation method in this article can be utilized as a robust tool for ocean engineers in their design, analysis and optimization of wave energy converters.

  4. Prediction of Positions of Active Compounds Makes It Possible To Increase Activity in Fragment-Based Drug Development

    Directory of Open Access Journals (Sweden)

    Yoshifumi Fukunishi

    2011-05-01

    Full Text Available We have developed a computational method that predicts the positions of active compounds, making it possible to increase activity as a fragment evolution strategy. We refer to the positions of these compounds as the active position. When an active fragment compound is found, the following lead generation process is performed, primarily to increase activity. In the current method, to predict the location of the active position, hydrogen atoms are replaced by small side chains, generating virtual compounds. These virtual compounds are docked to a target protein, and the docking scores (affinities are examined. The hydrogen atom that gives the virtual compound with good affinity should correspond to the active position and it should be replaced to generate a lead compound. This method was found to work well, with the prediction of the active position being 2 times more efficient than random synthesis. In the current study, 15 examples of lead generation were examined. The probability of finding active positions among all hydrogen atoms was 26%, and the current method accurately predicted 60% of the active positions.

  5. The power within: The experimental manipulation of power interacts with trait BDD symptoms to predict interoceptive accuracy.

    Science.gov (United States)

    Kunstman, Jonathan W; Clerkin, Elise M; Palmer, Kateyln; Peters, M Taylar; Dodd, Dorian R; Smith, April R

    2016-03-01

    This study tested whether relatively low levels of interoceptive accuracy (IAcc) are associated with body dysmorphic disorder (BDD) symptoms. Additionally, given research indicating that power attunes individuals to their internal states, we sought to determine if state interoceptive accuracy could be improved through an experimental manipulation of power.. Undergraduate women (N = 101) completed a baseline measure of interoceptive accuracy and then were randomized to a power or control condition. Participants were primed with power or a neutral control topic and then completed a post-manipulation measure of state IAcc. Trait BDD symptoms were assessed with a self-report measure. Controlling for baseline IAcc, within the control condition, there was a significant inverse relationship between trait BDD symptoms and interoceptive accuracy. Continuing to control for baseline IAcc, within the power condition, there was not a significant relationship between trait BDD symptoms and IAcc, suggesting that power may have attenuated this relationship. At high levels of BDD symptomology, there was also a significant simple effect of experimental condition, such that participants in the power (vs. control) condition had better interoceptive accuracy. These results provide initial evidence that power may positively impact interoceptive accuracy among those with high levels of BDD symptoms.. This cross-sectional study utilized a demographically homogenous sample of women that reflected a broad range of symptoms; thus, although there were a number of participants reporting elevated BDD symptoms, these findings might not generalize to other populations or clinical samples. This study provides the first direct test of the relationship between trait BDD symptoms and IAcc, and provides preliminary evidence that among those with severe BDD symptoms, power may help connect individuals with their internal states. Future research testing the mechanisms linking BDD symptoms with IAcc, as

  6. Wind Power Grid Connected Capacity Prediction Using LSSVM Optimized by the Bat Algorithm

    Directory of Open Access Journals (Sweden)

    Qunli Wu

    2015-12-01

    Full Text Available Given the stochastic nature of wind, wind power grid-connected capacity prediction plays an essential role in coping with the challenge of balancing supply and demand. Accurate forecasting methods make enormous contribution to mapping wind power strategy, power dispatching and sustainable development of wind power industry. This study proposes a bat algorithm (BA–least squares support vector machine (LSSVM hybrid model to improve prediction performance. In order to select input of LSSVM effectively, Stationarity, Cointegration and Granger causality tests are conducted to examine the influence of installed capacity with different lags, and partial autocorrelation analysis is employed to investigate the inner relationship of grid-connected capacity. The parameters in LSSVM are optimized by BA to validate the learning ability and generalization of LSSVM. Multiple model sufficiency evaluation methods are utilized. The research results reveal that the accuracy improvement of the present approach can reach about 20% compared to other single or hybrid models.

  7. Model predictive control for power flows in networks with limited capacity

    DEFF Research Database (Denmark)

    Biegel, Benjamin; Stoustrup, Jakob; Bendtsen, Jan Dimon

    2012-01-01

    this problem can be formulated as an optimization problem, leading directly to the design of a model predictive controller. Using this scheme, we are able to incorporate predictions of future consumption and exploit knowledge of link limitations such that the intelligent consumers are utilized ahead of time......We consider an interconnected network of consumers powered through an electrical grid of limited capacity. A subset of the consumers are intelligent consumers and have the ability to store energy in a controllable fashion; they can be filled and emptied as desired under power and capacity...... limitations. We address the problem of maintaining power balance between production and consumption using the intelligent consumers to ensure smooth power consumption from the grid. Further, certain capacity limitations to the links interconnecting the consumers must be honored. In this paper, we show how...

  8. Automatic Power Control for Daily Load-following Operation using Model Predictive Control Method

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Keuk Jong; Kim, Han Gon [KH, Daejeon (Korea, Republic of)

    2009-10-15

    Under the circumstances that nuclear power occupies more than 50%, nuclear power plants are required to be operated on load-following operation in order to make the effective management of electric grid system and enhanced responsiveness to rapid changes in power demand. Conventional reactors such as the OPR1000 and APR1400 have a regulating system that controls the average temperature of the reactor core relation to the reference temperature. This conventional method has the advantages of proven technology and ease of implementation. However, this method is unsuitable for controlling the axial power shape, particularly the load following operation. Accordingly, this paper reports on the development of a model predictive control method which is able to control the reactor power and the axial shape index. The purpose of this study is to analyze the behavior of nuclear reactor power and the axial power shape by using a model predictive control method when the power is increased and decreased for a daily load following operation. The study confirms that deviations in the axial shape index (ASI) are within the operating limit.

  9. Radical prostatectomy and positive surgical margins: tumor volume and Gleason score predicts cancer outcome

    International Nuclear Information System (INIS)

    La Roca, Ricardo L.R. Felts de; Fonseca, Francisco Paula da; Cunha, Isabela Werneck da; Bezerra, Stephania Martins

    2013-01-01

    Introduction: positive surgical margins (PSMs) are common adverse factors to predict the outcome of a patient submitted to radical prostatectomy (PR). However, not all of these men will follow with biochemical (BCR) or clinical (CR) recurrence. Relationship between PSMs with these recurrent events has to be correlated with other clinicopathological findings in order to recognize more aggressive tumors in order to recommend complementary treatment to these selected patients. Materials and methods: we retrospectively reviewed the outcome of 228 patients submitted to open retropubic RP between March 1991 and June 2008, where 161 had and 67 did not have PSMs. Minimum follow-up time was considered 2 years after surgery. BCR was considered when PSA ≥ 0.2 ng/ml. CR was determined when clinical evidence of tumor appeared. Chi-square test was used to correlate clinical and pathologic variables with PSMs. The estimated 5-year risk of BCR and CR in presence of PSMs was determined using the Kaplan-Meier method and compared to log-rank tests. Results: from the total of 228 patients, 161 (71%) had PSMs, while 67 (29%) had negative surgical margins (NSMs). Prostatic circumferential margin was the most common (43.4%) site. Univariate analysis showed statistically significant (p < 0.001) associations between the presence of PSMs and BCR, but not with CR (p = 0.06). Among 161 patients with PSMs, 61 (37.8%) presented BCR, while 100 (62.8%) did not. Predicting progression-free survival for 5 years, BCR was correlated with pathological stage; Gleason score; pre-treatment PSA; tumor volume in specimen; capsular and perineural invasion; presence and number of PSMs. RC correlated only with angiolymphatic invasion and Gleason score. Considering univariate analyses the clinicopathological factors predicting BCR for 5 years, results statistically significant links with prostate weight; pre-treatment PSA; Gleason score; pathological stage; tumor volume; PSMs; capsular and perineural

  10. Radical prostatectomy and positive surgical margins: tumor volume and Gleason score predicts cancer outcome

    Energy Technology Data Exchange (ETDEWEB)

    La Roca, Ricardo L.R. Felts de, E-mail: Ricardo@delarocaurologia.com.br [Hospital do Cancer A.C. Camargo, Sao Paulo, SP (Brazil); Fonseca, Francisco Paula da, E-mail: fpf@uol.com.br [Hospital do Cancer A.C. Camargo, Sao Paulo, SP (Brazil). Divisao de Urologia. Dept. de Cirurgia Pelvica; Cunha, Isabela Werneck da; Bezerra, Stephania Martins, E-mail: iwerneck@gmail.com, E-mail: stephaniab@gmail.com [Hospital do Cancer A.C. Camargo, Sao Paulo, SP (Brazil). Dept. de Patologia

    2013-07-01

    Introduction: positive surgical margins (PSMs) are common adverse factors to predict the outcome of a patient submitted to radical prostatectomy (PR). However, not all of these men will follow with biochemical (BCR) or clinical (CR) recurrence. Relationship between PSMs with these recurrent events has to be correlated with other clinicopathological findings in order to recognize more aggressive tumors in order to recommend complementary treatment to these selected patients. Materials and methods: we retrospectively reviewed the outcome of 228 patients submitted to open retropubic RP between March 1991 and June 2008, where 161 had and 67 did not have PSMs. Minimum follow-up time was considered 2 years after surgery. BCR was considered when PSA {>=} 0.2 ng/ml. CR was determined when clinical evidence of tumor appeared. Chi-square test was used to correlate clinical and pathologic variables with PSMs. The estimated 5-year risk of BCR and CR in presence of PSMs was determined using the Kaplan-Meier method and compared to log-rank tests. Results: from the total of 228 patients, 161 (71%) had PSMs, while 67 (29%) had negative surgical margins (NSMs). Prostatic circumferential margin was the most common (43.4%) site. Univariate analysis showed statistically significant (p < 0.001) associations between the presence of PSMs and BCR, but not with CR (p = 0.06). Among 161 patients with PSMs, 61 (37.8%) presented BCR, while 100 (62.8%) did not. Predicting progression-free survival for 5 years, BCR was correlated with pathological stage; Gleason score; pre-treatment PSA; tumor volume in specimen; capsular and perineural invasion; presence and number of PSMs. RC correlated only with angiolymphatic invasion and Gleason score. Considering univariate analyses the clinicopathological factors predicting BCR for 5 years, results statistically significant links with prostate weight; pre-treatment PSA; Gleason score; pathological stage; tumor volume; PSMs; capsular and perineural

  11. Predicting Ambulance Time of Arrival to the Emergency Department Using Global Positioning System and Google Maps

    Science.gov (United States)

    Fleischman, Ross J.; Lundquist, Mark; Jui, Jonathan; Newgard, Craig D.; Warden, Craig

    2014-01-01

    Objective To derive and validate a model that accurately predicts ambulance arrival time that could be implemented as a Google Maps web application. Methods This was a retrospective study of all scene transports in Multnomah County, Oregon, from January 1 through December 31, 2008. Scene and destination hospital addresses were converted to coordinates. ArcGIS Network Analyst was used to estimate transport times based on street network speed limits. We then created a linear regression model to improve the accuracy of these street network estimates using weather, patient characteristics, use of lights and sirens, daylight, and rush-hour intervals. The model was derived from a 50% sample and validated on the remainder. Significance of the covariates was determined by p times recorded by computer-aided dispatch. We then built a Google Maps-based web application to demonstrate application in real-world EMS operations. Results There were 48,308 included transports. Street network estimates of transport time were accurate within 5 minutes of actual transport time less than 16% of the time. Actual transport times were longer during daylight and rush-hour intervals and shorter with use of lights and sirens. Age under 18 years, gender, wet weather, and trauma system entry were not significant predictors of transport time. Our model predicted arrival time within 5 minutes 73% of the time. For lights and sirens transports, accuracy was within 5 minutes 77% of the time. Accuracy was identical in the validation dataset. Lights and sirens saved an average of 3.1 minutes for transports under 8.8 minutes, and 5.3 minutes for longer transports. Conclusions An estimate of transport time based only on a street network significantly underestimated transport times. A simple model incorporating few variables can predict ambulance time of arrival to the emergency department with good accuracy. This model could be linked to global positioning system data and an automated Google Maps web

  12. Mammography performance in Oman: Review of factors influencing cancer yield and positive predictive value.

    Science.gov (United States)

    Taif, Sawsan; Tufail, Fatma; Alnuaimi, Ahmed Sameer

    2016-06-01

    The aim of this study is to assess mammography performance in Oman by estimating the breast cancer rate and the positive predictive value (PPV) with the influence of some variables. This cross-sectional study was conducted on mammograms done in one of the three main breast imaging centers in Oman between January 2008 and July 2012. Diagnostic and screening groups were identified and assessed separately. Rate of abnormal mammograms, rate of breast cancer and the PPV were estimated according to Breast Imaging Reporting and Data System (BIRADS) score, presence of breast lump and patient's age. Total of 653 mammograms were included, 254 diagnostic and 399 screening. Abnormal mammograms (BIRADS 4 and 5) form 31.9% of the diagnostic examinations compared with 6.8% of screening examinations. Breast cancer was present in 17.9% of the diagnostic compared with 1.0% of the screening group. The PPV of BIRADS 5 was 94.1%, and for BIRADS 4 was 37.1 and 26.7% for diagnostic and screening studies. Overall PPV for abnormal mammograms was 65.2% in the diagnostic and 26.7% in the screening group. Mammography PPV shows positive association with age (P = 0.039) while presence of breast lump has no significant effect on the PPV (P = 0.38). BIRADS 5 score was found to have a high cancer yield making it a strong predictor of cancer. Different results were obtained in the diagnostic compared with screening mammography with higher rates of abnormal mammograms and breast cancer. Mammography performance should be better in the older women. © 2014 Wiley Publishing Asia Pty Ltd.

  13. Offset-Free Direct Power Control of DFIG Under Continuous-Time Model Predictive Control

    DEFF Research Database (Denmark)

    Errouissi, Rachid; Al-Durra, Ahmed; Muyeen, S.M.

    2017-01-01

    This paper presents a robust continuous-time model predictive direct power control for doubly fed induction generator (DFIG). The proposed approach uses Taylor series expansion to predict the stator current in the synchronous reference frame over a finite time horizon. The predicted stator current...... is directly used to compute the required rotor voltage in order to minimize the difference between the actual stator currents and their references over the predictive time. However, as the proposed strategy is sensitive to parameter variations and external disturbances, a disturbance observer is embedded...... into the control loop to remove the steady-state error of the stator current. It turns out that the steady-state and the transient performances can be identified by simple design parameters. In this paper, the reference of the stator current is directly calculated from the desired stator active and reactive powers...

  14. Predicting lower body power from vertical jump prediction equations for loaded jump squats at different intensities in men and women.

    Science.gov (United States)

    Wright, Glenn A; Pustina, Andrew A; Mikat, Richard P; Kernozek, Thomas W

    2012-03-01

    The purpose of this study was to determine the efficacy of estimating peak lower body power from a maximal jump squat using 3 different vertical jump prediction equations. Sixty physically active college students (30 men, 30 women) performed jump squats with a weighted bar's applied load of 20, 40, and 60% of body mass across the shoulders. Each jump squat was simultaneously monitored using a force plate and a contact mat. Peak power (PP) was calculated using vertical ground reaction force from the force plate data. Commonly used equations requiring body mass and vertical jump height to estimate PP were applied such that the system mass (mass of body + applied load) was substituted for body mass. Jump height was determined from flight time as measured with a contact mat during a maximal jump squat. Estimations of PP (PP(est)) for each load and for each prediction equation were compared with criterion PP values from a force plate (PP(FP)). The PP(est) values had high test-retest reliability and were strongly correlated to PP(FP) in both men and women at all relative loads. However, only the Harman equation accurately predicted PP(FP) at all relative loads. It can therefore be concluded that the Harman equation may be used to estimate PP of a loaded jump squat knowing the system mass and peak jump height when more precise (and expensive) measurement equipment is unavailable. Further, high reliability and correlation with criterion values suggest that serial assessment of power production across training periods could be used for relative assessment of change by either of the prediction equations used in this study.

  15. Research on prediction of agricultural machinery total power based on grey model optimized by genetic algorithm

    Science.gov (United States)

    Xie, Yan; Li, Mu; Zhou, Jin; Zheng, Chang-zheng

    2009-07-01

    Agricultural machinery total power is an important index to reflex and evaluate the level of agricultural mechanization. It is the power source of agricultural production, and is the main factors to enhance the comprehensive agricultural production capacity expand production scale and increase the income of the farmers. Its demand is affected by natural, economic, technological and social and other "grey" factors. Therefore, grey system theory can be used to analyze the development of agricultural machinery total power. A method based on genetic algorithm optimizing grey modeling process is introduced in this paper. This method makes full use of the advantages of the grey prediction model and characteristics of genetic algorithm to find global optimization. So the prediction model is more accurate. According to data from a province, the GM (1, 1) model for predicting agricultural machinery total power was given based on the grey system theories and genetic algorithm. The result indicates that the model can be used as agricultural machinery total power an effective tool for prediction.

  16. Prediction of small hydropower plant power production in Himreen Lake dam (HLD using artificial neural network

    Directory of Open Access Journals (Sweden)

    Ali Thaeer Hammid

    2018-03-01

    Full Text Available In developing countries, the power production is properly less than the request of power or load, and sustaining a system stability of power production is a trouble quietly. Sometimes, there is a necessary development to the correct quantity of load demand to retain a system of power production steadily. Thus, Small Hydropower Plant (SHP includes a Kaplan turbine was verified to explore its applicability. This paper concentrates on applying on Artificial Neural Networks (ANNs by approaching of Feed-Forward, Back-Propagation to make performance predictions of the hydropower plant at the Himreen lake dam-Diyala in terms of net turbine head, flow rate of water and power production that data gathered during a research over a 10 year period. The model studies the uncertainties of inputs and output operation and there's a designing to network structure and then trained by means of the entire of 3570 experimental and observed data. Furthermore, ANN offers an analyzing and diagnosing instrument effectively to model performance of the nonlinear plant. The study suggests that the ANN may predict the performance of the plant with a correlation coefficient (R between the variables of predicted and observed output that would be higher than 0.96. Keywords: Himreen Lake Dam, Small Hydropower plants, Artificial Neural Networks, Feed forward-back propagation model, Generation system's prediction

  17. Using Unsupervised Machine Learning for Outlier Detection in Data to Improve Wind Power Production Prediction

    OpenAIRE

    Åkerberg, Ludvig

    2017-01-01

    The expansion of wind power for electrical energy production has increased in recent years and shows no signs of slowing down. This unpredictable source of energy has contributed to destabilization of the electrical grid causing the energy market prices to vary significantly on a daily basis. For energy producers and consumers to make good investments, methods have been developed to make predictions of wind power production. These methods are often based on machine learning were historical we...

  18. Modeling and Model Predictive Power and Rate Control of Wireless Communication Networks

    Directory of Open Access Journals (Sweden)

    Cunwu Han

    2014-01-01

    Full Text Available A novel power and rate control system model for wireless communication networks is presented, which includes uncertainties, input constraints, and time-varying delays in both state and control input. A robust delay-dependent model predictive power and rate control method is proposed, and the state feedback control law is obtained by solving an optimization problem that is derived by using linear matrix inequality (LMI techniques. Simulation results are given to illustrate the effectiveness of the proposed method.

  19. Comparison and validation of statistical methods for predicting power outage durations in the event of hurricanes.

    Science.gov (United States)

    Nateghi, Roshanak; Guikema, Seth D; Quiring, Steven M

    2011-12-01

    This article compares statistical methods for modeling power outage durations during hurricanes and examines the predictive accuracy of these methods. Being able to make accurate predictions of power outage durations is valuable because the information can be used by utility companies to plan their restoration efforts more efficiently. This information can also help inform customers and public agencies of the expected outage times, enabling better collective response planning, and coordination of restoration efforts for other critical infrastructures that depend on electricity. In the long run, outage duration estimates for future storm scenarios may help utilities and public agencies better allocate risk management resources to balance the disruption from hurricanes with the cost of hardening power systems. We compare the out-of-sample predictive accuracy of five distinct statistical models for estimating power outage duration times caused by Hurricane Ivan in 2004. The methods compared include both regression models (accelerated failure time (AFT) and Cox proportional hazard models (Cox PH)) and data mining techniques (regression trees, Bayesian additive regression trees (BART), and multivariate additive regression splines). We then validate our models against two other hurricanes. Our results indicate that BART yields the best prediction accuracy and that it is possible to predict outage durations with reasonable accuracy. © 2011 Society for Risk Analysis.

  20. A novel implementation of kNN classifier based on multi-tupled meteorological input data for wind power prediction

    International Nuclear Information System (INIS)

    Yesilbudak, Mehmet; Sagiroglu, Seref; Colak, Ilhami

    2017-01-01

    Highlights: • An accurate wind power prediction model is proposed for very short-term horizon. • The k-nearest neighbor classifier is implemented based on the multi-tupled inputs. • The variation of wind power prediction errors is evaluated in various aspects. • Our approach shows the superior prediction performance over the persistence method. - Abstract: With the growing share of wind power production in the electric power grids, many critical challenges to the grid operators have been emerged in terms of the power balance, power quality, voltage support, frequency stability, load scheduling, unit commitment and spinning reserve calculations. To overcome such problems, numerous studies have been conducted to predict the wind power production, but a small number of them have attempted to improve the prediction accuracy by employing the multidimensional meteorological input data. The novelties of this study lie in the proposal of an efficient and easy to implement very short-term wind power prediction model based on the k-nearest neighbor classifier (kNN), in the usage of wind speed, wind direction, barometric pressure and air temperature parameters as the multi-tupled meteorological inputs and in the comparison of wind power prediction results with respect to the persistence reference model. As a result of the achieved patterns, we characterize the variation of wind power prediction errors according to the input tuples, distance measures and neighbor numbers, and uncover the most influential and the most ineffective meteorological parameters on the optimization of wind power prediction results.

  1. Development of equipment reliability process using predictive technologies at Hamaoka Nuclear Power Station

    International Nuclear Information System (INIS)

    Taniguchi, Yuji; Sakuragi, Futoshi; Hamada, Seiichi

    2014-01-01

    Development of equipment reliability(ER) process, specifically for predictive maintenance (PdM) technologies integrated condition based maintenance (CBM) process, at Hamaoka Nuclear Power Station is introduced in this paper. Integration of predictive maintenance technologies such as vibration, oil analysis and thermo monitoring is more than important to establish strong maintenance strategies and to direct a specific technical development. In addition, a practical example of CBM is also presented to support the advantage of the idea. (author)

  2. Prediction of reflood behavior for tests with differing axial power shapes using WCOBRA/TRAC

    International Nuclear Information System (INIS)

    Bajorek, S.M.; Hochreiter, L.E.

    1991-01-01

    The rector core power shape can vary over the fuel cycle due to load follow, control rod movement, burnup effects and Xenon transients. a best estimate thermal-hydraulic code must be able to accurately predict the reflooding behavior for different axial power shapes in order to find the power shapes effects on the loss-of-coolant peak cladding temperature. Several different reflood heat transfer experiments have been performed at the same or similar PWR reflood conditions with different axial power shapes. These experiments have different rod diameters, were full length, 3.65 m (12 feet) in height, and had simple egg crate grids. The WCOBRA/TRAC code has been used to model several different tests from these three experiments to examine the code's capability to predict the reflood transient for different power shapes, with a consistent model and noding scheme. This paper describes these different experiments, their power shapes, and the test conditions. The WCOBRA/TRAC code is described as well as the noding scheme, and the calculated results will be compared in detail with the test data rod temperatures. An overall assessment of the code's predictions of these experiments is presented

  3. Application of Model Predictive Control for Active Load Management in a Distributed Power System with High Wind Penetration

    DEFF Research Database (Denmark)

    Zong, Yi; Kullmann, Daniel; Thavlov, Anders

    2012-01-01

    management. It also presents in detail how to implement a thermal model predictive controller (MPC) for the heaters' power consumption prediction in the PowerFlexHouse. It demonstrates that this MPC strategy can realize load shifting, and using good predictions in MPC-based control, a better matching...

  4. Positive predictive value of peptic ulcer diagnosis codes in the Danish National Patient Registry.

    Science.gov (United States)

    Viborg, Søren; Søgaard, Kirstine Kobberøe; Jepsen, Peter

    2017-01-01

    Diagnoses of peptic ulcer are registered in the Danish National Patient Registry (DNPR) for administrative as well as research purposes, but it is unknown whether the coding validity depends on the location of the ulcer. To validate the International Classification of Diseases, 10 th revision diagnosis codes of peptic ulcer in the DNPR by estimating positive predictive values (PPVs) for gastric and duodenal ulcer diagnoses. We identified all patients registered with a hospital discharge diagnosis of peptic ulcer from Aarhus University Hospital, Denmark, in 1995-2006. Among them, we randomly selected 200 who had an outpatient gastroscopy at the time of ulcer diagnosis. We reviewed the findings from these gastroscopies to confirm the presence of peptic ulcer and its location. We calculated PPVs and corresponding 95% confidence intervals (CIs) of gastric and duodenal ulcer diagnoses, using descriptions from the gastroscopic examinations as standard reference. In total, 182 records (91%) were available for review. The overall PPV of peptic ulcer diagnoses in DNPR was 95.6% (95% CI 91.5-98.1), with PPVs of 90.3% (95% CI 82.4-95.5) for gastric ulcer diagnoses, and 94.4% (95% CI 87.4-98.2) for duodenal ulcer diagnoses. PPVs were constant over time. The PPV of uncomplicated peptic ulcer diagnoses in the DNPR is high, and the location of the ulcers is registered correctly in most cases, indicating that the diagnoses are useful for research purposes.

  5. Nonlinear Fuzzy Model Predictive Control for a PWR Nuclear Power Plant

    Directory of Open Access Journals (Sweden)

    Xiangjie Liu

    2014-01-01

    Full Text Available Reliable power and temperature control in pressurized water reactor (PWR nuclear power plant is necessary to guarantee high efficiency and plant safety. Since the nuclear plants are quite nonlinear, the paper presents nonlinear fuzzy model predictive control (MPC, by incorporating the realistic constraints, to realize the plant optimization. T-S fuzzy modeling on nuclear power plant is utilized to approximate the nonlinear plant, based on which the nonlinear MPC controller is devised via parallel distributed compensation (PDC scheme in order to solve the nonlinear constraint optimization problem. Improved performance compared to the traditional PID controller for a TMI-type PWR is obtained in the simulation.

  6. Predictive Power Estimation Algorithm (PPEA--a new algorithm to reduce overfitting for genomic biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Jiangang Liu

    Full Text Available Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA, which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1 PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2 the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3 using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4 more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses.

  7. Attracted to power: challenge/threat and promotion/prevention focus differentially predict the attractiveness of group power

    Science.gov (United States)

    Scholl, Annika; Sassenrath, Claudia; Sassenberg, Kai

    2015-01-01

    Depending on their motivation, individuals prefer different group contexts for social interactions. The present research sought to provide more insight into this relationship. More specifically, we tested how challenge/threat and a promotion/prevention focus predict attraction to groups with high- or low-power. As such, we examined differential outcomes of threat and prevention focus as well as challenge and promotion focus that have often been regarded as closely related. According to regulatory focus, individuals should prefer groups that they expect to “feel right” for them to join: Low-power groups should be more attractive in a prevention (than a promotion) focus, as these groups suggest security-oriented strategies, which fit a prevention focus. High-power groups should be more attractive in a promotion (rather than a prevention) focus, as these groups are associated with promotion strategies fitting a promotion focus (Sassenberg et al., 2007). In contrast, under threat (vs. challenge), groups that allow individuals to restore their (perceived) lack of control should be preferred: Low-power groups should be less attractive under threat (than challenge) because they provide low resources which threatened individuals already perceive as insufficient and high-power groups might be more attractive under threat (than under challenge), because their high resources allow individuals to restore control. Two experiments (N = 140) supported these predictions. The attractiveness of a group often depends on the motivation to engage in what fits (i.e., prefer a group that feels right in the light of one’s regulatory focus). However, under threat the striving to restore control (i.e., prefer a group allowing them to change the status quo under threat vs. challenge) overrides the fit effect, which may in turn guide individuals’ behavior in social interactions. PMID:25904887

  8. Hydrogen-powered road vehicles. Positive and negative health effects of new fuel

    International Nuclear Information System (INIS)

    2008-09-01

    Because of the political, social and environmental problems associated with dependency on fossil fuels, there is considerable interest in alternative energy sources. Hydrogen is regarded as a promising option, particularly as a fuel for road vehicles. The Dutch Energy research Centre of the Netherlands (ECN) recently published a vision of the future, in which it suggested that by 2050 more than half of all cars in the Netherlands could be running on hydrogen. Assuming that the hydrogen is produced from renewable energy sources, migration to hydrogen-powered vehicles would also curb carbon dioxide emissions. In the United States, Japan and Europe, considerable public and private investment is therefore being made with a view to developing the technologies needed to make the creation of a hydrogen-based economy possible within a few decades. A switch to using hydrogen as the primary energy source for road vehicles would have far-reaching social consequences. As with all technological developments, opportunities would be created, but drawbacks would inevitably be encountered as well. Some of the disadvantages associated with hydrogen are already known, and are to some degree manageable. It is likely, however, that other drawbacks would come to light only once hydrogen-powered cars were actually in use With that thought in mind, and in view of the social significance of a possible transition to hydrogen, it was decided that the Health Council should assess the positive and negative effects that hydrogen use could have on public health. It is particularly important to make such an assessment at the present early stage in the development of hydrogen technologies, so that gaps in existing scientific knowledge may be identified and appropriate strategies may be developed for addressing such gaps. This report has been produced by the Health and Environment Surveillance Committee, which has special responsibility for the identification of important correlations between

  9. Public acceptance of nuclear power: some ethical issues. [Position statement of World Council of Churches

    Energy Technology Data Exchange (ETDEWEB)

    Abrecht, P; Arungu-Olende, S; Francis, J M; de Gaspar, D; Nashed, W; Nwosu, B C.E.; Rose, D J; Shinn, R L

    1977-12-01

    The World Council of Churches favors the widest possible discussion of nuclear power issues with the immediate purpose of raising the level of public awareness of the social, political, and technical risks that are inevitably associated with the large-scale and accelerating adoption of nuclear power generation. Its general position on nuclear energy is presented as follows. (A) The availability of nuclear energy is a controversial feature of today's world in that it affords the opportunity to provide a large fraction of the world's energy needs, counter-balanced by the exceptional nature of the risks involved, and other problems related to the employment of large-scale, capital-intensive high technology. (B) The maturity of the nuclear energy system is not yet such as to justify its worldwide application; the consequences of large-scale expansion of nuclear energy production are still relatively poorly understood and require further assessment. (C) The rights of access to nuclear technology should be preserved to the extent that the nuclear ''haves'' may not deny the nuclear ''have nots'' by any form of exclusive consultation. (D) There should be sufficient discussion of the factors governing access to nuclear technology to bring all nations to a new awareness of its risks and uncertainties as well as its opportunities; and the collective responsibility for monitoring and administering safeguards should reside with the IAEA rather than with individual governments. (E) Public confidence in the use of nuclear energy, seriously shaken in recent years, can be revived only by the widest possible public discussion of the technical options and of the value judgements underlying present patterns of energy consumption.

  10. Optimal level of continuous positive airway pressure: Auto-CPAP titration versus predictive formulas

    Directory of Open Access Journals (Sweden)

    Nashwa Abdel Wahab

    2017-04-01

    Conclusions: Predictive formulas might be useful as an alternative to autoCPAP. The model of predictive formula derived from the present small sample of Egyptian patients with OSAHS should be validated on a larger sample size.

  11. Rehabilitation after stroke: predictive power of Barthel Index versus a cognitive and a motor index

    DEFF Research Database (Denmark)

    Engberg, A; Bentzen, L; Garde, B

    1995-01-01

    The aim of the present study was to investigate the predictive power of ratings of Barthel Index at Day 40 post stroke, compared with and/or combined with simultaneous ratings from a mobility scale (EG motor index) and a rather simple cognitive test scale (CT50). The parameter to be individually...... predicted was the need for special living facilities and support at discharge from a rehabilitation hospital, as well as six months later; 53 stroke patients with age median 68 years were included in this prospective study. It was shown that a combination of Barthel Index and CT50 had a stronger predictive...

  12. Nuclear position in power generation sector - under the pressure of anti-global warming and power market reform

    International Nuclear Information System (INIS)

    Hayashi, Taizo

    2005-01-01

    The future structure surrounding fuel choice in power generation sector should be understood how to evaluate actual and potential merit and demerit both in economic and environmental aspects on nuclear power generation. That is i.e. nuclear can be understood as superior power source without GHGs and on the other hand, as unfavorable power source which might cause some critical dangers due to its hazardous radioactive nuclear waste. On this specific characteristic, this theme on fuel choice surrounding nuclear in power generation sector could be understood as a highly cultural problem as much as economic and political one. For instance, we can observe quite opposite direction with each other on nuclear power development in European countries like France and Finland on one hand and Germany and Sweden on the other hand. Looking at Asian countries, we also observe the very reality of high economic growth with rapid growth of electricity demand like China. What on earth, is it really possible without nuclear power source for such gigantic countries. I will develop my personal idea on nuclear power source based on Japanese experience towards successfully managing nuclear power technologies in the world, consisting of developing countries with growing economies and of advanced ones with rather matured nuclear technology under the pressure of environmentally restricted world order. My basic view point to discuss nuclear power problem has, conclusionally speaking, several aspects; The first one is in the relation with deregulation or liberalization of electricity market, which has been undergoing among such developed countries as OECD member countries i.e. USA, EU, Japan and other countries. Deregulation or liberalization of electricity market seems to be the inevitable process towards more matured market economy among developed countries group, and that process inevitably forces management of power companies towards more near sighted attitude if those companies are

  13. Prediction of requirements on labor force in the fuel and power generation sector

    International Nuclear Information System (INIS)

    Kaveckova, R.

    1990-01-01

    One of the aspects of socio-economic assessment of development is quantification of the expected requirements on the number of personnel. Predictions are discussed for the period before the year 2005 for solid fuel mining and treatment, gas production and bitumen mining, power and heat generation and also for the production of electricity and heat by nuclear power plants. They are based on an analysis of past development and the present state, on presumed implementation of various concept variants, on the type structure of nuclear power plants, on the rules of the electric power supply system, and also on foreign materials. It is expected that in 2005, nuclear power will employ 15,654 personnel. (M.D.). 4 tabs., 16 refs

  14. Assess and Predict Automatic Generation Control Performances for Thermal Power Generation Units Based on Modeling Techniques

    Science.gov (United States)

    Zhao, Yan; Yang, Zijiang; Gao, Song; Liu, Jinbiao

    2018-02-01

    Automatic generation control(AGC) is a key technology to maintain real time power generation and load balance, and to ensure the quality of power supply. Power grids require each power generation unit to have a satisfactory AGC performance, being specified in two detailed rules. The two rules provide a set of indices to measure the AGC performance of power generation unit. However, the commonly-used method to calculate these indices is based on particular data samples from AGC responses and will lead to incorrect results in practice. This paper proposes a new method to estimate the AGC performance indices via system identification techniques. In addition, a nonlinear regression model between performance indices and load command is built in order to predict the AGC performance indices. The effectiveness of the proposed method is validated through industrial case studies.

  15. Positioning Space Solar Power (SSP) as the Next Logical Step after the International Space Station (ISS)

    Science.gov (United States)

    Charania, A.

    2002-01-01

    At the end of the first decade of the 21st century, the International Space Station (ISS) will stand as a testament of the engineering capabilities of the international community. The choices for the next logical step for this community remain vast and conflicting: a Mars mission, moon colonization, Space Solar Power (SSP), etc. This examination focuses on positioning SSP as one such candidate for consideration. A marketing roadmap is presented that reveals the potential benefits of SSP to both the space community and the global populace at large. Recognizing that scientific efficiency itself has no constituency large enough to persuade entities to outlay funds for such projects, a holistic approach is taken to positioning SSP. This includes the scientific, engineering, exploratory, economic, political, and development capabilities of the system. SSP can be seen as both space exploration related and a resource project for undeveloped nations. Coupling these two non-traditional areas yields a broader constituency for the project that each one alone could generate. Space exploration is many times seen as irrelevant to the condition of the populace of the planet from which the money comes for such projects. When in this new century, billions of people on the planet still have never made a phone call or even have access to clean water, the origins of this skepticism can be understandable. An area of concern is the problem of not living up to the claims of overeager program marketers. Just as the ISS may never live up to the claims of its advocates in terms of space research, any SSP program must be careful in not promising utopian global solutions to any future energy starved world. Technically, SSP is a very difficult problem, even harder than creating the ISS, yet the promise it can hold for both space exploration and Earth development can lead to a renaissance of the relevance of space to the lives of the citizens of the world.

  16. Multiple-Swarm Ensembles: Improving the Predictive Power and Robustness of Predictive Models and Its Use in Computational Biology.

    Science.gov (United States)

    Alves, Pedro; Liu, Shuang; Wang, Daifeng; Gerstein, Mark

    2018-01-01

    Machine learning is an integral part of computational biology, and has already shown its use in various applications, such as prognostic tests. In the last few years in the non-biological machine learning community, ensembling techniques have shown their power in data mining competitions such as the Netflix challenge; however, such methods have not found wide use in computational biology. In this work, we endeavor to show how ensembling techniques can be applied to practical problems, including problems in the field of bioinformatics, and how they often outperform other machine learning techniques in both predictive power and robustness. Furthermore, we develop a methodology of ensembling, Multi-Swarm Ensemble (MSWE) by using multiple particle swarm optimizations and demonstrate its ability to further enhance the performance of ensembles.

  17. Research Design and the Predictive Power of Measures of Self-Efficacy

    Science.gov (United States)

    Moriarty, Beverley

    2014-01-01

    The purpose of this enquiry was to examine how research design impacts on the predictive power of measures of self-efficacy. Three cautions for designing research into self-efficacy drawn from the seminal work of Albert Bandura (1986) and a further caution proposed by the current author together form the analytical framework for this enquiry. For…

  18. Analyzing power in pp scattering at low energies: the Paris potential predictions

    International Nuclear Information System (INIS)

    Cote, J.; Pires, P.; Tourreil, R. de; Lacombe, M.; Loiseau, B.; Vinh Mau, R.

    1979-12-01

    Predictions of the Paris potential for the analyzing power in pp scattering at low energies are compared with recent high precision measurements at 6.14MeV and earlier measurements at 10 and 16MeV. Phase shift values are also presented and discussed in view of previous analyses

  19. Loneliness among University Students: Predictive Power of Sex Roles and Attachment Styles on Loneliness

    Science.gov (United States)

    Ilhan, Tahsin

    2012-01-01

    This study examined the predictive power of sex roles and attachment styles on loneliness. A total of 188 undergraduate students (114 female, and 74 male) from Gazi University completed the Bem Sex Role Inventory, UCLA Loneliness Scale, and Relationship Scales Questionnaire. Hierarchic Multiple Regression analysis and t-test were used to test…

  20. Rehabilitation after stroke: predictive power of Barthel Index versus a cognitive and a motor index

    DEFF Research Database (Denmark)

    Engberg, A; Bentzen, L; Garde, B

    1995-01-01

    The aim of the present study was to investigate the predictive power of ratings of Barthel Index at Day 40 post stroke, compared with and/or combined with simultaneous ratings from a mobility scale (EG motor index) and a rather simple cognitive test scale (CT50). The parameter to be individually...

  1. Model Predictive Current Control for High-Power Grid-Connected Converters with Output LCL Filter

    DEFF Research Database (Denmark)

    Delpino, Hernan Anres Miranda; Teodorescu, Remus; Rodriguez, Pedro

    2009-01-01

    A model predictive control strategy for a highpower, grid connected 3-level neutral clamped point converter is presented. Power losses constraints set a limit on commutation losses so reduced switching frequency is required, thus producing low frequency current harmonics. To reduce these harmonics...

  2. Getting data for prediction of electricity generation from photovoltaic power plants

    International Nuclear Information System (INIS)

    Majer, V.; Hejtmankova, P.

    2012-01-01

    This paper deals with the short term prediction of generated electricity from photovoltaic power plants. This way of electricity generation is strongly dependent on the actual weather, mainly solar radiation and temperature. In this paper the simple method for getting solar radiation data is presented. (Authors)

  3. Model Predictive Control for Flexible Power Consumption of Large-Scale Refrigeration Systems

    DEFF Research Database (Denmark)

    Shafiei, Seyed Ehsan; Stoustrup, Jakob; Rasmussen, Henrik

    2014-01-01

    A model predictive control (MPC) scheme is introduced to directly control the electrical power consumption of large-scale refrigeration systems. Deviation from the baseline of the consumption is corresponded to the storing and delivering of thermal energy. By virtue of such correspondence...

  4. Predicting speech intelligibility based on a correlation metric in the envelope power spectrum domain

    DEFF Research Database (Denmark)

    Relaño-Iborra, Helia; May, Tobias; Zaar, Johannes

    2016-01-01

    A speech intelligibility prediction model is proposed that combines the auditory processing front end of the multi-resolution speech-based envelope power spectrum model [mr-sEPSM; Jørgensen, Ewert, and Dau (2013). J. Acoust. Soc. Am. 134(1), 436–446] with a correlation back end inspired by the sh...

  5. Achievement Motivation Revisited: New Longitudinal Data to Demonstrate Its Predictive Power

    Science.gov (United States)

    Hustinx, Paul W. J.; Kuyper, Hans; van der Werf, Margaretha P. C.; Dijkstra, Pieternel

    2009-01-01

    During recent decades, the classical one-dimensional concept of achievement motivation has become less popular among motivation researchers. This study aims to revive the concept by demonstrating its predictive power using longitudinal data from two cohort samples, each with 20,000 Dutch secondary school students. Two measures of achievement…

  6. Achievement motivation revisited : New longitudinal data to demonstrate its predictive power

    NARCIS (Netherlands)

    Hustinx, P.W.J.; Kuyper, H.; Van der Werf, M.P.C.; Dijkstra, Pieternel

    2009-01-01

    During recent decades, the classical one-dimensional concept of achievement motivation has become less popular among motivation researchers. This study aims to revive the concept by demonstrating its predictive power using longitudinal data from two cohort samples, each with 20,000 Dutch secondary

  7. Explicit model predictive control applications in power systems: an AGC study for an isolated industrial system

    DEFF Research Database (Denmark)

    Jiang, Hao; Lin, Jin; Song, Yonghua

    2016-01-01

    Model predictive control (MPC), that can consider system constraints, is one of the most advanced control technology used nowadays. In power systems, MPC is applied in a way that an optimal control sequence is given every step by an online MPC controller. The main drawback is that the control law...

  8. Prediction of Full-Scale Propulsion Power using Artificial Neural Networks

    DEFF Research Database (Denmark)

    Pedersen, Benjamin Pjedsted; Larsen, Jan

    2009-01-01

    Full scale measurements of the propulsion power, ship speed, wind speed and direction, sea and air temperature from four different loading conditions, together with hind cast data of wind and sea properties; and noon report data has been used to train an Artificial Neural Network for prediction...

  9. Aggression in Primary Schools: The Predictive Power of the School and Home Environment

    Science.gov (United States)

    Kozina, Ana

    2015-01-01

    In this study, we analyse the predictive power of home and school environment-related factors for determining pupils' aggression. The multiple regression analyses are performed for fourth- and eighth-grade pupils based on the Trends in Mathematics and Science Study (TIMSS) 2007 (N = 8394) and TIMSS 2011 (N = 9415) databases for Slovenia. At the…

  10. The Prediction Power of Servant and Ethical Leadership Behaviours of Administrators on Teachers' Job Satisfaction

    Science.gov (United States)

    Güngör, Semra Kiranli

    2016-01-01

    The purpose of this study is to identify servant leadership and ethical leadership behaviors of administrators and the prediction power of these behaviors on teachers' job satisfaction according to the views of schoolteachers. This research, figured in accordance with the quantitative research processes. The target population of the research has…

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

    Science.gov (United States)

    Özdemir, Gökhan; Dalkiran, Esra

    2017-01-01

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

  12. Nuclear power plants and their position in the competitive generation industry of the USA

    International Nuclear Information System (INIS)

    Petroll, M.R.

    2000-01-01

    One effect to be observed in the USA is that power trading in the deregulated electricity sector initiates a 'comeback' of the nuclear power stations, reputed to be dead by anti-nuclear power policy followers. Quite to the contrary, growing competition in the generation industry and the resulting upward pressure on costs increasingly induce power generation companies to enter into competitive buying of nuclear power stations, which offer better availability and prolonged service life. The article gives the technical details and explains the economic reasons for this trend in an analysis comparing nuclear power generation with conventional or new non-nuclear generation technologies. (orig./CB) [de

  13. Optimized Extreme Learning Machine for Power System Transient Stability Prediction Using Synchrophasors

    Directory of Open Access Journals (Sweden)

    Yanjun Zhang

    2015-01-01

    Full Text Available A new optimized extreme learning machine- (ELM- based method for power system transient stability prediction (TSP using synchrophasors is presented in this paper. First, the input features symbolizing the transient stability of power systems are extracted from synchronized measurements. Then, an ELM classifier is employed to build the TSP model. And finally, the optimal parameters of the model are optimized by using the improved particle swarm optimization (IPSO algorithm. The novelty of the proposal is in the fact that it improves the prediction performance of the ELM-based TSP model by using IPSO to optimize the parameters of the model with synchrophasors. And finally, based on the test results on both IEEE 39-bus system and a large-scale real power system, the correctness and validity of the presented approach are verified.

  14. Is It Really Self-Control? Examining the Predictive Power of the Delay of Gratification Task

    Science.gov (United States)

    Duckworth, Angela L.; Tsukayama, Eli; Kirby, Teri A.

    2013-01-01

    This investigation tests whether the predictive power of the delay of gratification task (colloquially known as the “marshmallow test”) derives from its assessment of self-control or of theoretically unrelated traits. Among 56 school-age children in Study 1, delay time was associated with concurrent teacher ratings of self-control and Big Five conscientiousness—but not with other personality traits, intelligence, or reward-related impulses. Likewise, among 966 preschool children in Study 2, delay time was consistently associated with concurrent parent and caregiver ratings of self-control but not with reward-related impulses. While delay time in Study 2 was also related to concurrently measured intelligence, predictive relations with academic, health, and social outcomes in adolescence were more consistently explained by ratings of effortful control. Collectively, these findings suggest that delay task performance may be influenced by extraneous traits, but its predictive power derives primarily from its assessment of self-control. PMID:23813422

  15. Positive predictive value of albumin: globulin ratio for feline infectious peritonitis in a mid-western referral hospital population.

    Science.gov (United States)

    Jeffery, Unity; Deitz, Krysta; Hostetter, Shannon

    2012-12-01

    Low albumin to globulin ratio has been found previously to have a high positive predictive value for feline infectious peritonitis (FIP) in cats with clinical signs highly suggestive of the disease. However, FIP can have a more vague clinical presentation. This retrospective study found that the positive predictive value of an albumin:globulin (A:G) ratio of <0.8 and <0.6 was only 12.5% and 25%, respectively, in a group of 100 cats with one or more clinical signs consistent with FIP. The negative predictive value was 100% and 99% for an A:G ratio of <0.8 and A:G<0.6%, respectively. Therefore, when the prevalence of FIP is low, the A:G ratio is useful to rule out FIP but is not helpful in making a positive diagnosis of FIP.

  16. Quantitative Prediction of Power Loss for Damaged Photovoltaic Modules Using Electroluminescence

    Directory of Open Access Journals (Sweden)

    Timo Kropp

    2018-05-01

    Full Text Available Electroluminescence (EL is a powerful tool for the qualitative mapping of the electronic properties of solar modules, where electronic and electrical defects are easily detected. However, a direct quantitative prediction of electrical module performance purely based on electroluminescence images has yet to be accomplished. Our novel approach, called “EL power prediction of modules” (ELMO as presented here, used just two electroluminescence images to predict the electrical loss of mechanically damaged modules when compared to their original (data sheet power. First, using this method, two EL images taken at different excitation currents were converted into locally resolved (relative series resistance images. From the known, total applied voltage to the module, we were then able to calculate absolute series resistance values and the real distribution of voltages and currents. Then, we reconstructed the complete current/voltage curve of the damaged module. We experimentally validated and confirmed the simulation model via the characterization of a commercially available photovoltaic module containing 60 multicrystalline silicon cells, which were mechanically damaged by hail. Deviation between the directly measured and predicted current/voltage curve was less than 4.3% at the maximum power point. For multiple modules of the same type, the level of error dropped below 1% by calibrating the simulation. We approximated the ideality factor from a module with a known current/voltage curve and then expand the application to modules of the same type. In addition to yielding series resistance mapping, our new ELMO method was also capable of yielding parallel resistance mapping. We analyzed the electrical properties of a commercially available module, containing 72 monocrystalline high-efficiency back contact solar cells, which suffered from potential induced degradation. For this module, we predicted electrical performance with an accuracy of better

  17. Predictive coding of visual object position ahead of moving objects revealed by time-resolved EEG decoding.

    Science.gov (United States)

    Hogendoorn, Hinze; Burkitt, Anthony N

    2018-05-01

    Due to the delays inherent in neuronal transmission, our awareness of sensory events necessarily lags behind the occurrence of those events in the world. If the visual system did not compensate for these delays, we would consistently mislocalize moving objects behind their actual position. Anticipatory mechanisms that might compensate for these delays have been reported in animals, and such mechanisms have also been hypothesized to underlie perceptual effects in humans such as the Flash-Lag Effect. However, to date no direct physiological evidence for anticipatory mechanisms has been found in humans. Here, we apply multivariate pattern classification to time-resolved EEG data to investigate anticipatory coding of object position in humans. By comparing the time-course of neural position representation for objects in both random and predictable apparent motion, we isolated anticipatory mechanisms that could compensate for neural delays when motion trajectories were predictable. As well as revealing an early neural position representation (lag 80-90 ms) that was unaffected by the predictability of the object's trajectory, we demonstrate a second neural position representation at 140-150 ms that was distinct from the first, and that was pre-activated ahead of the moving object when it moved on a predictable trajectory. The latency advantage for predictable motion was approximately 16 ± 2 ms. To our knowledge, this provides the first direct experimental neurophysiological evidence of anticipatory coding in human vision, revealing the time-course of predictive mechanisms without using a spatial proxy for time. The results are numerically consistent with earlier animal work, and suggest that current models of spatial predictive coding in visual cortex can be effectively extended into the temporal domain. Copyright © 2018 Elsevier Inc. All rights reserved.

  18. Validation of the FAST skating protocol to predict aerobic power in ice hockey players.

    Science.gov (United States)

    Petrella, Nicholas J; Montelpare, William J; Nystrom, Murray; Plyley, Michael; Faught, Brent E

    2007-08-01

    Few studies have reported a sport-specific protocol to measure the aerobic power of ice hockey players using a predictive process. The purpose of our study was to validate an ice hockey aerobic field test on players of varying ages, abilities, and levels. The Faught Aerobic Skating Test (FAST) uses an on-ice continuous skating protocol on a course measuring 160 feet (48.8 m) using a CD to pace the skater with a beep signal to cross the starting line at each end of the course. The FAST incorporates the principle of increasing workload at measured time intervals during a continuous skating exercise. Step-wise multiple regression modelling was used to determine the estimate of aerobic power. Participants completed a maximal aerobic power test using a modified Bruce incremental treadmill protocol, as well as the on-ice FAST. Normative data were collected on 406 ice hockey players (291 males, 115 females) ranging in age from 9 to 25 y. A regression to predict maximum aerobic power was developed using body mass (kg), height (m), age (y), and maximum completed lengths of the FAST as the significant predictors of skating aerobic power (adjusted R2 = 0.387, SEE = 7.25 mL.kg-1.min-1, p < 0.0001). These results support the application of the FAST in estimating aerobic power among male and female competitive ice hockey players between the ages of 9 and 25 years.

  19. Method of critical power prediction based on film flow model coupled with subchannel analysis

    International Nuclear Information System (INIS)

    Tomiyama, Akio; Yokomizo, Osamu; Yoshimoto, Yuichiro; Sugawara, Satoshi.

    1988-01-01

    A new method was developed to predict critical powers for a wide variety of BWR fuel bundle designs. This method couples subchannel analysis with a liquid film flow model, instead of taking the conventional way which couples subchannel analysis with critical heat flux correlations. Flow and quality distributions in a bundle are estimated by the subchannel analysis. Using these distributions, film flow rates along fuel rods are then calculated with the film flow model. Dryout is assumed to occur where one of the film flows disappears. This method is expected to give much better adaptability to variations in geometry, heat flux, flow rate and quality distributions than the conventional methods. In order to verify the method, critical power data under BWR conditions were analyzed. Measured and calculated critical powers agreed to within ±7%. Furthermore critical power data for a tight-latticed bundle obtained by LeTourneau et al. were compared with critical powers calculated by the present method and two conventional methods, CISE correlation and subchannel analysis coupled with the CISE correlation. It was confirmed that the present method can predict critical powers more accurately than the conventional methods. (author)

  20. Loss of NOTCH2 Positively Predicts Survival in Subgroups of Human Glial Brain Tumors

    Science.gov (United States)

    Boulay, Jean-Louis; Miserez, André R.; Zweifel, Christian; Sivasankaran, Balasubramanian; Kana, Veronika; Ghaffari, Anthony; Luyken, Cordelia; Sabel, Michael; Zerrouqi, Abdessamad; Wasner, Morten; Meir, Erwin Van; Tolnay, Markus; Reifenberger, Guido; Merlo, Adrian

    2007-01-01

    The structural complexity of chromosome 1p centromeric region has been an obstacle for fine mapping of tumor suppressor genes in this area. Loss of heterozygosity (LOH) on chromosome 1p is associated with the longer survival of oligodendroglioma (OD) patients. To test the clinical relevance of 1p loss in glioblastomas (GBM) patients and identifiy the underlying tumor suppressor locus, we constructed a somatic deletion map on chromosome 1p in 26 OG and 118 GBM. Deletion hotspots at 4 microsatellite markers located at 1p36.3, 1p36.1, 1p22 and 1p11 defined 10 distinct haplotypes that were related to patient survival. We found that loss of 1p centromeric marker D1S2696 within NOTCH2 intron 12 was associated with favorable prognosis in OD (P = 0.0007) as well as in GBM (P = 0.0175), while 19q loss, concomitant with 1p LOH in OD, had no influence on GBM survival (P = 0.918). Assessment of the intra-chromosomal ratio between NOTCH2 and its 1q21 pericentric duplication N2N (N2/N2N-test) allowed delineation of a consistent centromeric breakpoint in OD that also contained a minimally lost area in GBM. OD and GBM showed distinct deletion patterns that converged to the NOTCH2 gene in both glioma subtypes. Moreover, the N2/N2N-test disclosed homozygous deletions of NOTCH2 in primary OD. The N2/N2N test distinguished OD from GBM with a specificity of 100% and a sensitivity of 97%. Combined assessment of NOTCH2 genetic markers D1S2696 and N2/N2N predicted 24-month survival with an accuracy (0.925) that is equivalent to histological classification combined with the D1S2696 status (0.954) and higher than current genetic evaluation by 1p/19q LOH (0.762). Our data propose NOTCH2 as a powerful new molecular test to detect prognostically favorable gliomas. PMID:17593975

  1. Loss of NOTCH2 positively predicts survival in subgroups of human glial brain tumors.

    Directory of Open Access Journals (Sweden)

    Jean-Louis Boulay

    Full Text Available The structural complexity of chromosome 1p centromeric region has been an obstacle for fine mapping of tumor suppressor genes in this area. Loss of heterozygosity (LOH on chromosome 1p is associated with the longer survival of oligodendroglioma (OD patients. To test the clinical relevance of 1p loss in glioblastomas (GBM patients and identifiy the underlying tumor suppressor locus, we constructed a somatic deletion map on chromosome 1p in 26 OG and 118 GBM. Deletion hotspots at 4 microsatellite markers located at 1p36.3, 1p36.1, 1p22 and 1p11 defined 10 distinct haplotypes that were related to patient survival. We found that loss of 1p centromeric marker D1S2696 within NOTCH2 intron 12 was associated with favorable prognosis in OD (P = 0.0007 as well as in GBM (P = 0.0175, while 19q loss, concomitant with 1p LOH in OD, had no influence on GBM survival (P = 0.918. Assessment of the intra-chromosomal ratio between NOTCH2 and its 1q21 pericentric duplication N2N (N2/N2N-test allowed delineation of a consistent centromeric breakpoint in OD that also contained a minimally lost area in GBM. OD and GBM showed distinct deletion patterns that converged to the NOTCH2 gene in both glioma subtypes. Moreover, the N2/N2N-test disclosed homozygous deletions of NOTCH2 in primary OD. The N2/N2N test distinguished OD from GBM with a specificity of 100% and a sensitivity of 97%. Combined assessment of NOTCH2 genetic markers D1S2696 and N2/N2N predicted 24-month survival with an accuracy (0.925 that is equivalent to histological classification combined with the D1S2696 status (0.954 and higher than current genetic evaluation by 1p/19q LOH (0.762. Our data propose NOTCH2 as a powerful new molecular test to detect prognostically favorable gliomas.

  2. Turning the pink cloud grey: Dampening of positive affect predicts postpartum depressive symptoms.

    NARCIS (Netherlands)

    Raes, Filip; Smets, Jorien; Wessel, Ineke; Van Den Eede, Filip; Nelis, Sabine; Franck, Erik; Jacquemyn, Yves; Hanssens, Myriam

    OBJECTIVE: Maladaptive response styles to negative affect have been shown to be associated with prospective (postpartum) depression. Whether maladaptive styles to positive affect are also critically involved is understudied, even though anhedonia (a correlate of low positive affectivity) is a

  3. Prediction of elders′ general health based on positive and negative perfectionism and type-D personality

    Directory of Open Access Journals (Sweden)

    Reza Karaminia

    2013-01-01

    Conclusions: Positive perfectionism decreases mental disorder of the elders by creating optimistic attitudes and enhancing social functions. On the other hand, type-D personality, unlike positive perfectionism, makes elders susceptible to physical illness and mental disorder.

  4. Error induced by the estimation of the corneal power and the effective lens position with a rotationally asymmetric refractive multifocal intraocular lens.

    Science.gov (United States)

    Piñero, David P; Camps, Vicente J; Ramón, María L; Mateo, Verónica; Pérez-Cambrodí, Rafael J

    2015-01-01

    To evaluate the prediction error in intraocular lens (IOL) power calculation for a rotationally asymmetric refractive multifocal IOL and the impact on this error of the optimization of the keratometric estimation of the corneal power and the prediction of the effective lens position (ELP). Retrospective study including a total of 25 eyes of 13 patients (age, 50 to 83y) with previous cataract surgery with implantation of the Lentis Mplus LS-312 IOL (Oculentis GmbH, Germany). In all cases, an adjusted IOL power (PIOLadj) was calculated based on Gaussian optics using a variable keratometric index value (nkadj) for the estimation of the corneal power (Pkadj) and on a new value for ELP (ELPadj) obtained by multiple regression analysis. This PIOLadj was compared with the IOL power implanted (PIOLReal) and the value proposed by three conventional formulas (Haigis, Hoffer Q and Holladay I). PIOLReal was not significantly different than PIOLadj and Holladay IOL power (P>0.05). In the Bland and Altman analysis, PIOLadj showed lower mean difference (-0.07 D) and limits of agreement (of 1.47 and -1.61 D) when compared to PIOLReal than the IOL power value obtained with the Holladay formula. Furthermore, ELPadj was significantly lower than ELP calculated with other conventional formulas (P<0.01) and was found to be dependent on axial length, anterior chamber depth and Pkadj. Refractive outcomes after cataract surgery with implantation of the multifocal IOL Lentis Mplus LS-312 can be optimized by minimizing the keratometric error and by estimating ELP using a mathematical expression dependent on anatomical factors.

  5. Error induced by the estimation of the corneal power and the effective lens position with a rotationally asymmetric refractive multifocal intraocular lens

    Directory of Open Access Journals (Sweden)

    David P. Piñero

    2015-06-01

    Full Text Available AIM:To evaluate the prediction error in intraocular lens (IOL power calculation for a rotationally asymmetric refractive multifocal IOL and the impact on this error of the optimization of the keratometric estimation of the corneal power and the prediction of the effective lens position (ELP.METHODS:Retrospective study including a total of 25 eyes of 13 patients (age, 50 to 83y with previous cataract surgery with implantation of the Lentis Mplus LS-312 IOL (Oculentis GmbH, Germany. In all cases, an adjusted IOL power (PIOLadj was calculated based on Gaussian optics using a variable keratometric index value (nkadj for the estimation of the corneal power (Pkadj and on a new value for ELP (ELPadj obtained by multiple regression analysis. This PIOLadj was compared with the IOL power implanted (PIOLReal and the value proposed by three conventional formulas (Haigis, Hoffer Q and Holladay Ⅰ.RESULTS:PIOLReal was not significantly different than PIOLadj and Holladay IOL power (P>0.05. In the Bland and Altman analysis, PIOLadj showed lower mean difference (-0.07 D and limits of agreement (of 1.47 and -1.61 D when compared to PIOLReal than the IOL power value obtained with the Holladay formula. Furthermore, ELPadj was significantly lower than ELP calculated with other conventional formulas (P<0.01 and was found to be dependent on axial length, anterior chamber depth and Pkadj.CONCLUSION:Refractive outcomes after cataract surgery with implantation of the multifocal IOL Lentis Mplus LS-312 can be optimized by minimizing the keratometric error and by estimating ELP using a mathematical expression dependent on anatomical factors.

  6. When the dark ones gain power : perceived position power strengthens the effect of supervisor Machiavellianism on abusive supervision in work teams.

    OpenAIRE

    Wisse, B.; Sleebos, E.

    2016-01-01

    Previous work has focused on the potential maladaptive consequences of the Dark Triad personality traits (i.e., Machiavellianism, psychopathy, and narcissism) in organizational contexts. This research builds upon this work, examining the influence of supervisor position power on the relationship between supervisor Dark Triad traits and abusive supervision in teams. Regression analysis on the data of 225 teams revealed that supervisor Machiavellianism is positively related to abusive supervisi...

  7. The Role of Positive Psychological Capital and the Family Function in Prediction of Happiness in high school students

    Directory of Open Access Journals (Sweden)

    F rashidi kochi

    2016-11-01

    Full Text Available The aim of this study was to determine the role of positive psychological capital and family functioning in predicting happiness among adolescence. Correlational research method was recruited to analyze the data. The sample comprised of 290 high Scholl students that selected by the convenience sampling method. In this research Snyder’s hope, Nezami and Colleagues self-efficacy, Scheier and Carver's optimism, McMaster's family functioning and Connor and Davidson's Resiliency and Oxford happiness questionnaire used to collect data. Pearson correlation and stepwise regression were used to analyze data. The finding showed that there was a significant positive relationship between family function components and positive psychological capital with happiness. The results of stepwise regression showed that roles, Resiliency, self-efficacy, optimism and emotion expression had significant and important role in predicting happiness. Totally, explained 35% of the variance happiness. In conclusion, these findings indicate the importance roles of family and positive psychological capital in adolescence's happiness.

  8. Attitude of public opinion to nuclear power, and reasons of prejudiced position towards it

    International Nuclear Information System (INIS)

    Vishnevs'kij, Yi.M.; Trofimenko, A.P.

    1998-01-01

    A review of events which have led to the public opposition to nuclear power is given. Arguments of 'Greens' and social structure of this movement are exposed. INIS Database was used for finding the main directions of works in nuclear power in the World and for their comparison with such directions in thermal power field. The results obtained demonstrate that the 'Greens' strongly exaggerate the nuclear hazards and do not pay due attention to environmental pollution from fossil-fuel power plants. Attitude of the population in Ukraine to nuclear power after Chernobyl accident is analysed and actions for public opinion balancing are proposed

  9. Silver linings and candles in the dark: differences among positive coping strategies in predicting subjective well-being.

    Science.gov (United States)

    Shiota, Michelle N

    2006-05-01

    Ideal coping strategies enhance positive aspects of well-being as well as reduce distress. Although researchers have identified several "positive coping" strategies, it is unclear which are most strongly associated with well-being or whether all strategies are equally appropriate for all kinds of stressors. Participants completed well-being measures, and described the most negative event of the day and their emotion regulation strategies for the next 7 days. Dispositional use of positive emotion-inducing coping strategies was most strongly associated with positive aspects of well-being. Use of positive coping did not decrease with increased objective stress during the week, and use of particular strategies was partly predicted by the types of stressors that were reported. Implications for theories of positive coping are discussed. 2006 APA, all rights reserved

  10. An Optimized Prediction Intervals Approach for Short Term PV Power Forecasting

    Directory of Open Access Journals (Sweden)

    Qiang Ni

    2017-10-01

    Full Text Available High quality photovoltaic (PV power prediction intervals (PIs are essential to power system operation and planning. To improve the reliability and sharpness of PIs, in this paper, a new method is proposed, which involves the model uncertainties and noise uncertainties, and PIs are constructed with a two-step formulation. In the first step, the variance of model uncertainties is obtained by using extreme learning machine to make deterministic forecasts of PV power. In the second stage, innovative PI-based cost function is developed to optimize the parameters of ELM and noise uncertainties are quantization in terms of variance. The performance of the proposed approach is examined by using the PV power and meteorological data measured from 1kW rooftop DC micro-grid system. The validity of the proposed method is verified by comparing the experimental analysis with other benchmarking methods, and the results exhibit a superior performance.

  11. Prediction of power ramp defects - development of a physically based model and evaluation of existing criteria

    International Nuclear Information System (INIS)

    Notley, M.J.F.; Kohn, E.

    2001-01-01

    Power-ramp induced fuel failure is not a problem in the present CANDU reactors. The current empirical correlations that define probability of failure do not agree one-with-another and do not allow extrapolation outside the database. A new methodology, based on physical processes, is presented and compared to data. The methodology calculates the pre-ramp sheath stress and the incremental stress during the ramp, and whether or not there is a defect is predicted based on a failure threshold stress. The proposed model confirms the deductions made by daSilva from an empirical 'fit' to data from the 1988 PNGS power ramp failure incident. It is recommended that daSilvas' correlation be used as reference for OPG (Ontario Power Generation) power reactor fuel, and that extrapolation be performed using the new model. (author)

  12. Prediction of the Main Engine Power of a New Container Ship at the Preliminary Design Stage

    Science.gov (United States)

    Cepowski, Tomasz

    2017-06-01

    The paper presents mathematical relationships that allow us to forecast the estimated main engine power of new container ships, based on data concerning vessels built in 2005-2015. The presented approximations allow us to estimate the engine power based on the length between perpendiculars and the number of containers the ship will carry. The approximations were developed using simple linear regression and multivariate linear regression analysis. The presented relations have practical application for estimation of container ship engine power needed in preliminary parametric design of the ship. It follows from the above that the use of multiple linear regression to predict the main engine power of a container ship brings more accurate solutions than simple linear regression.

  13. Testing predictive models of positive and negative affect with psychosocial, acculturation, and coping variables in a multiethnic undergraduate sample

    OpenAIRE

    Kuo, Ben CH; Kwantes, Catherine T

    2014-01-01

    Despite the prevalence and popularity of research on positive and negative affect within the field of psychology, there is currently little research on affect involving the examination of cultural variables and with participants of diverse cultural and ethnic backgrounds. To the authors’ knowledge, currently no empirical studies have comprehensively examined predictive models of positive and negative affect based specifically on multiple psychosocial, acculturation, and coping variables as pr...

  14. Predictive power of task orientation, general self-efficacy and self-determined motivation on fun and boredom

    Directory of Open Access Journals (Sweden)

    Lorena Ruiz-González

    2015-12-01

    Full Text Available Abstract The aim of this study was to test the predictive power of dispositional orientations, general self-efficacy and self-determined motivation on fun and boredom in physical education classes, with a sample of 459 adolescents between 13 and 18 with a mean age of 15 years (SD = 0.88. The adolescents responded to four Likert scales: Perceptions of Success Questionnaire, General Self-Efficacy Scale, Sport Motivation Scale and Intrinsic Satisfaction Questionnaire in Sport. The results showed the structural regression model showed that task orientation and general self-efficacy positively predicted self-determined motivation and this in turn positively predicted more fun and less boredom in physical education classes. Consequently, the promotion of an educational task-oriented environment where learners perceive their progress and make them feel more competent, will allow them to overcome the intrinsically motivated tasks, and therefore they will have more fun. Pedagogical implications for less boredom and more fun in physical education classes are discussed.

  15. Low baseline levels of NK cells may predict a positive response to ipilimumab in melanoma therapy.

    Science.gov (United States)

    Tietze, Julia K; Angelova, Daniela; Heppt, Markus V; Ruzicka, Thomas; Berking, Carola

    2017-07-01

    The introduction of immune checkpoint blockade (ICB) has been a breakthrough in the therapy of metastatic melanoma. The influence of ICB on T-cell populations has been studied extensively, but little is known about the effect on NK cells. In this study, we analysed the relative and absolute amounts of NK cells and of the subpopulations of CD56 dim and CD56 bright NK cells among the peripheral blood mononuclear cells (PBMCs) of 32 patients with metastatic melanoma before and under treatment with ipilimumab or pembrolizumab by flow cytometry. In 15 (47%) patients, an abnormal low amount of NK cells was found at baseline. Analysis of the subpopulations showed also low or normal baseline levels for CD56 dim NK cells, whereas the baseline levels of CD56 bright NK cells were either normal or abnormally high. The relative and absolute amounts of NK cells and of CD56 dim and CD56 bright NK cell subpopulations in patients with a normal baseline did not change under treatment. However, patients with a low baseline of NK cells and CD56 dim NK cells showed a significant increase in these immune cell subsets, but the amounts remained to be lower than the normal baseline. The amount of CD56 bright NK cells was unaffected by treatment. The baseline levels of NK cells were correlated with the number of metastatic organs. Their proportion increased, whereas the expression of NKG2D decreased significantly when more than one organ was affected by metastases. Low baseline levels of NK cells and CD56 dim NK cells as well as normal baseline levels of CD56 bright NK cells correlated significantly with a positive response to ipilimumab but not to pembrolizumab. Survival curves of patients with low amounts of CD56 dim NK cells treated with ipilimumab showed a trend to longer survival. Normal baseline levels of CD56 bright NK cells were significantly correlated with longer survival as compared to patients with high baseline levels. In conclusion, analysis of the amounts of total NK cells

  16. Simulation research on multivariable fuzzy model predictive control of nuclear power plant

    International Nuclear Information System (INIS)

    Su Jie

    2012-01-01

    To improve the dynamic control capabilities of the nuclear power plant, the algorithm of the multivariable nonlinear predictive control based on the fuzzy model was applied in the main parameters control of the nuclear power plant, including control structure and the design of controller in the base of expounding the math model of the turbine and the once-through steam generator. The simulation results show that the respond of the change of the gas turbine speed and the steam pressure under the algorithm of multivariable fuzzy model predictive control is faster than that under the PID control algorithm, and the output value of the gas turbine speed and the steam pressure under the PID control algorithm is 3%-5% more than that under the algorithm of multi-variable fuzzy model predictive control. So it shows that the algorithm of multi-variable fuzzy model predictive control can control the output of the main parameters of the nuclear power plant well and get better control effect. (author)

  17. Self-Powered Wireless Sensor Network for Automated Corrosion Prediction of Steel Reinforcement

    Directory of Open Access Journals (Sweden)

    Dan Su

    2018-01-01

    Full Text Available Corrosion is one of the key issues that affect the service life and hinders wide application of steel reinforcement. Moreover, corrosion is a long-term process and not visible for embedded reinforcement. Thus, this research aims at developing a self-powered smart sensor system with integrated innovative prediction module for forecasting corrosion process of embedded steel reinforcement. Vibration-based energy harvester is used to harvest energy for continuous corrosion data collection. Spatial interpolation module was developed to interpolate corrosion data at unmonitored locations. Dynamic prediction module is used to predict the long-term corrosion based on collected data. Utilizing this new sensor network, the corrosion process can be automated predicted and appropriate mitigation actions will be recommended accordingly.

  18. Application of neural networks to signal prediction in nuclear power plant

    International Nuclear Information System (INIS)

    Wan Joo Kim; Soon Heung Chang; Byung Ho Lee

    1993-01-01

    This paper describes the feasibility study of an artificial neural network for signal prediction. The purpose of signal prediction is to estimate the value of undetected next time step signal. As the prediction method, based on the idea of auto regression, a few previous signals are inputs to the artificial neural network and the signal value of next time step is estimated with the outputs of the network. The artificial neural network can be applied to the nonlinear system and answers in short time. The training algorithm is a modified backpropagation model, which can effectively reduce the training time. The target signal of the simulation is the steam generator water level, which is one of the important parameters in nuclear power plants. The simulation result shows that the predicted value follows the real trend well

  19. Multivariate power-law models for streamflow prediction in the Mekong Basin

    Directory of Open Access Journals (Sweden)

    Guillaume Lacombe

    2014-11-01

    New hydrological insights for the region: A combination of 3–6 explanatory variables – chosen among annual rainfall, drainage area, perimeter, elevation, slope, drainage density and latitude – is sufficient to predict a range of flow metrics with a prediction R-squared ranging from 84 to 95%. The inclusion of forest or paddy percentage coverage as an additional explanatory variable led to slight improvements in the predictive power of some of the low-flow models (lowest prediction R-squared = 89%. A physical interpretation of the model structure was possible for most of the resulting relationships. Compared to regional regression models developed in other parts of the world, this new set of equations performs reasonably well.

  20. Intraocular lens power selection and positioning with and without intraoperative aberrometry.

    Science.gov (United States)

    Hatch, Kathryn M; Woodcock, Emily C; Talamo, Jonathan H

    2015-04-01

    To determine the value of intraoperative aberrometry in cases of toric intraocular lens (IOL) implantation and positioning. In this non-randomized retrospective comparative trial, two groups of eyes underwent cataract extraction with toric IOL implantation: the aberrometry group (n = 37 eyes), where toric IOL power and alignment were determined before surgery with automated keratometry, standard optical biometry, and an online calculator and then refined using intraoperative aberrometry, and the toric calculator group (n = 27 eyes), where IOL selection was performed in a similar manner but without intraoperative aberrometry. The primary outcome measure was mean postoperative residual refractive astigmatism (RRA). Mean RRA measured at follow-up after surgery was 0.46 ± 0.42 and 0.68 ± 0.34 diopters (D) in the aberrometry and toric calculator groups, respectively (P = .0153). A 75% and 57% reduction in cylinder was noted between preoperative keratometric astigmatism and postoperative RRA in the aberrometry and toric calculator groups, respectively (P = .0027). RRA of 0.25 D or less, 0.50 D or less, 0.75 D or less, and 1.00 D or less was seen 38%, 78%, 86%, and 95% of the time, respectively, in the aberrometry group and 22%, 33%, 74%, and 89% of the time, respectively, in the toric calculator group. These data show that the chance of a patient being in a lower postoperative RRA range increased when intraoperative aberrometry was used (P = .0130). Patients undergoing cataract extraction with toric IOL placement aided by intraoperative aberrometry were 2.4 times more likely to have less than 0.50 D of RRA compared to standard methods. Copyright 2015, SLACK Incorporated.

  1. Are there any differences in power performance and morphological characteristics of Croatian adolescent soccer players according to the team position?

    Science.gov (United States)

    Sporis, Goran; Vucetić, Vlatko; Jovanović, Mario; Milanović, Zoran; Rucević, Marijan; Vuleta, Dinko

    2011-12-01

    The aim of the study was to analyze differences in power performance and morphological characteristics of young Croatian soccer players with respect to their team positions and to establish correlations between the power performance variables. Anthropometric characteristics and jumping and sprint performances were analyzed for 45 soccer players (age 14-15; mean body height 175.4 +/- 6.61 cm; body weight 63.6 +/- 8.06 kg) according to their team positions (defender, midfielder, forward). Pearsons coefficient of correlation was used to determine the relationship between the power performance variables. There were no significant differences (p > 0.05) in the power performance of players according to their team position. The only significant differences between players were in some of the anthropometric characteristics, such as height and weight linear relationship was determined between almost all the power performance variables. Since the players in this study were very young and their sports careers have not reached their peak performance, it is possible that their nominal team positions may change during their soccer careers.

  2. Incorporating Wind Power Forecast Uncertainties Into Stochastic Unit Commitment Using Neural Network-Based Prediction Intervals.

    Science.gov (United States)

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2015-09-01

    Penetration of renewable energy resources, such as wind and solar power, into power systems significantly increases the uncertainties on system operation, stability, and reliability in smart grids. In this paper, the nonparametric neural network-based prediction intervals (PIs) are implemented for forecast uncertainty quantification. Instead of a single level PI, wind power forecast uncertainties are represented in a list of PIs. These PIs are then decomposed into quantiles of wind power. A new scenario generation method is proposed to handle wind power forecast uncertainties. For each hour, an empirical cumulative distribution function (ECDF) is fitted to these quantile points. The Monte Carlo simulation method is used to generate scenarios from the ECDF. Then the wind power scenarios are incorporated into a stochastic security-constrained unit commitment (SCUC) model. The heuristic genetic algorithm is utilized to solve the stochastic SCUC problem. Five deterministic and four stochastic case studies incorporated with interval forecasts of wind power are implemented. The results of these cases are presented and discussed together. Generation costs, and the scheduled and real-time economic dispatch reserves of different unit commitment strategies are compared. The experimental results show that the stochastic model is more robust than deterministic ones and, thus, decreases the risk in system operations of smart grids.

  3. Predictive Factors for Nonsentinel Lymph Node Metastasis in Patients With Positive Sentinel Lymph Nodes After Neoadjuvant Chemotherapy: Nomogram for Predicting Nonsentinel Lymph Node Metastasis.

    Science.gov (United States)

    Ryu, Jai Min; Lee, Se Kyung; Kim, Ji Young; Yu, Jonghan; Kim, Seok Won; Lee, Jeong Eon; Han, Se Hwan; Jung, Yong Sik; Nam, Seok Jin

    2017-11-01

    Axillary lymph node (ALN) status is an important prognostic factor for breast cancer patients. With increasing numbers of patients undergoing neoadjuvant chemotherapy (NAC), issues concerning sentinel lymph node biopsy (SLNB) after NAC have emerged. We analyzed the clinicopathologic features and developed a nomogram to predict the possibility of nonsentinel lymph node (NSLN) metastases in patients with positive SLNs after NAC. A retrospective medical record review was performed of 140 patients who had had clinically positive ALNs at presentation, had a positive SLN after NAC on subsequent SLNB, and undergone axillary lymph node dissection (ALND) from 2008 to 2014. On multivariate stepwise logistic regression analysis, pathologic T stage, lymphovascular invasion, SLN metastasis size, and number of positive SLN metastases were independent predictors for NSLN metastases (P Samsung Medical Center NAC nomogram was developed to predict the likelihood of additional positive NSLNs. The Samsung Medical Center NAC nomogram could provide information to surgeons regarding whether to perform additional ALND when the permanent biopsy revealed positive findings, although the intraoperative SLNB findings were negative. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

    Science.gov (United States)

    Ibrahim, Wael Refaat Anis

    The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an

  5. When the dark ones gain power: Perceived position power strengthens the effect of supervisor Machiavellianism on abusive supervision in work teams

    NARCIS (Netherlands)

    Wisse, B.; Sleebos, E.

    2016-01-01

    Previous work has focused on the potential maladaptive consequences of the Dark Triad personality traits (i.e., Machiavellianism, psychopathy, and narcissism) in organizational contexts. This research builds upon this work, examining the influence of supervisor position power on the relationship

  6. A Model Predictive Control-Based Power Converter System for Oscillating Water Column Wave Energy Converters

    Directory of Open Access Journals (Sweden)

    Gimara Rajapakse

    2017-10-01

    Full Text Available Despite the predictability and availability at large scale, wave energy conversion (WEC has still not become a mainstream renewable energy technology. One of the main reasons is the large variations in the extracted power which could lead to instabilities in the power grid. In addition, maintaining the speed of the turbine within optimal range under changing wave conditions is another control challenge, especially in oscillating water column (OWC type WEC systems. As a solution to the first issue, this paper proposes the direct connection of a battery bank into the dc-link of the back-to-back power converter system, thereby smoothening the power delivered to the grid. For the second issue, model predictive controllers (MPCs are developed for the rectifier and the inverter of the back-to-back converter system aiming to maintain the turbine speed within its optimum range. In addition, MPC controllers are designed to control the battery current as well, in both charging and discharging conditions. Operations of the proposed battery direct integration scheme and control solutions are verified through computer simulations. Simulation results show that the proposed integrated energy storage and control solutions are capable of delivering smooth power to the grid while maintaining the turbine speed within its optimum range under varying wave conditions.

  7. Joint positions matter for ultrasound examination of RA patients-increased power Doppler signal in neutral versus flat position of hands.

    Science.gov (United States)

    Husic, Rusmir; Lackner, Angelika; Stradner, Martin H; Hermann, Josef; Dejaco, Christian

    2017-08-01

    Position of joints might influence the result of US examination in patients with RA. The purpose of this work was to compare grey-scale (GS) and power Doppler (PWD) findings obtained in neutral vs flat position of hands. A cross-sectional study of 42 RA patients with active disease. Two dimensional and 3D sonography of wrists and MCP joints were conducted in two different joint positions: neutral position, which is a slight flexion of the fingers with relaxed extensor muscles; and flat position, where all palm and volar sides of fingers touch the Table. Two dimensional GS synovitis (GSS) and PWD signals were scored semi-quantitatively (0-3). For 3D sonography, the percentage of PWD voxels within a region of interest was calculated. GSS was not quantified using 3D sonography. Compared with neutral position, 2D PWD signals disappeared in 28.3% of joints upon flattening. The median global 2D PWD score (sum of all PWD scores of an individual patient) decreased from 8 to 3 ( P < 0.001), and the global 3D PWD voxel score from 3.8 to 0.9 ( P < 0.001). The reduction of PWD scores was similar in all joints (2D: minus 50%, 3D: minus 66.4-80.1%). Inter- and intrareader agreement of PWD results was good (intraclass correlation coefficient: 0.75-0.82). In RA, a neutral position of the hands is linked to a higher sensitivity of 2D and 3D sonography in detecting PWD signals at wrists and MCP joints, compared with a flat position. Standardization of the scanning procedure is essential for obtaining comparable US results in RA patients in trials and clinical routines. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  8. Utility of formulas predicting the optimal nasal continuous positive airway pressure in a Greek population.

    Science.gov (United States)

    Schiza, Sophia E; Bouloukaki, Izolde; Mermigkis, Charalampos; Panagou, Panagiotis; Tzanakis, Nikolaos; Moniaki, Violeta; Tzortzaki, Eleni; Siafakas, Nikolaos M

    2011-09-01

    There have been reports that optimal CPAP pressure can be predicted from a previously derived formula, with the Hoffstein formula being the most accurate and accepted in the literature so far. However, the validation of this predictive model has not been applied in different clinical settings. Our aim was to compare both the Hoffstein prediction formula and a newly derived formula to the CPAP pressure setting assessed during a formal CPAP titration study. We prospectively studied 1,111 patients (871 males/240 females) with obstructive sleep apnea hypopnea syndrome (OSAHS) undergoing a CPAP titration procedure. In this large population sample, we tested the Hoffstein formula, utilizing body mass index (BMI), neck circumference and apnea/hypopnea index (AHI), and we compared it with our new formula that included not only AHI and BMI but also smoking history and gender adjustment. We found that using the Hoffstein prediction formula, successful prediction (predicted CPAP pressure within ±2 cm H(2)O compared to the finally assessed optimum CPAP pressure during titration) was accomplished in 873 patients (79%), with significant correlation between CPAP predicted pressure (CPAPpred(1)) and the optimum CPAP pressure (CPAPopt) [r = 0.364, p history and gender adjustment, successful prediction was accomplished in 1,057 patients (95%), with significant correlation between CPAP predicted pressure (CPAPpred(2)) and the CPAPopt (r = 0.392, p titration. It may also be possible to shorten CPAP titration and perhaps in selected cases to combine it with the initial diagnostic study.

  9. Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction

    Directory of Open Access Journals (Sweden)

    Jianzhou Wang

    2014-01-01

    Full Text Available Swarm intelligence (SI is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities. In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS as well as the singular spectrum analysis (SSA, time series, and machine learning methods are proposed to conduct short-term power load prediction. The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon. The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA and support vector regression (SVR in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance. Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.

  10. Load Torque Compensator for Model Predictive Direct Current Control in High Power PMSM Drive Systems

    DEFF Research Database (Denmark)

    Preindl, Matthias; Schaltz, Erik

    2011-01-01

    The widely used cascade speed and torque controllers have a limited control performance in most high power applications due to the low switching frequency of power electronic converters and the convenience to avoid speed overshoots and oscillations for lifetime considerations. Model Predictive...... Direct Current Control (MPDCC) leads to an increase of torque control performance taking into account the discrete nature of inverters but temporary offsets and poor responses to load torque variations are still issues in speed control. A load torque estimator is proposed in this paper in order...

  11. Distributed Model Predictive Control for Active Power Control of Wind Farm

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard

    2014-01-01

    This paper presents the active power control of a wind farm using the Distributed Model Predictive Controller (D- MPC) via dual decomposition. Different from the conventional centralized wind farm control, multiple objectives such as power reference tracking performance and wind turbine load can...... be considered to achieve a trade-off between them. Additionally, D- MPC is based on communication among the subsystems. Through the interaction among the neighboring subsystems, the global optimization could be achieved, which significantly reduces the computation burden. It is suitable for the modern large......-scale wind farm control....

  12. Validation of Lifetime Prediction of IGBT Modules Based on Linear Damage Accumulation by Means of Superimposed Power Cycling Tests

    DEFF Research Database (Denmark)

    Choi, Ui-Min; Ma, Ke; Blaabjerg, Frede

    2018-01-01

    In this paper, the lifetime prediction of power device modules based on the linear damage accumulation is studied in conjunction with simple mission profiles of converters. Superimposed power cycling conditions, which are called simple mission profiles in this paper, are made based on a lifetime ...... prediction of IGBT modules under power converter applications.......In this paper, the lifetime prediction of power device modules based on the linear damage accumulation is studied in conjunction with simple mission profiles of converters. Superimposed power cycling conditions, which are called simple mission profiles in this paper, are made based on a lifetime...... model in respect to junction temperature swing duration. This model has been built based on 39 power cycling test results of 600-V 30-A three-phase-molded IGBT modules. Six tests are performed under three superimposed power cycling conditions using an advanced power cycling test setup. The experimental...

  13. Observed fearlessness and positive parenting interact to predict childhood callous-unemotional behaviors among low-income boys.

    Science.gov (United States)

    Waller, Rebecca; Shaw, Daniel S; Hyde, Luke W

    2017-03-01

    Callous-unemotional behaviors identify children at risk for severe and chronic antisocial behavior. Research is needed to establish pathways from temperament and parenting factors that give rise to callous-unemotional behaviors, including interactions of positive versus harsh parenting with child fearlessness. Multimethod data, including parent reports and observations of parent and child behavior, were drawn from a prospective, longitudinal sample of low-income boys (N = 310) with assessments at 18, 24, and 42 months, and at ages 10-12 years old. Parent-reported callous-unemotional, oppositional, and attention-deficit factors were separable at 42 months. Callous-unemotional behaviors at 42 months predicted callous-unemotional behaviors at ages 10-12, accounting for earlier oppositional and attention-deficit behaviors and self-reported child delinquency at ages 10-12. Observations of fearlessness at 24 months predicted callous-unemotional behaviors at 42 months, but only when parents exhibited low observed levels of positive parenting. The interaction of fearlessness and low positive parenting indirectly predicted callous-unemotional behaviors at 10-12 via callous-unemotional behaviors at 42 months. Early fearlessness interacts with low positive parenting to predict early callous-unemotional behaviors, with lasting effects of this person-by-context interaction on callous-unemotional behaviors into late childhood. © 2016 Association for Child and Adolescent Mental Health.

  14. 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.

  15. A review on the young history of the wind power short-term prediction

    DEFF Research Database (Denmark)

    Costa, A.; Crespo, A.; Navarro, J.

    2008-01-01

    This paper makes a brief review on 30 years of history of the wind power short-term prediction, since the first ideas and sketches on the theme to the actual state of the art oil models and tools, giving emphasis to the most significant proposals and developments. The two principal lines of thought...... on short-term prediction (mathematical and physical) are indistinctly treated here and comparisons between models and tools are avoided, mainly because, on the one hand, a standard for a measure of performance is still not adopted and, on the other hand, it is very important that the data are exactly...

  16. PID and predictive control of electrical drives and power converters using MATLAB/Simulink

    CERN Document Server

    Wang, Liuping; Yoo, Dae; Gan, Lu; Ng, Ki

    2015-01-01

    A timely introduction to current research on PID and predictive control by one of the leading authors on the subject PID and Predictive Control of Electric Drives and Power Supplies using MATLAB/Simulink examines the classical control system strategies, such as PID control, feed-forward control and cascade control, which are widely used in current practice.  The authors share their experiences in actual design and implementation of the control systems on laboratory test-beds, taking the reader from the fundamentals through to more sophisticated design and analysis.    The book contains secti

  17. Predicting the radioactive contamination of the surroundings near a nuclear power plant

    Energy Technology Data Exchange (ETDEWEB)

    Khristova, M; Paskalev, Z

    1975-01-01

    Predicting the radioactive contamination requires determining the concentration of radioactive material emitted from the stack of a nuclear power plant into the air and deposited on the earth's surface. The main factors determining the degree of contamination are the distance from the stack, the wind velocity and air turbulence. Formulas are presented for predicting the amount of radioactivity as a function of the initial concentration of activity, the distance from the stack and the meteorological condition. Formulas are given for the maximum deposition of radioactive aerosols at a distance R from the stack under wet and dry condtions. 2 refs. (SJR)

  18. Comparison between the effects of positive noncatastrophic HMB ESD stress in n-channel and p-channel power MOSFET's

    Science.gov (United States)

    Zupac, Dragan; Kosier, Steven L.; Schrimpf, Ronald D.; Galloway, Kenneth F.; Baum, Keith W.

    1991-10-01

    The effect of noncatastrophic positive human body model (HBM) electrostatic discharge (ESD) stress on n-channel power MOSFETs is radically different from that on p-channel MOSFETs. In n-channel transistors, the stress causes negative shifts of the current-voltage characteristics indicative of positive charge trapping in the gate oxide. In p-channel transistors, the stress increases the drain-to-source leakage current, probably due to localized avalanche electron injection from the p-doped drain.

  19. Preliminary evaluation of an algorithm to minimize the power error selection of an aspheric intraocular lens by optimizing the estimation of the corneal power and the effective lens position

    Directory of Open Access Journals (Sweden)

    David P. Piñero

    2016-06-01

    Full Text Available AIM: To evaluate the refractive predictability achieved with an aspheric intraocular lens(IOLand to develop a preliminary optimized algorithm for the calculation of its power(PIOL.METHODS: This study included 65 eyes implanted with the aspheric IOL LENTIS L-313(Oculentis GmbHthat were divided into 2 groups: 12 eyes(8 patientswith PIOL≥23.0 D(group A, and 53 eyes(35 patientswith PIOLIOLadjwas calculated considering a variable refractive index for corneal power estimation, the refractive outcome obtained, and an adjusted effective lens position(ELPadjaccording to age and anatomical factors. RESULTS: Postoperative spherical equivalent ranged from -0.75 to +0.75 D and from -1.38 to +0.75 D in groups A and B, respectively. No statistically significant differences were found in groups A(P=0.64and B(P=0.82between PIOLadj and the IOL power implanted(PIOLReal. The Bland and Altman analysis showed ranges of agreement between PIOLadj and PIOLReal of +1.11 to -0.96 D and +1.14 to -1.18 D in groups A and B, respectively. Clinically and statistically significant differences were found between PIOLadj and PIOL obtained with Hoffer Q and Holladay I formulas(PCONCLUSION: The refractive predictability of cataract surgery with implantation of an aspheric IOL can be optimized using paraxial optics combined with linear algorithms to minimize the error associated to the estimation of corneal power and ELP.

  20. Doing Gender for Different Reasons: Why Gender Conformity Positively and Negatively Predicts Self-Esteem

    Science.gov (United States)

    Good, Jessica J.; Sanchez, Diana T.

    2010-01-01

    Past research has shown that valuing gender conformity is associated with both positive and negative consequences for self-esteem and positive affect. The current research (women, n= 226; men, n= 175) explored these conflicting findings by separating out investing in societal gender ideals from personally valuing one's gender identity ("private…

  1. Do positive or negative stressful events predict the development of new brain lesions in people with Multiple Sclerosis?

    Science.gov (United States)

    Burns, Michelle Nicole; Nawacki, Ewa; Kwasny, Mary J.; Pelletier, Daniel; Mohr, David C.

    2014-01-01

    Background Stressful life events have long been suspected to contribute to multiple sclerosis (MS) disease activity. The few studies examining the relationship between stressful events and neuroimaging markers have been small and inconsistent. This study examined whether different types of stressful events and perceived stress could predict development of brain lesions. Methods This was a secondary analysis of 121 patients with MS followed for 48 weeks during a randomized controlled trial comparing Stress Management Therapy for MS to a waitlist control. Patients underwent MRI’s every 8 weeks. Monthly, patients completed an interview measure assessing stressful life events, and self-report measures of perceived stress, anxiety, and depressive symptoms, which were used to predict the presence of gadolinium enhancing (Gd+) and T2 lesions on MRI’s 29–62 days later. Participants classified stressful events as positive or negative. Negative events were considered “major” if they involved physical threat or threat to the patient’s family structure, and “moderate” otherwise. Results Positive stressful events predicted decreased risk for subsequent Gd+ lesions in the control group (OR=.53 for each additional positive stressful event, 95% CI=.30–.91) and less risk for new or enlarging T2 lesions regardless of group assignment (OR=.74, 95% CI=.55–.99). Across groups, major negative stressful events predicted Gd+ lesions (OR=1.77, 95% CI=1.18–2.64) and new or enlarging T2 lesions (OR=1.57, 95% CI=1.11–2.23), while moderate negative stressful events, perceived stress, anxiety, and depressive symptoms did not. Conclusions Major negative stressful events predict increased risk for Gd+ and T2 lesions, while positive stressful events predict decreased risk. PMID:23680407

  2. Restricted conformal invariance in QCD and its predictive power for virtual two-photon processes

    CERN Document Server

    Müller, D

    1998-01-01

    The conformal algebra provides powerful constraints, which guarantee that renormalized conformally covariant operators exist in the hypothetical conformal limit of the theory, where the $\\beta$-function vanishes. Thus, in this limit also the conformally covariant operator product expansion on the light cone holds true. This operator product expansion has predictive power for two-photon processes in the generalized Bjorken region. Only the Wilson coefficients and the anomalous dimensions that are known from deep inelastic scattering are required for the prediction of all other two-photon processes in terms of the process-dependent off-diagonal expectation values of conformal operators. It is checked that the next-to-leading order calculations for the flavour non-singlet meson transition form factors are consistent with the corrections to the corresponding Wilson coefficients in deep inelasitic scattering.

  3. Positive predictive value estimates for cell-free noninvasive prenatal screening from data of a large referral genetic diagnostic laboratory.

    Science.gov (United States)

    Petersen, Andrea K; Cheung, Sau Wai; Smith, Janice L; Bi, Weimin; Ward, Patricia A; Peacock, Sandra; Braxton, Alicia; Van Den Veyver, Ignatia B; Breman, Amy M

    2017-12-01

    Since its debut in 2011, cell-free fetal DNA screening has undergone rapid expansion with respect to both utilization and coverage. However, conclusive data regarding the clinical validity and utility of this screening tool, both for the originally included common autosomal and sex-chromosomal aneuploidies as well as the more recently added chromosomal microdeletion syndromes, have lagged behind. Thus, there is a continued need to educate clinicians and patients about the current benefits and limitations of this screening tool to inform pre- and posttest counseling, pre/perinatal decision making, and medical risk assessment/management. The objective of this study was to determine the positive predictive value and false-positive rates for different chromosomal abnormalities identified by cell-free fetal DNA screening using a large data set of diagnostic testing results on invasive samples submitted to the laboratory for confirmatory studies. We tested 712 patient samples sent to our laboratory to confirm a cell-free fetal DNA screening result, indicating high risk for a chromosome abnormality. We compiled data from all cases in which the indication for confirmatory testing was a positive cell-free fetal DNA screen, including the common trisomies, sex chromosomal aneuploidies, microdeletion syndromes, and other large genome-wide copy number abnormalities. Testing modalities included fluorescence in situ hybridization, G-banded karyotype, and/or chromosomal microarray analysis performed on chorionic villus samples, amniotic fluid, or postnatally obtained blood samples. Positive predictive values and false-positive rates were calculated from tabulated data. The positive predictive values for trisomy 13, 18, and 21 were consistent with previous reports at 45%, 76%, and 84%, respectively. For the microdeletion syndrome regions, positive predictive values ranged from 0% for detection of Cri-du-Chat syndrome and Prader-Willi/Angelman syndrome to 14% for 1p36 deletion

  4. Steady-State Plant Model to Predict Hydroden Levels in Power Plant Components

    Energy Technology Data Exchange (ETDEWEB)

    Glatzmaier, Greg C.; Cable, Robert; Newmarker, Marc

    2017-06-27

    The National Renewable Energy Laboratory (NREL) and Acciona Energy North America developed a full-plant steady-state computational model that estimates levels of hydrogen in parabolic trough power plant components. The model estimated dissolved hydrogen concentrations in the circulating heat transfer fluid (HTF), and corresponding partial pressures within each component. Additionally for collector field receivers, the model estimated hydrogen pressure in the receiver annuli. The model was developed to estimate long-term equilibrium hydrogen levels in power plant components, and to predict the benefit of hydrogen mitigation strategies for commercial power plants. Specifically, the model predicted reductions in hydrogen levels within the circulating HTF that result from purging hydrogen from the power plant expansion tanks at a specified target rate. Our model predicted hydrogen partial pressures from 8.3 mbar to 9.6 mbar in the power plant components when no mitigation treatment was employed at the expansion tanks. Hydrogen pressures in the receiver annuli were 8.3 to 8.4 mbar. When hydrogen partial pressure was reduced to 0.001 mbar in the expansion tanks, hydrogen pressures in the receiver annuli fell to a range of 0.001 mbar to 0.02 mbar. When hydrogen partial pressure was reduced to 0.3 mbar in the expansion tanks, hydrogen pressures in the receiver annuli fell to a range of 0.25 mbar to 0.28 mbar. Our results show that controlling hydrogen partial pressure in the expansion tanks allows us to reduce and maintain hydrogen pressures in the receiver annuli to any practical level.

  5. Prediction and attendance of Angra 2 nuclear power plant cycle extension

    International Nuclear Information System (INIS)

    Dias, Amory; Ferreira Junior, Decio Brandes M.; Morgado, Mario Monteiro; Santos, Barbara Oliveira dos; Oliveira, Monica Georgia Nunes

    2007-01-01

    The Report Project Nuclear and Thermohydraulic (RPNT) of the Nuclear Power Plant Angra 2 previews extension of the cycle, using a feedback of core reactor reactivity, through the reduction of the moderator average temperature and power. In this phase, the reactor power remains almost invariable. Furthermore, the extension of cycle can be stretch after the limit of the temperature reduction has been reached, through of reactor power fall until the determined date for the end cycle and the start outage for the next cycle. The proposal of this work is to show the Power Plant results during the phase of moderator temperature reduction and to compare with the predict values obtained from reactivity balance calculation methodology used for the Reactor Physics. In general, the results of this work can collaborate for the extension behavior evaluation of the cycles of the Nuclear Power Plant 2, being used the procedure of cooling reduction average temperature, as well as, it will also collaborate for methodology qualification applied for the Reactor Physics during the reactivity balance calculation. (author)

  6. Artificial Neural Networks to Predict the Power Output of a PV Panel

    Directory of Open Access Journals (Sweden)

    Valerio Lo Brano

    2014-01-01

    Full Text Available The paper illustrates an adaptive approach based on different topologies of artificial neural networks (ANNs for the power energy output forecasting of photovoltaic (PV modules. The analysis of the PV module’s power output needed detailed local climate data, which was collected by a dedicated weather monitoring system. The Department of Energy, Information Engineering, and Mathematical Models of the University of Palermo (Italy has built up a weather monitoring system that worked together with a data acquisition system. The power output forecast is obtained using three different types of ANNs: a one hidden layer Multilayer perceptron (MLP, a recursive neural network (RNN, and a gamma memory (GM trained with the back propagation. In order to investigate the influence of climate variability on the electricity production, the ANNs were trained using weather data (air temperature, solar irradiance, and wind speed along with historical power output data available for the two test modules. The model validation was performed by comparing model predictions with power output data that were not used for the network's training. The results obtained bear out the suitability of the adopted methodology for the short-term power output forecasting problem and identified the best topology.

  7. Short-term load and wind power forecasting using neural network-based prediction intervals.

    Science.gov (United States)

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2014-02-01

    Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

  8. Comparison of Anthropometry and Lower Limb Power Qualities According to Different Levels and Ranking Position of Competitive Surfers.

    Science.gov (United States)

    Fernandez-Gamboa, Iosu; Yanci, Javier; Granados, Cristina; Camara, Jesus

    2017-08-01

    Fernandez-Gamboa, I, Yanci, J, Granados, C, and Camara, J. Comparison of anthropometry and lower limb power qualities according to different levels and ranking position of competitive surfers. J Strength Cond Res 31(8): 2231-2237, 2017-The aim of this study was to compare competitive surfers' lower limb power output depending on their competitive level, and to evaluate the association between competition rankings. Twenty competitive surfers were divided according to the competitive level as follows: international (INT) or national (NAT), and competitive ranking (RANK1-50 or RANK51-100). Vertical jump and maximal peak power of the lower limbs were measured. No differences were found between INT and NAT surfers in the anthropometric variables, in the vertical jump, or in lower extremity power; although the NAT group had higher levels on the elasticity index, squat jumps (SJs), and counter movement jumps (CMJs) compared with the INT group. The RANK1-50 group had a lower biceps skinfold (p RANK1-50 group. Moderate to large significant correlations were obtained between the surfers' ranking position and some skinfolds, the sum of skinfolds, and vertical jump. Results demonstrate that surfers' physical performance seems to be an accurate indicator of ranking positioning, also revealing that vertical jump capacity and anthropometric variables play an important role in their competitive performance, which may be important when considering their power training.

  9. Common variant in OXTR predicts growth in positive emotions from loving-kindness training.

    Science.gov (United States)

    Isgett, Suzannah F; Algoe, Sara B; Boulton, Aaron J; Way, Baldwin M; Fredrickson, Barbara L

    2016-11-01

    Ample research suggests that social connection reliably generates positive emotions. Oxytocin, a neuropeptide implicated in social cognition and behavior, is one biological mechanism that may influence an individual's capacity to extract positive emotions from social contexts. Because variation in certain genes may indicate underlying neurobiological differences, we tested whether several SNPs in two genes related to oxytocin signaling would show effects on positive emotions that were context-specific, depending on sociality. For six weeks, a sample of mid-life adults (N=122) participated in either socially-focused loving-kindness training or mindfulness training. During this timespan they reported their positive emotions daily. Five SNPs within OXTR and CD38 were assayed, and each was tested for its individual effect on daily emotions. The hypothesized three-way interaction between time, training type, and genetic variability emerged: Individuals homozygous for the G allele of OXTR rs1042778 experienced gains in daily positive emotions from loving-kindness training, whereas individuals with the T allele did not experience gains in positive emotions with either training. These findings are among the first to show how genetic differences in oxytocin signaling may influence an individual's capacity to experience positive emotions as a result of a socially-focused intervention. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Comparison of Comet Enflow and VA One Acoustic-to-Structure Power Flow Predictions

    Science.gov (United States)

    Grosveld, Ferdinand W.; Schiller, Noah H.; Cabell, Randolph H.

    2010-01-01

    Comet Enflow is a commercially available, high frequency vibroacoustic analysis software based on the Energy Finite Element Analysis (EFEA). In this method the same finite element mesh used for structural and acoustic analysis can be employed for the high frequency solutions. Comet Enflow is being validated for a floor-equipped composite cylinder by comparing the EFEA vibroacoustic response predictions with Statistical Energy Analysis (SEA) results from the commercial software program VA One from ESI Group. Early in this program a number of discrepancies became apparent in the Enflow predicted response for the power flow from an acoustic space to a structural subsystem. The power flow anomalies were studied for a simple cubic, a rectangular and a cylindrical structural model connected to an acoustic cavity. The current investigation focuses on three specific discrepancies between the Comet Enflow and the VA One predictions: the Enflow power transmission coefficient relative to the VA One coupling loss factor; the importance of the accuracy of the acoustic modal density formulation used within Enflow; and the recommended use of fast solvers in Comet Enflow. The frequency region of interest for this study covers the one-third octave bands with center frequencies from 16 Hz to 4000 Hz.

  11. Adaptive on-line prediction of the available power of lithium-ion batteries

    Science.gov (United States)

    Waag, Wladislaw; Fleischer, Christian; Sauer, Dirk Uwe

    2013-11-01

    In this paper a new approach for prediction of the available power of a lithium-ion battery pack is presented. It is based on a nonlinear battery model that includes current dependency of the battery resistance. It results in an accurate power prediction not only at room temperature, but also at lower temperatures at which the current dependency is substantial. The used model parameters are fully adaptable on-line to the given state of the battery (state of charge, state of health, temperature). This on-line adaption in combination with an explicit consideration of differences between characteristics of individual cells in a battery pack ensures an accurate power prediction under all possible conditions. The proposed trade-off between the number of used cell parameters and the total accuracy as well as the optimized algorithm results in a real-time capability of the method, which is demonstrated on a low-cost 16 bit microcontroller. The verification tests performed on a software-in-the-loop test bench system with four 40 Ah lithium-ion cells show promising results.

  12. Neural Network Ensemble Based Approach for 2D-Interval Prediction of Solar Photovoltaic Power

    Directory of Open Access Journals (Sweden)

    Mashud Rana

    2016-10-01

    Full Text Available Solar energy generated from PhotoVoltaic (PV systems is one of the most promising types of renewable energy. However, it is highly variable as it depends on the solar irradiance and other meteorological factors. This variability creates difficulties for the large-scale integration of PV power in the electricity grid and requires accurate forecasting of the electricity generated by PV systems. In this paper we consider 2D-interval forecasts, where the goal is to predict summary statistics for the distribution of the PV power values in a future time interval. 2D-interval forecasts have been recently introduced, and they are more suitable than point forecasts for applications where the predicted variable has a high variability. We propose a method called NNE2D that combines variable selection based on mutual information and an ensemble of neural networks, to compute 2D-interval forecasts, where the two interval boundaries are expressed in terms of percentiles. NNE2D was evaluated for univariate prediction of Australian solar PV power data for two years. The results show that it is a promising method, outperforming persistence baselines and other methods used for comparison in terms of accuracy and coverage probability.

  13. Long-term field test of solar PV power generation using one-axis 3-position sun tracker

    KAUST Repository

    Huang, B.J.; Ding, W.L.; Huang, Y.C.

    2011-01-01

    The 1 axis-3 position (1A-3P) sun tracking PV was built and tested to measure the daily and long-term power generation of the solar PV system. A comparative test using a fixed PV and a 1A-3P tracking PV was carried out with two identical stand

  14. Combined Active and Reactive Power Control of Wind Farms based on Model Predictive Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Wang, Jianhui

    2017-01-01

    This paper proposes a combined wind farm controller based on Model Predictive Control (MPC). Compared with the conventional decoupled active and reactive power control, the proposed control scheme considers the significant impact of active power on voltage variations due to the low X=R ratio...... of wind farm collector systems. The voltage control is improved. Besides, by coordination of active and reactive power, the Var capacity is optimized to prevent potential failures due to Var shortage, especially when the wind farm operates close to its full load. An analytical method is used to calculate...... the sensitivity coefficients to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both normal and emergency conditions. A wind farm with 20 wind turbines was used to verify the proposed combined control scheme....

  15. Hierarchical model-based predictive control of a power plant portfolio

    DEFF Research Database (Denmark)

    Edlund, Kristian; Bendtsen, Jan Dimon; Jørgensen, John Bagterp

    2011-01-01

    One of the main difficulties in large-scale implementation of renewable energy in existing power systems is that the production from renewable sources is difficult to predict and control. For this reason, fast and efficient control of controllable power producing units – so-called “portfolio...... design for power system portfolio control, which aims specifically at meeting these demands.The design involves a two-layer hierarchical structure with clearly defined interfaces that facilitate an object-oriented implementation approach. The same hierarchical structure is reflected in the underlying...... optimisation problem, which is solved using Dantzig–Wolfe decomposition. This decomposition yields improved computational efficiency and better scalability compared to centralised methods.The proposed control scheme is compared to an existing, state-of-the-art portfolio control system (operated by DONG Energy...

  16. How Many Model Evaluations Are Required To Predict The AEP Of A Wind Power Plant?

    DEFF Research Database (Denmark)

    Murcia Leon, Juan Pablo; Réthoré, Pierre-Elouan; Natarajan, Anand

    2015-01-01

    (AEP) predictions expensive. The objective of the present paper is to minimize the number of model evaluations required to capture the wind power plant's AEP using stationary wind farm flow models. Polynomial chaos techniques are proposed based on arbitrary Weibull distributed wind speed and Von Misses...... distributed wind direction. The correlation between wind direction and wind speed are captured by defining Weibull-parameters as functions of wind direction. In order to evaluate the accuracy of these methods the expectation and variance of the wind farm power distributions are compared against...... the traditional binning method with trapezoidal and Simpson's integration rules. The wind farm flow model used in this study is the semi-empirical wake model developed by Larsen [1]. Three test cases are studied: a single turbine, a simple and a real offshore wind power plant. A reduced number of model...

  17. Power Prediction Model for Turning EN-31 Steel Using Response Surface Methodology

    Directory of Open Access Journals (Sweden)

    M. Hameedullah

    2010-01-01

    Full Text Available Power consumption in turning EN-31 steel (a material that is most extensively used in automotive industry with tungstencarbide tool under different cutting conditions was experimentally investigated. The experimental runs were planned accordingto 24+8 added centre point factorial design of experiments, replicated thrice. The data collected was statisticallyanalyzed using Analysis of Variance technique and first order and second order power consumption prediction models weredeveloped by using response surface methodology (RSM. It is concluded that second-order model is more accurate than thefirst-order model and fit well with the experimental data. The model can be used in the automotive industries for decidingthe cutting parameters for minimum power consumption and hence maximum productivity

  18. Power-Controlled MAC Protocols with Dynamic Neighbor Prediction for Ad hoc Networks

    Institute of Scientific and Technical Information of China (English)

    LI Meng; ZHANG Lin; XIAO Yong-kang; SHAN Xiu-ming

    2004-01-01

    Energy and bandwidth are the scarce resources in ad hoc networks because most of the mobile nodes are battery-supplied and share the exclusive wireless medium. Integrating the power control into MAC protocol is a promising technique to fully exploit these precious resources of ad hoc wireless networks. In this paper, a new intelligent power-controlled Medium Access Control (MAC) (iMAC) protocol with dynamic neighbor prediction is proposed. Through the elaborate design of the distributed transmit-receive strategy of mobile nodes, iMAC greatly outperforms the prevailing IEEE 802.11 MAC protocols in not only energy conservation but also network throughput. Using the Dynamic Neighbor Prediction (DNP), iMAC performs well in mobile scenes. To the best of our knowledge, iMAC is the first protocol that considers the performance deterioration of power-controlled MAC protocols in mobile scenes and then proposes a solution. Simulation results indicate that DNP is important and necessary for power-controlled MAC protocols in mobile ad hoc networks.

  19. A Study on the Tracking and Position Predictions of Artificial Satellite (II

    Directory of Open Access Journals (Sweden)

    Pil-Ho Park

    1991-06-01

    Full Text Available We developed a software system called IODS (ISSA Orbit Determination System, which can predict the orbit of arbitrary artificial satellite using the numerical method. For evaluating the orbit prediction accuracy of IODS, the orbital data predicted for the meteorological satellite NOAA-11 and the stationary satellite INTELSAT-V are intercompared with those tracked at the Central Bureau of Meteorology and the Kum-San Satellites Communication Station. And the Perturbation affecting the orbit of these artificial satellites are quantitatively analyzed. The orbital variation and the eclipse phenomina due to the earth shadow are analyzed for a hypothetical geostationary satellite called KORSAT-1 which is assumed to be located in longitude 110°E.

  20. Can positional MRI predict dynamic changes in the medial plantar arch?

    DEFF Research Database (Denmark)

    Johannsen, Finn E; Hansen, Philip; Stallknecht, Sandra

    2016-01-01

    BACKGROUND: Positional MRI (pMRI) allows for three-dimensional visual assessment of navicular position. In this exploratory pilot study pMRI was validated against a stretch sensor device, which measures movement of the medial plantar arch. We hypothesized that a combined pMRI measure incorporating...... and c) standing position with addition of 10 % body weight during static loading of the foot. Stretch sensor measurements were also performed during barefoot walking. RESULTS: The total change in navicular position measured by pMRI was 10.3 mm (CI: 7.0 to 13.5 mm). No further displacement occurred when.......08). CONCLUSIONS: Total navicular bone displacements determined by pMRI showed concurrent validity with stretch sensor measurements but only so under static loading conditions. Although assessment of total navicular displacement by combining concomitant vertical and medial navicular bone movements would appear...

  1. Losing a dime with a satisfied mind: positive affect predicts less search in sequential decision making.

    Science.gov (United States)

    von Helversen, Bettina; Mata, Rui

    2012-12-01

    We investigated the contribution of cognitive ability and affect to age differences in sequential decision making by asking younger and older adults to shop for items in a computerized sequential decision-making task. Older adults performed poorly compared to younger adults partly due to searching too few options. An analysis of the decision process with a formal model suggested that older adults set lower thresholds for accepting an option than younger participants. Further analyses suggested that positive affect, but not fluid abilities, was related to search in the sequential decision task. A second study that manipulated affect in younger adults supported the causal role of affect: Increased positive affect lowered the initial threshold for accepting an attractive option. In sum, our results suggest that positive affect is a key factor determining search in sequential decision making. Consequently, increased positive affect in older age may contribute to poorer sequential decisions by leading to insufficient search. 2013 APA, all rights reserved

  2. Conceptual Software Reliability Prediction Models for Nuclear Power Plant Safety Systems

    International Nuclear Information System (INIS)

    Johnson, G.; Lawrence, D.; Yu, H.

    2000-01-01

    The objective of this project is to develop a method to predict the potential reliability of software to be used in a digital system instrumentation and control system. The reliability prediction is to make use of existing measures of software reliability such as those described in IEEE Std 982 and 982.2. This prediction must be of sufficient accuracy to provide a value for uncertainty that could be used in a nuclear power plant probabilistic risk assessment (PRA). For the purposes of the project, reliability was defined to be the probability that the digital system will successfully perform its intended safety function (for the distribution of conditions under which it is expected to respond) upon demand with no unintended functions that might affect system safety. The ultimate objective is to use the identified measures to develop a method for predicting the potential quantitative reliability of a digital system. The reliability prediction models proposed in this report are conceptual in nature. That is, possible prediction techniques are proposed and trial models are built, but in order to become a useful tool for predicting reliability, the models must be tested, modified according to the results, and validated. Using methods outlined by this project, models could be constructed to develop reliability estimates for elements of software systems. This would require careful review and refinement of the models, development of model parameters from actual experience data or expert elicitation, and careful validation. By combining these reliability estimates (generated from the validated models for the constituent parts) in structural software models, the reliability of the software system could then be predicted. Modeling digital system reliability will also require that methods be developed for combining reliability estimates for hardware and software. System structural models must also be developed in order to predict system reliability based upon the reliability

  3. Some Comparisons of Measured and Predicted Primary Radiation Levels in the Aagesta Power Plant

    Energy Technology Data Exchange (ETDEWEB)

    Aalto, E; Sandlin, R; Krell, Aa

    1968-05-15

    Neutron fluxes and gamma exposure rates in the primary shields of the Aagesta nuclear plant have been measured and the results compared with values predicted during shield design, and with values obtained later by the NRN bulk shielding code. The input data for the problems are given. The radial predictions are conservative by a factor of not more than 2 close to the reactor and by an unknown, higher factor further out. The conservatism is explainable by the differences between the true local conditions and core power distributions and those assumed in the predictions. The axial flux levels based on streaming calculations are found to agree quite well with the estimated values. The conservatism here is not so large and it seems to be necessary to be very careful when handling streaming problems. The experience gained shows that a power plant is less suitable for studying the accuracy of the shield design codes as such, but the practical results from the combined application of massive shield codes and void streaming predictions to complicated problems give information about the true degree of conservatism present.

  4. Do Electrochemiluminescence Assays Improve Prediction of Time to Type 1 Diabetes in Autoantibody-Positive TrialNet Subjects?

    Science.gov (United States)

    Fouts, Alexandra; Pyle, Laura; Yu, Liping; Miao, Dongmei; Michels, Aaron; Krischer, Jeffrey; Sosenko, Jay; Gottlieb, Peter; Steck, Andrea K

    2016-10-01

    To explore whether electrochemiluminescence (ECL) assays can help improve prediction of time to type 1 diabetes in the TrialNet autoantibody-positive population. TrialNet subjects who were positive for one or more autoantibodies (microinsulin autoantibody, GAD65 autoantibody [GADA], IA-2A, and ZnT8A) with available ECL-insulin autoantibody (IAA) and ECL-GADA data at their initial visit were analyzed; after a median follow-up of 24 months, 177 of these 1,287 subjects developed diabetes. Univariate analyses showed that autoantibodies by radioimmunoassays (RIAs), ECL-IAA, ECL-GADA, age, sex, number of positive autoantibodies, presence of HLA DR3/4-DQ8 genotype, HbA1c, and oral glucose tolerance test (OGTT) measurements were all significantly associated with progression to diabetes. Subjects who were ECL positive had a risk of progression to diabetes within 6 years of 58% compared with 5% for the ECL-negative subjects (P < 0.0001). Multivariate Cox proportional hazards models were compared, with the base model including age, sex, OGTT measurements, and number of positive autoantibodies by RIAs. The model with positivity for ECL-GADA and/or ECL-IAA was the best, and factors that remained significantly associated with time to diabetes were area under the curve (AUC) C-peptide, fasting C-peptide, AUC glucose, number of positive autoantibodies by RIAs, and ECL positivity. Adding ECL to the Diabetes Prevention Trial risk score (DPTRS) improved the receiver operating characteristic curves with AUC of 0.83 (P < 0.0001). ECL assays improved the ability to predict time to diabetes in these autoantibody-positive relatives at risk for developing diabetes. These findings might be helpful in the design and eligibility criteria for prevention trials in the future. © 2016 by the American Diabetes Association.

  5. 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

  6. Data Analytics Based Dual-Optimized Adaptive Model Predictive Control for the Power Plant Boiler

    Directory of Open Access Journals (Sweden)

    Zhenhao Tang

    2017-01-01

    Full Text Available To control the furnace temperature of a power plant boiler precisely, a dual-optimized adaptive model predictive control (DoAMPC method is designed based on the data analytics. In the proposed DoAMPC, an accurate predictive model is constructed adaptively by the hybrid algorithm of the least squares support vector machine and differential evolution method. Then, an optimization problem is constructed based on the predictive model and many constraint conditions. To control the boiler furnace temperature, the differential evolution method is utilized to decide the control variables by solving the optimization problem. The proposed method can adapt to the time-varying situation by updating the sample data. The experimental results based on practical data illustrate that the DoAMPC can control the boiler furnace temperature with errors of less than 1.5% which can meet the requirements of the real production process.

  7. Predictive and prognostic properties of TB-LAM among HIV-positive patients initiating ART in Johannesburg, South Africa.

    Science.gov (United States)

    d'Elia, Alexander; Evans, Denise; McNamara, Lynne; Berhanu, Rebecca; Sanne, Ian; Lönnermark, Elisabet

    2015-01-01

    While the diagnostic properties of the TB LAM urine assay (LAM) have been well-described, little is known about its predictive and prognostic properties at ART initiation in a routine clinic setting. We describe the predictive and prognostic properties of LAM in HIV-positive patients initiating ART at an urban hospital in Johannesburg, South Africa. Retrospective study of HIV-positive adults (>18 years) who initiated standard first-line ART between February 2012 and April 2013 and had a LAM test at initiation. In HIV-positive patients with no known TB at ART initiation, we assessed the sensitivity, specificity and positive/negative likelihood ratios of LAM to predict incident TB within 6 months of ART initiation. In addition, in patients with a TB diagnosis and on TB treatment ART initiation, we measured the CD4 response at 6 months on ART. Of the 274 patients without TB at ART initiation, 65% were female with median CD4 count of 213 cells/mm(3). Among the 14 (5.1%) patients who developed active TB, none were urine LAM +ve at baseline. LAM had poor sensitivity (0.0% 95% CI 0.00-23.2) to predict incident TB within 6 months of initiation. We analyzed 22 patients with a confirmed TB diagnosis at initiation separately. Of these, LAM +ve patients (27%) showed lower CD4 gains compared to LAM negative patients (median increase 103 vs 199 cells/mm(3); p = 0.08). LAM has limited value for accurately predicting incident TB in patients with higher CD4 counts after ART initiation. LAM may help identify TB/HIV co-infected patients at ART initiation who respond more slowly to treatment and require targeted interventions to improve treatment outcomes. Larger studies with longer patient follow-up are needed.

  8. Kicking Back Cognitive Ageing: Leg Power Predicts Cognitive Ageing after Ten Years in Older Female Twins.

    Science.gov (United States)

    Steves, Claire J; Mehta, Mitul M; Jackson, Stephen H D; Spector, Tim D

    2016-01-01

    Many observational studies have shown a protective effect of physical activity on cognitive ageing, but interventional studies have been less convincing. This may be due to short time scales of interventions, suboptimal interventional regimes or lack of lasting effect. Confounding through common genetic and developmental causes is also possible. We aimed to test whether muscle fitness (measured by leg power) could predict cognitive change in a healthy older population over a 10-year time interval, how this performed alongside other predictors of cognitive ageing, and whether this effect was confounded by factors shared by twins. In addition, we investigated whether differences in leg power were predictive of differences in brain structure and function after 12 years of follow-up in identical twin pairs. A total of 324 healthy female twins (average age at baseline 55, range 43-73) performed the Cambridge Neuropsychological Test Automated Battery (CANTAB) at two time points 10 years apart. Linear regression modelling was used to assess the relationships between baseline leg power, physical activity and subsequent cognitive change, adjusting comprehensively for baseline covariates (including heart disease, diabetes, blood pressure, fasting blood glucose, lipids, diet, body habitus, smoking and alcohol habits, reading IQ, socioeconomic status and birthweight). A discordant twin approach was used to adjust for factors shared by twins. A subset of monozygotic pairs then underwent magnetic resonance imaging. The relationship between muscle fitness and brain structure and function was assessed using linear regression modelling and paired t tests. A striking protective relationship was found between muscle fitness (leg power) and both 10-year cognitive change [fully adjusted model standardised β-coefficient (Stdβ) = 0.174, p = 0.002] and subsequent total grey matter (Stdβ = 0.362, p = 0.005). These effects were robust in discordant twin analyses, where within

  9. Extracurricular Activity and Parental Involvement Predict Positive Outcomes in Elementary School Children

    Science.gov (United States)

    Lagace-Seguin, Daniel G.; Case, Emily

    2010-01-01

    The main goal of this study was to explore if parental involvement and extracurricular activity participation could predict well-being and academic competence in elementary school children. Seventy-two children (mean age = 10.9 years, SD = 0.85) and their parents participated. Results revealed that parental pressure and support, when paired with…

  10. Predicting biochemical recurrence-free survival for patients with positive pelvic lymph nodes at radical prostatectomy.

    Science.gov (United States)

    von Bodman, Christian; Godoy, Guilherme; Chade, Daher C; Cronin, Angel; Tafe, Laura J; Fine, Samson W; Laudone, Vincent; Scardino, Peter T; Eastham, James A

    2010-07-01

    We evaluated predictors of freedom from biochemical recurrence in patients with pelvic lymph node metastasis at radical prostatectomy. Of 207 patients with lymph node metastasis treated with radical prostatectomy and bilateral pelvic lymph node dissection 45 received adjuvant androgen deprivation therapy and 162 did not. Cox proportional hazards regression models were used to investigate predictors of biochemical recurrence after radical prostatectomy. Recurrence probability was estimated using the Kaplan-Meier method. A median of 13 lymph nodes were removed. Of the patients 122 had 1, 44 had 2 and 41 had 3 or greater positive lymph nodes. Of patients without androgen deprivation therapy 103 had 1, 35 had 2 and 24 had 3 or greater positive lymph nodes while 69 experienced biochemical recurrence. Median time to recurrence in patients with 1, 2 and 3 or greater lymph nodes was 59, 13 and 3 months, respectively. Only specimen Gleason score and the number of positive lymph nodes were independent predictors of biochemical recurrence. Recurrence-free probability 2 years after prostatectomy in men without androgen deprivation with 1 positive lymph node and a prostatectomy Gleason score of 7 or less was 79% vs 29% in those with Gleason score 8 or greater and 2 or more positive lymph nodes. Prognosis in patients with lymph node metastasis depends on the number of positive lymph nodes and primary tumor Gleason grade. Of all patients with lymph node metastasis 80% had 1 or 2 positive nodes. A large subset of those patients had a favorable prognosis. Full bilateral pelvic lymph node dissection should be done in patients with intermediate and high risk cancer to identify those likely to benefit from metastatic node removal. Copyright (c) 2010 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  11. A comparative analysis of primary and secondary Gleason pattern predictive ability for positive surgical margins after radical prostatectomy.

    Science.gov (United States)

    Sfoungaristos, S; Kavouras, A; Kanatas, P; Polimeros, N; Perimenis, P

    2011-01-01

    To compare the predictive ability of primary and secondary Gleason pattern for positive surgical margins in patients with clinically localized prostate cancer and a preoperative Gleason score ≤ 6. A retrospective analysis of the medical records of patients undergone a radical prostatectomy between January 2005 and October 2010 was conducted. Patients' age, prostate volume, preoperative PSA, biopsy Gleason score, the 1st and 2nd Gleason pattern were entered a univariate and multivariate analysis. The 1st and 2nd pattern were tested for their ability to predict positive surgical margins using receiver operating characteristic curves. Positive surgical margins were noticed in 56 cases (38.1%) out of 147 studied patients. The 2nd pattern was significantly greater in those with positive surgical margins while the 1st pattern was not significantly different between the 2 groups of patients. ROC analysis revealed that area under the curve was 0.53 (p=0.538) for the 1st pattern and 0.60 (p=0.048) for the 2nd pattern. Concerning the cases with PSA <10 ng/ml, it was also found that only the 2nd pattern had a predictive ability (p=0.050). When multiple logistic regression analysis was conducted it was found that the 2nd pattern was the only independent predictor. The second Gleason pattern was found to be of higher value than the 1st one for the prediction of positive surgical margins in patients with preoperative Gleason score ≤ 6 and this should be considered especially when a neurovascular bundle sparing radical prostatectomy is planned, in order not to harm the oncological outcome.

  12. Positively Biased Processing of Mother's Emotions Predicts Children's Social and Emotional Functioning.

    Science.gov (United States)

    Donohue, Meghan Rose; Goodman, Sherryl H; Tully, Erin C

    Risk for internalizing problems and social skills deficits likely emerges in early childhood when emotion processing and social competencies are developing. Positively biased processing of social information is typical during early childhood and may be protective against poorer psychosocial outcomes. We tested the hypothesis that young children with relatively less positively biased attention to, interpretations of, and attributions for their mother's emotions would exhibit poorer prosocial skills and more internalizing problems. A sample of 4- to 6-year-old children ( N =82) observed their mothers express happiness, sadness and anger during a simulated emotional phone conversation. Children's attention to their mother when she expressed each emotion was rated from video. Immediately following the phone conversation, children were asked questions about the conversation to assess their interpretations of the intensity of mother's emotions and misattributions of personal responsibility for her emotions. Children's prosocial skills and internalizing problems were assessed using mother-report rating scales. Interpretations of mother's positive emotions as relatively less intense than her negative emotions, misattributions of personal responsibility for her negative emotions, and lack of misattributions of personal responsibility for her positive emotions were associated with poorer prosocial skills. Children who attended relatively less to mother's positive than her negative emotions had higher levels of internalizing problems. These findings suggest that children's attention to, interpretations of, and attributions for their mother's emotions may be important targets of early interventions for preventing prosocial skills deficits and internalizing problems.

  13. Detailed neutronic study of the power evolution for the European Sodium Fast Reactor during a positive insertion of reactivity

    Energy Technology Data Exchange (ETDEWEB)

    Facchini, A.; Giusti, V.; Ciolini, R. [Department of Civil and Industrial Engineering (DICI), University of Pisa, Largo Lucio Lazzarino 2, I-56126 Pisa (Italy); Tuček, K.; Thomas, D. [Joint Research Centre, Institute for Energy and Transport (JRC - IET), European Commission, P.O. Box 2, NL-1755 ZG Petten (Netherlands); D' Agata, E., E-mail: elio.dagata@ec.europa.eu [Joint Research Centre, Institute for Energy and Transport (JRC - IET), European Commission, P.O. Box 2, NL-1755 ZG Petten (Netherlands)

    2017-03-15

    Highlights: • This paper studies the effect of an unexpected runway of a control rod in the ESFR. • The power peaked fuel pin within the core was identified. • The increase of the fission power density of the fuel pin has been evaluated. • Radial/axial fission power density of the power peaked fuel pin has been evaluated. - Abstract: The new reactor concepts proposed in the Generation IV International Forum require the development and validation of new components and new materials. Inside the Collaborative Project on the European Sodium Fast Reactor, several accidental scenario have been studied. Nevertheless, none of them coped with mechanical safety assessment of the fuel cladding under accidental conditions. Among the accidental conditions considered, there is the unprotected transient of overpower (UTOP), due to the insertion, at the end of the first fuel cycle, of a positive reactivity into the reactor core as a consequence of the unexpected runaway of one control rod. The goal of the study was the search for a detailed distribution of the fission power, in the radial and axial directions, within the power peaked fuel pin under the above accidental conditions. Results show that after the control rod ejection an increase from 658 W/cm{sup 3} to 894 W/cm{sup 3}, i.e. of some 36%, is expected for the power peaked fuel pin. This information will represent the base to investigate, in a future work, the fuel cladding safety margin.

  14. "I'm worth more than that": trait positivity predicts increased rejection of unfair financial offers.

    Directory of Open Access Journals (Sweden)

    Barnaby D Dunn

    2010-12-01

    Full Text Available Humans react strongly to unfairness, sometimes rejecting inequitable proposals even if this sacrifices personal financial gain. Here we explored whether emotional dispositions--trait tendencies to experience positive or negative feelings--shape the rejection of unfair financial offers. Participants played an Ultimatum Game, where the division of a sum of money is proposed and the player can accept or reject this offer. Individuals high in trait positivity and low in trait negativity rejected more unfair offers. These relationships could not be explained by existing accounts which argue that rejection behaviour results from a failure to regulate negative emotions, or serves to arbitrate social relationships and identity. Instead, the relationship between dispositional affect and rejection behaviour may be underpinned by perceived self worth, with those of a positive disposition believing that they are "worth more than that" and those of a negative disposition resigning themselves to "taking the crumbs from under the table".

  15. "I'm worth more than that": trait positivity predicts increased rejection of unfair financial offers.

    Science.gov (United States)

    Dunn, Barnaby D; Makarova, Dasha; Evans, David; Clark, Luke

    2010-12-08

    Humans react strongly to unfairness, sometimes rejecting inequitable proposals even if this sacrifices personal financial gain. Here we explored whether emotional dispositions--trait tendencies to experience positive or negative feelings--shape the rejection of unfair financial offers. Participants played an Ultimatum Game, where the division of a sum of money is proposed and the player can accept or reject this offer. Individuals high in trait positivity and low in trait negativity rejected more unfair offers. These relationships could not be explained by existing accounts which argue that rejection behaviour results from a failure to regulate negative emotions, or serves to arbitrate social relationships and identity. Instead, the relationship between dispositional affect and rejection behaviour may be underpinned by perceived self worth, with those of a positive disposition believing that they are "worth more than that" and those of a negative disposition resigning themselves to "taking the crumbs from under the table".

  16. Positive predictive value of the immunoassay for Clostridium difficile toxin A and B detection at a private hospital.

    Science.gov (United States)

    Pérez-Topete, S E; Miranda-Aquino, T; Hernández-Portales, J A

    Clostridium difficile (C. difficile) is a Gram-positive bacillus that is a common cause of diarrhea in the hospital environment, with a documented incidence of up to 10%. There are different methods to detect it, but a widely used test in our environment is the immunoassay for toxins A and B. The aim of our study was to 1) estimate the positive predictive value of the immunoassay for the detection of the C. difficile toxins A and B, 2) to establish the incidence of C. difficile-associated diarrhea in the hospital, and 3) to know the most common associated factors. A diagnostic test accuracy study was conducted within the time frame of January 2010 to August 2013 at the Hospital Christus Muguerza® Alta Especialidad on patients with symptoms suggestive of C. difficile-associated diarrhea that had a positive immunoassay test and confirmation of C. difficile through colon biopsy and stool culture. The immunoassay for toxins A and B was performed in 360 patients. Fifty-five of the cases had positive results, 35 of which showed the presence of C. difficile. Incidence was 10.2% and the positive predictive value of the test for C. difficile toxins A and B was 0.64 (95% CI, 0.51-0.76). Previous antibiotic therapy (n=29) and proton pump inhibitor use (n=19) were the most common associated factors. C. difficile incidence in our environment is similar to that found in the literature reviewed, but the positive predictive value of the test for toxin A and B detection was low. Copyright © 2016 Asociación Mexicana de Gastroenterología. Publicado por Masson Doyma México S.A. All rights reserved.

  17. Predictive value of prior injury on career in professional American football is affected by player position.

    Science.gov (United States)

    Brophy, Robert H; Lyman, Stephen; Chehab, Eric L; Barnes, Ronnie P; Rodeo, Scott A; Warren, Russell F

    2009-04-01

    The National Football League holds an annual combine where individual teams evaluate college football players The abstract goes here and covers two columns. likely to be drafted for physical skills, review players' medical history and imaging studies, and perform a physical examination. The purpose of this study was to test the effect of specific diagnoses and surgical procedures on the likelihood of playing and length of career in the league by position. Cohort study; Level of evidence, 3. A database for all players reviewed at the annual National Football League Combine by the medical staff of 1 National Football League team from 1987 to 2000 was created, including each player's orthopaedic rating, diagnoses, surgical procedures, number of games played, and number of seasons played in the National Football League. Athletes were grouped by position as follows: offensive backfield, offensive receiver, offensive line, quarterback, tight end, defensive line, defensive secondary, linebacker, and kicker. The percentage of athletes who played in the National Football League was calculated by position for each specific diagnosis and surgery. The effect of injury on the likelihood of playing in the league varied by position. Anterior cruciate ligament injury significantly lowered the likelihood of playing in the league for defensive linemen (P = .03) and linebackers (P = .04). Meniscal injury significantly reduced the probability of playing (P history of spondylolysis had a significant effect for running backs (P = .01). Miscellaneous injuries (eg. acromioclavicular joint, knee medial collateral ligament, carpal fractures) had isolated position-specific effects. The significant injuries and diagnoses appear congruent with the position-specific demands placed on the athletes. This information is useful to physicians and athletic trainers caring for college football athletes as well as those assessing these athletes at the National Football League Combine.

  18. Predicting the long tail of book sales: Unearthing the power-law exponent

    Science.gov (United States)

    Fenner, Trevor; Levene, Mark; Loizou, George

    2010-06-01

    The concept of the long tail has recently been used to explain the phenomenon in e-commerce where the total volume of sales of the items in the tail is comparable to that of the most popular items. In the case of online book sales, the proportion of tail sales has been estimated using regression techniques on the assumption that the data obeys a power-law distribution. Here we propose a different technique for estimation based on a generative model of book sales that results in an asymptotic power-law distribution of sales, but which does not suffer from the problems related to power-law regression techniques. We show that the proportion of tail sales predicted is very sensitive to the estimated power-law exponent. In particular, if we assume that the power-law exponent of the cumulative distribution is closer to 1.1 rather than to 1.2 (estimates published in 2003, calculated using regression by two groups of researchers), then our computations suggest that the tail sales of Amazon.com, rather than being 40% as estimated by Brynjolfsson, Hu and Smith in 2003, are actually closer to 20%, the proportion estimated by its CEO.

  19. The collective benefits of feeling good and letting go: positive emotion and (dis)inhibition interact to predict cooperative behavior.

    Science.gov (United States)

    Rand, David G; Kraft-Todd, Gordon; Gruber, June

    2015-01-01

    Cooperation is central to human existence, forming the bedrock of everyday social relationships and larger societal structures. Thus, understanding the psychological underpinnings of cooperation is of both scientific and practical importance. Recent work using a dual-process framework suggests that intuitive processing can promote cooperation while deliberative processing can undermine it. Here we add to this line of research by more specifically identifying deliberative and intuitive processes that affect cooperation. To do so, we applied automated text analysis using the Linguistic Inquiry and Word Count (LIWC) software to investigate the association between behavior in one-shot anonymous economic cooperation games and the presence inhibition (a deliberative process) and positive emotion (an intuitive process) in free-response narratives written after (Study 1, N = 4,218) or during (Study 2, N = 236) the decision-making process. Consistent with previous results, across both studies inhibition predicted reduced cooperation while positive emotion predicted increased cooperation (even when controlling for negative emotion). Importantly, there was a significant interaction between positive emotion and inhibition, such that the most cooperative individuals had high positive emotion and low inhibition. This suggests that inhibition (i.e., reflective or deliberative processing) may undermine cooperative behavior by suppressing the prosocial effects of positive emotion.

  20. The collective benefits of feeling good and letting go: positive emotion and (disinhibition interact to predict cooperative behavior.

    Directory of Open Access Journals (Sweden)

    David G Rand

    Full Text Available Cooperation is central to human existence, forming the bedrock of everyday social relationships and larger societal structures. Thus, understanding the psychological underpinnings of cooperation is of both scientific and practical importance. Recent work using a dual-process framework suggests that intuitive processing can promote cooperation while deliberative processing can undermine it. Here we add to this line of research by more specifically identifying deliberative and intuitive processes that affect cooperation. To do so, we applied automated text analysis using the Linguistic Inquiry and Word Count (LIWC software to investigate the association between behavior in one-shot anonymous economic cooperation games and the presence inhibition (a deliberative process and positive emotion (an intuitive process in free-response narratives written after (Study 1, N = 4,218 or during (Study 2, N = 236 the decision-making process. Consistent with previous results, across both studies inhibition predicted reduced cooperation while positive emotion predicted increased cooperation (even when controlling for negative emotion. Importantly, there was a significant interaction between positive emotion and inhibition, such that the most cooperative individuals had high positive emotion and low inhibition. This suggests that inhibition (i.e., reflective or deliberative processing may undermine cooperative behavior by suppressing the prosocial effects of positive emotion.

  1. Adaptation of fast responding power supply for radial position control in SST-1

    International Nuclear Information System (INIS)

    Sharma, Dinesh Kumar; Patel, Kiritkumar B.; Singh, Akhilesh Kumar; Dhongde, Jasraj

    2013-01-01

    A high current, fast responding power supply was installed in 2005 for vertical stabilization of elongated plasmas in SST-1 tokamak. Presently, during initial experiments of SST-1 tokamak the need for radial control during current build-up was envisaged. For this purpose the existing power supply was suitable and the same was re-commissioned and control adaptations were carried as per experimental requirements. This paper highlights the capabilities of the power supply and details the modifications in the control interfaces and test programs for the radial control purpose. Details of the operation of the power supply along with control interfaces with performance measurements are provided. The re-commissioning provided an opportunity in the trouble shooting methods and sequential operation of the system. With the operational use on the actual coil the mutual effects are understood better and appropriate test programs are prepared. The power supply provided satisfactory performance for the intended use. In additional the system is suitable to simulate a plasma current loop to enable the testing and calibration of Rogowski coil used for plasma current measurement. (author)

  2. Do Electrochemiluminescence Assays Improve Prediction of Time to Type 1 Diabetes in Autoantibody-Positive TrialNet Subjects?

    OpenAIRE

    Fouts, Alexandra; Pyle, Laura; Yu, Liping; Miao, Dongmei; Michels, Aaron; Krischer, Jeffrey; Sosenko, Jay; Gottlieb, Peter; Steck, Andrea K.

    2016-01-01

    OBJECTIVE To explore whether electrochemiluminescence (ECL) assays can help improve prediction of time to type 1 diabetes in the TrialNet autoantibody-positive population. RESEARCH DESIGN AND METHODS TrialNet subjects who were positive for one or more autoantibodies (microinsulin autoantibody, GAD65 autoantibody [GADA], IA-2A, and ZnT8A) with available ECL-insulin autoantibody (IAA) and ECL-GADA data at their initial visit were analyzed; after a median follow-up of 24 months, 177 of these 1,2...

  3. Predictive value of prostate specific antigen in a European HIV-positive cohort

    DEFF Research Database (Denmark)

    Shepherd, Leah; Borges, Álvaro H; Ravn, Lene

    2016-01-01

    BACKGROUND: It is common practice to use prostate specific antigen (PSA) ≥4.0 ng/ml as a clinical indicator for men at risk of prostate cancer (PCa), however, this is unverified in HIV+ men. We aimed to describe kinetics and predictive value of PSA for PCa in HIV+ men. METHODS: A nested case...... control study of 21 men with PCa and 40 matched-controls within EuroSIDA was conducted. Prospectively stored plasma samples before PCa (or matched date in controls) were measured for the following markers: total PSA (tPSA), free PSA (fPSA), testosterone and sex hormone binding globulin (SHBG). Conditional...... logistic regression models investigated associations between markers and PCa. Mixed models were used to describe kinetics. Sensitivity and specificity of using tPSA >4 ng/ml to predict PCa was calculated. Receiver operating characteristic curves were used to identify optimal cutoffs in HIV+ men for total...

  4. PANTHER-PSEP: predicting disease-causing genetic variants using position-specific evolutionary preservation.

    Science.gov (United States)

    Tang, Haiming; Thomas, Paul D

    2016-07-15

    PANTHER-PSEP is a new software tool for predicting non-synonymous genetic variants that may play a causal role in human disease. Several previous variant pathogenicity prediction methods have been proposed that quantify evolutionary conservation among homologous proteins from different organisms. PANTHER-PSEP employs a related but distinct metric based on 'evolutionary preservation': homologous proteins are used to reconstruct the likely sequences of ancestral proteins at nodes in a phylogenetic tree, and the history of each amino acid can be traced back in time from its current state to estimate how long that state has been preserved in its ancestors. Here, we describe the PSEP tool, and assess its performance on standard benchmarks for distinguishing disease-associated from neutral variation in humans. On these benchmarks, PSEP outperforms not only previous tools that utilize evolutionary conservation, but also several highly used tools that include multiple other sources of information as well. For predicting pathogenic human variants, the trace back of course starts with a human 'reference' protein sequence, but the PSEP tool can also be applied to predicting deleterious or pathogenic variants in reference proteins from any of the ∼100 other species in the PANTHER database. PANTHER-PSEP is freely available on the web at http://pantherdb.org/tools/csnpScoreForm.jsp Users can also download the command-line based tool at ftp://ftp.pantherdb.org/cSNP_analysis/PSEP/ CONTACT: pdthomas@usc.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  5. The predictive power of SIMION/SDS simulation software for modeling ion mobility spectrometry instruments

    Science.gov (United States)

    Lai, Hanh; McJunkin, Timothy R.; Miller, Carla J.; Scott, Jill R.; Almirall, José R.

    2008-09-01

    The combined use of SIMION 7.0 and the statistical diffusion simulation (SDS) user program in conjunction with SolidWorks® with COSMSOSFloWorks® fluid dynamics software to model a complete, commercial ion mobility spectrometer (IMS) was demonstrated for the first time and compared to experimental results for tests using compounds of immediate interest in the security industry (e.g., 2,4,6-trinitrotoluene, 2,7-dinitrofluorene, and cocaine). The effort of this research was to evaluate the predictive power of SIMION/SDS for application to IMS instruments. The simulation was evaluated against experimental results in three studies: (1) a drift:carrier gas flow rates study assesses the ability of SIMION/SDS to correctly predict the ion drift times; (2) a drift gas composition study evaluates the accuracy in predicting the resolution; (3) a gate width study compares the simulated peak shape and peak intensity with the experimental values. SIMION/SDS successfully predicted the correct drift time, intensity, and resolution trends for the operating parameters studied. Despite the need for estimations and assumptions in the construction of the simulated instrument, SIMION/SDS was able to predict the resolution between two ion species in air within 3% accuracy. The preliminary success of IMS simulations using SIMION/SDS software holds great promise for the design of future instruments with enhanced performance.

  6. Relational aggression, positive urgency and negative urgency: predicting alcohol use and consequences among college students.

    Science.gov (United States)

    Grimaldi, Elizabeth M; Napper, Lucy E; LaBrie, Joseph W

    2014-09-01

    Research on relational aggression (indirect and social means of inflicting harm) has previously focused on adolescent populations. The current study extends this research by exploring both the frequency of perpetrating and being the target of relational aggression as it relates to alcohol use outcomes in a college population. Further, this study examines whether positive urgency (e.g., acting impulsively in response to positive emotions) and negative urgency (e.g., acting impulsively in response to negative emotions) moderate the relationship between relational aggression and alcohol outcomes. In this study, 245 college students (65.7% female) completed an online survey. Results indicated greater frequency of perpetrating relational aggression, higher levels of positive urgency, or higher levels of negative urgency was associated with more negative consequences. Further, negative urgency moderated the relationship between frequency of perpetrating aggression and consequences such that aggression was more strongly associated with consequences for those high in urgency. Counter to the adolescent literature, the frequency of being the target of aggression was not associated with more alcohol use. These findings suggest that perpetrators of relational aggression may be at particular risk for negative alcohol-related consequences when they act impulsively in response to negative, but not positive, emotions. These students may benefit from interventions exploring alternative ways to cope with negative emotions.

  7. Risk prediction of ventricular arrhythmias and myocardial function in Lamin A/C mutation positive subjects

    DEFF Research Database (Denmark)

    Hasselberg, Nina E; Edvardsen, Thor; Petri, Helle

    2014-01-01

    Mutations in the Lamin A/C gene may cause atrioventricular block, supraventricular arrhythmias, ventricular arrhythmias (VA), and dilated cardiomyopathy. We aimed to explore the predictors and the mechanisms of VA in Lamin A/C mutation-positive subjects.METHODS AND RESULTS: We included 41 Lamin A/C...

  8. Factors Predicting Sustainability of the Schoolwide Positive Behavior Intervention Support Model

    Science.gov (United States)

    Chitiyo, Jonathan; May, Michael E.

    2018-01-01

    The Schoolwide Positive Behavior Intervention Support model (SWPBIS) continues to gain widespread use across schools in the United States and abroad. Despite its widespread implementation, little research has examined factors that influence its sustainability. Informed by Rogers's diffusion theory, this study examined school personnel's…

  9. Predicting the short-term risk of diabetes in HIV-positive patients

    DEFF Research Database (Denmark)

    Petoumenos, Kathy; Worm, Signe W; Fontas, Eric

    2012-01-01

    HIV-positive patients receiving combination antiretroviral therapy (cART) frequently experience metabolic complications such as dyslipidemia and insulin resistance, as well as lipodystrophy, increasing the risk of cardiovascular disease (CVD) and diabetes mellitus (DM). Rates of DM and other...

  10. Phylogeny is a powerful tool for predicting plant biomass responses to nitrogen enrichment.

    Science.gov (United States)

    Wooliver, Rachel C; Marion, Zachary H; Peterson, Christopher R; Potts, Brad M; Senior, John K; Bailey, Joseph K; Schweitzer, Jennifer A

    2017-08-01

    Increasing rates of anthropogenic nitrogen (N) enrichment to soils often lead to the dominance of nitrophilic plant species and reduce plant diversity in natural ecosystems. Yet, we lack a framework to predict which species will be winners or losers in soil N enrichment scenarios, a framework that current literature suggests should integrate plant phylogeny, functional tradeoffs, and nutrient co-limitation. Using a controlled fertilization experiment, we quantified biomass responses to N enrichment for 23 forest tree species within the genus Eucalyptus that are native to Tasmania, Australia. Based on previous work with these species' responses to global change factors and theory on the evolution of plant resource-use strategies, we hypothesized that (1) growth responses to N enrichment are phylogenetically structured, (2) species with more resource-acquisitive functional traits have greater growth responses to N enrichment, and (3) phosphorus (P) limits growth responses to N enrichment differentially across species, wherein P enrichment increases growth responses to N enrichment more in some species than others. We built a hierarchical Bayesian model estimating effects of functional traits (specific leaf area, specific stem density, and specific root length) and P fertilization on species' biomass responses to N, which we then compared between lineages to determine whether phylogeny explains variation in responses to N. In concordance with literature on N limitation, a majority of species responded strongly and positively to N enrichment. Mean responses ranged three-fold, from 6.21 (E. pulchella) to 16.87 (E. delegatensis) percent increases in biomass per g N·m -2 ·yr -1 added. We identified a strong difference in responses to N between two phylogenetic lineages in the Eucalyptus subgenus Symphyomyrtus, suggesting that shared ancestry explains variation in N limitation. However, our model indicated that after controlling for phylogenetic non

  11. Optimal position of the transmitter coil for wireless power transfer to the implantable device.

    Science.gov (United States)

    Jinghui Jian; Stanaćević, Milutin

    2014-01-01

    The maximum deliverable power through inductive link to the implantable device is limited by the tissue exposure to the electromagnetic field radiation. By moving away the transmitter coil from the body, the maximum deliverable power is increased as the magnitude of the electrical field at the interface with the body is kept constant. We demonstrate that the optimal distance between the transmitter coil and the body is on the order of 1 cm when the current of the transmitter coil is limited to 1 A. We also confirm that the conditions on the optimal frequency of the power transmission and the topology of the transmission coil remain the same as if the coil was directly adjacent to the body.

  12. Positively Biased Processing of Mother’s Emotions Predicts Children’s Social and Emotional Functioning

    Science.gov (United States)

    Donohue, Meghan Rose; Goodman, Sherryl H.; Tully, Erin C.

    2016-01-01

    Risk for internalizing problems and social skills deficits likely emerges in early childhood when emotion processing and social competencies are developing. Positively biased processing of social information is typical during early childhood and may be protective against poorer psychosocial outcomes. We tested the hypothesis that young children with relatively less positively biased attention to, interpretations of, and attributions for their mother’s emotions would exhibit poorer prosocial skills and more internalizing problems. A sample of 4- to 6-year-old children (N=82) observed their mothers express happiness, sadness and anger during a simulated emotional phone conversation. Children’s attention to their mother when she expressed each emotion was rated from video. Immediately following the phone conversation, children were asked questions about the conversation to assess their interpretations of the intensity of mother’s emotions and misattributions of personal responsibility for her emotions. Children’s prosocial skills and internalizing problems were assessed using mother-report rating scales. Interpretations of mother’s positive emotions as relatively less intense than her negative emotions, misattributions of personal responsibility for her negative emotions, and lack of misattributions of personal responsibility for her positive emotions were associated with poorer prosocial skills. Children who attended relatively less to mother’s positive than her negative emotions had higher levels of internalizing problems. These findings suggest that children’s attention to, interpretations of, and attributions for their mother’s emotions may be important targets of early interventions for preventing prosocial skills deficits and internalizing problems. PMID:28348456

  13. Static Analysis of High-Performance Fixed Fluid Power Drive with a Single Positive-Displacement Hydraulic Motor

    Directory of Open Access Journals (Sweden)

    O. F. Nikitin

    2015-01-01

    Full Text Available The article deals with the static calculations in designing a high-performance fixed fluid power drive with a single positive-displacement hydraulic motor. Designing is aimed at using a drive that is under development and yet unavailable to find and record the minimum of calculations and maximum of existing hydraulic units that enable clear and unambiguous performance, taking into consideration an available assortment of hydraulic units of hydraulic drives, to have the best efficiency.The specified power (power, moment and kinematics (linear velocity or angular velocity of rotation parameters of the output element of hydraulic motor determine the main output parameters of the hydraulic drive and the useful power of the hydraulic drive under development. The value of the overall efficiency of the hydraulic drive enables us to judge the efficiency of high-performance fixed fluid power drive.The energy analysis of a diagram of the high-performance fixed fluid power drive shows that its high efficiency is achieved when the flow rate of fluid flowing into each cylinder and the magnitude of the feed pump unit (pump are as nearly as possible.The paper considers the ways of determining the geometric parameters of working hydromotors (effective working area or working volume, which allow a selection of the pumping unit parameters. It discusses the ways to improve hydraulic drive efficiency. Using the principle of holding constant conductivity allows us to specify the values of the pressure losses in the hydraulic units used in noncatalog modes. In case of no exact matching between the parameters of existing hydraulic power modes and a proposed characteristics of the pump unit, the nearest to the expected characteristics is taken as a working version.All of the steps allow us to create the high-performance fixed fluid power drive capable of operating at the required power and kinematic parameters with high efficiency.

  14. ANN-based wavelet analysis for predicting electrical signal from photovoltaic power supply system

    Energy Technology Data Exchange (ETDEWEB)

    Mellit, A. [Medea Univ., Medea (Algeria). Inst. of Science Engineering, Dept. of Electronics

    2007-07-01

    This study was conducted to predict different electrical signals from a photovoltaic power supply system (PVPS) using an artificial neural networks (ANN) with wavelet analysis. It involved the creation of a database of electrical signals (PV-generator current, voltage, battery current voltage, regulator current and voltage) obtained from an experimental PVPS system installed in the south of Algeria. The potential applications were for sizing and analyzing the performance of PVPS systems; control of maximum power point tracker (MPPT) in order to deliver the maximum energy from the PV-array; prediction of the optimal configuration (PV-array and battery sizing) of PVPS systems; expert configuration of PV-systems; faults diagnosis; supervision; and, control and monitoring. First, based on the wavelet analysis each electrical signal was mapped in several time frequency domains. The PV-system was then divided into 3-subsystems corresponding to ANN-PV generator model, ANN-battery model, and ANN-regulator model. An example of day-by-day prediction for each electrical signal was presented. The results of the proposed approach were in good agreement with experimental results. In addition, the accuracy of the proposed approach was more satisfactory when only ANN was used. It was concluded that this methodology offers the possibility of developing a new expert configuration of PVPS by implementing the soft computing ANN-wavelet program with a digital signal processing (DSP) circuit. 26 refs., 1 tab., 5 figs.

  15. Wind power application research on the fusion of the determination and ensemble prediction

    Science.gov (United States)

    Lan, Shi; Lina, Xu; Yuzhu, Hao

    2017-07-01

    The fused product of wind speed for the wind farm is designed through the use of wind speed products of ensemble prediction from the European Centre for Medium-Range Weather Forecasts (ECMWF) and professional numerical model products on wind power based on Mesoscale Model5 (MM5) and Beijing Rapid Update Cycle (BJ-RUC), which are suitable for short-term wind power forecasting and electric dispatch. The single-valued forecast is formed by calculating the different ensemble statistics of the Bayesian probabilistic forecasting representing the uncertainty of ECMWF ensemble prediction. Using autoregressive integrated moving average (ARIMA) model to improve the time resolution of the single-valued forecast, and based on the Bayesian model averaging (BMA) and the deterministic numerical model prediction, the optimal wind speed forecasting curve and the confidence interval are provided. The result shows that the fusion forecast has made obvious improvement to the accuracy relative to the existing numerical forecasting products. Compared with the 0-24 h existing deterministic forecast in the validation period, the mean absolute error (MAE) is decreased by 24.3 % and the correlation coefficient (R) is increased by 12.5 %. In comparison with the ECMWF ensemble forecast, the MAE is reduced by 11.7 %, and R is increased 14.5 %. Additionally, MAE did not increase with the prolongation of the forecast ahead.

  16. Nuclear power plant shift technical advisor. Recommendations for position description, qualifications, education and training

    International Nuclear Information System (INIS)

    1981-01-01

    The purpose of this document is to describe the position and identify specific areas of formal education, plant-specific training and experience necessary to assure an advanced level of analytical ability on shift. These recommendations will provide a level of technical ability that is essential to improved operational safety and are consistent with regulatory requirements. This position was developed in conjunction with representatives of utilities, equipment vendors and engineering educators, giving consideration to specific contributions the function must make to shift operations

  17. Increase of the positive ion source power in JT-60 NBI

    International Nuclear Information System (INIS)

    Kawai, Mikito; Akino, Noboru; Ebisawa, Noboru

    1998-09-01

    Neutral Beam Injection (NBI) heating experiment in JT-60 started in 1986, and the rated injection power of 20MW at 75keV with hydrogen was achieved after several month operation. In 1991, the ion sources and power supply had been upgraded for a higher beam energy up to 120keV with deuterium, following which the ion source operation re-started aiming for an injection power of 40MW at 110keV. In the operation, the beam acceleration voltage was tried to increase by modifying the ion source structure against the break-down which occurred frequently in the ion source. The beam acceleration was, however, unstable in a beam energy range of more than 105keV because of voltage-holding deterioration in the accelerator. Therefore we changed the strategy to increase the injection power: i.e. we tried to increase the beam current with keeping the beam energy. The structure of the source has been modified to be operated in a high current regime. As a result, the deuterium neutral beam injection of 40MW at 91-96keV was achieved in July 1996. (author)

  18. "Instant status" during the slaughter: social positioning and power in a Sardinian shepherd family

    NARCIS (Netherlands)

    Janssens, F.

    2012-01-01

    This article uses food as a means to critically explore the existing theoretical debate on social change and power structures. Through a detailed ethnographic analysis of two events the milking of sheep and the slaughtering of a steer in rural Sardinia, Italy the article introduces the concept of

  19. Local environmental quality positively predicts breastfeeding in the UK's Millennium Cohort Study.

    Science.gov (United States)

    Brown, Laura J; Sear, Rebecca

    2017-01-01

    Background and Objectives: Breastfeeding is an important form of parental investment with clear health benefits. Despite this, rates remain low in the UK; understanding variation can therefore help improve interventions. Life history theory suggests that environmental quality may pattern maternal investment, including breastfeeding. We analyse a nationally representative dataset to test two predictions: (i) higher local environmental quality predicts higher likelihood of breastfeeding initiation and longer duration; (ii) higher socioeconomic status (SES) provides a buffer against the adverse influences of low local environmental quality. Methodology: We ran factor analysis on a wide range of local-level environmental variables. Two summary measures of local environmental quality were generated by this analysis-one 'objective' (based on an independent assessor's neighbourhood scores) and one 'subjective' (based on respondent's scores). We used mixed-effects regression techniques to test our hypotheses. Results: Higher objective, but not subjective, local environmental quality predicts higher likelihood of starting and maintaining breastfeeding over and above individual SES and area-level measures of environmental quality. Higher individual SES is protective, with women from high-income households having relatively high breastfeeding initiation rates and those with high status jobs being more likely to maintain breastfeeding, even in poor environmental conditions. Conclusions and Implications: Environmental quality is often vaguely measured; here we present a thorough investigation of environmental quality at the local level, controlling for individual- and area-level measures. Our findings support a shift in focus away from individual factors and towards altering the landscape of women's decision making contexts when considering behaviours relevant to public health.

  20. Situational Motivation and Perceived Intensity: Their Interaction in Predicting Changes in Positive Affect from Physical Activity

    OpenAIRE

    Eva Guérin; Michelle S. Fortier

    2012-01-01

    There is evidence that affective experiences surrounding physical activity can contribute to the proper self-regulation of an active lifestyle. Motivation toward physical activity, as portrayed by self-determination theory, has been linked to positive affect, as has the intensity of physical activity, especially of a preferred nature. The purpose of this experimental study was to examine the interaction between situational motivation and intensity [i.e., ratings of perceived exertion (RPE)] i...

  1. Predictable Technique to Register Retruded Contact Position (RCP) Using a Disposable Jaw Relation Recording Device.

    Science.gov (United States)

    Daher, Tony; Lobel, William A; Massad, Joseph; Ahuja, Swati; Danilov, Zarko Jack

    2015-05-01

    The dental literature presents various definitions and techniques to describe and register centric relation (CR) or centric occlusion (CO). Briefly reviewing the literature in relation to CR, this article proposes the use of the term retruded contact position (RCP), clinically defined as retruded, unstrained, repeatable position and where the mandibular movements start when a Gothic arch tracing is used. With this clinical definition, a technique can be easily selected that meets all the requirements of such position. The article discusses the use of a jaw recorder that is an intraorally graphic recording device that results in a tracing of mandibular movements in one plane, with the apex of the tracing indicating the retruded, unstrained, and repeatable relationship. The intersection of the arcs produced by the right and left working movement form the apex of the Gothic arch tracing. Several clinical situations using the jaw recorder are described. Clinicians can now quickly and accurately record RCP, balance complete, partial, or implant dentures, and orthopedically reposition the mandible. The technique achieves highly reliable and reproducible results.

  2. The clinical utility of lipid profile and positive troponin in predicting future cardiac events

    Directory of Open Access Journals (Sweden)

    Arun Kumar

    2012-02-01

    Full Text Available Objective: To study the usefulness of traditional lipid profile levels in screening subjects who had developed chest pain due to cardiac event as indicated by a positive troponin I (TnI test. Methods: In this retrospective study data of the 740 patients presented to the emergency department with symptoms of cardiac ischemia that underwent both troponin and lipid profiles tests were compared with the lipid profiles of 411 normal healthy subjects (controls. The troponin was detected qualitatively when a specimen contains TnI above the 99th percentile (TnI >0.5 ng/ mL. The total cholesterol (TC, high density lipoproteins (HDL, very low density lipoproteins (VLDL, and triacyl glycerol (TG levels were also analyzed and low density lipoprotein level (LDL was calculated using Friedewald ’s formula. Results: Patients with chest pain and positive troponin test (with confirmed cardiac event were found to have significantly elevated levels of TC, TG, LDL and significantly reduced HDL levels when compared to the patients who experienced only chest pain (negative troponin and healthy controls. Conclusions: Traditional lipid profile levels still can be used in screening populations to identify the subjects with high risk of developing cardiac event which is identified by highly sensitive and specific positive troponin test.

  3. High Fidelity, “Faster than Real-Time” Simulator for Predicting Power System Dynamic Behavior - Final Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Flueck, Alex [Illinois Inst. of Technology, Chicago, IL (United States)

    2017-07-14

    The “High Fidelity, Faster than Real­Time Simulator for Predicting Power System Dynamic Behavior” was designed and developed by Illinois Institute of Technology with critical contributions from Electrocon International, Argonne National Laboratory, Alstom Grid and McCoy Energy. Also essential to the project were our two utility partners: Commonwealth Edison and AltaLink. The project was a success due to several major breakthroughs in the area of large­scale power system dynamics simulation, including (1) a validated faster than real­ time simulation of both stable and unstable transient dynamics in a large­scale positive sequence transmission grid model, (2) a three­phase unbalanced simulation platform for modeling new grid devices, such as independently controlled single­phase static var compensators (SVCs), (3) the world’s first high fidelity three­phase unbalanced dynamics and protection simulator based on Electrocon’s CAPE program, and (4) a first­of­its­ kind implementation of a single­phase induction motor model with stall capability. The simulator results will aid power grid operators in their true time of need, when there is a significant risk of cascading outages. The simulator will accelerate performance and enhance accuracy of dynamics simulations, enabling operators to maintain reliability and steer clear of blackouts. In the long­term, the simulator will form the backbone of the newly conceived hybrid real­time protection and control architecture that will coordinate local controls, wide­area measurements, wide­area controls and advanced real­time prediction capabilities. The nation’s citizens will benefit in several ways, including (1) less down time from power outages due to the faster­than­real­time simulator’s predictive capability, (2) higher levels of reliability due to the detailed dynamics plus protection simulation capability, and (3) more resiliency due to the three­ phase unbalanced simulator’s ability to

  4. Position-specific prediction of methylation sites from sequence conservation based on information theory.

    Science.gov (United States)

    Shi, Yinan; Guo, Yanzhi; Hu, Yayun; Li, Menglong

    2015-07-23

    Protein methylation plays vital roles in many biological processes and has been implicated in various human diseases. To fully understand the mechanisms underlying methylation for use in drug design and work in methylation-related diseases, an initial but crucial step is to identify methylation sites. The use of high-throughput bioinformatics methods has become imperative to predict methylation sites. In this study, we developed a novel method that is based only on sequence conservation to predict protein methylation sites. Conservation difference profiles between methylated and non-methylated peptides were constructed by the information entropy (IE) in a wider neighbor interval around the methylation sites that fully incorporated all of the environmental information. Then, the distinctive neighbor residues were identified by the importance scores of information gain (IG). The most representative model was constructed by support vector machine (SVM) for Arginine and Lysine methylation, respectively. This model yielded a promising result on both the benchmark dataset and independent test set. The model was used to screen the entire human proteome, and many unknown substrates were identified. These results indicate that our method can serve as a useful supplement to elucidate the mechanism of protein methylation and facilitate hypothesis-driven experimental design and validation.

  5. Nomogram for prediction of level 2 axillary lymph node metastasis in proven level 1 node-positive breast cancer patients.

    Science.gov (United States)

    Jiang, Yanlin; Xu, Hong; Zhang, Hao; Ou, Xunyan; Xu, Zhen; Ai, Liping; Sun, Lisha; Liu, Caigang

    2017-09-22

    The current management of the axilla in level 1 node-positive breast cancer patients is axillary lymph node dissection regardless of the status of the level 2 axillary lymph nodes. The goal of this study was to develop a nomogram predicting the probability of level 2 axillary lymph node metastasis (L-2-ALNM) in patients with level 1 axillary node-positive breast cancer. We reviewed the records of 974 patients with pathology-confirmed level 1 node-positive breast cancer between 2010 and 2014 at the Liaoning Cancer Hospital and Institute. The patients were randomized 1:1 and divided into a modeling group and a validation group. Clinical and pathological features of the patients were assessed with uni- and multivariate logistic regression. A nomogram based on independent predictors for the L-2-ALNM identified by multivariate logistic regression was constructed. Independent predictors of L-2-ALNM by the multivariate logistic regression analysis included tumor size, Ki-67 status, histological grade, and number of positive level 1 axillary lymph nodes. The areas under the receiver operating characteristic curve of the modeling set and the validation set were 0.828 and 0.816, respectively. The false-negative rates of the L-2-ALNM nomogram were 1.82% and 7.41% for the predicted probability cut-off points of level 1 axillary lymph node metastasis. Patients with a low probability of L-2-ALNM could be spared level 2 axillary lymph node dissection, thereby reducing postoperative morbidity.

  6. Computational models for residual creep life prediction of power plant components

    International Nuclear Information System (INIS)

    Grewal, G.S.; Singh, A.K.; Ramamoortry, M.

    2006-01-01

    All high temperature - high pressure power plant components are prone to irreversible visco-plastic deformation by the phenomenon of creep. The steady state creep response as well as the total creep life of a material is related to the operational component temperature through, respectively, the exponential and inverse exponential relationships. Minor increases in the component temperature can thus have serious consequences as far as the creep life and dimensional stability of a plant component are concerned. In high temperature steam tubing in power plants, one mechanism by which a significant temperature rise can occur is by the growth of a thermally insulating oxide film on its steam side surface. In the present paper, an elegantly simple and computationally efficient technique is presented for predicting the residual creep life of steel components subjected to continual steam side oxide film growth. Similarly, fabrication of high temperature power plant components involves extensive use of welding as the fabrication process of choice. Naturally, issues related to the creep life of weldments have to be seriously addressed for safe and continual operation of the welded plant component. Unfortunately, a typical weldment in an engineering structure is a zone of complex microstructural gradation comprising of a number of distinct sub-zones with distinct meso-scale and micro-scale morphology of the phases and (even) chemistry and its creep life prediction presents considerable challenges. The present paper presents a stochastic algorithm, which can be' used for developing experimental creep-cavitation intensity versus residual life correlations for welded structures. Apart from estimates of the residual life in a mean field sense, the model can be used for predicting the reliability of the plant component in a rigorous probabilistic setting. (author)

  7. Discrete Model Predictive Control-Based Maximum Power Point Tracking for PV Systems: Overview and Evaluation

    DEFF Research Database (Denmark)

    Lashab, Abderezak; Sera, Dezso; Guerrero, Josep M.

    2018-01-01

    The main objective of this work is to provide an overview and evaluation of discrete model predictive controlbased maximum power point tracking (MPPT) for PV systems. A large number of MPC based MPPT methods have been recently introduced in the literature with very promising performance, however......, an in-depth investigation and comparison of these methods have not been carried out yet. Therefore, this paper has set out to provide an in-depth analysis and evaluation of MPC based MPPT methods applied to various common power converter topologies. The performance of MPC based MPPT is directly linked...... with the converter topology, and it is also affected by the accurate determination of the converter parameters, sensitivity to converter parameter variations is also investigated. The static and dynamic performance of the trackers are assessed according to the EN 50530 standard, using detailed simulation models...

  8. Application of an estimation model to predict future transients at US nuclear power plants

    International Nuclear Information System (INIS)

    Hallbert, B.P.; Blackman, H.S.

    1987-01-01

    A model developed by R.A. Fisher was applied to a set of Licensee Event Reports (LERs) summarizing transient initiating events at US commercial nuclear power plants. The empirical Bayes model was examined to study the feasibility of estimating the number of categories of transients which have not yet occurred at nuclear power plants. An examination of the model's predictive ability using an existing sample of data provided support for use of the model to estimate future transients. The estimate indicates that an approximate fifteen percent increase in the number of categories of transient initiating events may be expected during the period 1983--1993, assuming a stable process of transients. Limitations of the model and other possible applications are discussed. 10 refs., 1 fig., 3 tabs

  9. Model Predictive Control of Offshore Power Stations With Waste Heat Recovery

    DEFF Research Database (Denmark)

    Pierobon, Leonardo; Chan, Richard; Li, Xiangan

    2016-01-01

    The implementation of waste heat recovery units on oil and gas offshore platforms demands advances in both design methods and control systems. Model-based control algorithms can play an important role in the operation of offshore power stations. A novel regulator based on a linear model predictive...... control (MPC) coupled with a steady-state performance optimizer has been developed in the SIMULINK language and is documented in the paper. The test case is the regulation of a power system serving an oil and gas platform in the Norwegian Sea. One of the three gas turbines is combined with an organic...... Rankine cycle (ORC) turbogenerator to increase the energy conversion efficiency. Results show a potential reduction of frequency drop up to 40%for a step in the load set-point of 4 MW, compared to proportional–integral control systems. Fuel savings in the range of 2–3% are also expected by optimizing on...

  10. Distributed Model Predictive Load Frequency Control of Multi-area Power System with DFIGs

    Institute of Scientific and Technical Information of China (English)

    Yi Zhang; Xiangjie Liu; Bin Qu

    2017-01-01

    Reliable load frequency control(LFC) is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control(DMPC) based on coordination scheme.The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints(GRCs), load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed–loop performance, and computational burden with the physical constraints.

  11. How Many Model Evaluations Are Required To Predict The AEP Of A Wind Power Plant?

    International Nuclear Information System (INIS)

    Murcia, J P; Réthoré, P E; Natarajan, A; Sørensen, J D

    2015-01-01

    Wind farm flow models have advanced considerably with the use of large eddy simulations (LES) and Reynolds averaged Navier-Stokes (RANS) computations. The main limitation of these techniques is their high computational time requirements; which makes their use for wind farm annual energy production (AEP) predictions expensive. The objective of the present paper is to minimize the number of model evaluations required to capture the wind power plant's AEP using stationary wind farm flow models. Polynomial chaos techniques are proposed based on arbitrary Weibull distributed wind speed and Von Misses distributed wind direction. The correlation between wind direction and wind speed are captured by defining Weibull-parameters as functions of wind direction. In order to evaluate the accuracy of these methods the expectation and variance of the wind farm power distributions are compared against the traditional binning method with trapezoidal and Simpson's integration rules.The wind farm flow model used in this study is the semi-empirical wake model developed by Larsen [1]. Three test cases are studied: a single turbine, a simple and a real offshore wind power plant. A reduced number of model evaluations for a general wind power plant is proposed based on the convergence of the present method for each case. (paper)

  12. A Study of Performance in Low-Power Tokamak Reactor with Integrated Predictive Modeling Code

    International Nuclear Information System (INIS)

    Pianroj, Y.; Onjun, T.; Suwanna, S.; Picha, R.; Poolyarat, N.

    2009-07-01

    Full text: A fusion hybrid or a small fusion power output with low power tokamak reactor is presented as another useful application of nuclear fusion. Such tokamak can be used for fuel breeding, high-level waste transmutation, hydrogen production at high temperature, and testing of nuclear fusion technology components. In this work, an investigation of the plasma performance in a small fusion power output design is carried out using the BALDUR predictive integrated modeling code. The simulations of the plasma performance in this design are carried out using the empirical-based Mixed Bohm/gyro Bohm (B/gB) model, whereas the pedestal temperature model is based on magnetic and flow shear (δ α ρ ζ 2 ) stabilization pedestal width scaling. The preliminary results using this core transport model show that the central ion and electron temperatures are rather pessimistic. To improve the performance, the optimization approach are carried out by varying some parameters, such as plasma current and power auxiliary heating, which results in some improvement of plasma performance

  13. Model Predictive Control of Power Converters for Robust and Fast Operation of AC Microgrids

    DEFF Research Database (Denmark)

    Dragicevic, Tomislav

    2018-01-01

    the load power at the same time. Those functionalities are conventionally achieved by hierarchical linear control loops. However, they have limited transient response and high sensitivity to parameter variations. This paper aims to mitigate these problems by firstly introducing an improvement of the FCS......This paper proposes the application of a finite control set model predictive control (FCS-MPC) strategy in standalone ac microgrids (MGs). AC MGs are usually built from two or more voltage source converters (VSCs) which can regulate the voltage at the point of common coupling, while sharing......-MPC strategy for a single VSC based on tracking of derivative of the voltage reference trajectory. Using only a single step prediction horizon, the proposed strategy exhibits low computational expense but provides steady state performance comparable to PWM, while its transient response and robustness...

  14. Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

    Energy Technology Data Exchange (ETDEWEB)

    Xu Chengjian, E-mail: c.j.xu@umcg.nl [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van' t [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands)

    2012-03-15

    Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

  15. Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models.

    Science.gov (United States)

    Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A; van't Veld, Aart A

    2012-03-15

    To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended. Copyright © 2012 Elsevier Inc. All rights reserved.

  16. Nuclear power plant maintenance personnel reliability prediction (NPP/MPRP) effort at Oak Ridge National Laboratory

    International Nuclear Information System (INIS)

    Knee, H.E.; Haas, P.M.; Siegel, A.I.

    1981-01-01

    Human errors committed during maintenance activities are potentially a major contribution to the overall risk associated with the operation of a nuclear power plant (NPP). An NRC-sponsored program at Oak Ridge National Laboratory is attempting to develop a quantitative predictive technique to evaluate the contribution of maintenance errors to the overall NPP risk. The current work includes a survey of the requirements of potential users to ascertain the need for and content of the proposed quantitative model, plus an initial job/task analysis to determine the scope and applicability of various maintenance tasks. In addition, existing human reliability prediction models are being reviewed and assessed with respect to their applicability to NPP maintenance tasks. This paper discusses the status of the program and summarizes the results to date

  17. Model predictive control technologies for efficient and flexible power consumption in refrigeration systems

    DEFF Research Database (Denmark)

    Hovgaard, Tobias Gybel; Larsen, Lars F. S.; Edlund, Kristian

    2012-01-01

    . In this paper we describe a novel economic-optimizing Model Predictive Control (MPC) scheme that reduces operating costs by utilizing the thermal storage capabilities. A nonlinear optimization tool to handle a non-convex cost function is utilized for simulations with validated scenarios. In this way we...... explicitly address advantages from daily variations in outdoor temperature and electricity prices. Secondly, we formulate a new cost function that enables the refrigeration system to contribute with ancillary services to the balancing power market. This involvement can be economically beneficial...... of the system models allows us to describe and handle model as well as prediction uncertainties in this framework. This means we can demonstrate means for robustifying the performance of the controller....

  18. Prediction of critical flow rates through power-operated relief valves

    International Nuclear Information System (INIS)

    Abdollahian, D.; Singh, A.

    1983-01-01

    Existing single-phase and two-phase critical flow models are used to predict the flow rates through the power-operated relief valves tested in the EPRI Safety and Relief Valve test program. For liquid upstream conditions, Homogeneous Equilibrium Model, Moody, Henry-Fauske and Burnell two-phase critical flow models are used for comparison with data. Under steam upstream conditions, the flow rates are predicted either by the single-phase isentropic equations or the Homogeneous Equilibrium Model, depending on the thermodynamic condition of the fluid at the choking plane. The results of the comparisons are used to specify discharge coefficients for different valves under steam and liquid upstream conditions and evaluate the existing approximate critical flow relations for a wide range of subcooled water and steam conditions

  19. Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

    International Nuclear Information System (INIS)

    Xu Chengjian; Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van’t

    2012-01-01

    Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

  20. Optimal level of continuous positive airway pressure: auto-adjusting titration versus titration with a predictive equation.

    Science.gov (United States)

    Choi, Ji Ho; Jun, Young Joon; Oh, Jeong In; Jung, Jong Yoon; Hwang, Gyu Ho; Kwon, Soon Young; Lee, Heung Man; Kim, Tae Hoon; Lee, Sang Hag; Lee, Seung Hoon

    2013-05-01

    The aims of the present study were twofold. We sought to compare two methods of titrating the level of continuous positive airway pressure (CPAP) - auto-adjusting titration and titration using a predictive equation - with full-night manual titration used as the benchmark. We also investigated the reliability of the two methods in patients with obstructive sleep apnea syndrome (OSAS). Twenty consecutive adult patients with OSAS who had successful, full-night manual and auto-adjusting CPAP titration participated in this study. The titration pressure level was calculated with a previously developed predictive equation based on body mass index and apnea-hypopnea index. The mean titration pressure levels obtained with the manual, auto-adjusting, and predictive equation methods were 9.0 +/- 3.6, 9.4 +/- 3.0, and 8.1 +/- 1.6 cm H2O,respectively. There was a significant difference in the concordance within the range of +/- 2 cm H2O (p = 0.019) between both the auto-adjusting titration and the titration using the predictive equation compared to the full-night manual titration. However, there was no significant difference in the concordance within the range of +/- 1 cm H2O (p > 0.999). When compared to full-night manual titration as the standard method, auto-adjusting titration appears to be more reliable than using a predictive equation for determining the optimal CPAP level in patients with OSAS.

  1. Comparison of LOFT zero power physics testing measurement results with predicted values

    International Nuclear Information System (INIS)

    Rushton, B.L.; Howe, T.M.

    1978-01-01

    The results of zero power physics testing measurements in LOFT have been evaluated to assess the adequacy of the physics data used in the safety analyses performed for the LOFT FSAR and Technical Specifications. Comparisons of measured data with computed data were made for control rod worths, temperature coefficients, boron worths, and pressure coefficients. Measured boron concentrations at exact critical points were compared with predicted concentrations. Based on these comparisons, the reactivity parameter values used in the LOFT safety analyses were assessed for conservatism

  2. Predicting transmission of structure-borne sound power from machines by including terminal cross-coupling

    DEFF Research Database (Denmark)

    Ohlrich, Mogens

    2011-01-01

    of translational terminals in a global plane. This paired or bi-coupled power transmission represents the simplest case of cross-coupling. The procedure and quality of the predicted transmission using this improved technique is demonstrated experimentally for an electrical motor unit with an integrated radial fan......Structure-borne sound generated by audible vibration of machines in vehicles, equipment and house-hold appliances is often a major cause of noise. Such vibration of complex machines is mostly determined and quantified by measurements. It has been found that characterization of the vibratory source...

  3. Load Torque Compensator for Model Predictive Direct Current Control in High Power PMSM Drive Systems

    DEFF Research Database (Denmark)

    Preindl, Matthias; Schaltz, Erik

    2010-01-01

    In drive systems the most used control structure is the cascade control with an inner torque, i.e. current and an outer speed control loop. The fairly small converter switching frequency in high power applications, e.g. wind turbines lead to modest speed control performance. An improvement bring...... the use of a current controller which takes into account the discrete states of the inverter, e.g. DTC or a more modern approach: Model Predictive Direct Current Control (MPDCC). Moreover overshoots and oscillations in the speed are not desired in many applications, since they lead to mechanical stress...

  4. Prediction of accident sequence probabilities in a nuclear power plant due to earthquake events

    International Nuclear Information System (INIS)

    Hudson, J.M.; Collins, J.D.

    1980-01-01

    This paper presents a methodology to predict accident probabilities in nuclear power plants subject to earthquakes. The resulting computer program accesses response data to compute component failure probabilities using fragility functions. Using logical failure definitions for systems, and the calculated component failure probabilities, initiating event and safety system failure probabilities are synthesized. The incorporation of accident sequence expressions allows the calculation of terminal event probabilities. Accident sequences, with their occurrence probabilities, are finally coupled to a specific release category. A unique aspect of the methodology is an analytical procedure for calculating top event probabilities based on the correlated failure of primary events

  5. On accuracy of the wave finite element predictions of wavenumbers and power flow: A benchmark problem

    Science.gov (United States)

    Søe-Knudsen, Alf; Sorokin, Sergey

    2011-06-01

    This rapid communication is concerned with justification of the 'rule of thumb', which is well known to the community of users of the finite element (FE) method in dynamics, for the accuracy assessment of the wave finite element (WFE) method. An explicit formula linking the size of a window in the dispersion diagram, where the WFE method is trustworthy, with the coarseness of a FE mesh employed is derived. It is obtained by the comparison of the exact Pochhammer-Chree solution for an elastic rod having the circular cross-section with its WFE approximations. It is shown that the WFE power flow predictions are also valid within this window.

  6. Reflections on Researcher Identity and Power: The Impact of Positionality on Community Based Participatory Research (CBPR) Processes and Outcomes.

    Science.gov (United States)

    Muhammad, Michael; Wallerstein, Nina; Sussman, Andrew L; Avila, Magdalena; Belone, Lorenda; Duran, Bonnie

    2015-11-01

    The practice of community based participatory research (CBPR) has evolved over the past 20 years with the recognition that health equity is best achieved when academic researchers form collaborative partnerships with communities. This article theorizes the possibility that core principles of CBPR cannot be realistically applied unless unequal power relations are identified and addressed. It provides theoretical and empirical perspectives for understanding power, privilege, researcher identity and academic research team composition, and their effects on partnering processes and health disparity outcomes. The team's processes of conducting seven case studies of diverse partnerships in a national cross-site CBPR study are analyzed; the multi-disciplinary research team's self-reflections on identity and positionality are analyzed, privileging its combined racial, ethnic, and gendered life experiences, and integrating feminist and post-colonial theory into these reflections. Findings from the inquiry are shared, and incorporating academic researcher team identity is recommended as a core component of equalizing power distribution within CBPR.

  7. Study on profits and the financial position of the Dutch power transmission system operator Tennet 2005-2009

    International Nuclear Information System (INIS)

    2010-12-01

    A study has been conducted into the profits of the grid operator of the Dutch national high-voltage power transmission system operator TenneT in the years 2005 to 2009. Also attention is paid to the financial position of TenneT. These results are taken into account with regard to method decisions for TenneT in the fifth regulatory period. [nl

  8. Fault tolerant, multiplexed control rod position detection and indication system for nuclear power plants

    International Nuclear Information System (INIS)

    Dufek, W.L.; Jelovich, J.J.; Neuner, J.A.

    1977-01-01

    The majority of Westinghouse nuclear plants placed in service thus far have incorporated a Rod Position Indication system based upon an analog design philosophy. This system, while meeting all functional and accuracy requirements, has proven somewhat cumbersome, particularly in the area of initial field calibration and maintenance. This paper describes a new Digital Rod Position Indication system (DRPI) developed for use with pressurized water reactors. The system is based upon a digital design philosophy and meets all previous design constraints and environmental requirements. Further, fault tolerance, improved accuracy, interference from adjacent rods and the elimination of adjustments and calibration has been provided

  9. Review of the first line supervisory positions in nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Mullin, D; Mackenzie, C W [Hickling Corp. (Canada)

    1995-10-01

    The authors review the nature of the tasks performed by first line maintenance supervisors in three nuclear power plants. They compare these tasks to core supervisory training curriculum, supervisory job descriptions, and both the process related to performance appraisals, and the criteria applied in carrying out these performance evaluations. Recommendations have been made concerning methods of increasing the relevancy of training and improving the performance appraisal process. ( author). 5 figs.

  10. Review of the first line supervisory positions in nuclear power plants

    International Nuclear Information System (INIS)

    Mullin, D.; Mackenzie, C.W.

    1995-10-01

    The authors review the nature of the tasks performed by first line maintenance supervisors in three nuclear power plants. They compare these tasks to core supervisory training curriculum, supervisory job descriptions, and both the process related to performance appraisals, and the criteria applied in carrying out these performance evaluations. Recommendations have been made concerning methods of increasing the relevancy of training and improving the performance appraisal process. ( author). 5 figs

  11. Performance of a six-legged planetary rover - Power, positioning, and autonomous walking

    Science.gov (United States)

    Krotkov, Eric; Simmons, Reid

    The authors quantify several performance metrics for the Ambler, a six-legged robot configured for autonomous traversal of Mars-like terrain. They present power consumption measures for walking on sandy terrain and for vertical lifts at different velocities. They document the accuracy of a novel dead reckoning approach, and analyze the accuracy. They describe the results of autonomous walking experiments in terms of terrain traversed, walking speed, number of instructions executed and endurance.

  12. Barriers to women's representation in academic excellence and positions of power

    OpenAIRE

    Yousaf, Rizwana; Schmiede, Rudi

    2017-01-01

    "Nearly for half a century women's advancement in the workplace has been in a debate. Women’s under-represented in higher education institutions and universities across the globe, and especially in the most powerful or influential posts, is well established. Despite gender equality commitments and women's educational attainment, still, they are underrepresented. Regions and countries may vary in term of culture, achievements and development, but barriers for women's representation in academia...

  13. Aging predictions in nuclear power plants: Crosslinked polyolefin and EPR cable insulation materials

    International Nuclear Information System (INIS)

    Gillen, K.T.; Clough, R.L.

    1991-06-01

    In two earlier reports, we derived a time-temperature-dose rate superposition methodology, which, when applicable, can be used to predict cable degradation versus dose rate, temperature and exposure time. This methodology results in long-term predictive capabilities at the low dose rates appropriate to ambient nuclear power plant aging environments. The methodology was successfully applied to numerous important cable materials used in nuclear applications and the extrapolated predictions were verified by comparisons with long-term (7 to 12 year) results for similar or identical materials aged in nuclear environments. In this report, we test the methodology on three crosslinked polyolefin (CLPO) and two ethylene propylene rubber (EPR) cable insulation materials. The methodology applies to one of the CLPO materials and one of the EPR materials, allowing predictions to be made for these materials under low dose-rate, low temperature conditions. For the other materials, it is determined that, at low temperatures, a decrease in temperature at a constant radiation dose rate leads to an increase in the degradation rate for the mechanical properties. Since these results contradict the fundamental assumption underlying time-temperature-dose rate superposition, this methodology cannot be applied to such data. As indicated in the earlier reports, such anomalous results might be expected when attempting to model data taken across the crystalline melting region of semicrystalline materials. Nonetheless, the existing experimental evidence suggests that these CLPO and EPR materials have substantial aging endurance for typical reactor conditions. 28 refs., 26 figs., 3 tabs

  14. Prediction of crack coalescence of steam generator tubes in nuclear power plants

    International Nuclear Information System (INIS)

    Abou-Hanna, Jeries; McGreevy, Timothy E.; Majumdar, Saurin

    2004-01-01

    Prediction of failure pressures of cracked steam generator tubes of nuclear power plants is an important ingredient in scheduling inspection and repair of tubes. Prediction is usually based on nondestructive evaluation (NDE) of cracks. NDE often reveals two neighboring cracks. If the cracks interact, the tube pressure under which the ligament between the two cracks fails could be much lower than the critical burst pressure of an individual equivalent crack. The ability to accurately predict the ligament failure pressure, called ''coalescence pressure,'' is important. The failure criterion was established by nonlinear finite element model (FEM) analyses of coalescence of two 100% through-wall collinear cracks. The ligament failure is precipitated by local instability of the ligament under plane strain conditions. As a result of this local instability, the ligament thickness in the radial direction decreases abruptly with pressure. Good correlation of FEM analysis results with experimental data obtained at Argonne National Laboratory's Energy Technology Division demonstrated that nonlinear FEM analyses are capable of predicting the coalescence pressure accurately for 100% through-wall cracks. This failure criterion and FEA work have been extended to axial cracks of varying ligament width, crack length, and cases where cracks are offset by axial or circumferential ligaments

  15. Power Transformer Operating State Prediction Method Based on an LSTM Network

    Directory of Open Access Journals (Sweden)

    Hui Song

    2018-04-01

    Full Text Available The state of transformer equipment is usually manifested through a variety of information. The characteristic information will change with different types of equipment defects/faults, location, severity, and other factors. For transformer operating state prediction and fault warning, the key influencing factors of the transformer panorama information are analyzed. The degree of relative deterioration is used to characterize the deterioration of the transformer state. The membership relationship between the relative deterioration degree of each indicator and the transformer state is obtained through fuzzy processing. Through the long short-term memory (LSTM network, the evolution of the transformer status is extracted, and a data-driven state prediction model is constructed to realize preliminary warning of a potential fault of the equipment. Through the LSTM network, the quantitative index and qualitative index are organically combined in order to perceive the corresponding relationship between the characteristic parameters and the operating state of the transformer. The results of different time-scale prediction cases show that the proposed method can effectively predict the operation status of power transformers and accurately reflect their status.

  16. Short-term prediction of windfarm power output - from theory to practice

    International Nuclear Information System (INIS)

    Landberg, L.

    1998-01-01

    From the very complicated and evolved theories of boundary-layer meteorology encompassing the equations of turbulence and mean flow, a model has been derived to predict the power output from wind farms. For practical dispatching purposes the predictions must reach as far into the future as 36 hours. The model has been put into an operation frame-work where the predictions for a number of wind farms scattered all over Europe are available on-line on the World Wide Web. The system is very versatile and new wind farms can be included within a few days. The system is made up of predictions from the Danish Meteorological Institute HIRLAM model which are refined using the WASP model from Risoe National Laboratory. The paper will describe this operation set-up, give examples of the performance of the model of wind farms in the UK, Denmark, Greece and the US. An analysis of the error for a one-year period will also be presented. Finally, possible improvements will be discussed. These include Kalman filtering and other statistical methods. (Author)

  17. A new solar power output prediction based on hybrid forecast engine and decomposition model.

    Science.gov (United States)

    Zhang, Weijiang; Dang, Hongshe; Simoes, Rolando

    2018-06-12

    Regarding to the growing trend of photovoltaic (PV) energy as a clean energy source in electrical networks and its uncertain nature, PV energy prediction has been proposed by researchers in recent decades. This problem is directly effects on operation in power network while, due to high volatility of this signal, an accurate prediction model is demanded. A new prediction model based on Hilbert Huang transform (HHT) and integration of improved empirical mode decomposition (IEMD) with feature selection and forecast engine is presented in this paper. The proposed approach is divided into three main sections. In the first section, the signal is decomposed by the proposed IEMD as an accurate decomposition tool. To increase the accuracy of the proposed method, a new interpolation method has been used instead of cubic spline curve (CSC) fitting in EMD. Then the obtained output is entered into the new feature selection procedure to choose the best candidate inputs. Finally, the signal is predicted by a hybrid forecast engine composed of support vector regression (SVR) based on an intelligent algorithm. The effectiveness of the proposed approach has been verified over a number of real-world engineering test cases in comparison with other well-known models. The obtained results prove the validity of the proposed method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  18. Seismic response prediction for cabinets of nuclear power plants by using impact hammer test

    Energy Technology Data Exchange (ETDEWEB)

    Koo, Ki Young [Department of Civil and Structural Engineering, University of Sheffield, Sheffield (United Kingdom); Gook Cho, Sung [JACE KOREA, Gyeonggi-do (Korea, Republic of); Cui, Jintao [Department of Civil Engineering, Kunsan National University, Jeonbuk (Korea, Republic of); Kim, Dookie, E-mail: kim2kie@kunsan.ac.k [Department of Civil Engineering, Kunsan National University, Jeonbuk (Korea, Republic of)

    2010-10-15

    An effective method to predict the seismic response of electrical cabinets of nuclear power plants is developed. This method consists of three steps: (1) identification of the earthquake-equivalent force based on the idealized lumped-mass system of the cabinet, (2) identification of the state-space equation (SSE) model of the system using input-output measurements from impact hammer tests, and (3) seismic response prediction by calculating the output of the identified SSE model under the identified earthquake-equivalent force. A three-dimensional plate model of cabinet structures is presented for the numerical verification of the proposed method. Experimental validation of the proposed method is carried out on a three-story frame which represents the structure of a cabinet. The SSE model of the frame is accurately identified by impact hammer tests with high fitness values over 85% of the actual frame characteristics. Shaking table tests are performed using El Centro, Kobe, and Northridge earthquakes as input motions and the acceleration responses are measured. The responses of the model under the three earthquakes are predicted and then compared with the measured responses. The predicted and measured responses agree well with each other with fitness values of 65-75%. The proposed method is more advantageous over other methods that are based on finite element (FE) model updating since it is free from FE modeling errors. It will be especially effective for cabinet structures in nuclear power plants where conducting shaking table tests may not be feasible. Limitations of the proposed method are also discussed.

  19. Parameter optimization of parenchymal texture analysis for prediction of false-positive recalls from screening mammography

    Science.gov (United States)

    Ray, Shonket; Keller, Brad M.; Chen, Jinbo; Conant, Emily F.; Kontos, Despina

    2016-03-01

    This work details a methodology to obtain optimal parameter values for a locally-adaptive texture analysis algorithm that extracts mammographic texture features representative of breast parenchymal complexity for predicting falsepositive (FP) recalls from breast cancer screening with digital mammography. The algorithm has two components: (1) adaptive selection of localized regions of interest (ROIs) and (2) Haralick texture feature extraction via Gray- Level Co-Occurrence Matrices (GLCM). The following parameters were systematically varied: mammographic views used, upper limit of the ROI window size used for adaptive ROI selection, GLCM distance offsets, and gray levels (binning) used for feature extraction. Each iteration per parameter set had logistic regression with stepwise feature selection performed on a clinical screening cohort of 474 non-recalled women and 68 FP recalled women; FP recall prediction was evaluated using area under the curve (AUC) of the receiver operating characteristic (ROC) and associations between the extracted features and FP recall were assessed via odds ratios (OR). A default instance of mediolateral (MLO) view, upper ROI size limit of 143.36 mm (2048 pixels2), GLCM distance offset combination range of 0.07 to 0.84 mm (1 to 12 pixels) and 16 GLCM gray levels was set. The highest ROC performance value of AUC=0.77 [95% confidence intervals: 0.71-0.83] was obtained at three specific instances: the default instance, upper ROI window equal to 17.92 mm (256 pixels2), and gray levels set to 128. The texture feature of sum average was chosen as a statistically significant (p<0.05) predictor and associated with higher odds of FP recall for 12 out of 14 total instances.

  20. [Predictive factors for failure of non-invasive positive pressure ventilation in immunosuppressed patients with acute respiratory failure].

    Science.gov (United States)

    Jia, Xiangli; Yan, Ci; Xu, Sicheng; Gu, Xingli; Wan, Qiufeng; Hu, Xinying; Li, Jingwen; Liu, Guangming; Caikai, Shareli; Guo, Zhijin

    2018-02-01

    To evaluate the predictive factors for failure of non-invasive positive pressure ventilation (NIPPV) in immunosuppressed patients with acute respiratory failure (ARF). The clinical data of 118 immuno-deficient patients treated with NIPPV in the respiratory and intensive care unit (RICU) of the First Affiliated Hospital of Xinjiang Medical University from January 2012 to August 2017 were retrospectively analyzed. The patients were divided into a non-endotracheal intubation (ETI) group (n = 62) and ETI group (n = 56) according to whether ETI was performed during the hospitalization period or not. Each observed indicator was analyzed by univariate analysis, and factors leading to failure of NIPPV were further analyzed by Logistic regression. Receiver operating characteristic (ROC) curve was plotted to evaluate the predictive value of risk factors for failure of NIPPV in immunosuppressed patients with ARF. The non-intubation rate for NIPPV in immunosuppressed patients was 50.8% (60/118). Compared with the non-ETI group, the body temperature, pH value in the ETI group were significantly increased, the partial pressure of arterial carbon dioxide (PaCO 2 ) was significantly decreased, the ratio of oxygenation index (PaO 2 /FiO 2 ) failure of NIPPV. ROC curve analysis showed that the APACHE II score ≥ 20 and PaO 2 /FiO 2 failure of NIPPV, the area under ROC curve (AUC) of the APACHE II score ≥ 20 was 0.787, the sensitivity was 83.93%, the specificity was 69.35%, the positive predict value (PPV) was 71.21%, the negative predict value (NPV) was 82.69%, the positive likelihood ratio (PLR) was 2.74, the negative likelihood ratio (NLR) was 0.23, and Youden index was 0.53; the AUC of PaO 2 /FiO 2 failure of NIPPV in immunocompromised patients.