Ensuring the Reliable Operation of the Power Grid: State-Based and Distributed Approaches to Scheduling Energy and Contingency Reserves

NASA Astrophysics Data System (ADS)

Prada, Jose Fernando

Keeping a contingency reserve in power systems is necessary to preserve the security of real-time operations. This work studies two different approaches to the optimal allocation of energy and reserves in the day-ahead generation scheduling process. Part I presents a stochastic security-constrained unit commitment model to co-optimize energy and the locational reserves required to respond to a set of uncertain generation contingencies, using a novel state-based formulation. The model is applied in an offer-based electricity market to allocate contingency reserves throughout the power grid, in order to comply with the N-1 security criterion under transmission congestion. The objective is to minimize expected dispatch and reserve costs, together with post contingency corrective redispatch costs, modeling the probability of generation failure and associated post contingency states. The characteristics of the scheduling problem are exploited to formulate a computationally efficient method, consistent with established operational practices. We simulated the distribution of locational contingency reserves on the IEEE RTS96 system and compared the results with the conventional deterministic method. We found that assigning locational spinning reserves can guarantee an N-1 secure dispatch accounting for transmission congestion at a reasonable extra cost. The simulations also showed little value of allocating downward reserves but sizable operating savings from co-optimizing locational nonspinning reserves. Overall, the results indicate the computational tractability of the proposed method. Part II presents a distributed generation scheduling model to optimally allocate energy and spinning reserves among competing generators in a day-ahead market. The model is based on the coordination between individual generators and a market entity. The proposed method uses forecasting, augmented pricing and locational signals to induce efficient commitment of generators based on firm posted prices. It is price-based but does not rely on multiple iterations, minimizes information exchange and simplifies the market clearing process. Simulations of the distributed method performed on a six-bus test system showed that, using an appropriate set of prices, it is possible to emulate the results of a conventional centralized solution, without need of providing make-whole payments to generators. Likewise, they showed that the distributed method can accommodate transactions with different products and complex security constraints.

Day-Ahead Anticipation of Complex Network Vulnerability

NASA Astrophysics Data System (ADS)

Stefanov, S. Z.; Wang, Paul P.

2017-11-01

In this paper, a day-ahead anticipation of complex network vulnerability for an intentional threat of an attack or a shock is carried out. An ecological observer is introduced for that reason, which is a watch in the intentional multiverse, tiled by cells; dynamics of the intentional threat for a day-ahead is characterized by a space-time cell; spreading of the intentional threat is derived from its energy; duration of the intentional threat is found by the self-assembling of a space-time cell; the lower bound of probability is assessed to anticipate for a day-ahead the intentional threat; it is indicated that this vulnerability anticipation for a day-ahead is right when the intentional threat leads to dimension doubling of the complex network.

77 FR 56745 - Patriot Day and National Day of Service and Remembrance, 2012

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-13

... helped our Nation rebuild and recover long after the dust had settled, donating and volunteering and... compassion by serving their communities in the days and weeks ahead. From volunteering with a faith-based...

Multi-time scale energy management of wind farms based on comprehensive evaluation technology

NASA Astrophysics Data System (ADS)

Xu, Y. P.; Huang, Y. H.; Liu, Z. J.; Wang, Y. F.; Li, Z. Y.; Guo, L.

2017-11-01

A novel energy management of wind farms is proposed in this paper. Firstly, a novel comprehensive evaluation system is proposed to quantify economic properties of each wind farm to make the energy management more economical and reasonable. Then, a combination of multi time-scale schedule method is proposed to develop a novel energy management. The day-ahead schedule optimizes unit commitment of thermal power generators. The intraday schedule is established to optimize power generation plan for all thermal power generating units, hydroelectric generating sets and wind power plants. At last, the power generation plan can be timely revised in the process of on-line schedule. The paper concludes with simulations conducted on a real provincial integrated energy system in northeast China. Simulation results have validated the proposed model and corresponding solving algorithms.

Determination of the Prosumer's Optimal Bids

NASA Astrophysics Data System (ADS)

Ferruzzi, Gabriella; Rossi, Federico; Russo, Angela

2015-12-01

This paper considers a microgrid connected with a medium-voltage (MV) distribution network. It is assumed that the microgrid, which is managed by a prosumer, operates in a competitive environment and participates in the day-ahead market. Then, as the first step of the short-term management problem, the prosumer must determine the bids to be submitted to the market. The offer strategy is based on the application of an optimization model, which is solved for different hourly price profiles of energy exchanged with the main grid. The proposed procedure is applied to a microgrid and four different its configurations were analyzed. The configurations consider the presence of thermoelectric units that only produce electricity, a boiler or/and cogeneration power plants for the thermal loads, and an electric storage system. The numerical results confirmed the numerous theoretical considerations that have been made.

Barriers to Breast Cancer Screening Among Latinas in the U.S.-Mexico Border Region

DTIC Science & Technology

2009-05-01

Catholic religion, % 22.13 AHEAD cohort, % 51.53 Age, years 68.25 Education, years 12.26 Household wealth, US$ 100,000 2.99 Sample size 1143 AHEAD, Asset and...Methods Based on Ranks. San Francisco: Holden-Day; 1975. 13. Franses PH, Cramer M. On the number of categories in an ordered regression model. Erasmus

Model Predictive Control-based Optimal Coordination of Distributed Energy Resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming

2013-01-07

Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive controlmore » (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.« less

Model Predictive Control-based Optimal Coordination of Distributed Energy Resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming

2013-04-03

Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive controlmore » (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.« less

Management of a stage-structured insect pest: an application of approximate optimization.

PubMed

Hackett, Sean C; Bonsall, Michael B

2018-06-01

Ecological decision problems frequently require the optimization of a sequence of actions over time where actions may have both immediate and downstream effects. Dynamic programming can solve such problems only if the dimensionality is sufficiently low. Approximate dynamic programming (ADP) provides a suite of methods applicable to problems of arbitrary complexity at the expense of guaranteed optimality. The most easily generalized method is the look-ahead policy: a brute-force algorithm that identifies reasonable actions by constructing and solving a series of temporally truncated approximations of the full problem over a defined planning horizon. We develop and apply this approach to a pest management problem inspired by the Mediterranean fruit fly, Ceratitis capitata. The model aims to minimize the cumulative costs of management actions and medfly-induced losses over a single 16-week season. The medfly population is stage-structured and grows continuously while management decisions are made at discrete, weekly intervals. For each week, the model chooses between inaction, insecticide application, or one of six sterile insect release ratios. Look-ahead policy performance is evaluated over a range of planning horizons, two levels of crop susceptibility to medfly and three levels of pesticide persistence. In all cases, the actions proposed by the look-ahead policy are contrasted to those of a myopic policy that minimizes costs over only the current week. We find that look-ahead policies always out-performed a myopic policy and decision quality is sensitive to the temporal distribution of costs relative to the planning horizon: it is beneficial to extend the planning horizon when it excludes pertinent costs. However, longer planning horizons may reduce decision quality when major costs are resolved imminently. ADP methods such as the look-ahead-policy-based approach developed here render questions intractable to dynamic programming amenable to inference but should be applied carefully as their flexibility comes at the expense of guaranteed optimality. However, given the complexity of many ecological management problems, the capacity to propose a strategy that is "good enough" using a more representative problem formulation may be preferable to an optimal strategy derived from a simplified model. © 2018 by the Ecological Society of America.

Single step optimization of manipulator maneuvers with variable structure control

NASA Technical Reports Server (NTRS)

Chen, N.; Dwyer, T. A. W., III

1987-01-01

One step ahead optimization has been recently proposed for spacecraft attitude maneuvers as well as for robot manipulator maneuvers. Such a technique yields a discrete time control algorithm implementable as a sequence of state-dependent, quadratic programming problems for acceleration optimization. Its sensitivity to model accuracy, for the required inversion of the system dynamics, is shown in this paper to be alleviated by a fast variable structure control correction, acting between the sampling intervals of the slow one step ahead discrete time acceleration command generation algorithm. The slow and fast looping concept chosen follows that recently proposed for optimal aiming strategies with variable structure control. Accelerations required by the VSC correction are reserved during the slow one step ahead command generation so that the ability to overshoot the sliding surface is guaranteed.

Potential Arbitrage Revenue of Energy Storage Systems in PJM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salles, Mauricio; Huang, Junling; Aziz, Michael

The volatility of electricity prices is attracting interest in the opportunity of providing net revenue by energy arbitrage. We analyzed the potential revenue of a generic Energy Storage System (ESS) in 7395 different locations within the electricity markets of Pennsylvania-New Jersey-Maryland interconnection (PJM), the largest U.S. regional transmission organization, using hourly locational marginal prices over the seven-year period 2008–2014. Assuming a price-taking ESS with perfect foresight in the real-time market, we optimized the charge-discharge profile to determine the maximum potential revenue for a 1 MW system as a function of energy/power ratio, or rated discharge duration, from 1 to 14more » h, including a limited analysis of sensitivity to round-trip efficiency. We determined minimum potential revenue with a similar analysis of the day-ahead market. We presented the distribution over the set of nodes and years of price, price volatility, and maximum potential arbitrage revenue. From these results, we determined the break even overnight installed cost of an ESS below which arbitrage would be profitable, its dependence on rated discharge duration, its distribution over grid nodes, and its variation over the years. We showed that dispatch into real-time markets based on day-ahead market settlement prices is a simple, feasible method that raises the lower bound on the achievable arbitrage revenue.« less

Potential Arbitrage Revenue of Energy Storage Systems in PJM

DOE PAGES

Salles, Mauricio; Huang, Junling; Aziz, Michael; ...

2017-07-27

The volatility of electricity prices is attracting interest in the opportunity of providing net revenue by energy arbitrage. We analyzed the potential revenue of a generic Energy Storage System (ESS) in 7395 different locations within the electricity markets of Pennsylvania-New Jersey-Maryland interconnection (PJM), the largest U.S. regional transmission organization, using hourly locational marginal prices over the seven-year period 2008–2014. Assuming a price-taking ESS with perfect foresight in the real-time market, we optimized the charge-discharge profile to determine the maximum potential revenue for a 1 MW system as a function of energy/power ratio, or rated discharge duration, from 1 to 14more » h, including a limited analysis of sensitivity to round-trip efficiency. We determined minimum potential revenue with a similar analysis of the day-ahead market. We presented the distribution over the set of nodes and years of price, price volatility, and maximum potential arbitrage revenue. From these results, we determined the break even overnight installed cost of an ESS below which arbitrage would be profitable, its dependence on rated discharge duration, its distribution over grid nodes, and its variation over the years. We showed that dispatch into real-time markets based on day-ahead market settlement prices is a simple, feasible method that raises the lower bound on the achievable arbitrage revenue.« less

Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoff, Thomas Hoff; Kankiewicz, Adam

Four major research objectives were completed over the course of this study. Three of the objectives were to evaluate three, new, state-of-the-art solar irradiance forecasting models. The fourth objective was to improve the California Independent System Operator’s (ISO) load forecasts by integrating behind-the-meter (BTM) PV forecasts. The three, new, state-of-the-art solar irradiance forecasting models included: the infrared (IR) satellite-based cloud motion vector (CMV) model; the WRF-SolarCA model and variants; and the Optimized Deep Machine Learning (ODML)-training model. The first two forecasting models targeted known weaknesses in current operational solar forecasts. They were benchmarked against existing operational numerical weather prediction (NWP)more » forecasts, visible satellite CMV forecasts, and measured PV plant power production. IR CMV, WRF-SolarCA, and ODML-training forecasting models all improved the forecast to a significant degree. Improvements varied depending on time of day, cloudiness index, and geographic location. The fourth objective was to demonstrate that the California ISO’s load forecasts could be improved by integrating BTM PV forecasts. This objective represented the project’s most exciting and applicable gains. Operational BTM forecasts consisting of 200,000+ individual rooftop PV forecasts were delivered into the California ISO’s real-time automated load forecasting (ALFS) environment. They were then evaluated side-by-side with operational load forecasts with no BTM-treatment. Overall, ALFS-BTM day-ahead (DA) forecasts performed better than baseline ALFS forecasts when compared to actual load data. Specifically, ALFS-BTM DA forecasts were observed to have the largest reduction of error during the afternoon on cloudy days. Shorter term 30 minute-ahead ALFS-BTM forecasts were shown to have less error under all sky conditions, especially during the morning time periods when traditional load forecasts often experience their largest uncertainties. This work culminated in a GO decision being made by the California ISO to include zonal BTM forecasts into its operational load forecasting system. The California ISO’s Manager of Short Term Forecasting, Jim Blatchford, summarized the research performed in this project with the following quote: “The behind-the-meter (BTM) California ISO region forecasting research performed by Clean Power Research and sponsored by the Department of Energy’s SUNRISE program was an opportunity to verify value and demonstrate improved load forecast capability. In 2016, the California ISO will be incorporating the BTM forecast into the Hour Ahead and Day Ahead load models to look for improvements in the overall load forecast accuracy as BTM PV capacity continues to grow.”« less

Predicting Jakarta composite index using hybrid of fuzzy time series and support vector regression models

NASA Astrophysics Data System (ADS)

Febrian Umbara, Rian; Tarwidi, Dede; Budi Setiawan, Erwin

2018-03-01

The paper discusses the prediction of Jakarta Composite Index (JCI) in Indonesia Stock Exchange. The study is based on JCI historical data for 1286 days to predict the value of JCI one day ahead. This paper proposes predictions done in two stages., The first stage using Fuzzy Time Series (FTS) to predict values of ten technical indicators, and the second stage using Support Vector Regression (SVR) to predict the value of JCI one day ahead, resulting in a hybrid prediction model FTS-SVR. The performance of this combined prediction model is compared with the performance of the single stage prediction model using SVR only. Ten technical indicators are used as input for each model.

Development and validation of a 5-day-ahead hay fever forecast for patients with grass-pollen-induced allergic rhinitis

NASA Astrophysics Data System (ADS)

de Weger, Letty A.; Beerthuizen, Thijs; Hiemstra, Pieter S.; Sont, Jacob K.

2014-08-01

One-third of the Dutch population suffers from allergic rhinitis, including hay fever. In this study, a 5-day-ahead hay fever forecast was developed and validated for grass pollen allergic patients in the Netherlands. Using multiple regression analysis, a two-step pollen and hay fever symptom prediction model was developed using actual and forecasted weather parameters, grass pollen data and patient symptom diaries. Therefore, 80 patients with a grass pollen allergy rated the severity of their hay fever symptoms during the grass pollen season in 2007 and 2008. First, a grass pollen forecast model was developed using the following predictors: (1) daily means of grass pollen counts of the previous 10 years; (2) grass pollen counts of the previous 2-week period of the current year; and (3) maximum, minimum and mean temperature ( R 2 = 0.76). The second modeling step concerned the forecasting of hay fever symptom severity and included the following predictors: (1) forecasted grass pollen counts; (2) day number of the year; (3) moving average of the grass pollen counts of the previous 2 week-periods; and (4) maximum and mean temperatures ( R 2 = 0.81). Since the daily hay fever forecast is reported in three categories (low-, medium- and high symptom risk), we assessed the agreement between the observed and the 1- to 5-day-ahead predicted risk categories by kappa, which ranged from 65 % to 77 %. These results indicate that a model based on forecasted temperature and grass pollen counts performs well in predicting symptoms of hay fever up to 5 days ahead.

Development and validation of a 5-day-ahead hay fever forecast for patients with grass-pollen-induced allergic rhinitis.

PubMed

de Weger, Letty A; Beerthuizen, Thijs; Hiemstra, Pieter S; Sont, Jacob K

2014-08-01

One-third of the Dutch population suffers from allergic rhinitis, including hay fever. In this study, a 5-day-ahead hay fever forecast was developed and validated for grass pollen allergic patients in the Netherlands. Using multiple regression analysis, a two-step pollen and hay fever symptom prediction model was developed using actual and forecasted weather parameters, grass pollen data and patient symptom diaries. Therefore, 80 patients with a grass pollen allergy rated the severity of their hay fever symptoms during the grass pollen season in 2007 and 2008. First, a grass pollen forecast model was developed using the following predictors: (1) daily means of grass pollen counts of the previous 10 years; (2) grass pollen counts of the previous 2-week period of the current year; and (3) maximum, minimum and mean temperature (R (2)=0.76). The second modeling step concerned the forecasting of hay fever symptom severity and included the following predictors: (1) forecasted grass pollen counts; (2) day number of the year; (3) moving average of the grass pollen counts of the previous 2 week-periods; and (4) maximum and mean temperatures (R (2)=0.81). Since the daily hay fever forecast is reported in three categories (low-, medium- and high symptom risk), we assessed the agreement between the observed and the 1- to 5-day-ahead predicted risk categories by kappa, which ranged from 65 % to 77 %. These results indicate that a model based on forecasted temperature and grass pollen counts performs well in predicting symptoms of hay fever up to 5 days ahead.

Smoothing-based compressed state Kalman filter for joint state-parameter estimation: Applications in reservoir characterization and CO2 storage monitoring

NASA Astrophysics Data System (ADS)

Li, Y. J.; Kokkinaki, Amalia; Darve, Eric F.; Kitanidis, Peter K.

2017-08-01

The operation of most engineered hydrogeological systems relies on simulating physical processes using numerical models with uncertain parameters and initial conditions. Predictions by such uncertain models can be greatly improved by Kalman-filter techniques that sequentially assimilate monitoring data. Each assimilation constitutes a nonlinear optimization, which is solved by linearizing an objective function about the model prediction and applying a linear correction to this prediction. However, if model parameters and initial conditions are uncertain, the optimization problem becomes strongly nonlinear and a linear correction may yield unphysical results. In this paper, we investigate the utility of one-step ahead smoothing, a variant of the traditional filtering process, to eliminate nonphysical results and reduce estimation artifacts caused by nonlinearities. We present the smoothing-based compressed state Kalman filter (sCSKF), an algorithm that combines one step ahead smoothing, in which current observations are used to correct the state and parameters one step back in time, with a nonensemble covariance compression scheme, that reduces the computational cost by efficiently exploring the high-dimensional state and parameter space. Numerical experiments show that when model parameters are uncertain and the states exhibit hyperbolic behavior with sharp fronts, as in CO2 storage applications, one-step ahead smoothing reduces overshooting errors and, by design, gives physically consistent state and parameter estimates. We compared sCSKF with commonly used data assimilation methods and showed that for the same computational cost, combining one step ahead smoothing and nonensemble compression is advantageous for real-time characterization and monitoring of large-scale hydrogeological systems with sharp moving fronts.

Is the economic value of hydrological forecasts related to their quality? Case study of the hydropower sector.

NASA Astrophysics Data System (ADS)

Cassagnole, Manon; Ramos, Maria-Helena; Thirel, Guillaume; Gailhard, Joël; Garçon, Rémy

2017-04-01

The improvement of a forecasting system and the evaluation of the quality of its forecasts are recurrent steps in operational practice. However, the evaluation of forecast value or forecast usefulness for better decision-making is, to our knowledge, less frequent, even if it might be essential in many sectors such as hydropower and flood warning. In the hydropower sector, forecast value can be quantified by the economic gain obtained with the optimization of operations or reservoir management rules. Several hydropower operational systems use medium-range forecasts (up to 7-10 days ahead) and energy price predictions to optimize hydropower production. Hence, the operation of hydropower systems, including the management of water in reservoirs, is impacted by weather, climate and hydrologic variability as well as extreme events. In order to assess how the quality of hydrometeorological forecasts impact operations, it is essential to first understand if and how operations and management rules are sensitive to input predictions of different quality. This study investigates how 7-day ahead deterministic and ensemble streamflow forecasts of different quality might impact the economic gains of energy production. It is based on a research model developed by Irstea and EDF to investigate issues relevant to the links between quality and value of forecasts in the optimisation of energy production at the short range. Based on streamflow forecasts and pre-defined management constraints, the model defines the best hours (i.e., the hours with high energy prices) to produce electricity. To highlight the link between forecasts quality and their economic value, we built several synthetic ensemble forecasts based on observed streamflow time series. These inputs are generated in a controlled environment in order to obtain forecasts of different quality in terms of accuracy and reliability. These forecasts are used to assess the sensitivity of the decision model to forecast quality. Relationships between forecast quality and economic value are discussed. This work is part of the IMPREX project, a research project supported by the European Commission under the Horizon 2020 Framework programme, with grant No. 641811 (http://www.imprex.eu)

A three-stage birandom program for unit commitment with wind power uncertainty.

PubMed

Zhang, Na; Li, Weidong; Liu, Rao; Lv, Quan; Sun, Liang

2014-01-01

The integration of large-scale wind power adds a significant uncertainty to power system planning and operating. The wind forecast error is decreased with the forecast horizon, particularly when it is from one day to several hours ahead. Integrating intraday unit commitment (UC) adjustment process based on updated ultra-short term wind forecast information is one way to improve the dispatching results. A novel three-stage UC decision method, in which the day-ahead UC decisions are determined in the first stage, the intraday UC adjustment decisions of subfast start units are determined in the second stage, and the UC decisions of fast-start units and dispatching decisions are determined in the third stage is presented. Accordingly, a three-stage birandom UC model is presented, in which the intraday hours-ahead forecasted wind power is formulated as a birandom variable, and the intraday UC adjustment event is formulated as a birandom event. The equilibrium chance constraint is employed to ensure the reliability requirement. A birandom simulation based hybrid genetic algorithm is designed to solve the proposed model. Some computational results indicate that the proposed model provides UC decisions with lower expected total costs.

77 FR 19280 - Increasing Market and Planning Efficiency Through Improved Software; Notice of Technical...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-30

... Market and Planning Efficiency Through Improved Software; Notice of Technical Conference: Increasing Real-Time and Day- Ahead Market Efficiency Through Improved Software Take notice that Commission staff will...-time and day-ahead market efficiency through improved software. A detailed agenda with the list of and...

76 FR 28022 - Increasing Market and Planning Efficiency Through Improved Software; Notice of Technical...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-13

... Market and Planning Efficiency Through Improved Software; Notice of Technical Conference: Increasing Real-Time and Day- Ahead Market Efficiency Through Improved Software Take notice that Commission staff will... for increasing real-time and day-ahead market efficiency through improved software. This conference...

Dual pricing algorithm in ISO markets

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Neill, Richard P.; Castillo, Anya; Eldridge, Brent

The challenge to create efficient market clearing prices in centralized day-ahead electricity markets arises from inherent non-convexities in unit commitment problems. When this aspect is ignored, marginal prices may result in economic losses to market participants who are part of the welfare maximizing solution. In this essay, we present an axiomatic approach to efficient prices and cost allocation for a revenue neutral and non-confiscatory day-ahead market. Current cost allocation practices do not adequately attribute costs based on transparent cost causation criteria. Instead we propose an ex post multi-part pricing scheme, which we refer to as the Dual Pricing Algorithm. Lastly,more » our approach can be incorporated into current dayahead markets without altering the market equilibrium.« less

Dual pricing algorithm in ISO markets

DOE PAGES

O'Neill, Richard P.; Castillo, Anya; Eldridge, Brent; ...

2016-10-10

The challenge to create efficient market clearing prices in centralized day-ahead electricity markets arises from inherent non-convexities in unit commitment problems. When this aspect is ignored, marginal prices may result in economic losses to market participants who are part of the welfare maximizing solution. In this essay, we present an axiomatic approach to efficient prices and cost allocation for a revenue neutral and non-confiscatory day-ahead market. Current cost allocation practices do not adequately attribute costs based on transparent cost causation criteria. Instead we propose an ex post multi-part pricing scheme, which we refer to as the Dual Pricing Algorithm. Lastly,more » our approach can be incorporated into current dayahead markets without altering the market equilibrium.« less

Artificial neural network intelligent method for prediction

NASA Astrophysics Data System (ADS)

Trifonov, Roumen; Yoshinov, Radoslav; Pavlova, Galya; Tsochev, Georgi

2017-09-01

Accounting and financial classification and prediction problems are high challenge and researchers use different methods to solve them. Methods and instruments for short time prediction of financial operations using artificial neural network are considered. The methods, used for prediction of financial data as well as the developed forecasting system with neural network are described in the paper. The architecture of a neural network used four different technical indicators, which are based on the raw data and the current day of the week is presented. The network developed is used for forecasting movement of stock prices one day ahead and consists of an input layer, one hidden layer and an output layer. The training method is algorithm with back propagation of the error. The main advantage of the developed system is self-determination of the optimal topology of neural network, due to which it becomes flexible and more precise The proposed system with neural network is universal and can be applied to various financial instruments using only basic technical indicators as input data.

Flight Departure Delay and Rerouting Under Uncertainty in En Route Convective Weather

NASA Technical Reports Server (NTRS)

Mukherjee, Avijit; Grabbe, Shon; Sridhar, Banavar

2011-01-01

Delays caused by uncertainty in weather forecasts can be reduced by improving traffic flow management decisions. This paper presents a methodology for traffic flow management under uncertainty in convective weather forecasts. An algorithm for assigning departure delays and reroutes to aircraft is presented. Departure delay and route assignment are executed at multiple stages, during which, updated weather forecasts and flight schedules are used. At each stage, weather forecasts up to a certain look-ahead time are treated as deterministic and flight scheduling is done to mitigate the impact of weather on four-dimensional flight trajectories. Uncertainty in weather forecasts during departure scheduling results in tactical airborne holding of flights. The amount of airborne holding depends on the accuracy of forecasts as well as the look-ahead time included in the departure scheduling. The weather forecast look-ahead time is varied systematically within the experiments performed in this paper to analyze its effect on flight delays. Based on the results, longer look-ahead times cause higher departure delays and additional flying time due to reroutes. However, the amount of airborne holding necessary to prevent weather incursions reduces when the forecast look-ahead times are higher. For the chosen day of traffic and weather, setting the look-ahead time to 90 minutes yields the lowest total delay cost.

Constructing probabilistic scenarios for wide-area solar power generation

DOE PAGES

Woodruff, David L.; Deride, Julio; Staid, Andrea; ...

2017-12-22

Optimizing thermal generation commitments and dispatch in the presence of high penetrations of renewable resources such as solar energy requires a characterization of their stochastic properties. In this study, we describe novel methods designed to create day-ahead, wide-area probabilistic solar power scenarios based only on historical forecasts and associated observations of solar power production. Each scenario represents a possible trajectory for solar power in next-day operations with an associated probability computed by algorithms that use historical forecast errors. Scenarios are created by segmentation of historic data, fitting non-parametric error distributions using epi-splines, and then computing specific quantiles from these distributions.more » Additionally, we address the challenge of establishing an upper bound on solar power output. Our specific application driver is for use in stochastic variants of core power systems operations optimization problems, e.g., unit commitment and economic dispatch. These problems require as input a range of possible future realizations of renewables production. However, the utility of such probabilistic scenarios extends to other contexts, e.g., operator and trader situational awareness. Finally, we compare the performance of our approach to a recently proposed method based on quantile regression, and demonstrate that our method performs comparably to this approach in terms of two widely used methods for assessing the quality of probabilistic scenarios: the Energy score and the Variogram score.« less

Constructing probabilistic scenarios for wide-area solar power generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woodruff, David L.; Deride, Julio; Staid, Andrea

Optimizing thermal generation commitments and dispatch in the presence of high penetrations of renewable resources such as solar energy requires a characterization of their stochastic properties. In this study, we describe novel methods designed to create day-ahead, wide-area probabilistic solar power scenarios based only on historical forecasts and associated observations of solar power production. Each scenario represents a possible trajectory for solar power in next-day operations with an associated probability computed by algorithms that use historical forecast errors. Scenarios are created by segmentation of historic data, fitting non-parametric error distributions using epi-splines, and then computing specific quantiles from these distributions.more » Additionally, we address the challenge of establishing an upper bound on solar power output. Our specific application driver is for use in stochastic variants of core power systems operations optimization problems, e.g., unit commitment and economic dispatch. These problems require as input a range of possible future realizations of renewables production. However, the utility of such probabilistic scenarios extends to other contexts, e.g., operator and trader situational awareness. Finally, we compare the performance of our approach to a recently proposed method based on quantile regression, and demonstrate that our method performs comparably to this approach in terms of two widely used methods for assessing the quality of probabilistic scenarios: the Energy score and the Variogram score.« less

Underway Recovery Test 6 (URT-6) - Day 1 Activities

NASA Image and Video Library

2018-01-17

The USS Anchorage leaves Naval Base San Diego for a multi-day Underway Recovery Test with NASA. The NASA Recovery Team from Kennedy Space Center and the U.S. Navy are working together to hone recovery procedures and hardware ahead of Orion’s next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

75 FR 4316 - Integration of Variable Energy Resources

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-27

... their supply in the real-time energy markets (i.e., act as a price taker). Because day-ahead schedules... conditions and that day-ahead and real-time energy prices will converge under the scenario of increasing... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission 18 CFR Chapter I [Docket No. RM10-11-000...

76 FR 41790 - Increasing Market and Planning Efficiency Through Improved Software; Notice Establishing Date for...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-15

... Market and Planning Efficiency Through Improved Software; Notice Establishing Date for Comments From June... real-time and day- ahead market efficiency through improved software.\\1\\ \\1\\ Notice of technical conference: increasing real-time and day-ahead market efficiency through improved software, 76 Fed. Reg. 28...

Short-Term Planning of Hybrid Power System

NASA Astrophysics Data System (ADS)

Knežević, Goran; Baus, Zoran; Nikolovski, Srete

2016-07-01

In this paper short-term planning algorithm for hybrid power system consist of different types of cascade hydropower plants (run-of-the river, pumped storage, conventional), thermal power plants (coal-fired power plants, combined cycle gas-fired power plants) and wind farms is presented. The optimization process provides a joint bid of the hybrid system, and thus making the operation schedule of hydro and thermal power plants, the operation condition of pumped-storage hydropower plants with the aim of maximizing profits on day ahead market, according to expected hourly electricity prices, the expected local water inflow in certain hydropower plants, and the expected production of electrical energy from the wind farm, taking into account previously contracted bilateral agreement for electricity generation. Optimization process is formulated as hourly-discretized mixed integer linear optimization problem. Optimization model is applied on the case study in order to show general features of the developed model.

Short-Term Global Horizontal Irradiance Forecasting Based on Sky Imaging and Pattern Recognition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodge, Brian S; Feng, Cong; Cui, Mingjian

Accurate short-term forecasting is crucial for solar integration in the power grid. In this paper, a classification forecasting framework based on pattern recognition is developed for 1-hour-ahead global horizontal irradiance (GHI) forecasting. Three sets of models in the forecasting framework are trained by the data partitioned from the preprocessing analysis. The first two sets of models forecast GHI for the first four daylight hours of each day. Then the GHI values in the remaining hours are forecasted by an optimal machine learning model determined based on a weather pattern classification model in the third model set. The weather pattern ismore » determined by a support vector machine (SVM) classifier. The developed framework is validated by the GHI and sky imaging data from the National Renewable Energy Laboratory (NREL). Results show that the developed short-term forecasting framework outperforms the persistence benchmark by 16% in terms of the normalized mean absolute error and 25% in terms of the normalized root mean square error.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baone, Chaitanya; Acharya, Naresh; Wiegman, Herman

As microgrid installations are steadily growing in the United States and around the world, widespread adoption of commercial microgrids would rely upon the economic benefit to the owners and operators. With the introduction of new market mechanisms and growing penetration of non-traditional generation assets, there is an increasing need and interest in allowing distributed assets to participate in traditional grid services such as frequency regulation. This paper considers the problem of determining the optimal balance of energy and ancillary services for individual microgrid generation assets to participate in such markets. An optimization framework that maximizes the predicted performance of themore » microgrid over a day-ahead time horizon while accounting for individual asset constraints is proposed. Simulation results on a realistic test system with practical considerations are presented.« less

Availability Based Tariff and its impact On different Industry Players-A Review

NASA Astrophysics Data System (ADS)

Holmukhe, R. M.; Pawar, Yogini; Desai, R. S.; Hasarmani, T. S.

2010-10-01

ABT is a performance-based tariff for the supply of electricity by generators owned and controlled by the central government. It is also a new system of scheduling and dispatch, which requires both generators and beneficiaries to commit to day-ahead schedules. It is a system of rewards and penalties seeking to enforce day ahead pre-committed schedules, though variations are permitted if notified One and one half hours in advance. The order emphasizes prompt payment of dues. ABT (Availability Based Tariff) along with the Electricity Act of 2003 is perhaps the most significant and definitive step taken in the Indian power sector so far to bring more efficiency and focus to this vital infrastructure. The ABT mechanism is based on financial principles. ABT scheme is for unscheduled interchange of power. The paper reviews ABT issues, its components, clauses, mechanism, benefits and the impact of grid on different players like generation utilities, grid operator, consumers involved in power generation, transmission and distribution. While the proposed tariff structure has wide implications for each player, this deals exclusively with the technology challenges/opportunities thrown up by ABT.

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.

2013-07-25

This paper presents four algorithms to generate random forecast error time series. The performance of four algorithms is compared. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets used in power grid operation to study the net load balancing need in variable generation integration studies. The four algorithms are truncated-normal distribution models, state-space based Markov models, seasonal autoregressive moving average (ARMA) models, and a stochastic-optimization based approach. The comparison is made using historical DA load forecast and actual load valuesmore » to generate new sets of DA forecasts with similar stoical forecast error characteristics (i.e., mean, standard deviation, autocorrelation, and cross-correlation). The results show that all methods generate satisfactory results. One method may preserve one or two required statistical characteristics better the other methods, but may not preserve other statistical characteristics as well compared with the other methods. Because the wind and load forecast error generators are used in wind integration studies to produce wind and load forecasts time series for stochastic planning processes, it is sometimes critical to use multiple methods to generate the error time series to obtain a statistically robust result. Therefore, this paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.« less

Evaluating the Impacts of Real-Time Pricing on the Cost and Value of Wind Generation

DOE PAGES

Siohansi, Ramteen

2010-05-01

One of the costs associated with integrating wind generation into a power system is the cost of redispatching the system in real-time due to day-ahead wind resource forecast errors. One possible way of reducing these redispatch costs is to introduce demand response in the form of real-time pricing (RTP), which could allow electricity demand to respond to actual real-time wind resource availability using price signals. A day-ahead unit commitment model with day-ahead wind forecasts and a real-time dispatch model with actual wind resource availability is used to estimate system operations in a high wind penetration scenario. System operations are comparedmore » to a perfect foresight benchmark, in which actual wind resource availability is known day-ahead. The results show that wind integration costs with fixed demands can be high, both due to real-time redispatch costs and lost load. It is demonstrated that introducing RTP can reduce redispatch costs and eliminate loss of load events. Finally, social surplus with wind generation and RTP is compared to a system with neither and the results demonstrate that introducing wind and RTP into a market can result in superadditive surplus gains.« less

A stochastic electricity market clearing formulation with consistent pricing properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zavala, Victor M.; Kim, Kibaek; Anitescu, Mihai

We argue that deterministic market clearing formulations introduce arbitrary distortions between day-ahead and expected real-time prices that bias economic incentives. We extend and analyze a previously proposed stochastic clearing formulation in which the social surplus function induces penalties between day-ahead and real-time quantities. We prove that the formulation yields price bounded price distortions, and we show that adding a similar penalty term to transmission flows and phase angles ensures boundedness throughout the network. We prove that when the price distortions are zero, day-ahead quantities equal a quantile of their real-time counterparts. The undesired effects of price distortions suggest that stochasticmore » settings provide significant benefits over deterministic ones that go beyond social surplus improvements. Finally, we propose additional metrics to evaluate these benefits.« less

A stochastic electricity market clearing formulation with consistent pricing properties

DOE PAGES

Zavala, Victor M.; Kim, Kibaek; Anitescu, Mihai; ...

2017-03-16

We argue that deterministic market clearing formulations introduce arbitrary distortions between day-ahead and expected real-time prices that bias economic incentives. We extend and analyze a previously proposed stochastic clearing formulation in which the social surplus function induces penalties between day-ahead and real-time quantities. We prove that the formulation yields price bounded price distortions, and we show that adding a similar penalty term to transmission flows and phase angles ensures boundedness throughout the network. We prove that when the price distortions are zero, day-ahead quantities equal a quantile of their real-time counterparts. The undesired effects of price distortions suggest that stochasticmore » settings provide significant benefits over deterministic ones that go beyond social surplus improvements. Finally, we propose additional metrics to evaluate these benefits.« less

Forecasting peaks of seasonal influenza epidemics.

PubMed

Nsoesie, Elaine; Mararthe, Madhav; Brownstein, John

2013-06-21

We present a framework for near real-time forecast of influenza epidemics using a simulation optimization approach. The method combines an individual-based model and a simple root finding optimization method for parameter estimation and forecasting. In this study, retrospective forecasts were generated for seasonal influenza epidemics using web-based estimates of influenza activity from Google Flu Trends for 2004-2005, 2007-2008 and 2012-2013 flu seasons. In some cases, the peak could be forecasted 5-6 weeks ahead. This study adds to existing resources for influenza forecasting and the proposed method can be used in conjunction with other approaches in an ensemble framework.

75 FR 42380 - Orders Finding That the SP-15 Financial Day-Ahead LMP Peak Contract and SP-15 Financial Day-Ahead...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-21

...Exchange, Inc. (``ICE''), an exempt commercial market (``ECM'') under sections 2(h)(3)-(5) of the Commodity... with respect to ECMs by creating, in section 2(h)(7) of the CEA, a new regulatory category--ECMs on which significant price discovery contracts (``SPDCs'') are traded--and treating ECMs in that category...

PSO-MISMO modeling strategy for multistep-ahead time series prediction.

PubMed

Bao, Yukun; Xiong, Tao; Hu, Zhongyi

2014-05-01

Multistep-ahead time series prediction is one of the most challenging research topics in the field of time series modeling and prediction, and is continually under research. Recently, the multiple-input several multiple-outputs (MISMO) modeling strategy has been proposed as a promising alternative for multistep-ahead time series prediction, exhibiting advantages compared with the two currently dominating strategies, the iterated and the direct strategies. Built on the established MISMO strategy, this paper proposes a particle swarm optimization (PSO)-based MISMO modeling strategy, which is capable of determining the number of sub-models in a self-adaptive mode, with varying prediction horizons. Rather than deriving crisp divides with equal-size s prediction horizons from the established MISMO, the proposed PSO-MISMO strategy, implemented with neural networks, employs a heuristic to create flexible divides with varying sizes of prediction horizons and to generate corresponding sub-models, providing considerable flexibility in model construction, which has been validated with simulated and real datasets.

An application of ensemble/multi model approach for wind power production forecast.

NASA Astrophysics Data System (ADS)

Alessandrini, S.; Decimi, G.; Hagedorn, R.; Sperati, S.

2010-09-01

The wind power forecast of the 3 days ahead period are becoming always more useful and important in reducing the problem of grid integration and energy price trading due to the increasing wind power penetration. Therefore it's clear that the accuracy of this forecast is one of the most important requirements for a successful application. The wind power forecast is based on a mesoscale meteorological models that provides the 3 days ahead wind data. A Model Output Statistic correction is then performed to reduce systematic error caused, for instance, by a wrong representation of surface roughness or topography in the meteorological models. The corrected wind data are then used as input in the wind farm power curve to obtain the power forecast. These computations require historical time series of wind measured data (by an anemometer located in the wind farm or on the nacelle) and power data in order to be able to perform the statistical analysis on the past. For this purpose a Neural Network (NN) is trained on the past data and then applied in the forecast task. Considering that the anemometer measurements are not always available in a wind farm a different approach has also been adopted. A training of the NN to link directly the forecasted meteorological data and the power data has also been performed. The normalized RMSE forecast error seems to be lower in most cases by following the second approach. We have examined two wind farms, one located in Denmark on flat terrain and one located in a mountain area in the south of Italy (Sicily). In both cases we compare the performances of a prediction based on meteorological data coming from a single model with those obtained by using two or more models (RAMS, ECMWF deterministic, LAMI, HIRLAM). It is shown that the multi models approach reduces the day-ahead normalized RMSE forecast error of at least 1% compared to the singles models approach. Moreover the use of a deterministic global model, (e.g. ECMWF deterministic model) seems to reach similar level of accuracy of those of the mesocale models (LAMI and RAMS). Finally we have focused on the possibility of using the ensemble model (ECMWF) to estimate the hourly, three days ahead, power forecast accuracy. Contingency diagram between RMSE of the deterministic power forecast and the ensemble members spread of wind forecast have been produced. From this first analysis it seems that ensemble spread could be used as an indicator of the forecast's accuracy at least for the first day ahead period. In fact low spreads often correspond to low forecast error. For longer forecast horizon the correlation between RMSE and ensemble spread decrease becoming too low to be used for this purpose.

Multi-time Scale Joint Scheduling Method Considering the Grid of Renewable Energy

NASA Astrophysics Data System (ADS)

Zhijun, E.; Wang, Weichen; Cao, Jin; Wang, Xin; Kong, Xiangyu; Quan, Shuping

2018-01-01

Renewable new energy power generation prediction error like wind and light, brings difficulties to dispatch the power system. In this paper, a multi-time scale robust scheduling method is set to solve this problem. It reduces the impact of clean energy prediction bias to the power grid by using multi-time scale (day-ahead, intraday, real time) and coordinating the dispatching power output of various power supplies such as hydropower, thermal power, wind power, gas power and. The method adopts the robust scheduling method to ensure the robustness of the scheduling scheme. By calculating the cost of the abandon wind and the load, it transforms the robustness into the risk cost and optimizes the optimal uncertainty set for the smallest integrative costs. The validity of the method is verified by simulation.

Comparison of Wind Power and Load Forecasting Error Distributions: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodge, B. M.; Florita, A.; Orwig, K.

2012-07-01

The introduction of large amounts of variable and uncertain power sources, such as wind power, into the electricity grid presents a number of challenges for system operations. One issue involves the uncertainty associated with scheduling power that wind will supply in future timeframes. However, this is not an entirely new challenge; load is also variable and uncertain, and is strongly influenced by weather patterns. In this work we make a comparison between the day-ahead forecasting errors encountered in wind power forecasting and load forecasting. The study examines the distribution of errors from operational forecasting systems in two different Independent Systemmore » Operator (ISO) regions for both wind power and load forecasts at the day-ahead timeframe. The day-ahead timescale is critical in power system operations because it serves the unit commitment function for slow-starting conventional generators.« less

Support vector machine for day ahead electricity price forecasting

NASA Astrophysics Data System (ADS)

Razak, Intan Azmira binti Wan Abdul; Abidin, Izham bin Zainal; Siah, Yap Keem; Rahman, Titik Khawa binti Abdul; Lada, M. Y.; Ramani, Anis Niza binti; Nasir, M. N. M.; Ahmad, Arfah binti

2015-05-01

Electricity price forecasting has become an important part of power system operation and planning. In a pool- based electric energy market, producers submit selling bids consisting in energy blocks and their corresponding minimum selling prices to the market operator. Meanwhile, consumers submit buying bids consisting in energy blocks and their corresponding maximum buying prices to the market operator. Hence, both producers and consumers use day ahead price forecasts to derive their respective bidding strategies to the electricity market yet reduce the cost of electricity. However, forecasting electricity prices is a complex task because price series is a non-stationary and highly volatile series. Many factors cause for price spikes such as volatility in load and fuel price as well as power import to and export from outside the market through long term contract. This paper introduces an approach of machine learning algorithm for day ahead electricity price forecasting with Least Square Support Vector Machine (LS-SVM). Previous day data of Hourly Ontario Electricity Price (HOEP), generation's price and demand from Ontario power market are used as the inputs for training data. The simulation is held using LSSVMlab in Matlab with the training and testing data of 2004. SVM that widely used for classification and regression has great generalization ability with structured risk minimization principle rather than empirical risk minimization. Moreover, same parameter settings in trained SVM give same results that absolutely reduce simulation process compared to other techniques such as neural network and time series. The mean absolute percentage error (MAPE) for the proposed model shows that SVM performs well compared to neural network.

Impacts of calibration strategies and ensemble methods on ensemble flood forecasting over Lanjiang basin, Southeast China

NASA Astrophysics Data System (ADS)

Liu, Li; Xu, Yue-Ping

2017-04-01

Ensemble flood forecasting driven by numerical weather prediction products is becoming more commonly used in operational flood forecasting applications.In this study, a hydrological ensemble flood forecasting system based on Variable Infiltration Capacity (VIC) model and quantitative precipitation forecasts from TIGGE dataset is constructed for Lanjiang Basin, Southeast China. The impacts of calibration strategies and ensemble methods on the performance of the system are then evaluated.The hydrological model is optimized by parallel programmed ɛ-NSGAII multi-objective algorithm and two respectively parameterized models are determined to simulate daily flows and peak flows coupled with a modular approach.The results indicatethat the ɛ-NSGAII algorithm permits more efficient optimization and rational determination on parameter setting.It is demonstrated that the multimodel ensemble streamflow mean have better skills than the best singlemodel ensemble mean (ECMWF) and the multimodel ensembles weighted on members and skill scores outperform other multimodel ensembles. For typical flood event, it is proved that the flood can be predicted 3-4 days in advance, but the flows in rising limb can be captured with only 1-2 days ahead due to the flash feature. With respect to peak flows selected by Peaks Over Threshold approach, the ensemble means from either singlemodel or multimodels are generally underestimated as the extreme values are smoothed out by ensemble process.

Managing risks of market price uncertainty for a microgrid operation

NASA Astrophysics Data System (ADS)

Raghavan, Sriram

After deregulation of electricity in the United States, the day-ahead and real-time markets allow load serving entities and generation companies to bid and purchase/sell energy under the supervision of the independent system operator (ISO). The electricity market prices are inherently uncertain, and can be highly volatile. The main objective of this thesis is to hedge against the risk from the uncertainty of the market prices when purchasing/selling energy from/to the market. The energy manager can also schedule distributed generators (DGs) and storage of the microgrid to meet the demand, in addition to energy transactions from the market. The risk measure used in this work is the variance of the uncertain market purchase/sale cost/revenue, assuming the price following a Gaussian distribution. Using Markowitz optimization, the risk is minimized to find the optimal mix of purchase from the markets. The problem is formulated as a mixed integer quadratic program. The microgrid at Illinois Institute of Technology (IIT) in Chicago, IL was used as a case study. The result of this work reveals the tradeoff faced by the microgrid energy manager between minimizing the risk and minimizing the mean of the total operating cost (TOC) of the microgrid. With this information, the microgrid energy manager can make decisions in the day-ahead and real-time markets according to their risk aversion preference. The assumption of market prices following Gaussian distribution is also verified to be reasonable for the purpose of hedging against their risks. This is done by comparing the result of the proposed formulation with that obtained from the sample market prices randomly generated using the distribution of actual historic market price data.

Residential Consumption Scheduling Based on Dynamic User Profiling

NASA Astrophysics Data System (ADS)

Mangiatordi, Federica; Pallotti, Emiliano; Del Vecchio, Paolo; Capodiferro, Licia

Deployment of household appliances and of electric vehicles raises the electricity demand in the residential areas and the impact of the building's electrical power. The variations of electricity consumption across the day, may affect both the design of the electrical generation facilities and the electricity bill, mainly when a dynamic pricing is applied. This paper focuses on an energy management system able to control the day-ahead electricity demand in a residential area, taking into account both the variability of the energy production costs and the profiling of the users. The user's behavior is dynamically profiled on the basis of the tasks performed during the previous days and of the tasks foreseen for the current day. Depending on the size and on the flexibility in time of the user tasks, home inhabitants are grouped in, one over N, energy profiles, using a k-means algorithm. For a fixed energy generation cost, each energy profile is associated to a different hourly energy cost. The goal is to identify any bad user profile and to make it pay a highest bill. A bad profile example is when a user applies a lot of consumption tasks and low flexibility in task reallocation time. The proposed energy management system automatically schedules the tasks, solving a multi-objective optimization problem based on an MPSO strategy. The goals, when identifying bad users profiles, are to reduce the peak to average ratio in energy demand, and to minimize the energy costs, promoting virtuous behaviors.

Neural network based short-term load forecasting using weather compensation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chow, T.W.S.; Leung, C.T.

This paper presents a novel technique for electric load forecasting based on neural weather compensation. The proposed method is a nonlinear generalization of Box and Jenkins approach for nonstationary time-series prediction. A weather compensation neural network is implemented for one-day ahead electric load forecasting. The weather compensation neural network can accurately predict the change of actual electric load consumption from the previous day. The results, based on Hong Kong Island historical load demand, indicate that this methodology is capable of providing a more accurate load forecast with a 0.9% reduction in forecast error.

Optimal Electric Vehicle Scheduling: A Co-Optimized System and Customer Perspective

NASA Astrophysics Data System (ADS)

Maigha

Electric vehicles provide a two pronged solution to the problems faced by the electricity and transportation sectors. They provide a green, highly efficient alternative to the internal combustion engine vehicles, thus reducing our dependence on fossil fuels. Secondly, they bear the potential of supporting the grid as energy storage devices while incentivising the customers through their participation in energy markets. Despite these advantages, widespread adoption of electric vehicles faces socio-technical and economic bottleneck. This dissertation seeks to provide solutions that balance system and customer objectives under present technological capabilities. The research uses electric vehicles as controllable loads and resources. The idea is to provide the customers with required tools to make an informed decision while considering the system conditions. First, a genetic algorithm based optimal charging strategy to reduce the impact of aggregated electric vehicle load has been presented. A Monte Carlo based solution strategy studies change in the solution under different objective functions. This day-ahead scheduling is then extended to real-time coordination using a moving-horizon approach. Further, battery degradation costs have been explored with vehicle-to-grid implementations, thus accounting for customer net-revenue and vehicle utility for grid support. A Pareto front, thus obtained, provides the nexus between customer and system desired operating points. Finally, we propose a transactive business model for a smart airport parking facility. This model identifies various revenue streams and satisfaction indices that benefit the parking lot owner and the customer, thus adding value to the electric vehicle.

Wet tropospheric delays forecast based on Vienna Mapping Function time series analysis

NASA Astrophysics Data System (ADS)

Rzepecka, Zofia; Kalita, Jakub

2016-04-01

It is well known that the dry part of the zenith tropospheric delay (ZTD) is much easier to model than the wet part (ZTW). The aim of the research is applying stochastic modeling and prediction of ZTW using time series analysis tools. Application of time series analysis enables closer understanding of ZTW behavior as well as short-term prediction of future ZTW values. The ZTW data used for the studies were obtained from the GGOS service hold by Vienna technical University. The resolution of the data is six hours. ZTW for the years 2010 -2013 were adopted for the study. The International GNSS Service (IGS) permanent stations LAMA and GOPE, located in mid-latitudes, were admitted for the investigations. Initially the seasonal part was separated and modeled using periodic signals and frequency analysis. The prominent annual and semi-annual signals were removed using sines and consines functions. The autocorrelation of the resulting signal is significant for several days (20-30 samples). The residuals of this fitting were further analyzed and modeled with ARIMA processes. For both the stations optimal ARMA processes based on several criterions were obtained. On this basis predicted ZTW values were computed for one day ahead, leaving the white process residuals. Accuracy of the prediction can be estimated at about 3 cm.

Integrated Traffic Flow Management Decision Making

NASA Technical Reports Server (NTRS)

Grabbe, Shon R.; Sridhar, Banavar; Mukherjee, Avijit

2009-01-01

A generalized approach is proposed to support integrated traffic flow management decision making studies at both the U.S. national and regional levels. It can consider tradeoffs between alternative optimization and heuristic based models, strategic versus tactical flight controls, and system versus fleet preferences. Preliminary testing was accomplished by implementing thirteen unique traffic flow management models, which included all of the key components of the system and conducting 85, six-hour fast-time simulation experiments. These experiments considered variations in the strategic planning look-ahead times, the replanning intervals, and the types of traffic flow management control strategies. Initial testing indicates that longer strategic planning look-ahead times and re-planning intervals result in steadily decreasing levels of sector congestion for a fixed delay level. This applies when accurate estimates of the air traffic demand, airport capacities and airspace capacities are available. In general, the distribution of the delays amongst the users was found to be most equitable when scheduling flights using a heuristic scheduling algorithm, such as ration-by-distance. On the other hand, equity was the worst when using scheduling algorithms that took into account the number of seats aboard each flight. Though the scheduling algorithms were effective at alleviating sector congestion, the tactical rerouting algorithm was the primary control for avoiding en route weather hazards. Finally, the modeled levels of sector congestion, the number of weather incursions, and the total system delays, were found to be in fair agreement with the values that were operationally observed on both good and bad weather days.

Short-Term Load Forecasting Error Distributions and Implications for Renewable Integration Studies: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodge, B. M.; Lew, D.; Milligan, M.

2013-01-01

Load forecasting in the day-ahead timescale is a critical aspect of power system operations that is used in the unit commitment process. It is also an important factor in renewable energy integration studies, where the combination of load and wind or solar forecasting techniques create the net load uncertainty that must be managed by the economic dispatch process or with suitable reserves. An understanding of that load forecasting errors that may be expected in this process can lead to better decisions about the amount of reserves necessary to compensate errors. In this work, we performed a statistical analysis of themore » day-ahead (and two-day-ahead) load forecasting errors observed in two independent system operators for a one-year period. Comparisons were made with the normal distribution commonly assumed in power system operation simulations used for renewable power integration studies. Further analysis identified time periods when the load is more likely to be under- or overforecast.« less

Data on Support Vector Machines (SVM) model to forecast photovoltaic power.

PubMed

Malvoni, M; De Giorgi, M G; Congedo, P M

2016-12-01

The data concern the photovoltaic (PV) power, forecasted by a hybrid model that considers weather variations and applies a technique to reduce the input data size, as presented in the paper entitled "Photovoltaic forecast based on hybrid pca-lssvm using dimensionality reducted data" (M. Malvoni, M.G. De Giorgi, P.M. Congedo, 2015) [1]. The quadratic Renyi entropy criteria together with the principal component analysis (PCA) are applied to the Least Squares Support Vector Machines (LS-SVM) to predict the PV power in the day-ahead time frame. The data here shared represent the proposed approach results. Hourly PV power predictions for 1,3,6,12, 24 ahead hours and for different data reduction sizes are provided in Supplementary material.

Options for pricing ancillary services in a deregulated power system

NASA Astrophysics Data System (ADS)

Yamin, Hatim Yahya

2001-07-01

GENCOs in restructured systems are compensated for selling energy in the market. In a restructured market, a mechanism is required to entice participants in the market to provide ancillary services and to ensure adequate compensation that would guarantee its economic viability. The ISO controls the dispatch of generation, manages the reliability of the transmission grid, provides open access to the transmission, buys and provides ancillary services as required, coordinates day-ahead, hour-ahead schedules and performs real time balancing of load and generation, settles real time imbalances and ancillary services sales and purchases. The ISO, also, administers congestion management protocols for the transmission grid. Since the ISO does not own any generating units it must ensure that there is enough reserves for maintaining reliability according to FERC regulations, and sufficient unloaded generating capacity for balancing services in a real-time market. The ISO could meet these requirements by creating a competitive market for ancillary services, which are metered and remain unbundled to provide an accurate compensation for each supplier and cost to each consumer, In this study, we give an overview for restructuring and ancillary services in a restructured power marketplace. Also, we discuss the effect of GENCOs' actions in the competitive energy and ancillary service markets. In addition, we propose an auction market design for hedging ancillary service costs in California market. Furthermore, we show how to include the n-1 and voltage contingencies in security constrained unit commitment. Finally, we present two approaches for GENCOs' unit commitment in a restructured power market; one is based on game theory and the other is based on market price forecasting. In each of the two GENCOs' unit commitment approaches, we discuss the GENCOs' optimal bidding strategies in energy and ancillary service markets to maximize the GENCOs' profit.

Deadlock-free genetic scheduling algorithm for automated manufacturing systems based on deadlock control policy.

PubMed

Xing, KeYi; Han, LiBin; Zhou, MengChu; Wang, Feng

2012-06-01

Deadlock-free control and scheduling are vital for optimizing the performance of automated manufacturing systems (AMSs) with shared resources and route flexibility. Based on the Petri net models of AMSs, this paper embeds the optimal deadlock avoidance policy into the genetic algorithm and develops a novel deadlock-free genetic scheduling algorithm for AMSs. A possible solution of the scheduling problem is coded as a chromosome representation that is a permutation with repetition of parts. By using the one-step look-ahead method in the optimal deadlock control policy, the feasibility of a chromosome is checked, and infeasible chromosomes are amended into feasible ones, which can be easily decoded into a feasible deadlock-free schedule. The chromosome representation and polynomial complexity of checking and amending procedures together support the cooperative aspect of genetic search for scheduling problems strongly.

A look-ahead variant of the Lanczos algorithm and its application to the quasi-minimal residual method for non-Hermitian linear systems. Ph.D. Thesis - Massachusetts Inst. of Technology, Aug. 1991

NASA Technical Reports Server (NTRS)

Nachtigal, Noel M.

1991-01-01

The Lanczos algorithm can be used both for eigenvalue problems and to solve linear systems. However, when applied to non-Hermitian matrices, the classical Lanczos algorithm is susceptible to breakdowns and potential instabilities. In addition, the biconjugate gradient (BCG) algorithm, which is the natural generalization of the conjugate gradient algorithm to non-Hermitian linear systems, has a second source of breakdowns, independent of the Lanczos breakdowns. Here, we present two new results. We propose an implementation of a look-ahead variant of the Lanczos algorithm which overcomes the breakdowns by skipping over those steps where a breakdown or a near-breakdown would occur. The new algorithm can handle look-ahead steps of any length and requires the same number of matrix-vector products and inner products per step as the classical Lanczos algorithm without look-ahead. Based on the proposed look-ahead Lanczos algorithm, we then present a novel BCG-like approach, the quasi-minimal residual (QMR) method, which avoids the second source of breakdowns in the BCG algorithm. We present details of the new method and discuss some of its properties. In particular, we discuss the relationship between QMR and BCG, showing how one can recover the BCG iterates, when they exist, from the QMR iterates. We also present convergence results for QMR, showing the connection between QMR and the generalized minimal residual (GMRES) algorithm, the optimal method in this class of methods. Finally, we give some numerical examples, both for eigenvalue computations and for non-Hermitian linear systems.

Assessment of Energy Storage Alternatives in the Puget Sound Energy System Volume 2: Energy Storage Evaluation Tool

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Di; Jin, Chunlian; Balducci, Patrick J.

2013-12-01

This volume presents the battery storage evaluation tool developed at Pacific Northwest National Laboratory (PNNL), which is used to evaluate benefits of battery storage for multiple grid applications, including energy arbitrage, balancing service, capacity value, distribution system equipment deferral, and outage mitigation. This tool is based on the optimal control strategies to capture multiple services from a single energy storage device. In this control strategy, at each hour, a look-ahead optimization is first formulated and solved to determine battery base operating point. The minute by minute simulation is then performed to simulate the actual battery operation. This volume provide backgroundmore » and manual for this evaluation tool.« less

Minimizing forced outage risk in generator bidding

NASA Astrophysics Data System (ADS)

Das, Dibyendu

Competition in power markets has exposed the participating companies to physical and financial uncertainties. Generator companies bid to supply power in a day-ahead market. Once their bids are accepted by the ISO they are bound to supply power. A random outage after acceptance of bids forces a generator to buy power from the expensive real-time hourly spot market and sell to the ISO at the set day-ahead market clearing price, incurring losses. A risk management technique is developed to assess this financial risk associated with forced outages of generators and then minimize it. This work presents a risk assessment module which measures the financial risk of generators bidding in an open market for different bidding scenarios. The day-ahead power market auction is modeled using a Unit Commitment algorithm and a combination of Normal and Cauchy distributions generate the real time hourly spot market. Risk profiles are derived and VaRs are calculated at 98 percent confidence level as a measure of financial risk. Risk Profiles and VaRs help the generators to analyze the forced outage risk and different factors affecting it. The VaRs and the estimated total earning for different bidding scenarios are used to develop a risk minimization module. This module will develop a bidding strategy of the generator company such that its estimated total earning is maximized keeping the VaR below a tolerable limit. This general framework of a risk management technique for the generating companies bidding in competitive day-ahead market can also help them in decisions related to building new generators.

DESIGN OF A GAMMA-RAY SOURCE BASED ON INVERSE COMPTON SCATTERING AT THE FAST SUPERCONDUCTING LINAC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mihalcea, D.; Jacobson, B.; Murokh, A.

2016-10-10

A watt-level average-power gamma-ray source is currently under development at the Fermilab Accelerator Science & Technology (FAST) facility. The source is based on the Inverse Compton Scattering of a high-brightness 300-MeV beam against a high-power laser beam circulating in an optical cavity. The back scattered gamma rays are expected to have photon energies up to 1.5 MeV. This paper discusses the optimization of the source, its performances, and the main challenges ahead.

Big Data and Dementia: Charting the Route Ahead for Research, Ethics, and Policy

PubMed Central

Ienca, Marcello; Vayena, Effy; Blasimme, Alessandro

2018-01-01

Emerging trends in pervasive computing and medical informatics are creating the possibility for large-scale collection, sharing, aggregation and analysis of unprecedented volumes of data, a phenomenon commonly known as big data. In this contribution, we review the existing scientific literature on big data approaches to dementia, as well as commercially available mobile-based applications in this domain. Our analysis suggests that big data approaches to dementia research and care hold promise for improving current preventive and predictive models, casting light on the etiology of the disease, enabling earlier diagnosis, optimizing resource allocation, and delivering more tailored treatments to patients with specific disease trajectories. Such promissory outlook, however, has not materialized yet, and raises a number of technical, scientific, ethical, and regulatory challenges. This paper provides an assessment of these challenges and charts the route ahead for research, ethics, and policy. PMID:29468161

Big Data and Dementia: Charting the Route Ahead for Research, Ethics, and Policy.

PubMed

Ienca, Marcello; Vayena, Effy; Blasimme, Alessandro

2018-01-01

Emerging trends in pervasive computing and medical informatics are creating the possibility for large-scale collection, sharing, aggregation and analysis of unprecedented volumes of data, a phenomenon commonly known as big data. In this contribution, we review the existing scientific literature on big data approaches to dementia, as well as commercially available mobile-based applications in this domain. Our analysis suggests that big data approaches to dementia research and care hold promise for improving current preventive and predictive models, casting light on the etiology of the disease, enabling earlier diagnosis, optimizing resource allocation, and delivering more tailored treatments to patients with specific disease trajectories. Such promissory outlook, however, has not materialized yet, and raises a number of technical, scientific, ethical, and regulatory challenges. This paper provides an assessment of these challenges and charts the route ahead for research, ethics, and policy.

A Comparison of the Performance of Advanced Statistical Techniques for the Refinement of Day-ahead and Longer NWP-based Wind Power Forecasts

NASA Astrophysics Data System (ADS)

Zack, J. W.

2015-12-01

Predictions from Numerical Weather Prediction (NWP) models are the foundation for wind power forecasts for day-ahead and longer forecast horizons. The NWP models directly produce three-dimensional wind forecasts on their respective computational grids. These can be interpolated to the location and time of interest. However, these direct predictions typically contain significant systematic errors ("biases"). This is due to a variety of factors including the limited space-time resolution of the NWP models and shortcomings in the model's representation of physical processes. It has become common practice to attempt to improve the raw NWP forecasts by statistically adjusting them through a procedure that is widely known as Model Output Statistics (MOS). The challenge is to identify complex patterns of systematic errors and then use this knowledge to adjust the NWP predictions. The MOS-based improvements are the basis for much of the value added by commercial wind power forecast providers. There are an enormous number of statistical approaches that can be used to generate the MOS adjustments to the raw NWP forecasts. In order to obtain insight into the potential value of some of the newer and more sophisticated statistical techniques often referred to as "machine learning methods" a MOS-method comparison experiment has been performed for wind power generation facilities in 6 wind resource areas of California. The underlying NWP models that provided the raw forecasts were the two primary operational models of the US National Weather Service: the GFS and NAM models. The focus was on 1- and 2-day ahead forecasts of the hourly wind-based generation. The statistical methods evaluated included: (1) screening multiple linear regression, which served as a baseline method, (2) artificial neural networks, (3) a decision-tree approach called random forests, (4) gradient boosted regression based upon an decision-tree algorithm, (5) support vector regression and (6) analog ensemble, which is a case-matching scheme. The presentation will provide (1) an overview of each method and the experimental design, (2) performance comparisons based on standard metrics such as bias, MAE and RMSE, (3) a summary of the performance characteristics of each approach and (4) a preview of further experiments to be conducted.

Advancing solar energy forecasting through the underlying physics

NASA Astrophysics Data System (ADS)

Yang, H.; Ghonima, M. S.; Zhong, X.; Ozge, B.; Kurtz, B.; Wu, E.; Mejia, F. A.; Zamora, M.; Wang, G.; Clemesha, R.; Norris, J. R.; Heus, T.; Kleissl, J. P.

2017-12-01

As solar power comprises an increasingly large portion of the energy generation mix, the ability to accurately forecast solar photovoltaic generation becomes increasingly important. Due to the variability of solar power caused by cloud cover, knowledge of both the magnitude and timing of expected solar power production ahead of time facilitates the integration of solar power onto the electric grid by reducing electricity generation from traditional ancillary generators such as gas and oil power plants, as well as decreasing the ramping of all generators, reducing start and shutdown costs, and minimizing solar power curtailment, thereby providing annual economic value. The time scales involved in both the energy markets and solar variability range from intra-hour to several days ahead. This wide range of time horizons led to the development of a multitude of techniques, with each offering unique advantages in specific applications. For example, sky imagery provides site-specific forecasts on the minute-scale. Statistical techniques including machine learning algorithms are commonly used in the intra-day forecast horizon for regional applications, while numerical weather prediction models can provide mesoscale forecasts on both the intra-day and days-ahead time scale. This talk will provide an overview of the challenges unique to each technique and highlight the advances in their ongoing development which come alongside advances in the fundamental physics underneath.

Field Experience with and Potential for Multi-time Scale Grid Transactions from Responsive Commercial Buildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Piette, Mary Ann; Kiliccote, Sila; Ghatikar, Girish

2014-08-01

The need for and concepts behind demand response are evolving. As the electric system changes with more intermittent renewable electric supply systems, there is a need to allow buildings to provide more flexible demand. This paper presents results from field studies and pilots, as well as engineering estimates of the potential capabilities of fast load responsiveness in commercial buildings. We present a sector wide analysis of flexible loads in commercial buildings, which was conducted to improve resource planning and determine which loads to evaluate in future demonstrations. These systems provide important capabilities for future transactional systems. The field analysis ismore » based on results from California, plus projects in the northwest and east coast. End-uses considered include heating, ventilation, air conditioning and lighting. The timescales of control include day-ahead, as well as day-of, 10-minute ahead and even faster response. This technology can provide DR signals on different times scales to interact with responsive building loads. We describe the latency of the control systems in the building and the round trip communications with the wholesale grid operators.« less

Boiler tuning using SPO at Detroit Edison`s River Rouge plant for best economic performance while minimizing NO{sub x} emissions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haman, R.L.; Kerry, T.G.; Jarc, C.A.

1996-12-31

A technology provided by Ultramax Corporation and EPRI, based on sequential process optimization (SPO), is being used as a cost-effective tool to gain improvements prior to decisions for capital-intensive solutions. This empirical method of optimization, called the ULTRAMAX{reg_sign} Method, can determine the best boiler capabilities and help delay, or even avoid, expensive retrofits or repowering. SPO can serve as a least-cost way to attain the right degree of compliance with current and future phases of CAAA. Tuning ensures a staged strategy to stay ahead of emissions regulations, but not so far ahead as to cause regret for taking actions thatmore » ultimately are not mandated or warranted. One large utility investigating SPO as a tool to lower NO{sub x} emissions and to optimize boiler performance is Detroit Edison. The company has applied SPO to tune two coal-fired units at its River Rouge Power Plant to evaluate the technology for possible system-wide usage. Following the successful demonstration in reducing NO{sub x} from these units, SPO is being considered for use in other Detroit Edison fossil-fired plants. Tuning first will be used as a least-cost option to drive NO{sub x} to its lowest level with operating adjustment. In addition, optimization shows the true capability of the units and the margins available when the Phase 2 rules become effective in 2000. This paper includes a case study of the second tuning process and discusses the opportunities the technology affords.« less

77 FR 67533 - Veterans Day, 2012

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-13

... trials we face, there is no challenge we cannot overcome, and our best days are still ahead. This year... respect for and in recognition of the contributions our service members have made to the cause of peace...

Adaptive Portfolio Optimization for Multiple Electricity Markets Participation.

PubMed

Pinto, Tiago; Morais, Hugo; Sousa, Tiago M; Sousa, Tiago; Vale, Zita; Praca, Isabel; Faia, Ricardo; Pires, Eduardo Jose Solteiro

2016-08-01

The increase of distributed energy resources, mainly based on renewable sources, requires new solutions that are able to deal with this type of resources' particular characteristics (namely, the renewable energy sources intermittent nature). The smart grid concept is increasing its consensus as the most suitable solution to facilitate the small players' participation in electric power negotiations while improving energy efficiency. The opportunity for players' participation in multiple energy negotiation environments (smart grid negotiation in addition to the already implemented market types, such as day-ahead spot markets, balancing markets, intraday negotiations, bilateral contracts, forward and futures negotiations, and among other) requires players to take suitable decisions on whether to, and how to participate in each market type. This paper proposes a portfolio optimization methodology, which provides the best investment profile for a market player, considering different market opportunities. The amount of power that each supported player should negotiate in each available market type in order to maximize its profits, considers the prices that are expected to be achieved in each market, in different contexts. The price forecasts are performed using artificial neural networks, providing a specific database with the expected prices in the different market types, at each time. This database is then used as input by an evolutionary particle swarm optimization process, which originates the most advantage participation portfolio for the market player. The proposed approach is tested and validated with simulations performed in multiagent simulator of competitive electricity markets, using real electricity markets data from the Iberian operator-MIBEL.

Prediction of Regulation Reserve Requirements in California ISO Control Area based on BAAL Standard

DOE Office of Scientific and Technical Information (OSTI.GOV)

Etingov, Pavel V.; Makarov, Yuri V.; Samaan, Nader A.

This paper presents new methodologies developed at Pacific Northwest National Laboratory (PNNL) to estimate regulation capacity requirements in the California ISO control area. Two approaches have been developed: (1) an approach based on statistical analysis of actual historical area control error (ACE) and regulation data, and (2) an approach based on balancing authority ACE limit control performance standard. The approaches predict regulation reserve requirements on a day-ahead basis including upward and downward requirements, for each operating hour of a day. California ISO data has been used to test the performance of the proposed algorithms. Results show that software tool allowsmore » saving up to 30% on the regulation procurements cost .« less

An Energy Storage Assessment: Using Optimal Control Strategies to Capture Multiple Services

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Di; Jin, Chunlian; Balducci, Patrick J.

2015-09-01

This paper presents a methodology for evaluating benefits of battery storage for multiple grid applications, including energy arbitrage, balancing service, capacity value, distribution system equipment deferral, and outage mitigation. In the proposed method, at each hour, a look-ahead optimization is first formulated and solved to determine battery base operating point. The minute by minute simulation is then performed to simulate the actual battery operation. This methodology is used to assess energy storage alternatives in Puget Sound Energy System. Different battery storage candidates are simulated for a period of one year to assess different value streams and overall benefits, as partmore » of a financial feasibility evaluation of battery storage projects.« less

Economic Viability of Pumped-Storage Power Plants Equipped with Ternary Units and Considering Hydraulic Short-Circuit Operation

NASA Astrophysics Data System (ADS)

Chazarra, Manuel; Pérez-Díaz, Juan I.; García-González, Javier

2017-04-01

This paper analyses the economic viability of pumped-storage hydropower plants equipped with ternary units and considering hydraulic short-circuit operation. The analysed plant is assumed to participate in the day-ahead energy market and in the secondary regulation service of the Spanish power system. A deterministic day-ahead energy and reserve scheduling model is used to estimate the maximum theoretical income of the plant assuming perfect information of the next day prices and the residual demand curves of the secondary regulation reserve market. Results show that the pay-back periods with and without the hydraulic short-circuit operation are significantly lower than their expected lifetime and that the pay-back periods can be reduced with the inclusion of the hydraulic short-circuit operation.

Defense.gov Special Report: Memorial Day - 2015

Science.gov Websites

, Legacy Destiny Flynn visits the grave of her husband, Marine Corps Special Operations Staff Sgt. Liam Flynn, with their daughter, 1-year-old Leilani, ahead of Memorial Day. Destiny Flynn is in Arlington

Joint Seasonal ARMA Approach for Modeling of Load Forecast Errors in Planning Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hafen, Ryan P.; Samaan, Nader A.; Makarov, Yuri V.

2014-04-14

To make informed and robust decisions in the probabilistic power system operation and planning process, it is critical to conduct multiple simulations of the generated combinations of wind and load parameters and their forecast errors to handle the variability and uncertainty of these time series. In order for the simulation results to be trustworthy, the simulated series must preserve the salient statistical characteristics of the real series. In this paper, we analyze day-ahead load forecast error data from multiple balancing authority locations and characterize statistical properties such as mean, standard deviation, autocorrelation, correlation between series, time-of-day bias, and time-of-day autocorrelation.more » We then construct and validate a seasonal autoregressive moving average (ARMA) model to model these characteristics, and use the model to jointly simulate day-ahead load forecast error series for all BAs.« less

Are Wind Power and Hydropower Complements or Competitors? An Analysis of Ecosystem Service Constraints in the Roanoke Basin

NASA Astrophysics Data System (ADS)

Reed, P. M.; Fernandez, A. R.; Blumsack, S.

2011-12-01

Hydropower can provide inexpensive, flexible fill-in power to compensate for intermittent renewable generation. Policies for hydropower dams maintain multiple services beyond electric generation, including environmental protection, flood control and recreation. We model the decision of a hydroelectric generator to shift some of its power production capacity away from the day-ahead energy market into a "wind-following" service that smoothes the intermittent production of wind turbines. Offering such a service imposes both private and social opportunity costs. Since fluctuations in wind energy output are not perfectly correlated with day-ahead energy prices, a wind-following service will necessarily affect generator revenues. Seasonal wind patterns produce conflicts with the goal of managing rivers for "ecosystem services" - the maintenance or enhancement of downstream ecosystems. We illustrate our decision model using the Kerr Dam in PJM's territory in North Carolina. We simulate the operation of Kerr Dam over a three-year period that features hydrologic variability from normal water years to extreme drought conditions. We use an optimization framework to estimate reservation prices for Kerr Dam offering wind-following services in the PJM market. Wind-following may be profitable for Kerr Dam at low capacity levels during some time periods if ecosystems services are neglected and if side payments, or reserves-type payments, are provided. Wind-following with ecosystem services yields revenue losses that typically cannot be recovered with reserves market payments. Water release patterns are inconsistent with ecosystem-services goals when Kerr Dam dedicates significant capacity to wind-following, particularly in drought years.

Hydroeconomic Analysis of the Balance between Renewable Wind Energy, Hydropower, and Ecosystems Services in the Roanoke River Basin

NASA Astrophysics Data System (ADS)

Fernandez, A.; Blumsack, S.; Reed, P.

2012-04-01

Hydropower can provide inexpensive, flexible fill-in power to compensate for intermittent renewable generation. Policies for hydropower dams maintain multiple services beyond electric generation, including environmental protection, flood control and recreation. We model the decision of a hydroelectric generator to shift some of its power production capacity away from the day-ahead energy market into a "wind-following" service that smoothes the intermittent production of wind turbines. Offering such a service imposes both private and social opportunity costs. Since fluctuations in wind energy output are not perfectly correlated with day-ahead energy prices, a wind-following service will necessarily affect generator revenues. Seasonal wind patterns produce conflicts with the goal of managing rivers for "ecosystem services" - the maintenance or enhancement of downstream ecosystems. We illustrate our decision model using the Kerr Dam in PJM's territory in North Carolina. We simulate the operation of Kerr Dam over a three-year period that features hydrologic variability from normal water years to extreme drought conditions. We use an optimization framework to estimate reservation prices for Kerr Dam offering wind-following services in the PJM market. Wind-following may be profitable for Kerr Dam at low capacity levels during some time periods if ecosystems services are neglected and if side payments, or reserves-type payments, are provided. Wind-following with ecosystem services yields revenue losses that typically cannot be recovered with reserves market payments. Water release patterns are inconsistent with ecosystem-services goals when Kerr Dam dedicates significant capacity to wind-following, particularly in drought years.

Early warning of limit-exceeding concentrations of cyanobacteria and cyanotoxins in drinking water reservoirs by inferential modelling.

PubMed

Recknagel, Friedrich; Orr, Philip T; Bartkow, Michael; Swanepoel, Annelie; Cao, Hongqing

2017-11-01

An early warning scheme is proposed that runs ensembles of inferential models for predicting the cyanobacterial population dynamics and cyanotoxin concentrations in drinking water reservoirs on a diel basis driven by in situ sonde water quality data. When the 10- to 30-day-ahead predicted concentrations of cyanobacteria cells or cyanotoxins exceed pre-defined limit values, an early warning automatically activates an action plan considering in-lake control, e.g. intermittent mixing and ad hoc water treatment in water works, respectively. Case studies of the sub-tropical Lake Wivenhoe (Australia) and the Mediterranean Vaal Reservoir (South Africa) demonstrate that ensembles of inferential models developed by the hybrid evolutionary algorithm HEA are capable of up to 30days forecasts of cyanobacteria and cyanotoxins using data collected in situ. The resulting models for Dolicospermum circinale displayed validity for up to 10days ahead, whilst concentrations of Cylindrospermopsis raciborskii and microcystins were successfully predicted up to 30days ahead. Implementing the proposed scheme for drinking water reservoirs enhances current water quality monitoring practices by solely utilising in situ monitoring data, in addition to cyanobacteria and cyanotoxin measurements. Access to routinely measured cyanotoxin data allows for development of models that predict explicitly cyanotoxin concentrations that avoid to inadvertently model and predict non-toxic cyanobacterial strains. Copyright © 2017 Elsevier B.V. All rights reserved.

Coordinated EV adoption: double-digit reductions in emissions and fuel use for $40/vehicle-year.

PubMed

Choi, Dong Gu; Kreikebaum, Frank; Thomas, Valerie M; Divan, Deepak

2013-09-17

Adoption of electric vehicles (EVs) would affect the costs and sources of electricity and the United States efficiency requirements for conventional vehicles (CVs). We model EV adoption scenarios in each of six regions of the Eastern Interconnection, containing 70% of the United States population. We develop electricity system optimization models at the multidecade, day-ahead, and hour-ahead time scales, incorporating spatial wind energy modeling, endogenous modeling of CV efficiencies, projections for EV efficiencies, and projected CV and EV costs. We find two means to reduce total consumer expenditure (TCE): (i) controlling charge timing and (ii) unlinking the fuel economy regulations for CVs from EVs. Although EVs provide minimal direct GHG reductions, controlled charging provides load flexibility, lowering the cost of renewable electricity. Without EVs, a 33% renewable electricity standard (RES) would cost $193/vehicle-year more than the reference case (10% RES). Combining a 33% RES, EVs with controlled charging and unlinking would reduce combined electric- and vehicle-sector CO2 emissions by 27% and reduce gasoline consumption by 59% for $40/vehicle-year more than the reference case. Coordinating EV adoption with adoption of controlled charging, unlinked fuel economy regulations, and renewable electricity standards would provide low-cost reductions in emissions and fuel usage.

3 CFR 8902 - Proclamation 8902 of November 7, 2012. Veterans Day, 2012

Code of Federal Regulations, 2013 CFR

2013-01-01

... face, there is no challenge we cannot overcome, and our best days are still ahead. This year, we marked... our country moving forward. With respect for and in recognition of the contributions our service...

Correlations and clustering in wholesale electricity markets

DOE PAGES

Cui, Tianyu; Caravelli, Francesco; Ududec, Cozmin

2017-11-24

We study the structure of locational marginal prices in day-ahead and real-time wholesale electricity markets. In particular, we consider the case of two North American markets and show that the price correlations contain information on the locational structure of the grid. We study various clustering methods and introduce a type of correlation function based on event synchronization for spiky time series, and another based on string correlations of location names provided by the markets. As a result, this allows us to reconstruct aspects of the locational structure of the grid.

Correlations and clustering in wholesale electricity markets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cui, Tianyu; Caravelli, Francesco; Ududec, Cozmin

We study the structure of locational marginal prices in day-ahead and real-time wholesale electricity markets. In particular, we consider the case of two North American markets and show that the price correlations contain information on the locational structure of the grid. We study various clustering methods and introduce a type of correlation function based on event synchronization for spiky time series, and another based on string correlations of location names provided by the markets. As a result, this allows us to reconstruct aspects of the locational structure of the grid.

Correlations and clustering in wholesale electricity markets

NASA Astrophysics Data System (ADS)

Cui, Tianyu; Caravelli, Francesco; Ududec, Cozmin

2018-02-01

We study the structure of locational marginal prices in day-ahead and real-time wholesale electricity markets. In particular, we consider the case of two North American markets and show that the price correlations contain information on the locational structure of the grid. We study various clustering methods and introduce a type of correlation function based on event synchronization for spiky time series, and another based on string correlations of location names provided by the markets. This allows us to reconstruct aspects of the locational structure of the grid.

Optimizing Industrial Consumer Demand Response Through Disaggregation, Hour-Ahead Pricing, and Momentary Autonomous Control

NASA Astrophysics Data System (ADS)

Abdulaal, Ahmed

The work in this study addresses the current limitations of the price-driven demand response (DR) approach. Mainly, the dependability on consumers to respond in an energy aware conduct, the response timeliness, the difficulty of applying DR in a busy industrial environment, and the problem of load synchronization are of utmost concern. In order to conduct a simulation study, realistic price simulation model and consumers' building load models are created using real data. DR action is optimized using an autonomous control method, which eliminates the dependency on frequent consumer engagement. Since load scheduling and long-term planning approaches are infeasible in the industrial environment, the proposed method utilizes instantaneous DR in response to hour-ahead price signals (RTP-HA). Preliminary simulation results concluded savings at the consumer-side at the cost of increased supplier-side burden due to the aggregate effect of the universal DR policies. Therefore, a consumer disaggregation strategy is briefly discussed. Finally, a refined discrete-continuous control system is presented, which utilizes multi-objective Pareto optimization, evolutionary programming, utility functions, and bidirectional loads. Demonstrated through a virtual testbed fit with real data, the new system achieves momentary optimized DR in real-time while maximizing the consumer's wellbeing.

Fiber Intake and PAI-1 in type 2 diabetes: Look AHEAD Trial Findings at Baseline and Year 1

PubMed Central

Belalcazar, L. Maria; Anderson, Andrea M.; Lang, Wei; Schwenke, Dawn C.; Haffner, Steven M.; Yatsuya, Hiroshi; Rushing, Julia; Vitolins, Mara Z.; Reeves, Rebecca; Pi-Sunyer, F. Xavier; Tracy, Russell P.; Ballantyne, Christie M.

2014-01-01

Plasminogen Activator Inhibitor 1 (PAI-1) is elevated in obese individuals with type 2 diabetes (T2DM) and may contribute, independently of traditional factors, to increased cardiovascular disease (CVD) risk. Fiber intake may decrease PAI-1 levels. We examined the associations of fiber intake and its changes with PAI-1, before and during an intensive lifestyle intervention for weight loss (ILI) in 1,701 Look AHEAD participants with dietary, fitness and PAI-1 data at baseline and 1-year. Look AHEAD was a randomized CVD trial in 5,145 overweight/obese subjects with T2DM, comparing ILI (goal of ≥7% reduction in baseline weight) with a control arm of diabetes support and education (DSE). ILI participants were encouraged to consume vegetables, fruits and grain products low in sugar and fat. At baseline, median fiber intake was 17.9 g/d. Each 8.3 g/day higher fiber intake was associated with a 9.2% lower PAI-1 level (p=0.008); this association persisted after weight and fitness adjustments (p=0.03). Higher baseline intake of fruit (p=0.019) and high-fiber grain and cereal (p=0.029) were related to lower PAI-1 levels. Although successful in improving weight and physical fitness at 1-year, ILI in Look AHEAD resulted in small increases in fiber intake (4.1g/day, compared with -2.35 g/day with DSE), which were not related to PAI-1 change (p=0.34). Only 31.3% of ILI participants (39.8% of women; 19.1% of men) met daily fiber intake recommendations. Increasing fiber intake in overweight/obese individuals with diabetes interested in weight loss is challenging. Future studies evaluating changes in fiber consumption during weight loss interventions are warranted. PMID:25131348

Pricing and Application of Electric Storage

NASA Astrophysics Data System (ADS)

Zhao, Jialin

Electric storage provides a vehicle to store power for future use. It contributes to the grids in multiple aspects. For instance, electric storage is a more effective approach to provide electricity ancillary services than conventional methods. Additionally, electric storage, especially fast-responding units, allows owners to implement high-frequency power transactions in settings such as the 5-min real-time trading market. Such high-frequency power trades were limited in the past. However, as technology advances, the power markets have evolved. For instance, the California Independent System Operator now supports the 5-min real-time trading and the hourly day-ahead ancillary services bidding. Existing valuation models of electric storage were not designed to accommodate these recent market developments. To fill this gap, I focus on the fast-responding grid-level electric storage that provides both the real-time trading and the day-ahead ancillary services bidding. To evaluate such an asset, I propose a Monte Carlo Simulation-based valuation model. The foundation of my model is simulations of power prices. This study develops a new simulation model of electric prices. It is worth noting that, unlike existing models, my proposed simulation model captures the dependency of the real-time markets on the day-ahead markets. Upon such simulations, this study investigates the pricing and the application of electric storage at a 5-min granularity. Essentially, my model is a Dynamic Programming system with both endogenous variables (i.e., the State-of-Charge of electric storage) and exogenous variables (i.e., power prices). My first numerical example is the valuation of a fictitious 4MWh battery. Similarly, my second example evaluates the application of two units of 2MWh batteries. By comparing these two experiments, I investigate the issues related to battery configurations, such as the impacts of splitting storage capability on the valuation of electric storage.

Hospital daily outpatient visits forecasting using a combinatorial model based on ARIMA and SES models.

PubMed

Luo, Li; Luo, Le; Zhang, Xinli; He, Xiaoli

2017-07-10

Accurate forecasting of hospital outpatient visits is beneficial for the reasonable planning and allocation of healthcare resource to meet the medical demands. In terms of the multiple attributes of daily outpatient visits, such as randomness, cyclicity and trend, time series methods, ARIMA, can be a good choice for outpatient visits forecasting. On the other hand, the hospital outpatient visits are also affected by the doctors' scheduling and the effects are not pure random. Thinking about the impure specialty, this paper presents a new forecasting model that takes cyclicity and the day of the week effect into consideration. We formulate a seasonal ARIMA (SARIMA) model on a daily time series and then a single exponential smoothing (SES) model on the day of the week time series, and finally establish a combinatorial model by modifying them. The models are applied to 1 year of daily visits data of urban outpatients in two internal medicine departments of a large hospital in Chengdu, for forecasting the daily outpatient visits about 1 week ahead. The proposed model is applied to forecast the cross-sectional data for 7 consecutive days of daily outpatient visits over an 8-weeks period based on 43 weeks of observation data during 1 year. The results show that the two single traditional models and the combinatorial model are simplicity of implementation and low computational intensiveness, whilst being appropriate for short-term forecast horizons. Furthermore, the combinatorial model can capture the comprehensive features of the time series data better. Combinatorial model can achieve better prediction performance than the single model, with lower residuals variance and small mean of residual errors which needs to be optimized deeply on the next research step.

Approaching Endeavour Crater, Sol 2,680

NASA Image and Video Library

2011-10-10

This image from the navigation camera on NASA Mars Exploration Rover Opportunity shows the view ahead on the day before the rover reached the rim of Endeavour crater. It was taken during the 2,680th Martian day, or sol, of the rover work on Mars.

Seasonal-Scale Optimization of Conventional Hydropower Operations in the Upper Colorado System

NASA Astrophysics Data System (ADS)

Bier, A.; Villa, D.; Sun, A.; Lowry, T. S.; Barco, J.

2011-12-01

Sandia National Laboratories is developing the Hydropower Seasonal Concurrent Optimization for Power and the Environment (Hydro-SCOPE) tool to examine basin-wide conventional hydropower operations at seasonal time scales. This tool is part of an integrated, multi-laboratory project designed to explore different aspects of optimizing conventional hydropower operations. The Hydro-SCOPE tool couples a one-dimensional reservoir model with a river routing model to simulate hydrology and water quality. An optimization engine wraps around this model framework to solve for long-term operational strategies that best meet the specific objectives of the hydrologic system while honoring operational and environmental constraints. The optimization routines are provided by Sandia's open source DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) software. Hydro-SCOPE allows for multi-objective optimization, which can be used to gain insight into the trade-offs that must be made between objectives. The Hydro-SCOPE tool is being applied to the Upper Colorado Basin hydrologic system. This system contains six reservoirs, each with its own set of objectives (such as maximizing revenue, optimizing environmental indicators, meeting water use needs, or other objectives) and constraints. This leads to a large optimization problem with strong connectedness between objectives. The systems-level approach used by the Hydro-SCOPE tool allows simultaneous analysis of these objectives, as well as understanding of potential trade-offs related to different objectives and operating strategies. The seasonal-scale tool will be tightly integrated with the other components of this project, which examine day-ahead and real-time planning, environmental performance, hydrologic forecasting, and plant efficiency.

Analytical design and evaluation of an active control system for helicopter vibration reduction and gust response alleviation

NASA Technical Reports Server (NTRS)

Taylor, R. B.; Zwicke, P. E.; Gold, P.; Miao, W.

1980-01-01

An analytical study was conducted to define the basic configuration of an active control system for helicopter vibration and gust response alleviation. The study culminated in a control system design which has two separate systems: narrow band loop for vibration reduction and wider band loop for gust response alleviation. The narrow band vibration loop utilizes the standard swashplate control configuration to input controller for the vibration loop is based on adaptive optimal control theory and is designed to adapt to any flight condition including maneuvers and transients. The prime characteristics of the vibration control system is its real time capability. The gust alleviation control system studied consists of optimal sampled data feedback gains together with an optimal one-step-ahead prediction. The prediction permits the estimation of the gust disturbance which can then be used to minimize the gust effects on the helicopter.

Mitigating Short-Term Variations of Photovoltaic Generation Using Energy Storage with VOLTTRON

NASA Astrophysics Data System (ADS)

Morrissey, Kevin

A smart-building communications system performs smoothing on photovoltaic (PV) power generation using a battery energy storage system (BESS). The system runs using VOLTTRON(TM), a multi-agent python-based software platform dedicated to power systems. The VOLTTRON(TM) system designed for this project runs synergistically with the larger University of Washington VOLTTRON(TM) environment, which is designed to operate UW device communications and databases as well as to perform real-time operations for research. One such research algorithm that operates simultaneously with this PV Smoothing System is an energy cost optimization system which optimizes net demand and associated cost throughout a day using the BESS. The PV Smoothing System features an active low-pass filter with an adaptable time constant, as well as adjustable limitations on the output power and accumulated battery energy of the BESS contribution. The system was analyzed using 26 days of PV generation at 1-second resolution. PV smoothing was studied with unconstrained BESS contribution as well as under a broad range of BESS constraints analogous to variable-sized storage. It was determined that a large inverter output power was more important for PV smoothing than a large battery energy capacity. Two methods of selecting the time constant in real time, static and adaptive, are studied for their impact on system performance. It was found that both systems provide a high level of PV smoothing performance, within 8% of the ideal case where the best time constant is known ahead of time. The system was run in real time using VOLTTRON(TM) with BESS limitations of 5 kW/6.5 kWh and an adaptive update period of 7 days. The system behaved as expected given the BESS parameters and time constant selection methods, providing smoothing on the PV generation and updating the time constant periodically using the adaptive time constant selection method.

A hybrid predictive model for acoustic noise in urban areas based on time series analysis and artificial neural network

NASA Astrophysics Data System (ADS)

Guarnaccia, Claudio; Quartieri, Joseph; Tepedino, Carmine

2017-06-01

The dangerous effect of noise on human health is well known. Both the auditory and non-auditory effects are largely documented in literature, and represent an important hazard in human activities. Particular care is devoted to road traffic noise, since it is growing according to the growth of residential, industrial and commercial areas. For these reasons, it is important to develop effective models able to predict the noise in a certain area. In this paper, a hybrid predictive model is presented. The model is based on the mixing of two different approach: the Time Series Analysis (TSA) and the Artificial Neural Network (ANN). The TSA model is based on the evaluation of trend and seasonality in the data, while the ANN model is based on the capacity of the network to "learn" the behavior of the data. The mixed approach will consist in the evaluation of noise levels by means of TSA and, once the differences (residuals) between TSA estimations and observed data have been calculated, in the training of a ANN on the residuals. This hybrid model will exploit interesting features and results, with a significant variation related to the number of steps forward in the prediction. It will be shown that the best results, in terms of prediction, are achieved predicting one step ahead in the future. Anyway, a 7 days prediction can be performed, with a slightly greater error, but offering a larger range of prediction, with respect to the single day ahead predictive model.

Day-Ahead PM2.5 Concentration Forecasting Using WT-VMD Based Decomposition Method and Back Propagation Neural Network Improved by Differential Evolution

PubMed Central

Wang, Deyun; Liu, Yanling; Luo, Hongyuan; Yue, Chenqiang; Cheng, Sheng

2017-01-01

Accurate PM2.5 concentration forecasting is crucial for protecting public health and atmospheric environment. However, the intermittent and unstable nature of PM2.5 concentration series makes its forecasting become a very difficult task. In order to improve the forecast accuracy of PM2.5 concentration, this paper proposes a hybrid model based on wavelet transform (WT), variational mode decomposition (VMD) and back propagation (BP) neural network optimized by differential evolution (DE) algorithm. Firstly, WT is employed to disassemble the PM2.5 concentration series into a number of subsets with different frequencies. Secondly, VMD is applied to decompose each subset into a set of variational modes (VMs). Thirdly, DE-BP model is utilized to forecast all the VMs. Fourthly, the forecast value of each subset is obtained through aggregating the forecast results of all the VMs obtained from VMD decomposition of this subset. Finally, the final forecast series of PM2.5 concentration is obtained by adding up the forecast values of all subsets. Two PM2.5 concentration series collected from Wuhan and Tianjin, respectively, located in China are used to test the effectiveness of the proposed model. The results demonstrate that the proposed model outperforms all the other considered models in this paper. PMID:28704955

Surgical simulation: Current practices and future perspectives for technical skills training.

PubMed

Bjerrum, Flemming; Thomsen, Ann Sofia Skou; Nayahangan, Leizl Joy; Konge, Lars

2018-06-17

Simulation-based training (SBT) has become a standard component of modern surgical education, yet successful implementation of evidence-based training programs remains challenging. In this narrative review, we use Kern's framework for curriculum development to describe where we are now and what lies ahead for SBT within surgery with a focus on technical skills in operative procedures. Despite principles for optimal SBT (proficiency-based, distributed, and deliberate practice) having been identified, massed training with fixed time intervals or a fixed number of repetitions is still being extensively used, and simulators are generally underutilized. SBT should be part of surgical training curricula, including theoretical, technical, and non-technical skills, and be based on relevant needs assessments. Furthermore, training should follow evidence-based theoretical principles for optimal training, and the effect of training needs to be evaluated using relevant outcomes. There is a larger, still unrealized potential of surgical SBT, which may be realized in the near future as simulator technologies evolve, more evidence-based training programs are implemented, and cost-effectiveness and impact on patient safety is clearly demonstrated.

In-Flight Subsonic Lift and Drag Characteristics Unique to Blunt-Based Lifting Reentry Vehicles

NASA Technical Reports Server (NTRS)

Saltzman, Edwin J.; Wang, K. Charles; Iliff, Kenneth W.

2007-01-01

Lift and drag measurements have been analyzed for subsonic flight conditions for seven blunt-based reentry-type vehicles. Five of the vehicles are lifting bodies (M2-F1, M2-F2, HL-10, X-24A, and X-24B) and two are wing-body configurations (the X-15 and the Space Shuttle Enterprise). Base pressure measurements indicate that the base drag for full-scale vehicles is approximately three times greater than predicted by Hoerner's equation for three-dimensional bodies. Base drag and forebody drag combine to provide an optimal overall minimum drag (a drag "bucket") for a given configuration. The magnitude of this optimal drag, as well as the associated forebody drag, is dependent on the ratio of base area to vehicle wetted area. Counter-intuitively, the flight-determined optimal minimum drag does not occur at the point of minimum forebody drag, but at a higher forebody drag value. It was also found that the chosen definition for reference area for lift parameters should include the projection of planform area ahead of the wing trailing edge (i.e., forebody plus wing). Results are assembled collectively to provide a greater understanding of this class of vehicles than would occur by considering them individually.

Tackling optimization challenges in industrial load control and full-duplex radios

NASA Astrophysics Data System (ADS)

Gholian, Armen

In price-based demand response programs in smart grid, utilities set the price in accordance with the grid operating conditions and consumers respond to price signals by conducting optimal load control to minimize their energy expenditure while satisfying their energy needs. Industrial sector consumes a large portion of world electricity and addressing optimal load control of energy-intensive industrial complexes, such as steel industry and oil-refinery, is of practical importance. Formulating a general industrial complex and addressing issues in optimal industrial load control in smart grid is the focus of the second part of this dissertation. Several industrial load details are considered in the proposed formulation, including those that do not appear in residential or commercial load control problems. Operation under different smart pricing scenarios, namely, day-ahead pricing, time-of-use pricing, peak pricing, inclining block rates, and critical peak pricing are considered. The use of behind-the-meter renewable generation and energy storage is also considered. The formulated optimization problem is originally nonlinear and nonconvex and thus hard to solve. However, it is then reformulated into a tractable linear mixed-integer program. The performance of the design is assessed through various simulations for an oil refinery and a steel mini-mill. In the third part of this dissertation, a novel all-analog RF interference canceler is proposed. Radio self-interference cancellation (SIC) is the fundamental enabler for full-duplex radios. While SIC methods based on baseband digital signal processing and/or beamforming are inadequate, an all-analog method is useful to drastically reduce the self-interference as the first stage of SIC. It is shown that a uniform architecture with uniformly distributed RF attenuators has a performance highly dependent on the carrier frequency. It is also shown that a new architecture with the attenuators distributed in a clustered fashion has important advantages over the uniform architecture. These advantages are shown numerically through random multipath interference channels, number of control bits in step attenuators, attenuation-dependent phases, single and multi-level structures, etc.

Prototype Test Results for the Single Photon Detection SLR2000 Satellite Laser Ranging System

NASA Technical Reports Server (NTRS)

Zagwodzki, Thomas W.; McGarry, Jan F.; Degnan, John J.; Cheek, Jack W.; Dunn, Peter J.; Patterson, Don; Donovan, Howard

2004-01-01

NASA's aging Satellite Laser Ranging (SLR) network is scheduled to be replaced over the next few years with a fully automated single photon detection system. A prototype of this new system, called SLR2000, is currently undergoing field trials at the Goddard Space Flight Center in Greenbelt, Maryland to evaluate photon counting techniques and determine system hardware, software, and control algorithm performance levels and limitations. Newly developed diode pumped microchip lasers and quadrant microchannel plate-based photomultiplier tubes have enabled the development of this high repetition rate single photon detection SLR system. The SLR2000 receiver threshold is set at the single photoelectron (pe) level but tracks satellites with an average signal level typically much less than 1 pe. The 2 kHz laser fire rate aids in satellite acquisition and tracking and will enable closed loop tracking by accumulating single photon count statistics in a quadrant detector and using this information to correct for pointing errors. Laser transmitter beamwidths of 10 arcseconds (FWHM) or less are currently being used to maintain an adequate signal level for tracking while the receiver field of view (FOV) has been opened to 40 arcseconds to accommodate point ahead/look behind angular offsets. In the near future, the laser transmitter point ahead will be controlled by a pair of Risley prisms. This will allow the telescope to point behind and enable closure of the receiver FOV to roughly match the transmitter beam divergence. Bandpass filters (BPF) are removed for night tracking operations while 0.2 nm or 1 nm filters are used during daylight operation. Both day and night laser tracking of Low Earth Orbit (LEO) satellites has been achieved with a laser transmitter energy of only 65 microjoules per pulse. Satellite tracking is presently limited to LEO satellites until the brassboard laser transmitter can be upgraded or replaced. Simultaneous tracks have also been observed with NASA s SLR standard, MOBLAS 7, for the purposes of data comparison and identification of biases. Work continues to optimize the receive optics; upgrade or replace the laser transmitter; calibrate the quadrant detector, the point ahead Risley prisms, and event timer verniers; and test normal point generation with SLR2000 data. This paper will report on the satellite tracking results to date, issues yet to be resolved, and future plans for the SLR2000 system.

Forecasting volatility of SSEC in Chinese stock market using multifractal analysis

NASA Astrophysics Data System (ADS)

Wei, Yu; Wang, Peng

2008-03-01

In this paper, taking about 7 years’ high-frequency data of the Shanghai Stock Exchange Composite Index (SSEC) as an example, we propose a daily volatility measure based on the multifractal spectrum of the high-frequency price variability within a trading day. An ARFIMA model is used to depict the dynamics of this multifractal volatility (MFV) measures. The one-day ahead volatility forecasting performances of the MFV model and some other existing volatility models, such as the realized volatility model, stochastic volatility model and GARCH, are evaluated by the superior prediction ability (SPA) test. The empirical results show that under several loss functions, the MFV model obtains the best forecasting accuracy.

Using L-M BP Algorithm Forecase the 305 Days Production of First-Breed Dairy

NASA Astrophysics Data System (ADS)

Wei, Xiaoli; Qi, Guoqiang; Shen, Weizheng; Jian, Sun

Aiming at the shortage of conventional BP algorithm, a BP neural net works improved by L-M algorithm is put forward. On the basis of the network, a Prediction model for 305 day's milk productions was set up. Traditional methods finish these data must spend at least 305 days, But this model can forecast first-breed dairy's 305 days milk production ahead of 215 days. The validity of the improved BP neural network predictive model was validated through the experiments.

Sustainability Activities In The Mining Sector: Current Status And Challenges Ahead Limestone Mining In Nusakambangan

NASA Astrophysics Data System (ADS)

Ayuningrum, Theresia Vika; Purnaweni, Hartuti

2018-02-01

Potential Karst area in Nusakambangan has an important role in maintaining the balance of nature. But with the existence of mining activities, will automatically change the environmental conditions there. In order for the utilization of resources to meet the rules of optimization between the interests of mining and sustainability of the environment so in every mining sector activities required a variety of environmental studies. The purpose of this study is to find out how the analysis of environmental management due to limestone mining activities in Nusakambangan so that it can be known the management of mining areas are optimal, wise based on ecological principles, and sustainability. In qualitative research methods, data analysis using description percentage, with the type of data collected in the form of primary data and secondary data.

Ophthalmic public health; the way ahead.

PubMed

Heidary, F; Rahimi, A; Gharebaghi, R

2012-01-01

Visual sciences have been progressing quickly in recent decades through globalization phenomenon. An enormous change has taken place in ocular health issues, however, there are various problems facing ophthalmic public health worldwide. In the previous years, the World Health Organization and the International Agency for the Prevention of Blindness in partnership launched the global initiative to eradicate avoidable blindness by the year 2020, VISION 2020 the Right to Sight. It has concentrated on the prevention of blindness disability and recognized a health issue-sight as a human right. In view of challenges ahead of visual sciences, close collaboration between international agencies at the global level to implement new strategies and monitor the progress will be mandatory. In these circumstances non-governmental organizations should not be neglected. World Sight Day 2012 would be a great opportunity to be a focus on importance of visual impairment as an important public health issue and discovering new challenges ahead.

Generating Data Flow Programs from Nonprocedural Specifications.

DTIC Science & Technology

1983-03-01

With the I-structures, Gajski points out, it is difficult to know ahead of time the optimal memory allocation scheme to pertition large arrays. amory...contention problems may occur for frequently accessed elements stored in the sam memory module. Gajski observes that these are the same problem which

Rainy Days: Program Ideas That Make a Splash.

ERIC Educational Resources Information Center

Grayson, Randall

1996-01-01

Stresses the importance of planning ahead for rainy day activities at camp. Suggested outdoor activities include learning to build a fire in the rain, dam building, canoe puzzles, and holey garbage-can fill; indoor activities include crafts, pass the present, human game pieces, and opportunities for cabin groups to plan and host a fun activity.…

The Educational Leader's Alchemy: Creating the Gold Within

ERIC Educational Resources Information Center

Sytsma, Sandra

2009-01-01

In going ahead and showing the way, leading can be seen as a process of changing. The busyness of day-to-day leadership in schools and other educational facilities bears witness to the necessity of leaders' "thinking on their feet" as they strive to resolve multiple issues. However, the constant pressure or stress of this lifestyle has its price…

Load alleviation maneuvers for a launch vehicle

NASA Technical Reports Server (NTRS)

Seywald, Hans; Bless, Robert

1993-01-01

This paper addresses the design of a forward-looking autopilot that is capable of employing a priori knowledge of wind gusts ahead of the flight path to reduce the bending loads experienced by a launch vehicle. The analysis presented in the present paper is only preliminary, employing a very simple vehicle dynamical model and restricting itself to wind gusts of the form of isolated spikes. The main result of the present study is that LQR based feedback laws are inappropriate to handle spike-type wind perturbations with large amplitude and narrow base. The best performance is achieved with an interior-point penalty optimal control formulation which can be well approximated by a simple feedback control law. Reduction of the maximum bending loads by nearly 50 percent is demonstrated.

Bright Days Ahead for Curiosity Mars Rover

NASA Image and Video Library

2011-03-18

This image shows preparation for March 2011 testing of the Mars Science Laboratory rover, Curiosity, in a space-simulation chamber; the rover will go through operational sequences in environmental conditions similar to what it will experience on Mars.

78 FR 61941 - Combined Notice of Filings #1

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-07

.... Applicants: Southwest Power Pool, Inc. Description: Revisions to Day-Ahead Virtual Energy Transaction Fee to...: 20130924-5121. Comments Due: 5 p.m. e.t. 10/15/13. The filings are accessible in the Commission's eLibrary...

Energy storage arbitrage under day-ahead and real-time price uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnamurthy, Dheepak; Uckun, Canan; Zhou, Zhi

Electricity markets must match real-time supply and demand of electricity. With increasing penetration of renewable resources, it is important that this balancing is done effectively, considering the high uncertainty of wind and solar energy. Storing electrical energy can make the grid more reliable and efficient and energy storage is proposed as a complement to highly variable renewable energy sources. However, for investments in energy storage to increase, participating in the market must become economically viable for owners. This paper proposes a stochastic formulation of a storage owner’s arbitrage profit maximization problem under uncertainty in day-ahead (DA) and real-time (RT) marketmore » prices. The proposed model helps storage owners in market bidding and operational decisions and in estimation of the economic viability of energy storage. Finally, case study results on realistic market price data show that the novel stochastic bidding approach does significantly better than the deterministic benchmark.« less

Energy storage arbitrage under day-ahead and real-time price uncertainty

DOE PAGES

Krishnamurthy, Dheepak; Uckun, Canan; Zhou, Zhi; ...

2017-04-04

Electricity markets must match real-time supply and demand of electricity. With increasing penetration of renewable resources, it is important that this balancing is done effectively, considering the high uncertainty of wind and solar energy. Storing electrical energy can make the grid more reliable and efficient and energy storage is proposed as a complement to highly variable renewable energy sources. However, for investments in energy storage to increase, participating in the market must become economically viable for owners. This paper proposes a stochastic formulation of a storage owner’s arbitrage profit maximization problem under uncertainty in day-ahead (DA) and real-time (RT) marketmore » prices. The proposed model helps storage owners in market bidding and operational decisions and in estimation of the economic viability of energy storage. Finally, case study results on realistic market price data show that the novel stochastic bidding approach does significantly better than the deterministic benchmark.« less

An implementation of the QMR method based on coupled two-term recurrences

NASA Technical Reports Server (NTRS)

Freund, Roland W.; Nachtigal, Noeel M.

1992-01-01

The authors have proposed a new Krylov subspace iteration, the quasi-minimal residual algorithm (QMR), for solving non-Hermitian linear systems. In the original implementation of the QMR method, the Lanczos process with look-ahead is used to generate basis vectors for the underlying Krylov subspaces. In the Lanczos algorithm, these basis vectors are computed by means of three-term recurrences. It has been observed that, in finite precision arithmetic, vector iterations based on three-term recursions are usually less robust than mathematically equivalent coupled two-term vector recurrences. This paper presents a look-ahead algorithm that constructs the Lanczos basis vectors by means of coupled two-term recursions. Implementation details are given, and the look-ahead strategy is described. A new implementation of the QMR method, based on this coupled two-term algorithm, is described. A simplified version of the QMR algorithm without look-ahead is also presented, and the special case of QMR for complex symmetric linear systems is considered. Results of numerical experiments comparing the original and the new implementations of the QMR method are reported.

75 FR 42411 - Orders Finding That the SP-15 Financial Day-Ahead LMP Peak Daily Contract; SP-15 Financial Day...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-21

...''), an exempt commercial market (``ECM'') under sections 2(h)(3)-(5) of the Commodity Exchange Act (``CEA... (``Reauthorization Act'') \\5\\ significantly broadened the CFTC's regulatory authority with respect to ECMs by creating, in section 2(h)(7) of the CEA, a new regulatory category--ECMs on which significant price...

Towards the development of a multimodel hydrological ensemble prediction system for La Mojana, Colombia

NASA Astrophysics Data System (ADS)

Brochero, D.; Peña, J.; Anctil, F.; Boucher, M. A.; Nogales, J.; Reyes, N.

2016-12-01

The impacts of floods in Colombia during 2010 and 2011 as a result of ENSO in its cold phase (La Niña) marked a milestone in Colombian politics. In La Mojana region the balance was around 100,000 homeless and 3 km2 of flooded crops. We model the upstream basin of La Mojana (3600 km2 and a mean annual precipitation from 1000mm in valleys to 4500 mm in mountains). A forecasting system of at least three days in advance was judged prudent. This basin receives an streamflow highly regulated by multiple reservoirs that we model with a recurrent neural networks from 1 to 3-days ahead. For hydrological modeling purposes we use the GR4J, HBV, and SIMHYD models, records of daily precipitation, temperature, and streamflows, and 110 prediction scenarios of precipitation and temperature from Canada, USA, Brazil, and Europe extracted from the TIGGE database (MEPS). Calibration period is between January 2004 and August 2011. Validation from September to December 2011, taking as meteorological input the MEPS. We analised four alternative for the 3-day Hydrological Ensemble Prediction System (HEPS) Calibration: 1) only the GR4J model and observed values, 2). as 1 but HBV and SIMHYD are included, 3). Simultaneous optimization of the three hydrological models based on the reliability maximisation and the CRPS minimisation using the multiobjective calibration, observed and forecasted temperature and precipitation from the MEPS and, 4). as 3 but adding the daily streamflow data assimilation. Results show that the use of multiple hydrological models is clearly advantageous but even more performing the simultaneous optimization of hydrological models in the probabilistic context directly. The results evolution of the MAE on the reliability diagram (MAE-RD) are 43%, 27%, 17% and 15% respectively for the four alternatives. Regarding CRPS, MAE results show that the probabilistic prediction improves the deterministic estimate based on the daily mean HEPS scenario, despite the improvement in reliability is not necessarily reflected in the CRPS for the four alternatives: 4.3, 3.06 , 9.98, and 3.94, values that also accompany the mean scenario Nash-Sutcliffe of 0.93, 0.96, 0.51, and 0.93 respectively. In conclusion it shows that alternative 4 reached a good compromise between the deterministic and probabilistic performance (NS=0.93 and MAERD = 15%).

Rolling scheduling of electric power system with wind power based on improved NNIA algorithm

NASA Astrophysics Data System (ADS)

Xu, Q. S.; Luo, C. J.; Yang, D. J.; Fan, Y. H.; Sang, Z. X.; Lei, H.

2017-11-01

This paper puts forth a rolling modification strategy for day-ahead scheduling of electric power system with wind power, which takes the operation cost increment of unit and curtailed wind power of power grid as double modification functions. Additionally, an improved Nondominated Neighbor Immune Algorithm (NNIA) is proposed for solution. The proposed rolling scheduling model has further improved the operation cost of system in the intra-day generation process, enhanced the system’s accommodation capacity of wind power, and modified the key transmission section power flow in a rolling manner to satisfy the security constraint of power grid. The improved NNIA algorithm has defined an antibody preference relation model based on equal incremental rate, regulation deviation constraints and maximum & minimum technical outputs of units. The model can noticeably guide the direction of antibody evolution, and significantly speed up the process of algorithm convergence to final solution, and enhance the local search capability.

Predicting outcomes to optimize disease management in inflammatory bowel disease in Japan: their differences and similarities to Western countries.

PubMed

Kobayashi, Taku; Hisamatsu, Tadakazu; Suzuki, Yasuo; Ogata, Haruhiko; Andoh, Akira; Araki, Toshimitsu; Hokari, Ryota; Iijima, Hideki; Ikeuchi, Hiroki; Ishiguro, Yoh; Kato, Shingo; Kunisaki, Reiko; Matsumoto, Takayuki; Motoya, Satoshi; Nagahori, Masakazu; Nakamura, Shiro; Nakase, Hiroshi; Tsujikawa, Tomoyuki; Sasaki, Makoto; Yokoyama, Kaoru; Yoshimura, Naoki; Watanabe, Kenji; Katafuchi, Miiko; Watanabe, Mamoru; Hibi, Toshifumi

2018-04-01

Inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), is a chronic inflammatory disease of the gastrointestinal tract, with increasing prevalence worldwide. IBD Ahead is an international educational program that aims to explore questions commonly raised by clinicians about various areas of IBD care and to consolidate available published evidence and expert opinion into a consensus for the optimization of IBD management. Given differences in the epidemiology, clinical and genetic characteristics, management, and prognosis of IBD between patients in Japan and the rest of the world, this statement was formulated as the result of literature reviews and discussions among Japanese experts as part of the IBD Ahead program to consolidate statements of factors for disease prognosis in IBD. Evidence levels were assigned to summary statements in the following categories: disease progression in CD and UC; surgery, hospitalization, intestinal failure, and permanent stoma in CD; acute severe UC; colectomy in UC; and colorectal carcinoma and dysplasia in IBD. The goal is that this statement can aid in the optimization of the treatment strategy for Japanese patients with IBD and help identify high-risk patients that require early intervention, to provide a better long-term prognosis in these patients.

Predicting outcomes to optimize disease management in inflammatory bowel disease in Japan: their differences and similarities to Western countries

PubMed Central

Kobayashi, Taku; Suzuki, Yasuo; Ogata, Haruhiko; Andoh, Akira; Araki, Toshimitsu; Hokari, Ryota; Iijima, Hideki; Ikeuchi, Hiroki; Ishiguro, Yoh; Kato, Shingo; Kunisaki, Reiko; Matsumoto, Takayuki; Motoya, Satoshi; Nagahori, Masakazu; Nakamura, Shiro; Nakase, Hiroshi; Tsujikawa, Tomoyuki; Sasaki, Makoto; Yokoyama, Kaoru; Yoshimura, Naoki; Watanabe, Kenji; Katafuchi, Miiko; Watanabe, Mamoru; Hibi, Toshifumi

2018-01-01

Inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), is a chronic inflammatory disease of the gastrointestinal tract, with increasing prevalence worldwide. IBD Ahead is an international educational program that aims to explore questions commonly raised by clinicians about various areas of IBD care and to consolidate available published evidence and expert opinion into a consensus for the optimization of IBD management. Given differences in the epidemiology, clinical and genetic characteristics, management, and prognosis of IBD between patients in Japan and the rest of the world, this statement was formulated as the result of literature reviews and discussions among Japanese experts as part of the IBD Ahead program to consolidate statements of factors for disease prognosis in IBD. Evidence levels were assigned to summary statements in the following categories: disease progression in CD and UC; surgery, hospitalization, intestinal failure, and permanent stoma in CD; acute severe UC; colectomy in UC; and colorectal carcinoma and dysplasia in IBD. The goal is that this statement can aid in the optimization of the treatment strategy for Japanese patients with IBD and help identify high-risk patients that require early intervention, to provide a better long-term prognosis in these patients.

Inductive reasoning and forecasting of population dynamics of Cylindrospermopsis raciborskii in three sub-tropical reservoirs by evolutionary computation.

PubMed

Recknagel, Friedrich; Orr, Philip T; Cao, Hongqing

2014-01-01

Seven-day-ahead forecasting models of Cylindrospermopsis raciborskii in three warm-monomictic and mesotrophic reservoirs in south-east Queensland have been developed by means of water quality data from 1999 to 2010 and the hybrid evolutionary algorithm HEA. Resulting models using all measured variables as inputs as well as models using electronically measurable variables only as inputs forecasted accurately timing of overgrowth of C. raciborskii and matched well high and low magnitudes of observed bloom events with 0.45≤r 2 >0.61 and 0.4≤r 2 >0.57, respectively. The models also revealed relationships and thresholds triggering bloom events that provide valuable information on synergism between water quality conditions and population dynamics of C. raciborskii. Best performing models based on using all measured variables as inputs indicated electrical conductivity (EC) within the range of 206-280mSm -1 as threshold above which fast growth and high abundances of C. raciborskii have been observed for the three lakes. Best models based on electronically measurable variables for the Lakes Wivenhoe and Somerset indicated a water temperature (WT) range of 25.5-32.7°C within which fast growth and high abundances of C. raciborskii can be expected. By contrast the model for Lake Samsonvale highlighted a turbidity (TURB) level of 4.8 NTU as indicator for mass developments of C. raciborskii. Experiments with online measured water quality data of the Lake Wivenhoe from 2007 to 2010 resulted in predictive models with 0.61≤r 2 >0.65 whereby again similar levels of EC and WT have been discovered as thresholds for outgrowth of C. raciborskii. The highest validity of r 2 =0.75 for an in situ data-based model has been achieved after considering time lags for EC by 7 days and dissolved oxygen by 1 day. These time lags have been discovered by a systematic screening of all possible combinations of time lags between 0 and 10 days for all electronically measurable variables. The so-developed model performs seven-day-ahead forecasts and is currently implemented and tested for early warning of C. raciborskii blooms in the Wivenhoe reservoir. Copyright © 2013 Elsevier B.V. All rights reserved.

Multi-stage flash degaser

DOEpatents

Rapier, P.M.

1980-06-26

A multi-stage flash degaser is incorporated in an energy conversion system having a direct-contact, binary-fluid heat exchanger to remove essentially all of the noncondensable gases from geothermal brine ahead of the direct-contact binary-fluid heat exchanger in order that the heat exchanger and a turbine and condenser of the system can operate at optimal efficiency.

Adaptive MPC based on MIMO ARX-Laguerre model.

PubMed

Ben Abdelwahed, Imen; Mbarek, Abdelkader; Bouzrara, Kais

2017-03-01

This paper proposes a method for synthesizing an adaptive predictive controller using a reduced complexity model. This latter is given by the projection of the ARX model on Laguerre bases. The resulting model is entitled MIMO ARX-Laguerre and it is characterized by an easy recursive representation. The adaptive predictive control law is computed based on multi-step-ahead finite-element predictors, identified directly from experimental input/output data. The model is tuned in each iteration by an online identification algorithms of both model parameters and Laguerre poles. The proposed approach avoids time consuming numerical optimization algorithms associated with most common linear predictive control strategies, which makes it suitable for real-time implementation. The method is used to synthesize and test in numerical simulations adaptive predictive controllers for the CSTR process benchmark. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Efficient Resources Provisioning Based on Load Forecasting in Cloud

PubMed Central

Hu, Rongdong; Jiang, Jingfei; Liu, Guangming; Wang, Lixin

2014-01-01

Cloud providers should ensure QoS while maximizing resources utilization. One optimal strategy is to timely allocate resources in a fine-grained mode according to application's actual resources demand. The necessary precondition of this strategy is obtaining future load information in advance. We propose a multi-step-ahead load forecasting method, KSwSVR, based on statistical learning theory which is suitable for the complex and dynamic characteristics of the cloud computing environment. It integrates an improved support vector regression algorithm and Kalman smoother. Public trace data taken from multitypes of resources were used to verify its prediction accuracy, stability, and adaptability, comparing with AR, BPNN, and standard SVR. Subsequently, based on the predicted results, a simple and efficient strategy is proposed for resource provisioning. CPU allocation experiment indicated it can effectively reduce resources consumption while meeting service level agreements requirements. PMID:24701160

Spirit Look Ahead After Sol 1866 Drive

NASA Image and Video Library

2009-07-16

This scene combines three frames taken by the navigation camera on NASA Mars Exploration Rover Spirit during the 1,866th Martian day, or sol, of Spirit mission on Mars April 3, 2009. It spans 120 degrees, with south at the center.

Spirit Look Ahead on Sol 1869

NASA Image and Video Library

2009-07-16

This scene combines three frames taken by the navigation camera on NASA Mars Exploration Rover Spirit during the 1,869th Martian day, or sol, of Spirit mission on Mars April 6, 2009. It spans 120 degrees, with south at the center.

Planning a Library Leadership Retreat on the Cheap: Case Study and Analysis

ERIC Educational Resources Information Center

Brower, Stewart

2016-01-01

Staying ahead of the pitch: an old baseball metaphor that means to anticipate where the ball is going to go so that the batter can score a hit. But to anticipate changes in a field as robust and challenging as information sciences, reflection and contemplation are often key to good planning. With simple day-to-day management of libraries already…

Application of satellite-based rainfall and medium range meteorological forecast in real-time flood forecasting in the Mahanadi River basin

NASA Astrophysics Data System (ADS)

Nanda, Trushnamayee; Beria, Harsh; Sahoo, Bhabagrahi; Chatterjee, Chandranath

2016-04-01

Increasing frequency of hydrologic extremes in a warming climate call for the development of reliable flood forecasting systems. The unavailability of meteorological parameters in real-time, especially in the developing parts of the world, makes it a challenging task to accurately predict flood, even at short lead times. The satellite-based Tropical Rainfall Measuring Mission (TRMM) provides an alternative to the real-time precipitation data scarcity. Moreover, rainfall forecasts by the numerical weather prediction models such as the medium term forecasts issued by the European Center for Medium range Weather Forecasts (ECMWF) are promising for multistep-ahead flow forecasts. We systematically evaluate these rainfall products over a large catchment in Eastern India (Mahanadi River basin). We found spatially coherent trends, with both the real-time TRMM rainfall and ECMWF rainfall forecast products overestimating low rainfall events and underestimating high rainfall events. However, no significant bias was found for the medium rainfall events. Another key finding was that these rainfall products captured the phase of the storms pretty well, but suffered from consistent under-prediction. The utility of the real-time TRMM and ECMWF forecast products are evaluated by rainfall-runoff modeling using different artificial neural network (ANN)-based models up to 3-days ahead. Keywords: TRMM; ECMWF; forecast; ANN; rainfall-runoff modeling

AHEAD. Advate in HaEmophilia A outcome Database.

PubMed

Oldenburg, J; Kurnik, K; Huth-Kühne, A; Zimmermann, R; Abraham, I; Klamroth, R

2010-11-01

The clinical picture of haemophilia A patients is often characterised by recurrent bleedings, in particular joint bleeds. Thus far, long-term data on the outcome of haemophilia A patients are scarce as regards the development of target joints, joint replacement, lost days from school or work due to bleedings, and the quality of life, as most previous studies were limited to the aspects of safety and efficacy. The Baxter-initiated AHEAD (Advate in HaEmophilia A outcome Database) study is a multi-centre, prospective, non-interventional observational study of haemophilia A patients. All patients with a residual FVIII activity of £5% who are being treated with ADVATE are eligible. There are no limitations in terms of patient age or treatment regimen. AHEAD is scientifically supported by a renowned interdisciplinary steering board and is intended to yield data on 500 patients in up to 30 haemophilia centres, collected during a period of four years. The large patient population has been chosen in order to ensure a valid database. The objective of the study is to record haemophilia-related arthropathies, which will be defined based on imaging techniques (e. g. MRI, X-ray, ultrasound) and the judgment of the attending physician. In addition, extensive data will be collected on joint replacement surgeries, pseudotumour development, bleeding-related pain, quality of life (age-related questionnaires: Haem-A-QoL, Haemo-QoL, SF10, SF12v2), risk factors (diabetes mellitus, arterial hypertension, nicotine abuse), blood group, gene mutation, physical activity, and on the efficacy and safety of Advate. The patient data will be entered into an electronic CRF system at the centres. Plausibility checks during data entry, regular monitoring visits, and the option of auditing all serve to ensure a high data quality for AHEAD. The first patient was enrolled in the study in early June 2010; recruitment is planned to continue until the end of 2011. The Ethics Committee of the University of Bonn has given its favorable opinion.

Pilot trial of a dissonance-based cognitive-behavioral group depression prevention with college students.

PubMed

Rohde, Paul; Stice, Eric; Shaw, Heather; Gau, Jeff M

2016-07-01

Conduct a pilot trial testing whether a new cognitive-behavioral (CB) group prevention program that incorporated cognitive-dissonance change principles was feasible and appeared effective in reducing depressive symptoms and major depressive disorder onset relative to a brochure control condition in college students with elevated depressive symptoms. 59 college students (M age = 21.8, SD = 2.3; 68% female, 70% White) were randomized to the 6-session Change Ahead group or educational brochure control condition, completing assessments at pretest, posttest, and 3-month follow-up. Recruitment and screening methods were effective and intervention attendance was high (86% attended all 6 sessions). Change Ahead participants showed medium-large reductions in depressive symptoms at posttest (M d = 0.64), though the effect attenuated by 3-month follow-up. Incidence of major depression onset at 3-month follow-up was 4% for Change Ahead participants versus 13% (difference ns). Change Ahead appears highly feasible and showed positive indications of reduced acute phase depressive symptoms and MDD onset relative to a minimal intervention control in this initial pilot. Given the brevity of the intervention, its apparent feasibility, and the lack of evidence-based depression prevention programs for college students, continued evaluation of Change Ahead appears warranted. Copyright © 2016 Elsevier Ltd. All rights reserved.

Pilot Trial of a Dissonance-Based Cognitive-Behavioral Group Depression Prevention with College Students

PubMed Central

Rohde, Paul; Stice, Eric; Shaw, Heather; Gau, Jeff M.

2016-01-01

Objective Conduct a pilot trial testing whether a new cognitive-behavioral (CB) group prevention program that incorporated cognitive-dissonance change principles was feasible and appeared effective in reducing depressive symptoms and major depressive disorder onset relative to a brochure control condition in college students with elevated depressive symptoms. Method 59 college students (M age = 21.8, SD = 2.3; 68% female, 70% White) were randomized to the 6-session Change Ahead group or educational brochure control condition, completing assessments at pretest, posttest, and 3-month follow-up. Results Recruitment and screening methods were effective and intervention attendance was high (86% attended all 6 sessions). Change Ahead participants showed medium-large reductions in depressive symptoms at posttest (M d = .64), though the effect attenuated by 3-month follow-up. Incidence of major depression onset at 3-month follow-up was 4% for Change Ahead participants versus 13% (difference ns). Conclusions Change Ahead appears highly feasible and showed positive indications of reduced acute phase depressive symptoms and MDD onset relative to a minimal intervention control in this initial pilot. Given the brevity of the intervention, its apparent feasibility, and the lack of evidence-based depression prevention programs for college students, continued evaluation of Change Ahead appears warranted. PMID:27176493

Load alleviation maneuvers for a launch vehicle

NASA Technical Reports Server (NTRS)

Seywald, Hans; Bless, Robert R.

1993-01-01

This paper addresses the design of a forward-looking autopilot that is capable of employing a priori knowledge of wind gusts ahead of the flight path to reduce the bending loads experienced by a launch vehicle. The analysis presented in the present paper is only preliminary, employing a very simple vehicle dynamical model and restricting itself to wind gusts of the form of isolated spikes. The main result of the present study is that linear quadratic regulator (LQR) based feedback laws are inappropriate to handle spike-type wind perturbations with large amplitude and narrow base. The best performance is achieved with an interior-point penalty optimal control formulation which can be well approximated by a simple feedback control law. Reduction of the maximum bending loads by nearly 50% is demonstrated.

Optimizing distance-based methods for large data sets

NASA Astrophysics Data System (ADS)

Scholl, Tobias; Brenner, Thomas

2015-10-01

Distance-based methods for measuring spatial concentration of industries have received an increasing popularity in the spatial econometrics community. However, a limiting factor for using these methods is their computational complexity since both their memory requirements and running times are in {{O}}(n^2). In this paper, we present an algorithm with constant memory requirements and shorter running time, enabling distance-based methods to deal with large data sets. We discuss three recent distance-based methods in spatial econometrics: the D&O-Index by Duranton and Overman (Rev Econ Stud 72(4):1077-1106, 2005), the M-function by Marcon and Puech (J Econ Geogr 10(5):745-762, 2010) and the Cluster-Index by Scholl and Brenner (Reg Stud (ahead-of-print):1-15, 2014). Finally, we present an alternative calculation for the latter index that allows the use of data sets with millions of firms.

Intra-Hour Dispatch and Automatic Generator Control Demonstration with Solar Forecasting - Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coimbra, Carlos F. M.

2016-02-25

In this project we address multiple resource integration challenges associated with increasing levels of solar penetration that arise from the variability and uncertainty in solar irradiance. We will model the SMUD service region as its own balancing region, and develop an integrated, real-time operational tool that takes solar-load forecast uncertainties into consideration and commits optimal energy resources and reserves for intra-hour and intra-day decisions. The primary objectives of this effort are to reduce power system operation cost by committing appropriate amount of energy resources and reserves, as well as to provide operators a prediction of the generation fleet’s behavior inmore » real time for realistic PV penetration scenarios. The proposed methodology includes the following steps: clustering analysis on the expected solar variability per region for the SMUD system, Day-ahead (DA) and real-time (RT) load forecasts for the entire service areas, 1-year of intra-hour CPR forecasts for cluster centers, 1-year of smart re-forecasting CPR forecasts in real-time for determination of irreducible errors, and uncertainty quantification for integrated solar-load for both distributed and central stations (selected locations within service region) PV generation.« less

3 CFR 8986 - Proclamation 8986 of May 24, 2013. National Hurricane Preparedness Week, 2013

Code of Federal Regulations, 2014 CFR

2014-01-01

... forecasting with the latest science and technology. And in the months and years ahead, we will continue to... lives and protect communities. IN WITNESS WHEREOF, I have hereunto set my hand this twenty-fourth day of...

Optimal control, investment and utilization schemes for energy storage under uncertainty

NASA Astrophysics Data System (ADS)

Mirhosseini, Niloufar Sadat

Energy storage has the potential to offer new means for added flexibility on the electricity systems. This flexibility can be used in a number of ways, including adding value towards asset management, power quality and reliability, integration of renewable resources and energy bill savings for the end users. However, uncertainty about system states and volatility in system dynamics can complicate the question of when to invest in energy storage and how best to manage and utilize it. This work proposes models to address different problems associated with energy storage within a microgrid, including optimal control, investment, and utilization. Electric load, renewable resources output, storage technology cost and electricity day-ahead and spot prices are the factors that bring uncertainty to the problem. A number of analytical methodologies have been adopted to develop the aforementioned models. Model Predictive Control and discretized dynamic programming, along with a new decomposition algorithm are used to develop optimal control schemes for energy storage for two different levels of renewable penetration. Real option theory and Monte Carlo simulation, coupled with an optimal control approach, are used to obtain optimal incremental investment decisions, considering multiple sources of uncertainty. Two stage stochastic programming is used to develop a novel and holistic methodology, including utilization of energy storage within a microgrid, in order to optimally interact with energy market. Energy storage can contribute in terms of value generation and risk reduction for the microgrid. The integration of the models developed here are the basis for a framework which extends from long term investments in storage capacity to short term operational control (charge/discharge) of storage within a microgrid. In particular, the following practical goals are achieved: (i) optimal investment on storage capacity over time to maximize savings during normal and emergency operations; (ii) optimal market strategy of buy and sell over 24-hour periods; (iii) optimal storage charge and discharge in much shorter time intervals.

Real-time drought forecasting system for irrigation management

NASA Astrophysics Data System (ADS)

Ceppi, A.; Ravazzani, G.; Corbari, C.; Salerno, R.; Meucci, S.; Mancini, M.

2014-09-01

In recent years frequent periods of water scarcity have enhanced the need to use water more carefully, even in European areas which traditionally have an abundant supply of water, such as the Po Valley in northern Italy. In dry periods, water shortage problems can be enhanced by conflicting uses of water, such as irrigation, industry and power production (hydroelectric and thermoelectric). Furthermore, in the last decade the social perspective in relation to this issue has been increasing due to the possible impact of climate change and global warming scenarios which emerge from the IPCC Fifth Assessment Report (IPCC, 2013). Hence, the increased frequency of drought periods has stimulated the improvement of irrigation and water management. In this study we show the development and implementation of the PREGI real-time drought forecasting system; PREGI is an Italian acronym that means "hydro-meteorological forecast for irrigation management". The system, planned as a tool for irrigation optimization, is based on meteorological ensemble forecasts (20 members) at medium range (30 days) coupled with hydrological simulations of water balance to forecast the soil water content on a maize field in the Muzza Bassa Lodigiana (MBL) consortium in northern Italy. The hydrological model was validated against measurements of latent heat flux acquired by an eddy-covariance station, and soil moisture measured by TDR (time domain reflectivity) probes; the reliability of this forecasting system and its benefits were assessed in the 2012 growing season. The results obtained show how the proposed drought forecasting system is able to have a high reliability of forecast at least for 7-10 days ahead of time.

Underway Recovery Test 6 (URT-6) - Day 4 Activities

NASA Image and Video Library

2018-01-20

The USS Anchorage sails toward sunrise while Kennedy Space Center’s NASA Recovery Team prepares for another day of testing as part of Underway Recovery Test 6. The testing with the NASA Recovery Team and the U.S. Navy will provide important data that is being used to improve recovery procedures and hardware ahead of Orion's next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

3 CFR 8739 - Proclamation 8739 of October 14, 2011. Blind Americans Equality Day, 2011

Code of Federal Regulations, 2012 CFR

2012-01-01

... we have made progress in the march to equality for the blind and those with low vision, there is... contributions of Americans who are blind or have low vision. Today, let us recommit to forging ahead with the...

Multi-time scale control of demand flexibility in smart distribution networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhattarai, Bishnu; Myers, Kurt; Bak-Jensen, Birgitte

This study presents a multi-timescale control strategy to deploy demand flexibilities of electric vehicles (EV) for providing system balancing and local congestion management by simultaneously ensuring economic benefits to participating actors. First, the EV charging problem from consumer, aggregator, and grid operator’s perspective is investigated. A hierarchical control architecture (HCA) comprising scheduling, coordinative, and adaptive layers is then designed to realize their coordinative goal. This is realized by integrating a multi-time scale control, which works from a day-ahead scheduling up to real-time adaptive control. The performance of the developed method is investigated with high EV penetration in a typical distributionmore » network. The simulation results demonstrates that HCA exploit EV flexibility to solve grid unbalancing and congestions with simultaneous maximization of economic benefits by ensuring EV participation to day-ahead, balancing, and regulation markets. For the given network configuration and pricing structure, HCA ensures the EV owners to get paid up to 5 times the cost they were paying without control.« less

Multi-time scale control of demand flexibility in smart distribution networks

DOE PAGES

Bhattarai, Bishnu; Myers, Kurt; Bak-Jensen, Birgitte; ...

2017-01-01

This study presents a multi-timescale control strategy to deploy demand flexibilities of electric vehicles (EV) for providing system balancing and local congestion management by simultaneously ensuring economic benefits to participating actors. First, the EV charging problem from consumer, aggregator, and grid operator’s perspective is investigated. A hierarchical control architecture (HCA) comprising scheduling, coordinative, and adaptive layers is then designed to realize their coordinative goal. This is realized by integrating a multi-time scale control, which works from a day-ahead scheduling up to real-time adaptive control. The performance of the developed method is investigated with high EV penetration in a typical distributionmore » network. The simulation results demonstrates that HCA exploit EV flexibility to solve grid unbalancing and congestions with simultaneous maximization of economic benefits by ensuring EV participation to day-ahead, balancing, and regulation markets. For the given network configuration and pricing structure, HCA ensures the EV owners to get paid up to 5 times the cost they were paying without control.« less

Space Radiation Transport Code Development: 3DHZETRN

NASA Technical Reports Server (NTRS)

Wilson, John W.; Slaba, Tony C.; Badavi, Francis F.; Reddell, Brandon D.; Bahadori, Amir A.

2015-01-01

The space radiation transport code, HZETRN, has been used extensively for research, vehicle design optimization, risk analysis, and related applications. One of the simplifying features of the HZETRN transport formalism is the straight-ahead approximation, wherein all particles are assumed to travel along a common axis. This reduces the governing equation to one spatial dimension allowing enormous simplification and highly efficient computational procedures to be implemented. Despite the physical simplifications, the HZETRN code is widely used for space applications and has been found to agree well with fully 3D Monte Carlo simulations in many circumstances. Recent work has focused on the development of 3D transport corrections for neutrons and light ions (Z < 2) for which the straight-ahead approximation is known to be less accurate. Within the development of 3D corrections, well-defined convergence criteria have been considered, allowing approximation errors at each stage in model development to be quantified. The present level of development assumes the neutron cross sections have an isotropic component treated within N explicit angular directions and a forward component represented by the straight-ahead approximation. The N = 1 solution refers to the straight-ahead treatment, while N = 2 represents the bi-directional model in current use for engineering design. The figure below shows neutrons, protons, and alphas for various values of N at locations in an aluminum sphere exposed to a solar particle event (SPE) spectrum. The neutron fluence converges quickly in simple geometry with N > 14 directions. The improved code, 3DHZETRN, transports neutrons, light ions, and heavy ions under space-like boundary conditions through general geometry while maintaining a high degree of computational efficiency. A brief overview of the 3D transport formalism for neutrons and light ions is given, and extensive benchmarking results with the Monte Carlo codes Geant4, FLUKA, and PHITS are provided for a variety of boundary conditions and geometries. Improvements provided by the 3D corrections are made clear in the comparisons. Developments needed to connect 3DHZETRN to vehicle design and optimization studies will be discussed. Future theoretical development will relax the forward plus isotropic interaction assumption to more general angular dependence.

Origin of the ahead of tsunami traveling ionospheric disturbances during Sumatra tsunami and offshore forecasting

NASA Astrophysics Data System (ADS)

Bagiya, Mala S.; Kherani, E. A.; Sunil, P. S.; Sunil, A. S.; Sunda, S.; Ramesh, D. S.

2017-07-01

The presence of ionospheric disturbances associated with Sumatra 2004 tsunami that propagated ahead of tsunami itself has previously been identified. However, their origin remains unresolved till date. Focusing on their origin mechanism, we document these ionospheric disturbances referred as Ahead of tsunami Traveling Ionospheric Disturbances (ATIDs). Using total electron content (TEC) data from GPS Aided GEO Augmented Navigation GPS receivers located near the Indian east coast, we first confirm the ATIDs presence in TEC that appear 90 min ahead of the arrival of tsunami at the Indian east coast. We propose here a simulation study based on tsunami-atmospheric-ionospheric coupling that considers tsunamigenic acoustic gravity waves (AGWs) to excite these disturbances. We explain the ATIDs generation based on the dissipation of transverse mode of the primary AGWs. The simulation corroborates the excitation of ATIDs with characteristics similar to the observations. Therefore, we offer an alternative theoretical tool to monitor the offshore ATIDs where observations are either rare or not available and could be potentially important for the tsunami early warning.

Optimizing the Operation of Windfarms, Energy Storage and Flexible Loads in Modern Power Systems and Deregulated Electricity Markets

NASA Astrophysics Data System (ADS)

Dar, Zamiyad

The amount of wind energy in power systems is increasing at a significant rate. With this increased penetration, there are certain problems associated with the operation of windfarms which need careful attention. In the operations side, the wake effects of upstream wind turbines on downstream wind turbines can cause a reduction in the total generated power of a windfarm. On the market side, the fluctuation of real-time prices can make the operation of windfarms less profitable. Similarly, the intermittent nature of wind power prevents the windfarms from participating in the day-ahead and forward markets. On the system side, the volatile nature of wind speeds is also an obstacle for windfarms to provide frequency regulation to the system. In this thesis, we address these issues and optimize the operation of windfarms in power systems and deregulated electricity markets. First, the total power generation in a windfarm is maximized by using yaw angle of wind turbines as a control variable. We extend the existing wake models to include the effects of yaw misalignment and wake deflection of wind turbines. A numerical study is performed to find the optimal values of induction factor and yaw misalignment angle of wind turbines in a single row of a windfarm for achieving the maximum total power with wake effects. The numerical study shows that the maximum power is achieved by keeping the induction factor close to 1/3 and only changing the yaw angle to deflect the wake. We then propose a Dynamic Programming Framework (DPF) to maximize the total power production of a windfarm using yaw angle as the control variable. We compare the windfarm efficiency achieved with our DPF with the efficiency values obtained through greedy control strategy and induction factor optimization. We also extend our expressions to a windfarm with multiple rows and columns of turbines and perform simulations on the 3x3 and 4x4 grid topologies. Our results show that the optimal induction factor for most turbines is quite close to 1/3 and yaw angle acts as the dominant optimization variable. In the next part of this dissertation, a system comprising of a windfarm and energy storage operating in real-time electricity markets is studied. An Energy-balancing Threshold Price (ETP) policy is proposed to maximize the revenue of a windfarm with on-site storage. We propose and analyze a scheme for a windfarm to store or sell energy based on a threshold price. The threshold price is calculated based on long-term distributions of the electricity price and wind power generation processes, and is chosen so as to balance the energy flows in and out of the storage-equipped windfarm. It is also shown mathematically that the proposed policy is optimal in terms of the long-term revenue generated. Comparing it with the optimal policy that has knowledge of the future, we observe that the revenue obtained by the proposed ETP policy is approximately 90% of the maximum attainable revenue at a storage capacity of 10-15 times the power rating of the windfarm. The intermittent nature of wind power is a hindrance to the efficient participation of windfarms in the day-ahead and forward electricity markets. In this regard, a flexible forward contract is proposed in this dissertation which allows the windfarms to enter into a forward contract with flexible load with an option to deviate from the contracted amount of power. Using such a flexible contract would allow the windfarms to supply more or less than the contracted amount of power in case of unexpected wind conditions or real-time prices. We also propose models for forecasting wind power and real-time electricity prices. The comparison between the proposed contracting framework and a simple fixed contract (currently existing in the market) for different levels of flexibility and load shows that there is a net gain in windfarm revenues, if the transaction price of the two contracts are set equal. Lastly, we present and analyze distributed control schemes for frequency regulation in a smart grid using energy storage, wind generators, demand response and conventional generators while having no communication or data sharing between them. We also propose a novel control scheme for frequency support by energy storage in which the power output of energy storage changes proportionally with the reduction in its available energy. The application of the proposed control schemes indicates an improvement in system frequency characteristics, when there is a sudden net loss of generation.

A modified priority list-based MILP method for solving large-scale unit commitment problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ke, Xinda; Lu, Ning; Wu, Di

This paper studies the typical pattern of unit commitment (UC) results in terms of generator’s cost and capacity. A method is then proposed to combine a modified priority list technique with mixed integer linear programming (MILP) for UC problem. The proposed method consists of two steps. At the first step, a portion of generators are predetermined to be online or offline within a look-ahead period (e.g., a week), based on the demand curve and generator priority order. For the generators whose on/off status is predetermined, at the second step, the corresponding binary variables are removed from the UC MILP problemmore » over the operational planning horizon (e.g., 24 hours). With a number of binary variables removed, the resulted problem can be solved much faster using the off-the-shelf MILP solvers, based on the branch-and-bound algorithm. In the modified priority list method, scale factors are designed to adjust the tradeoff between solution speed and level of optimality. It is found that the proposed method can significantly speed up the UC problem with minor compromise in optimality by selecting appropriate scale factors.« less

Ahead of the Times in Murfreesboro.

ERIC Educational Resources Information Center

Jones, John Hodge

1994-01-01

Murfreesboro (Tennessee) City Schools extended the school day and year with no additional cost to taxpayers. Implementation was arduous and faced great resistance. Eventual solution made better use of the school system's capital assets and human resources, rearranged Chapter 1 money, required additional business support and parents' willingness to…

Private Higher Education: The Job Ahead.

ERIC Educational Resources Information Center

American Association of Presidents of Independent Colleges and Universities, Rockford, IL.

Speeches from the 1978 annual meeting of the American Association of Presidents of Independent Colleges and Universities are presented. Contents of the report are as follows: "Earning Respect" by Drew S. Days, III.; "The College in Controversy: Government Relations 1978"; "Until the Year 2000: Reflections of a Retired…

Overcoming Obstacles, Optimizing Opportunities: State Policies to Increase Postsecondary Attainment for Low-Skilled Adults

ERIC Educational Resources Information Center

Duke, Amy-Ellen; Strawn, Julie

2008-01-01

Just as American business and industry need workers with higher skills to compete in a global economy, workers need higher skills to get ahead. This convergence presents an opportunity for states to work with their community colleges and other key partners to help business and industry compete and entry-level workers advance to higher-paying jobs.…

Multi-stage flash degaser

DOEpatents

Rapier, Pascal M.

1982-01-01

A multi-stage flash degaser (18) is incorporated in an energy conversion system (10) having a direct-contact, binary-fluid heat exchanger to remove essentially all of the noncondensable gases from geothermal brine ahead of the direct-contact binary-fluid heat exchanger (22) in order that the heat exchanger (22) and a turbine (48) and condenser (32) of the system (10) can operate at optimal efficiency.

Short time ahead wind power production forecast

NASA Astrophysics Data System (ADS)

Sapronova, Alla; Meissner, Catherine; Mana, Matteo

2016-09-01

An accurate prediction of wind power output is crucial for efficient coordination of cooperative energy production from different sources. Long-time ahead prediction (from 6 to 24 hours) of wind power for onshore parks can be achieved by using a coupled model that would bridge the mesoscale weather prediction data and computational fluid dynamics. When a forecast for shorter time horizon (less than one hour ahead) is anticipated, an accuracy of a predictive model that utilizes hourly weather data is decreasing. That is because the higher frequency fluctuations of the wind speed are lost when data is averaged over an hour. Since the wind speed can vary up to 50% in magnitude over a period of 5 minutes, the higher frequency variations of wind speed and direction have to be taken into account for an accurate short-term ahead energy production forecast. In this work a new model for wind power production forecast 5- to 30-minutes ahead is presented. The model is based on machine learning techniques and categorization approach and using the historical park production time series and hourly numerical weather forecast.

Season-ahead Drought Forecast Models for the Lower Colorado River Authority in Texas

NASA Astrophysics Data System (ADS)

Block, P. J.; Zimmerman, B.; Grzegorzewski, M.; Watkins, D. W., Jr.; Anderson, R.

2014-12-01

The Lower Colorado River Authority (LCRA) in Austin, Texas, manages the Highland Lakes reservoir system in Central Texas, a series of six lakes on the Lower Colorado River. This system provides water to approximately 1.1 million people in Central Texas, supplies hydropower to a 55-county area, supports rice farming along the Texas Gulf Coast, and sustains in-stream flows in the Lower Colorado River and freshwater inflows to Matagorda Bay. The current, prolonged drought conditions are severely taxing the LCRA's system, making allocation and management decisions exceptionally challenging, and affecting the ability of constituents to conduct proper planning. In this work, we further develop and evaluate season-ahead statistical streamflow and precipitation forecast models for integration into LCRA decision support models. Optimal forecast lead time, predictive skill, form, and communication are all considered.

STS-89 Day 06 Highlights

NASA Technical Reports Server (NTRS)

1998-01-01

On this sixth day of the STS-89 mission, the flight crew, Cmdr. Terrence W. Wilcutt, Pilot Frank Edwards, and Mission Specialists Michael P. Anderson, James F. Reilly, Bonnie J. Dunbar, Salizhan Shakirovich Sharipov, David A. Wolf and Andrew S.W. Thomas, are interviewed by John Holliman of Cable News Network (CNN) and Russian news media. The crew discuss the progress of the mission and activities that lie ahead for Mir crew member Andy Thomas.

A 30-day-ahead forecast model for grass pollen in north London, United Kingdom.

PubMed

Smith, Matt; Emberlin, Jean

2006-03-01

A 30-day-ahead forecast method has been developed for grass pollen in north London. The total period of the grass pollen season is covered by eight multiple regression models, each covering a 10-day period running consecutively from 21 May to 8 August. This means that three models were used for each 30-day forecast. The forecast models were produced using grass pollen and environmental data from 1961 to 1999 and tested on data from 2000 and 2002. Model accuracy was judged in two ways: the number of times the forecast model was able to successfully predict the severity (relative to the 1961-1999 dataset as a whole) of grass pollen counts in each of the eight forecast periods on a scale of 1 to 4; the number of times the forecast model was able to predict whether grass pollen counts were higher or lower than the mean. The models achieved 62.5% accuracy in both assessment years when predicting the relative severity of grass pollen counts on a scale of 1 to 4, which equates to six of the eight 10-day periods being forecast correctly. The models attained 87.5% and 100% accuracy in 2000 and 2002, respectively, when predicting whether grass pollen counts would be higher or lower than the mean. Attempting to predict pollen counts during distinct 10-day periods throughout the grass pollen season is a novel approach. The models also employed original methodology in the use of winter averages of the North Atlantic Oscillation to forecast 10-day means of allergenic pollen counts.

An adaptive critic-based scheme for consensus control of nonlinear multi-agent systems

NASA Astrophysics Data System (ADS)

Heydari, Ali; Balakrishnan, S. N.

2014-12-01

The problem of decentralised consensus control of a network of heterogeneous nonlinear systems is formulated as an optimal tracking problem and a solution is proposed using an approximate dynamic programming based neurocontroller. The neurocontroller training comprises an initial offline training phase and an online re-optimisation phase to account for the fact that the reference signal subject to tracking is not fully known and available ahead of time, i.e., during the offline training phase. As long as the dynamics of the agents are controllable, and the communication graph has a directed spanning tree, this scheme guarantees the synchronisation/consensus even under switching communication topology and directed communication graph. Finally, an aerospace application is selected for the evaluation of the performance of the method. Simulation results demonstrate the potential of the scheme.

Political Skill as Moderator of Personality--Job Performance Relationships in Socioanalytic Theory: Test of the Getting Ahead Motive in Automobile Sales

ERIC Educational Resources Information Center

Blickle, Gerhard; Wendel, Stephanie; Ferris, Gerald R.

2010-01-01

Based on the socioanalytic perspective of performance prediction ([Hogan, 1991] and [Hogan and Shelton, 1998]), this study tests whether the motive to get ahead produces greater performance when interactively combined with social effectiveness. Specifically, we investigated whether interactions of the five-factor model constructs of extraversion…

Mathematic simulation of mining company’s power demand forecast (by example of “Neryungri” coal strip mine)

NASA Astrophysics Data System (ADS)

Antonenkov, D. V.; Solovev, D. B.

2017-10-01

The article covers the aspects of forecasting and consideration of the wholesale market environment in generating the power demand forecast. Major mining companies that operate in conditions of the present day power market have to provide a reliable energy demand request for a certain time period ahead, thus ensuring sufficient reduction of financial losses associated with deviations of the actual power demand from the expected figures. Normally, under the power supply agreement, the consumer is bound to provide a per-month and per-hour request annually. It means that the consumer has to generate one-month-ahead short-term and medium-term hourly forecasts. The authors discovered that empiric distributions of “Yakutugol”, Holding Joint Stock Company, power demand belong to the sustainable rank parameter H-distribution type used for generating forecasts based on extrapolation of such distribution parameters. For this reason they justify the need to apply the mathematic rank analysis in short-term forecasting of the contracted power demand of “Neryungri” coil strip mine being a component of the technocenosis-type system of the mining company “Yakutugol”, Holding JSC.

23 CFR 635.102 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... to conduct business in a particular State. A State is as defined in 23 U.S.C. 101. Force account... the actual cost of labor, equipment, and materials furnished and consideration for overhead and profit... contractor a certain amount of money for each day identified critical work is completed ahead of schedule and...

78 FR 31916 - Increasing Market and Planning Efficiency Through Improved Software; Supplemental Agenda Notice

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-28

... Market and Planning Efficiency Through Improved Software; Supplemental Agenda Notice Take notice that... for increasing real-time and day-ahead market efficiency through improved software. A detailed agenda..., the software industry, government, research centers and academia and is intended to build on the...

17 CFR Appendix F to Part 43 - Initial Appropriate Minimum Block Sizes by Asset Class for Block Trades and Large Notional Off...

Code of Federal Regulations, 2014 CFR

2014-04-01

.... Light Sweet Crude Oil (NYMEX) 50,000 bbl. Live Cattle (CME) NO BLOCKS. Mid-Columbia Day-Ahead Off-Peak.... Sugar #11 (ICE and NYMEX) 5,000 metric tons. Sugar #16 (ICE) NO BLOCKS. Temperature Index (CME) 400...

Keep Your Windows Open and Mirrors Polished: On Quality Education in a Changing America

ERIC Educational Resources Information Center

Katz, Lucinda Lee

2011-01-01

Lucinda Lee Katz, head of Marin Country Day School (California), received the 2009 NAIS Diversity Leadership Award. This article presents an edited excerpt of her acceptance speech. In this speech, she outlines what is necessary to move school communities ahead in one's diversity work.

Long-term sensorimotor and therapeutical effects of a mild regime of prism adaptation in spatial neglect. A double-blind RCT essay.

PubMed

Rode, G; Lacour, S; Jacquin-Courtois, S; Pisella, L; Michel, C; Revol, P; Alahyane, N; Luauté, J; Gallagher, S; Halligan, P; Pélisson, D; Rossetti, Y

2015-04-01

Spatial neglect (SN) is commonly associated with poor functional outcome. Adaptation to a rightward optical deviation of vision has been shown to benefit to SN rehabilitation. The neurophysiological foundations and the optimal modalities of prism adaptation (PA) therapy however remain to be validated. This study is aimed at exploring the long-term sensory-motor, cognitive and functional effects produced by weekly PA sessions over a period of four weeks. A double-blind, monocentric randomized and controlled trial (RCT) was carried out. Twenty patients with left SN secondary to stroke were included, 10 in the "prism" group and 10 in the "control" group. The sensory-motor effects of PA were evaluated by measurement of manual and visual straight-ahead, and also by precision of pointing without visual feedback before and after each PA session. The functional independence measure (FIM) was evaluated before and at 1, 3 and 6 months after PA, while SN severity was assessed using the Behavioural Inattention Test (BIT) before and 6 months after PA. Before the intervention, only manual straight-ahead pointing constituted a reproducible sensory-motor measurement. During prism exposure, a questionnaire showed that not a single patient were aware of the direct effects of optical deviation on pointing movement performance. The sensory-motor after-effects produced by the PA produced a more rapid reduction of the rightward manual straight-ahead, which was secondarily followed by visual straight-ahead. These sensory-motor effects helped to clarify the action mechanisms of PA on SN. At the conclusion of the 6-month follow-up, the two groups showed similar improvement, indicating that a weekly PA session over 4 weeks was not sufficient to produce long-term functional benefit. This improvement was correlated with the evolution of visual straight-ahead, which can be proposed as a marker for patients outcome. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

[Complexity and its integrative effects of the time lags of environment factors affecting Larix gmelinii stem sap flow].

PubMed

Wang, Hui-Mei; Sun, Wei; Zu, Yuan-Gang; Wang, Wen-Jie

2011-12-01

Based on the one-year (2005) observations with a frequency of half hour on the stem sap flow of Larix gmelinii plantation trees planted in 1969 and the related environmental factors air humidity (RH), air temperature (T(air)), photosynthetic components active radiation (PAR), soil temperature (T(soil)), and soil moisture (TDR), principal analysis (PCA) and correction analysis were made on the time lag effect of the stem flow in different seasons (26 days of each season) and in a year via dislocation analysis, with the complexity and its integrative effects of the time lags of environment factors affecting the stem sap flow approached. The results showed that in different seasons and for different environmental factors, the time lag effect varied obviously. In general, the time lag of PAR was 0.5-1 hour ahead of sap flow, that of T(air) and RH was 0-2 hours ahead of or behind the sap flow, and the time lags of T(soil) and TDR were much longer or sometimes undetectable. Because of the complexity of the time lags, no evident improvements were observed in the linear correlations (R2, slope, and intercept) when the time lags based on short-term (20 days) data were used to correct the time lags based on whole year data. However, obvious improvements were found in the standardized and non-standardized correlation coefficients in stepwise multiple regressions, i.e., the time lag corrections could improve the effects of RH, but decreased the effects of PAR, T(air), and T(soil). PCA could be used to simplify the complexity. The first and the second principal components could stand for over 75% information of all the environmental factors in different seasons and in whole year. The time lags of both the first and the second principal components were 1-1.5 hours in advance of the sap flow, except in winter (no time lag effect).

Probabilistic objective functions for sensor management

NASA Astrophysics Data System (ADS)

Mahler, Ronald P. S.; Zajic, Tim R.

2004-08-01

This paper continues the investigation of a foundational and yet potentially practical basis for control-theoretic sensor management, using a comprehensive, intuitive, system-level Bayesian paradigm based on finite-set statistics (FISST). In this paper we report our most recent progress, focusing on multistep look-ahead -- i.e., allocation of sensor resources throughout an entire future time-window. We determine future sensor states in the time-window using a "probabilistically natural" sensor management objective function, the posterior expected number of targets (PENT). This objective function is constructed using a new "maxi-PIMS" optimization strategy that hedges against unknowable future observation-collections. PENT is used in conjuction with approximate multitarget filters: the probability hypothesis density (PHD) filter or the multi-hypothesis correlator (MHC) filter.

Integrating Solar Power onto the Electric Grid - Bridging the Gap between Atmospheric Science, Engineering and Economics

NASA Astrophysics Data System (ADS)

Ghonima, M. S.; Yang, H.; Zhong, X.; Ozge, B.; Sahu, D. K.; Kim, C. K.; Babacan, O.; Hanna, R.; Kurtz, B.; Mejia, F. A.; Nguyen, A.; Urquhart, B.; Chow, C. W.; Mathiesen, P.; Bosch, J.; Wang, G.

2015-12-01

One of the main obstacles to high penetrations of solar power is the variable nature of solar power generation. To mitigate variability, grid operators have to schedule additional reliability resources, at considerable expense, to ensure that load requirements are met by generation. Thus despite the cost of solar PV decreasing, the cost of integrating solar power will increase as penetration of solar resources onto the electric grid increases. There are three principal tools currently available to mitigate variability impacts: (i) flexible generation, (ii) storage, either virtual (demand response) or physical devices and (iii) solar forecasting. Storage devices are a powerful tool capable of ensuring smooth power output from renewable resources. However, the high cost of storage is prohibitive and markets are still being designed to leverage their full potential and mitigate their limitation (e.g. empty storage). Solar forecasting provides valuable information on the daily net load profile and upcoming ramps (increasing or decreasing solar power output) thereby providing the grid advance warning to schedule ancillary generation more accurately, or curtail solar power output. In order to develop solar forecasting as a tool that can be utilized by the grid operators we identified two focus areas: (i) develop solar forecast technology and improve solar forecast accuracy and (ii) develop forecasts that can be incorporated within existing grid planning and operation infrastructure. The first issue required atmospheric science and engineering research, while the second required detailed knowledge of energy markets, and power engineering. Motivated by this background we will emphasize area (i) in this talk and provide an overview of recent advancements in solar forecasting especially in two areas: (a) Numerical modeling tools for coastal stratocumulus to improve scheduling in the day-ahead California energy market. (b) Development of a sky imager to provide short term forecasts (0-20 min ahead) to improve optimization and control of equipment on distribution feeders with high penetration of solar. Leveraging such tools that have seen extensive use in the atmospheric sciences supports the development of accurate physics-based solar forecast models. Directions for future research are also provided.

Local TEC modelling and forecasting using neural networks

NASA Astrophysics Data System (ADS)

Tebabal, A.; Radicella, S. M.; Nigussie, M.; Damtie, B.; Nava, B.; Yizengaw, E.

2018-07-01

Modelling the Earth's ionospheric characteristics is the focal task for the ionospheric community to mitigate its effect on the radio communication, and satellite navigation. However, several aspects of modelling are still challenging, for example, the storm time characteristics. This paper presents modelling efforts of TEC taking into account solar and geomagnetic activity, time of the day and day of the year using neural networks (NNs) modelling technique. The NNs have been designed with GPS-TEC measured data from low and mid-latitude GPS stations. The training was conducted using the data obtained for the period from 2011 to 2014. The model prediction accuracy was evaluated using data of year 2015. The model results show that diurnal and seasonal trend of the GPS-TEC is well reproduced by the model for the two stations. The seasonal characteristics of GPS-TEC is compared with NN and NeQuick 2 models prediction when the latter one is driven by the monthly average value of solar flux. It is found that NN model performs better than the corresponding NeQuick 2 model for low latitude region. For the mid-latitude both NN and NeQuick 2 models reproduce the average characteristics of TEC variability quite successfully. An attempt of one day ahead forecast of TEC at the two locations has been made by introducing as drivers previous day solar flux and geomagnetic index values. The results show that a reasonable day ahead forecast of local TEC can be achieved.

Local TEC Modelling and Forecasting using Neural Networks

NASA Astrophysics Data System (ADS)

Tebabal, A.; Radicella, S. M.; Nigussie, M.; Damtie, B.; Nava, B.; Yizengaw, E.

2017-12-01

Abstract Modelling the Earth's ionospheric characteristics is the focal task for the ionospheric community to mitigate its effect on the radio communication, satellite navigation and technologies. However, several aspects of modelling are still challenging, for example, the storm time characteristics. This paper presents modelling efforts of TEC taking into account solar and geomagnetic activity, time of the day and day of the year using neural networks (NNs) modelling technique. The NNs have been designed with GPS-TEC measured data from low and mid-latitude GPS stations. The training was conducted using the data obtained for the period from 2011 to 2014. The model prediction accuracy was evaluated using data of year 2015. The model results show that diurnal and seasonal trend of the GPS-TEC is well reproduced by the model for the two stations. The seasonal characteristics of GPS-TEC is compared with NN and NeQuick 2 models prediction when the latter one is driven by the monthly average value of solar flux. It is found that NN model performs better than the corresponding NeQuick 2 model for low latitude region. For the mid-latitude both NN and NeQuick 2 models reproduce the average characteristics of TEC variability quite successfully. An attempt of one day ahead forecast of TEC at the two locations has been made by introducing as driver previous day solar flux and geomagnetic index values. The results show that a reasonable day ahead forecast of local TEC can be achieved.

Power management of remote microgrids considering battery lifetime

NASA Astrophysics Data System (ADS)

Chalise, Santosh

Currently, 20% (1.3 billion) of the world's population still lacks access to electricity and many live in remote areas where connection to the grid is not economical or practical. Remote microgrids could be the solution to the problem because they are designed to provide power for small communities within clearly defined electrical boundaries. Reducing the cost of electricity for remote microgrids can help to increase access to electricity for populations in remote areas and developing countries. The integration of renewable energy and batteries in diesel based microgrids has shown to be effective in reducing fuel consumption. However, the operational cost remains high due to the low lifetime of batteries, which are heavily used to improve the system's efficiency. In microgrid operation, a battery can act as a source to augment the generator or a load to ensure full load operation. In addition, a battery increases the utilization of PV by storing extra energy. However, the battery has a limited energy throughput. Therefore, it is required to provide balance between fuel consumption and battery lifetime throughput in order to lower the cost of operation. This work presents a two-layer power management system for remote microgrids. First layer is day ahead scheduling, where power set points of dispatchable resources were calculated. Second layer is real time dispatch, where schedule set points from the first layer are accepted and resources are dispatched accordingly. A novel scheduling algorithm is proposed for a dispatch layer, which considers the battery lifetime in optimization and is expected to reduce the operational cost of the microgrid. This method is based on a goal programming approach which has the fuel and the battery wear cost as two objectives to achieve. The effectiveness of this method was evaluated through a simulation study of a PV-diesel hybrid microgrid using deterministic and stochastic approach of optimization.

Terrorist Networks, Money Laundering Schemes, and Nation Stability

DTIC Science & Technology

2010-06-01

Stabilization Initiative  $106,400,000.00 to recon/stab  Seven countries per fiscal year  American Academy of Actuaries insured losses (relatively...Indicators  Political Instability Task Force Report  Mathematical Model (Linear Program Optimization)  Develop a value system (utility theory) to...deeper ahead. 47 LIST OF REFERENCES American Academy of Actuaries (Finance Data). Retrieved September 20, 2009, from, http://www.actuary.org

Development and validation of a protocol for optimizing the use of paraffin blocks in molecular epidemiological studies: The example from the HPV-AHEAD study.

PubMed

Mena, Marisa; Lloveras, Belen; Tous, Sara; Bogers, Johannes; Maffini, Fausto; Gangane, Nitin; Kumar, Rekha Vijay; Somanathan, Thara; Lucas, Eric; Anantharaman, Devasena; Gheit, Tarik; Castellsagué, Xavier; Pawlita, Michael; de Sanjosé, Silvia; Alemany, Laia; Tommasino, Massimo

2017-01-01

Worldwide use of formalin-fixed paraffin-embedded blocks (FFPE) is extensive in diagnosis and research. Yet, there is a lack of optimized/standardized protocols to process the blocks and verify the quality and presence of the targeted tissue. In the context of an international study on head and neck cancer (HNC)-HPV-AHEAD, a standardized protocol for optimizing the use of FFPEs in molecular epidemiology was developed and validated. First, a protocol for sectioning the FFPE was developed to prevent cross-contamination and distributed between participating centers. Before processing blocks, all sectioning centers underwent a quality control to guarantee a satisfactory training process. The first and last sections of the FFPEs were used for histopathological assessment. A consensus histopathology evaluation form was developed by an international panel of pathologists and evaluated for four indicators in a pilot analysis in order to validate it: 1) presence/type of tumor tissue, 2) identification of other tissue components that could affect the molecular diagnosis and 3) quality of the tissue. No HPV DNA was found in sections from empty FFPE generated in any histology laboratories of HPV-AHEAD consortium and all centers passed quality assurance for processing after quality control. The pilot analysis to validate the histopathology form included 355 HNC cases. The form was filled by six pathologists and each case was randomly assigned to two of them. Most samples (86%) were considered satisfactory. Presence of >50% of invasive carcinoma was observed in all sections of 66% of cases. Substantial necrosis (>50%) was present in <2% of samples. The concordance for the indicators targeted to validate the histopathology form was very high (kappa > 0.85) between first and last sections and fair to high between pathologists (kappa/pabak 0.21-0.72). The protocol allowed to correctly process without signs of contamination all FFPE of the study. The histopathology evaluation of the cases assured the presence of the targeted tissue, identified the presence of other tissues that could disturb the molecular diagnosis and allowed the assessment of tissue quality.

Advanced Intelligent System Application to Load Forecasting and Control for Hybrid Electric Bus

NASA Technical Reports Server (NTRS)

Momoh, James; Chattopadhyay, Deb; Elfayoumy, Mahmoud

1996-01-01

The primary motivation for this research emanates from providing a decision support system to the electric bus operators in the municipal and urban localities which will guide the operators to maintain an optimal compromise among the noise level, pollution level, fuel usage etc. This study is backed up by our previous studies on study of battery characteristics, permanent magnet DC motor studies and electric traction motor size studies completed in the first year. The operator of the Hybrid Electric Car must determine optimal power management schedule to meet a given load demand for different weather and road conditions. The decision support system for the bus operator comprises three sub-tasks viz. forecast of the electrical load for the route to be traversed divided into specified time periods (few minutes); deriving an optimal 'plan' or 'preschedule' based on the load forecast for the entire time-horizon (i.e., for all time periods) ahead of time; and finally employing corrective control action to monitor and modify the optimal plan in real-time. A fully connected artificial neural network (ANN) model is developed for forecasting the kW requirement for hybrid electric bus based on inputs like climatic conditions, passenger load, road inclination, etc. The ANN model is trained using back-propagation algorithm employing improved optimization techniques like projected Lagrangian technique. The pre-scheduler is based on a Goal-Programming (GP) optimization model with noise, pollution and fuel usage as the three objectives. GP has the capability of analyzing the trade-off among the conflicting objectives and arriving at the optimal activity levels, e.g., throttle settings. The corrective control action or the third sub-task is formulated as an optimal control model with inputs from the real-time data base as well as the GP model to minimize the error (or deviation) from the optimal plan. These three activities linked with the ANN forecaster proving the output to the GP model which in turn produces the pre-schedule of the optimal control model. Some preliminary results based on a hypothetical test case will be presented for the load forecasting module. The computer codes for the three modules will be made available fe adoption by bus operating agencies. Sample results will be provided using these models. The software will be a useful tool for supporting the control systems for the Electric Bus project of NASA.

Late effects awareness website for pediatric survivors of acute lymphocytic leukemia

PubMed Central

Navarro, Ana; Klonoff, Elizabeth A.

2018-01-01

Objectives Every day 43 children are newly diagnosed with cancer. Fortunately, almost 90% of these childhood cancer patients will survive. However, 60–90% of these survivors will experience late effects, health problems that occur months or years after treatment has ended. Late effects could occur as a result of the disease, its treatment, and patient-related factors. The two main objectives of this research are to: 1) Examine the existence of all web-based resources for childhood cancer survivors with acute lymphocytic leukemia which focus on medical and psychological aspects of late effects, and 2) Create an innovative website specifically designed to fill this void. Materials and methods A systematic literature review, followed by input from >20 different organizations, resulted in the creation of LEAP3 AHEAD (Late Effects Awareness for Patients, Physicians and the Public; Advancing Health and Eliminating All Disparities), a multi-dimensional website centering on late effects. Results An extensive review revealed 14 pediatric cancer websites, none of which focused exclusively on late effects. LEAP3 AHEAD is the first interactive website for acute lympocytic leukemia childhood cancer survivors and families, as well as physicians, and the public to: a) increase awareness about risks, detection, diagnosis, treatment, and prevention of medical and psychological late effects, b) provide suggestions to successfully reintegrate into schools, careers, and socially, and c) present opportunities including camps, scholarships, and pet therapy programs. Conclusion LEAP3 AHEAD is the first national website to provide a comprehensive, accessible, affordable, and multi-dimensional resource for pediatricians, internists, nurse practitioners, psychologists, survivors and their families, as well as the public about late effects. PMID:29451924

3D Space Radiation Transport in a Shielded ICRU Tissue Sphere

NASA Technical Reports Server (NTRS)

Wilson, John W.; Slaba, Tony C.; Badavi, Francis F.; Reddell, Brandon D.; Bahadori, Amir A.

2014-01-01

A computationally efficient 3DHZETRN code capable of simulating High Charge (Z) and Energy (HZE) and light ions (including neutrons) under space-like boundary conditions with enhanced neutron and light ion propagation was recently developed for a simple homogeneous shield object. Monte Carlo benchmarks were used to verify the methodology in slab and spherical geometry, and the 3D corrections were shown to provide significant improvement over the straight-ahead approximation in some cases. In the present report, the new algorithms with well-defined convergence criteria are extended to inhomogeneous media within a shielded tissue slab and a shielded tissue sphere and tested against Monte Carlo simulation to verify the solution methods. The 3D corrections are again found to more accurately describe the neutron and light ion fluence spectra as compared to the straight-ahead approximation. These computationally efficient methods provide a basis for software capable of space shield analysis and optimization.

Obesity susceptibility loci and dietary intake in the Look AHEAD Trial.

PubMed

McCaffery, Jeanne M; Papandonatos, George D; Peter, Inga; Huggins, Gordon S; Raynor, Hollie A; Delahanty, Linda M; Cheskin, Lawrence J; Balasubramanyam, Ashok; Wagenknecht, Lynne E; Wing, Rena R

2012-06-01

Genome-wide association studies (GWAS) have identified consistent associations with obesity. However, the mechanisms remain unclear. The objective was to determine the association between obesity susceptibility loci and dietary intake. The association of GWAS-identified obesity risk alleles (FTO, MC4R, SH2B1, BDNF, INSIG2, TNNI3K, NISCH-STAB1, MTIF3, MAP2K5, QPCTL/GIPR, and PPARG) with dietary intake, measured through food-frequency questionnaires, was investigated in 2075 participants from the Look AHEAD (Action for Health in Diabetes) clinical trial. We adjusted for age, sex, population stratification, and study site. Obesity risk alleles at FTO rs1421085 significantly predicted more eating episodes per day (P = 0.001)-an effect that persisted after adjustment for body weight (P = 0.004). Risk variants within BDNF were significantly associated with more servings from the dairy product and the meat, eggs, nuts, and beans food groups (P ≤ 0.004). The risk allele at SH2B1 rs4788099 was significantly associated with more servings of dairy products (P = 0.001), whereas the risk allele at TNNI3K rs1514176 was significantly associated with a lower percentage of energy from protein (P = 0.002). These findings suggest that obesity risk loci may affect the pattern and content of food consumption among overweight or obese individuals with type 2 diabetes. The Look AHEAD Genetic Ancillary Study was registered at clinicaltrials.gov as NCT01270763 and the Look AHEAD study as NCT00017953.

Patient navigation based on predictive modeling decreases no-show rates in cancer care.

PubMed

Percac-Lima, Sanja; Cronin, Patrick R; Ryan, David P; Chabner, Bruce A; Daly, Emily A; Kimball, Alexandra B

2015-05-15

Patient adherence to appointments is key to improving outcomes in health care. "No-show" appointments contribute to suboptimal resource use. Patient navigation and telephone reminders have been shown to improve cancer care and adherence, particularly in disadvantaged populations, but may not be cost-effective if not targeted at the appropriate patients. In 5 clinics within a large academic cancer center, patients who were considered to be likely (the top 20th percentile) to miss a scheduled appointment without contacting the clinic ahead of time ("no-shows") were identified using a predictive model and then randomized to an intervention versus a usual-care group. The intervention group received telephone calls from a bilingual patient navigator 7 days before and 1 day before the appointment. Over a 5-month period, of the 40,075 appointments scheduled, 4425 patient appointments were deemed to be at high risk of a "no-show" event. After the patient navigation intervention, the no-show rate in the intervention group was 10.2% (167 of 1631), compared with 17.5% in the control group (280 of 1603) (P<.001). Reaching a patient or family member was associated with a significantly lower no-show rate (5.9% and 3.0%, respectively; P<.001 and .006, respectively) compared with leaving a message (14.7%: P = .117) or no contact (no-show rate, 21.6%: P = .857). Telephone navigation targeted at those patients predicted to be at high risk of visit nonadherence was found to effectively and substantially improve patient adherence to cancer clinic appointments. Further studies are needed to determine the long-term impact on patient outcomes, but short-term gains in the optimization of resources can be recognized immediately. © 2015 American Cancer Society.

78 FR 53712 - Surface Transportation Project Delivery Program Application Requirements

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-30

... the 21st Century Act (MAP-21), which converted the Surface Transportation Project Delivery Pilot... signed into law the Moving Ahead for Progress in the 21st Century Act (MAP-21), Public Law 112-141, 126... days from the date of MAP-21's enactment (October 1, 2012)--the regulations concerning the information...

Major Topics of School Business Management.

ERIC Educational Resources Information Center

Clark, James E., Ed.; Hertz, Karl V., Ed.

Thirteen articles on major topics facing school business officials in the 1980s are presented in this book. The titles and their authors are (1) "The Pursuit of Equity in Financing Public Education," by R. Craig Wood, Helene B. Jones, and William L. Riley; (2) "Facilities: Major Issues Ahead," by C. William Day; (3)…

2013 Inaugural Parade

NASA Image and Video Library

2013-01-21

Members of The U.S. Army Band, Herald Trumpets Ensemble, look to make sure their feet are on markers in front of the Preidential viewing stand ahead of the 2013 Inauguration Parade, Monday, Jan. 21, 2013 in Washington. President Barack Obama was sworn-in as the nation's 44th President earlier in the day. Photo Credt: (NASA/Bill Ingalls)

Day Care Facts.

ERIC Educational Resources Information Center

Hart, Annie L.; And Others

The need for child care will continue to increase in the decade ahead because of: (1) a growing number of children aged five and younger, (2) the accelerating trend in employment of mothers, (3) increased emphasis on providing child care services for welfare mothers who desire to work, and (4) widespread awareness that a child's early years are of…

77 FR 73027 - Combined Notice of Filings #2

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-07

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission Combined Notice of Filings 2 Take notice....13(a)(2)(iii: Revisions to the PJM OATT & OA re Day-ahead and Balancing Operating Reserves to be... Electric Company submits tariff filing per 35.13(a)(2)(iii: Western IA November 2012 Biannual Filing to be...

Underway Recovery Test 6 (URT-6) - Day 6 Activities

NASA Image and Video Library

2018-01-22

During Underway Recovery Test 6, Kennedy Space Center's NASA Recovery Team spent a week aboard the USS Anchorage where they and the U.S. Navy tested procedures and ground support equipment to improve recovery procedures and hardware ahead of Orion's next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

Ready, Set, Conference! Mastering the Logistics

ERIC Educational Resources Information Center

McGuire, Margaret

2005-01-01

Planning to have a successful NAEYC Annual Conference experience is similar to preparing for a day of bargain shopping. In this article, the author describes how to get the most out of NAEYC's Annual Conference by analyzing their goals, preparing ahead, and being flexible. As a veteran conference attendee, the author learned from her mistakes and…

Ahead of Their Class

ERIC Educational Resources Information Center

Jacobson, Linda

2005-01-01

This article discusses a pilot project in New Mexico that gives kindergartners--and some 1st graders--20 extra days before the school year begins to learn the ropes and jump into their lessons. The project is called Kindergarten-Plus, the concept is the brainchild of former American Federation of Teachers President Sandra Feldman. According to…

Hope and Learning: The Outcomes of Contemporary Student Activism

ERIC Educational Resources Information Center

Quaye, Stephen John

2007-01-01

For years, educators and politicians have sought to foster a sense of hope among students--a hope that moves them beyond cynicism about society and incite them to envision better days ahead. Yet as Princeton University professor of religion and author Cornel West discusses in his 2004 book "Democracy Matters", many students today are…

Optimization of ACC system spacing policy on curved highway

NASA Astrophysics Data System (ADS)

Ma, Jun; Qian, Kun; Gong, Zaiyan

2017-05-01

The paper optimizes the original spacing policy when adopting VTH (Variable Time Headway), proposes to introduce the road curve curvature K to the spacing policy to cope with following the wrong vehicle or failing to follow the vehicle owing to the radar limitation of curve in ACC system. By utilizing MATLAB/Simulink, automobile longitudinal dynamics model is established. At last, the paper sets up such three common cases as the vehicle ahead runs at a uniform velocity, an accelerated velocity and hits the brake suddenly, simulates these cases on the curve with different curvature, analyzes the curve spacing policy in the perspective of safety and vehicle following efficiency and draws the conclusion whether the optimization scheme is effective or not.

Planning Beyond the Next Trial in Adaptive Experiments: A Dynamic Programming Approach.

PubMed

Kim, Woojae; Pitt, Mark A; Lu, Zhong-Lin; Myung, Jay I

2017-11-01

Experimentation is at the heart of scientific inquiry. In the behavioral and neural sciences, where only a limited number of observations can often be made, it is ideal to design an experiment that leads to the rapid accumulation of information about the phenomenon under study. Adaptive experimentation has the potential to accelerate scientific progress by maximizing inferential gain in such research settings. To date, most adaptive experiments have relied on myopic, one-step-ahead strategies in which the stimulus on each trial is selected to maximize inference on the next trial only. A lingering question in the field has been how much additional benefit would be gained by optimizing beyond the next trial. A range of technical challenges has prevented this important question from being addressed adequately. This study applies dynamic programming (DP), a technique applicable for such full-horizon, "global" optimization, to model-based perceptual threshold estimation, a domain that has been a major beneficiary of adaptive methods. The results provide insight into conditions that will benefit from optimizing beyond the next trial. Implications for the use of adaptive methods in cognitive science are discussed. Copyright © 2016 Cognitive Science Society, Inc.

Spousal caregivers and persons with dementia: Increasing participation in shared leisure activities among hospital-based dementia support program participants.

PubMed

DiLauro, Michelle; Pereira, Amanda; Carr, Jennifer; Chiu, Mary; Wesson, Virginia

2015-02-20

Spousal caregivers of persons with dementia often have difficulty engaging persons with dementia in leisure activities. This qualitative descriptive study identifies how caregivers perceive their spouses' participation in leisure activities since dementia onset and the professional guidance caregivers require to increase persons with dementia participation in shared leisure activities. Nine spousal caregivers from a hospital-based caregiver intervention attended one of three focus groups. Using symbolic interactionism and selective optimization with compensation theory as guiding frameworks, thematic content analysis was performed. Three major themes were identified: Recognizing and acknowledging changes, Making sense of changes and conflicts, and Embracing changes and forging ahead. Findings can be used by healthcare providers to better understand caregivers' needs for engaging persons with dementia in shared leisure activities, and inform development of feedback protocols to enhance caregiver interventions. © The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Hypoglycemia early alarm systems based on recursive autoregressive partial least squares models.

PubMed

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. © 2012 Diabetes Technology Society.

Hypoglycemia Early Alarm Systems Based on Recursive Autoregressive Partial Least Squares Models

PubMed Central

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Background Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. Methods A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Results Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. Conclusions The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. PMID:23439179

Understanding Activity Engagement Across Weekdays and Weekend Days: A Multivariate Multiple Discrete-Continuous Modeling Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garikapati, Venu; Astroza, Sebastian; Bhat, Prerna C.

This paper is motivated by the increasing recognition that modeling activity-travel demand for a single day of the week, as is done in virtually all travel forecasting models, may be inadequate in capturing underlying processes that govern activity-travel scheduling behavior. The considerable variability in daily travel suggests that there are important complementary relationships and competing tradeoffs involved in scheduling and allocating time to various activities across days of the week. Both limited survey data availability and methodological challenges in modeling week-long activity-travel schedules have precluded the development of multi-day activity-travel demand models. With passive and technology-based data collection methods increasinglymore » in vogue, the collection of multi-day travel data may become increasingly commonplace in the years ahead. This paper addresses the methodological challenge associated with modeling multi-day activity-travel demand by formulating a multivariate multiple discrete-continuous probit (MDCP) model system. The comprehensive framework ties together two MDCP model components, one corresponding to weekday time allocation and the other to weekend activity-time allocation. By tying the two MDCP components together, the model system also captures relationships in activity-time allocation between weekdays on the one hand and weekend days on the other. Model estimation on a week-long travel diary data set from the United Kingdom shows that there are significant inter-relationships between weekdays and weekend days in activity-travel scheduling behavior. The model system presented in this paper may serve as a higher-level multi-day activity scheduler in conjunction with existing daily activity-based travel models.« less

Forecasting Wind and Solar Generation: Improving System Operations, Greening the Grid (Spanish Version)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tian, Tian; Chernyakhovskiy, Ilya; Brancucci Martinez-Anido, Carlo

This document is the Spanish version of 'Greening the Grid- Forecasting Wind and Solar Generation Improving System Operations'. It discusses improving system operations with forecasting with and solar generation. By integrating variable renewable energy (VRE) forecasts into system operations, power system operators can anticipate up- and down-ramps in VRE generation in order to cost-effectively balance load and generation in intra-day and day-ahead scheduling. This leads to reduced fuel costs, improved system reliability, and maximum use of renewable resources.

Final Technical Report for Contract No. DE-EE0006332, "Integrated Simulation Development and Decision Support Tool-Set for Utility Market and Distributed Solar Power Generation"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cormier, Dallas; Edra, Sherwin; Espinoza, Michael

This project will enable utilities to develop long-term strategic plans that integrate high levels of renewable energy generation, and to better plan power system operations under high renewable penetration. The program developed forecast data streams for decision support and effective integration of centralized and distributed solar power generation in utility operations. This toolset focused on real time simulation of distributed power generation within utility grids with the emphasis on potential applications in day ahead (market) and real time (reliability) utility operations. The project team developed and demonstrated methodologies for quantifying the impact of distributed solar generation on core utility operations,more » identified protocols for internal data communication requirements, and worked with utility personnel to adapt the new distributed generation (DG) forecasts seamlessly within existing Load and Generation procedures through a sophisticated DMS. This project supported the objectives of the SunShot Initiative and SUNRISE by enabling core utility operations to enhance their simulation capability to analyze and prepare for the impacts of high penetrations of solar on the power grid. The impact of high penetration solar PV on utility operations is not only limited to control centers, but across many core operations. Benefits of an enhanced DMS using state-of-the-art solar forecast data were demonstrated within this project and have had an immediate direct operational cost savings for Energy Marketing for Day Ahead generation commitments, Real Time Operations, Load Forecasting (at an aggregate system level for Day Ahead), Demand Response, Long term Planning (asset management), Distribution Operations, and core ancillary services as required for balancing and reliability. This provided power system operators with the necessary tools and processes to operate the grid in a reliable manner under high renewable penetration.« less

Runtime Speculative Software-Only Fault Tolerance

DTIC Science & Technology

2012-06-01

reliability of RSFT, a in-depth analysis on its window of vulnerability is also discussed and measured via simulated fault injection. The performance...propagation of faults through the entire program. For optimal performance, these techniques have to use herotic alias analysis to find the minimum set of...affect program output. No program source code or alias analysis is needed to analyze the fault propagation ahead of time. 2.3 Limitations of Existing

Development and implementation of a dynamic TES dispatch control component in a PV-CSP techno-economic performance modelling tool

NASA Astrophysics Data System (ADS)

Hansson, Linus; Guédez, Rafael; Larchet, Kevin; Laumert, Bjorn

2017-06-01

The dispatchability offered by thermal energy storage (TES) in concentrated solar power (CSP) and solar hybrid plants based on such technology presents the most important difference compared to power generation based only on photovoltaics (PV). This has also been one reason for recent hybridization efforts of the two technologies and the creation of Power Purchase Agreement (PPA) payment schemes based on offering higher payment multiples during daily hours of higher (peak or priority) demand. Recent studies involving plant-level thermal energy storage control strategies are however to a large extent based on pre-determined approaches, thereby not taking into account the actual dynamics of thermal energy storage system operation. In this study, the implementation of a dynamic dispatch strategy in the form of a TRNSYS controller for hybrid PV-CSP plants in the power-plant modelling tool DYESOPT is presented. In doing this it was attempted to gauge the benefits of incorporating a day-ahead approach to dispatch control compared to a fully pre-determined approach determining hourly dispatch only once prior to annual simulation. By implementing a dynamic strategy, it was found possible to enhance technical and economic performance for CSP-only plants designed for peaking operation and featuring low values of the solar multiple. This was achieved by enhancing dispatch control, primarily by taking storage levels at the beginning of every simulation day into account. The sequential prediction of the TES level could therefore be improved, notably for evaluated plants without integrated PV, for which the predicted storage levels deviated less than when PV was present in the design. While also featuring dispatch performance gains, optimal plant configurations for hybrid PV-CSP was found to present a trade-off in economic performance in the form of an increase in break-even electricity price when using the dynamic strategy which was offset to some extent by a reduction in upfront investment cost. An increase in turbine starts for the implemented strategy however highlights that this is where further improvements can be made.

Main doorway to the display area, straight ahead. Double doors ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Main doorway to the display area, straight ahead. Double doors with "top secret" alert lights, coded doorbell, and one way mirror. Stairway to second floor and basement is at the left, as well as the secondary entrance at the east part of the north front. View to east - March Air Force Base, Strategic Air Command, Combat Operations Center, 5220 Riverside Drive, Moreno Valley, Riverside County, CA

Underway Recovery Test 6 (URT-6) - Day 1 Activities

NASA Image and Video Library

2018-01-17

A test article of Orion floats in 6-feet of water in the well deck of the USS Anchorage. The NASA Recovery Team from Kennedy Space Center is working with the U.S. Navy to improve recovery procedures and hardware ahead of Orion’s next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

Education the Way Ahead? An Evaluation of a Pilot Course on Scenario Writing

ERIC Educational Resources Information Center

Viebahn, Peter; Hilton, Gillian

2006-01-01

Scenario writing is a method to promote creative thinking and a proactive approach to dealing with the future. ATEE's Research and Development Centre "Curricula in Teacher Education" has adapted this method for use in teacher education. A Comenius funded course on Scenario writing was run over five days with teachers, teacher--educators,…

Looking Ahead: Future Directions in, and Future Research into, Second Language Acquisition

ERIC Educational Resources Information Center

Larsen-Freeman, Diane

2018-01-01

This article begins by situating modern-day second language acquisition (SLA) research in a historical context, tracing its evolution from cognitive to social to sociocognitive accounts. Next, the influence of the zeitgeist is considered. In this era of rapid change and turmoil, there are both perils and opportunities afforded by globalization. In…

Education Department to Push for Major Changes in Accreditation

ERIC Educational Resources Information Center

Basken, Paul

2007-01-01

The U.S. Department of Education, overriding opposition from colleges and accreditors, is pushing ahead with a plan to remake American higher education by requiring that colleges show results if they want to remain eligible for more than $90-billion in federal student aid. At the end of a three-day session last month, representatives of colleges…

Flight-measured pressure characteristics of aft-facing steps in high Reynolds number flow at Mach numbers of 2.20, 2.50, and 2.80 and comparison with other data

NASA Technical Reports Server (NTRS)

Powers, S. G.

1978-01-01

The YF-12 airplane was studied to determine the pressure characteristics associated with an aft-facing step in high Reynolds number flow for nominal Mach numbers of 2.20, 2.50, and 2.80. Base pressure coefficients were obtained for three step heights. The surface static pressures ahead of and behind the step were measured for the no-step condition and for each of the step heights. A boundary layer rake was used to determine the local boundary layer conditions. The Reynolds number based on the length of flow ahead of the step was approximately 10 to the 8th power and the ratios of momentum thickness to step height ranged from 0.2 to 1.0. Base pressure coefficients were compared with other available data at similar Mach numbers and at ratios of momentum thickness to step height near 1.0. In addition, the data were compared with base pressure coefficients calculated by a semiempirical prediction method. The base pressure ratios are shown to be a function of Reynolds number based on momentum thickness. Profiles of the surface pressures ahead of and behind the step and the local boundary layer conditions are also presented.

Distributed Energy Resource Optimization Using a Software as Service (SaaS) Approach at the University of California, Davis Campus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stadler, Michael; Marnay, Chris; Donadee, Jon

2011-02-06

Together with OSIsoft LLC as its private sector partner and matching sponsor, the Lawrence Berkeley National Laboratory (Berkeley Lab) won an FY09 Technology Commercialization Fund (TCF) grant from the U.S. Department of Energy. The goal of the project is to commercialize Berkeley Lab's optimizing program, the Distributed Energy Resources Customer Adoption Model (DER-CAM) using a software as a service (SaaS) model with OSIsoft as its first non-scientific user. OSIsoft could in turn provide optimization capability to its software clients. In this way, energy efficiency and/or carbon minimizing strategies could be made readily available to commercial and industrial facilities. Specialized versionsmore » of DER-CAM dedicated to solving OSIsoft's customer problems have been set up on a server at Berkeley Lab. The objective of DER-CAM is to minimize the cost of technology adoption and operation or carbon emissions, or combinations thereof. DER-CAM determines which technologies should be installed and operated based on specific site load, price information, and performance data for available equipment options. An established user of OSIsoft's PI software suite, the University of California, Davis (UCD), was selected as a demonstration site for this project. UCD's participation in the project is driven by its motivation to reduce its carbon emissions. The campus currently buys electricity economically through the Western Area Power Administration (WAPA). The campus does not therefore face compelling cost incentives to improve the efficiency of its operations, but is nonetheless motivated to lower the carbon footprint of its buildings. Berkeley Lab attempted to demonstrate a scenario wherein UCD is forced to purchase electricity on a standard time-of-use tariff from Pacific Gas and Electric (PG&E), which is a concern to Facilities staff. Additionally, DER-CAM has been set up to consider the variability of carbon emissions throughout the day and seasons. Two distinct analyses of value to UCD are possible using this approach. First, optimal investment choices for buildings under the two alternative objectives can be derived. Second, a week-ahead building operations forecaster has been written that executes DER-CAM to find an optimal operating schedule for buildings given their expected building energy services requirements, electricity prices, and local weather. As part of its matching contribution, OSIsoft provided a full implementation of PI and a server to install it on at Berkeley Lab. Using the PItoPI protocol, this gives Berkeley Lab researchers direct access to UCD's PI data base. However, this arrangement is in itself inadequate for performing optimizations. Additional data not included in UCD's PI database would be needed and the campus was not able to provide this information. This report details the process, results, and lessons learned of this commercialization project.« less

Design and Optimization of an EEG-Based Brain Machine Interface (BMI) to an Upper-Limb Exoskeleton for Stroke Survivors

PubMed Central

Bhagat, Nikunj A.; Venkatakrishnan, Anusha; Abibullaev, Berdakh; Artz, Edward J.; Yozbatiran, Nuray; Blank, Amy A.; French, James; Karmonik, Christof; Grossman, Robert G.; O'Malley, Marcia K.; Francisco, Gerard E.; Contreras-Vidal, Jose L.

2016-01-01

This study demonstrates the feasibility of detecting motor intent from brain activity of chronic stroke patients using an asynchronous electroencephalography (EEG)-based brain machine interface (BMI). Intent was inferred from movement related cortical potentials (MRCPs) measured over an optimized set of EEG electrodes. Successful intent detection triggered the motion of an upper-limb exoskeleton (MAHI Exo-II), to guide movement and to encourage active user participation by providing instantaneous sensory feedback. Several BMI design features were optimized to increase system performance in the presence of single-trial variability of MRCPs in the injured brain: (1) an adaptive time window was used for extracting features during BMI calibration; (2) training data from two consecutive days were pooled for BMI calibration to increase robustness to handle the day-to-day variations typical of EEG, and (3) BMI predictions were gated by residual electromyography (EMG) activity from the impaired arm, to reduce the number of false positives. This patient-specific BMI calibration approach can accommodate a broad spectrum of stroke patients with diverse motor capabilities. Following BMI optimization on day 3, testing of the closed-loop BMI-MAHI exoskeleton, on 4th and 5th days of the study, showed consistent BMI performance with overall mean true positive rate (TPR) = 62.7 ± 21.4% on day 4 and 67.1 ± 14.6% on day 5. The overall false positive rate (FPR) across subjects was 27.74 ± 37.46% on day 4 and 27.5 ± 35.64% on day 5; however for two subjects who had residual motor function and could benefit from the EMG-gated BMI, the mean FPR was quite low (< 10%). On average, motor intent was detected −367 ± 328 ms before movement onset during closed-loop operation. These findings provide evidence that closed-loop EEG-based BMI for stroke patients can be designed and optimized to perform well across multiple days without system recalibration. PMID:27065787

Economic assessment and optimal operation of CSP systems with TES in California electricity markets

NASA Astrophysics Data System (ADS)

Dowling, Alexander W.; Dyreson, Ana; Miller, Franklin; Zavala, Victor M.

2017-06-01

The economics and performance of concentrated power (CSP) systems with thermal energy storage (TES) inherently depend on operating policies and the surrounding weather conditions and electricity markets. We present an integrated economic assessment framework to quantify the maximum possible revenues from simultaneous energy and ancillary services sales by CSP systems. The framework includes both discrete start-up/shutdown restrictions and detailed physical models. Analysis of coinci-dental historical market and meteorological data reveals provision of ancillary services increases market revenue 18% to 37% relative to energy-only participation. Surprisingly, only 53% to 62% of these revenues are available through sole participation in the day-ahead market, indicating significant opportunities at faster timescales. Motivated by water-usage concerns and permitting requirements, we also describe a new nighttime radiative-enhanced dry-cooling system with cold-side storage that consumes no water and offers higher effciencies than traditional air-cooled designs. Operation of this new system is complicated by the cold-side storage and inherent coupling between the cooling system and power plant, further motivating integrated economic analysis.

Short term load forecasting using a self-supervised adaptive neural network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoo, H.; Pimmel, R.L.

The authors developed a self-supervised adaptive neural network to perform short term load forecasts (STLF) for a large power system covering a wide service area with several heavy load centers. They used the self-supervised network to extract correlational features from temperature and load data. In using data from the calendar year 1993 as a test case, they found a 0.90 percent error for hour-ahead forecasting and 1.92 percent error for day-ahead forecasting. These levels of error compare favorably with those obtained by other techniques. The algorithm ran in a couple of minutes on a PC containing an Intel Pentium --more » 120 MHz CPU. Since the algorithm included searching the historical database, training the network, and actually performing the forecasts, this approach provides a real-time, portable, and adaptable STLF.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Joyce Jihyun; Yin, Rongxin; Kiliccote, Sila

Open Automated Demand Response (OpenADR), an XML-based information exchange model, is used to facilitate continuous price-responsive operation and demand response participation for large commercial buildings in New York who are subject to the default day-ahead hourly pricing. We summarize the existing demand response programs in New York and discuss OpenADR communication, prioritization of demand response signals, and control methods. Building energy simulation models are developed and field tests are conducted to evaluate continuous energy management and demand response capabilities of two commercial buildings in New York City. Preliminary results reveal that providing machine-readable prices to commercial buildings can facilitate bothmore » demand response participation and continuous energy cost savings. Hence, efforts should be made to develop more sophisticated algorithms for building control systems to minimize customer's utility bill based on price and reliability information from the electricity grid.« less

"First Light" Approaches for VLT MELIPAL

NASA Astrophysics Data System (ADS)

2000-01-01

The year 1999 was a very busy one at ESO's Paranal Observatory , the site of the Very Large Telescope (VLT). Soon after the official Inauguration on March 5, 1999, regular observations started with the first 8.2-m VLT Unit Telescope ANTU . During the first nine months of operation (April - December 1999), about 79,000 exposures were made with the FORS1 and ISAAC astronomical instruments at this telescope. Altogether, more than 68 Gigabytes of unique data were gathered during this period for about 200 individual research programmes and stored in the VLT Data Archive. "First Light" was successfully achieved early in the year for the second 8.2-m VLT Unit telescope, KUEYEN . It has since been equipped with two powerful instruments, UVES and FORS2. Science observations with this telescope will start on April 1, 2000. Already in early December 1999, ahead of the schedule, the third 8.2-m Zerodur mirror in its cell was attached to the third 8.2-m VLT Unit Telescope, MELIPAL , cf. ESO PR Photos 42a-ad/99. The moment of "First Light" is approaching for this telescope. Originally planned for mid-February 2000, this significant event is now expected to take place about two weeks ahead of schedule, in late January 2000. From then on, the VLT will possess nearly 160 square metres of extremely accurate, highly reflecting mirror surface. While the observations for "First Light" and the subsequent commissioning period will be carried out with the VLT Test Camera, MELIPAL will receive its first special astronomical instrument, the VIsible MultiObject Spectrograph (VIMOS) towards the middle of the year. It is optimized for large field imaging and spectroscopic surveys and will become a real workhorse of the VLT for this type of research projects, together with the Near InfraRed MultiObject Spectrograph (NIRMOS) , to be installed later at the fourth 8.2-m Unit Telescope, YEPUN . YEPUN will have "First Light" later this year and the work on this telescope also progresses well. The "M1 Dummy" that was mounted on the telescope frame for balance during the mechanical assembly was removed on January 4. The next day, it was transported down to the Base Camp storage area where it was lifted off the Carriage using a combination of two cranes. The empty M1 Carriage was then moved to the Mirror Maintenance Building (MMB) where the fourth M1 Cell with a dummy concrete mirror was loaded. Later that day it was transported up to YEPUN and the next morning (January 6), the Mirror Cell was moved inside the enclosure. Over the next weeks, it will be fitted to the back of the telescope structure. In parallel, the "M2 Unit" on which the 1.1-m secondary mirror of beryllium will later be mounted, is now being assembled in the Integration Laboratory in the MMB. The following digital photos were obtained during the past days and illustrate the recent work.

Weight Loss Strategies Associated With BMI in Overweight Adults With Type 2 Diabetes at Entry Into the Look AHEAD (Action for Health in Diabetes) Trial

PubMed Central

Raynor, Hollie A.; Jeffery, Robert W.; Ruggiero, Andrea M.; Clark, Jeanne M.; Delahanty, Linda M.

2008-01-01

OBJECTIVE—Intentional weight loss is recommended for those with type 2 diabetes, but the strategies patients attempt and their effectiveness for weight management are unknown. In this investigation we describe intentional weight loss strategies used and those related to BMI in a diverse sample of overweight participants with type 2 diabetes at enrollment in the Look AHEAD (Action for Health in Diabetes) clinical trial. RESEARCH DESIGN AND METHODS—This was a cross-sectional study of baseline weight loss strategies, including self-weighing frequency, eating patterns, and weight control practices, reported in 3,063 women and 2,082 men aged 45–74 years with BMI ≥25 kg/m2. RESULTS—Less than half (41.4%) of participants self-weighed ≥1/week. Participants ate breakfast 6.0 ± 1.8 days/week, ate 5.0 ± 3.1 meals/snacks per day, and ate 1.9 ± 2.7 fast food meals/week. The three most common weight control practices (increasing fruits and vegetables, cutting out sweets, and eating less high-carbohydrate foods) were reported by ∼60% of participants for ≥20 weeks over the previous year. Adjusted models showed that self-weighing less than once per week (B = 0.83), more fast food meals consumed per week (B = 0.14), and fewer breakfast meals consumed per week (B = −0.19) were associated (P < 0.05) with a higher BMI (R2 = 0.24). CONCLUSIONS—Regular self-weighing and breakfast consumption, along with infrequent consumption of fast food, were related to lower BMI in the Look AHEAD study population. PMID:18375417

Observations and mechanisms of GATE waterspouts

NASA Technical Reports Server (NTRS)

Simpson, J.; Mccumber, M. C.; Morton, B. R.; Penc, R. S.

1986-01-01

The present numerical and observational investigation of interacting cumulus processes implicated in the formation of waterspouts, the GATE database for days 261 and 186 is noted to imply that the existence of cumulus-scale parent vortices is a necessary (albeit not sufficient) condition for the production of waterspouts. A high resolution version of the Schlessinger (1975) three-dimensional cumulus model with a Kessler (1969) type precipitation scheme is used to analyze cumulus-scale vorticity organization, which on the two days in question exhibited contrasting thermal stratification and cloud features. The observations from both days suggest that the waterspouts formed ahead of the wind shift, due to the passage of a gust front.

Airborne castanea pollen forecasting model for ecological and allergological implementation.

PubMed

Astray, G; Fernández-González, M; Rodríguez-Rajo, F J; López, D; Mejuto, J C

2016-04-01

Castanea sativa Miller belongs to the natural vegetation of many European deciduous forests prompting impacts in the forestry, ecology, allergological and chestnut food industry fields. The study of the Castanea flowering represents an important tool for evaluating the ecological conservation of North-Western Spain woodland and the possible changes in the chestnut distribution due to recent climatic change. The Castanea pollen production and dispersal capacity may cause hypersensitivity reactions in the sensitive human population due to the relationship between patients with chestnut pollen allergy and a potential cross reactivity risk with other pollens or plant foods. In addition to Castanea pollen's importance as a pollinosis agent, its study is also essential in North-Western Spain due to the economic impact of the industry around the chestnut tree cultivation and its beekeeping interest. The aim of this research is to develop an Artificial Neural Networks for predict the Castanea pollen concentration in the atmosphere of the North-West Spain area by means a 20years data set. It was detected an increasing trend of the total annual Castanea pollen concentrations in the atmosphere during the study period. The Artificial Neural Networks (ANNs) implemented in this study show a great ability to predict Castanea pollen concentration one, two and three days ahead. The model to predict the Castanea pollen concentration one day ahead shows a high linear correlation coefficient of 0.784 (individual ANN) and 0.738 (multiple ANN). The results obtained improved those obtained by the classical methodology used to predict the airborne pollen concentrations such as time series analysis or other models based on the correlation of pollen levels with meteorological variables. Copyright © 2016 Elsevier B.V. All rights reserved.

Customer response to day-ahead wholesale market electricity prices: Case study of RTP program experience in New York

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldman, C.; Hopper, N.; Sezgen, O.

2004-07-01

There is growing interest in policies, programs and tariffs that encourage customer loads to provide demand response (DR) to help discipline wholesale electricity markets. Proposals at the retail level range from eliminating fixed rate tariffs as the default service for some or all customer groups to reinstituting utility-sponsored load management programs with market-based inducements to curtail. Alternative rate designs include time-of-use (TOU), day-ahead real-time pricing (RTP), critical peak pricing, and even pricing usage at real-time market balancing prices. Some Independent System Operators (ISOs) have implemented their own DR programs whereby load curtailment capabilities are treated as a system resource andmore » are paid an equivalent value. The resulting load reductions from these tariffs and programs provide a variety of benefits, including limiting the ability of suppliers to increase spot and long-term market-clearing prices above competitive levels (Neenan et al., 2002; Boren stein, 2002; Ruff, 2002). Unfortunately, there is little information in the public domain to characterize and quantify how customers actually respond to these alternative dynamic pricing schemes. A few empirical studies of large customer RTP response have shown modest results for most customers, with a few very price-responsive customers providing most of the aggregate response (Herriges et al., 1993; Schwarz et al., 2002). However, these studies examined response to voluntary, two-part RTP programs implemented by utilities in states without retail competition.1 Furthermore, the researchers had limited information on customer characteristics so they were unable to identify the drivers to price response. In the absence of a compelling characterization of why customers join RTP programs and how they respond to prices, many initiatives to modernize retail electricity rates seem to be stymied.« less

Forecast the energetic electron flux on geosynchronous orbit with interplanetary parameters

NASA Astrophysics Data System (ADS)

Xue, B.; Ye, Z.

The high flux of energetic electron on geo-synchronous orbit can cause many kinds of malfunction of the satellite there, within which the bulk charging is the most significant that several broadcast satellite failures were confirmed to be due to this effect. The electron flux on geo-synchronous orbit varies in a large range even up to three orders accompanied the passage of interplanetary magnetic cloud and the following geomagnetic disturbances. Upon investigating electron flux, interplanetary solar wind data, and geomagnetic data as well, we found that: (1) The enhancement of energetic flux on the geo-synchronous orbit exhibits periodic recurrence of 27days. (2)Significant increase of electron flux relates to interplanetary index and characters of their distribution. (3)The electron flux also has relation to solar activity index. In our research work, artificial neural network was employed and constructed according to the job. The neural network, we call it full connecting network, was proved to be a sufficient tool to analyze the character of the evolving parameters, remember the omen of "electron storm", and establish the relationship between interplanetary parameters etc., and the fluence of high energetic electrons. The neural network was carefully constructed and trained to do the job mentioned above. Preliminary result showed that the accuracy forecast of electron flux 1 day ahead can reach 80%, and 70% for 2 days ahead.

A new cellular automata model of traffic flow with negative exponential weighted look-ahead potential

NASA Astrophysics Data System (ADS)

Ma, Xiao; Zheng, Wei-Fan; Jiang, Bao-Shan; Zhang, Ji-Ye

2016-10-01

With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver’s random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations. Project supported by the National Natural Science Foundation of China (Grant Nos. 11572264, 11172247, 11402214, and 61373009).

The role of resilience and mindful leadership in oncology nursing.

PubMed

Rishel, Cindy J

2015-03-01

When oncology nurses think of the word resilient, they often describe the term in the context of the patients and families they care for each day. When patients face a diagnosis of cancer, their lives have suddenly been altered in a frightening manner. Everything changes, and they must find a way to navigate the troubled waters ahead. 
.

Expedition 38 Press Conference

NASA Image and Video Library

2013-11-06

Expedition 38 Soyuz Commander Mikhail Tyurin of Roscosmos, center, talks as Flight Engineer Koichi Wakata of the Japan Aerospace Exploration Agency, left, and, Flight Engineer Rick Mastracchio of NASA listen, while quarantine behind glass, during the final press conference held a day ahead of their launch to the International Space Station, Wednesday, Nov. 6, 2013 at the Cosmonaut Hotel in Baikonur, Kazakhstan. Photo Credit: (NASA/Bill Ingalls)

Underway Recovery Test 6 (URT-6) - Day 5 Activities

NASA Image and Video Library

2018-01-21

Lead Instrumentation Engineer Kevin Taylor keeps an eye on the load levels during Underway Recovery Test 6 operations off the coast of San Diego. Kennedy Space Center’s NASA Recovery Team works with the U.S. Navy to improve recovery procedures and hardware ahead of Orion's next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

Full STEAM Ahead: From Earth to Ploonoids

NASA Astrophysics Data System (ADS)

Runyon, C. R.; Hall, C.; Blackman, C. L.; Royle, M.; Williams, M. N.

2015-12-01

What the heck is a plunoid, you ask? The NASA Solar System Exploration Research Virtual Institute's Education/Public Engagement (EPE) program,from two SSERVI teams (SEEED at Brown/MIT and CLASS at University of Central Florida), is moving full STEAM ahead, engaging the public in the exciting discoveries being made around small bodies, including PLanetary mOONs and asterOIDS (i.e ploonoids). The team has incorporated the arts, from visual representations, storytelling, and music into every facet of the program, to stimulate an affective and personal connection to the content. This past year, the SSERVI STEAM team has participated in numerous public science events, including International Observe the Moon Night, two Astronomy Nights at a local baseball venue, Dark Skies at the US and Canadian National Parks, and Space Day at Camp Happy Days, a camp for children with cancer. Through these events, the team reached over 10000 members of the general public, showcasing current NASA SSERVI research, dispelling myths about our landing and exploring the moon, demonstrating the excitement of STEM through hands-on interactive displays, and providing an outlet for creativity by having multiple ways of representing and explaining scientific information through the arts. Join us on our "ed"venture through the solar system ploonoids.

Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parks, K.; Wan, Y. H.; Wiener, G.

2011-10-01

The focus of this report is the wind forecasting system developed during this contract period with results of performance through the end of 2010. The report is intentionally high-level, with technical details disseminated at various conferences and academic papers. At the end of 2010, Xcel Energy managed the output of 3372 megawatts of installed wind energy. The wind plants span three operating companies1, serving customers in eight states2, and three market structures3. The great majority of the wind energy is contracted through power purchase agreements (PPAs). The remainder is utility owned, Qualifying Facilities (QF), distributed resources (i.e., 'behind the meter'),more » or merchant entities within Xcel Energy's Balancing Authority footprints. Regardless of the contractual or ownership arrangements, the output of the wind energy is balanced by Xcel Energy's generation resources that include fossil, nuclear, and hydro based facilities that are owned or contracted via PPAs. These facilities are committed and dispatched or bid into day-ahead and real-time markets by Xcel Energy's Commercial Operations department. Wind energy complicates the short and long-term planning goals of least-cost, reliable operations. Due to the uncertainty of wind energy production, inherent suboptimal commitment and dispatch associated with imperfect wind forecasts drives up costs. For example, a gas combined cycle unit may be turned on, or committed, in anticipation of low winds. The reality is winds stayed high, forcing this unit and others to run, or be dispatched, to sub-optimal loading positions. In addition, commitment decisions are frequently irreversible due to minimum up and down time constraints. That is, a dispatcher lives with inefficient decisions made in prior periods. In general, uncertainty contributes to conservative operations - committing more units and keeping them on longer than may have been necessary for purposes of maintaining reliability. The downside is costs are higher. In organized electricity markets, units that are committed for reliability reasons are paid their offer price even when prevailing market prices are lower. Often, these uplift charges are allocated to market participants that caused the inefficient dispatch in the first place. Thus, wind energy facilities are burdened with their share of costs proportional to their forecast errors. For Xcel Energy, wind energy uncertainty costs manifest depending on specific market structures. In the Public Service of Colorado (PSCo), inefficient commitment and dispatch caused by wind uncertainty increases fuel costs. Wind resources participating in the Midwest Independent System Operator (MISO) footprint make substantial payments in the real-time markets to true-up their day-ahead positions and are additionally burdened with deviation charges called a Revenue Sufficiency Guarantee (RSG) to cover out of market costs associated with operations. Southwest Public Service (SPS) wind plants cause both commitment inefficiencies and are charged Southwest Power Pool (SPP) imbalance payments due to wind uncertainty and variability. Wind energy forecasting helps mitigate these costs. Wind integration studies for the PSCo and Northern States Power (NSP) operating companies have projected increasing costs as more wind is installed on the system due to forecast error. It follows that reducing forecast error would reduce these costs. This is echoed by large scale studies in neighboring regions and states that have recommended adoption of state-of-the-art wind forecasting tools in day-ahead and real-time planning and operations. Further, Xcel Energy concluded reduction of the normalized mean absolute error by one percent would have reduced costs in 2008 by over $1 million annually in PSCo alone. The value of reducing forecast error prompted Xcel Energy to make substantial investments in wind energy forecasting research and development.« less

Comparison and optimization of radar-based hail detection algorithms in Slovenia

NASA Astrophysics Data System (ADS)

Stržinar, Gregor; Skok, Gregor

2018-05-01

Four commonly used radar-based hail detection algorithms are evaluated and optimized in Slovenia. The algorithms are verified against ground observations of hail at manned stations in the period between May and August, from 2002 to 2010. The algorithms are optimized by determining the optimal values of all possible algorithm parameters. A number of different contingency-table-based scores are evaluated with a combination of Critical Success Index and frequency bias proving to be the best choice for optimization. The best performance indexes are given by Waldvogel and the severe hail index, followed by vertically integrated liquid and maximum radar reflectivity. Using the optimal parameter values, a hail frequency climatology map for the whole of Slovenia is produced. The analysis shows that there is a considerable variability of hail occurrence within the Republic of Slovenia. The hail frequency ranges from almost 0 to 1.7 hail days per year with an average value of about 0.7 hail days per year.

The Value of Weather Forecast in Irrigation

NASA Astrophysics Data System (ADS)

Cai, X.; Wang, D.

2007-12-01

This paper studies irrigation scheduling (when and how much water to apply during the crop growth season) in the Havana Lowlands region, Illinois, using meteorological, agronomic and agricultural production data from 2002. Irrigation scheduling determines the timing and amount of water applied to an irrigated cropland during the crop growing season. In this study a hydrologic-agronomic simulation is coupled with an optimization algorithm to search for the optimal irrigation schedule under various weather forecast horizons. The economic profit of irrigated corn from an optimized scheduling is compared to that from and the actual schedule, which is adopted from a pervious study. Extended and reliable climate prediction and weather forecast are found to be significantly valuable. If a weather forecast horizon is long enough to include the critical crop growth stage, in which crop yield bears the maximum loss over all stages, much economic loss can be avoided. Climate predictions of one to two months, which can cover the critical period, might be even more beneficial during a dry year. The other purpose of this paper is to analyze farmers' behavior in irrigation scheduling by comparing the "actual" schedule to the "optimized" ones. The ultimate goal of irrigation schedule optimization is to provide information to farmers so that they may modify their behavior. In practice, farmers' decision may not follow an optimal irrigation schedule due to the impact of various factors such as natural conditions, policies, farmers' habits and empirical knowledge, and the uncertain or inexact information that they receive. In this study farmers' behavior in irrigation decision making is analyzed by comparing the "actual" schedule to the "optimized" ones. This study finds that the identification of the crop growth stage with the most severe water stress is critical for irrigation scheduling. For the case study site in the year of 2002, framers' response to water stress was found to be late; they did not even respond appropriately to a major rainfall just 3 days ahead, which might be due to either an unreliable weather forecast or farmer's ignorance of the forecast.

A modeling approach to energy savings of flying Canada geese using computational fluid dynamics.

PubMed

Maeng, Joo-Sung; Park, Jae-Hyung; Jang, Seong-Min; Han, Seog-Young

2013-03-07

A flapping flight mechanism of the Canada goose (Branta canadensis) was estimated using a two-jointed arm model in unsteady aerodynamic performance to examine how much energy can be saved in migration. Computational fluid dynamics (CFD) was used to evaluate airflow fields around the wing and in the wake. From the distributions of velocity and pressure on the wing, it was found that about 15% of goose flight energy could be saved by drag reduction from changing the morphology of the wing. From the airflow field in the wake, it was found that a pair of three-dimensional spiral flapping advantage vortices (FAV) was alternately generated. We quantitatively deduced that the optimal depth (the distance along the flight path between birds) was around 4m from the wing tip of a goose ahead, and optimal wing tip spacing (WTS, the distance between wing tips of adjacent birds perpendicular to the flight path) ranged between 0 and -0.40m in the spanwise section. It was found that a goose behind can save about 16% of its energy by induced power from FAV in V-formation. The phase difference of flapping between the goose ahead and behind was estimated at around 90.7° to take full aerodynamic benefit caused by FAV. Copyright © 2012 Elsevier Ltd. All rights reserved.

[Research on engine remaining useful life prediction based on oil spectrum analysis and particle filtering].

PubMed

Sun, Lei; Jia, Yun-xian; Cai, Li-ying; Lin, Guo-yu; Zhao, Jin-song

2013-09-01

The spectrometric oil analysis(SOA) is an important technique for machine state monitoring, fault diagnosis and prognosis, and SOA based remaining useful life(RUL) prediction has an advantage of finding out the optimal maintenance strategy for machine system. Because the complexity of machine system, its health state degradation process can't be simply characterized by linear model, while particle filtering(PF) possesses obvious advantages over traditional Kalman filtering for dealing nonlinear and non-Gaussian system, the PF approach was applied to state forecasting by SOA, and the RUL prediction technique based on SOA and PF algorithm is proposed. In the prediction model, according to the estimating result of system's posterior probability, its prior probability distribution is realized, and the multi-step ahead prediction model based on PF algorithm is established. Finally, the practical SOA data of some engine was analyzed and forecasted by the above method, and the forecasting result was compared with that of traditional Kalman filtering method. The result fully shows the superiority and effectivity of the

Approaches to Enable Demand Response by Industrial Loads for Ancillary Services Provision

NASA Astrophysics Data System (ADS)

Zhang, Xiao

Demand response has gained significant attention in recent years as it demonstrates potentials to enhance the power system's operational flexibility in a cost-effective way. Industrial loads such as aluminum smelters, steel manufacturers, and cement plants demonstrate advantages in supporting power system operation through demand response programs, because of their intensive power consumption, already existing advanced monitoring and control infrastructure, and the strong economic incentive due to the high energy costs. In this thesis, we study approaches to efficiently integrate each of these types of manufacturing processes as demand response resources. The aluminum smelting process is able to change its power consumption both accurately and quickly by controlling the pots' DC voltage, without affecting the production quality. Hence, an aluminum smelter has both the motivation and the ability to participate in demand response. First, we focus on determining the optimal regulation capacity that such a manufacturing plant should provide. Next, we focus on determining its optimal bidding strategy in the day-ahead energy and ancillary services markets. Electric arc furnaces (EAFs) in steel manufacturing consume a large amount of electric energy. However, a steel plant can take advantage of time-based electricity prices by optimally arranging energy-consuming activities to avoid peak hours. We first propose scheduling methods that incorporate the EAFs' flexibilities to reduce the electricity cost. We then propose methods to make the computations more tractable. Finally, we extend the scheduling formulations to enable the provision of spinning reserve. Cement plants are able to quickly adjust their power consumption rate by switching on/off the crushers. However, switching on/off the loading units only achieves discrete power changes, which restricts the load from offering valuable ancillary services such as regulation and load following, as continuous power changes are required for these services. We propose methods that enable these services with the support of an on-site energy storage device. As demonstrated by the case studies, the proposed approaches are effective and can generate practical production instructions for the industrial loads. This thesis not only provides methods to enable demand response by industrial loads but also potentially encourages industrial loads to be active in electricity markets.

Optimal Operation of Data Centers in Future Smart Grid

NASA Astrophysics Data System (ADS)

Ghamkhari, Seyed Mahdi

The emergence of cloud computing has established a growing trend towards building massive, energy-hungry, and geographically distributed data centers. Due to their enormous energy consumption, data centers are expected to have major impact on the electric grid by significantly increasing the load at locations where they are built. However, data centers also provide opportunities to help the grid with respect to robustness and load balancing. For instance, as data centers are major and yet flexible electric loads, they can be proper candidates to offer ancillary services, such as voluntary load reduction, to the smart grid. Also, data centers may better stabilize the price of energy in the electricity markets, and at the same time reduce their electricity cost by exploiting the diversity in the price of electricity in the day-ahead and real-time electricity markets. In this thesis, such potentials are investigated within an analytical profit maximization framework by developing new mathematical models based on queuing theory. The proposed models capture the trade-off between quality-of-service and power consumption in data centers. They are not only accurate, but also they posses convexity characteristics that facilitate joint optimization of data centers' service rates, demand levels and demand bids to different electricity markets. The analysis is further expanded to also develop a unified comprehensive energy portfolio optimization for data centers in the future smart grid. Specifically, it is shown how utilizing one energy option may affect selecting other energy options that are available to a data center. For example, we will show that the use of on-site storage and the deployment of geographical workload distribution can particularly help data centers in utilizing high-risk energy options such as renewable generation. The analytical approach in this thesis takes into account service-level-agreements, risk management constraints, and also the statistical characteristics of the Internet workload and the electricity prices. Using empirical data, the performance of our proposed profit maximization models for data centers are evaluated, and the capability of data centers to benefit from participation in a variety of Demand Response programs is assessed.

Frequency Based Real-time Pricing for Residential Prosumers

NASA Astrophysics Data System (ADS)

Hambridge, Sarah Mabel

This work is the first to explore frequency based pricing for secondary frequency control as a price-reactive control mechanism for residential prosumers. A frequency based real-time electricity rate is designed as an autonomous market control mechanism for residential prosumers to provide frequency support as an ancillary service. In addition, prosumers are empowered to participate in dynamic energy transactions, therefore integrating Distributed Energy Resources (DERs), and increasing distributed energy storage onto the distributed grid. As the grid transitions towards DERs, a new market based control system will take the place of the legacy distributed system and possibly the legacy bulk power system. DERs provide many benefits such as energy independence, clean generation, efficiency, and reliability to prosumers during blackouts. However, the variable nature of renewable energy and current lack of installed energy storage on the grid will create imbalances in supply and demand as uptake increases, affecting the grid frequency and system operation. Through a frequency-based electricity rate, prosumers will be encouraged to purchase energy storage systems (ESS) to offset their neighbor's distributed generation (DG) such as solar. Chapter 1 explains the deregulation of the power system and move towards Distributed System Operators (DSOs), as prosumers become owners of microgrids and energy cells connected to the distributed system. Dynamic pricing has been proposed as a benefit to prosumers, giving them the ability to make decisions in the energy market, while also providing a way to influence and control their behavior. Frequency based real-time pricing is a type of dynamic pricing which falls between price-reactive control and transactive control. Prosumer-to-prosumer transactions may take the place of prosumer-to-utility transactions, building The Energy Internet. Frequency based pricing could be a mechanism for determining prosumer prices and supporting stability in a free, competitive, market. Frequency based pricing is applied to secondary frequency control in this work, providing support at one to five minute time intervals. In Chapter 2, a frequency based pricing curve is designed as a preliminary study and the response of the prosumer is optimized for economic dispatch. In Chapter 3, a day-ahead schedule and real-time adjustment energy management framework is presented for the prosumer, creating a market structure similar to the existing energy market supervised by Independent System Operators (ISOs). Enabling technology, such as the solid state transformer (SST) is described for prosumer energy transactions, controlling power flow from the prosumer's energy cell to the grid or neighboring prosumer as an energy router. Experimental results are shown to demonstrate this capability. Additionally, the SST is capable of measuring the grid frequency. Lastly, a frequency based real-time hybrid electricity rate is presented in Chapter 4 and Chapter 5. Chapter 4 specializes in a single direction rate while Chapter 5 presents a bi-directional rate. A Time-of-use (TOU) rate is combined with the real-time frequency based price to lower energy bills for a residential prosumer with ESS, in agreement with the proposed day-ahead and real-time energy management framework. The cost to the ESS is also considered in this section. Linear programming and strategic rule based methods are utilized to find the lowest energy bill. As a result, prosumers can use ESS to balance the grid, reducing their bill as much per kWh as PV or DG under a TOU net-metering price scheme, while providing distributed frequency support to the grid authority. The variability of the frequency based rate is similar to variability in the stock market, which gives a sense of how prosumers will interact with variable prices in a system supported by The Energy Internet.

CME Cornucopia (May 11, 2012)

NASA Image and Video Library

2012-05-15

Nearly a dozen coronal mass ejections in less than four days (May 3-6, 2012) may serve as a reminder that the Sun is approaching its period of maximum activity, expected to peak next year. STEREO (Ahead) from its position over 100 degrees ahead of Earth, captured several major eruptions, with most of them heading way to the right (i.e., away from Earth). In these coronagraph images the Sun is represented by the white circle. The black occulting disk blocks out the Sun and some of the corona so that we can see the faint structures beyond that. Credit: NASA/GSFC/SOHO NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Essays in market power mitigation and supply function equilibrium

NASA Astrophysics Data System (ADS)

Subramainam, Thiagarajah Natchie

Market power mitigation has been an integral part of wholesale electricity markets since deregulation. In wholesale electricity markets, different regions in the US take different approaches to regulating market power. While the exercise of market power has received considerable attention in the literature, the issue of market power mitigation has attracted scant attention. In the first chapter, I examine the market power mitigation rules used in New York ISO (Independent System Operator) and California ISO (CAISO) with respect to day-ahead and real-time energy markets. I test whether markups associated with New York in-city generators would be lower with an alternative approach to mitigation, the CAISO approach. Results indicate the difference in markups between these two mitigation rules is driven by the shape of residual demand curves for suppliers. Analysis of residual demand curves faced by New York in-city suppliers show similar markups under both mitigation rules when no one supplier is necessary to meet the demand (i.e., when no supplier is pivotal). However, when some supplier is crucial for the market to clear, the mitigation rule adopted by the NYISO consistently leads to higher markups than would the CAISO rule. This result suggest that market power episodes in New York is confined to periods where some supplier is pivotal. As a result, I find that applying the CAISOs' mitigation rules to the New York market could lower wholesale electricity prices by 18%. The second chapter of my dissertation focuses on supply function equilibrium. In power markets, suppliers submit offer curves in auctions, indicating their willingness to supply at different price levels. Although firms are allowed to submit different offer curves for different time periods, surprisingly many firms stick to a single offer curve for the entire day. This essentially means that firms are submitting a single offer curve for multiple demand realizations. A suitable framework to analyze such oligopolistic competition between power market suppliers is supply function equilibrium models. Using detailed bidding data, I develop equilibrium in supply functions by restricting supplier offers to a class of supply functions. By collating equilibrium supply functions corresponding to different realizations of demand, I obtain a single optimal supply function for the entire day. Then I compare the resulting supply function with actual day-ahead offers in New York. In addition to supply function equilibrium, I also develop a conservative bidding approach in which each firm assumes that rivals bid at marginal costs. Results show that the supply functions derived from equilibrium bidding model in this paper is not consistent with actual bidding in New York. This result is mainly driven by the class of supply functions used in this study to generate the equilibrium. Further, actual offers do not resemble offers generated by the conservative bidding algorithm.

Implementation details of the coupled QMR algorithm

NASA Technical Reports Server (NTRS)

Freund, Roland W.; Nachtigal, Noel M.

1992-01-01

The original quasi-minimal residual method (QMR) relies on the three-term look-ahead Lanczos process, to generate basis vectors for the underlying Krylov subspaces. However, empirical observations indicate that, in finite precision arithmetic, three-term vector recurrences are less robust than mathematically equivalent coupled two-term recurrences. Therefore, we recently proposed a new implementation of the QMR method based on a coupled two-term look-ahead Lanczos procedure. In this paper, we describe implementation details of this coupled QMR algorithm, and we present results of numerical experiments.

Stress changes ahead of an advancing tunnel

USGS Publications Warehouse

Abel, J.F.; Lee, F.T.

1973-01-01

Instrumentation placed ahead of three model tunnels in the laboratory and ahead of a crosscut driven in a metamorphic rock mass detected stress changes several tunnel diameters ahead of the tunnel face. Stress changes were detected 4 diameters ahead of a model tunnel drilled into nearly elastic acrylic, 2??50 diameters ahead of a model tunnel drilled into concrete, and 2 diameters ahead of a model tunnel drilled into Silver Plume Granite. Stress changes were detected 7??50 diameters ahead of a crosscut driven in jointed, closely foliated gneisses and gneissic granites in an experimental mine at Idaho Springs, Colorado. These results contrast markedly with a theoretical elastic estimate of the onset of detectable stress changes at 1 tunnel diameter ahead of the tunnel face. A small compressive stress concentration was detected 2 diameters ahead of the model tunnel in acrylic, 1.25 diameters ahead of the model tunnel in concrete, and 1 diameter ahead of the model tunnel in granite. A similar stress peak was detected about 6 diameters ahead of the crosscut. No such stress peak is predicted from elastic theory. The 3-dimensional in situ stress determined in the field demonstrate that geologic structure controls stress orientations in the metamorphic rock mass. Two of the computed principal stresses are parallel to the foliation and the other principal stress is normal to it. The principal stress orientations vary approximately as the foliation attitude varies. The average horizontal stress components and the average vertical stress component are three times and twice as large, respectively, as those predicted from the overburden load. An understanding of the measured stress field appears to require the application of either tectonic or residual stress components, or both. Laboratory studies indicate the presence of proportionately large residual stresses. Mining may have triggered the release of strain energy, which is controlled by geologic structure. ?? 1973.

Predicting asthma exacerbations using artificial intelligence.

PubMed

Finkelstein, Joseph; Wood, Jeffrey

2013-01-01

Modern telemonitoring systems identify a serious patient deterioration when it already occurred. It would be much more beneficial if the upcoming clinical deterioration were identified ahead of time even before a patient actually experiences it. The goal of this study was to assess artificial intelligence approaches which potentially can be used in telemonitoring systems for advance prediction of changes in disease severity before they actually occur. The study dataset was based on daily self-reports submitted by 26 adult asthma patients during home telemonitoring consisting of 7001 records. Two classification algorithms were employed for building predictive models: naïve Bayesian classifier and support vector machines. Using a 7-day window, a support vector machine was able to predict asthma exacerbation to occur on the day 8 with the accuracy of 0.80, sensitivity of 0.84 and specificity of 0.80. Our study showed that methods of artificial intelligence have significant potential in developing individualized decision support for chronic disease telemonitoring systems.

Day-Ahead Short-Term Forecasting Electricity Load via Approximation

NASA Astrophysics Data System (ADS)

Khamitov, R. N.; Gritsay, A. S.; Tyunkov, D. A.; E Sinitsin, G.

2017-04-01

The method of short-term forecasting of a power consumption which can be applied to short-term forecasting of power consumption is offered. The offered model is based on sinusoidal function for the description of day and night cycles of power consumption. Function coefficients - the period and amplitude are set up is adaptive, considering dynamics of power consumption with use of an artificial neural network. The presented results are tested on real retrospective data of power supply company. The offered method can be especially useful if there are no opportunities of collection of interval indications of metering devices of consumers, and the power supply company operates with electrical supply points. The offered method can be used by any power supply company upon purchase of the electric power in the wholesale market. For this purpose, it is necessary to receive coefficients of approximation of sinusoidal function and to have retrospective data on power consumption on an interval not less than one year.

The ophthalmologist's office: planning and practice. Getting paid and completing insurance forms.

PubMed

Byron, H M

1975-01-01

This chapter describes a systematic approach to the art of collection for services rendered, based primarily on a pay-as-you-go philosophy. A system of internal office-controlled billing, timed so that the statements reach the patients on the last day of the billing month instead of the first day of the following month, unequivocally works more smoothly in the author's office than external computerized billing did. Suggestions to effect and maintain a collection ratio of at least 95 percent have been enumerated. The use of a new statement-and-insurance form facilitates billing, keeping ahead of insurance applications for patients, and advising the front office of other internal tasks to be performed. Finally, the importance of the general ledger, under the supervision of the ophthalmologist's accountant and in conjunction with a control procedure (employing the daily master appointment page attached to the ophthalmologist's personal worksheet) is stressed, in order to safeguard the physician's revenue.

A Data-driven Approach for Forecasting Next-day River Discharge

NASA Astrophysics Data System (ADS)

Sharif, H. O.; Billah, K. S.

2017-12-01

This study focuses on evaluating the performance of the Soil and Water Assessment Tool (SWAT) eco-hydrological model, a simple Auto-Regressive with eXogenous input (ARX) model, and a Gene expression programming (GEP)-based model in one-day-ahead forecasting of discharge of a subtropical basin (the upper Kentucky River Basin). The three models were calibrated with daily flow at the US Geological Survey (USGS) stream gauging station not affected by flow regulation for the period of 2002-2005. The calibrated models were then validated at the same gauging station as well as another USGS gauge 88 km downstream for the period of 2008-2010. The results suggest that simple models outperform a sophisticated hydrological model with GEP having the advantage of being able to generate functional relationships that allow scientific investigation of the complex nonlinear interrelationships among input variables. Unlike SWAT, GEP, and to some extent, ARX are less sensitive to the length of the calibration time series and do not require a spin-up period.

Real-time 3D reconstruction of road curvature in far look-ahead distance from analysis of image sequences

NASA Astrophysics Data System (ADS)

Behringer, Reinhold

1995-12-01

A system for visual road recognition in far look-ahead distance, implemented in the autonomous road vehicle VaMP (a passenger car), is described. Visual cues of a road in a video image are the bright lane markings and the edges formed at the road borders. In a distance of more than 100 m, the most relevant road cue is the homogeneous road area, limited by the two border edges. These cues can be detected by the image processing module KRONOS applying edge detection techniques and areal 2D segmentation based on resolution triangles (analogous to a resolution pyramid). An estimation process performs an update of a state vector, which describes spatial road shape and vehicle orientation relative to the road. This state vector is estimated every 40 ms by exploiting knowledge about the vehicle movement (spatio-temporal model of vehicle dynamics) and the road design rules (clothoidal segments). Kalman filter techniques are applied to obtain an optimal estimate of the state vector by evaluating the measurements of the road border positions in the image sequence taken by a set of CCD cameras. The road consists of segments with piecewise constant curvature parameters. The borders between these segments can be detected by applying methods which have been developed for detection of discontinuities during time-discrete measurements. The road recognition system has been tested in autonomous rides with VaMP on public Autobahnen in real traffic at speeds up to 130 km/h.

Smart Sampling and HPC-based Probabilistic Look-ahead Contingency Analysis Implementation and its Evaluation with Real-world Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yousu; Etingov, Pavel V.; Ren, Huiying

This paper describes a probabilistic look-ahead contingency analysis application that incorporates smart sampling and high-performance computing (HPC) techniques. Smart sampling techniques are implemented to effectively represent the structure and statistical characteristics of uncertainty introduced by different sources in the power system. They can significantly reduce the data set size required for multiple look-ahead contingency analyses, and therefore reduce the time required to compute them. High-performance-computing (HPC) techniques are used to further reduce computational time. These two techniques enable a predictive capability that forecasts the impact of various uncertainties on potential transmission limit violations. The developed package has been tested withmore » real world data from the Bonneville Power Administration. Case study results are presented to demonstrate the performance of the applications developed.« less

Expedition 38 Press Conference

NASA Image and Video Library

2013-11-06

Expedition 38 Flight Engineer Rick Mastracchio of NASA talks, while in quarantine behind glass, during the final press conference held a day ahead of his launch with fellow crew mates, Soyuz Commander Mikhail Tyurin of Roscosmos, and, Flight Engineer Koichi Wakata of the Japan Aerospace Exploration Agency, to the International Space Station, Wednesday, Nov. 6, 2013 at the Cosmonaut Hotel in Baikonur, Kazakhstan. Photo Credit: (NASA/Bill Ingalls)

Expedition 38 Press Conference

NASA Image and Video Library

2013-11-06

Expedition 38 Flight Engineer Koichi Wakata of the Japan Aerospace Exploration Agency is seen in quarantine, behind glass, during the final press conference held a day ahead of his launch with fellow crew mates, Expedition 38 Soyuz Commander Mikhail Tyurin of Roscosmos, and, Flight Engineer Rick Mastracchio of NASA, to the International Space Station, Wednesday, Nov. 6, 2013 at the Cosmonaut Hotel in Baikonur, Kazakhstan. Photo Credit: (NASA/Bill Ingalls)

Expedition 38 Press Conference

NASA Image and Video Library

2013-11-06

Expedition 38 Soyuz Commander Mikhail Tyurin of Roscosmos is seen in quarantine behind glass during the final press conference held a day ahead of his launch with fellow crew mates, Flight Engineer Koichi Wakata of the Japan Aerospace Exploration Agency, and, Flight Engineer Rick Mastracchio of NASA, to the International Space Station, Wednesday, Nov. 6, 2013 at the Cosmonaut Hotel in Baikonur, Kazakhstan. Photo Credit: (NASA/Bill Ingalls)

Expedition 38 Press Conference

NASA Image and Video Library

2013-11-06

Expedition 38 Soyuz Commander Mikhail Tyurin of Roscosmos, right, talks as Flight Engineer Koichi Wakata of the Japan Aerospace Exploration Agency, listens, from quarantine behind glass, during the final press conference held a day ahead of their launch with fellow crew mate, Flight Engineer Rick Mastracchio of NASA, to the International Space Station, Wednesday, Nov. 6, 2013 at the Cosmonaut Hotel in Baikonur, Kazakhstan. Photo Credit: (NASA/Bill Ingalls)

Air-Ground Teamwork on the Western Front. The Role of the XIX Tactical Air Command During August 1944

DTIC Science & Technology

1992-01-01

Several trains and a power plant were successfully attacked as far east as Troyes and Soissons. It was moving day, this time from the vicinity of...planes were seen. Flying armed reconnaissance ahead of our columns thrusting east past Sens and Troyes , P-47’s had just dropped eight 5oo-pound bombs

Underway Recovery Test 6 (URT-6) - Day 4 Afternoon Activities

NASA Image and Video Library

2018-01-20

During Underway Recovery Test 6, NASA astronaut Stephen Bowen talks with sailors about the correlations between his Navy and NASA experiences. Bowen is aboard USS Anchorage as Kennedy Space Center’s NASA Recovery Team works with the U.S. Navy to improve recovery procedures and hardware ahead of Orion's next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

An Agenda for the Future: Mapping the Terrain of California Education. Meeting 33 Summary (McClellan Park, California, June 22-23, 2017)

ERIC Educational Resources Information Center

Knudson, Joel

2017-01-01

Changes at the federal level and an upcoming California election are shaping the social, economic, and political context in which K-12 districts operate. The California Collaborative on District Reform convened for a two-day meeting to step back, reflect, and take stock of the road ahead. Meeting participants listened to research-based…

DefenseLink Special: Iraq Transition of Power Anniversary, 2005

Science.gov Websites

their hopes. They are determined to carry out a political process that will lead to a free and Iraq, and two days ahead of schedule, the world witnessed the arrival of a free and sovereign Iraqi terrorists are doing all they can to stop the rise of a free Iraq, but their bombs and attacks have not

Elaboration of Programmes, Programmes, Plans and Budgets of the National Libraries in Socialist Countries (37th Session, Liverpool, August 1971).

ERIC Educational Resources Information Center

Kanevsky, B. P.

Long-term and short-term planning and programming and budgeting are an important part of the every-day activity of the national libraries in the socialist countries. The libraries extensively apply various types of planning ranging from current annual plans to complicated prognoses for 15-20 years ahead. These libraries display increasing…

Beyond Carrots and Sticks: Toward a Transformative Model of Division I Athletics

ERIC Educational Resources Information Center

Clubb, Sandy Hatfield

2012-01-01

The old expression about the carrot and the stick, which refers to the application of reward and punishment to induce action, dates back to the days when pack mules were used for transportation. The mules would move toward carrots that dangled just ahead of them--and move all the faster because they feared drivers with sticks behind them. In 2012,…

Optimization of Methylphenidate Extended-Release Chewable Tablet Dose in Children with ADHD: Open-Label Dose Optimization in a Laboratory Classroom Study.

PubMed

Wigal, Sharon B; Childress, Ann; Berry, Sally A; Belden, Heidi W; Chappell, Phillip; Wajsbrot, Dalia B; Nagraj, Praneeta; Abbas, Richat; Palumbo, Donna

2018-06-01

To examine methylphenidate extended-release chewable tablets (MPH ERCT) dose patterns, attention-deficit/hyperactivity disorder (ADHD) symptom scores, and safety during the 6-week, open-label (OL) dose-optimization period of a phase 3, laboratory classroom study. Boys and girls (6-12 years) diagnosed with ADHD were enrolled. MPH ERCT was initiated at 20 mg/day; participants were titrated in 10-20 mg/day increments weekly based on efficacy and tolerability (maximum dose, 60 mg/day). Dose-optimization period efficacy assessments included the ADHD Rating Scale (ADHD-RS-IV), analyzed by week in a post hoc analysis using a mixed-effects model for repeated measures with final optimized dose (20, 30/40, or 50/60 mg), visit, final optimized dose and visit interaction, and baseline score as terms. Adverse events (AEs) and concomitant medications were collected throughout the study. Mean MPH ERCT daily dose increased weekly from 29.4 mg/day after the first dose adjustment at week 1 (n = 90) to 42.8 mg/day after the final adjustment at week 5 (n = 86). Final optimized MPH ERCT dose ranged from 20 to 60 mg/day. Mean final optimized MPH ERCT dose ranged from 40.0 mg/day in 6-8 year-old participants to 44.8 mg/day for 11-12 year-old participants. There was a progressive decrease in mean (standard deviation) ADHD-RS-IV total score from 40.1 (8.72) at baseline to 12.4 (7.88) at OL week 5, with similar improvement patterns for hyperactivity/impulsivity and inattentiveness subscale scores. Participants optimized to MPH ERCT 50/60 mg/day had a significantly higher mean (standard error) ADHD-RS-IV score at baseline compared with participants optimized to MPH ERCT 20 mg/day (42.4 [1.34] vs. 35.1 [2.55]; p = 0.013). Treatment-emergent AEs were reported by 65/90 (72.2%) participants in the dose-optimization period. Dose-optimization period results describing relationships between change in ADHD symptom scores and final optimized MPH ERCT dose will be valuable for clinicians optimizing MPH ERCT dose.

Let the pigeon drive the bus: pigeons can plan future routes in a room.

PubMed

Gibson, Brett; Wilkinson, Matthew; Kelly, Debbie

2012-05-01

The task of determining an optimal route to several locations is called the traveling salesperson problem (TSP). The TSP has been used recently to examine spatial cognition in humans and non-human animals. It remains unclear whether or not the decision process of animals other than non-human primates utilizes rigid rule-based heuristics, or whether non-human animals are able to flexibly 'plan' future routes/behavior based on their knowledge of multiple locations. We presented pigeons in a One-way and Round-Trip group with TSPs that included two or three destinations (feeders) in a laboratory environment. The pigeons departed a start location, traveled to each feeder once before returning to a final destination. Pigeons weighed the proximity of the next location heavily, but appeared to plan ahead multiple steps when the travel costs for inefficient behavior appeared to increase. The results provide clear and strong evidence that animals other than primates are capable of planning sophisticated travel routes.

FASTER - A tool for DSN forecasting and scheduling

NASA Technical Reports Server (NTRS)

Werntz, David; Loyola, Steven; Zendejas, Silvino

1993-01-01

FASTER (Forecasting And Scheduling Tool for Earth-based Resources) is a suite of tools designed for forecasting and scheduling JPL's Deep Space Network (DSN). The DSN is a set of antennas and other associated resources that must be scheduled for satellite communications, astronomy, maintenance, and testing. FASTER consists of MS-Windows based programs that replace two existing programs (RALPH and PC4CAST). FASTER was designed to be more flexible, maintainable, and user friendly. FASTER makes heavy use of commercial software to allow for customization by users. FASTER implements scheduling as a two pass process: the first pass calculates a predictive profile of resource utilization; the second pass uses this information to calculate a cost function used in a dynamic programming optimization step. This information allows the scheduler to 'look ahead' at activities that are not as yet scheduled. FASTER has succeeded in allowing wider access to data and tools, reducing the amount of effort expended and increasing the quality of analysis.

Prediction of optical communication link availability: real-time observation of cloud patterns using a ground-based thermal infrared camera

NASA Astrophysics Data System (ADS)

Bertin, Clément; Cros, Sylvain; Saint-Antonin, Laurent; Schmutz, Nicolas

2015-10-01

The growing demand for high-speed broadband communications with low orbital or geostationary satellites is a major challenge. Using an optical link at 1.55 μm is an advantageous solution which potentially can increase the satellite throughput by a factor 10. Nevertheless, cloud cover is an obstacle for this optical frequency. Such communication requires an innovative management system to optimize the optical link availability between a satellite and several Optical Ground Stations (OGS). The Saint-Exupery Technological Research Institute (France) leads the project ALBS (French acronym for BroadBand Satellite Access). This initiative involving small and medium enterprises, industrial groups and research institutions specialized in aeronautics and space industries, is currently developing various solutions to increase the telecommunication satellite bandwidth. This paper presents the development of a preliminary prediction system preventing the cloud blockage of an optical link between a satellite and a given OGS. An infrared thermal camera continuously observes (night and day) the sky vault. Cloud patterns are observed and classified several times a minute. The impact of the detected clouds on the optical beam (obstruction or not) is determined by the retrieval of the cloud optical depth at the wavelength of communication. This retrieval is based on realistic cloud-modelling on libRadtran. Then, using subsequent images, cloud speed and trajectory are estimated. Cloud blockage over an OGS can then be forecast up to 30 minutes ahead. With this information, the preparation of the new link between the satellite and another OGS under a clear sky can be prepared before the link breaks due to cloud blockage.

Do intensive care data on respiratory infections reflect influenza epidemics?

PubMed

Koetsier, Antonie; van Asten, Liselotte; Dijkstra, Frederika; van der Hoek, Wim; Snijders, Bianca E; van den Wijngaard, Cees C; Boshuizen, Hendriek C; Donker, Gé A; de Lange, Dylan W; de Keizer, Nicolette F; Peek, Niels

2013-01-01

Severe influenza can lead to Intensive Care Unit (ICU) admission. We explored whether ICU data reflect influenza like illness (ILI) activity in the general population, and whether ICU respiratory infections can predict influenza epidemics. We calculated the time lag and correlation between ILI incidence (from ILI sentinel surveillance, based on general practitioners (GP) consultations) and percentages of ICU admissions with a respiratory infection (from the Dutch National Intensive Care Registry) over the years 2003-2011. In addition, ICU data of the first three years was used to build three regression models to predict the start and end of influenza epidemics in the years thereafter, one to three weeks ahead. The predicted start and end of influenza epidemics were compared with observed start and end of such epidemics according to the incidence of ILI. Peaks in respiratory ICU admissions lasted longer than peaks in ILI incidence rates. Increases in ICU admissions occurred on average two days earlier compared to ILI. Predicting influenza epidemics one, two, or three weeks ahead yielded positive predictive values ranging from 0.52 to 0.78, and sensitivities from 0.34 to 0.51. ICU data was associated with ILI activity, with increases in ICU data often occurring earlier and for a longer time period. However, in the Netherlands, predicting influenza epidemics in the general population using ICU data was imprecise, with low positive predictive values and sensitivities.

Simulation of the 1994 Charlotte Microburst with Look-Ahead Windshear Radar

NASA Technical Reports Server (NTRS)

Proctor, F. H.; Bracalente, E. M.; Harrah, S. D.; Switzer, G. F.; Britt, C. L.

1995-01-01

A severe microburst occurred on 2 July 1994 at Charlotte, NC, and was associated with the crash of USAir Flight 1016 (FL-1016) (Salottolo 1994; Phillips 1994). The inbound DC-9 unexpectedly encountered a rapidly intensifying rainshaft just seconds before it was to touchdown on runway 18R. The aircraft crashed after encountering strong windshear, killing 37 of the 57 souls on board. The pilots did not recognize the windshear condition in time to prevent the accident and received no warning from the aircraft's Honeywell in-situ windshear detection system or from ground-based systems (Charlotte maintains both an ASR-9 weather radar and a Phase-2 LLWAS). Also two other aircraft landed ahead of FL-1016 without incident and reported smooth approaches to 18R. Section-2 of this paper reports briefly on the reconstruction of the event based on numerical results generated by the Terminal Area Simulation System (TASS) as presented at the National Transportation Safety Board (NTSB) public hearing (Proctor 1994). Section-3 discusses the simulation of this event with a look-ahead windshear radar.

Concepts. The Journal of Defense Systems Acquisition Management. Winter 1981. Volume 4. Number 1.

DTIC Science & Technology

1981-01-01

Long, USAF A major challenge facing the program manager is to effectively obtain and manage program funds. It is the author’s view that too few...Henry H. Mendenhall As defense systems become more and more complex, an effective test and evaluation program becomes more and more necessary. This means...that lies ahead for the military acquisition manager. And let us not think for a moment that optimism alone will suffice. Good, effective , efficient

Parallel Harmony Search Based Distributed Energy Resource Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ceylan, Oguzhan; Liu, Guodong; Tomsovic, Kevin

2015-01-01

This paper presents a harmony search based parallel optimization algorithm to minimize voltage deviations in three phase unbalanced electrical distribution systems and to maximize active power outputs of distributed energy resources (DR). The main contribution is to reduce the adverse impacts on voltage profile during a day as photovoltaics (PVs) output or electrical vehicles (EVs) charging changes throughout a day. The IEEE 123- bus distribution test system is modified by adding DRs and EVs under different load profiles. The simulation results show that by using parallel computing techniques, heuristic methods may be used as an alternative optimization tool in electricalmore » power distribution systems operation.« less

Alternative Fuels Data Center: Idaho Surges Ahead with Electric Vehicle

Science.gov Websites

Charging Idaho Surges Ahead with Electric Vehicle Charging to someone by E-mail Share Alternative Fuels Data Center: Idaho Surges Ahead with Electric Vehicle Charging on Facebook Tweet about Alternative Fuels Data Center: Idaho Surges Ahead with Electric Vehicle Charging on Twitter Bookmark

Underway Recovery Test 6 (URT-6) - Day 3 Activities

NASA Image and Video Library

2018-01-19

After a day of working with the Orion test article under rough seas, the NASA Recovery Team inspects the capsule and their lines. As part of Underway Recovery Test 6, the Orion test article was intentionally subjected to an increased sea state to ensure the team could control the spacecraft under all possible scenarios. The testing with Kennedy Space Center's NASA Recovery Team and the U.S. Navy will provide important data that is being used to improve recovery procedures and hardware ahead of Orion's next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

New Methodology for Evaluating Optimal Pricing for Primary Regulation of Deregulated Power Systems under Steady State Condition

NASA Astrophysics Data System (ADS)

Satyaramesh, P. V.; RadhaKrishna, C.

2013-06-01

A generalized pricing structure for procurement of power under frequency ancillary service is developed in this paper. It is a frequency linked-price model and suitable for deregulation market environment. This model takes into consideration: governor characteristics and frequency characteristics of generator as additional parameters in load flow method. The main objective of the new approach proposed in this paper is to establish bidding price structure for frequency regulation services in competitive ancillary electrical markets under steady state condition. Lot of literatures are available for calculating the frequency deviations with respect to load changes by using dynamic simulation methods. But in this paper, the model computes the frequency deviations for additional requirements of power under steady state with considering power system network topology. An attempt is also made in this paper to develop optimal bidding price structure for the frequency-regulated systems. It gives a signal to traders or bidders that the power demand can be assessed more accurately much closer to real time and helps participants bid more accurate quantities on day-ahead market. The recent trends of frequency linked-price model existing in Indian power systems issues required for attention are also dealt in this paper. Test calculations have been performed on 30-bus system. The paper also explains adoptability of 33 this model to practical Indian power system. The results presented are analyzed and useful conclusions are drawn.

33 CFR 164.76 - Towline and terminal gear for towing alongside and pushing ahead.

Code of Federal Regulations, 2010 CFR

2010-07-01

... towing alongside and pushing ahead. 164.76 Section 164.76 Navigation and Navigable Waters COAST GUARD... Towline and terminal gear for towing alongside and pushing ahead. The owner, master, or operator of each vessel towing alongside or pushing ahead shall ensure that the face wires, spring lines, and push gear...

Climate impacts on human livelihoods: where uncertainty matters in projections of water availability

NASA Astrophysics Data System (ADS)

Lissner, T. K.; Reusser, D. E.; Schewe, J.; Lakes, T.; Kropp, J. P.

2014-10-01

Climate change will have adverse impacts on many different sectors of society, with manifold consequences for human livelihoods and well-being. However, a systematic method to quantify human well-being and livelihoods across sectors is so far unavailable, making it difficult to determine the extent of such impacts. Climate impact analyses are often limited to individual sectors (e.g. food or water) and employ sector-specific target measures, while systematic linkages to general livelihood conditions remain unexplored. Further, recent multi-model assessments have shown that uncertainties in projections of climate impacts deriving from climate and impact models, as well as greenhouse gas scenarios, are substantial, posing an additional challenge in linking climate impacts with livelihood conditions. This article first presents a methodology to consistently measure what is referred to here as AHEAD (Adequate Human livelihood conditions for wEll-being And Development). Based on a trans-disciplinary sample of concepts addressing human well-being and livelihoods, the approach measures the adequacy of conditions of 16 elements. We implement the method at global scale, using results from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) to show how changes in water availability affect the fulfilment of AHEAD at national resolution. In addition, AHEAD allows for the uncertainty of climate and impact model projections to be identified and differentiated. We show how the approach can help to put the substantial inter-model spread into the context of country-specific livelihood conditions by differentiating where the uncertainty about water scarcity is relevant with regard to livelihood conditions - and where it is not. The results indicate that livelihood conditions are compromised by water scarcity in 34 countries. However, more often, AHEAD fulfilment is limited through other elements. The analysis shows that the water-specific uncertainty ranges of the model output are outside relevant thresholds for AHEAD for 65 out of 111 countries, and therefore do not contribute to the overall uncertainty about climate change impacts on livelihoods. In 46 of the countries in the analysis, water-specific uncertainty is relevant to AHEAD. The AHEAD method presented here, together with first results, forms an important step towards making scientific results more applicable for policy decisions.

Estimating the snowfall limit in alpine and pre-alpine valleys: A local evaluation of operational approaches

NASA Astrophysics Data System (ADS)

Fehlmann, Michael; Gascón, Estíbaliz; Rohrer, Mario; Schwarb, Manfred; Stoffel, Markus

2018-05-01

The snowfall limit has important implications for different hazardous processes associated with prolonged or heavy precipitation such as flash floods, rain-on-snow events and freezing precipitation. To increase preparedness and to reduce risk in such situations, early warning systems are frequently used to monitor and predict precipitation events at different temporal and spatial scales. However, in alpine and pre-alpine valleys, the estimation of the snowfall limit remains rather challenging. In this study, we characterize uncertainties related to snowfall limit for different lead times based on local measurements of a vertically pointing micro rain radar (MRR) and a disdrometer in the Zulg valley, Switzerland. Regarding the monitoring, we show that the interpolation of surface temperatures tends to overestimate the altitude of the snowfall limit and can thus lead to highly uncertain estimates of liquid precipitation in the catchment. This bias is much smaller in the Integrated Nowcasting through Comprehensive Analysis (INCA) system, which integrates surface station and remotely sensed data as well as outputs of a numerical weather prediction model. To reduce systematic error, we perform a bias correction based on local MRR measurements and thereby demonstrate the added value of such measurements for the estimation of liquid precipitation in the catchment. Regarding the nowcasting, we show that the INCA system provides good estimates up to 6 h ahead and is thus considered promising for operational hydrological applications. Finally, we explore the medium-range forecasting of precipitation type, especially with respect to rain-on-snow events. We show for a selected case study that the probability for a certain precipitation type in an ensemble-based forecast is more persistent than the respective type in the high-resolution forecast (HRES) of the European Centre for Medium Range Weather Forecasts Integrated Forecasting System (ECMWF IFS). In this case study, the ensemble-based forecast could be used to anticipate such an event up to 7-8 days ahead, whereas the use of the HRES is limited to a lead time of 4-5 days. For the different lead times investigated, we point out possibilities of considering uncertainties in snowfall limit and precipitation type estimates so as to increase preparedness to risk situations.

Optimizing spacecraft design - optimization engine development : progress and plans

NASA Technical Reports Server (NTRS)

Cornford, Steven L.; Feather, Martin S.; Dunphy, Julia R; Salcedo, Jose; Menzies, Tim

2003-01-01

At JPL and NASA, a process has been developed to perform life cycle risk management. This process requires users to identify: goals and objectives to be achieved (and their relative priorities), the various risks to achieving those goals and objectives, and options for risk mitigation (prevention, detection ahead of time, and alleviation). Risks are broadly defined to include the risk of failing to design a system with adequate performance, compatibility and robustness in addition to more traditional implementation and operational risks. The options for mitigating these different kinds of risks can include architectural and design choices, technology plans and technology back-up options, test-bed and simulation options, engineering models and hardware/software development techniques and other more traditional risk reduction techniques.

Underway Recovery Test 6 (URT-6) - Day 4 Activities

NASA Image and Video Library

2018-01-20

Jamie Peer, part of Kennedy Space Center’s NASA Recovery Team analyzes data from the previous day’s testing as part of Underway Recovery Test 6. The testing with the NASA Recovery Team and the U.S. Navy will provide important data that is being used to improve recovery procedures and hardware ahead of Orion's next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

Underway Recovery Test 6 (URT-6) - Day 1 Activities

NASA Image and Video Library

2018-01-17

Members of the Wave Monitoring System check their data during the Underway Recovery Test 6, or URT-6, aboard the USS Anchorage. The testing with Kennedy Space Center’s NASA Recovery Team and the U.S. Navy will provide important data that is being used to improve recovery procedures and hardware ahead of Orion’s next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

Underway Recovery Test 6 (URT-6) - Day 5 Activities

NASA Image and Video Library

2018-01-21

Navy Diver 2nd Class Laethem and his fellow divers get briefed before heading out to sea to recover the Orion test article during Underway Recovery Test 6 off the coast of San Diego. Kennedy Space Center’s NASA Recovery Team works with the U.S. Navy to improve recovery procedures and hardware ahead of Orion's next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

Tell it to someone who cares. The health care industry wants more information--and Anne Arundel Health Care Systems is giving it to them.

PubMed

Appleby, C

1995-10-20

The way to succeed in the health care industry these days is to stay ahead of the information curve. With a lot of ingenuity and a stern eye on the bottom line, Anne Arundel Health Care Systems in Maryland is doing just that. Here's how and why they did it, and how much they paid.

Predicting apricot phenology using meteorological data.

PubMed

Ruml, Mirjana; Milatović, Dragan; Vulić, Todor; Vuković, Ana

2011-09-01

The main objective of this study was to develop feasible, easy to apply models for early prediction of full flowering (FF) and maturing (MA) in apricot (Prunus armeniaca L.). Phenological data for 20 apricot cultivars grown in the Belgrade region were modeled against averages of daily temperature records over ten seasons for FF and eight seasons for MA. A much stronger correlation was found between the phenological timing and temperature at the very beginning than at the end of phenophases. Also, the length of developmental periods were better correlated to daily maximum than to daily minimum and mean air temperatures. Using prediction models based on daily maximum temperatures averaged over 30-, 45- and 60-day periods, starting from 1 January for FF prediction and from the date of FF for MA prediction, the onset of examined phenophases in apricot cultivars could be predicted from a few weeks to up to 2 months ahead with acceptable accuracy. The mean absolute differences between the observations and cross-validated predictions obtained by 30-, 45- and 60-day models were 8.6, 6.9 and 5.7 days for FF and 6.1, 3.6 and 2.8 days for MA, respectively. The validity of the results was confirmed using an independent data set for the year 2009.

Predicting apricot phenology using meteorological data

NASA Astrophysics Data System (ADS)

Ruml, Mirjana; Milatović, Dragan; Vulić, Todor; Vuković, Ana

2011-09-01

The main objective of this study was to develop feasible, easy to apply models for early prediction of full flowering (FF) and maturing (MA) in apricot ( Prunus armeniaca L.). Phenological data for 20 apricot cultivars grown in the Belgrade region were modeled against averages of daily temperature records over ten seasons for FF and eight seasons for MA. A much stronger correlation was found between the phenological timing and temperature at the very beginning than at the end of phenophases. Also, the length of developmental periods were better correlated to daily maximum than to daily minimum and mean air temperatures. Using prediction models based on daily maximum temperatures averaged over 30-, 45- and 60-day periods, starting from 1 January for FF prediction and from the date of FF for MA prediction, the onset of examined phenophases in apricot cultivars could be predicted from a few weeks to up to 2 months ahead with acceptable accuracy. The mean absolute differences between the observations and cross-validated predictions obtained by 30-, 45- and 60-day models were 8.6, 6.9 and 5.7 days for FF and 6.1, 3.6 and 2.8 days for MA, respectively. The validity of the results was confirmed using an independent data set for the year 2009.

AI techniques in geomagnetic storm forecasting

NASA Astrophysics Data System (ADS)

Lundstedt, Henrik

This review deals with how geomagnetic storms can be predicted with the use of Artificial Intelligence (AI) techniques. Today many different Al techniques have been developed, such as symbolic systems (expert and fuzzy systems) and connectionism systems (neural networks). Even integrations of AI techniques exist, so called Intelligent Hybrid Systems (IHS). These systems are capable of learning the mathematical functions underlying the operation of non-linear dynamic systems and also to explain the knowledge they have learned. Very few such powerful systems exist at present. Two such examples are the Magnetospheric Specification Forecast Model of Rice University and the Lund Space Weather Model of Lund University. Various attempts to predict geomagnetic storms on long to short-term are reviewed in this article. Predictions of a month to days ahead most often use solar data as input. The first SOHO data are now available. Due to the high temporal and spatial resolution new solar physics have been revealed. These SOHO data might lead to a breakthrough in these predictions. Predictions hours ahead and shorter rely on real-time solar wind data. WIND gives us real-time data for only part of the day. However, with the launch of the ACE spacecraft in 1997, real-time data during 24 hours will be available. That might lead to the second breakthrough for predictions of geomagnetic storms.

Reservoir water level forecasting using group method of data handling

NASA Astrophysics Data System (ADS)

Zaji, Amir Hossein; Bonakdari, Hossein; Gharabaghi, Bahram

2018-06-01

Accurately forecasted reservoir water level is among the most vital data for efficient reservoir structure design and management. In this study, the group method of data handling is combined with the minimum description length method to develop a very practical and functional model for predicting reservoir water levels. The models' performance is evaluated using two groups of input combinations based on recent days and recent weeks. Four different input combinations are considered in total. The data collected from Chahnimeh#1 Reservoir in eastern Iran are used for model training and validation. To assess the models' applicability in practical situations, the models are made to predict a non-observed dataset for the nearby Chahnimeh#4 Reservoir. According to the results, input combinations (L, L -1) and (L, L -1, L -12) for recent days with root-mean-squared error (RMSE) of 0.3478 and 0.3767, respectively, outperform input combinations (L, L -7) and (L, L -7, L -14) for recent weeks with RMSE of 0.3866 and 0.4378, respectively, with the dataset from https://www.typingclub.com/st. Accordingly, (L, L -1) is selected as the best input combination for making 7-day ahead predictions of reservoir water levels.

Silicate phosphors and white LED technology: improvements and opportunities

NASA Astrophysics Data System (ADS)

Sommer, Christian; Wenzl, Franz P.; Hartmann, Paul; Pachler, Peter; Schweighart, Marko; Leising, Guenther; Tasch, Stefan

2007-09-01

With the advent of a new generation of high brightness LEDs especially in the blue spectral range, white light technology based on phosphor conversion gains maturity for a successful penetration of, e.g., the general lighting market within the next years. Major challenges ahead are originating from the specific demands of the markets on small emission areas, highest possible intensities, long-term color stability, and spatial homogeneity of color coordinates. The LED industry more or less relies on the conversion phosphor classes of YAG, Sulfates, and Silicates, embedded in silicone matrices. A number of conformal coating technologies are in use. The optimization of the coating geometries with the help of software simulation offers a high potential for increased angular color homogeneity and high package densities, especially when secondary optics is in use. We report on recent progress in simulating parameters for improved white LEDs manufactured by coating technologies.

Ultra-fast consensus of discrete-time multi-agent systems with multi-step predictive output feedback

NASA Astrophysics Data System (ADS)

Zhang, Wenle; Liu, Jianchang

2016-04-01

This article addresses the ultra-fast consensus problem of high-order discrete-time multi-agent systems based on a unified consensus framework. A novel multi-step predictive output mechanism is proposed under a directed communication topology containing a spanning tree. By predicting the outputs of a network several steps ahead and adding this information into the consensus protocol, it is shown that the asymptotic convergence factor is improved by a power of q + 1 compared to the routine consensus. The difficult problem of selecting the optimal control gain is solved well by introducing a variable called convergence step. In addition, the ultra-fast formation achievement is studied on the basis of this new consensus protocol. Finally, the ultra-fast consensus with respect to a reference model and robust consensus is discussed. Some simulations are performed to illustrate the effectiveness of the theoretical results.

Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions.

PubMed

Brooks, Logan C; Farrow, David C; Hyun, Sangwon; Tibshirani, Ryan J; Rosenfeld, Roni

2018-06-15

Accurate and reliable forecasts of seasonal epidemics of infectious disease can assist in the design of countermeasures and increase public awareness and preparedness. This article describes two main contributions we made recently toward this goal: a novel approach to probabilistic modeling of surveillance time series based on "delta densities", and an optimization scheme for combining output from multiple forecasting methods into an adaptively weighted ensemble. Delta densities describe the probability distribution of the change between one observation and the next, conditioned on available data; chaining together nonparametric estimates of these distributions yields a model for an entire trajectory. Corresponding distributional forecasts cover more observed events than alternatives that treat the whole season as a unit, and improve upon multiple evaluation metrics when extracting key targets of interest to public health officials. Adaptively weighted ensembles integrate the results of multiple forecasting methods, such as delta density, using weights that can change from situation to situation. We treat selection of optimal weightings across forecasting methods as a separate estimation task, and describe an estimation procedure based on optimizing cross-validation performance. We consider some details of the data generation process, including data revisions and holiday effects, both in the construction of these forecasting methods and when performing retrospective evaluation. The delta density method and an adaptively weighted ensemble of other forecasting methods each improve significantly on the next best ensemble component when applied separately, and achieve even better cross-validated performance when used in conjunction. We submitted real-time forecasts based on these contributions as part of CDC's 2015/2016 FluSight Collaborative Comparison. Among the fourteen submissions that season, this system was ranked by CDC as the most accurate.

Improving Agent Bidding in Power Stock Markets through a Data Mining Enhanced Agent Platform

NASA Astrophysics Data System (ADS)

Chrysopoulos, Anthony C.; Symeonidis, Andreas L.; Mitkas, Pericles A.

Like in any other auctioning environment, entities participating in Power Stock Markets have to compete against other in order to maximize own revenue. Towards the satisfaction of their goal, these entities (agents - human or software ones) may adopt different types of strategies - from na?ve to extremely complex ones - in order to identify the most profitable goods compilation, the appropriate price to buy or sell etc, always under time pressure and auction environment constraints. Decisions become even more difficult to make in case one takes the vast volumes of historical data available into account: goods’ prices, market fluctuations, bidding habits and buying opportunities. Within the context of this paper we present Cassandra, a multi-agent platform that exploits data mining, in order to extract efficient models for predicting Power Settlement prices and Power Load values in typical Day-ahead Power markets. The functionality of Cassandra is discussed, while focus is given on the bidding mechanism of Cassandra’s agents, and the way data mining analysis is performed in order to generate the optimal forecasting models. Cassandra has been tested in a real-world scenario, with data derived from the Greek Energy Stock market.

ReEDS-Mexico: A Capacity Expansion Model of the Mexican Power System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ho, Jonathan L; Cole, Wesley J; Spyrou, Evangelia

This report documents the ReEDS-Mexico capacity expansion model, which is an extension of the ReEDS model to the Mexican power system. In recent years Mexico’s power sector has undergone considerable reform that has significant potential to impact the future electricity mix (Alpizar–Castro and Rodríguez–Monroy 2016). Day-ahead and real-time trading in Mexico’s power markets opened in early 2016. In addition to this reform, Mexico is striving to ensure that 35% of its electricity is generated from clean energy sources by 2024, 40% by 2035, and 50% by 2050 (Presidencia de la República 2016). These rapid changes in both the market andmore » the generation mix create a need for robust tools that can help electricity sector stakeholders make informed decisions. The purpose of this report is to document the extension of the National Renewable Energy Laboratory’s (NREL’s) Regional Energy Deployment System (ReEDS) model (Eurek et al. 2016) to cover the Mexico power system. This extension, which we will refer to throughout this paper as ReEDS-Mexico, provides a model of the Mexico power sector using a system-wide, least-cost optimization framework.« less

Ionospheric ion temperature forecasting in multiples of 27 days

NASA Astrophysics Data System (ADS)

Sojka, Jan J.; Schunk, Robert W.; Nicolls, Michael J.

2014-03-01

The ionospheric variability found at auroral locations is usually assumed to be unpredictable. The magnetosphere, which drives this ionospheric variability via storms and substorms, is at best only qualitatively describable. In this study we demonstrate that over a 3 year period, ionospheric variability observed from Poker Flat, Alaska, has, in fact, a high degree of long-term predictability. The observations used in this study are (a) the solar wind high speed stream velocity measured by the NASA Advanced Composition Explorer satellite, used to define the corotating interaction region (CIR), and (b) the ion temperature at 300 km altitude measured by the National Science Foundation Poker Flat Incoherent Scatter Radar over Poker Flat, Alaska. After determining a seasonal and diurnal climatology for the ion temperature, we show that the residual ion temperature heating events occur synchronously with CIR-geospace interactions. Furthermore, we demonstrate examples of ion temperature forecasting at 27, 54, and 81 days. A rudimentary operational forecasting scenario is described for forecasting recurrence 27 days ahead for the CIR-generated geomagnetic storms. These forecasts apply specifically to satellite tracking operations (thermospheric drag) and emergency HF-radio communications (ionospheric modifications) in the polar regions. The forecast is based on present-day solar and solar wind observations that can be used to uniquely identify the coronal hole and its CIR. From this CIR epoch, a 27 day forecast is then made.

Use of scatterometry for resist process control

NASA Astrophysics Data System (ADS)

Bishop, Kenneth P.; Milner, Lisa-Michelle; Naqvi, S. Sohail H.; McNeil, John R.; Draper, B. L.

1992-06-01

The formation of resist lines having submicron critical dimensions (CDs) is a complex multistep process, requiring precise control of each processing step. Optimization of parameters for each processing step may be accomplished through theoretical modeling techniques and/or the use of send-ahead wafers followed by scanning electron microscope measurements. Once the optimum parameters for any process having been selected, (e.g., time duration and temperature for post-exposure bake process), no in-situ CD measurements are made. In this paper we describe the use of scatterometry to provide this essential metrology capability. It involves focusing a laser beam on a periodic grating and predicting the shape of the grating lines from a measurement of the scattered power in the diffraction orders. The inverse prediction of lineshape from a measurement of the scatter power is based on a vector diffraction analysis used in conjunction with photolithography simulation tools to provide an accurate scatter model for latent image gratings. This diffraction technique has previously been applied to looking at latent image grating formation, as exposure is taking place. We have broadened the scope of the application and consider the problem of determination of optimal focus.

Dynamic Portfolio Strategy Using Clustering Approach

PubMed Central

Lu, Ya-Nan; Li, Sai-Ping; Jiang, Xiong-Fei; Zhong, Li-Xin; Qiu, Tian

2017-01-01

The problem of portfolio optimization is one of the most important issues in asset management. We here propose a new dynamic portfolio strategy based on the time-varying structures of MST networks in Chinese stock markets, where the market condition is further considered when using the optimal portfolios for investment. A portfolio strategy comprises two stages: First, select the portfolios by choosing central and peripheral stocks in the selection horizon using five topological parameters, namely degree, betweenness centrality, distance on degree criterion, distance on correlation criterion and distance on distance criterion. Second, use the portfolios for investment in the investment horizon. The optimal portfolio is chosen by comparing central and peripheral portfolios under different combinations of market conditions in the selection and investment horizons. Market conditions in our paper are identified by the ratios of the number of trading days with rising index to the total number of trading days, or the sum of the amplitudes of the trading days with rising index to the sum of the amplitudes of the total trading days. We find that central portfolios outperform peripheral portfolios when the market is under a drawup condition, or when the market is stable or drawup in the selection horizon and is under a stable condition in the investment horizon. We also find that peripheral portfolios gain more than central portfolios when the market is stable in the selection horizon and is drawdown in the investment horizon. Empirical tests are carried out based on the optimal portfolio strategy. Among all possible optimal portfolio strategies based on different parameters to select portfolios and different criteria to identify market conditions, 65% of our optimal portfolio strategies outperform the random strategy for the Shanghai A-Share market while the proportion is 70% for the Shenzhen A-Share market. PMID:28129333

Dynamic Portfolio Strategy Using Clustering Approach.

PubMed

Ren, Fei; Lu, Ya-Nan; Li, Sai-Ping; Jiang, Xiong-Fei; Zhong, Li-Xin; Qiu, Tian

2017-01-01

The problem of portfolio optimization is one of the most important issues in asset management. We here propose a new dynamic portfolio strategy based on the time-varying structures of MST networks in Chinese stock markets, where the market condition is further considered when using the optimal portfolios for investment. A portfolio strategy comprises two stages: First, select the portfolios by choosing central and peripheral stocks in the selection horizon using five topological parameters, namely degree, betweenness centrality, distance on degree criterion, distance on correlation criterion and distance on distance criterion. Second, use the portfolios for investment in the investment horizon. The optimal portfolio is chosen by comparing central and peripheral portfolios under different combinations of market conditions in the selection and investment horizons. Market conditions in our paper are identified by the ratios of the number of trading days with rising index to the total number of trading days, or the sum of the amplitudes of the trading days with rising index to the sum of the amplitudes of the total trading days. We find that central portfolios outperform peripheral portfolios when the market is under a drawup condition, or when the market is stable or drawup in the selection horizon and is under a stable condition in the investment horizon. We also find that peripheral portfolios gain more than central portfolios when the market is stable in the selection horizon and is drawdown in the investment horizon. Empirical tests are carried out based on the optimal portfolio strategy. Among all possible optimal portfolio strategies based on different parameters to select portfolios and different criteria to identify market conditions, 65% of our optimal portfolio strategies outperform the random strategy for the Shanghai A-Share market while the proportion is 70% for the Shenzhen A-Share market.

A Systematic Multi-Time Scale Solution for Regional Power Grid Operation

NASA Astrophysics Data System (ADS)

Zhu, W. J.; Liu, Z. G.; Cheng, T.; Hu, B. Q.; Liu, X. Z.; Zhou, Y. F.

2017-10-01

Many aspects need to be taken into consideration in a regional grid while making schedule plans. In this paper, a systematic multi-time scale solution for regional power grid operation considering large scale renewable energy integration and Ultra High Voltage (UHV) power transmission is proposed. In the time scale aspect, we discuss the problem from month, week, day-ahead, within-day to day-behind, and the system also contains multiple generator types including thermal units, hydro-plants, wind turbines and pumped storage stations. The 9 subsystems of the scheduling system are described, and their functions and relationships are elaborated. The proposed system has been constructed in a provincial power grid in Central China, and the operation results further verified the effectiveness of the system.

Tracking in a ground-to-satellite optical link: effects due to lead-ahead and aperture mismatch, including temporal tracking response.

PubMed

Basu, Santasri; Voelz, David

2008-07-01

Establishing a link between a ground station and a geosynchronous orbiting satellite can be aided greatly with the use of a beacon on the satellite. A tracker, or even an adaptive optics system, can use the beacon during communication or tracking activities to correct beam pointing for atmospheric turbulence and mount jitter effects. However, the pointing lead-ahead required to illuminate the moving object and an aperture mismatch between the tracking and the pointing apertures can limit the effectiveness of the correction, as the sensed tilt will not be the same as the tilt required for optimal transmission to the satellite. We have developed an analytical model that addresses the combined impact of these tracking issues in a ground-to-satellite optical link. We present these results for different tracker/pointer configurations. By setting the low-pass cutoff frequency of the tracking servo properly, the tracking errors can be minimized. The analysis considers geosynchronous Earth orbit satellites as well as low Earth orbit satellites.

Control of nonlinear systems represented in quasilinear form. Ph.D. Thesis, 1994 Final Report

NASA Technical Reports Server (NTRS)

Coetsee, Josef A.

1993-01-01

Methods to synthesize controllers for nonlinear systems are developed by exploiting the fact that under mild differentiability conditions, systems of the form: x-dot = f(x) + G(x)u can be represented in quasilinear form, viz: x-dot = A(x)x + B(x)u. Two classes of control methods are investigated. The first is zero-look-ahead control, where the control input depends only on the current values of A(x) and B(x). For this case the control input is computed by continuously solving a matrix Riccati equation as the system progresses along a trajectory. The second is controllers with look-ahead, where the control input depends on the future behavior of A(x) and B(x). These controllers use the similarity between quasilinear systems and linear time varying systems to find approximate solutions to optimal control type problems. The methods that are developed are not guaranteed to be globally stable. However in simulation studies they were found to be useful alternatives for synthesizing control laws for a general class of nonlinear systems.

Development and preliminary validation of a leadership competency instrument for existing and emerging allied health professional leaders.

PubMed

Ang, Hui-Gek; Koh, Jeremy Meng-Yeow; Lee, Jeffrey; Pua, Yong-Hao

2016-02-19

No instruments, to our knowledge, exist to assess leadership competency in existing and emerging allied health professional (AHP) leaders. This paper describes the development and preliminary exploration of the psychometric properties of a leadership competency instrument for existing and emerging AHP leaders and examines (i) its factor structure, (ii) its convergent validity with the Leadership Practices Inventory (LPI), and (iii) its discriminative validity in AHPs with different grades. During development, we included 25 items in the AHEAD (Aspiring leaders in Healthcare-Empowering individuals, Achieving excellence, Developing talents) instrument. A cross-sectional study was then conducted in 106 high-potential AHPs from Singapore General Hospital (34 men and 72 women) of different professional grades (49 principal-grade AHPs, 41 senior-grade AHPs, and 16 junior-grade AHPs) who completed both AHEAD and LPI instruments. Exploratory factor analysis was used to test the theoretical structure of AHEAD. Spearman correlation analysis was performed to evaluate the convergent validity of AHEAD with LPI. Using proportional odds regression models, we evaluated the association of grades of AHPs with AHEAD and LPI. To assess discriminative validity, the c-statistics - a measure of discrimination - were derived from these ordinal models. As theorized, factor analysis suggested a two-factor solution, where "skills" and "values" formed separate factors. Internal consistency of AHEAD was excellent (α-values > 0.88). Total and component AHEAD and LPI scores correlated moderately (Spearman ρ-values, 0.37 to 0.58). The c-index for discriminating between AHP grades was higher for AHEAD than for the LPI (0.76 vs. 0.65). The factorial structure of AHEAD was generally supported in our study. AHEAD showed convergent validity with the LPI and outperformed the LPI in terms of discriminative validity. These results provide initial evidence for the use of AHEAD to assess leadership competency in AHPs.

Multi-time Scale Coordination of Distributed Energy Resources in Isolated Power Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayhorn, Ebony; Xie, Le; Butler-Purry, Karen

2016-03-31

In isolated power systems, including microgrids, distributed assets, such as renewable energy resources (e.g. wind, solar) and energy storage, can be actively coordinated to reduce dependency on fossil fuel generation. The key challenge of such coordination arises from significant uncertainty and variability occurring at small time scales associated with increased penetration of renewables. Specifically, the problem is with ensuring economic and efficient utilization of DERs, while also meeting operational objectives such as adequate frequency performance. One possible solution is to reduce the time step at which tertiary controls are implemented and to ensure feedback and look-ahead capability are incorporated tomore » handle variability and uncertainty. However, reducing the time step of tertiary controls necessitates investigating time-scale coupling with primary controls so as not to exacerbate system stability issues. In this paper, an optimal coordination (OC) strategy, which considers multiple time-scales, is proposed for isolated microgrid systems with a mix of DERs. This coordination strategy is based on an online moving horizon optimization approach. The effectiveness of the strategy was evaluated in terms of economics, technical performance, and computation time by varying key parameters that significantly impact performance. The illustrative example with realistic scenarios on a simulated isolated microgrid test system suggests that the proposed approach is generalizable towards designing multi-time scale optimal coordination strategies for isolated power systems.« less

Direct numerical simulation of the effect of an electric field on flame stability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Belhi, Memdouh; Domingo, Pascale; Vervisch, Pierre

2010-12-15

The role of electric fields in stabilising combustion is a well-known phenomenon. Among the possible mechanisms favouring the anchorage of the flame base, the ion-driven wind acting directly on flow momentum ahead of the flame base could be the leading one. Direct numerical simulation has been used to verify this hypothesis and lead to a better understanding of diffusion flame base anchoring in the presence of an externally applied voltage. In this context, a simplified modelling approach is proposed to describe combustion in the presence of electric body forces. The model reproduces the tendencies of experimental observations found in themore » literature. The sensitivity of the flame lift-off height to the applied voltage is studied and the modification of the velocity field ahead of the flame base induced by the electric volume forces is highlighted. (author)« less

Motorcycle Drag Reduction using a Streamlined Object Ahead of the Rider

NASA Astrophysics Data System (ADS)

Selvamuthu, Thirukumaran; Thangadurai, Murugan

2018-05-01

Aerodynamics design of various components plays a significant role in reducing the overall drag of the vehicle to improve the fuel efficiency. In the present study, the effects of a semi-ellipsoidal structure placed ahead of a rider on the HONDA CBR 600 RR bike have been studied in detail for Reynolds number varying from 1.24 to 3.72 million. Three-dimensional numerical simulations were performed by solving the Reynolds averaged Navier-Stokes equations with the SST k-ω turbulence model. The numerical results were validated with the wind tunnel testing performed on a 1:12 scale down model using an external pyramidal balance. It has been observed that the wake pattern behind the vehicle, pressure and velocity distribution over the vehicle were modified remarkably by the inclusion of semi-ellipsoidal structure compared to the model with the rider. The drag coefficient of the bike was increased about 16% by placing a dummy rider over the vehicle. However, it decreased substantially and reached close to the base model value when the semi-ellipsoidal structure placed ahead of the rider. Further, the inclusion of semi-ellipsoidal structure produced a negative lift which improves the traction on the road compared to the base model.

Multi-step-ahead crude oil price forecasting using a hybrid grey wave model

NASA Astrophysics Data System (ADS)

Chen, Yanhui; Zhang, Chuan; He, Kaijian; Zheng, Aibing

2018-07-01

Crude oil is crucial to the operation and economic well-being of the modern society. Huge changes of crude oil price always cause panics to the global economy. There are many factors influencing crude oil price. Crude oil price prediction is still a difficult research problem widely discussed among researchers. Based on the researches on Heterogeneous Market Hypothesis and the relationship between crude oil price and macroeconomic factors, exchange market, stock market, this paper proposes a hybrid grey wave forecasting model, which combines Random Walk (RW)/ARMA to forecast multi-step-ahead crude oil price. More specifically, we use grey wave forecasting model to model the periodical characteristics of crude oil price and ARMA/RW to simulate the daily random movements. The innovation also comes from using the information of the time series graph to forecast crude oil price, since grey wave forecasting is a graphical prediction method. The empirical results demonstrate that based on the daily data of crude oil price, the hybrid grey wave forecasting model performs well in 15- to 20-step-ahead prediction and it always dominates ARMA and Random Walk in correct direction prediction.

Text-to-phonemic transcription and parsing into mono-syllables of English text

NASA Astrophysics Data System (ADS)

Jusgir Mullick, Yugal; Agrawal, S. S.; Tayal, Smita; Goswami, Manisha

2004-05-01

The present paper describes a program that converts the English text (entered through the normal computer keyboard) into its phonemic representation and then parses it into mono-syllables. For every letter a set of context based rules is defined in lexical order. A default rule is also defined separately for each letter. Beginning from the first letter of the word the rules are checked and the most appropriate rule is applied on the letter to find its actual orthographic representation. If no matching rule is found, then the default rule is applied. Current rule sets the next position to be analyzed. Proceeding in the same manner orthographic representation for each word can be found. For example, ``reading'' is represented as ``rEdiNX'' by applying the following rules: r-->r move 1 position ahead ead-->Ed move 3 position ahead i-->i move 1 position ahead ng-->NX move 2 position ahead, i.e., end of word. The phonemic representations obtained from the above procedure are parsed to get mono-syllabic representation for various combinations such as CVC, CVCC, CV, CVCVC, etc. For example, the above phonemic representation will be parsed as rEdiNX---> /rE/ /diNX/. This study is a part of developing TTS for Indian English.

A Substance Exchanger-Based Bioreactor Culture of Pig Discs for Studying the Immature Nucleus Pulposus.

PubMed

Li, Pei; Gan, Yibo; Wang, Haoming; Xu, Yuan; Song, Lei; Wang, Liyuan; Ouyang, Bin; Zhou, Qiang

2017-11-01

Various research models have been developed to study the biology of disc cells. Recently, the adult disc nucleus pulposus (NP) has been well studied. However, the immature NP is underinvestigated due to a lack of a suitable model. This study aimed to establish an organ culture of immature porcine disc by optimizing culture conditions and using a self-developed substance exchanger-based bioreactor. Immature porcine discs were first cultured in the bioreactor for 7 days at various levels of glucose (low, medium, high), osmolarity (hypo-, iso-, hyper-) and serum (5, 10, 20%) to determine the respective optimal level. The porcine discs were then cultured under the optimized conditions in the novel bioreactor, and were compared with fresh discs at day 14. For high-glucose, iso-osmolarity, or 10% serum, cell viability, the gene expression profile (for anabolic genes and catabolic genes), and glycosaminoglycan (GAG) and hydroxyproline (HYP) contents were more favorable than for other levels of glucose, osmolarity, and serum. When the immature discs were cultured under the optimized conditions using the novel bioreactor for 14 days, the viability of the immature NP was maintained based on histology, cell viability, GAG and HYP contents, and matrix molecule expression. In conclusion, the viability of the immature NP in organ culture could be maintained under the optimized culture conditions (high-glucose, iso-osmolarity, and 10% serum) in the substance exchanger-based bioreactor. © 2017 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Expedition 38 Press Conference

NASA Image and Video Library

2013-11-06

Expedition 38 backup crew member Reid Wiseman of NASA is seen in quarantine, behind glass, during the final press conference held a day ahead of the launch of Expedition 38 prime crew members; Flight Engineer Koichi Wakata of the Japan Aerospace Exploration Agency, Soyuz Commander Mikhail Tyurin of Roscosmos, and, Flight Engineer Rick Mastracchio of NASA, to the International Space Station, Wednesday, Nov. 6, 2013 at the Cosmonaut Hotel in Baikonur, Kazakhstan. Photo Credit: (NASA/Bill Ingalls)

KSC-2009-3310

NASA Image and Video Library

2009-05-28

CAPE CANAVERAL, Fla. – Guests at the annual Community Leaders Breakfast held in the Debus Center at Kennedy Space Center's Visitor Complex enjoy reminiscing about the early days of the Space Shuttle Program with Center Director Bob Cabana, far right on stage. Community leaders, business executives, educators, community organizers and state and local government heard Cabana provide an overview of operations at the space center and a look ahead at upcoming missions and activities. Photo credit: NASA/Kim Shiflett

Underway Recovery Test 6 (URT-6) - Day 6 Activities

NASA Image and Video Library

2018-01-22

During Underway Recovery Test 6, Kennedy Space Center's NASA Recovery Team spent a week aboard the USS Anchorage where they and the U.S. Navy tested procedures and ground support equipment to improve recovery procedures and hardware ahead of Orion's next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean. The Orion test article sits inside the well deck of the USS Anchorage after a successful recovery test.

Underway Recovery Test 6 (URT-6) - Day 6 Activities

NASA Image and Video Library

2018-01-22

During Underway Recovery Test 6, NASA Recovery Director Melissa Jones and astronaut Stephen Bowen discuss how the recovery operations of Orion might impact astronauts onboard after spending weeks in microgravity. The testing with Kennedy Space Center's NASA Recovery Team and the U.S. Navy will provide important data that is being used to improve recovery procedures and hardware ahead of Orion's next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

Overview of Wholesale Electricity Markets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Milligan, Michael; Bloom, Aaron P; Cochran, Jaquelin M

This chapter provides a comprehensive review of four key electricity markets: energy markets (day-ahead and real-time markets); ancillary service markets; financial transmission rights markets; capacity markets. It also discusses how the outcomes of each of these markets may be impacted by the introduction of high penetrations of variable generation. Furthermore, the chapter examines considerations needed to ensure that wholesale market designs are inclusive of emerging technologies, such as demand response, distributed generation, and distributed storage.

Remarks of Ernest L. Boyer, U.S. Commissioner of Education at the 1978 Convention of the American Vocational Association, Dallas, Texas, Saturday, December 2, 1978.

ERIC Educational Resources Information Center

Boyer, Ernest L.

Dan Dunham, my Deputy Commissioner, and I agreed on six top priorities for occupational and adult education to guide our administration in the days ahead. First, we agreed that we must continue to expand access. Second, we must have equity of opportunity. Third, we must develop better accountability and data systems in vocational education. As a…

Day Care Centers for Seniors in Singapore: Looking Back and Looking Ahead.

PubMed

Liu, Germaine; Yap, Philip; Wong, Gabriel H Z; Wei, Heng Xiao; Hua, Ee Chye

2015-07-01

The burden of care for frail elderly persons on families and the society is ever real as our population ages. Given the dual-income nature of many working families, day care centers offer a strong alternative to nursing homes for families wishing to provide custodial care and meaningful engagement for seniors while continuing to uphold their filial duties. Recognizing this, several initiatives, such as SPICE (Singapore Programme for Integrated Care for the Elderly) and Weekend Respite Care, have been launched to enhance the services of Singapore's day care centers. This article traces the evolution of this process, distills current challenges, and offers policy recommendations to improve Singapore's day care services for seniors. Copyright © 2015 AMDA - The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Simulated Annealing Based Hybrid Forecast for Improving Daily Municipal Solid Waste Generation Prediction

PubMed Central

Song, Jingwei; He, Jiaying; Zhu, Menghua; Tan, Debao; Zhang, Yu; Ye, Song; Shen, Dingtao; Zou, Pengfei

2014-01-01

A simulated annealing (SA) based variable weighted forecast model is proposed to combine and weigh local chaotic model, artificial neural network (ANN), and partial least square support vector machine (PLS-SVM) to build a more accurate forecast model. The hybrid model was built and multistep ahead prediction ability was tested based on daily MSW generation data from Seattle, Washington, the United States. The hybrid forecast model was proved to produce more accurate and reliable results and to degrade less in longer predictions than three individual models. The average one-week step ahead prediction has been raised from 11.21% (chaotic model), 12.93% (ANN), and 12.94% (PLS-SVM) to 9.38%. Five-week average has been raised from 13.02% (chaotic model), 15.69% (ANN), and 15.92% (PLS-SVM) to 11.27%. PMID:25301508

Three-Stage Production Cost Modeling Approach for Evaluating the Benefits of Intra-Hour Scheduling between Balancing Authorities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Samaan, Nader A.; Milligan, Michael; Hunsaker, Matthew

This paper introduces a Production Cost Modeling (PCM) approach to evaluate the benefits of intra-hour scheduling between Balancing Authorities (BAs). The system operation is modeled in a three-stage sequential manner: day ahead (DA)-hour ahead (HA)-real time (RT). In addition to contingency reserve, each BA will need to carry out “up” and “down” load following and regulation reserve capacity requirements in the DA and HA time frames. In the real-time simulation, only contingency and regulation reserves are carried out as load following is deployed. To model current real-time operation with hourly schedules, a new constraint was introduced to force each BAmore » net exchange schedule deviation from HA schedules to be within NERC ACE limits. Case studies that investigate the benefits of moving from hourly exchange schedules between WECC BAs into 10-min exchange schedules under two different levels of wind and solar penetration (11% and 33%) are presented.« less

Three-Stage Production Cost Modeling Approach for Evaluating the Benefits of Intra-Hour Scheduling Between Balancing Authorities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Samaan, Nader; Milligan, Michael; Hunsaker, Matt

This paper introduces a production cost modeling approach for evaluating the benefits of intra-hour scheduling among Balancing Authorities (BAs). System operation is modeled in a three-stage sequential manner: day ahead (DA)-hour ahead (HA) real time (RT). In addition to contingency reserve, each BA will need to carry out 'up' and 'down' load following and regulation reserve capacity requirements in the DA and HA time frames. In the RT simulation, only contingency and regulation reserves are carried out as load following is deployed. To model current RT operation with hourly schedules, a new constraint was introduced to force each BA netmore » exchange schedule deviation from HA schedules to be within North American Electric Reliability Corporation (NERC) area control error (ACE) limits. Case studies that investigate the benefits of moving from hourly exchange schedules between Western Electricity Coordinating Council (WECC) BAs into 10-minute exchange schedules under two different levels of wind and solar penetration (11% and 33%) are presented.« less

Leveraging Trauma Lessons from War to Win in a Complex Global Environment.

PubMed

Remick, Kyle N

2016-01-01

The US military has made great strides in combat casualty care since 2001. As the Army concludes combat operations in Iraq and Afghanistan, it faces new operational challenges in trauma care. The military medical community must stay ahead of the curve through sustaining current investments in combat casualty care research. This article describes lessons learned at war from a Joint Trauma System perspective in order to place in context how we should proceed in order to provide optimal care for our Warfighters in the future.

USS Anchorage Leaves Port for Launch of Orion

NASA Image and Video Library

2014-12-01

The USNS Salvor, a safeguard-class rescue and salvage ship, is docked at Naval Base San Diego in California. The ship will head out to sea along with the USS Anchorage ahead of Orion's first flight test. NASA and U.S. Navy personnel are making preparations ahead of Orion's flight test for recovery of the crew module, forward bay cover and parachutes on its return from space and splashdown in the Pacific Ocean. If needed, the Salvor would be used for an alternate recovery method. Ground Systems Development and Operations Program is leading the recovery efforts.

Optimal use of modern antibiotics: emerging trends.

PubMed

Polk, R

1999-08-01

Development of new antimicrobial drugs is an essential component in the effort to remain ahead of emerging microbial resistance. However, when new antibiotics are used with unrestrained enthusiasm, a predictable consequence is the further expansion of resistance. This problem is well known to the infectious diseases specialist and is increasingly appreciated by the nonspecialist and the public. A far more sensible strategy is to identify new ways to use these drugs to increase the duration of their usefulness. New methods to optimize antibiotic selection, dose, and duration of therapy are being investigated, and application of some of these strategies has been shown to have a favorable impact on resistance. Much of the classic thinking of how to use antibiotics is changing, and these newer strategies may result in prolongation of the era of the "antibiotic miracle."

Comparative Analysis of NOAA REFM and SNB3GEO Tools for the Forecast of the Fluxes of High-Energy Electrons at GEO

NASA Technical Reports Server (NTRS)

Balikhin, M. A.; Rodriguez, J. V.; Boynton, R. J.; Walker, S. N.; Aryan, Homayon; Sibeck, D. G.; Billings, S. A.

2016-01-01

Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1. The high reliability of this forecasting tool serves as a benchmark for the assessment of other forecasting tools. Since 2012 the Sheffield SNB3GEO model has been operating online, providing a 24 h ahead forecast of the same fluxes. In addition to solar wind speed, the SNB3GEO forecasts use solar wind density and interplanetary magnetic field B(sub z) observations at L1. The period of joint operation of both of these forecasts has been used to compare their accuracy. Daily averaged measurements of electron fluxes by GOES 13 have been used to estimate the prediction efficiency of both forecasting tools. To assess the reliability of both models to forecast infrequent events of very high fluxes, the Heidke skill score was employed. The results obtained indicate that SNB3GEO provides a more accurate 1 day ahead forecast when compared to REFM. It is shown that the correction methodology utilized by REFM potentially can improve the SNB3GEO forecast.

Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables

NASA Astrophysics Data System (ADS)

Mortensen, Eric; Wu, Shu; Notaro, Michael; Vavrus, Stephen; Montgomery, Rob; De Piérola, José; Sánchez, Carlos; Block, Paul

2018-01-01

Located at a complex topographic, climatic, and hydrologic crossroads, southern Peru is a semiarid region that exhibits high spatiotemporal variability in precipitation. The economic viability of the region hinges on this water, yet southern Peru is prone to water scarcity caused by seasonal meteorological drought. Meteorological droughts in this region are often triggered during El Niño episodes; however, other large-scale climate mechanisms also play a noteworthy role in controlling the region's hydrologic cycle. An extensive season-ahead precipitation prediction model is developed to help bolster the existing capacity of stakeholders to plan for and mitigate deleterious impacts of drought. In addition to existing climate indices, large-scale climatic variables, such as sea surface temperature, are investigated to identify potential drought predictors. A principal component regression framework is applied to 11 potential predictors to produce an ensemble forecast of regional January-March precipitation totals. Model hindcasts of 51 years, compared to climatology and another model conditioned solely on an El Niño-Southern Oscillation index, achieve notable skill and perform better for several metrics, including ranked probability skill score and a hit-miss statistic. The information provided by the developed model and ancillary modeling efforts, such as extending the lead time of and spatially disaggregating precipitation predictions to the local level as well as forecasting the number of wet-dry days per rainy season, may further assist regional stakeholders and policymakers in preparing for drought.

Comparative analysis of NOAA REFM and SNB3GEO tools for the forecast of the fluxes of high-energy electrons at GEO.

PubMed

Balikhin, M A; Rodriguez, J V; Boynton, R J; Walker, S N; Aryan, H; Sibeck, D G; Billings, S A

2016-01-01

Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1. The high reliability of this forecasting tool serves as a benchmark for the assessment of other forecasting tools. Since 2012 the Sheffield SNB 3 GEO model has been operating online, providing a 24 h ahead forecast of the same fluxes. In addition to solar wind speed, the SNB 3 GEO forecasts use solar wind density and interplanetary magnetic field B z observations at L1.The period of joint operation of both of these forecasts has been used to compare their accuracy. Daily averaged measurements of electron fluxes by GOES 13 have been used to estimate the prediction efficiency of both forecasting tools. To assess the reliability of both models to forecast infrequent events of very high fluxes, the Heidke skill score was employed. The results obtained indicate that SNB 3 GEO provides a more accurate 1 day ahead forecast when compared to REFM. It is shown that the correction methodology utilized by REFM potentially can improve the SNB 3 GEO forecast.

Improving of local ozone forecasting by integrated models.

PubMed

Gradišar, Dejan; Grašič, Boštjan; Božnar, Marija Zlata; Mlakar, Primož; Kocijan, Juš

2016-09-01

This paper discuss the problem of forecasting the maximum ozone concentrations in urban microlocations, where reliable alerting of the local population when thresholds have been surpassed is necessary. To improve the forecast, the methodology of integrated models is proposed. The model is based on multilayer perceptron neural networks that use as inputs all available information from QualeAria air-quality model, WRF numerical weather prediction model and onsite measurements of meteorology and air pollution. While air-quality and meteorological models cover large geographical 3-dimensional space, their local resolution is often not satisfactory. On the other hand, empirical methods have the advantage of good local forecasts. In this paper, integrated models are used for improved 1-day-ahead forecasting of the maximum hourly value of ozone within each day for representative locations in Slovenia. The WRF meteorological model is used for forecasting meteorological variables and the QualeAria air-quality model for gas concentrations. Their predictions, together with measurements from ground stations, are used as inputs to a neural network. The model validation results show that integrated models noticeably improve ozone forecasts and provide better alert systems.

An Emotional ANN (EANN) approach to modeling rainfall-runoff process

NASA Astrophysics Data System (ADS)

Nourani, Vahid

2017-01-01

This paper presents the first hydrological implementation of Emotional Artificial Neural Network (EANN), as a new generation of Artificial Intelligence-based models for daily rainfall-runoff (r-r) modeling of the watersheds. Inspired by neurophysiological form of brain, in addition to conventional weights and bias, an EANN includes simulated emotional parameters aimed at improving the network learning process. EANN trained by a modified version of back-propagation (BP) algorithm was applied to single and multi-step-ahead runoff forecasting of two watersheds with two distinct climatic conditions. Also to evaluate the ability of EANN trained by smaller training data set, three data division strategies with different number of training samples were considered for the training purpose. The overall comparison of the obtained results of the r-r modeling indicates that the EANN could outperform the conventional feed forward neural network (FFNN) model up to 13% and 34% in terms of training and verification efficiency criteria, respectively. The superiority of EANN over classic ANN is due to its ability to recognize and distinguish dry (rainless days) and wet (rainy days) situations using hormonal parameters of the artificial emotional system.

Performance of AHEAD Score in an Asian Cohort of Acute Heart Failure With Either Preserved or Reduced Left Ventricular Systolic Function.

PubMed

Chen, Yu-Jen; Sung, Shih-Hsien; Cheng, Hao-Min; Huang, Wei-Ming; Wu, Chung-Li; Huang, Chi-Jung; Hsu, Pai-Feng; Yeh, Jong-Shiuan; Guo, Chao-Yu; Yu, Wen-Chung; Chen, Chen-Huan

2017-05-04

AHEAD (A: atrial fibrillation; H: hemoglobin; E: elderly; A: abnormal renal parameters; D: diabetes mellitus) score has been related to clinical outcomes of acute heart failure. However, the prognostic value of the AHEAD score in acute heart failure patients with either reduced or preserved left ventricular ejection fraction (HFrEF and HFpEF) remain to be elucidated. The study population consisted of 2143 patients (age 77±12 years, 68% men, 38% HFrEF) hospitalized primarily for acute heart failure with a median follow-up of 23.75 months. The performance of the AHEAD score (atrial fibrillation, hemoglobin <13 mg/dL for men and 12 mg/dL for women, age >70 years, creatinine >130 μmol/L, and diabetes mellitus) was evaluated by Cox's regression analysis for predicting cardiovascular and all-cause mortality. The mean AHEAD scores were 2.7±1.2 in the total study population, 2.6±1.3 in the HFrEF group, and 2.7±1.1 in the HFpEF group. After accounting for sex, sodium, uric acid, and medications, the AHEAD score remained significantly associated with all-cause and cardiovascular mortality (hazard ratio and 95% CI: 1.49, 1.38-1.60 and 1.48, 1.33-1.64), respectively. The associations of AHEAD score with mortality remained significant in the subgroups of HFrEF (1.63, 1.47-1.82) and HFpEF (1.34, 1.22-1.48). Moreover, when we calculated a new AHEAD-U score by considering uric acid (>8.6 mg/dL) in addition to the AHEAD score, the net reclassification was improved by 19.7% and 20.1% for predicting all-cause and cardiovascular mortality, respectively. The AHEAD score was useful in predicting long-term mortality in the Asian acute heart failure cohort with either HFrEF or HFpEF. The new AHEAD-U score may further improve risk stratification. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Systolic Blood Pressure Control Among Individuals With Type 2 Diabetes: A Comparative Effectiveness Analysis of Three Interventions

PubMed Central

Probstfield, Jeffery; Hire, Donald; Redmon, J. Bruce; Evans, Gregory W.; Coday, Mace; Lewis, Cora E.; Johnson, Karen C.; Wilmoth, Sharon; Bahnson, Judy; Dulin, Michael F.; Green, Jennifer B.; Knowler, William C.; Kitabchi, Abbas; Murillo, Anne L.; Osei, Kwame; Rehman, Shakaib U.; Cushman, William C.

2015-01-01

BACKGROUND The relative effectiveness of 3 approaches to blood pressure control—(i) an intensive lifestyle intervention (ILI) focused on weight loss, (ii) frequent goal-based monitoring of blood pressure with pharmacological management, and (iii) education and support—has not been established among overweight and obese adults with type 2 diabetes who are appropriate for each intervention. METHODS Participants from the Action for Health in Diabetes (Look AHEAD) and the Action to Control Cardiovascular Risk in Diabetes (ACCORD) cohorts who met criteria for both clinical trials were identified. The proportions of these individuals with systolic blood pressure (SBP) <140mm Hg from annual standardized assessments over time were compared with generalized estimating equations. RESULTS Across 4 years among 480 Look AHEAD and 1,129 ACCORD participants with baseline SBPs between 130 and 159mm Hg, ILI (OR = 1.46; 95% CI = [1.18–1.81]) and frequent goal-based monitoring with pharmacotherapy (OR = 1.51; 95% CI = [1.16–1.97]) yielded higher rates of blood pressure control compared to education and support. The intensive behavioral-based intervention may have been more effective among individuals with body mass index >30kg/m2, while frequent goal-based monitoring with medication management may be more effective among individuals with lower body mass index (interaction P = 0.047). CONCLUSIONS Among overweight and obese adults with type 2 diabetes, both ILI and frequent goal-based monitoring with pharmacological management can be successful strategies for blood pressure control. CLINICAL TRIALS REGISTRY clinicaltrials.gov identifiers NCT00017953 (Look AHEAD) and NCT00000620 (ACCORD). PMID:25666468

Expedition 38 Press Conference

NASA Image and Video Library

2013-11-06

Expedition 38 backup crew member Alexander Gerst of the European Space Agency is seen in quarantine, behind glass, during the final press conference held a day ahead of the launch of Expedition 38 prime crew members; Flight Engineer Koichi Wakata of the Japan Aerospace Exploration Agency, Soyuz Commander Mikhail Tyurin of Roscosmos, and, Flight Engineer Rick Mastracchio of NASA, to the International Space Station, Wednesday, Nov. 6, 2013 at the Cosmonaut Hotel in Baikonur, Kazakhstan. Photo Credit: (NASA/Bill Ingalls)

Underway Recovery Test 6 (URT-6) - Day 3 Activities

NASA Image and Video Library

2018-01-19

As part of Underway Recovery Test 6, the Orion test article is intentionally subjected to an increased sea state as the NASA Recovery Team works hard to keep control of the spacecraft. The testing with Kennedy Space Center's NASA Recovery Team and the U.S. Navy will provide important data that is being used to improve recovery procedures and hardware ahead of Orion's next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

Intraseasonal sea surface warming in the western Indian Ocean by oceanic equatorial Rossby waves

DTIC Science & Technology

2017-05-09

using observational and reanalysis products , respectively. In the heat budget, horizontal advection is the leading contributor to warming, in part due to...warming and cooling in these studies . SST is observed to maximize just ahead of MJO convection. After convection begins, SST rapidly cools and reaches a...minimum ~5 days later. However, several studies have observed a certain class of MJO events that deviate from the previously observed relationship of

Underway Recovery Test 6 (URT-6) - Day 5 Activities

NASA Image and Video Library

2018-01-21

Teams from the U.S. Navy’s Explosive Ordnance Disposal Mobile Unit 3, the Special Boat Unit, the USS Anchorage and the USS New Orleans work together to connect tending lines to the Orion test article off the coast of San Diego. Kennedy Space Center’s NASA Recovery Team works with the U.S. Navy to improve recovery procedures and hardware ahead of Orion's next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

Tracheal bioengineering: the next steps. Proceeds of an International Society of Cell Therapy Pulmonary Cellular Therapy Signature Series Workshop, Paris, France, April 22, 2014.

PubMed

Weiss, Daniel J; Elliott, Martin; Jang, Queenie; Poole, Brian; Birchall, Martin

2014-12-01

There has been significant and exciting recent progress in the development of bioengineering approaches for generating tracheal tissue that can be used for congenital and acquired tracheal diseases. This includes a growing clinical experience in both pediatric and adult patients with life-threatening tracheal diseases. However, not all of these attempts have been successful, and there is ongoing discussion and debate about the optimal approaches to be used. These include considerations of optimal materials, particularly use of synthetic versus biologic scaffolds, appropriate cellularization of the scaffolds, optimal surgical approaches and optimal measure of both clinical and biologic outcomes. To address these issues, the International Society of Cell Therapy convened a first-ever meeting of the leading clinicians and tracheal biologists, along with experts in regulatory and ethical affairs, to discuss and debate the issues. A series of recommendations are presented for how to best move the field ahead. Copyright © 2014 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

The Joint Adaptive Kalman Filter (JAKF) for Vehicle Motion State Estimation.

PubMed

Gao, Siwei; Liu, Yanheng; Wang, Jian; Deng, Weiwen; Oh, Heekuck

2016-07-16

This paper proposes a multi-sensory Joint Adaptive Kalman Filter (JAKF) through extending innovation-based adaptive estimation (IAE) to estimate the motion state of the moving vehicles ahead. JAKF views Lidar and Radar data as the source of the local filters, which aims to adaptively adjust the measurement noise variance-covariance (V-C) matrix 'R' and the system noise V-C matrix 'Q'. Then, the global filter uses R to calculate the information allocation factor 'β' for data fusion. Finally, the global filter completes optimal data fusion and feeds back to the local filters to improve the measurement accuracy of the local filters. Extensive simulation and experimental results show that the JAKF has better adaptive ability and fault tolerance. JAKF enables one to bridge the gap of the accuracy difference of various sensors to improve the integral filtering effectivity. If any sensor breaks down, the filtered results of JAKF still can maintain a stable convergence rate. Moreover, the JAKF outperforms the conventional Kalman filter (CKF) and the innovation-based adaptive Kalman filter (IAKF) with respect to the accuracy of displacement, velocity, and acceleration, respectively.

Benchmark analysis of forecasted seasonal temperature over different climatic areas

NASA Astrophysics Data System (ADS)

Giunta, G.; Salerno, R.; Ceppi, A.; Ercolani, G.; Mancini, M.

2015-12-01

From a long-term perspective, an improvement of seasonal forecasting, which is often exclusively based on climatology, could provide a new capability for the management of energy resources in a time scale of just a few months. This paper regards a benchmark analysis in relation to long-term temperature forecasts over Italy in the year 2010, comparing the eni-kassandra meteo forecast (e-kmf®) model, the Climate Forecast System-National Centers for Environmental Prediction (CFS-NCEP) model, and the climatological reference (based on 25-year data) with observations. Statistical indexes are used to understand the reliability of the prediction of 2-m monthly air temperatures with a perspective of 12 weeks ahead. The results show how the best performance is achieved by the e-kmf® system which improves the reliability for long-term forecasts compared to climatology and the CFS-NCEP model. By using the reliable high-performance forecast system, it is possible to optimize the natural gas portfolio and management operations, thereby obtaining a competitive advantage in the European energy market.

Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model

PubMed Central

Zhu, Qing; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations. PMID:25061614

Day-ahead crude oil price forecasting using a novel morphological component analysis based model.

PubMed

Zhu, Qing; He, Kaijian; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.

A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting.

PubMed

Ben Taieb, Souhaib; Atiya, Amir F

2016-01-01

Multistep-ahead forecasts can either be produced recursively by iterating a one-step-ahead time series model or directly by estimating a separate model for each forecast horizon. In addition, there are other strategies; some of them combine aspects of both aforementioned concepts. In this paper, we present a comprehensive investigation into the bias and variance behavior of multistep-ahead forecasting strategies. We provide a detailed review of the different multistep-ahead strategies. Subsequently, we perform a theoretical study that derives the bias and variance for a number of forecasting strategies. Finally, we conduct a Monte Carlo experimental study that compares and evaluates the bias and variance performance of the different strategies. From the theoretical and the simulation studies, we analyze the effect of different factors, such as the forecast horizon and the time series length, on the bias and variance components, and on the different multistep-ahead strategies. Several lessons are learned, and recommendations are given concerning the advantages, disadvantages, and best conditions of use of each strategy.

Using Forecast and Observed Weather Data to Assess Performance of Forecast Products in Identifying Heat Waves and Estimating Heat Wave Effects on Mortality

PubMed Central

Chen, Yeh-Hsin; Schwartz, Joel D.; Rood, Richard B.; O’Neill, Marie S.

2014-01-01

Background: Heat wave and health warning systems are activated based on forecasts of health-threatening hot weather. Objective: We estimated heat–mortality associations based on forecast and observed weather data in Detroit, Michigan, and compared the accuracy of forecast products for predicting heat waves. Methods: We derived and compared apparent temperature (AT) and heat wave days (with heat waves defined as ≥ 2 days of daily mean AT ≥ 95th percentile of warm-season average) from weather observations and six different forecast products. We used Poisson regression with and without adjustment for ozone and/or PM10 (particulate matter with aerodynamic diameter ≤ 10 μm) to estimate and compare associations of daily all-cause mortality with observed and predicted AT and heat wave days. Results: The 1-day-ahead forecast of a local operational product, Revised Digital Forecast, had about half the number of false positives compared with all other forecasts. On average, controlling for heat waves, days with observed AT = 25.3°C were associated with 3.5% higher mortality (95% CI: –1.6, 8.8%) than days with AT = 8.5°C. Observed heat wave days were associated with 6.2% higher mortality (95% CI: –0.4, 13.2%) than non–heat wave days. The accuracy of predictions varied, but associations between mortality and forecast heat generally tended to overestimate heat effects, whereas associations with forecast heat waves tended to underestimate heat wave effects, relative to associations based on observed weather metrics. Conclusions: Our findings suggest that incorporating knowledge of local conditions may improve the accuracy of predictions used to activate heat wave and health warning systems. Citation: Zhang K, Chen YH, Schwartz JD, Rood RB, O’Neill MS. 2014. Using forecast and observed weather data to assess performance of forecast products in identifying heat waves and estimating heat wave effects on mortality. Environ Health Perspect 122:912–918; http://dx.doi.org/10.1289/ehp.1306858 PMID:24833618

Mechanism of demyelination after HSV type I intraocular injection in rabbits.

PubMed

Narang, H K

1980-02-01

Intraocular injection of herpes simplex virus (HSV) type I into the vitreous body of 18-day-old rabbits induced, on the 7th day post-inoculation, neurological signs with marked head jerking and atazia. Examination of semi-serial 1-micrometers thick sections of the whole lengths of right and left optic nerves and chiasma of 4--64 days post-inoculated rabbits revealed a small lesion, restricted to the medial side, which had extended 2--3 mm, during the first 4 days, along the optic nerve. Ahead of the developing lesion marked chromatin changes of neuroglial cells were noticed followed by cuffing of blood vessels, infiltration by macrophages, demyelination and remyelination. The present study indicated that demyelination occurred following the infection of the myelinating cells. It appeared that virus did not become latent and many cells survived the viral attack. Repeated episodies of viral activity caused further damage while repair did not keep pace.

Integrated Detection and Prediction of Influenza Activity for Real-Time Surveillance: Algorithm Design

PubMed Central

2017-01-01

Background Influenza is a viral respiratory disease capable of causing epidemics that represent a threat to communities worldwide. The rapidly growing availability of electronic “big data” from diagnostic and prediagnostic sources in health care and public health settings permits advance of a new generation of methods for local detection and prediction of winter influenza seasons and influenza pandemics. Objective The aim of this study was to present a method for integrated detection and prediction of influenza virus activity in local settings using electronically available surveillance data and to evaluate its performance by retrospective application on authentic data from a Swedish county. Methods An integrated detection and prediction method was formally defined based on a design rationale for influenza detection and prediction methods adapted for local surveillance. The novel method was retrospectively applied on data from the winter influenza season 2008-09 in a Swedish county (population 445,000). Outcome data represented individuals who met a clinical case definition for influenza (based on International Classification of Diseases version 10 [ICD-10] codes) from an electronic health data repository. Information from calls to a telenursing service in the county was used as syndromic data source. Results The novel integrated detection and prediction method is based on nonmechanistic statistical models and is designed for integration in local health information systems. The method is divided into separate modules for detection and prediction of local influenza virus activity. The function of the detection module is to alert for an upcoming period of increased load of influenza cases on local health care (using influenza-diagnosis data), whereas the function of the prediction module is to predict the timing of the activity peak (using syndromic data) and its intensity (using influenza-diagnosis data). For detection modeling, exponential regression was used based on the assumption that the beginning of a winter influenza season has an exponential growth of infected individuals. For prediction modeling, linear regression was applied on 7-day periods at the time in order to find the peak timing, whereas a derivate of a normal distribution density function was used to find the peak intensity. We found that the integrated detection and prediction method detected the 2008-09 winter influenza season on its starting day (optimal timeliness 0 days), whereas the predicted peak was estimated to occur 7 days ahead of the factual peak and the predicted peak intensity was estimated to be 26% lower than the factual intensity (6.3 compared with 8.5 influenza-diagnosis cases/100,000). Conclusions Our detection and prediction method is one of the first integrated methods specifically designed for local application on influenza data electronically available for surveillance. The performance of the method in a retrospective study indicates that further prospective evaluations of the methods are justified. PMID:28619700

Integrated Detection and Prediction of Influenza Activity for Real-Time Surveillance: Algorithm Design.

PubMed

Spreco, Armin; Eriksson, Olle; Dahlström, Örjan; Cowling, Benjamin John; Timpka, Toomas

2017-06-15

Influenza is a viral respiratory disease capable of causing epidemics that represent a threat to communities worldwide. The rapidly growing availability of electronic "big data" from diagnostic and prediagnostic sources in health care and public health settings permits advance of a new generation of methods for local detection and prediction of winter influenza seasons and influenza pandemics. The aim of this study was to present a method for integrated detection and prediction of influenza virus activity in local settings using electronically available surveillance data and to evaluate its performance by retrospective application on authentic data from a Swedish county. An integrated detection and prediction method was formally defined based on a design rationale for influenza detection and prediction methods adapted for local surveillance. The novel method was retrospectively applied on data from the winter influenza season 2008-09 in a Swedish county (population 445,000). Outcome data represented individuals who met a clinical case definition for influenza (based on International Classification of Diseases version 10 [ICD-10] codes) from an electronic health data repository. Information from calls to a telenursing service in the county was used as syndromic data source. The novel integrated detection and prediction method is based on nonmechanistic statistical models and is designed for integration in local health information systems. The method is divided into separate modules for detection and prediction of local influenza virus activity. The function of the detection module is to alert for an upcoming period of increased load of influenza cases on local health care (using influenza-diagnosis data), whereas the function of the prediction module is to predict the timing of the activity peak (using syndromic data) and its intensity (using influenza-diagnosis data). For detection modeling, exponential regression was used based on the assumption that the beginning of a winter influenza season has an exponential growth of infected individuals. For prediction modeling, linear regression was applied on 7-day periods at the time in order to find the peak timing, whereas a derivate of a normal distribution density function was used to find the peak intensity. We found that the integrated detection and prediction method detected the 2008-09 winter influenza season on its starting day (optimal timeliness 0 days), whereas the predicted peak was estimated to occur 7 days ahead of the factual peak and the predicted peak intensity was estimated to be 26% lower than the factual intensity (6.3 compared with 8.5 influenza-diagnosis cases/100,000). Our detection and prediction method is one of the first integrated methods specifically designed for local application on influenza data electronically available for surveillance. The performance of the method in a retrospective study indicates that further prospective evaluations of the methods are justified. ©Armin Spreco, Olle Eriksson, Örjan Dahlström, Benjamin John Cowling, Toomas Timpka. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 15.06.2017.

A stochastic post-processing method for solar irradiance forecasts derived from NWPs models

NASA Astrophysics Data System (ADS)

Lara-Fanego, V.; Pozo-Vazquez, D.; Ruiz-Arias, J. A.; Santos-Alamillos, F. J.; Tovar-Pescador, J.

2010-09-01

Solar irradiance forecast is an important area of research for the future of the solar-based renewable energy systems. Numerical Weather Prediction models (NWPs) have proved to be a valuable tool for solar irradiance forecasting with lead time up to a few days. Nevertheless, these models show low skill in forecasting the solar irradiance under cloudy conditions. Additionally, climatic (averaged over seasons) aerosol loading are usually considered in these models, leading to considerable errors for the Direct Normal Irradiance (DNI) forecasts during high aerosols load conditions. In this work we propose a post-processing method for the Global Irradiance (GHI) and DNI forecasts derived from NWPs. Particularly, the methods is based on the use of Autoregressive Moving Average with External Explanatory Variables (ARMAX) stochastic models. These models are applied to the residuals of the NWPs forecasts and uses as external variables the measured cloud fraction and aerosol loading of the day previous to the forecast. The method is evaluated for a set one-moth length three-days-ahead forecast of the GHI and DNI, obtained based on the WRF mesoscale atmospheric model, for several locations in Andalusia (Southern Spain). The Cloud fraction is derived from MSG satellite estimates and the aerosol loading from the MODIS platform estimates. Both sources of information are readily available at the time of the forecast. Results showed a considerable improvement of the forecasting skill of the WRF model using the proposed post-processing method. Particularly, relative improvement (in terms of the RMSE) for the DNI during summer is about 20%. A similar value is obtained for the GHI during the winter.

Exploring the meteorological potential for planning a high performance European electricity super-grid: optimal power capacity distribution among countries

NASA Astrophysics Data System (ADS)

Santos-Alamillos, Francisco J.; Brayshaw, David J.; Methven, John; Thomaidis, Nikolaos S.; Ruiz-Arias, José A.; Pozo-Vázquez, David

2017-11-01

The concept of a European super-grid for electricity presents clear advantages for a reliable and affordable renewable power production (photovoltaics and wind). Based on the mean-variance portfolio optimization analysis, we explore optimal scenarios for the allocation of new renewable capacity at national level in order to provide to energy decision-makers guidance about which regions should be mostly targeted to either maximize total production or reduce its day-to-day variability. The results show that the existing distribution of renewable generation capacity across Europe is far from optimal: i.e. a ‘better’ spatial distribution of resources could have been achieved with either a ~31% increase in mean power supply (for the same level of day-to-day variability) or a ~37.5% reduction in day-to-day variability (for the same level of mean productivity). Careful planning of additional increments in renewable capacity at the European level could, however, act to significantly ameliorate this deficiency. The choice of where to deploy resources depends, however, on the objective being pursued—if the goal is to maximize average output, then new capacity is best allocated in the countries with highest resources, whereas investment in additional capacity in a north/south dipole pattern across Europe would act to most reduce daily variations and thus decrease the day-to-day volatility of renewable power supply.

Evaluating the Subjective Straight Ahead Before and After Spaceflight

NASA Technical Reports Server (NTRS)

Campbell, D. J.; Wood, S. J.; Reschke, M. F.; Clement, G.

2017-01-01

Introduction. This joint European Space Agency/NASA pre- and post-flight study investigates the influence of exposure to microgravity on the subjective straight ahead (SSA) in crewmembers returning from long-duration expeditions to the International Space Station (ISS). The SSA is a measure of the internal representation of body orientation and to be influenced by stimulation of sensory systems involved in postural control. The use of a vibrotactile sensory aid to correct the representation of body tilted relative to gravity is also tested as a countermeasure. This study addresses the sensorimotor research gap to "determine the changes in sensorimotor function over the course of a mission and during recovery after landing." Research Plans. The ISS study will involve eight crewmembers who will participate in three pre-flight sessions (between 120 and 60 days before launch) and then three post-flight sessions on R plus 0/1 day, R plus 4 days, and R plus 8 days. Sixteen control subjects were also tested during three sessions to evaluate the effects of repeated testing and to establish normative values. The experimental protocol includes measurements of gaze and arm movements during the following tasks: (1) Near & Far Fixation: The subject is asked to look at actual targets in the true straight-ahead direction or to imagine these targets in the dark. Targets are located at near distance (arm's length) and far distance (beyond 2 meters). This task is successively performed with the subject's body aligned with the gravitational vertical, and with the subject's body tilted in pitch relative to the gravitational vertical using a tilt chair. Measures are then compared with and without a vibrotactile sensory aid that indicates how far one has tilted relative to the vertical; (2) Eye and Arm Movements: The subject is asked to look and point in the SSA direction in darkness and then make horizontal and vertical eye or arm movements, relative to Earth coordinates (allocentric) and to the subject's head/body reference (egocentric). This task is successively performed with the subject's body aligned with the gravitational vertical, and with subject's body tilted in roll using a tilt chair; (3) Linear Vestibulo-Ocular Reflex: The subject is asked to fixate actual visual targets at near and far distances in the true straight-ahead direction, and to evaluate the distance of these targets. The subject is asked to continue fixating the same imagined targets in darkness while he/she is passively accelerated up and down on a spring-loaded vertical linear accelerator. Results. In the control subject population, the perceived tilt angles, translations, and distances were remarkably close to the actual values. The pointing tasks indicated that the orientation of arm saccades was influenced by both the gravitational vertical and the body idiotropic vector. Repeating the testing did not reveal any significant changes. Preliminary results obtained in three crewmembers before and after flight will also be presented. Applications. A change in an individual's egocentric reference might have negative consequences on evaluating the direction of an approaching object or on the accuracy of reaching movements or locomotion. Consequently, investigating how microgravity affects the target location will have theoretical, operational, and even clinical implications for future space exploration missions. The use of vibrotactile feedback as a sensorimotor countermeasure is applicable to balance therapy applications for patients with vestibular loss and the elderly to mitigate risks due to loss of spatial orientation.

Climate impacts on human livelihoods: where uncertainty matters in projections of water availability

NASA Astrophysics Data System (ADS)

Lissner, T. K.; Reusser, D. E.; Schewe, J.; Lakes, T.; Kropp, J. P.

2014-03-01

Climate change will have adverse impacts on many different sectors of society, with manifold consequences for human livelihoods and well-being. However, a systematic method to quantify human well-being and livelihoods across sectors is so far unavailable, making it difficult to determine the extent of such impacts. Climate impact analyses are often limited to individual sectors (e.g. food or water) and employ sector-specific target-measures, while systematic linkages to general livelihood conditions remain unexplored. Further, recent multi-model assessments have shown that uncertainties in projections of climate impacts deriving from climate and impact models as well as greenhouse gas scenarios are substantial, posing an additional challenge in linking climate impacts with livelihood conditions. This article first presents a methodology to consistently measure Adequate Human livelihood conditions for wEll-being And Development (AHEAD). Based on a transdisciplinary sample of influential concepts addressing human well-being, the approach measures the adequacy of conditions of 16 elements. We implement the method at global scale, using results from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) to show how changes in water availability affect the fulfilment of AHEAD at national resolution. In addition, AHEAD allows identifying and differentiating uncertainty of climate and impact model projections. We show how the approach can help to put the substantial inter-model spread into the context of country-specific livelihood conditions by differentiating where the uncertainty about water scarcity is relevant with regard to livelihood conditions - and where it is not. The results indicate that in many countries today, livelihood conditions are compromised by water scarcity. However, more often, AHEAD fulfilment is limited through other elements. Moreover, the analysis shows that for 44 out of 111 countries, the water-specific uncertainty ranges are outside relevant thresholds for AHEAD, and therefore do not contribute to the overall uncertainty about climate change impacts on livelihoods. The AHEAD method presented here, together with first results, forms an important step towards making scientific results more applicable for policy-decisions.

Optimizing a Drone Network to Deliver Automated External Defibrillators.

PubMed

Boutilier, Justin J; Brooks, Steven C; Janmohamed, Alyf; Byers, Adam; Buick, Jason E; Zhan, Cathy; Schoellig, Angela P; Cheskes, Sheldon; Morrison, Laurie J; Chan, Timothy C Y

2017-06-20

Public access defibrillation programs can improve survival after out-of-hospital cardiac arrest, but automated external defibrillators (AEDs) are rarely available for bystander use at the scene. Drones are an emerging technology that can deliver an AED to the scene of an out-of-hospital cardiac arrest for bystander use. We hypothesize that a drone network designed with the aid of a mathematical model combining both optimization and queuing can reduce the time to AED arrival. We applied our model to 53 702 out-of-hospital cardiac arrests that occurred in the 8 regions of the Toronto Regional RescuNET between January 1, 2006, and December 31, 2014. Our primary analysis quantified the drone network size required to deliver an AED 1, 2, or 3 minutes faster than historical median 911 response times for each region independently. A secondary analysis quantified the reduction in drone resources required if RescuNET was treated as a large coordinated region. The region-specific analysis determined that 81 bases and 100 drones would be required to deliver an AED ahead of median 911 response times by 3 minutes. In the most urban region, the 90th percentile of the AED arrival time was reduced by 6 minutes and 43 seconds relative to historical 911 response times in the region. In the most rural region, the 90th percentile was reduced by 10 minutes and 34 seconds. A single coordinated drone network across all regions required 39.5% fewer bases and 30.0% fewer drones to achieve similar AED delivery times. An optimized drone network designed with the aid of a novel mathematical model can substantially reduce the AED delivery time to an out-of-hospital cardiac arrest event. © 2017 American Heart Association, Inc.

Design of experiments confirms optimization of lithium administration parameters for enhanced fracture healing.

PubMed

Vachhani, Kathak; Pagotto, Andrea; Wang, Yufa; Whyne, Cari; Nam, Diane

2018-01-03

Fracture healing is a lengthy process which fails in 5-10% of cases. Lithium, a low-cost therapeutic used in psychiatric medicine, up-regulates the canonical Wingless pathway crucial for osteoblastic mineralization in fracture healing. A design-of-experiments (DOE) methodology was used to optimize lithium administration parameters (dose, onset time and treatment duration) to enhance healing in a rat femoral fracture model. In the previously completed first stage (screening), onset time was found to significantly impact healing, with later (day 7 vs. day 3 post-fracture) treatment yielding improved maximum yield torque. The greatest strength was found in healing femurs treated at day 7 post fracture, with a low lithium dose (20 mg/kg) for 2 weeks duration. This paper describes the findings of the second (optimization) and third (verification) stages of the DOE investigation. Closed traumatic diaphyseal femur fractures were induced in 3-month old rats. Healing was evaluated on day 28 post fracture by CT-based morphometry and torsional loading. In optimization, later onset times of day 10 and 14 did not perform as well as day 7 onset. As such, efficacy of the best regimen (20 mg/kg dose given at day 7 onset for 2 weeks duration) was reassessed in a distinct cohort of animals to complete the DOE verification. A significant 44% higher maximum yield torque (primary outcome) was seen with optimized lithium treatment vs. controls, which paralleled the 46% improvement seen in the screening stage. Successful completion of this robustly designed preclinical DOE study delineates the optimal lithium regimen for enhancing preclinical long-bone fracture healing. Copyright © 2017 Elsevier Ltd. All rights reserved.

Foraging habitat for shorebirds in southeastern Missouri and its predicted future availability

USGS Publications Warehouse

Twedt, Daniel J.

2013-01-01

Water management to protect agriculture in alluvial floodplains often conflicts with wildlife use of seasonal floodwater. Such is the case along the Mississippi River in southeastern Missouri where migrating shorebirds forage in shallow-flooded fields. I estimated the current availability of habitat for foraging shorebirds within the New Madrid and St. Johns Basins based on daily river elevations (1943–2009), under assumptions that shorebirds forage in open habitat with water depth <15 cm and use mudflats for 3 days after exposure. The area of shorebird foraging habitat, based on replicated 50-year random samples, averaged 975 ha per day during spring and 33 ha per day during fall. Adjustments to account for habitat quality associated with different water depths, duration of mudflat exposure, intra-seasonal availability, and state of agricultural crops, indicated the equivalent of 494 ha daily of optimal habitat during spring and 11 ha during fall. Proposed levees and pumps to protect cropland would reduce shorebird foraging habitat by 80 %: to 211 ha (108 optimal ha) per day during spring and 9 ha (<3 optimal ha) per day during fall. Alternative water management that allows natural flooding below a prescribed elevation would retain nearly all existing shorebird foraging habitat during fall and about 60 % of extant habitat during spring.

Heliocentric phasing performance of electric sail spacecraft

NASA Astrophysics Data System (ADS)

Mengali, Giovanni; Quarta, Alessandro A.; Aliasi, Generoso

2016-10-01

We investigate the heliocentric in-orbit repositioning problem of a spacecraft propelled by an Electric Solar Wind Sail. Given an initial circular parking orbit, we look for the heliocentric trajectory that minimizes the time required for the spacecraft to change its azimuthal position, along the initial orbit, of a (prescribed) phasing angle. The in-orbit repositioning problem can be solved using either a drift ahead or a drift behind maneuver and, in general, the flight times for the two cases are different for a given value of the phasing angle. However, there exists a critical azimuthal position, whose value is numerically found, which univocally establishes whether a drift ahead or behind trajectory is superior in terms of flight time it requires for the maneuver to be completed. We solve the optimization problem using an indirect approach for different values of both the spacecraft maximum propulsive acceleration and the phasing angle, and the solution is then specialized to a repositioning problem along the Earth's heliocentric orbit. Finally, we use the simulation results to obtain a first order estimate of the minimum flight times for a scientific mission towards triangular Lagrangian points of the Sun-[Earth+Moon] system.

Underway Recovery Test 6 (URT-6) - Day 5 Activities

NASA Image and Video Library

2018-01-21

Chief Warrant Officer Ferrari from the USS Anchorage watches over members of the U.S. Navy’s Mobile Diving Salvage Co. 3-1 as they set off to sea to recover the Orion test capsule during Underway Recovery Test 6 off the coast of San Diego. Kennedy Space Center’s NASA Recovery Team works with the U.S. Navy to improve recovery procedures and hardware ahead of Orion's next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

Critical Technologies Plan for the Committees on Armed Services, United States Congress. Revision

DTIC Science & Technology

1989-05-05

materials; however, it does not appear to be a concerted effort. Only the British have a space-qualified cryocooler . This Stirling cooler has been life...published results of innovative concepts utilizing pulse tube refrigerators and appear to be far ahead of the US in this technology. A-61 11. AUTOMATIC...12. PERSONAL AUTHOR(S) 13a. TYPE OF REPORT 113b. TIME COVERED 114. DATE OF REPORT (Year, Month, Day) 5. PAGE COUNT1aTYEOREOT 7 FROM TO - 1989 MAY 05

Expedition 37 Soyuz Landing Preparation

NASA Image and Video Library

2013-11-10

A member of Russian search and rescue exits a helicopter moments after landing at Zhezkazgan airport in Kazakhstan, Sunday, Nov. 10, 2013, a day ahead of the scheduled landing of the Soyuz TMA-09M spacecraft with Expedition 37 Commander Fyodor Yurchikhin of the Russian Federal Space Agency (Roscosmos), Flight Engineer Karen Nyberg of NASA and Flight Engineer Luca Parmitano of the European Space Agency. Yurchikhin, Nyberg and Parmitano are returning to Earth after five and a half months on the International Space Station. Photo Credit: (NASA/Carla Cioffi)

Win, Learn, Focus, Adapt, Win Again: The Scrimmage Should be as Hard as the Game

DTIC Science & Technology

2011-03-01

prepare us for what lies ahead only if, as GEN Gorman put it, “forceful, effective ideas on how to fight pervade the force.” We know how to fight to- day...and policies to develop leaders who can effectively op- erate in a much more transpar- ent, complex and decentralized February 2011 � ARMY 25... effectiveness of our leader-development programs against clearly defined tasks, conditions and stan- dards. What I’m suggesting here, however, is that

Underway Recovery Test 6 (URT-6) - Day 3 Activities

NASA Image and Video Library

2018-01-19

NASA astronaut Stephen Bowen gets a birds-eye view of the rough seas during part of Underway Recovery Test 6. Bowen is watching the testing so he can provide the team with an astronaut’s perspective. The testing with Kennedy Space Center's NASA Recovery Team and the U.S. Navy will provide important data that is being used to improve recovery procedures and hardware ahead of Orion's next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

Naval War College Review. Volume 59, Number 3, Summer 2006

DTIC Science & Technology

2006-06-01

academically inclined Mahan had seen only scant sea duty and had possessed lit- tle taste for more. (“I am the man of thought, not the man of action...diversification will impel the MSDF to transform itself into a service with all the trappings of a tra- ditional navy remains to be seen . Japan got off to...COLLISION COURSE AHEAD? Sino-Japanese relations have seen better days. Some of the problems that have ratcheted the two countries’ mutual ambivalence to new

National Symposium: Surface Navy Leading the Way (5th) Held at Washington, DC on 26-29 October 1992

DTIC Science & Technology

1992-10-29

nation. We all hope that in the days and years ahead a grateful nation continues to be grateful, and will not forget the price we paid for this... skimming threats. The Outlaw Bandit Program will continue. This program reduces the radar cross section of combatants significantly and increases the...Weapon Systems to provide a precision, multi-mode strike Cruise missile with an imaging seeker and hard target penetrator warhead. 22 With the

Successes and limitations of targeted therapies in renal cell carcinoma.

PubMed

Pracht, Marc; Berthold, Dominik

2014-01-01

Until recently, the standard treatment for metastatic renal cell carcinoma (RCC) was nonspecific immunotherapy based on interleukin-2 or interferon-α. This was associated with a modest survival benefit and with significant clinical toxicities. The understanding of numerous molecular pathways in RCC, including HIF, VEGF, mTOR, and the consecutive use of targeted therapies since the beginning of 2005 have significantly improved outcomes for patients with metastatic RCC with an overall survival greater than 2 years. At present, at least 7 targeted agents are approved for first and consecutive lines of treatment of clear cell metastatic RCC. Long-term benefit and extended survival may be achieved through the optimal use of targeted therapies: optimal dosing, adverse event management and treatment duration and compliance. Advances in the finding of prognostic factors highlight the potential for personalizing treatment for patients with metastatic RCC. Data regarding the best sequencing of targeted therapies, predictive biomarkers, best timing of surgery, patient risk profiles, understanding of resistance mechanisms and safety of targeted therapies are growing and will provide a further step ahead in the management of advanced RCC. In parallel, a new class of therapeutics is emerging in RCC: immunotherapy; in particular check-point blockade antibodies are showing very promising results. © 2014 S. Karger AG, Basel.

Active versus Passive Proprioceptive Straight-Ahead Pointing in Normal Subjects

ERIC Educational Resources Information Center

Chokron, Sylvie; Colliot, Pascale; Atzeni, Thierry; Bartolomeo, Paolo; Ohlmann, Theophile

2004-01-01

Eighty blindfolded healthy female subjects participated in an active and a passive straight-ahead pointing task to study the estimation of the subjective sagittal middle in the presence or absence of an active haptic exploration. Subjects were to point straight-ahead with their left or right index finger starting from different right- or…

An improved car-following model considering velocity fluctuation of the immediately ahead car

NASA Astrophysics Data System (ADS)

Yu, Shaowei; Huang, Mengxing; Ren, Jia; Shi, Zhongke

2016-05-01

To better describe car-following behaviors in the adaptive cruise control strategy and further increase roadway traffic mobility and reduce fuel consumptions, the linkage between velocity fluctuation of the immediately ahead car and the following car's acceleration or deceleration is explored with respect to the measured car-following data by employing the gray correlation analysis theory and then an improved car-following model considering velocity fluctuation of the immediately ahead car on basis of the full velocity difference model is proposed. Numerical simulations are carried out and the effects of velocity fluctuation of the immediately ahead car on each car's velocity, acceleration, vehicular gap, fuel consumptions and the total fuel consumptions of the whole car-following system with different time window lengths are investigated in detail. The results show that velocity fluctuation of the immediately ahead car has significant effects on car-following behaviors and fuel consumptions, and that considering velocity fluctuation of the immediately ahead car in designing the adaptive cruise control system can improve traffic flow stability and reduce fuel consumptions.

The art of getting what you want for optimal patient care.

PubMed

Davidhizar, R

2000-01-01

Getting your way is a mix of logical and emotional issues. It is important to establish rapport and meet a person emotionally before trying to sell an idea. It is essential to think an idea through clearly ahead of time and to present it clearly and logically. The possibility of resistance should be anticipated so that the presentation addresses potential areas of resistance. It is important to actively listen, to agree when possible, and to not appear too eager. Persuasion is both an art and science. When used skillfully, persuasive techniques are powerful tools of communication and productivity.

Travelling with medications and medical equipment across international borders.

PubMed

Mutie, M; Cooper, G; Kyle, G; Naunton, M; Zwar, N

2014-01-01

The international traveller needs to plan ahead to ensure medicines are available and used as directed for optimal therapeutic outcome. The planning needs to take account of legal and customs requirements for travelling with medicines for personal use. The standard advice by travel health providers is that travellers should check with the country of destination for requirements when travelling into the country with medicines for personal use. This is akin to introducing a barrier to care for this category of travellers. Innovative method of care for this group of traveller is needed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predicting the Poaceae pollen season: six month-ahead forecasting and identification of relevant features

NASA Astrophysics Data System (ADS)

Navares, Ricardo; Aznarte, José Luis

2017-04-01

In this paper, we approach the problem of predicting the concentrations of Poaceae pollen which define the main pollination season in the city of Madrid. A classification-based approach, based on a computational intelligence model (random forests), is applied to forecast the dates in which risk concentration levels are to be observed. Unlike previous works, the proposal extends the range of forecasting horizons up to 6 months ahead. Furthermore, the proposed model allows to determine the most influential factors for each horizon, making no assumptions about the significance of the weather features. The performace of the proposed model proves it as a successful tool for allergy patients in preventing and minimizing the exposure to risky pollen concentrations and for researchers to gain a deeper insight on the factors driving the pollination season.

Predicting the Poaceae pollen season: six month-ahead forecasting and identification of relevant features.

PubMed

Navares, Ricardo; Aznarte, José Luis

2017-04-01

In this paper, we approach the problem of predicting the concentrations of Poaceae pollen which define the main pollination season in the city of Madrid. A classification-based approach, based on a computational intelligence model (random forests), is applied to forecast the dates in which risk concentration levels are to be observed. Unlike previous works, the proposal extends the range of forecasting horizons up to 6 months ahead. Furthermore, the proposed model allows to determine the most influential factors for each horizon, making no assumptions about the significance of the weather features. The performace of the proposed model proves it as a successful tool for allergy patients in preventing and minimizing the exposure to risky pollen concentrations and for researchers to gain a deeper insight on the factors driving the pollination season.

Building regional early flood warning systems by AI techniques

NASA Astrophysics Data System (ADS)

Chang, F. J.; Chang, L. C.; Amin, M. Z. B. M.

2017-12-01

Building early flood warning system is essential for the protection of the residents against flood hazards and make actions to mitigate the losses. This study implements AI technology for forecasting multi-step-ahead regional flood inundation maps during storm events. The methodology includes three major schemes: (1) configuring the self-organizing map (SOM) to categorize a large number of regional inundation maps into a meaningful topology; (2) building dynamic neural networks to forecast multi-step-ahead average inundated depths (AID); and (3) adjusting the weights of the selected neuron in the constructed SOM based on the forecasted AID to obtain real-time regional inundation maps. The proposed models are trained, and tested based on a large number of inundation data sets collected in regions with the most frequent and serious flooding in the river basin. The results appear that the SOM topological relationships between individual neurons and their neighbouring neurons are visible and clearly distinguishable, and the hybrid model can continuously provide multistep-ahead visible regional inundation maps with high resolution during storm events, which have relatively small RMSE values and high R2 as compared with numerical simulation data sets. The computing time is only few seconds, and thereby leads to real-time regional flood inundation forecasting and make early flood inundation warning system. We demonstrate that the proposed hybrid ANN-based model has a robust and reliable predictive ability and can be used for early warning to mitigate flood disasters.

Coordinated Scheduling for Interdependent Electric Power and Natural Gas Infrastructures

DOE PAGES

Zlotnik, Anatoly; Roald, Line; Backhaus, Scott; ...

2016-03-24

The extensive installation of gas-fired power plants in many parts of the world has led electric systems to depend heavily on reliable gas supplies. The use of gas-fired generators for peak load and reserve provision causes high intraday variability in withdrawals from high-pressure gas transmission systems. Such variability can lead to gas price fluctuations and supply disruptions that affect electric generator dispatch, electricity prices, and threaten the security of power systems and gas pipelines. These infrastructures function on vastly different spatio-temporal scales, which prevents current practices for separate operations and market clearing from being coordinated. Here in this article, wemore » apply new techniques for control of dynamic gas flows on pipeline networks to examine day-ahead scheduling of electric generator dispatch and gas compressor operation for different levels of integration, spanning from separate forecasting, and simulation to combined optimal control. We formulate multiple coordination scenarios and develop tractable physically accurate computational implementations. These scenarios are compared using an integrated model of test networks for power and gas systems with 24 nodes and 24 pipes, respectively, which are coupled through gas-fired generators. The analysis quantifies the economic efficiency and security benefits of gas-electric coordination and dynamic gas system operation.« less

Systolic Blood Pressure Control Among Individuals With Type 2 Diabetes: A Comparative Effectiveness Analysis of Three Interventions.

PubMed

Espeland, Mark A; Probstfield, Jeffery; Hire, Donald; Redmon, J Bruce; Evans, Gregory W; Coday, Mace; Lewis, Cora E; Johnson, Karen C; Wilmoth, Sharon; Bahnson, Judy; Dulin, Michael F; Green, Jennifer B; Knowler, William C; Kitabchi, Abbas; Murillo, Anne L; Osei, Kwame; Rehman, Shakaib U; Cushman, William C

2015-08-01

The relative effectiveness of 3 approaches to blood pressure control-(i) an intensive lifestyle intervention (ILI) focused on weight loss, (ii) frequent goal-based monitoring of blood pressure with pharmacological management, and (iii) education and support-has not been established among overweight and obese adults with type 2 diabetes who are appropriate for each intervention. Participants from the Action for Health in Diabetes (Look AHEAD) and the Action to Control Cardiovascular Risk in Diabetes (ACCORD) cohorts who met criteria for both clinical trials were identified. The proportions of these individuals with systolic blood pressure (SBP) <140 mm Hg from annual standardized assessments over time were compared with generalized estimating equations. Across 4 years among 480 Look AHEAD and 1,129 ACCORD participants with baseline SBPs between 130 and 159 mm Hg, ILI (OR = 1.46; 95% CI = [1.18-1.81]) and frequent goal-based monitoring with pharmacotherapy (OR = 1.51; 95% CI = [1.16-1.97]) yielded higher rates of blood pressure control compared to education and support. The intensive behavioral-based intervention may have been more effective among individuals with body mass index >30 kg/m2, while frequent goal-based monitoring with medication management may be more effective among individuals with lower body mass index (interaction P = 0.047). Among overweight and obese adults with type 2 diabetes, both ILI and frequent goal-based monitoring with pharmacological management can be successful strategies for blood pressure control. clinicaltrials.gov identifiers NCT00017953 (Look AHEAD) and NCT00000620 (ACCORD). © American Journal of Hypertension, Ltd 2015. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Variable Generation Power Forecasting as a Big Data Problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haupt, Sue Ellen; Kosovic, Branko

To blend growing amounts of power from renewable resources into utility operations requires accurate forecasts. For both day ahead planning and real-time operations, the power from the wind and solar resources must be predicted based on real-time observations and a series of models that span the temporal and spatial scales of the problem, using the physical and dynamical knowledge as well as computational intelligence. Accurate prediction is a Big Data problem that requires disparate data, multiple models that are each applicable for a specific time frame, and application of computational intelligence techniques to successfully blend all of the model andmore » observational information in real-time and deliver it to the decision makers at utilities and grid operators. This paper describes an example system that has been used for utility applications and how it has been configured to meet utility needs while addressing the Big Data issues.« less

Trading strategies for distribution company with stochastic distributed energy resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Chunyu; Wang, Qi; Wang, Jianhui

2016-09-01

This paper proposes a methodology to address the trading strategies of a proactive distribution company (PDISCO) engaged in the transmission-level (TL) markets. A one-leader multi-follower bilevel model is presented to formulate the gaming framework between the PDISCO and markets. The lower-level (LL) problems include the TL day-ahead market and scenario-based real-time markets, respectively with the objectives of maximizing social welfare and minimizing operation cost. The upper-level (UL) problem is to maximize the PDISCO’s profit across these markets. The PDISCO’s strategic offers/bids interactively influence the outcomes of each market. Since the LL problems are linear and convex, while the UL problemmore » is non-linear and non-convex, an equivalent primal–dual approach is used to reformulate this bilevel model to a solvable mathematical program with equilibrium constraints (MPEC). The effectiveness of the proposed model is verified by case studies.« less

[France, an attractive country for international clinical research: 2008 survey assessed by Leem (French association of pharmaceutical companies)].

PubMed

Lassale, Catherine; Sibenaler, Claire; Béhier, Jehan-Michel; Plétan, Yannick; Courcier, Soizic

2008-01-01

In order to evaluate the attractiveness of France for conducting international clinical trials, a survey is performed every two years among pharmaceutical companies that are based in France or have affiliates in France. Nineteen companies (61.9 % of the French market) have participated in the current survey which included 385 international phase II and III clinical studies, 77 countries, 29,708 centres and 312,835 patients (included in 2006/2007). France (400 patients/million inhabitants) ranked among the best European recruiters in second position behind Scandinavia. Since 2006, France has improved administrative processes and reduced deadlines for hospital contracts. Protocols are now to be given the go-ahead by French Authorities (Afssaps and CPP) within 60 days, in accordance with European directive. Its performance in early phases, oncology/hematology and vaccines/anti-infectious contribute to the attractiveness of France in international clinical research.

Improving Fermi Orbit Determination and Prediction in an Uncertain Atmospheric Drag Environment

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Newman, Clark P.; Slojkowski, Steven E.; Carpenter, J. Russell

2014-01-01

Orbit determination and prediction of the Fermi Gamma-ray Space Telescope trajectory is strongly impacted by the unpredictability and variability of atmospheric density and the spacecraft's ballistic coefficient. Operationally, Global Positioning System point solutions are processed with an extended Kalman filter for orbit determination, and predictions are generated for conjunction assessment with secondary objects. When these predictions are compared to Joint Space Operations Center radar-based solutions, the close approach distance between the two predictions can greatly differ ahead of the conjunction. This work explores strategies for improving prediction accuracy and helps to explain the prediction disparities. Namely, a tuning analysis is performed to determine atmospheric drag modeling and filter parameters that can improve orbit determination as well as prediction accuracy. A 45% improvement in three-day prediction accuracy is realized by tuning the ballistic coefficient and atmospheric density stochastic models, measurement frequency, and other modeling and filter parameters.

Water quality in the Schuylkill River, Pennsylvania: the potential for long-lead forecasts

NASA Astrophysics Data System (ADS)

Block, P. J.; Peralez, J.

2012-12-01

Prior analysis of pathogen levels in the Schuylkill River has led to a categorical daily forecast of water quality (denoted as red, yellow, or green flag days.) The forecast, available to the public online through the Philadelphia Water Department, is predominantly based on the local precipitation forecast. In this study, we explore the feasibility of extending the forecast to the seasonal scale by associating large-scale climate drivers with local precipitation and water quality parameter levels. This advance information is relevant for recreational activities, ecosystem health, and water treatment (energy, chemicals), as the Schuylkill provides 40% of Philadelphia's water supply. Preliminary results indicate skillful prediction of average summertime water quality parameters and characteristics, including chloride, coliform, turbidity, alkalinity, and others, using season-ahead oceanic and atmospheric variables, predominantly from the North Atlantic. Water quality parameter trends, including historic land use changes along the river, association with climatic variables, and prediction models will be presented.

The role of fear-avoidance and helplessness in explaining functional disability in chronic pain: a prospective study.

PubMed

Samwel, Han J A; Kraaimaat, Floris W; Crul, Ben J P; Evers, Andrea W M

2007-01-01

Based on the fear-avoidance and helplessness models, the relative contribution of fear of pain, avoidance behavior, worrying, and helplessness were examined in relation to fluctuations in functional disability in chronic-pain patients. A cohort of 181 chronic-pain patients first completed various questionnaires and kept a 7-day pain journal during a standard 3-month waiting-list period prior to their scheduled treatment at an Interdisciplinary Pain Centre and did so again immediately preceding the intervention. At baseline, fear of pain, avoidance behavior, and helplessness all predicted functional disability after 3 months. Stepwise regression analyses showed avoidance behavior to be the strongest predictor of change in functional disability followed by helplessness, thus both ahead of fear of pain. The current findings support the roles of both fear-avoidance factors and helplessness in the functional disability in chronic-pain patients awaiting treatment but revealed a central role for avoidance behavior.

Variable Generation Power Forecasting as a Big Data Problem

DOE PAGES

Haupt, Sue Ellen; Kosovic, Branko

2016-10-10

To blend growing amounts of power from renewable resources into utility operations requires accurate forecasts. For both day ahead planning and real-time operations, the power from the wind and solar resources must be predicted based on real-time observations and a series of models that span the temporal and spatial scales of the problem, using the physical and dynamical knowledge as well as computational intelligence. Accurate prediction is a Big Data problem that requires disparate data, multiple models that are each applicable for a specific time frame, and application of computational intelligence techniques to successfully blend all of the model andmore » observational information in real-time and deliver it to the decision makers at utilities and grid operators. This paper describes an example system that has been used for utility applications and how it has been configured to meet utility needs while addressing the Big Data issues.« less

The application of SVR model in the improvement of QbD: a case study of the extraction of podophyllotoxin.

PubMed

Zhai, Chun-Hui; Xuan, Jian-Bang; Fan, Hai-Liu; Zhao, Teng-Fei; Jiang, Jian-Lan

2018-05-03

In order to make a further optimization of process design via increasing the stability of design space, we brought in the model of Support Vector Regression (SVR). In this work, the extraction of podophyllotoxin was researched as a case study based on Quality by Design (QbD). We compared the fitting effect of SVR and the most used quadratic polynomial model (QPM) in QbD, and an analysis was made between the two design spaces obtained by SVR and QPM. As a result, the SVR stayed ahead of QPM in prediction accuracy, the stability of model and the generalization ability. The introduction of SVR into QbD made the extraction process of podophyllotoxin well designed and easier to control. The better fitting effect of SVR improved the application effect of QbD and the universal applicability of SVR, especially for non-linear, complicated and weak-regularity problems, widened the application field of QbD.

Bounds imposed on the sheath velocity of a dense plasma focus by conservation laws and ionization stability condition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Auluck, S. K. H., E-mail: skhauluck@gmail.com, E-mail: skauluck@barc.gov.in

2014-09-15

Experimental data compiled over five decades of dense plasma focus research are consistent with the snowplow model of sheath propagation, based on the hypothetical balance between magnetic pressure driving the plasma into neutral gas ahead and “wind pressure” resisting its motion. The resulting sheath velocity, or the numerically proportional “drive parameter,” is known to be approximately constant for devices optimized for neutron production over 8 decades of capacitor bank energy. This paper shows that the validity of the snowplow hypothesis, with some correction, as well as the non-dependence of sheath velocity on device parameters, have their roots in local conservationmore » laws for mass, momentum, and energy coupled with the ionization stability condition. Both upper and lower bounds on sheath velocity are shown to be related to material constants of the working gas and independent of the device geometry and capacitor bank impedance.« less

A System for Planning Ahead

NASA Technical Reports Server (NTRS)

2002-01-01

A software system that uses artificial intelligence techniques to help with complex Space Shuttle scheduling at Kennedy Space Center is commercially available. Stottler Henke Associates, Inc.(SHAI), is marketing its automatic scheduling system, the Automated Manifest Planner (AMP), to industries that must plan and project changes many different times before the tasks are executed. The system creates optimal schedules while reducing manpower costs. Using information entered into the system by expert planners, the system automatically makes scheduling decisions based upon resource limitations and other constraints. It provides a constraint authoring system for adding other constraints to the scheduling process as needed. AMP is adaptable to assist with a variety of complex scheduling problems in manufacturing, transportation, business, architecture, and construction. AMP can benefit vehicle assembly plants, batch processing plants, semiconductor manufacturing, printing and textiles, surface and underground mining operations, and maintenance shops. For most of SHAI's commercial sales, the company obtains a service contract to customize AMP to a specific domain and then issues the customer a user license.

A novel single-parameter approach for forecasting algal blooms.

PubMed

Xiao, Xi; He, Junyu; Huang, Haomin; Miller, Todd R; Christakos, George; Reichwaldt, Elke S; Ghadouani, Anas; Lin, Shengpan; Xu, Xinhua; Shi, Jiyan

2017-01-01

Harmful algal blooms frequently occur globally, and forecasting could constitute an essential proactive strategy for bloom control. To decrease the cost of aquatic environmental monitoring and increase the accuracy of bloom forecasting, a novel single-parameter approach combining wavelet analysis with artificial neural networks (WNN) was developed and verified based on daily online monitoring datasets of algal density in the Siling Reservoir, China and Lake Winnebago, U.S.A. Firstly, a detailed modeling process was illustrated using the forecasting of cyanobacterial cell density in the Chinese reservoir as an example. Three WNN models occupying various prediction time intervals were optimized through model training using an early stopped training approach. All models performed well in fitting historical data and predicting the dynamics of cyanobacterial cell density, with the best model predicting cyanobacteria density one-day ahead (r = 0.986 and mean absolute error = 0.103 × 10 4  cells mL -1 ). Secondly, the potential of this novel approach was further confirmed by the precise predictions of algal biomass dynamics measured as chl a in both study sites, demonstrating its high performance in forecasting algal blooms, including cyanobacteria as well as other blooming species. Thirdly, the WNN model was compared to current algal forecasting methods (i.e. artificial neural networks, autoregressive integrated moving average model), and was found to be more accurate. In addition, the application of this novel single-parameter approach is cost effective as it requires only a buoy-mounted fluorescent probe, which is merely a fraction (∼15%) of the cost of a typical auto-monitoring system. As such, the newly developed approach presents a promising and cost-effective tool for the future prediction and management of harmful algal blooms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Essays in the California electricity reserves markets

NASA Astrophysics Data System (ADS)

Metaxoglou, Konstantinos

This dissertation examines inefficiencies in the California electricity reserves markets. In Chapter 1, I use the information released during the investigation of the state's electricity crisis of 2000 and 2001 by the Federal Energy Regulatory Commission to diagnose allocative inefficiencies. Building upon the work of Wolak (2000), I calculate a lower bound for the sellers' price-cost margins using the inverse elasticities of their residual demand curves. The downward bias in my estimates stems from the fact that I don't account for the hierarchical substitutability of the reserve types. The margins averaged at least 20 percent for the two highest quality types of reserves, regulation and spinning, generating millions of dollars in transfers to a handful of sellers. I provide evidence that the deviations from marginal cost pricing were due to the markets' high concentration and a principal-agent relationship that emerged from their design. In Chapter 2, I document systematic differences between the markets' day- and hour-ahead prices. I use a high-dimensional vector moving average model to estimate the premia and conduct correct inferences. To obtain exact maximum likelihood estimates of the model, I employ the EM algorithm that I develop in Chapter 3. I uncover significant day-ahead premia, which I attribute to market design characteristics too. On the demand side, the market design established a principal-agent relationship between the markets' buyers (principal) and their supervisory authority (agent). The agent had very limited incentives to shift reserve purchases to the lower priced hour-ahead markets. On the supply side, the market design raised substantial entry barriers by precluding purely speculative trading and by introducing a complicated code of conduct that induced uncertainty about which actions were subject to regulatory scrutiny. In Chapter 3, I introduce a state-space representation for vector autoregressive moving average models that enables exact maximum likelihood estimation using the EM algorithm. Moreover, my algorithm uses only analytical expressions; it requires the Kalman filter and a fixed-interval smoother in the E step and least squares-type regression in the M step. In contrast, existing maximum likelihood estimation methods require numerical differentiation, both for univariate and multivariate models.

A Multi-Period Optimization Model for Service Providers Using Online Reservation Systems: An Application to Hotels.

PubMed

Xu, Ming; Jiao, Yan; Li, Xiaoming; Cao, Qingfeng; Wang, Xiaoyang

2015-01-01

This paper presents a multi-period optimization model for high margin and zero salvage products in online distribution channels with classifying customers based on number of products required. Taking hotel customers as an example, one is regular customers who reserve rooms for one day, and the other is long term stay (LTS) customers who reserve rooms for a number of days. LTS may guarantee a specific amount of demand and generate opportunity income for a certain number of periods, meanwhile with risk of punishment incurred by overselling. By developing an operational optimization model and exploring the effects of parameters on optimal decisions, we suggest that service providers should make decisions based on the types of customers, number of products required, and duration of multi-period to reduce the loss of reputation and obtain more profit; at the same time, multi-period buying customers should buy products early. Finally, the paper conducts a numerical experiment, and the results are consistent with prevailing situations.

A Multi-Period Optimization Model for Service Providers Using Online Reservation Systems: An Application to Hotels

PubMed Central

Xu, Ming; Jiao, Yan; Li, Xiaoming; Cao, Qingfeng; Wang, Xiaoyang

2015-01-01

This paper presents a multi-period optimization model for high margin and zero salvage products in online distribution channels with classifying customers based on number of products required. Taking hotel customers as an example, one is regular customers who reserve rooms for one day, and the other is long term stay (LTS) customers who reserve rooms for a number of days. LTS may guarantee a specific amount of demand and generate opportunity income for a certain number of periods, meanwhile with risk of punishment incurred by overselling. By developing an operational optimization model and exploring the effects of parameters on optimal decisions, we suggest that service providers should make decisions based on the types of customers, number of products required, and duration of multi-period to reduce the loss of reputation and obtain more profit; at the same time, multi-period buying customers should buy products early. Finally, the paper conducts a numerical experiment, and the results are consistent with prevailing situations. PMID:26147663

46 CFR 190.02-1 - Navigation bridge visibility.

Code of Federal Regulations, 2012 CFR

2012-10-01

... lengths or 500 meters (1640 feet) from dead ahead to 10 degrees on either side of the vessel. Within this... arc from at least 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to at... 45 degrees on the opposite bow, through dead ahead, to at least dead astern. (4) From the main...

46 CFR 72.04-1 - Navigation bridge visibility.

Code of Federal Regulations, 2014 CFR

2014-10-01

... meters (1640 feet) from dead ahead to 10 degrees on either side of the vessel. Within this arc of... 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to at least 22.5 degrees... bow, through dead ahead, to at least dead astern. (4) From the main steering position, the field of...

46 CFR 108.801 - Navigation bridge visibility.

Code of Federal Regulations, 2011 CFR

2011-10-01

... lengths or 500 meters (1,640 feet) from dead ahead to 10 degrees on either side of the vessel. Within this... arc from at least 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to at... 45 degrees on the opposite bow, through dead ahead, to at least dead astern. (4) From the main...

33 CFR 164.15 - Navigation bridge visibility.

Code of Federal Regulations, 2013 CFR

2013-07-01

... obscured by more than the lesser of two ship lengths or 500 meters (1640 feet) from dead ahead to 10... the vessel, through dead ahead, to at least 22.5 degrees abaft the beam on the other side of the... of vision must extend over an arc from at least 45 degrees on the opposite bow, through dead ahead...

46 CFR 190.02-1 - Navigation bridge visibility.

Code of Federal Regulations, 2014 CFR

2014-10-01

... lengths or 500 meters (1640 feet) from dead ahead to 10 degrees on either side of the vessel. Within this... arc from at least 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to at... 45 degrees on the opposite bow, through dead ahead, to at least dead astern. (4) From the main...

33 CFR 164.15 - Navigation bridge visibility.

Code of Federal Regulations, 2014 CFR

2014-07-01

... obscured by more than the lesser of two ship lengths or 500 meters (1640 feet) from dead ahead to 10... the vessel, through dead ahead, to at least 22.5 degrees abaft the beam on the other side of the... of vision must extend over an arc from at least 45 degrees on the opposite bow, through dead ahead...

46 CFR 190.02-1 - Navigation bridge visibility.

Code of Federal Regulations, 2011 CFR

2011-10-01

... lengths or 500 meters (1640 feet) from dead ahead to 10 degrees on either side of the vessel. Within this... arc from at least 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to at... 45 degrees on the opposite bow, through dead ahead, to at least dead astern. (4) From the main...

46 CFR 72.04-1 - Navigation bridge visibility.

Code of Federal Regulations, 2012 CFR

2012-10-01

... meters (1640 feet) from dead ahead to 10 degrees on either side of the vessel. Within this arc of... 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to at least 22.5 degrees... bow, through dead ahead, to at least dead astern. (4) From the main steering position, the field of...

46 CFR 190.02-1 - Navigation bridge visibility.

Code of Federal Regulations, 2013 CFR

2013-10-01

... lengths or 500 meters (1640 feet) from dead ahead to 10 degrees on either side of the vessel. Within this... arc from at least 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to at... 45 degrees on the opposite bow, through dead ahead, to at least dead astern. (4) From the main...

46 CFR 72.04-1 - Navigation bridge visibility.

Code of Federal Regulations, 2013 CFR

2013-10-01

... meters (1640 feet) from dead ahead to 10 degrees on either side of the vessel. Within this arc of... 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to at least 22.5 degrees... bow, through dead ahead, to at least dead astern. (4) From the main steering position, the field of...

46 CFR 108.801 - Navigation bridge visibility.

Code of Federal Regulations, 2013 CFR

2013-10-01

... lengths or 500 meters (1,640 feet) from dead ahead to 10 degrees on either side of the vessel. Within this... arc from at least 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to at... 45 degrees on the opposite bow, through dead ahead, to at least dead astern. (4) From the main...

46 CFR 108.801 - Navigation bridge visibility.

Code of Federal Regulations, 2012 CFR

2012-10-01

... lengths or 500 meters (1,640 feet) from dead ahead to 10 degrees on either side of the vessel. Within this... arc from at least 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to at... 45 degrees on the opposite bow, through dead ahead, to at least dead astern. (4) From the main...

33 CFR 164.15 - Navigation bridge visibility.

Code of Federal Regulations, 2012 CFR

2012-07-01

... obscured by more than the lesser of two ship lengths or 500 meters (1640 feet) from dead ahead to 10... the vessel, through dead ahead, to at least 22.5 degrees abaft the beam on the other side of the... of vision must extend over an arc from at least 45 degrees on the opposite bow, through dead ahead...

46 CFR 108.801 - Navigation bridge visibility.

Code of Federal Regulations, 2014 CFR

2014-10-01

... lengths or 500 meters (1,640 feet) from dead ahead to 10 degrees on either side of the vessel. Within this... arc from at least 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to at... 45 degrees on the opposite bow, through dead ahead, to at least dead astern. (4) From the main...

Advanced inflow forecasting for a hydropower plant in an Alpine hydropower regulated catchment - coupling of operational and hydrological forecasts

NASA Astrophysics Data System (ADS)

Tilg, Anna-Maria; Schöber, Johannes; Huttenlau, Matthias; Messner, Jakob; Achleitner, Stefan

2017-04-01

Hydropower is a renewable energy source which can help to stabilize fluctuations in the volatile energy market. Especially pumped-storage infrastructures in the European Alps play an important role within the European energy grid system. Today, the runoff of rivers in the Alps is often influenced by cascades of hydropower infrastructures where the operational procedures are triggered by energy market demands, water deliveries and flood control aspects rather than by hydro-meteorological variables. An example for such a highly hydropower regulated river is the catchment of the river Inn in the Eastern European Alps, originating in the Engadin (Switzerland). A new hydropower plant is going to be built as transboundary project at the boarder of Switzerland and Austria using the water of the Inn River. For the operation, a runoff forecast to the plant is required. The challenge in this case is that a high proportion of runoff is turbine water from an upstream situated hydropower cascade. The newly developed physically based hydrological forecasting system is mainly capable to cover natural hydrological runoff processes caused by storms and snow melt but can model only a small degree of human impact. These discontinuous parts of the runoff downstream of the pumped storage are described by means of an additional statistical model which has been developed. The main goal of the statistical model is to forecast the turbine water up to five days in advance. The lead time of the data driven model exceeds the lead time of the used energy production forecast. Additionally, the amount of turbine water is linked to the need of electricity production and the electricity price. It has been shown that especially the parameters day-ahead prognosis of the energy production and turbine inflow of the previous week are good predictors and are therefore used as input parameters for the model. As the data is restricted due to technical conditions, so-called Tobit models have been used to develop a linear regression for the runoff forecast. Although the day-ahead prognosis cannot always be kept, the regression model delivers, especially during office hours, very reasonable results. In the remaining hours the error between measurement and the forecast increases. Overall, the inflow forecast can be substantially improved by the implementation of the developed regression in the hydrological modelling system.

Advanced Communication and Control Solutions of Distributed Energy Resources (DER)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asgeirsson, Haukur; Seguin, Richard; Sherding, Cameron

2007-01-10

This report covers work performed in Phase II of a two phase project whose objective was to demonstrate the aggregation of multiple Distributed Energy Resources (DERs) and to offer them into the energy market. The Phase I work (DE-FC36-03CH11161) created an integrated, but distributed, system and procedures to monitor and control multiple DERs from numerous manufacturers connected to the electric distribution system. Procedures were created which protect the distribution network and personnel that may be working on the network. Using the web as the communication medium for control and monitoring of the DERs, the integration of information and security wasmore » accomplished through the use of industry standard protocols such as secure SSL,VPN and ICCP. The primary objective of Phase II was to develop the procedures for marketing the power of the Phase I aggregated DERs in the energy market, increase the number of DER units, and implement the marketing procedures (interface with ISOs) for the DER generated power. The team partnered with the Midwest Independent System Operator (MISO), the local ISO, to address the energy market and demonstrate the economic dispatch of DERs in response to market signals. The selection of standards-based communication technologies offers the ability of the system to be deployed and integrated with other utilities’ resources. With the use of a data historian technology to facilitate the aggregation, the developed algorithms and procedures can be verified, audited, and modified. The team has demonstrated monitoring and control of multiple DERs as outlined in phase I report including procedures to perform these operations in a secure and safe manner. In Phase II, additional DER units were added. We also expanded on our phase I work to enhance communication security and to develop the market model of having DERs, both customer and utility owned, participate in the energy market. We are proposing a two-part DER energy market model--a utility need business model and an independent energy aggregator-business model. The approach of developing two group models of DER energy participation in the market is unique. The Detroit Edison (DECo, Utility)-led team includes: DTE Energy Technologies (Dtech, DER provider), Electrical Distribution Design (EDD, Virginia Tech company supporting EPRI’s Distribution Engineering Workstation, DEW), Systems Integration Specialists Company (SISCO, economic scheduling and real-time protocol integrator), and OSIsoft (PI software system for managing real-time information). This team is focused on developing the application engineering, including software systems necessary for DER’s integration, control and sale into the market place. Phase II Highlights Installed and tested an ICCP link with SSL (security) between DECo, the utility, and DTE Energy Technologies (DTECH), the aggregator, making DER data available to the utility for both monitoring and control. Installed and tested PI process book with circuit & DER operational models for DECo SOC/ROC operator’s use for monitoring of both utility circuit and customer DER parameters. The PI Process Book models also included DER control for the DECo SOC/ROC operators, which was tested and demonstrated control. The DER Tagging and Operating Procedures were developed, which allowed that control to be done in a safe manner, were modified for required MOC/MISO notification procedures. The Distribution Engineering Workstation (DEW) was modified to include temperature normalized load research statistics, using a 30 hour day-ahead weather feed. This allowed day-ahead forecasting of the customer load profile and the entire circuit to determine overload and low voltage problems. This forecast at the point of common coupling was passed to DTech DR SOC for use in their economic dispatch algorithm. Standard Work Instructions were developed for DER notification, sale, and operation into the MISO market. A software mechanism consisting of a suite of new and revised functionality was developed that integrated with the local ISO such that offers can be made electronically without human intervention. A suite of software was developed by DR SOC enabling DER usage in real time and day-ahead: Generation information file exchange with PI and the utility power flow A utility day-ahead information file Energy Offer Web Service Market Result Web Service Real-Time Meter Data Web Service Real-Time Notification Web Service Registered over 20 DER with MISO in Demand Response Market and demonstrated electronic sale to MISO.« less

Accurate Influenza Monitoring and Forecasting Using Novel Internet Data Streams: A Case Study in the Boston Metropolis

PubMed Central

Lu, Fred Sun; Hou, Suqin; Baltrusaitis, Kristin; Shah, Manan; Leskovec, Jure; Sosic, Rok; Hawkins, Jared; Brownstein, John; Conidi, Giuseppe; Gunn, Julia; Gray, Josh; Zink, Anna

2018-01-01

Background Influenza outbreaks pose major challenges to public health around the world, leading to thousands of deaths a year in the United States alone. Accurate systems that track influenza activity at the city level are necessary to provide actionable information that can be used for clinical, hospital, and community outbreak preparation. Objective Although Internet-based real-time data sources such as Google searches and tweets have been successfully used to produce influenza activity estimates ahead of traditional health care–based systems at national and state levels, influenza tracking and forecasting at finer spatial resolutions, such as the city level, remain an open question. Our study aimed to present a precise, near real-time methodology capable of producing influenza estimates ahead of those collected and published by the Boston Public Health Commission (BPHC) for the Boston metropolitan area. This approach has great potential to be extended to other cities with access to similar data sources. Methods We first tested the ability of Google searches, Twitter posts, electronic health records, and a crowd-sourced influenza reporting system to detect influenza activity in the Boston metropolis separately. We then adapted a multivariate dynamic regression method named ARGO (autoregression with general online information), designed for tracking influenza at the national level, and showed that it effectively uses the above data sources to monitor and forecast influenza at the city level 1 week ahead of the current date. Finally, we presented an ensemble-based approach capable of combining information from models based on multiple data sources to more robustly nowcast as well as forecast influenza activity in the Boston metropolitan area. The performances of our models were evaluated in an out-of-sample fashion over 4 influenza seasons within 2012-2016, as well as a holdout validation period from 2016 to 2017. Results Our ensemble-based methods incorporating information from diverse models based on multiple data sources, including ARGO, produced the most robust and accurate results. The observed Pearson correlations between our out-of-sample flu activity estimates and those historically reported by the BPHC were 0.98 in nowcasting influenza and 0.94 in forecasting influenza 1 week ahead of the current date. Conclusions We show that information from Internet-based data sources, when combined using an informed, robust methodology, can be effectively used as early indicators of influenza activity at fine geographic resolutions. PMID:29317382

Predicting Drug Recalls From Internet Search Engine Queries.

PubMed

Yom-Tov, Elad

2017-01-01

Batches of pharmaceuticals are sometimes recalled from the market when a safety issue or a defect is detected in specific production runs of a drug. Such problems are usually detected when patients or healthcare providers report abnormalities to medical authorities. Here, we test the hypothesis that defective production lots can be detected earlier by monitoring queries to Internet search engines. We extracted queries from the USA to the Bing search engine, which mentioned one of the 5195 pharmaceutical drugs during 2015 and all recall notifications issued by the Food and Drug Administration (FDA) during that year. By using attributes that quantify the change in query volume at the state level, we attempted to predict if a recall of a specific drug will be ordered by FDA in a time horizon ranging from 1 to 40 days in future. Our results show that future drug recalls can indeed be identified with an AUC of 0.791 and a lift at 5% of approximately 6 when predicting a recall occurring one day ahead. This performance degrades as prediction is made for longer periods ahead. The most indicative attributes for prediction are sudden spikes in query volume about a specific medicine in each state. Recalls of prescription drugs and those estimated to be of medium-risk are more likely to be identified using search query data. These findings suggest that aggregated Internet search engine data can be used to facilitate in early warning of faulty batches of medicines.

Modeling Reservoir-River Networks in Support of Optimizing Seasonal-Scale Reservoir Operations

NASA Astrophysics Data System (ADS)

Villa, D. L.; Lowry, T. S.; Bier, A.; Barco, J.; Sun, A.

2011-12-01

HydroSCOPE (Hydropower Seasonal Concurrent Optimization of Power and the Environment) is a seasonal time-scale tool for scenario analysis and optimization of reservoir-river networks. Developed in MATLAB, HydroSCOPE is an object-oriented model that simulates basin-scale dynamics with an objective of optimizing reservoir operations to maximize revenue from power generation, reliability in the water supply, environmental performance, and flood control. HydroSCOPE is part of a larger toolset that is being developed through a Department of Energy multi-laboratory project. This project's goal is to provide conventional hydropower decision makers with better information to execute their day-ahead and seasonal operations and planning activities by integrating water balance and operational dynamics across a wide range of spatial and temporal scales. This presentation details the modeling approach and functionality of HydroSCOPE. HydroSCOPE consists of a river-reservoir network model and an optimization routine. The river-reservoir network model simulates the heat and water balance of river-reservoir networks for time-scales up to one year. The optimization routine software, DAKOTA (Design Analysis Kit for Optimization and Terascale Applications - dakota.sandia.gov), is seamlessly linked to the network model and is used to optimize daily volumetric releases from the reservoirs to best meet a set of user-defined constraints, such as maximizing revenue while minimizing environmental violations. The network model uses 1-D approximations for both the reservoirs and river reaches and is able to account for surface and sediment heat exchange as well as ice dynamics for both models. The reservoir model also accounts for inflow, density, and withdrawal zone mixing, and diffusive heat exchange. Routing for the river reaches is accomplished using a modified Muskingum-Cunge approach that automatically calculates the internal timestep and sub-reach lengths to match the conditions of each timestep and minimize computational overhead. Power generation for each reservoir is estimated using a 2-dimensional regression that accounts for both the available head and turbine efficiency. The object-oriented architecture makes run configuration easy to update. The dynamic model inputs include inflow and meteorological forecasts while static inputs include bathymetry data, reservoir and power generation characteristics, and topological descriptors. Ensemble forecasts of hydrological and meteorological conditions are supplied in real-time by Pacific Northwest National Laboratory and are used as a proxy for uncertainty, which is carried through the simulation and optimization process to produce output that describes the probability that different operational scenario's will be optimal. The full toolset, which includes HydroSCOPE, is currently being tested on the Feather River system in Northern California and the Upper Colorado Storage Project.

78 FR 72949 - Self-Regulatory Organizations; BATS Exchange, Inc.; Order Approving a Proposed Rule Change To...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-04

... Conform to FINRA Rule 5320 Relating to Trading Ahead of Customer Orders November 27, 2013. I. Introduction... Change The Exchange proposes to amend Rule 12.6, which limits trading ahead of customer orders by Members... proposed amendments to Rule 12.6 would prohibit Members from trading ahead of customer orders, subject to...

78 FR 72944 - Self-Regulatory Organizations; BATS Y-Exchange, Inc.; Order Approving a Proposed Rule Change To...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-04

....6 To Conform to FINRA Rule 5320 Relating to Trading Ahead of Customer Orders November 27, 2013. I... Rule Change The Exchange proposes to amend Rule 12.6, which limits trading ahead of customer orders by... proposed amendments to Rule 12.6 would prohibit Members from trading ahead of customer orders, subject to...

78 FR 60226 - Amendments To Implement Certain Provisions of the Moving Ahead for Progress in the 21st Century...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-01

... Moving Ahead for Progress in the 21st Century Act (MAP-21) AGENCY: Federal Motor Carrier Safety...) adopts, as final, certain regulations required by the Moving Ahead for Progress in the 21st Century... required by MAP-21. Benefits and Costs The rule provisions considered both individually and in the...

46 CFR 92.03-1 - Navigation bridge visibility.

Code of Federal Regulations, 2011 CFR

2011-10-01

... of two ship lengths or 500 meters (1,640 feet) from dead ahead to 10 degrees on either side of the... over an arc from at least 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to... least 45 degrees on the opposite bow, through dead ahead, to at least dead astern. (4) From the main...

46 CFR 32.16-1 - Navigation bridge visibility-T/ALL.

Code of Federal Regulations, 2013 CFR

2013-10-01

... meters (1,640 feet) from dead ahead to 10 degrees on either side of the vessel. Within this arc of... 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to at least 22.5 degrees... bow, through dead ahead, to at least dead astern. (4) From the main steering position, the field of...

46 CFR 32.16-1 - Navigation bridge visibility-T/ALL.

Code of Federal Regulations, 2014 CFR

2014-10-01

... meters (1,640 feet) from dead ahead to 10 degrees on either side of the vessel. Within this arc of... 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to at least 22.5 degrees... bow, through dead ahead, to at least dead astern. (4) From the main steering position, the field of...

46 CFR 92.03-1 - Navigation bridge visibility.

Code of Federal Regulations, 2014 CFR

2014-10-01

... of two ship lengths or 500 meters (1,640 feet) from dead ahead to 10 degrees on either side of the... over an arc from at least 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to... least 45 degrees on the opposite bow, through dead ahead, to at least dead astern. (4) From the main...

46 CFR 92.03-1 - Navigation bridge visibility.

Code of Federal Regulations, 2012 CFR

2012-10-01

... of two ship lengths or 500 meters (1,640 feet) from dead ahead to 10 degrees on either side of the... over an arc from at least 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to... least 45 degrees on the opposite bow, through dead ahead, to at least dead astern. (4) From the main...

46 CFR 32.16-1 - Navigation bridge visibility-T/ALL.

Code of Federal Regulations, 2012 CFR

2012-10-01

... meters (1,640 feet) from dead ahead to 10 degrees on either side of the vessel. Within this arc of... 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to at least 22.5 degrees... bow, through dead ahead, to at least dead astern. (4) From the main steering position, the field of...

46 CFR 92.03-1 - Navigation bridge visibility.

Code of Federal Regulations, 2013 CFR

2013-10-01

... of two ship lengths or 500 meters (1,640 feet) from dead ahead to 10 degrees on either side of the... over an arc from at least 22.5 degrees abaft the beam on one side of the vessel, through dead ahead, to... least 45 degrees on the opposite bow, through dead ahead, to at least dead astern. (4) From the main...

Ahead of the Curve. Future Shifts in Higher Education

ERIC Educational Resources Information Center

Jackson, Shirley Ann

2005-01-01

It used to be that physicians stayed "ahead of the curve" with new research in their secialties by reading medical journal articles. Yet medical literature databases today house more than 10 million abstracts and are adding 7,000 to 8,000 more each week. Staying ahead of the curve is thus impossible for any single individual to manage. Further,…

78 FR 62828 - Self-Regulatory Organizations; BATS Exchange, Inc.; Notice of Filing of a Proposed Rule Change To...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-22

... To Conform to FINRA Rule 5320 Relating to Trading Ahead of Customer Orders October 11, 2013. Pursuant... Exchange proposes to amend Rule 12.6, which limits trading ahead of customer orders by Members,\\3\\ to make... would prohibit Members from trading ahead of customer orders, subject to specified exceptions. The...

78 FR 62896 - Self-Regulatory Organizations; BATS Y-Exchange, Inc.; Notice of Filing of a Proposed Rule Change...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-22

....6 To Conform to FINRA Rule 5320 Relating to Trading Ahead of Customer Orders October 11, 2013... Change 1. Purpose The Exchange proposes to amend Rule 12.6, which limits trading ahead of customer orders..., amended Rule 12.6 would prohibit Members from trading ahead of customer orders, subject to specified...

Linear Look-Ahead in Conjunctive Cells: An Entorhinal Mechanism for Vector-Based Navigation

PubMed Central

Kubie, John L.; Fenton, André A.

2012-01-01

The crisp organization of the “firing bumps” of entorhinal grid cells and conjunctive cells leads to the notion that the entorhinal cortex may compute linear navigation routes. Specifically, we propose a process, termed “linear look-ahead,” by which a stationary animal could compute a series of locations in the direction it is facing. We speculate that this computation could be achieved through learned patterns of connection strengths among entorhinal neurons. This paper has three sections. First, we describe the minimal grid cell properties that will be built into our network. Specifically, the network relies on “rigid modules” of neurons, where all members have identical grid scale and orientation, but differ in spatial phase. Additionally, these neurons must be densely interconnected with synapses that are modifiable early in the animal’s life. Second, we investigate whether plasticity during short bouts of locomotion could induce patterns of connections amongst grid cells or conjunctive cells. Finally, we run a simulation to test whether the learned connection patterns can exhibit linear look-ahead. Our results are straightforward. A simulated 30-min walk produces weak strengthening of synapses between grid cells that do not support linear look-ahead. Similar training in a conjunctive cell module produces a small subset of very strong connections between cells. These strong pairs have three properties: the pre- and post-synaptic cells have similar heading direction. The cell pairs have neighboring grid bumps. Finally, the spatial offset of firing bumps of the cell pair is in the direction of the common heading preference. Such a module can produce strong and accurate linear look-ahead starting in any location and extending in any direction. We speculate that this process may: (1) compute linear paths to goals; (2) update grid cell firing during navigation; and (3) stabilize the rigid modules of grid cells and conjunctive cells. PMID:22557948

Sputtering, Surging Sun [HD Video

NASA Image and Video Library

2017-12-08

STEREO (Ahead) caught the action as one edge of a single active region spurted out more than a dozen surges of plasma in less than two days (Feb. 15-16, 2010). As seen in extreme UV light, the surges were narrow and directional outbursts driven by intense magnetic activity in the active region. While these kinds of outbursts have been observed numerous times, it was the frequency of so many surges in a short span of time that caught our attention. In this wavelength of UV light we are seeing singly ionized Helium at about 60,000 degrees C. For more information: stereo.gsfc.nasa.gov/ Credit: NASA/GSFC/STEREO To learn more about NASA's Sun Earth Day go here: sunearthday.nasa.gov/2010/index.php

Transportation asset management : organizational performance and risk review : final report.

DOT National Transportation Integrated Search

2012-11-15

The 2012 Federal reauthorization of surface transportation programs, Moving Ahead for Progress in the 21st : Century (MAP-21) formally introduced performance-based decision making for investments in surface : transportation programs. This report revi...

Optimization of FPM system in Barsukovskoye deposit with hydrodynamic modeling and analysis of inter-well interaction

NASA Astrophysics Data System (ADS)

Almukhametova, E. M.; Gizetdinov, I. A.

2018-05-01

Development of most deposits in Russia is accompanied with a high level of crude water cut. More than 70% of the operating well count of Barsukovskoye deposit operates with water; about 12% of the wells are characterized by a saturated water cut; many wells with high water cut are idling. To optimize the current FPM system of the Barsukovskoye deposit, a calculation method over a hydrodynamic model was applied with further analysis of hydrodynamic connectivity between the wells. A plot was selected, containing several wells with water cut going ahead of reserve recovery rate; injection wells, exerting the most influence onto the selected producer wells, were determined. Then, several variants were considered for transformation of the FPM system of this plot. The possible cases were analyzed with the hydrodynamic model with further determination of economic effect of each of them.

Semantic Representation and Scale-Up of Integrated Air Traffic Management Data

NASA Technical Reports Server (NTRS)

Keller, Richard M.; Ranjan, Shubha; Wei, Mei Y.; Eshow, Michelle M.

2016-01-01

Each day, the global air transportation industry generates a vast amount of heterogeneous data from air carriers, air traffic control providers, and secondary aviation entities handling baggage, ticketing, catering, fuel delivery, and other services. Generally, these data are stored in isolated data systems, separated from each other by significant political, regulatory, economic, and technological divides. These realities aside, integrating aviation data into a single, queryable, big data store could enable insights leading to major efficiency, safety, and cost advantages. In this paper, we describe an implemented system for combining heterogeneous air traffic management data using semantic integration techniques. The system transforms data from its original disparate source formats into a unified semantic representation within an ontology-based triple store. Our initial prototype stores only a small sliver of air traffic data covering one day of operations at a major airport. The paper also describes our analysis of difficulties ahead as we prepare to scale up data storage to accommodate successively larger quantities of data -- eventually covering all US commercial domestic flights over an extended multi-year timeframe. We review several approaches to mitigating scale-up related query performance concerns.

Computational tool for optimizing the essential oils utilization in inhibiting the bacterial growth

PubMed Central

El-Attar, Noha E; Awad, Wael A

2017-01-01

Day after day, the importance of relying on nature in many fields such as food, medical, pharmaceutical industries, and others is increasing. Essential oils (EOs) are considered as one of the most significant natural products for use as antimicrobials, antioxidants, antitumorals, and anti-inflammatories. Optimizing the usage of EOs is a big challenge faced by the scientific researchers because of the complexity of chemical composition of every EO, in addition to the difficulties to determine the best in inhibiting the bacterial activity. The goal of this article is to present a new computational tool based on two methodologies: reduction by using rough sets and optimization with particle swarm optimization. The developed tool dubbed as Essential Oil Reduction and Optimization Tool is applied on 24 types of EOs that have been tested toward 17 different species of bacteria. PMID:28919787

The role of hydrology in water resources management

NASA Astrophysics Data System (ADS)

Shamir, U.

2011-12-01

Modern water resources management developed as a branch of science based engineering since the landmark publication of Mass et al. (1962&1967) which emerged from the Harvard Water Program. Clearly, water was managed much earlier, in fact since the early days of civilization, as evidenced by the publication of Vitruvius on architecture in the 1st Century BC, but the 1950s marked the advent of modeling enabled by computers, which transformed the field we call Water Resources Management (WRM). Since then, thousands of papers have been published and thousands of decisions and projects have been aided by WRM methodologies and model results. This presentation is not an historical review of water resources management, although it appears in a session titled The Evolution of WRM Paradigms. Instead, it is an attempt to discuss the role of hydrology as a feeder of information for the management domain. The issues faced by hydrologists who work to serve and support WRM will be discussed and elucidated by case studies. For hydrologists, some of the important points in this regard are: - Planning, design and operation are three interconnected "layers" of WRM. Planning is where the sources and consumers are identified, the overall "architecture" of a proposed system is laid out, including its topology and connectivity. Design is where sizes of facilities are fixed. Operational policy determines the operation of the system under a selected forecasted set of typical and/or critical conditions, while real-time operation means setting the operational variables for a defined time period ahead (hour, day, week, month, year). The three "layers" are inter-connected and inter-dependent, but still can be addressed differently. - Hydrological data of different types are required, according to the management issue being addressed. They range from short term now-casting/forecasting for real-time operation and response, e.g., for flood protection, to long-term time probabilistic series and ensembles for planning, which consider changing natural and anthropogenic drivers (land use, climate change). Since hydrology is a continuous process that is not divided internally according to the needs of management, the hydrological analysis must be geared to produce the suitable information for the different management issues. - Aggregation and disaggregation in space and time: selection of the level of detail in time and space should begin from the needs of the management issue being addressed, and dictate the monitoring, collection and processing. - Water quality: should receive more attention, as it is playing an ever increasing role in management, including its importance in ecological services. - Optimization, simulation and combining the two: optimization for WRM is used extensively. Some optimization models are able to address uncertainty internally, and further development continues. Simulation is easier to employ, but it merely produces "if-then" analysis. Combination of optimization and simulation is a common way to combine the advantages of the two. - Uncertainty, forecasting, ensembles: the uncertainties inherent in hydrological analysis and forecasting lead to the requirement for generating forecasts with a probabilistic characterization. This can be in the form of PDFs, time series, ensembles.

Selenoprotein P: an extracellular protein with unique physical characteristics and a role in selenium homeostasis.

PubMed

Burk, Raymond F; Hill, Kristina E

2005-01-01

Selenoprotein P is an abundant extracellular glycoprotein that is rich in selenocysteine. It has two domains with respect to selenium content. The N-terminal domain of the rat protein contains one selenocysteine residue in a UxxC redox motif. This domain also has a pH-sensitive heparin-binding site and two histidine-rich amino acid stretches. The smaller C-terminal domain contains nine selenocysteine and ten cysteine residues. Four isoforms of selenoprotein P are present in rat plasma. They share the same N terminus and amino acid sequence. One isoform is full length and the three others terminate at the positions of the second, third, and seventh selenocysteine residues. Selenoprotein P turns over rapidly in rat plasma with the consequence that approximately 25% of the amount of whole-body selenium passes through it each day. Evidence supports functions of the protein in selenium homeostasis and oxidant defense. Selenoprotein P knockout mice have very low selenium concentrations in the brain, the testis, and the fetus, with severe pathophysiological consequences in each tissue. In addition, those mice waste moderate amounts of selenium in the urine. Selenoprotein P binds to endothelial cells in the rat, and plasma levels of the protein correlate with prevention of diquat-induced lipid peroxidation and hepatic endothelial cell injury. The mechanisms of these apparent functions remain speculative and much work on the mechanism of selenoprotein P function lies ahead. Measurement of selenoprotein P in human plasma has shown that it is depressed by selenium deficiency and by cirrhosis. Selenium supplementation of selenium-deficient human subjects showed that glutathione peroxidase activity was optimized before selenoprotein P concentration was optimized, indicating that plasma selenoprotein P is the better index of human selenium nutritional status.

Optimal Operation of Energy Storage in Power Transmission and Distribution

NASA Astrophysics Data System (ADS)

Akhavan Hejazi, Seyed Hossein

In this thesis, we investigate optimal operation of energy storage units in power transmission and distribution grids. At transmission level, we investigate the problem where an investor-owned independently-operated energy storage system seeks to offer energy and ancillary services in the day-ahead and real-time markets. We specifically consider the case where a significant portion of the power generated in the grid is from renewable energy resources and there exists significant uncertainty in system operation. In this regard, we formulate a stochastic programming framework to choose optimal energy and reserve bids for the storage units that takes into account the fluctuating nature of the market prices due to the randomness in the renewable power generation availability. At distribution level, we develop a comprehensive data set to model various stochastic factors on power distribution networks, with focus on networks that have high penetration of electric vehicle charging load and distributed renewable generation. Furthermore, we develop a data-driven stochastic model for energy storage operation at distribution level, where the distribution of nodal voltage and line power flow are modelled as stochastic functions of the energy storage unit's charge and discharge schedules. In particular, we develop new closed-form stochastic models for such key operational parameters in the system. Our approach is analytical and allows formulating tractable optimization problems. Yet, it does not involve any restricting assumption on the distribution of random parameters, hence, it results in accurate modeling of uncertainties. By considering the specific characteristics of random variables, such as their statistical dependencies and often irregularly-shaped probability distributions, we propose a non-parametric chance-constrained optimization approach to operate and plan energy storage units in power distribution girds. In the proposed stochastic optimization, we consider uncertainty from various elements, such as solar photovoltaic , electric vehicle chargers, and residential baseloads, in the form of discrete probability functions. In the last part of this thesis we address some other resources and concepts for enhancing the operation of power distribution and transmission systems. In particular, we proposed a new framework to determine the best sites, sizes, and optimal payment incentives under special contracts for committed-type DG projects to offset distribution network investment costs. In this framework, the aim is to allocate DGs such that the profit gained by the distribution company is maximized while each DG unit's individual profit is also taken into account to assure that private DG investment remains economical.

Optimal Sequence of Irinotecan and Oxaliplatin-Based Regimens in Metastatic Colorectal Cancer: A Population-Based Observational Study

PubMed Central

Lin, Ching-Heng; Hwang, Wen-Li

2015-01-01

The optimal sequence of irinotecan and oxaliplatin-based regimens for metastatic colorectal cancer remains unclear. We conducted a population-based observational study by retrospectively reviewing records from Taiwan’s National Health Insurance Research Database to explore this issue. Patients aged ≥20 years with metastatic colorectal cancer newly diagnosed between 2004 and 2008 (n = 9490) were enrolled in current study. Among these 9490 patients, 3895 patients (41.04%) did not receive any chemotherapy within the first three months after catastrophic illness registration. Patients who received best supportive care were older and had higher Charlson comorbidity indexes and incidences of comorbidities than those who received irinotecan-based regimens, oxaliplatin-based regimens, and 5-fluorouracil/capecitabine alone. Patients who received irinotecan followed by oxaliplatin-based regimens and those who received the reverse sequence were further stratified into arm A (n = 542) and arm B (n = 1156), respectively. The median first time to next treatment was not significantly different between arm A and arm B (210 days vs. 196 days; p = 0.17). However, the median second time to next treatment was longer in arm A than in arm B (155 days vs. 123 days; p = 0.006), which translated into a better overall survival (487 days vs. 454 days; p = 0.02). The crossover rate was higher in arm A than in arm B (47.84% vs. 41.61%; p<0.001). Multivariate Cox regression analyses showed that overall survival was comparable between the two chemotherapy sequences (p = 0.27). Our study suggested that irinotecan followed by oxaliplatin-based regimens might be a better chemotherapy treatment option for metastatic colorectal cancer than the reverse sequence given the higher crossover rate and potential overall survival benefit. PMID:26273837

Optimal Sequence of Irinotecan and Oxaliplatin-Based Regimens in Metastatic Colorectal Cancer: A Population-Based Observational Study.

PubMed

Teng, Chieh-Lin Jerry; Wang, Chen-Yu; Chen, Yi-Huei; Lin, Ching-Heng; Hwang, Wen-Li

2015-01-01

The optimal sequence of irinotecan and oxaliplatin-based regimens for metastatic colorectal cancer remains unclear. We conducted a population-based observational study by retrospectively reviewing records from Taiwan's National Health Insurance Research Database to explore this issue. Patients aged ≥ 20 years with metastatic colorectal cancer newly diagnosed between 2004 and 2008 (n = 9490) were enrolled in current study. Among these 9490 patients, 3895 patients (41.04%) did not receive any chemotherapy within the first three months after catastrophic illness registration. Patients who received best supportive care were older and had higher Charlson comorbidity indexes and incidences of comorbidities than those who received irinotecan-based regimens, oxaliplatin-based regimens, and 5-fluorouracil/capecitabine alone. Patients who received irinotecan followed by oxaliplatin-based regimens and those who received the reverse sequence were further stratified into arm A (n = 542) and arm B (n = 1156), respectively. The median first time to next treatment was not significantly different between arm A and arm B (210 days vs. 196 days; p = 0.17). However, the median second time to next treatment was longer in arm A than in arm B (155 days vs. 123 days; p = 0.006), which translated into a better overall survival (487 days vs. 454 days; p = 0.02). The crossover rate was higher in arm A than in arm B (47.84% vs. 41.61%; p<0.001). Multivariate Cox regression analyses showed that overall survival was comparable between the two chemotherapy sequences (p = 0.27). Our study suggested that irinotecan followed by oxaliplatin-based regimens might be a better chemotherapy treatment option for metastatic colorectal cancer than the reverse sequence given the higher crossover rate and potential overall survival benefit.

Picture book support for preparing children ahead of and during day surgery.

PubMed

Nilsson, Elisabeth; Svensson, Gunnar; Frisman, Gunilla Hollman

2016-10-07

Aim To develop and evaluate the use of a specific picture book aiming to prepare children for anaesthesia and surgery. Methods An intervention comparing two different information methods before ear, nose and throat day surgery was performed. The intervention involved using a specific information sheet and a specific picture book. Parents (n=104) of children aged 2-12 years completed open-ended questions that were analysed with qualitative content analysis. They were divided into two groups: one group received routine information and one received routine information and the intervention. Findings The picture sheet and picture book were valuable aids to prepare small children for anaesthesia and surgery by explaining the procedures that would take place. The parents expressed that knowledge of the procedures made them and the child feel secure. Conclusion Peri-operative information through pictures supports children and their parents during day surgery and may be helpful in future healthcare visits.

An implementation of the look-ahead Lanczos algorithm for non-Hermitian matrices, part 2

NASA Technical Reports Server (NTRS)

Freund, Roland W.; Nachtigal, Noel M.

1990-01-01

It is shown how the look-ahead Lanczos process (combined with a quasi-minimal residual QMR) approach) can be used to develop a robust black box solver for large sparse non-Hermitian linear systems. Details of an implementation of the resulting QMR algorithm are presented. It is demonstrated that the QMR method is closely related to the biconjugate gradient (BCG) algorithm; however, unlike BCG, the QMR algorithm has smooth convergence curves and good numerical properties. We report numerical experiments with our implementation of the look-ahead Lanczos algorithm, both for eigenvalue problem and linear systems. Also, program listings of FORTRAN implementations of the look-ahead algorithm and the QMR method are included.

An implementation of the look-ahead Lanczos algorithm for non-Hermitian matrices

NASA Technical Reports Server (NTRS)

Freund, Roland W.; Gutknecht, Martin H.; Nachtigal, Noel M.

1991-01-01

The nonsymmetric Lanczos method can be used to compute eigenvalues of large sparse non-Hermitian matrices or to solve large sparse non-Hermitian linear systems. However, the original Lanczos algorithm is susceptible to possible breakdowns and potential instabilities. An implementation is presented of a look-ahead version of the Lanczos algorithm that, except for the very special situation of an incurable breakdown, overcomes these problems by skipping over those steps in which a breakdown or near-breakdown would occur in the standard process. The proposed algorithm can handle look-ahead steps of any length and requires the same number of matrix-vector products and inner products as the standard Lanczos process without look-ahead.

Improving spatial resolution in skin-contact thermography: comparison between a spline based and linear interpolation.

PubMed

Giansanti, Daniele

2008-07-01

A wearable device for skin-contact thermography [Giansanti D, Maccioni G. Development and testing of a wearable integrated thermometer sensor for skin contact thermography. Med Eng Phys 2006 [ahead of print

TEMPO Early Adopters in Air-Quality Forecasting, Planning and Assessment, Pollution Emissions, Health, Agriculture, and Environmental Impacts: Applications and Decision Support

NASA Astrophysics Data System (ADS)

Newchurch, M.; Zavodsky, B.; Chance, K.; Haynes, J.; Lefer, B. L.; Naeger, A.

2016-12-01

The AQ research community has a long legacy of using space-based observations (e.g., Solar Backscatter Ultraviolet Instrument [SBUV], Global Ozone Monitoring Experiment [GOME], Ozone Monitoring Instrument [OMI], and the Ozone Mapping & Profiler Suite [OMPS]) to study atmospheric chemistry. These measurements have been used to observe day-to-day and year-to-year changes in atmospheric constituents. However, they have not been able to capture the diurnal variability of pollution with enough temporal or spatial fidelity and a low enough latency for regular use by operational decision makers. As a result, the operational AQ community has traditionally relied on ground-based (e.g., collection stations, LIDAR) and airborne observing systems to study tropospheric chemistry. In order to maximize its utility for applications and decision support, there is a need to educate the community about the game-changing potential for the geostationary TEMPO mission well ahead of its expected launch date early in the third decade of this millinium. This NASA mission will engage user communities and enable science across the NASA Applied Science Focus Areas of Health and Air Quality, Disasters, Water Resources, and Ecological Forecasting, In addition, topics discussed will provide opportunities for collaborations extending TEMPO applications to future program areas in Agriculture, Weather and Climate (including Numerical Weather Prediction), Energy, and Oceans.

Radiation induced precursor flow field ahead of a Jovian entry body

NASA Technical Reports Server (NTRS)

Tiwari, S.; Szema, K. Y.

1977-01-01

The change in flow properties ahead of the bow shock of a Jovian entry body, resulting from absorption of radiation from the shock layer, is investigated. Ultraviolet radiation is absorbed by the free stream gases, causing dissociation, ionization, and an increase in enthalpy of flow ahead of the shock wave. As a result of increased fluid enthalpy, the entire flow field in the precursor region is perturbed. The variation in flow properties is determined by employing the small perturbation technique of classical aerodynamics as well as the thin layer approximation for the preheating zone. By employing physically realistic models of radiative transfer, solutions are obtained for velocity, pressure, density, temperature, and enthalpy variations. The results indicate that the precursor flow effects, in general, are greater at higher altitudes. Just ahead of the shock, however, the effects are larger at lower altitudes. Pre-heating of the gas significantly increases the static pressure and temperature ahead of the shock for velocities exceeding 36 km/sec.

Underway Recovery Test 6 (URT-6) - Day 4 Activities

NASA Image and Video Library

2018-01-20

Navy diver Michael Tuft (far right) and his team wait to be called for their part in Underway Recovery Test 6 aboard the USS Anchorage. The divers will be the first people astronauts aboard the Orion spacecraft see when they splash down in the Pacific Ocean after Exploration Mission-2. The testing with the NASA Recovery Team and the U.S. Navy will provide important data that is being used to improve recovery procedures and hardware ahead of Orion's next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

Expedition 37 Soyuz Landing Preparation

NASA Image and Video Library

2013-11-10

View from the cockpit of one of twelve Russian search and rescue helicopters as they fly from the city of Karaganda to Zhezkazgan in Kazakhstan, Sunday, Nov. 10, 2013, a day ahead of the scheduled landing of the Soyuz TMA-09M spacecraft with the Expedition 37 crew. Exp. 37 Commander Fyodor Yurchikhin of the Russian Federal Space Agency (Roscosmos), Flight Engineer Karen Nyberg of NASA and Flight Engineer Luca Parmitano of the European Space Agency are returning to Earth after five and a half months on the International Space Station. Photo Credit: (NASA/Carla Cioffi)

Underway Recovery Test 6 (URT-6) - Day 3 Activities

NASA Image and Video Library

2018-01-19

NASA Recovery Director Melissa Jones watches part of Underway Recovery Test 6, from the flight deck of the USS Anchorage. During this portion, the Orion test article is intentionally subjected to an increased sea state as the NASA Recovery Team works hard to keep control of the spacecraft. The testing with Kennedy Space Center's NASA Recovery Team and the U.S. Navy will provide important data that is being used to improve recovery procedures and hardware ahead of Orion's next flight, Exploration Mission-1, when it splashes down in the Pacific Ocean.

Interest rate next-day variation prediction based on hybrid feedforward neural network, particle swarm optimization, and multiresolution techniques

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

2016-02-01

Multiresolution analysis techniques including continuous wavelet transform, empirical mode decomposition, and variational mode decomposition are tested in the context of interest rate next-day variation prediction. In particular, multiresolution analysis techniques are used to decompose interest rate actual variation and feedforward neural network for training and prediction. Particle swarm optimization technique is adopted to optimize its initial weights. For comparison purpose, autoregressive moving average model, random walk process and the naive model are used as main reference models. In order to show the feasibility of the presented hybrid models that combine multiresolution analysis techniques and feedforward neural network optimized by particle swarm optimization, we used a set of six illustrative interest rates; including Moody's seasoned Aaa corporate bond yield, Moody's seasoned Baa corporate bond yield, 3-Month, 6-Month and 1-Year treasury bills, and effective federal fund rate. The forecasting results show that all multiresolution-based prediction systems outperform the conventional reference models on the criteria of mean absolute error, mean absolute deviation, and root mean-squared error. Therefore, it is advantageous to adopt hybrid multiresolution techniques and soft computing models to forecast interest rate daily variations as they provide good forecasting performance.

Mirage events & driver haptic steering alerts in a motion-base driving simulator: A method for selecting an optimal HMI.

PubMed

Talamonti, Walter; Tijerina, Louis; Blommer, Mike; Swaminathan, Radhakrishnan; Curry, Reates; Ellis, R Darin

2017-11-01

This paper describes a new method, a 'mirage scenario,' to support formative evaluation of driver alerting or warning displays for manual and automated driving. This method provides driving contexts (e.g., various Times-To-Collision (TTCs) to a lead vehicle) briefly presented and then removed. In the present study, during each mirage event, a haptic steering display was evaluated. This haptic display indicated a steering response may be initiated to drive around an obstacle ahead. A motion-base simulator was used in a 32-participant study to present vehicle motion cues similar to the actual application. Surprise was neither present nor of concern, as it would be for a summative evaluation of a forward collision warning system. Furthermore, no collision avoidance maneuvers were performed, thereby reducing the risk of simulator sickness. This paper illustrates the mirage scenario procedures, the rating methods and definitions used with the mirage scenario, and analysis of the ratings obtained, together with a multi-attribute utility theory (MAUT) approach to evaluate and select among alternative designs for future summative evaluation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effect of driving experience on anticipatory look-ahead fixations in real curve driving.

PubMed

Lehtonen, Esko; Lappi, Otto; Koirikivi, Iivo; Summala, Heikki

2014-09-01

Anticipatory skills are a potential factor for novice drivers' curve accidents. Behavioural data show that steering and speed regulation are affected by forward planning of the trajectory. When approaching a curve, the relevant visual information for online steering control and for planning is located at different eccentricities, creating a need to disengage the gaze from the guidance of steering to anticipatory look-ahead fixations over curves. With experience, peripheral vision can be increasingly used in the visual guidance of steering. This could leave experienced drivers more gaze time to invest on look-ahead fixations over curves, facilitating the trajectory planning. Eighteen drivers (nine novices, nine experienced) drove an instrumented vehicle on a rural road four times in both directions. Their eye movements were analyzed in six curves. The trajectory of the car was modelled and divided to approach, entry and exit phases. Experienced drivers spent less time on the road-ahead and more time on the look-ahead fixations over the curves. Look-ahead fixations were also more common in the approach than in the entry phase of the curve. The results suggest that with experience drivers allocate greater part of their visual attention to trajectory planning. Copyright © 2014 Elsevier Ltd. All rights reserved.

Input/output behavior of supercomputing applications

NASA Technical Reports Server (NTRS)

Miller, Ethan L.

1991-01-01

The collection and analysis of supercomputer I/O traces and their use in a collection of buffering and caching simulations are described. This serves two purposes. First, it gives a model of how individual applications running on supercomputers request file system I/O, allowing system designer to optimize I/O hardware and file system algorithms to that model. Second, the buffering simulations show what resources are needed to maximize the CPU utilization of a supercomputer given a very bursty I/O request rate. By using read-ahead and write-behind in a large solid stated disk, one or two applications were sufficient to fully utilize a Cray Y-MP CPU.

Dissemination of the Look AHEAD Lifestyle Intervention in the United States Air Force: Study Rationale, Design and Methods

PubMed Central

Krukowski, Rebecca A.; Hare, Marion E.; Talcott, Gerald W.; Johnson, Karen C.; Richey, Phyllis A.; Kocak, Mehmet; Balderas, Jennifer; Colvin, Lauren; Keller, Patrick L.; Waters, Teresa M.; Klesges, Robert C.

2014-01-01

Despite an increase in overweight and obesity similar to the civilian population, there have been few randomized controlled trials examining behavioral weight management interventions in the military settings. This paper describes the design, intervention development and analysis plan of the Fit Blue study, a randomized controlled behavioral weight loss trial taking place in the United States Air Force. This study compares two adapted versions of the efficacious Look AHEAD Intensive Lifestyle Intervention (ILI), a counselor-initiated condition and a self-paced condition. Also described are the unique steps required when conducting military-based health promotion research and adaptations made to the Look AHEAD intervention to accommodate the military environment. To our knowledge, this is the first translation of the Look AHEAD ILI in the military setting and one of the first translations of the ILI in general. If successful, this intervention could be disseminated to the entire U.S. Military as this project is designed to overcome the barriers and utilize the facilitators for weight loss that are unique to a military population. Programs validated in military populations can have a major public health impact given that with 1.4 million active duty personnel, the Department of Defense is the nation’s largest employer. However, while this intervention is designed for a military population and there are unique aspects of the military that may enhance weight loss interventions, the diversity of the study population should help inform obesity efforts in both civilian and military settings. PMID:25545025

Dissemination of the Look AHEAD intensive lifestyle intervention in the United States Air Force: study rationale, design and methods.

PubMed

Krukowski, Rebecca A; Hare, Marion E; Talcott, Gerald W; Johnson, Karen C; Richey, Phyllis A; Kocak, Mehmet; Balderas, Jennifer; Colvin, Lauren; Keller, Patrick L; Waters, Teresa M; Klesges, Robert C

2015-01-01

Despite an increase in overweight and obesity similar to the civilian population, there have been few randomized controlled trials examining behavioral weight management interventions in the military settings. This paper describes the design, intervention development and analysis plan of the Fit Blue study, a randomized controlled behavioral weight loss trial taking place in the United States Air Force. This study compares two adapted versions of the efficacious Look AHEAD Intensive Lifestyle Intervention (ILI), a counselor-initiated condition and a self-paced condition. Also described are the unique steps required when conducting military-based health promotion research and adaptations made to the Look AHEAD intervention to accommodate the military environment. To our knowledge, this is the first translation of the Look AHEAD ILI in the military setting and one of the first translations of the ILI in general. If successful, this intervention could be disseminated to the entire U.S. Military as this project is designed to overcome the barriers and utilize the facilitators for weight loss that are unique to a military population. Programs validated in military populations can have a major public health impact given that with 1.4 million active duty personnel, the Department of Defense is the nation's largest employer. However, while this intervention is designed for a military population and there are unique aspects of the military that may enhance weight loss interventions, the diversity of the study population should help inform obesity efforts in both civilian and military settings. Copyright © 2014 Elsevier Inc. All rights reserved.

In-situ deformation studies of an aluminum metal-matrix composite in a scanning electron microscope

NASA Technical Reports Server (NTRS)

Manoharan, M.; Lewandowski, J. J.

1989-01-01

Tensile specimens made of a metal-matrix composite (cast and extruded aluminum alloy-based matrix reinforced with Al2O3 particulate) were tested in situ in a scanning electron microscope equipped with a deformation stage, to directly monitor the crack propagation phenomenon. The in situ SEM observations revealed the presence of microcracks both ahead of and near the crack-tip region. The microcracks were primarily associated with cracks in the alumina particles. The results suggest that a region of intense deformation exists ahead of the crack and corresponds to the region of microcracking. As the crack progresses, a region of plastically deformed material and associated microcracks remains in the wake of the crack.

Data Structures for Extreme Scale Computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kahan, Simon

As computing problems of national importance grow, the government meets the increased demand by funding the development of ever larger systems. The overarching goal of the work supported in part by this grant is to increase efficiency of programming and performing computations on these large computing systems. In past work, we have demonstrated that some of these computations once thought to require expensive hardware designs and/or complex, special-purpose programming may be executed efficiently on low-cost commodity cluster computing systems using a general-purpose “latency-tolerant” programming framework. One important developed application of the ideas underlying this framework is graph database technology supportingmore » social network pattern matching used by US intelligence agencies to more quickly identify potential terrorist threats. This database application has been spun out by the Pacific Northwest National Laboratory, a Department of Energy Laboratory, into a commercial start-up, Trovares Inc. We explore an alternative application of the same underlying ideas to a well-studied challenge arising in engineering: solving unstructured sparse linear equations. Solving these equations is key to predicting the behavior of large electronic circuits before they are fabricated. Predicting that behavior ahead of fabrication means that designs can optimized and errors corrected ahead of the expense of manufacture.« less

Key Action Items for the Stem Cell Field: Looking Ahead to 2014

PubMed Central

Knoepfler, Paul S.

2013-01-01

Abstract The stem cell field is at a critical juncture in late 2013. We find ourselves buoyed by building momentum for both transformative basic science discoveries and clinical translation of stem cells. Cellular reprogramming has given the field exciting new avenues as well. The overall prospect of novel stem cell–based therapies becoming a reality for patients in the coming years has never seemed higher. At the same time, we face serious challenges. Some of these challenges, such as stem cell tourism, are familiar to us, although even those are evolving in ways that require adaptability and action by the stem cell field. Other new challenges are also emerging, including an urgent need for formal physician training in stem cells, regulatory compliance balanced with innovation and U.S. Food and Drug Administration reform, and savvy educational outreach. Looking ahead to 2014, both the challenges and opportunities for the stem cell field require a proactive, thoughtful approach to maximize the potential for a positive impact from stem cell advances. In this study, I discuss the key action items for the field as we look ahead to the coming year and beyond. PMID:24147571

Key action items for the stem cell field: looking ahead to 2014.

PubMed

Knoepfler, Paul S

2013-12-01

The stem cell field is at a critical juncture in late 2013. We find ourselves buoyed by building momentum for both transformative basic science discoveries and clinical translation of stem cells. Cellular reprogramming has given the field exciting new avenues as well. The overall prospect of novel stem cell-based therapies becoming a reality for patients in the coming years has never seemed higher. At the same time, we face serious challenges. Some of these challenges, such as stem cell tourism, are familiar to us, although even those are evolving in ways that require adaptability and action by the stem cell field. Other new challenges are also emerging, including an urgent need for formal physician training in stem cells, regulatory compliance balanced with innovation and U.S. Food and Drug Administration reform, and savvy educational outreach. Looking ahead to 2014, both the challenges and opportunities for the stem cell field require a proactive, thoughtful approach to maximize the potential for a positive impact from stem cell advances. In this study, I discuss the key action items for the field as we look ahead to the coming year and beyond.

Optimization of Hyaluronidase Inhibition Activity from Prunus davidiana (Carriere) Franch Fruit Extract Fermented by its Isolated Bacillus subtilis Strain SPF4211.

PubMed

Kim, Won-Baek; Park, So Hae; Koo, Kyoung Yoon; Kim, Bo Ram; Kim, Minji; Lee, Heeseob

2016-09-28

Strain SPF4211, having hyaluronidase (HAase) inhibition activity, was isolated from P. davidiana (Carriere) Franch fruit (PrDF) sugar extract. The phenotypic and biochemical properties based on 16S rDNA sequencing and an API 50 CHB kit suggested that the organism was B. subtilis. To optimize the HAase inhibition activity of PrDF extract by fermentation of strain SPF4211, a central composite design (CCD) was introduced based on three variables: concentration of PrDF extract (X₁: 1-5%), amount of starter culture (X₂: 1-5%), and fermentation time (X₃: 0-7 days). The experimental data were fitted with quadratic regression equations, and the accuracy of the equations was analyzed by ANOVA. The statistical model predicted the highest HAase inhibition activity of 37.936% under the optimal conditions of X₁ = 1%, X₂ = 2.53%, and X₃ = 7 days. The optimized conditions were validated by observation of an actual HAase inhibition activity of 38.367% from extract of PrDF fermented by SPF4211. These results agree well with the predicted model value.

The labor force of the future.

PubMed

Norwood, J L

1987-07-01

In the decades ahead, the US labor force will reflect changes in the industrial structure, with declines in some manufacturing industries and expansion in service industries. The services sector is so diverse that the jobs within it cannot be categorized as either high wage or low wage. The service-producing sector employs 85% of professional specialty workers in the US. In general, information on compensation trends indicates that greater increases in compensation have occurred for workers in service-producing as opposed to goods-producing industries. The increase in service sector jobs has created opportunities for women to enter the labor force and, at present, 5 out of 6 women work in this sector compared to fewer than 2 out of 3 men. Productivity growth rates in the service-producing industries vary substantially and are strongly affected by the business cycle. Central to employment opportunities in the years ahead will be the effect of new technology. To date, the aggregate effect of new technology has been increased employment and higher living standards. Although retraining programs should be in place, the scenario of a huge technology-created labor surplus seems unlikely. In fact, a more likely problem is a shortage of labor resulting from earlier labor force withdrawal and demographic aging of the population. Those in the 25-54-year age group will represent a larger share of the labor force in the years ahead. In addition, blacks are expected to account for 20% of the labor force growth in the next decade. Finally, given increasing labor force participation rates among mothers, employers may have to provide more flexible work schedules, assistance with day care, and more attractive benefits packages.

Current STEREO Status on the Far Side of the Sun

NASA Astrophysics Data System (ADS)

Thompson, William T.; Gurman, Joseph; Ossing, Daniel; Luhmann, Janet; Curtis, David; Schroeder, Peter; Mewaldt, Richard; Davis, Andrew; Wortman, Kristin; Russell, Christopher; Galvin, Antoinette; Kistler, Lynn; Ellis, Lorna; Howard, Russell; Vourlidas, Angelos; Rich, Nathan; Hutting, Lynn; Maksimovic, Milan; Bale, Stuart D.; Goetz, Keith

2015-04-01

The current positions of the two STEREO spacecraft on the opposite side of the Sun from Earth (superior solar conjunction) has forced some significant changes in the spacecraft and instrument operations. No communications are possible when the spacecraft is within 2 degrees of the Sun, requiring that the spacecraft be put into safe mode until communications can be restored. Unfortunately, communications were lost with the STEREO Behind spacecraft on October 1, 2014, during testing for superior solar conjunction operations. We will discuss what is known about the causes of loss of contact, the steps being taken to try to recover the Behind spacecraft, and what has been done to prevent a similar occurrence on STEREO Ahead.We will also discuss the effect of being on the far side of the Sun on the science operations of STEREO Ahead. Starting on August 20, 2014, the telemetry rate from the STEREO Ahead spacecraft has been tremendously reduced due to the need to keep the temperature of the feed horn on the high gain antenna below acceptable limits. However, the amount of telemetry that can be brought down has been highly reduced. Even so, significant science is still possible from STEREO's unique position on the solar far side. We will discuss the science and space weather products that are, or will be, available from each STEREO instrument, when those products will be available, and how they will be used. Some data, including the regular space weather beacon products, are brought down for an average of a few hours each day during the daily real-time passes, while the in situ and radio beacon data are being stored on the onboard recorder to provide a continuous 24-hour coverage for eventual downlink once the spacecraft is back to normal operations.

Do-Ahead Event: The Pringle Caper

NASA Astrophysics Data System (ADS)

Bouffard, Karen

1998-12-01

In this second Physics Olympics column, we present a staple of many Olympics competitions—a "Do-Ahead" experiment that is prepared in the classroom and brought to the Olympics. "The Pringle Caper" was designed by Steve Cremer, physics teacher from the Braintree (Massachusetts) high school. We include one such activity at each Eastern Massachusetts Physics Olympics meet. Among other pluses, the "Do-Ahead" allows students who are unable to travel to the Olympics to participate.

An implementation of the look-ahead Lanczos algorithm for non-Hermitian matrices, part 1

NASA Technical Reports Server (NTRS)

Freund, Roland W.; Gutknecht, Martin H.; Nachtigal, Noel M.

1990-01-01

The nonsymmetric Lanczos method can be used to compute eigenvalues of large sparse non-Hermitian matrices or to solve large sparse non-Hermitian linear systems. However, the original Lanczos algorithm is susceptible to possible breakdowns and potential instabilities. We present an implementation of a look-ahead version of the Lanczos algorithm which overcomes these problems by skipping over those steps in which a breakdown or near-breakdown would occur in the standard process. The proposed algorithm can handle look-ahead steps of any length and is not restricted to steps of length 2, as earlier implementations are. Also, our implementation has the feature that it requires roughly the same number of inner products as the standard Lanczos process without look-ahead.

Presentation and assessment of rideability of a novel single-track vehicle: the Anaconda

NASA Astrophysics Data System (ADS)

Verlinden, O.; Kabeya, P.

2012-08-01

In this paper, a new single-track vehicle, the Anaconda, is presented and modelled according to a multibody theory. This articulated vehicle begins with a traditional bicycle, called the head module, followed by a succession of so-called pedal modules (PMs) equipped with one rear-steered wheel. Each module is connected to the preceding one by a spherical joint. To assess its dynamic behaviour, the model of an Anaconda with two PMs is simulated under the EasyDyn framework, a multibody library based on the minimal coordinates approach. The simulation of such a vehicle cannot be performed without the riders' action, consisting of the torques applied on the handlebars. The latter is implemented through controllers designed by optimal control, from the out-of-plane dynamics of the vehicle going straight ahead at 20 km/h. First, two optimal controllers are determined separately for the Head Module alone on one hand and for the Pedal Module alone on the other hand. They are then implemented on the Anaconda and it appears that the vehicle is close to instability and that the handling of the pedal modules is delicate but humanly possible. Finally, the difficulty in riding the Anaconda is evaluated through the so-called rideability index, which increases, as expected, with the amount of PMs, and shows that good psycho-motor skills will be needed to drive the Anaconda.

Intelligent electric vehicle charging: Rethinking the valley-fill

NASA Astrophysics Data System (ADS)

Valentine, Keenan; Temple, William G.; Zhang, K. Max

This study proposes an intelligent PEV charging scheme that significantly reduces power system cost while maintaining reliability compared to the widely discussed valley-fill method of aggregated charging in the early morning. This study considers optimal PEV integration into the New York Independent System Operator's (NYISO) day-ahead and real-time wholesale energy markets for 21 days in June, July, and August of 2006, a record-setting summer for peak load. NYISO market and load data is used to develop a statistical Locational Marginal Price (LMP) and wholesale energy cost model. This model considers the high cost of ramping generators at peak-load and the traditional cost of steady-state operation, resulting in a framework with two competing cost objectives. Results show that intelligent charging assigns roughly 80% of PEV load to valley hours to take advantage of low steady-state cost, while placing the remaining 20% equally at shoulder and peak hours to reduce ramping cost. Compared to unregulated PEV charging, intelligent charging reduces system cost by 5-16%; a 4-9% improvement over the flat valley-fill approach. Moreover, a Charge Flexibility Constraint (CFC), independent of market modeling, is constructed from a vehicle-at-home profile and the mixture of Level 1 and Level 2 charging infrastructure. The CFC is found to severely restrict the ability to charge vehicles during the morning load valley. This study further shows that adding more Level 2 chargers without regulating PEV charging will significantly increase wholesale energy cost. Utilizing the proposed intelligent PEV charging method, there is a noticeable reduction in system cost if the penetration of Level 2 chargers is increased from 70/30 to 50/50 (Level 1/Level 2). However, the system benefit is drastically diminished for higher penetrations of Level 2 chargers.

Competency-Based Education: Helping All Kentucky Students Succeed. Final Report

ERIC Educational Resources Information Center

Kentucky Department of Education, 2013

2013-01-01

The Commonwealth of Kentucky is exploring competency-based education as a way to better prepare students for success in college and their careers. Some individual schools and districts are moving ahead with this innovative approach where achievement is the constant and time is the variable. Not all students learn at the same rate, or in the same…

Ultrathin endoscopes based on multicore fibers and adaptive optics: a status review and perspectives.

PubMed

Andresen, Esben Ravn; Sivankutty, Siddharth; Tsvirkun, Viktor; Bouwmans, Géraud; Rigneault, Hervé

2016-12-01

We take stock of the progress that has been made into developing ultrathin endoscopes assisted by wave front shaping. We focus our review on multicore fiber-based lensless endoscopes intended for multiphoton imaging applications. We put the work into perspective by comparing with alternative approaches and by outlining the challenges that lie ahead.

The role of differential delays in integrating transient visual and proprioceptive information

PubMed Central

Cameron, Brendan D.; de la Malla, Cristina; López-Moliner, Joan

2014-01-01

Many actions involve limb movements toward a target. Visual and proprioceptive estimates are available online, and by optimally combining (Ernst and Banks, 2002) both modalities during the movement, the system can increase the precision of the hand estimate. The notion that both sensory modalities are integrated is also motivated by the intuition that we do not consciously perceive any discrepancy between the felt and seen hand's positions. This coherence as a result of integration does not necessarily imply realignment between the two modalities (Smeets et al., 2006). For example, the two estimates (visual and proprioceptive) might be different without either of them (e.g., proprioception) ever being adjusted after recovering the other (e.g., vision). The implication that the felt and seen positions might be different has a temporal analog. Because the actual feedback from the hand at a given instantaneous position reaches brain areas at different times for proprioception and vision (shorter for proprioception), the corresponding instantaneous unisensory position estimates will be different, with the proprioceptive one being ahead of the visual one. Based on the assumption that the system integrates optimally and online the available evidence from both senses, we introduce a temporal mechanism that explains the reported overestimation of hand positions when vision is occluded for active and passive movements (Gritsenko et al., 2007) without the need to resort to initial feedforward estimates (Wolpert et al., 1995). We set up hypotheses to test the validity of the model, and we contrast simulation-based predictions with empirical data. PMID:24550870

7-year of surface ozone in a coastal city of central Italy: Observations and models

NASA Astrophysics Data System (ADS)

Biancofiore, Fabio; Verdecchia, Marco; Di Carlo, Piero; Tomassetti, Barbara; Aruffo, Eleonora; Busilacchio, Marcella; Bianco, Sebastiano; Di Tommaso, Sinibaldo; Colangeli, Carlo

2014-05-01

Hourly concentrations of ozone (O3) and nitrogen dioxide (NO2) have been measured for seven years, from 1998 to 2005, in a seaside town in the central Italy. Seasonal trends of O3 and NO2 recorded in the considered years are studied. Furthermore, we have focused our attention on data collected during the 2005, analyzing them using two different methods: a regression model and a neural network model. Both models are used to simulate the hourly ozone concentration, using several sets of input. In order to evaluate the performance of the model four statistical criteria are used: correlation coefficient (R), fractional bias (FB), normalized mean squared error (NMSE) e factor of two (FA2). All the criteria show that the neural network has better results compared to the regression model in all the simulations. In addiction we have tested some improvements of the neural network model, results of these tests are discussed. Finally, we have used the neural network to forecast the ozone hourly concentrations a day ahead and 1, 3, 6, 12 hour ahead. Performances of the model in predicting ozone levels are discussed.

Integrating Solar PV in Utility System Operations: Analytical Framework and Arizona Case Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Jing; Botterud, Audun; Mills, Andrew

2015-06-01

A systematic framework is proposed to estimate the impact on operating costs due to uncertainty and variability in renewable resources. The framework quantifies the integration costs associated with subhourly variability and uncertainty as well as day-ahead forecasting errors in solar PV (photovoltaics) power. A case study illustrates how changes in system operations may affect these costs for a utility in the southwestern United States (Arizona Public Service Company). We conduct an extensive sensitivity analysis under different assumptions about balancing reserves, system flexibility, fuel prices, and forecasting errors. We find that high solar PV penetrations may lead to operational challenges, particularlymore » during low-load and high solar periods. Increased system flexibility is essential for minimizing integration costs and maintaining reliability. In a set of sensitivity cases where such flexibility is provided, in part, by flexible operations of nuclear power plants, the estimated integration costs vary between $1.0 and $4.4/MWh-PV for a PV penetration level of 17%. The integration costs are primarily due to higher needs for hour-ahead balancing reserves to address the increased sub-hourly variability and uncertainty in the PV resource. (C) 2015 Elsevier Ltd. All rights reserved.« less

Straight Ahead in Microgravity

NASA Technical Reports Server (NTRS)

Wood, S. J.; Vanya, R. D.; Clement, G.

2014-01-01

This joint ESA-NASA study will address adaptive changes in spatial orientation related to the subjective straight ahead, and the use of a vibrotactile sensory aid to reduce perceptual errors. The study will be conducted before and after long-duration expeditions to the International Space Station (ISS) to examine how spatial processing of target location is altered following exposure to microgravity. This project specifically addresses the sensorimotor research gap "What are the changes in sensorimotor function over the course of a mission?" Six ISS crewmembers will be requested to participate in three preflight sessions (between 120 and 60 days prior to launch) and then three postflight sessions on R+0/1 day, R+4 +/-2 days, and R+8 +/-2 days. The three specific aims include: (a) fixation of actual and imagined target locations at different distances; (b) directed eye and arm movements along different spatial reference frames; and (c) the vestibulo-ocular reflex during translation motion with fixation targets at different distances. These measures will be compared between upright and tilted conditions. Measures will then be compared with and without a vibrotactile sensory aid that indicates how far one has tilted relative to the straight-ahead direction. The flight study was been approved by the medical review boards and will be implemented in the upcoming Informed Crew Briefings to solicit flight subject participation. Preliminary data has been recorded on 6 subjects during parabolic flight to examine the spatial coding of eye movements during roll tilt relative to perceived orientations while free-floating during the microgravity phase of parabolic flight or during head tilt in normal gravity. Binocular videographic recordings obtained in darkness allowed us to quantify the mean deviations in gaze trajectories along both horizontal and vertical coordinates relative to the aircraft and head orientations. During some parabolas, a vibrotactile sensory aid provided feedback of body orientation relative to the plane coordinates. RESULTS Both variability and curvature of gaze trajectories increased during roll tilt compared to the upright position. The saccades were less accurate during parabolic flight compared to measurements obtained in normal gravity. Although subjects were instructed to look off in the distance while performing the eye movements, fixation distance varied with vertical gaze direction independent of whether the saccades were made along perceived aircraft or head orientations. The increased errors in gaze trajectories along both perceived orientations during microgravity can be attributed to the otolith's role in spatial coding of eye movements. A change in an individual's egocentric reference might have negative consequences on evaluating the direction of an approaching object or on the accuracy of reaching movements or locomotion. Consequently, investigating how microgravity affects the target location will have theoretical, operational and even clinical implications for future space exploration missions. The use of vibrotactile feedback as a sensorimotor countermeasure is applicable to balance therapy applications for vestibular loss patients and the elderly to mitigate risks due to loss of orientation.

Dynamic linear models to explore time-varying suspended sediment-discharge rating curves

NASA Astrophysics Data System (ADS)

Ahn, Kuk-Hyun; Yellen, Brian; Steinschneider, Scott

2017-06-01

This study presents a new method to examine long-term dynamics in sediment yield using time-varying sediment-discharge rating curves. Dynamic linear models (DLMs) are introduced as a time series filter that can assess how the relationship between streamflow and sediment concentration or load changes over time in response to a wide variety of natural and anthropogenic watershed disturbances or long-term changes. The filter operates by updating parameter values using a recursive Bayesian design that responds to 1 day-ahead forecast errors while also accounting for observational noise. The estimated time series of rating curve parameters can then be used to diagnose multiscale (daily-decadal) variability in sediment yield after accounting for fluctuations in streamflow. The technique is applied in a case study examining changes in turbidity load, a proxy for sediment load, in the Esopus Creek watershed, part of the New York City drinking water supply system. The results show that turbidity load exhibits a complex array of variability across time scales. The DLM highlights flood event-driven positive hysteresis, where turbidity load remained elevated for months after large flood events, as a major component of dynamic behavior in the rating curve relationship. The DLM also produces more accurate 1 day-ahead loading forecasts compared to other static and time-varying rating curve methods. The results suggest that DLMs provide a useful tool for diagnosing changes in sediment-discharge relationships over time and may help identify variability in sediment concentrations and loads that can be used to inform dynamic water quality management.

Monthly streamflow forecasting at varying spatial scales in the Rhine basin

NASA Astrophysics Data System (ADS)

Schick, Simon; Rössler, Ole; Weingartner, Rolf

2018-02-01

Model output statistics (MOS) methods can be used to empirically relate an environmental variable of interest to predictions from earth system models (ESMs). This variable often belongs to a spatial scale not resolved by the ESM. Here, using the linear model fitted by least squares, we regress monthly mean streamflow of the Rhine River at Lobith and Basel against seasonal predictions of precipitation, surface air temperature, and runoff from the European Centre for Medium-Range Weather Forecasts. To address potential effects of a scale mismatch between the ESM's horizontal grid resolution and the hydrological application, the MOS method is further tested with an experiment conducted at the subcatchment scale. This experiment applies the MOS method to 133 additional gauging stations located within the Rhine basin and combines the forecasts from the subcatchments to predict streamflow at Lobith and Basel. In doing so, the MOS method is tested for catchments areas covering 4 orders of magnitude. Using data from the period 1981-2011, the results show that skill, with respect to climatology, is restricted on average to the first month ahead. This result holds for both the predictor combination that mimics the initial conditions and the predictor combinations that additionally include the dynamical seasonal predictions. The latter, however, reduce the mean absolute error of the former in the range of 5 to 12 %, which is consistently reproduced at the subcatchment scale. An additional experiment conducted for 5-day mean streamflow indicates that the dynamical predictions help to reduce uncertainties up to about 20 days ahead, but it also reveals some shortcomings of the present MOS method.

Improving delivery routes using combined heuristic and optimization in a consumer goods distribution company

NASA Astrophysics Data System (ADS)

Wibisono, E.; Santoso, A.; Sunaryo, M. A.

2017-11-01

XYZ is a distributor of various consumer goods products. The company plans its delivery routes daily and in order to obtain route construction in a short amount of time, it simplifies the process by assigning drivers based on geographic regions. This approach results in inefficient use of vehicles leading to imbalance workloads. In this paper, we propose a combined method involving heuristic and optimization to obtain better solutions in acceptable computation time. The heuristic is based on a time-oriented, nearest neighbor (TONN) to form clusters if the number of locations is higher than a certain value. The optimization part uses a mathematical modeling formulation based on vehicle routing problem that considers heterogeneous vehicles, time windows, and fixed costs (HVRPTWF) and is used to solve routing problem in clusters. A case study using data from one month of the company’s operations is analyzed, and data from one day of operations are detailed in this paper. The analysis shows that the proposed method results in 24% cost savings on that month, but it can be as high as 54% in a day.

People-People. $$$ Ahead--Training Pays Off

ERIC Educational Resources Information Center

Williams, Alec

1978-01-01

Based on experiences in establishing a personnel department and writing an affirmative action plan at Furman University, suggestions are offered for supervisory and employee training to reduce turnover rates. Selection, training, and motivation procedures are identified, and specific questions to ask applicants are listed. (LBH)

Design and Laboratory Implementation of Autonomous Optimal Motion Planning for Non-Holonomic Planetary Rovers

DTIC Science & Technology

2012-12-01

autonomy helped to maximize a Mars day journey, because humans could only plan the first portion of the journey based on images sent from the rover...safe trajectory based on its sensors [1]. The distance between Mars and Earth ranges from 100-200 million miles [1] and at this distance, the time...This feature worked for the pre- planned maneuvers, which were planned by humans the day before based on available sensory and visual inputs. Once the

Straight ahead running of a nonlinear car and driver model - new nonlinear behaviours highlighted

NASA Astrophysics Data System (ADS)

Della Rossa, Fabio; Mastinu, Giampiero

2018-05-01

The paper deals with the bifurcation analysis of a validated simple model describing a vehicle+driver running straight ahead. The mechanical model of the car has two degrees of freedom and the related equations of motion contain the nonlinear tyre characteristics. The driver is described by a very simple model. Bifurcation analysis is adopted for characterising straight ahead motion at different speeds for different drivers. A nonlinear sensitivity analysis is performed as a function of the driver's parameters and forward vehicle speed. A wealth of unreferenced bifurcations is discovered both for the understeering (UN) and for the oversteering (OV) vehicle. For the UN vehicle, a supercritical Hopf bifurcation may occur as the forward speed is increased. Also tangent (fold) bifurcations (saddle-node bifurcation of limit cycles) occur as the speed (or disturbance) is further increased. For the OV vehicle, a subcritical Hopf bifurcation occurs as the speed reaches a critical value. The preview distance (a driver's control parameter) plays a fundamental role in straight ahead driving. Either too short or too long preview distances are negative for straight ahead running.

Breast Radiotherapy with Mixed Energy Photons; a Model for Optimal Beam Weighting.

PubMed

Birgani, Mohammadjavad Tahmasebi; Fatahiasl, Jafar; Hosseini, Seyed Mohammad; Bagheri, Ali; Behrooz, Mohammad Ali; Zabiehzadeh, Mansour; Meskani, Reza; Gomari, Maryam Talaei

2015-01-01

Utilization of high energy photons (>10 MV) with an optimal weight using a mixed energy technique is a practical way to generate a homogenous dose distribution while maintaining adequate target coverage in intact breast radiotherapy. This study represents a model for estimation of this optimal weight for day to day clinical usage. For this purpose, treatment planning computed tomography scans of thirty-three consecutive early stage breast cancer patients following breast conservation surgery were analyzed. After delineation of the breast clinical target volume (CTV) and placing opposed wedge paired isocenteric tangential portals, dosimeteric calculations were conducted and dose volume histograms (DVHs) were generated, first with pure 6 MV photons and then these calculations were repeated ten times with incorporating 18 MV photons (ten percent increase in weight per step) in each individual patient. For each calculation two indexes including maximum dose in the breast CTV (Dmax) and the volume of CTV which covered with 95% Isodose line (VCTV, 95%IDL) were measured according to the DVH data and then normalized values were plotted in a graph. The optimal weight of 18 MV photons was defined as the intersection point of Dmax and VCTV, 95%IDL graphs. For creating a model to predict this optimal weight multiple linear regression analysis was used based on some of the breast and tangential field parameters. The best fitting model for prediction of 18 MV photons optimal weight in breast radiotherapy using mixed energy technique, incorporated chest wall separation plus central lung distance (Adjusted R2=0.776). In conclusion, this study represents a model for the estimation of optimal beam weighting in breast radiotherapy using mixed photon energy technique for routine day to day clinical usage.

Ensemble forecasting for renewable energy applications - status and current challenges for their generation and verification

NASA Astrophysics Data System (ADS)

Pinson, Pierre

2016-04-01

The operational management of renewable energy generation in power systems and electricity markets requires forecasts in various forms, e.g., deterministic or probabilistic, continuous or categorical, depending upon the decision process at hand. Besides, such forecasts may also be necessary at various spatial and temporal scales, from high temporal resolutions (in the order of minutes) and very localized for an offshore wind farm, to coarser temporal resolutions (hours) and covering a whole country for day-ahead power scheduling problems. As of today, weather predictions are a common input to forecasting methodologies for renewable energy generation. Since for most decision processes, optimal decisions can only be made if accounting for forecast uncertainties, ensemble predictions and density forecasts are increasingly seen as the product of choice. After discussing some of the basic approaches to obtaining ensemble forecasts of renewable power generation, it will be argued that space-time trajectories of renewable power production may or may not be necessitate post-processing ensemble forecasts for relevant weather variables. Example approaches and test case applications will be covered, e.g., looking at the Horns Rev offshore wind farm in Denmark, or gridded forecasts for the whole continental Europe. Eventually, we will illustrate some of the limitations of current frameworks to forecast verification, which actually make it difficult to fully assess the quality of post-processing approaches to obtain renewable energy predictions.

High Penetration of Electrical Vehicles in Microgrids: Threats and Opportunities

NASA Astrophysics Data System (ADS)

Khederzadeh, Mojtaba; Khalili, Mohammad

2014-10-01

Given that the microgrid concept is the building block of future electric distribution systems and electrical vehicles (EVs) are the future of transportation market, in this paper, the impact of EVs on the performance of microgrids is investigated. Demand-side participation is used to cope with increasing demand for EV charging. The problem of coordination of EV charging and discharging (with vehicle-to-grid (V2G) functionality) and demand response is formulated as a market-clearing mechanism that accepts bids from the demand and supply sides and takes into account the constraints put forward by different parts. Therefore, a day-ahead market with detailed bids and offers within the microgrid is designed whose objective is to maximize the social welfare which is the difference between the value that consumers attach to the electrical energy they buy plus the benefit of the EV owners participating in the V2G functionality and the cost of producing/purchasing this energy. As the optimization problem is a mixed integer nonlinear programming one, it is decomposed into one master problem for energy scheduling and one subproblem for power flow computation. The two problems are solved iteratively by interfacing MATLAB with GAMS. Simulation results on a sample microgrid with different residential, commercial and industrial consumers with associated demand-side biddings and different penetration level of EVs support the proposed formulation of the problem and the applied methods.

Identification of Visual Cues and Quantification of Drivers' Perception of Proximity Risk to the Lead Vehicle in Car-Following Situations

NASA Astrophysics Data System (ADS)

Kondoh, Takayuki; Yamamura, Tomohiro; Kitazaki, Satoshi; Kuge, Nobuyuki; Boer, Erwin Roeland

Longitudinal vehicle control and/or warning technologies that operate in accordance with drivers' subjective perception of risk need to be developed for driver-support systems, if such systems are to be used fully to achieve safer, more comfortable driving. In order to accomplish this goal, it is necessary to identify the visual cues utilized by drivers in their perception of risk when closing on the vehicle ahead in a car-following situation. It is also necessary to quantify the relation between the physical parameters defining the spatial relationship to the vehicle ahead and psychological metrics with regard to the risk perceived by the driver. This paper presents the results of an empirical study on quantification and formulization of drivers' subjective perception of risk based on experiments performed with a fixed-base driving simulator at the Nissan Research Center. Experiments were carried out to investigate the subjective perception of risk relative to the headway distance and closing velocity to the vehicle ahead using the magnitude estimation method. The experimental results showed that drivers' perception of risk was strongly affected by two variables: time headway, i.e., the distance to the lead vehicle divided by the following vehicle's velocity, and time to collision, i.e., the distance to the lead vehicle divided by relative velocity. It was also found that an equation for estimating drivers' perception of risk can be formulated as the summation of the time headway inverse and the time to collision inverse and that this expression can be applied to various approaching situations. Furthermore, the validity of this equation was examined based on real-world driver behavior data measured with an instrumented vehicle.

Lessons from a peer-led obesity prevention programme in English schools.

PubMed

Bell, Sarah L; Audrey, Suzanne; Cooper, Ashley R; Noble, Sian; Campbell, Rona

2017-04-01

Obesity in young people is a major public health concern. Energy balance, the interrelationship between diet and physical activity, is known to be a key determinant. Evidence supports the development of school-based approaches to obesity prevention. ASSIST (A Stop Smoking in Schools Trial) is an effective school-based, peer-led smoking prevention programme for 12-13-year-old students, based on diffusion of innovations theory. The AHEAD (Activity and Healthy Eating in ADolescence) study tested the feasibility of adapting ASSIST to an obesity prevention intervention. The AHEAD intervention was tested and refined during a pilot study in one school, followed by an exploratory trial in six schools. Quantitative (self-report behavioural questionnaires and evaluation forms) and qualitative (structured observations, focus groups and interviews) research methods were used to examine the implementation and acceptability of the intervention. The potential effectiveness of the intervention in increasing healthy eating was measured using self-report behavioural questionnaires. Activity monitors (accelerometers) were used to measure physical activity. Results show it was feasible to implement the AHEAD intervention, which was well received. However, implementation was resource and labour intensive and relatively expensive. Furthermore, there was no evidence of promise that the intervention would increase physical activity or healthy eating in adolescents. Although diet and physical activity are both relevant for obesity prevention, the focus on two behaviours appeared too complex for informal diffusion through peer networks. This identifies a tension, particularly for adolescent peer-led health promotion, between the desire not to isolate or oversimplify health behaviours and the need to present clear, succinct health promotion messages. © The Author (2014). Published by Oxford University Press.

A Control-Based Multidimensional Approach to the Role of Optimism in the Use of Dementia Day Care Services.

PubMed

Contador, Israel; Fernández-Calvo, Bernardino; Palenzuela, David L; Campos, Francisco Ramos; Rivera-Navarro, Jesús; de Lucena, Virginia Menezes

2015-11-01

We examined whether grounded optimism and external locus of control are associated with admission to dementia day care centers (DCCs). A total of 130 informal caregivers were recruited from the Alzheimer's Association in Salamanca (northwest Spain). All caregivers completed an assessment protocol that included the Battery of Generalized Expectancies of Control Scales (BEEGC-20, acronym in Spanish) as well as depression and burden measures. The decision of the care setting at baseline assessment (own home vs DCC) was considered the main outcome measure in the logistic regression analyses. Grounded optimism was a preventive factor for admission (odds ratio [OR]: 0.34 and confidence interval [CI]: 0.15-0.75), whereas external locus of control (OR: 2.75, CI: 1.25-6.03) increased the probabilities of using DCCs. Depression mediated the relationship between optimism and DCCs, but this effect was not consistent for burden. Grounded optimism promotes the extension of care at home for patients with dementia. © The Author(s) 2013.

Optimization and control of perfusion cultures using a viable cell probe and cell specific perfusion rates.

PubMed

Dowd, Jason E; Jubb, Anthea; Kwok, K Ezra; Piret, James M

2003-05-01

Consistent perfusion culture production requires reliable cell retention and control of feed rates. An on-line cell probe based on capacitance was used to assay viable biomass concentrations. A constant cell specific perfusion rate controlled medium feed rates with a bioreactor cell concentration of approximately 5 x 10(6) cells mL(-1). Perfusion feeding was automatically adjusted based on the cell concentration signal from the on-line biomass sensor. Cell specific perfusion rates were varied over a range of 0.05 to 0.4 nL cell(-1) day(-1). Pseudo-steady-state bioreactor indices (concentrations, cellular rates and yields) were correlated to cell specific perfusion rates investigated to maximize recombinant protein production from a Chinese hamster ovary cell line. The tissue-type plasminogen activator concentration was maximized ( approximately 40 mg L(-1)) at 0.2 nL cell(-1) day(-1). The volumetric protein productivity ( approximately 60 mg L(-1) day(-1) was maximized above 0.3 nL cell(-1) day(-1). The use of cell specific perfusion rates provided a straightforward basis for controlling, modeling and optimizing perfusion cultures.

Optimal recall period for caregiver-reported illness in risk factor and intervention studies: a multicountry study.

PubMed

Arnold, Benjamin F; Galiani, Sebastian; Ram, Pavani K; Hubbard, Alan E; Briceño, Bertha; Gertler, Paul J; Colford, John M

2013-02-15

Many community-based studies of acute child illness rely on cases reported by caregivers. In prior investigations, researchers noted a reporting bias when longer illness recall periods were used. The use of recall periods longer than 2-3 days has been discouraged to minimize this reporting bias. In the present study, we sought to determine the optimal recall period for illness measurement when accounting for both bias and variance. Using data from 12,191 children less than 24 months of age collected in 2008-2009 from Himachal Pradesh in India, Madhya Pradesh in India, Indonesia, Peru, and Senegal, we calculated bias, variance, and mean squared error for estimates of the prevalence ratio between groups defined by anemia, stunting, and underweight status to identify optimal recall periods for caregiver-reported diarrhea, cough, and fever. There was little bias in the prevalence ratio when a 7-day recall period was used (<10% in 35 of 45 scenarios), and the mean squared error was usually minimized with recall periods of 6 or more days. Shortening the recall period from 7 days to 2 days required sample-size increases of 52%-92% for diarrhea, 47%-61% for cough, and 102%-206% for fever. In contrast to the current practice of using 2-day recall periods, this work suggests that studies should measure caregiver-reported illness with a 7-day recall period.

2017 Presidential Address: Staying Ahead of the Curve.

PubMed

Allen, Bibb

2018-05-01

The practice of the radiological sciences has always been dynamic. From economics and payment policy to imaging appropriateness, the ACR has led the way in keeping our specialty ahead of the curve. However, being ahead of the curve is a fragile place, and constant diligence is needed to remain there. There will always be major changes on our horizon, and the ACR will be there to empower us to adapt to change. Copyright © 2018 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Price of gasoline: forecasting comparisons. [Box-Jenkins, econometric, and regression methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bopp, A.E.; Neri, J.A.

Gasoline prices are simulated using three popular forecasting methodologies: A Box--Jenkins type method, an econometric method, and a regression method. One-period-ahead and 18-period-ahead comparisons are made. For the one-period-ahead method, a Box--Jenkins type time-series model simulated best, although all do well. However, for the 18-period simulation, the econometric and regression methods perform substantially better than the Box-Jenkins formulation. A rationale for and implications of these results ae discussed. 11 references.

Challenges ahead for mass spectrometry and proteomics applications in epigenetics.

PubMed

Kessler, Benedikt M

2010-02-01

Inheritance of biological information to future generations depends on the replication of DNA and the Mendelian principle of distribution of genes. In addition, external and environmental factors can influence traits that can be propagated to offspring, but the molecular details of this are only beginning to be understood. The discoveries of DNA methylation and post-translational modifications on chromatin and histones provided entry points for regulating gene expression, an area now defined as epigenetics and epigenomics. Mass spectrometry turned out to be instrumental in uncovering molecular details involved in these processes. The central role of histone post-translational modifications in epigenetics related biological processes has revitalized mass spectrometry based investigations. In this special report, current approaches and future challenges that lay ahead due to the enormous complexity are discussed.

An experimental and computational investigation of electrical resistivity imaging for prediction ahead of tunnel boring machines

NASA Astrophysics Data System (ADS)

Schaeffer, Kevin P.

Tunnel boring machines (TBMs) are routinely used for the excavation of tunnels across a range of ground conditions, from hard rock to soft ground. In complex ground conditions and in urban environments, the TBM susceptible to damage due to uncertainty of what lies ahead of the tunnel face. The research presented here explores the application of electrical resistivity theory for use in the TBM tunneling environment to detect changing conditions ahead of the machine. Electrical resistivity offers a real-time and continuous imaging solution to increase the resolution of information along the tunnel alignment and may even unveil previously unknown geologic or man-made features ahead of the TBM. The studies presented herein, break down the tunneling environment and the electrical system to understand how its fundamental parameters can be isolated and tested, identifying how they influence the ability to predict changes ahead of the tunnel face. A proof-of-concept, scaled experimental model was constructed in order assess the ability of the model to predict a metal pipe (or rod) ahead of face as the TBM excavates through a saturated sand. The model shows that a prediction of up to three tunnel diameters could be achieved, but the unique presence of the pipe (or rod) could not be concluded with certainty. Full scale finite element models were developed in order evaluate the various influences on the ability to detect changing conditions ahead of the face. Results show that TBM/tunnel geometry, TBM type, and electrode geometry can drastically influence prediction ahead of the face by tens of meters. In certain conditions (i.e., small TBM diameter, low cover depth, large material contrasts), changes can be detected over 100 meters in front of the TBM. Various electrode arrays were considered and show that in order to better detect more finite differences (e.g., boulder, lens, pipe), the use of individual cutting tools as electrodes is highly advantageous to increase spatial resolution and current density close to the cutterhead.

Selection of broilers for increased innate immune markers: Past strategies and looking ahead

USDA-ARS?s Scientific Manuscript database

Economic efficiency demanded by the poultry industry has pushed selection towards high production with improved feed conversion ratios (FCR) and high yield; however, selection based heavily on growth characteristics and other phenotypic traits has adversely affected immune competence. Despite incre...

Gauging Possibilities for Action Based on Friction Underfoot

ERIC Educational Resources Information Center

Joh, Amy S.; Adolph, Karen E.; Narayanan, Priya J.; Dietz, Victoria A.

2007-01-01

Standing and walking generate information about friction underfoot. Five experiments examined whether walkers use such perceptual information for prospective control of locomotion. In particular, do walkers integrate information about friction underfoot with visual cues for sloping ground ahead to make adaptive locomotor decisions? Participants…

Framework for implementing performance planning for rural planning organizations : project summary.

DOT National Transportation Integrated Search

2017-01-01

Performance-based transportation planning has existed for many years and is being put in practice more as a result of recent federal rules. Moving Ahead for Progress in the 21st Century (MAP-21) and the Fixing Americas Surface Transportation Act p...

Water balance models in one-month-ahead streamflow forecasting

USGS Publications Warehouse

Alley, William M.

1985-01-01

Techniques are tested that incorporate information from water balance models in making 1-month-ahead streamflow forecasts in New Jersey. The results are compared to those based on simple autoregressive time series models. The relative performance of the models is dependent on the month of the year in question. The water balance models are most useful for forecasts of April and May flows. For the stations in northern New Jersey, the April and May forecasts were made in order of decreasing reliability using the water-balance-based approaches, using the historical monthly means, and using simple autoregressive models. The water balance models were useful to a lesser extent for forecasts during the fall months. For the rest of the year the improvements in forecasts over those obtained using the simpler autoregressive models were either very small or the simpler models provided better forecasts. When using the water balance models, monthly corrections for bias are found to improve minimum mean-square-error forecasts as well as to improve estimates of the forecast conditional distributions.

Alaska Satellite Facility: The Quest to Stay Ahead of the Big Data Wave

NASA Astrophysics Data System (ADS)

Labelle-Hamer, A. L.; Nicoll, J.; Munk, S.

2014-12-01

Big Data is getting bigger. Fast enough is getting faster. The number and type of products produced is growing. The ideas on how to handle the day-to-day management of data and data systems need to scale with the data and the demand. We have seen the effects of rapid growth spurts at the Alaska Satellite Facility (ASF) and anticipate we are not done yet. Looking back, ASF was conceived in 1982 to be a single-purpose imaging radar receiving station supporting a science team focused on geophysical processes. The primary construction at the University of Alaska Fairbanks (UAF) was completed in 1988 and full operational status achieved in 1991. The expected supports were estimated at 10 minutes per day and quickly grew to 70 minutes per day. In 1994, a Memorandum of Agreement (MOA) between NASA and UAF formed the ASF Distributed Active Archive Center (DAAC) complementing, the existing agreement for ASF. The demand for the use of ASF as a receiving station and as a data center grew as fast as, and at times faster, than the capabilities. Looking forward, as demand drives the system larger just adding on more of the same often complicates rather than simplifies the system. A growing percentage of efforts and resources spent on dealing with problems that originate from a legacy system can creep up on an organization. This in turn limits the ability to keep the overall sustaining costs under control and leads to a crisis. Such growth means more-of-the-same philosophy has to shift into change-or-die philosophy in order to boot strap up to the next level. In this talk, we review how ASF has faced this several times in the past as the volume and demand of data grew along with the technology to acquire and disseminate it. We will look at what is coming for ASF as a data center and what we think are the next steps to stay ahead of the Big Data wave.

Evaluation of an Early-Warning System for Heat Wave-Related Mortality in Europe: Implications for Sub-seasonal to Seasonal Forecasting and Climate Services

PubMed Central

Lowe, Rachel; García-Díez, Markel; Ballester, Joan; Creswick, James; Robine, Jean-Marie; Herrmann, François R.; Rodó, Xavier

2016-01-01

Heat waves have been responsible for more fatalities in Europe over the past decades than any other extreme weather event. However, temperature-related illnesses and deaths are largely preventable. Reliable sub-seasonal-to-seasonal (S2S) climate forecasts of extreme temperatures could allow for better short-to-medium-term resource management within heat-health action plans, to protect vulnerable populations and ensure access to preventive measures well in advance. The objective of this study is to assess the extent to which S2S climate forecasts could be incorporated into heat-health action plans, to support timely public health decision-making ahead of imminent heat wave events in Europe. Forecasts of apparent temperature at different lead times (e.g., 1 day, 4 days, 8 days, up to 3 months) were used in a mortality model to produce probabilistic mortality forecasts up to several months ahead of the 2003 heat wave event in Europe. Results were compared to mortality predictions, inferred using observed apparent temperature data in the mortality model. In general, we found a decreasing transition in skill between excellent predictions when using observed temperature, to predictions with no skill when using forecast temperature with lead times greater than one week. However, even at lead-times up to three months, there were some regions in Spain and the United Kingdom where excess mortality was detected with some certainty. This suggests that in some areas of Europe, there is potential for S2S climate forecasts to be incorporated in localised heat–health action plans. In general, these results show that the performance of this climate service framework is not limited by the mortality model itself, but rather by the predictability of the climate variables, at S2S time scales, over Europe. PMID:26861369

Long-range transport of Asian pollution to the northeast Pacific: Seasonal variations and transport pathways of carbon monoxide

NASA Astrophysics Data System (ADS)

Liang, Qing; Jaeglé, Lyatt; Jaffe, Daniel A.; Weiss-Penzias, Peter; Heckman, Anna; Snow, Julie A.

2004-12-01

Continuous CO measurements were obtained at Cheeka Peak Observatory (CPO, 48.3°N, 124.6°W, 480 m), a coastal site in Washington state, between 9 March 2001 and 31 May 2002. We analyze these observations as well as CO observations at ground sites throughout the North Pacific using the GEOS-CHEM global tropospheric chemistry model to examine the seasonal variations of Asian long-range transport. The model reproduces the observed CO levels, their seasonal cycle and day-to-day variability, with a 5-20 ppbv negative bias in winter/spring and 5-10 ppbv positive bias during summer. Asian influence on CO levels in the North Pacific troposphere maximizes during spring and minimizes during summer, ranging from 91 ppbv (44% of total CO) to 52 ppbv (39%) along the Asian Pacific Rim and from 44 ppbv (30%) to 24 ppbv (23%) at CPO. Maximum export of Asian pollution to the western Pacific occurs at 20°-50°N during spring throughout the tropospheric column, shifting to 30°-60°N during summer, mostly in the upper troposphere. The model captures five particularly strong transpacific transport events reaching CPO (four in spring, one in winter) resulting in 20-40 ppbv increases in observed CO levels. Episodic long-range transport of pollutants from Asia to the NE Pacific occurs throughout the year every 10, 15, and 30 days in the upper, middle, and lower troposphere, respectively. Lifting ahead of cold fronts followed by transport in midlatitude westerlies accounts for 78% of long-range transport events reaching the NE Pacific middle and upper troposphere. During summer, convective injection into the upper troposphere competes with frontal mechanisms in this export. Most events reaching the NE Pacific lower troposphere below 2 km altitude result from boundary layer outflow behind cold fronts (for spring) or ahead of cold fronts (for other seasons) followed by low-level transpacific transport.

Evaluation of an Early-Warning System for Heat Wave-Related Mortality in Europe: Implications for Sub-seasonal to Seasonal Forecasting and Climate Services.

PubMed

Lowe, Rachel; García-Díez, Markel; Ballester, Joan; Creswick, James; Robine, Jean-Marie; Herrmann, François R; Rodó, Xavier

2016-02-06

Heat waves have been responsible for more fatalities in Europe over the past decades than any other extreme weather event. However, temperature-related illnesses and deaths are largely preventable. Reliable sub-seasonal-to-seasonal (S2S) climate forecasts of extreme temperatures could allow for better short-to-medium-term resource management within heat-health action plans, to protect vulnerable populations and ensure access to preventive measures well in advance. The objective of this study is to assess the extent to which S2S climate forecasts could be incorporated into heat-health action plans, to support timely public health decision-making ahead of imminent heat wave events in Europe. Forecasts of apparent temperature at different lead times (e.g., 1 day, 4 days, 8 days, up to 3 months) were used in a mortality model to produce probabilistic mortality forecasts up to several months ahead of the 2003 heat wave event in Europe. Results were compared to mortality predictions, inferred using observed apparent temperature data in the mortality model. In general, we found a decreasing transition in skill between excellent predictions when using observed temperature, to predictions with no skill when using forecast temperature with lead times greater than one week. However, even at lead-times up to three months, there were some regions in Spain and the United Kingdom where excess mortality was detected with some certainty. This suggests that in some areas of Europe, there is potential for S2S climate forecasts to be incorporated in localised heat-health action plans. In general, these results show that the performance of this climate service framework is not limited by the mortality model itself, but rather by the predictability of the climate variables, at S2S time scales, over Europe.

Midcourse correction to a clinical trial when the event rate is underestimated: the Look AHEAD (Action for Health in Diabetes) Study.

PubMed

Brancati, Frederick L; Evans, Mary; Furberg, Curt D; Geller, Nancy; Haffner, Steven; Kahn, Steven E; Kaufmann, Peter G; Lewis, Cora E; Nathan, David M; Pitt, Bertram; Safford, Monika M

2012-02-01

The Look AHEAD (Action for Health in Diabetes) Study is a long-term clinical trial that aims to determine the cardiovascular disease (CVD) benefits of an intensive lifestyle intervention (ILI) in obese adults with type 2 diabetes. The study was designed to have 90% statistical power to detect an 18% reduction in the CVD event rate in the ILI Group compared to the Diabetes Support and Education (DSE) Group over 10.5 years of follow-up. The original power calculations were based on an expected CVD rate of 3.125% per year in the DSE group; however, a much lower-than-expected rate in the first 2 years of follow-up prompted the Data and Safety Monitoring Board (DSMB) to recommend that the Steering Committee undertake a formal blinded evaluation of these design considerations. The Steering Committee created an Endpoint Working Group (EPWG) that consisted of individuals masked to study data to examine relevant issues. The EPWG considered two primary options: (1) expanding the definition of the primary endpoint and (2) extending follow-up of participants. Ultimately, the EPWG recommended that the Look AHEAD Steering Committee approve both strategies. The DSMB accepted these modifications, rather than recommending that the trial continue with inadequate statistical power. Trialists sometimes need to modify endpoints after launch. This decision should be well justified and should be made by individuals who are fully masked to interim results that could introduce bias. This article describes this process in the Look AHEAD study and places it in the context of recent articles on endpoint modification and recent trials that reported endpoint modification.

Advances in air quality prediction with the use of integrated systems

NASA Astrophysics Data System (ADS)

Dragani, R.; Benedetti, A.; Engelen, R. J.; Peuch, V. H.

2017-12-01

Recent years have seen the rise of global operational atmospheric composition forecasting systems for several applications including climate monitoring, provision of boundary conditions for regional air quality forecasting, energy sector applications, to mention a few. Typically, global forecasts are provided in the medium-range up to five days ahead and are initialized with an analysis based on satellite data. In this work we present the latest advances in data assimilation using the ECMWF's 4D-Var system extended to atmospheric composition which is currently operational under the Copernicus Atmosphere Monitoring Service of the European Commission. The service is based on acquisition of all relevant data available in near-real-time, the processing of these datasets in the assimilation and the subsequent dissemination of global forecasts at ECMWF. The global forecasts are used by the CAMS regional models as boundary conditions for the European forecasts based on a multi-model ensemble. The global forecasts are also used to provide boundary conditions for other parts of the world (e.g., China) and are freely available to all interested entities. Some of the regional models also perform assimilation of satellite and ground-based observations. All products are assessed, validated and made publicly available on https://atmosphere.copernicus.eu/.

Estimating of aquifer parameters from the single-well water-level measurements in response to advancing longwall mine by using particle swarm optimization

NASA Astrophysics Data System (ADS)

Buyuk, Ersin; Karaman, Abdullah

2017-04-01

We estimated transmissivity and storage coefficient values from the single well water-level measurements positioned ahead of the mining face by using particle swarm optimization (PSO) technique. The water-level response to the advancing mining face contains an semi-analytical function that is not suitable for conventional inversion shemes because the partial derivative is difficult to calculate . Morever, the logaritmic behaviour of the model create difficulty for obtaining an initial model that may lead to a stable convergence. The PSO appears to obtain a reliable solution that produce a reasonable fit between water-level data and model function response. Optimization methods have been used to find optimum conditions consisting either minimum or maximum of a given objective function with regard to some criteria. Unlike PSO, traditional non-linear optimization methods have been used for many hydrogeologic and geophysical engineering problems. These methods indicate some difficulties such as dependencies to initial model, evolution of the partial derivatives that is required while linearizing the model and trapping at local optimum. Recently, Particle swarm optimization (PSO) became the focus of modern global optimization method that is inspired from the social behaviour of birds of swarms, and appears to be a reliable and powerful algorithms for complex engineering applications. PSO that is not dependent on an initial model, and non-derivative stochastic process appears to be capable of searching all possible solutions in the model space either around local or global optimum points.

A Solar Time-Based Analog Ensemble Method for Regional Solar Power Forecasting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodge, Brian S; Zhang, Xinmin; Li, Yuan

This paper presents a new analog ensemble method for day-ahead regional photovoltaic (PV) power forecasting with hourly resolution. By utilizing open weather forecast and power measurement data, this prediction method is processed within a set of historical data with similar meteorological data (temperature and irradiance), and astronomical date (solar time and earth declination angle). Further, clustering and blending strategies are applied to improve its accuracy in regional PV forecasting. The robustness of the proposed method is demonstrated with three different numerical weather prediction models, the North American Mesoscale Forecast System, the Global Forecast System, and the Short-Range Ensemble Forecast, formore » both region level and single site level PV forecasts. Using real measured data, the new forecasting approach is applied to the load zone in Southeastern Massachusetts as a case study. The normalized root mean square error (NRMSE) has been reduced by 13.80%-61.21% when compared with three tested baselines.« less

Cross-correlation earthquake precursors in the hydrogeochemical and geoacoustic signals for the Kamchatka peninsula

NASA Astrophysics Data System (ADS)

Ryabinin, Gennadiy; Gavrilov, Valeriy; Polyakov, Yuriy; Timashev, Serge

2012-06-01

We propose a new type of earthquake precursor based on the analysis of correlation dynamics between geophysical signals of different nature. The precursor is found using a two-parameter cross-correlation function introduced within the framework of flicker-noise spectroscopy, a general statistical physics approach to the analysis of time series. We consider an example of cross-correlation analysis for water salinity time series, an integral characteristic of the chemical composition of groundwater, and geoacoustic emissions recorded at the G-1 borehole on the Kamchatka peninsula in the time frame from 2001 to 2003, which is characterized by a sequence of three groups of significant seismic events. We found that cross-correlation precursors took place 27, 31, and 35 days ahead of the strongest earthquakes for each group of seismic events, respectively. At the same time, precursory anomalies in the signals themselves were observed only in the geoacoustic emissions for one group of earthquakes.

Mexican demand for US natural gas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kanter, M.A.; Kier, P.H.

1993-09-01

This study describes the Mexican natural gas industry as it exists today and the factors that have shaped the evolution of the industry in the past or that are expected to influence its progress; it also projects production and use of natural gas and estimates the market for exports of natural gas from the United States to Mexico. The study looks ahead to two periods, a near term (1993--1995) and an intermediate term (1996--2000). The bases for estimates under two scenarios are described. Under the conservative scenario, exports of natural gas from the United States would decrease from the 1992more » level of 250 million cubic feet per day (MMCF/d), would return to that level by 1995, and would reach about 980 MMCF/D by 2000. Under the more optimistic scenario, exports would decrease in 1993 and would recover and rise to about 360 MMCF/D in 1995 and to 1,920 MMCF/D in 2000.« less

[The attractive position of France in international clinical research: 2006 survey assessed by Leem (French pharmaceutical companies)].

PubMed

Courcier, Soizic; Sibenaler, Claire; Couderc, Monique; Trinquet, Françoise; Plétan, Yannick; Lassale, Catherine

2006-01-01

In order to evaluate the attractiveness of France for conducting international clinical trials, a survey is performed every two years among pharmaceutical companies that are based in France or have affiliates in France. Initiated in 2006, the current survey was much more representative than the previous ones with 20 companies accounting for 61% of the French market. This survey included 352 international phase II and III clinical studies carried out in 2004 and 2005, 74 countries, 17 345 centres and 137 989 patients. France has participated to half of the overall number of international clinical trials. France ranked among the best European recruiters (0,19 patient/1000 inhabitants) at the second position behind Scandinavian countries, taking in account numbers of inhabitants. Protocols are now to be given the go-ahead by Ethics Committee (CCPPRB) within 60 days. With a high productivity in phase IIb and in oncology, France is still an attractive place to locate clinical research.

Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia.

PubMed

Ng, Kar Yong; Awang, Norhashidah

2018-01-06

Frequent haze occurrences in Malaysia have made the management of PM 10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM 10 variation and good forecast of PM 10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM 10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM 10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM 10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.

Modeling and simulation of consumer response to dynamic pricing.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valenzuela, J.; Thimmapuram, P.; Kim, J

2012-08-01

Assessing the impacts of dynamic-pricing under the smart grid concept is becoming extremely important for deciding its full deployment. In this paper, we develop a model that represents the response of consumers to dynamic pricing. In the model, consumers use forecasted day-ahead prices to shift daily energy consumption from hours when the price is expected to be high to hours when the price is expected to be low while maintaining the total energy consumption as unchanged. We integrate the consumer response model into the Electricity Market Complex Adaptive System (EMCAS). EMCAS is an agent-based model that simulates restructured electricity markets.more » We explore the impacts of dynamic-pricing on price spikes, peak demand, consumer energy bills, power supplier profits, and congestion costs. A simulation of an 11-node test network that includes eight generation companies and five aggregated consumers is performed for a period of 1 month. In addition, we simulate the Korean power system.« less

Smoothing strategies combined with ARIMA and neural networks to improve the forecasting of traffic accidents.

PubMed

Barba, Lida; Rodríguez, Nibaldo; Montt, Cecilia

2014-01-01

Two smoothing strategies combined with autoregressive integrated moving average (ARIMA) and autoregressive neural networks (ANNs) models to improve the forecasting of time series are presented. The strategy of forecasting is implemented using two stages. In the first stage the time series is smoothed using either, 3-point moving average smoothing, or singular value Decomposition of the Hankel matrix (HSVD). In the second stage, an ARIMA model and two ANNs for one-step-ahead time series forecasting are used. The coefficients of the first ANN are estimated through the particle swarm optimization (PSO) learning algorithm, while the coefficients of the second ANN are estimated with the resilient backpropagation (RPROP) learning algorithm. The proposed models are evaluated using a weekly time series of traffic accidents of Valparaíso, Chilean region, from 2003 to 2012. The best result is given by the combination HSVD-ARIMA, with a MAPE of 0:26%, followed by MA-ARIMA with a MAPE of 1:12%; the worst result is given by the MA-ANN based on PSO with a MAPE of 15:51%.

Ahead of the game protocol: a multi-component, community sport-based program targeting prevention, promotion and early intervention for mental health among adolescent males.

PubMed

Vella, Stewart A; Swann, Christian; Batterham, Marijka; Boydell, Katherine M; Eckermann, Simon; Fogarty, Andrea; Hurley, Diarmuid; Liddle, Sarah K; Lonsdale, Chris; Miller, Andrew; Noetel, Michael; Okely, Anthony D; Sanders, Taren; Telenta, Joanne; Deane, Frank P

2018-03-21

There is a recognised need for targeted community-wide mental health strategies and interventions aimed specifically at prevention and early intervention in promoting mental health. Young males are a high need group who hold particularly negative attitudes towards mental health services, and these views are detrimental for early intervention and help-seeking. Organised sports provide a promising context to deliver community-wide mental health strategies and interventions to adolescent males. The aim of the Ahead of the Game program is to test the effectiveness of a multi-component, community-sport based program targeting prevention, promotion and early intervention for mental health among adolescent males. The Ahead of the Game program will be implemented within a sample drawn from community sporting clubs and evaluated using a sample drawn from a matched control community. Four programs are proposed, including two targeting adolescents, one for parents, and one for sports coaches. One adolescent program aims to increase mental health literacy, intentions to seek and/or provide help for mental health, and to decrease stigmatising attitudes. The second adolescent program aims to increase resilience. The goal of the parent program is to increase parental mental health literacy and confidence to provide help. The coach program is intended to increase coaches' supportive behaviours (e.g., autonomy supportive behaviours), and in turn facilitate high-quality motivation and wellbeing among adolescents. Programs will be complemented by a messaging campaign aimed at adolescents to enhance mental health literacy. The effects of the program on adolescent males' psychological distress and wellbeing will also be explored. Organised sports represent a potentially engaging avenue to promote mental health and prevent the onset of mental health problems among adolescent males. The community-based design, with samples drawn from an intervention and a matched control community, enables evaluation of adolescent males' incremental mental health literacy, help-seeking intentions, stigmatising attitudes, motivation, and resilience impacts from the multi-level, multi-component Ahead of the Game program. Notable risks to the study include self-selection bias, the non-randomised design, and the translational nature of the program. However, strengths include extensive community input, as well as the multi-level and multi-component design. Australian New Zealand Clinical Trials Registry ACTRN12617000709347 . Date registered 17 May 2017. Retrospectively registered.

3. West portal of Tunnel 23, view to north, 135mm ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

3. West portal of Tunnel 23, view to north, 135mm lens. Concrete foundation in right foreground was from 'telltale,' a simple post-and-beam frame that spanned the tracks with lengths of rope suspended from the beam. In the days when brakemen were required to be on, and walk along, the tops of freight cars to set brakes, the 'telltale' ropes would strike the unwary to warn of the tunnel ahead, allowing them to lie flat and avoid being struck by the tunnel portal. - Central Pacific Transcontinental Railroad, Tunnel No. 23, Milepost 132.69, Applegate, Placer County, CA

One Rx for solo survival.

PubMed

McKenzie, L F

1993-08-01

The Clinton administration's prescription for the "health care crisis" that was a hot campaign topic will be forthcoming. Mrs. Clinton is not backing away from the 100-day deadline set by the President. Hillary has already begun to focus on some of her big hits, if one can believe the media reports about her comments related to drug companies. The months ahead will be crucial for solo and independent physicians and should be used by them to prepare for a change in how they practice medicine. The following article suggests one area to which they may choose to direct their energies.

History of the Army Ground Forces. Study Number 13. Activation and Early Training of ’D’ Division

DTIC Science & Technology

1948-06-30

CONTENTS,. Page Prefatory Note I - Preactivation Period, 1 `-Act ivation. 10 >Basic Training. 11 The NP Test, 17 ’ýUnit Training, 24 K:,Platoon...of the hard days ahead. "A leader must be fair; he must be interested in his men; above all, he must kaow his job. No men wants to follow a stumbler or...said, "Be sure you donIt shoot me, Joe." Lieutenant 0’Keefe did not have the. best control of his squads as they advanced but he worked hard , dashing

Three years of biomedical FEL use in medicine and surgery How far have we come?

NASA Astrophysics Data System (ADS)

Jean, Benedikt

1997-02-01

Since the FEL has been made available for biophysical research in the IR, it has revolutionized the optimization strategies of laser-tissue interaction and the minimizing of adverse effects, in particular for photoablative use in surgery. Its tunability together with the free combination of wavelength and energy made it an efficient research tool, allowing the reduction of risks and costs of preclinical biomedical research. New computer-assisted surgical techniques evolved and the broader data basis of IR photothermal ablation allows more accurate predictive modelling of the efficiency and the adverse effects of photoablation. New applications for diagnostic imaging as well as the first clinical applications in neurosurgery lay ahead.

The Supply and Demand of the Cardiovascular Workforce

PubMed Central

Narang, Akhil; Sinha, Shashank S.; Rajagopalan, Bharath; Ijioma, Nkechinyere N.; Jayaram, Natalie; Kithcart, Aaron P.; Tanguturi, Varsha K.; Cullen, Michael W.

2017-01-01

As the burden of cardiovascular disease in the United States continues to increase, uncertainty remains on how well-equipped the cardiovascular workforce is to meet the challenges that lie ahead. In a time when health care is rapidly shifting, numerous factors affect the supply and demand of the cardiovascular workforce. This Council Commentary critically examines several factors that influence the cardiovascular workforce. These include current workforce demographics and projections, evolving health care and practice environments, and the increasing burden of cardiovascular disease. Finally, we propose 3 strategies to optimize the workforce. These focus on cardiovascular disease prevention, the effective utilization of the cardiovascular care team, and alterations to the training pathway for cardiologists. PMID:27712782

The Impact of Emerging Electronic Highway Control Systems on Motorist Information Requirements

NASA Technical Reports Server (NTRS)

Huchingson, R. Dale; Dudek, Conrad L.

1974-01-01

Advanced forms of electronic and computerized control systems are being developed to optimize traffic flow in and between cities. Modern technology permits communication of real-time information via signs and auditory messages and allows motorists to plan ahead for safer and more efficient travel. This paper describes an on-going research program for defining drivers' information needs and behavior in response to various message types and modes of presentation. Human engineer design criteria for real-time displays will be investigated in the laboratory and in research vehicles with field testing in actual city corridors. The results will be incorporated into a design handbook for use by sign design engineers.

Multiple-vehicle collision induced by a sudden stop in traffic flow

NASA Astrophysics Data System (ADS)

Sugiyama, Naoki; Nagatani, Takashi

2012-04-01

We study the dynamic process of the multiple-vehicle collision when a vehicle stops suddenly in a traffic flow. We apply the optimal-velocity model to the vehicular motion. If a vehicle does not decelerate successfully, it crashes into the vehicle ahead with a residual speed. The collision criterion is presented by vi(t)/Δxi(t)→∞ if Δxi(t)→0 where vi(t) and Δxi(t) are the speed and headway of vehicle i at time t. The number of crumpled vehicles depends on the initial velocity, the sensitivity, and the initial headway. We derive the region map (or phase diagram) for the multiple-vehicle collision.

Paradox in AI - AI 2.0: The Way to Machine Consciousness

NASA Astrophysics Data System (ADS)

Palensky, Peter; Bruckner, Dietmar; Tmej, Anna; Deutsch, Tobias

Artificial Intelligence, the big promise of the last millennium, has apparently made its way into our daily lives. Cell phones with speech control, evolutionary computing in data mining or power grids, optimized via neural network, show its applicability in industrial environments. The original expectation of true intelligence and thinking machines lies still ahead of us. Researchers are, however, optimistic as never before. This paper tries to compare the views, challenges and approaches of several disciplines: engineering, psychology, neuroscience, philosophy. It gives a short introduction to Psychoanalysis, discusses the term consciousness, social implications of intelligent machines, related theories, and expectations and shall serve as a starting point for first attempts of combining these diverse thoughts.

Event-based internet biosurveillance: relation to epidemiological observation

PubMed Central

2012-01-01

Background The World Health Organization (WHO) collects and publishes surveillance data and statistics for select diseases, but traditional methods of gathering such data are time and labor intensive. Event-based biosurveillance, which utilizes a variety of Internet sources, complements traditional surveillance. In this study we assess the reliability of Internet biosurveillance and evaluate disease-specific alert criteria against epidemiological data. Methods We reviewed and compared WHO epidemiological data and Argus biosurveillance system data for pandemic (H1N1) 2009 (April 2009 – January 2010) from 8 regions and 122 countries to: identify reliable alert criteria among 15 Argus-defined categories; determine the degree of data correlation for disease progression; and assess timeliness of Internet information. Results Argus generated a total of 1,580 unique alerts; 5 alert categories generated statistically significant (p < 0.05) correlations with WHO case count data; the sum of these 5 categories was highly correlated with WHO case data (r = 0.81, p < 0.0001), with expected differences observed among the 8 regions. Argus reported first confirmed cases on the same day as WHO for 21 of the first 64 countries reporting cases, and 1 to 16 days (average 1.5 days) ahead of WHO for 42 of those countries. Conclusion Confirmed pandemic (H1N1) 2009 cases collected by Argus and WHO methods returned consistent results and confirmed the reliability and timeliness of Internet information. Disease-specific alert criteria provide situational awareness and may serve as proxy indicators to event progression and escalation in lieu of traditional surveillance data; alerts may identify early-warning indicators to another pandemic, preparing the public health community for disease events. PMID:22709988

Revisiting the synoptic-scale predictability of severe European winter storms using ECMWF ensemble reforecasts

NASA Astrophysics Data System (ADS)

Pantillon, Florian; Knippertz, Peter; Corsmeier, Ulrich

2017-10-01

New insights into the synoptic-scale predictability of 25 severe European winter storms of the 1995-2015 period are obtained using the homogeneous ensemble reforecast dataset from the European Centre for Medium-Range Weather Forecasts. The predictability of the storms is assessed with different metrics including (a) the track and intensity to investigate the storms' dynamics and (b) the Storm Severity Index to estimate the impact of the associated wind gusts. The storms are well predicted by the whole ensemble up to 2-4 days ahead. At longer lead times, the number of members predicting the observed storms decreases and the ensemble average is not clearly defined for the track and intensity. The Extreme Forecast Index and Shift of Tails are therefore computed from the deviation of the ensemble from the model climate. Based on these indices, the model has some skill in forecasting the area covered by extreme wind gusts up to 10 days, which indicates a clear potential for early warnings. However, large variability is found between the individual storms. The poor predictability of outliers appears related to their physical characteristics such as explosive intensification or small size. Longer datasets with more cases would be needed to further substantiate these points.

Element level bridge inspection : benefits and use of data for bridge management.

DOT National Transportation Integrated Search

2016-02-01

In 2012, Congress passed the Moving Ahead for Progress in the 21st Century Act (MAP-21) and committed to the development of a datadriven, : risk based approach to asset management in the United States. This law requires the collection and submission ...

Analysis of the Osteogenic Effects of Biomaterials Using Numerical Simulation

PubMed Central

Zhang, Jie; Zhang, Wen; Yang, Hui-Lin

2017-01-01

We describe the development of an optimization algorithm for determining the effects of different properties of implanted biomaterials on bone growth, based on the finite element method and bone self-optimization theory. The rate of osteogenesis and the bone density distribution of the implanted biomaterials were quantitatively analyzed. Using the proposed algorithm, a femur with implanted biodegradable biomaterials was simulated, and the osteogenic effects of different materials were measured. Simulation experiments mainly considered variations in the elastic modulus (20–3000 MPa) and degradation period (10, 20, and 30 days) for the implanted biodegradable biomaterials. Based on our algorithm, the osteogenic effects of the materials were optimal when the elastic modulus was 1000 MPa and the degradation period was 20 days. The simulation results for the metaphyseal bone of the left femur were compared with micro-CT images from rats with defective femurs, which demonstrated the effectiveness of the algorithm. The proposed method was effective for optimization of the bone structure and is expected to have applications in matching appropriate bones and biomaterials. These results provide important insights into the development of implanted biomaterials for both clinical medicine and materials science. PMID:28116309

Analysis of the Osteogenic Effects of Biomaterials Using Numerical Simulation.

PubMed

Wang, Lan; Zhang, Jie; Zhang, Wen; Yang, Hui-Lin; Luo, Zong-Ping

2017-01-01

We describe the development of an optimization algorithm for determining the effects of different properties of implanted biomaterials on bone growth, based on the finite element method and bone self-optimization theory. The rate of osteogenesis and the bone density distribution of the implanted biomaterials were quantitatively analyzed. Using the proposed algorithm, a femur with implanted biodegradable biomaterials was simulated, and the osteogenic effects of different materials were measured. Simulation experiments mainly considered variations in the elastic modulus (20-3000 MPa) and degradation period (10, 20, and 30 days) for the implanted biodegradable biomaterials. Based on our algorithm, the osteogenic effects of the materials were optimal when the elastic modulus was 1000 MPa and the degradation period was 20 days. The simulation results for the metaphyseal bone of the left femur were compared with micro-CT images from rats with defective femurs, which demonstrated the effectiveness of the algorithm. The proposed method was effective for optimization of the bone structure and is expected to have applications in matching appropriate bones and biomaterials. These results provide important insights into the development of implanted biomaterials for both clinical medicine and materials science.

Overcoming Spatial and Temporal Barriers to Public Access Defibrillators Via Optimization.

PubMed

Sun, Christopher L F; Demirtas, Derya; Brooks, Steven C; Morrison, Laurie J; Chan, Timothy C Y

2016-08-23

Immediate access to an automated external defibrillator (AED) increases the chance of survival for out-of-hospital cardiac arrest (OHCA). Current deployment usually considers spatial AED access, assuming AEDs are available 24 h a day. The goal of this study was to develop an optimization model for AED deployment, accounting for spatial and temporal accessibility, to evaluate if OHCA coverage would improve compared with deployment based on spatial accessibility alone. This study was a retrospective population-based cohort trial using data from the Toronto Regional RescuNET Epistry cardiac arrest database. We identified all nontraumatic public location OHCAs in Toronto, Ontario, Canada (January 2006 through August 2014) and obtained a list of registered AEDs (March 2015) from Toronto Paramedic Services. Coverage loss due to limited temporal access was quantified by comparing the number of OHCAs that occurred within 100 meters of a registered AED (assumed coverage 24 h per day, 7 days per week) with the number that occurred both within 100 meters of a registered AED and when the AED was available (actual coverage). A spatiotemporal optimization model was then developed that determined AED locations to maximize OHCA actual coverage and overcome the reported coverage loss. The coverage gain between the spatiotemporal model and a spatial-only model was computed by using 10-fold cross-validation. A total of 2,440 nontraumatic public OHCAs and 737 registered AED locations were identified. A total of 451 OHCAs were covered by registered AEDs under assumed coverage 24 h per day, 7 days per week, and 354 OHCAs under actual coverage, representing a coverage loss of 21.5% (p < 0.001). Using the spatiotemporal model to optimize AED deployment, a 25.3% relative increase in actual coverage was achieved compared with the spatial-only approach (p < 0.001). One in 5 OHCAs occurred near an inaccessible AED at the time of the OHCA. Potential AED use was significantly improved with a spatiotemporal optimization model guiding deployment. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Meaningful use of health information technology: evidence suggests benefits and challenges lie ahead.

PubMed

Furukawa, Michael F; Poon, Eric

2011-12-01

Less than 3 years into the passage of the Health Information Technology for Economic and Clinical Health (HITECH) provisions of the American Recovery and Reinvestment Act of 2009, measurable results are emerging. For example, in the first 11 months during which healthcare providers ("eligible professionals") and acute care hospitals ("eligible hospitals") had the opportunity to demonstrate stage 1 "Meaningful Use" of Healthcare Information Technology (HIT), more than 20,000 "eligible professionals" and 750 "eligible hospitals" have done so. In the current issue of The American Journal of Managed Care, we showcase examples of HITECH's potential impact, as well as illustrate the opportunities and challenges ahead. Two studies in this issue illustrate how HIT can improve the capacity of our healthcare system to manage chronic illnesses. The study by Vollmer et al describes how an interactive voice recognition system can improve adherence to inhaled corticosteroids among individuals with asthma in a large health maintenance organization. Shelley's study shows that the combination of electronic medical records, clinical decision support, and performance feedback can improve the rate of blood pressure control in patients with hypertension who receive care in community health centers. Together, these studies provide hope that the nation's investment in HIT could one day yield clinical dividends. Three other studies in this issue suggest that success for HIT will require attention to both technological and sociological factors. The study by Millery et al attributes the success of an HIT-based intervention to a multi-faceted approach that involves a combination of decision support tools, systematic provider feedback, implementation support, and leadership. Results from Abramson's study suggest that the full error-reduction potential of e-prescribing may only be reached with the combination of on-line clinical decision support and support for clinicians. The study by Dimitropoulos et al further illustrates that a broad spectrum of healthcare consumers needs to be engaged to allay their privacy and security concerns about Health Information Exchange. To be sure, the challenges that lie ahead remain formidable. The survey results reported by Jha et al warn us that in spite of the broad-based enthusiasm for the HITECH program among US hospitals, certain required functionalities remain challenging to implement. Attainment of the HITECH objectives is by no means certain. The HITECH legislation represents a once-in-a-generation opportunity to deploy tools that could address many of the problems underlying the US healthcare system. While the healthcare community appears to be making good progress toward making these tools available to clinicians, these tools will mean little unless we leverage them to redesign healthcare to be safe, effective, patient-centered, timely, efficient, and equitable.

A 1-Diopter Vertical Prism Induces a Decrease of Head Rotation: A Pilot Investigation.

PubMed

Matheron, Eric; Zandi, Ava; Wang, Danping; Kapoula, Zoï

2016-01-01

Clinical studies in non-specific chronic arthralgia and back pain seem to indicate an association between vertical heterophoria (VH - latent vertical retinal misalignment) and asymmetrical head rotation. Such clinical observations suggest a link between VH and head rotation, but this was never tested. The purpose of this study was to simulate a VH in healthy subjects and examine its influence on the amplitude of active head rotation during 3D motion capture in upright stance. Subjects were asked to rotate their head three times from the straight ahead position and then to the right, back to straight ahead, to the left, and back to the straight ahead again. Three randomized conditions were run: normal viewing, with a 1-diopter prism base down on the dominant eye, or the non-dominant eye. The most important finding is that the experimental VH whichever the eye with the prism induces a significant decrease in the mean angle of head rotation compared to the normal viewing condition. This decrease was significant for rotation to the left. We suggest that the prism-induced VH modifies the reference posture and thereby affects head rotation; further studies are needed to confirm this effect and to extend to other types of dynamic activities.

Depressive symptomatology in middle-aged and older married couples: a dyadic analysis.

PubMed

Townsend, A L; Miller, B; Guo, S

2001-11-01

Depressive symptomatology has been frequently conceptualized as an individual matter, but social contextual models argue that symptom levels are likely to covary in close relationships. The present study investigated correlation between spouses' depressive symptomatology in middle-aged and older married couples, the influence of gender and race/ethnicity in predicting variability in symptom level, and the importance of individual-level covariates (education, health, and age) and couple-level covariates (household income and net worth). Results were based on secondary analysis of Wave 1 interviews with White, Black, and Mexican American married couples (N = 5,423) from the Health and Retirement Study (HRS) and the Study of Asset and Health Dynamics Among the Oldest Old (AHEAD). Dyadic data from husbands and wives were analyzed with multilevel modeling. Husbands' and wives' depressive symptoms were moderately correlated, gender and race/ethnicity (and their interaction) predicted depressive symptoms, and both individual-level and couple-level characteristics were significant covariates. Similarities as well as differences are noted between the HRS and AHEAD results. Results highlight the importance of dyadic data and multilevel models for understanding depressive symptomatology in married couples. The influence of race/ethnicity merits greater attention in future research. Differences in findings between HRS and AHEAD suggest life-course, cohort, or methodological influences.