The minimum of the mean square time-delay error is obtained by the optimal wavefront phase predictor. In the upcom- ing sections, the optimal predictor is derived and an analytical expression for the minimum variance of the time-delay error is given. The analysis is based on a stochastic dynamic model for wavefront phase fluctuations. This model fol- lows from a factorization of the von Kármán power spectrum. The stochastic model is the key to finding the optimal predictor of wavefront phase fluctuations over a horizon of the time delay ∆t. The properties of optimal prediction are discussed and compared to those of the AO integrator controller.
This study addresses error between measured and true ambient concentrations. Our results are consistent with previous finding that suggest that Berkson error, as defined on an unlogged scale (additive), produces no bias in the effect estimate [8,11] as shown in Figure 5; however, Berkson-like error defined on a log basis (multiplicative) can lead to risk ratio estimates per unit increase that are biased away from the null (although with a reduction in significance). Thus, the direction and magnitude of the bias are functions of error type. With the multiplicative error structure used here in conjunction with a linear dose response, large “true” values of air pollution would likely be underestimated, resulting in an overestimation of pollution health effects. We have shown how multiple air pollution measurements over space can be used to quantify the amount of error and provide a strategy for evaluating impacts of different types of this error. The results suggest that estimating impacts of measurement error on health risk assessment are particularly important when comparing results across primary and secondary pollutants as the corresponding error will vary widely in both amount and type depending on the degree of spatial variability. These results are suggestive of error impacts one would have from time-series studies in which a single measure, such as the population- weighted average, is used to characterize an urban or regional population exposure. The methodology used here can be applied to other study areas to quantify this type of measurement error and quantify its impacts on health risk estimates.
The fundamental observations made during an ARO event are the time series of phase and signal-to-noise ratio (SNR) of the RO signals. After the precise positions of the GPS and the receiver are known (e.g., Muradyan et al., 2010), the excess phase delay due to atmospheric refraction can be derived by differencing the measured signal total phase (with some initial ambiguity) with the GPS–receiver line-of- sight (LOS) distance. In this study we simulate GPS L1 sig- nals (1575.42 MHz) for an airborne receiver at 14 km. We neglect ionospheric effects, which can be removed through the linear combination of dual frequency measurements (e.g., Vorobev and Krasil’nikova, 1994; Hajj et al., 2002). Iono- spheric errors dominate spaceborne RO retrievals above 30 km (Kursinski et al., 1997); however, ARO retrievals are not possible above the height of the aircraft. In the- ory, the ionospheric effects are negligible for ARO retrievals in a spherically symmetric atmosphere, because the ARO retrieval requires the differencing between the RO signals originating from below (negative elevation angle) and above (positive elevation angle) the local horizon, which will cancel out most of the ionospheric errors (Xie et al., 2008) (hereafter referred to as X08). In practice, the largest part of the iono- spheric error is compensated by an initial code delay in the closed-loop tracking before transitioning to open-loop track- ing, and the remaining decrease in ionospheric delay (ad- vance) over the course of the occultation is much smaller than the neutral delay (Wang et al., 2016) and other error sources. This will minimize the need for dual GPS frequency ARO measurements. The partial bending angle, defined as the dif- ference between the bending angle measurements at the neg- ative elevation and the bending at the positive elevation, cor- responding to the same impact parameter, is then used to derive the refractivity through the inverse Abel transform. The derivative of the excess phase represents the Doppler shift of the carrier signal. The commonly used geometric op- tics (GO) method uses the measured Doppler and the GPS– receiver positions and velocities to retrieve the bending angle (Vorobev and Krasil’nikova, 1994). One major limitation of the GO method is its inability to account for signal interfer- ence, known as multipath, that frequently occurs in the moist lower troposphere due to sharp water vapor gradients. When multipath occurs, the signal at the receiver at a given time
complete the desired motor response in addition to the reaction time. 32 Given the implications of subjective assessment and examiner error in non-computer based assessments, computerized assessments of eye-hand coordination and reaction time are largely preferred to traditional assessments using various objects and timers. 47 Before computer-based assessments were available, eye-hand coordination and reaction time were assessed by the amount of time it took subjects to match colored marbles in colored holes, 48 or the number of pegs a subject could insert into a pegboard in a given amount of time. 49 Go/no go assessments take simple reaction time assessments a step further by adding in the aspect of decision making. In go/no go assessments there are two different stimuli, one that subjects should react to and one that subjects should not react to. When a stimulus is shown, the subject must quickly decide whether or not they should react to it, and if so execute the appropriate action. Reaction time in a go/no go situation is longer than simple reaction time, as the response selection phase of information processing is more complex. 50
This research, conducted in 1998 and 2008, uses go/no-go data to investigate the fundamentals of cognitive functioning in the inhibitory control ability of Japanese children. 844 subjects from kindergarten to junior high school participated in go/no-go task experiments. Performance of go/no-go tasks, which are frequently used to investigate response inhibition, measures a variety of cognitive components besides response inhibition. With normal brain development, the ability to inhibit responses improves substantially in adolescence. An increase over time in the error rate during the go/no-go tasks of subjects of the same age indicates that these processes are not functioning properly. Comparisons between the 1998 and 2008 data revealed several differences in error rates. In 2008, there were increases in the number of errors in groups from each age range. The comparison also revealed that overall error rates peaked at later ages in the 2008 subjects. Taken together, these results show changing conditions in the inhibitory function of the prefrontal cortex. However, the reason for these changing conditions remains unclear. While a lifestyle questionnaire revealed several differences in factors such as bedtimes and hours spent watching TV, analysis did not reveal a significant correlation.
ing the `bits' of the message so that `burst are spread out'. In theory we could do better than this by using the statistical properties of such bursts. In practice this may not be possible. In the paradigm case of mobile phones, the properties of the transmission chan- nel are constantly changing and are not well understood. (Here the main restriction on interleaving is that it introduces time delays. One way round this is `frequency hopping' in which several users constantly swap transmission channels `dividing bursts among users.) One desirable property of codes for mobile phone users is that they should `fail gracefully', that is that as the error rate for the channel rises the error rate for the receiver should not suddenly explode.
Hiring managers and recruiters are going through hundreds of applications for every one position. They don’t have the time or patience to try to decipher a resume that is cluttered, unorganized or difficult to read because of all the different styles and fonts going on. Make sure your resume is reader friendly – meaning it’s structured simply, includes clear headers and not too busy. Believe it or not, a simply typo or grammatical error can get your resume tossed in the trash so look over your resume several times and ask a friend to proofread it for any common mistakes you might have missed.
presented 0.25° above a central white fixation cross on a grey background. The task specifications were programmed and stimuli were delivered using the Presentation® software package (Version 0.75, www.neurobs.com). For each trial, a digit was presented for 150 ms followed by an Inter-Stimulus-Interval (ISI) of 1000ms. Participants were instructed to respond with a left mouse button press with their right forefinger upon presentation of each digit (Go trials) with the exception of the 25 occasions per block when the digit 3 (No-go target) appeared, where they were required to withhold their response. Participants were instructed to time their button presses to the offset of each stimulus. This kind of ‘response-locking’ has been shown to reduce inter-individual variability and eliminate speed accuracy trade-offs (Manly, Davison, Heutink, Galloway, & Robertson, 2000; Stuss, Murphy, Binns, & Alexander, 2003). In the present study, response-locking ensured that similar response strategies were employed by participants for both conditions. Timing of task stimuli and the basic response requirements are demonstrated in Figure 1.
We hypothesized that music might have a multifaceted influence on cognitive processes. Music might act as an extra-task interfering factor and engage parts of cogni- tive resources and therefore adversely affect performance in ongoing tasks and at the same time directly influence the emotional state or executive control functions and exert an enhancing effect on some cognitive functions. The stop-signal task requires participation and coordin- ation of multiple cognitive processes and is a suitable task to examine the effects of music on executive func- tions. Various behavioral measures in this task reflect the efficiency of the inhibitory processes and also context-dependent trial-by-trial modulations of behavior that are evoked by experiencing error (post-error slow- ing) or changes in task demand. It is still unclear whether and how sex and music might interact to influ- ence executive control of a goal-directed behavior. The differential effects of music on executive control functions in females versus males have rarely been investigated. In this study, we tested female and male participants in a stop-signal task to assess their ability to inhibit planned movement as an index of executive control function. We aimed at examining how exposure to task demands and practice would affect inhibitory ability in a stop-signal task, whether it is dependent on participants’ sex and whether music would influence these processes.
The Augmented Dickey-Fuller (ADF) test examines the unit root properties of the time series and determines the order of integration of each of the variables. Granger (1986) noted that a test for Cointegration is conducted as a pre test to avoid ‘spurious regression’ situations. Therefore, the widely used Johansen Cointegration technique was applied to determine if the variables are cointegrated i.e. if there is evidence for long run relationship among the variables. Further, Engle and Granger (1987) demonstrated that that any set of Cointegrated time series has an error correction representation, therefore, an Error Correction Model was formulated to show the speed at which the dependent variable adjusts to changes in the explanatory variables in an effort to achieve long run static equilibrium. Thereafter, the long run static regression analysis was estimated for (5). In all, E-views statistical package was extensively used to conduct the analyses.
But, after analyzing elaborately, this study finds that more filtration is required for choosing best algorithm among three classification algorithm. So, the TP Rate, FP Rate, Precision, Recall, F-Measure, ROC area values have been verified. In detailed Accuracy by Class, both Naïve Bayes and SMO classification algorithm has also same value without comparison of error rate measure. Besides this, at the time of comparing different type of error rates namely Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Relative Absolute Error (RAE), Root Relative Squared Error (RRSE) in the mushroom dataset, then among two algorithm consisting of same accuracy it has been investigated that Naïve Bayes Classification algorithm has become finally more preferable because of less prone to error among all different type of error rates during this experimental analysis. Naïve Bayes Classification algorithm performs best with accuracy 100% with less error rate.
Hence, we can conclude that, since lesser number of generations is required for absolute error model for both speed, it takes less time to establish the steady state rather quickly than any other type of model. But at the time of transition of speed command, the drive had shown smaller percentage of overshoot and undershoots under specified operating conditions when compared to other models. Therefore, based on the results we conclude that the absolute error model is the best model for optimization and can be used for the velocity control of DC Motor.
d from point 0. The NGO incurs operating costs to reach the producers that increase with distance. Each producer borrows one unit of capital from the NGO to produce one unit of good. We assume that there exists a single marketplace on the unit interval and it is also located at point 0 (the Thana headquarters). The reason for this assumption is that marketing opportunities in remote areas are very limited or even non-existent because of underdeveloped physical infrastructure. The NGO does not purchase goods from the producers, nor do the producers consume their goods. An individual producer needs to travel to point 0 to sell her goods and incurs transaction (transportation and time) costs, which is increasing with distance. Therefore, transaction costs for searching buyers is very high for the producer as one moves way from point 0. This leads to output market imperfection.
If we consider male patterns of participation, we see that Q4 males were significantly more active (p < 0.05) than Q1 and Q2 males in all periods except for Weekend mornings (the least active period overall for males). We also find that the After School, and Weekend Afternoon periods were the times when the differences between the most and least active Quartile of males were greatest. This difference is further amplified when we consider the length of these time blocks (see Table 3, Total Differences (minutes/day)); the 2.6 more min/hour that Q4 males accumulate when compared to Q1 males in the After School period, means an actual difference of 10.4 minutes each day during this 4 hour time block. This is consistent with the findings of Mota et al., 14 who found that males generally seemed to be more
The overall incidence of EPS-related TEAEs and their TTO and TTR were similar in patients treated with PP3M and PP1M. Subgroup analyses did not reveal any effect of dose or age on the TTO or TTR of the EPS-related TEAEs for any of the two treatments. Having similar or lower EPS-related TEAEs and less frequent dosing may encourage the use of PP3M to increase the overall adherence rates in patients with schizophrenia and will allow more time for physicians, caregivers, and patients to treat other issues frequently con- straining a good quality of life for these patients, such as psychosocial rehabilitation, substance abuse treatment, health maintenance, and vocational rehabilitation.
To illustrate, consider the analyses conducted by Miyake et al. (2000) concerning the factors underlying the production of perseverative errors on the Wisconsin Card Sorting Test (Milner, 1963). The test requires participants to sort cards according to a changing criterion. Each card shows a number of coloured shapes, e.g., four red circles or two blue triangles. Participants sort the cards into piles that match “target” cards according to the number, type or colour of the shapes on the cards. After each sorting attempt they are told only if they were correct or incorrect. To perform well on the test, participants must infer the experimenter’s sorting criterion, but the experimenter changes this criterion when the participant achieves a run of ten (or in some versions six) correct sorts. Perseverative errors arise when a participant continues to sort by an old, no longer valid, criterion, despite receiving negative feedback. Such errors may relate to poor set-shifting (i.e., failure to switch to a new sorting criterion), to inadequate response inhibition (i.e., failure to inhibit sorting to an old and now falsified rule), or even to failure to monitor for and integrate negative feedback. Miyake et al. considered five possible models relating their three factors (set-shifting, memory updating and response inhibition) to the number of perseverative errors produced by their participants. The model they endorsed consists of one path from the set-shifting factor, with a standardised path coefficient of 0.38 for the set-shifting factor. However, the fit of this model (χ 2 (32) = 25.45; IFI = 1.06) 1 is only slightly better than that of a model with paths from both set-shifting and response inhibition (χ 2 (31) = 25.02; IFI = 1.06), and the model with one path from response inhibition also produces a reasonable fit (χ 2 (32) = 30.59; IFI = 1.01), with a standardised path coefficient of 0.33 for the response inhibition factor. Critically, three different models produce qualitatively similar fits to the data. While goodness-of-fit statistics may be used to rank order these models, the models are based on factors inferred from the inter-correlations between performance on the nine simple tasks. Any statistical error in these factors could easily alter this rank ordering.