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At least 19 records

Neural Predictors of Visuomotor Adaptation Rate and Multi-Day Savings

Recent studies of sensorimotor adaptation have found that individual differences in task-based functional brain activation are associated with the rate of adaptation and savings at subsequent sessions. However, few studies to date have investigated offline neural predictors of adaptation and multi-day savings. In the present study, we explore whether individual differences in the rate of visuomotor adaptation and multi-day savings are associated with differences in resting state functional connectivity and gray matter volume. Thirty-four participants performed a manual adaptation task during two separate test sessions, on average 9 days apart. We found that resting state functional connectivity strength between sensorimotor, anterior cingulate, and temporoparietal areas of the brain was a significant predictor of adaptation rate during the early, cognitive phase of practice. In contrast, default mode network functional connectivity strength was found to predict late adaptation rate and savings on day two, which suggests that these behaviors may rely on overlapping processes. We also found that gray matter volume in temporoparietal and occipital regions was a significant predictor of early learning, whereas gray matter volume in superior posterior regions of the cerebellum was a significant predictor of late adaptation. The results from this study suggest that offline neural predictors of early adaptation facilitate the cognitive mechanisms of sensorimotor adaptation, with support from by the involvement of temporoparietal and cingulate networks. In contrast, the neural predictors of late adaptation and savings, including the default mode network and the cerebellum, likely support the storage and modification of newly acquired sensorimotor representations. These findings provide novel insights into the neural processes associated with individual differences in sensorimotor adaptation.

Cassady, Kaitlin

The development of a Kalman filter clock predictor

A Kalman filter based clock predictor is developed, and its performance evaluated using both simulated and real data. The clock predictor is shown to possess a neat to optimal Prediction Error Variance (PEV) when the underlying noise consists of one of the power law noise processes commonly encountered in time and frequency measurements. The predictor's performance is the presence of multiple noise processes is also examined. The relationship between the PEV obtained in the presence of multiple noise processes and those obtained for the individual component noise processes is examined. Comparisons are made with a simple linear clock predictor. The clock predictor is used to predict future values of the time offset between pairs of NPL's active hydrogen masers.

clock predictor

Predictor symbology in computer-generated perspective displays

An advanced display format for the four dimensional commercial aircraft approach-to-landing is evaluated. The desired curved and descending approach path is presented by displaying the perspective image of a tunnel. Attention is focussed on the predictor symbology, superimposed on the tunnel image. A perspective three dimensional predictor symbol, providing future position, as well as future attitude information, is compared with a flat two dimensional version, which only provides the future position. In addition to this, the predictor displays the actual airspeed as well as the desired airspeed, prescribed by the four dimensional path. Results show that the three dimensional predictor symbol outperforms the two dimensional predictor in following the trajectory in a moderate-to-heavy turbulent environment, which is manifested in accurate manual true airspeed control was obtained without affecting the main task performance significantly.

Grunwald, A. J.

Predictor symbology in computer-generated pictorial displays

The display under investigation, is a tunnel display for the four-dimensional commercial aircraft approach-to-landing under instrument flight rules. It is investigated whether more complex predictive information such as a three-dimensional perspective vehicle symbol, predicting the future vehicle position as well as future vehicle attitude angles, contributes to a better system response, and suitable predictor laws for the predictor motions, are formulated. Methods for utilizing the predictor symbol in controlling the forward velocity of the aircraft in four-dimensional approaches, are investigated. The simulator tests show, that the complex perspective vehicle symbol yields improved damping in the lateral response as compared to a flat two-dimensional predictor cross, but yields generally larger vertical deviations. Methods of using the predictor symbol in controlling the forward velocity of the vehicle are shown to be effective. The tunnel display with superimposed perspective vehicle symbol yields very satisfactory results and pilot acceptance in the lateral control but is found to be unsatisfactory in the vertical control, as a result of too large vertical path-angle deviations.

Grunwald, A. J.

Calibration of Predictor Models Using Multiple Validation Experiments

This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.

Crespo, Luis G.

Separation Monitoring with Four Types of Predictors on a Cockpit Display of Traffic Information

A clear and concise display format for use in later full mission simulator evaluation of the cockpit display of traffic information (CDTI) concept was studied. This experiment required airline pilots to monitor a CDTI and make perceptual judgments concerning the future position of a single intruder aircraft in relationship to their own aircraft (ownship). The main experimental variable was the type of predictor used to display future position of each aircraft. Predictors were referenced to the ground or to ownship and they either included turn rate information or did not. Other variables were the aircraft's separation distance when the judgment was required and the type of encounter (straight or turning). Results indicate that under these experimental conditions fewer errors were made when the predictor included turn rate information. There was little difference in overall error rate for the curved ground referenced and the ownship referenced predictors.

Jago, S.

Predictor laws for pictorial flight displays

Two predictor laws are formulated and analyzed: (1) a circular path law based on constant accelerations perpendicular to the path and (2) a predictor law based on state transition matrix computations. It is shown that for both methods the predictor provides the essential lead zeros for the path-following task. However, in contrast to the circular path law, the state transition matrix law furnishes the system with additional zeros that entirely cancel out the higher-frequency poles of the vehicle dynamics. On the other hand, the circular path law yields a zero steady-state error in following a curved trajectory with a constant radius. A combined predictor law is suggested that utilizes the advantages of both methods. A simple analysis shows that the optimal prediction time mainly depends on the level of precision required in the path-following task, and guidelines for determining the optimal prediction time are given.

Grunwald, A. J.

Regional Distribution Models with Lack of Proximate Predictors: Africanized Honeybees Expanding North

Species distribution models have often been hampered by poor local species data, reliance on coarse-scale climate predictors and the assumption that species-environment relationships, even with non-proximate predictors, are consistent across geographical space. Yet locally accurate maps of invasive species, such as the Africanized honeybee (AHB) in North America, are needed to support conservation efforts. Current AHB range maps are relatively coarse and are inconsistent with observed data. Our aim was to improve distribution maps using more proximate predictors (phenology) and using regional models rather than one across the entire range of interest to explore potential differences in drivers.

PRedictors

Pilot performance during a simulated standard instrument procedure turn with and without a predictor display

A simulator study was conducted to measure the effectiveness of predictor information incorporated into a CRT display of a computer simulated aircraft's horizontal and vertical situation. Professional pilots served as subjects for the task of executing a standard instrument procedure turn at constant altitude in constant crosswinds with and without their predicted ground track displayed. The results showed that the display with the predicted ground track was markedly and significantly superior to the display without this information and that the subjects were generally satisfied with this type of information. Mean rms lateral path error was independent of the crosswind velocity with the predictor information, and increased without it and with increasing wind velocity. Rms stick activity decreased with the predictor display which also uncoupled aileron and elevator activity.

Kreifeldt, J. G.

Pilot Performance During A Simulated Standard Instrument Procedure Turn With and Without A Predictor Display

A simulator study was conducted to measure the effectiveness of predictor information incorporated into a CRT display of a computer simulated aircraft's horizontal and vertical situation. Professional pilots served as subjects for the task of executing a standard instrument procedure turn at constant altitude in constant crosswinds with and without their predicted ground track displayed. The results show that the display with the predicted ground track was markedly and significantly superior to the display without this information and that the subjects were generally satisfied with this type of information. Mean rms lateral path error was independent of the crosswind velocity with the predictor information, and increased without it with increasing wind velocity. Rms stick activity decreased with the predictor display which also uncoupled aileron and elevator activity.

John G Kreifeldt

Evaluating a CRT map predictor for airborne use

Six airline pilots participated in a fixed-base simulator experiment designed to study the advantages and disadvantages of incorporating a simple horizontal flight-path predictor on both fixed and rotating electronic CRT map displays. The pilots were asked to fly a modified 'figure eight' ground track while attempting to maintain constant altitude. All flight information was displayed on one 17-in. (43-cm) CRT monitor. The controlled variables were the map orientation, pilots, presence or absence of crosswinds, presence or absence of wind gusts, and presence or absence of predictor. Error scores were recorded as deviations from the commanded ground track and altitude. It was found that the predictor reduced deviations from the commanded ground track, narrowed performance differences among pilots, narrowed the error differences found with and without crosswinds, and decreased pilot work load.

Baty, D. L.

Parametric study of predictor accuracy impact on OFT rendezvous targeting

A parametric study was made to quantitatively define the effects of errors in the state vector predictor used by the Operational Flight Trainer (OFT) rendezvous targeting algorithms. The effect of the predictor accuracy on the OFT rendezvous profile is shown by the sensitivity of various critical rendezvous parameters with respect to downrange and radial predictor error rates. The effect of both inertial (same errors on both vehicles) and relative (differential errors on one vehicle with respect to the other) errors were considered. Relative radial error rates had the largest impact on the rendezvous followed by relative downrange errors, radial inertial errors and downrange inertial errors.

Glenn, S. W.

Crop weather models of corn and soybeans for Agrophysical Units (APU's) in Iowa using monthly meteorological predictors

Models based on multiple regression were developed to estimate corn and soybean yield from weather data for agrophysical units (APU) in Iowa. The predictor variables are derived from monthly average temperature and monthly total precipitation data at meteorological stations in the cooperative network. The models are similar in form to the previous models developed for crop reporting districts (CRD). The trends and derived variables were the same and the approach to select the significant predictors was similar to that used in developing the CRD models. The APU's were selected to be more homogeneous with respect crop to production than the CRDs. The APU models are quite similar to the CRD models, similar explained variation and number of predictor variables. The APU models are to be independently evaluated and compared to the previously evaluated CRD models. That comparison should indicate the preferred model area for this application, i.e., APU or CRD.

Leduc, S.

Predictor-corrector procedures for thermal buckling analysis of multilayered composite plates

A study is made of two predictor-corrector procedures for the accurate determination of global, as well as detailed, thermal buckling response characteristics of composite plates. Both procedures use first-order shear deformation theory in the predictor phase, but differ in the elements of the computational model being adjusted in the corrector phase. The first procedure calculates a posteriori estimates of the composite correction factors and uses them to adjust the transverse shear stiffnesses of the plate. The second procedure calculates a posteriori the functional dependence of the displacement components on the thickness coordinate. The corrected quantities are then used in conjunction with three-dimensional equations to obtain better estimates for the different response quantities. Extensive numerical results are presented, showing the effects of variation in the geometric and lamination parameters for antisymmetrically laminated composite plates subjected to uniform temperature rise, on the accuracy of the thermal buckling response obtained by predictor-corrector procedures.

Noor, A. K.

Comparison of transform coding methods with an optimal predictor for the data compression of digital elevation models

Statistical encoding techniques enable the reduction of the number of bits required to encode a set of symbols, and are derived from their probabilities. Huffman encoding is an example of statistical encoding that has been used for error-free data compression. The degree of compression given by Huffman encoding in this application can be improved by the use of prediction methods. These replace the set of elevations by a set of corrections that have a more advantageous probability distribution. In particular, the method of Lagrange Multipliers for minimization of the mean square error has been applied to local geometrical predictors. Using this technique, an 8-point predictor achieved about a 7 percent improvement over an existing simple triangular predictor.

Lewis, Michael

Prediction of Coronal Mass Ejections From Vector Magnetograms: Quantitative Measures as Predictors

We derived two quantitative measures of an active region's global nonpotentiality from the region's vector magnetogram, 1) the net current (I(sub N)), and 2) the length of strong-shear, strong-field main neutral line (Lss), and used these two measures in a pilot study of the CME productivity of 4 active regions. We compared the global nonpotentiality measures to the active regions' CME productivity determined from GOES and Yohkoh/SXT observations. We found that two of the active regions were highly globally nonpotential and were CME productive, while the other two active regions had little global nonpotentiality and produced no CMEs. At the Fall 2000 AGU, we reported on an expanded study (12 active regions and 17 magnetograms) in which we evaluated four quantitative global measures of an active region's magnetic field and compared these measures with the CME productivity. The four global measures (all derived from MSFC vector magnetograms) included our two previous measures (I(sub N) and L(sub ss)) as well as two new ones, the total magnetic flux (PHI) (a measure of an active region's size), and the normalized twist (alpha (bar)= muIN/PHI). We found that the three quantitative measures of global nonpotentiality (I(sub N), L(sub ss), alpha (bar)) were all well correlated (greater than 99% confidence level) with an active region's CME productivity within plus or minus 2 days of the day of the magnetogram. We will now report on our findings of how good our quantitative measures are as predictors of active-region CME productivity, using only CMEs that occurred after the magnetogram. We report the preliminary skill test of these quantitative measures as predictors. We compare the CME prediction success of our quantitative measures to the CME prediction success based on an active region's past CME productivity. We examine the cases of the handful of false positive and false negatives to look for improvements to our predictors. This work is funded by NSF through the Space Weather Program and by NASA through the Solar Physics Supporting Research and Technology Program.

Falconer, D. A.

Predictor-Corrector Entry Guidance for Reusable Launch Vehicles

An online entry guidance algorithm has been developed using a predictor-corrector approach. The algorithm is designed for the Reusable Launch Vehicle (RLV) and is demonstrated by using, the X-33 model. The objective of the design is to handle widely dispersed entry conditions and deliver the vehicle at the Terminal Area Energy Management (TAEM) interface box within an acceptable tolerance and without violating any of the vehicle physical constraints. Combination of several control variables is used in testing the performance and computational requirement of the algorithm. The control variables are the bank angle, angle-of-attack and the time for roll reversal. The bank angle and angle-of-attack profiles are the nominal profiles plus the perturbations in each direction. The initial guess of the bank profile is a 45 degrees bank angle with reversal at 360 seconds from liftoff. A six-element state vector is propagated to the TAEM interface box through the integration of the equations of motion (EOM). Altitude, heading and range errors are computed between the desired and the achieved state at the TAEM interface. These errors are used to correct the initial guess of the control variables. This process is repeated until the errors meet an acceptable level at the TAEM interface. Several numerical optimization methods are used to evaluate the convergent property of the predictor-predictor methodology. Successful results are demonstrated using the X-33 model.

Youssef, Hussein

Survey and Method for Determination of Trajectory Predictor Requirements

A survey of air-traffic-management researchers, representing a broad range of automation applications, was conducted to document trajectory-predictor requirements for future decision-support systems. Results indicated that the researchers were unable to articulate a basic set of trajectory-prediction requirements for their automation concepts. Survey responses showed the need to establish a process to help developers determine the trajectory-predictor-performance requirements for their concepts. Two methods for determining trajectory-predictor requirements are introduced. A fast-time simulation method is discussed that captures the sensitivity of a concept to the performance of its trajectory-prediction capability. A characterization method is proposed to provide quicker, yet less precise results, based on analysis and simulation to characterize the trajectory-prediction errors associated with key modeling options for a specific concept. Concept developers can then identify the relative sizes of errors associated with key modeling options, and qualitatively determine which options lead to significant errors. The characterization method is demonstrated for a case study involving future airport surface traffic management automation. Of the top four sources of error, results indicated that the error associated with accelerations to and from turn speeds was unacceptable, the error associated with the turn path model was acceptable, and the error associated with taxi-speed estimation was of concern and needed a higher fidelity concept simulation to obtain a more precise result

Rentas, Tamika L.