980 resultados para Speed-accuracy tradeoff
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When a racing driver steers a car around a sharp bend, there is a trade-off between speed and accuracy, in that high speed can lead to a skid whereas a low speed increases lap time, both of which can adversely affect the driver's payoff function. While speed-accuracy trade-offs have been studied extensively, their susceptibility to risk sensitivity is much less understood, since most theories of motor control are risk neutral with respect to payoff, i.e., they only consider mean payoffs and ignore payoff variability. Here we investigate how individual risk attitudes impact a motor task that involves such a speed-accuracy trade-off. We designed an experiment where a target had to be hit and the reward (given in points) increased as a function of both subjects' endpoint accuracy and endpoint velocity. As faster movements lead to poorer endpoint accuracy, the variance of the reward increased for higher velocities. We tested subjects on two reward conditions that had the same mean reward but differed in the variance of the reward. A risk-neutral account predicts that subjects should only maximize the mean reward and hence perform identically in the two conditions. In contrast, we found that some (risk-averse) subjects chose to move with lower velocities and other (risk-seeking) subjects with higher velocities in the condition with higher reward variance (risk). This behavior is suboptimal with regard to maximizing the mean number of points but is in accordance with a risk-sensitive account of movement selection. Our study suggests that individual risk sensitivity is an important factor in motor tasks with speed-accuracy trade-offs.
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Among the cognitive studies of action, an important behavioral method is used to observe Reaction Time (RT) and Movement Time (MT) as the functions of motor parameters. RT is measured from the beginning of target presentation to the initiation of a movement, which is regarded as the programming of the ongoing movement. MT is measured from the initiation to the end of the movement, which is regarded as the execution of the movement. However, the relationship between RT and motor parameters remains uncertain till now. Under the uncertainty many related issues cannot be settled for long period, especially the issues as whether the amplitude effect appears during RT, or what should the amplitude effect be during RT. The present study aimed to find out the amplitude effect and the related cognitive process under different experimental conditions. First, we discussed the potential composition of RT and suggested that RT that normally measured in previous experiments might not reflect motor programming very well. Then we designed a series experiments to observe the relationship between RT and motor programming by using different Index of Difficulty (ID), different instructions in which speed and accuracy were emphasized respectively, different vision condition during movement execution and Go/NoGo paradigm. Meanwhile, we compared the amplitude effect under the respective RT to make the specific conclusion about the amplitude effect, and the relationship between RT and MT as well. The main findings are showed as following. 1) Because of the existing of “preview”, “visual feedback control” and “speed-accuracy tradeoff”, RT reflects motor programming differently under different experimental conditions. 2) Under different experimental conditions, the amplitude effect on RT varies. RT could be too short to exhibit the amplitude effect. Or the amplitude effect could be that more RT is needed for shorter movement when RT is prolonged. Or the amplitude effect could be that more RT is needed for longer movement when RT is further prolonged. 3) Under the present experimental conditions, the amplitude effect on MT showed consistently that longer movement needs longer MT. 4) Under the present experimental conditions, the relationship between RT and MT is a kind of compensation. The present study has important theoretic significance. The cognitive process of action is an important part of human cognitive behavior. The related studies could be very helpful for human people to know about themselves and the relation between themselves and the surroundings as well. Keywords motor programming; amplitude effect; Reaction Time (RT); Movement Time (MT)
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Performance of cyclical and discrete movements executed in Fitts’ task simulated by computer Abstract This study compared the performance of cyclical and discrete movements in Fitts’ task simulated by a computer. Twenty male adults, between 25 and 30 years old, participated as volunteers in the study. The software Discrete Aiming Task (v.2.0) simulated the Fitts’ task, in the discrete and cyclical conditions, and provided the movement time (TM). It was manipulated 4 target widths and 3 distances between the targets to provide index of difficulties (ID) from 1 to 6 bits. The ANOVA TWO WAY, 3 (Conditions) x 6 (ID), with repeated measures in the last factor, compared the TM in the different conditions. Regression analysis verified the relationship between TM x ID. There were no significant differences between the conditions; the virtual environment and the mouse were used to explain such results. All movement conditions showed a straight relationship between TM x ID with R²>0.990. Therefore, Fitts’ law showed to be consistent, independently of the movement strategy performed.
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Whenever we open our eyes, we are confronted with an overwhelming amount of visual information. Covert attention allows us to select visual information at a cued location, without eye movements, and to grant such information priority in processing. Covert attention can be voluntarily allocated, to a given location according to goals, or involuntarily allocated, in a reflexive manner, to a cue that appears suddenly in the visual field. Covert attention improves discriminability in a wide variety of visual tasks. An important unresolved issue is whether covert attention can also speed the rate at which information is processed. To address this issue, it is necessary to obtain conjoint measures of the effects of covert attention on discriminability and rate of information processing. We used the response-signal speed-accuracy tradeoff (SAT) procedure to derive measures of how cueing a target location affects speed and accuracy in a visual search task. Here, we show that covert attention not only improves discriminability but also accelerates the rate of information processing.
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This study evaluated effects of defensive pressure on running velocity in footballers during the approach to kick a stationary football. Approach velocity and ball speed/accuracy data were recorded from eight football youth academy participants (15.25, SD=0.46 yrs). Participants were required to run to a football to cross it to a receiver to score against a goal-keeper. Defensive pressure was manipulated across three counterbalanced conditions: defender-absent (DA); defender-far (DF) and defender-near (DN). Pass accuracy (percentages of a total of 32 trials with 95% confidence limits in parenthesis) did not significantly reduce under changing defensive pressure: DA, 78% (55–100%); DF, 78% (61–96%); DN, 59% (40–79%). Ball speed (m·s−1) significantly reduced as defensive pressure was included and increased: DA, 23.10 (22.38–23.83); DF, 20.40 (19.69–21.11); DN, 19.22 (18.51–19.93). When defensive pressure was introduced, average running velocity of attackers did not change significantly: DA versus DF (m·s−1), 5.40 (5.30–5.51) versus 5.41 (5.34–5.48). Scaling defender starting positions closer to the start position of the attacker (DN) significantly increased average running velocity relative to the DA and DF conditions, 5.60 (5.50–5.71). In the final approach footfalls, all conditions significantly differed: DA, 5.69 (5.35–6.03); DF, 6 .22 (5.93–6.50); DN, 6.52 (6.23–6.80). Data suggested that approach velocity is constrained by both presence and initial distance of the defender during task performance. Implications are that the expression of kicking behaviour is specific to a performance context and some movement regulation features will not emerge unless a defender is present as a task constraint in practice.
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Objectives The relationship between performance variability and accuracy in cricket fast bowlers of different skill levels under three different task conditions was investigated. Bowlers of different skill levels were examined to observe if they could adapt movement patterns to maintain performance accuracy on a bowling skills test. Design 8 national, 12 emerging and 12 junior pace bowlers completed an adapted version of the Cricket Australia bowling skills test, in which they performed 30 trials involving short (n = 10), good (n = 10), and full (n = 10) length deliveries. Methods Bowling accuracy was recorded by digitising ball position relative to the centre of a target. Performance measures were mean radial error (accuracy), variable error (consistency), centroid error (bias), bowling score and ball speed. Radial error changes across the duration of the skills test were used to record accuracy adjustment in subsequent deliveries. Results Elite fast bowlers performed better in speed, accuracy, and test scores than developing athletes. Bowlers who were less variable were also more accurate across all delivery lengths. National and emerging bowlers were able to adapt subsequent performance trials within the same bowling session for short length deliveries. Conclusions Accuracy and adaptive variability were key components of elite performance in fast bowling which improved with skill level. In this study, only national elite bowlers showed requisite levels of adaptive variability to bowl a range of lengths to different pitch locations.
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Visual inputs to artificial and biological visual systems are often quantized: cameras accumulate photons from the visual world, and the brain receives action potentials from visual sensory neurons. Collecting more information quanta leads to a longer acquisition time and better performance. In many visual tasks, collecting a small number of quanta is sufficient to solve the task well. The ability to determine the right number of quanta is pivotal in situations where visual information is costly to obtain, such as photon-starved or time-critical environments. In these situations, conventional vision systems that always collect a fixed and large amount of information are infeasible. I develop a framework that judiciously determines the number of information quanta to observe based on the cost of observation and the requirement for accuracy. The framework implements the optimal speed versus accuracy tradeoff when two assumptions are met, namely that the task is fully specified probabilistically and constant over time. I also extend the framework to address scenarios that violate the assumptions. I deploy the framework to three recognition tasks: visual search (where both assumptions are satisfied), scotopic visual recognition (where the model is not specified), and visual discrimination with unknown stimulus onset (where the model is dynamic over time). Scotopic classification experiments suggest that the framework leads to dramatic improvement in photon-efficiency compared to conventional computer vision algorithms. Human psychophysics experiments confirmed that the framework provides a parsimonious and versatile explanation for human behavior under time pressure in both static and dynamic environments.
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This study examined physiological and performance effects of pre-cooling on medium-fast bowling in the heat. Ten, medium-fast bowlers completed two randomised trials involving either cooling (mixed-methods) or control (no cooling) interventions before a 6-over bowling spell in 31.9±2.1°C and 63.5±9.3% relative humidity. Measures included bowling performance (ball speed, accuracy and run-up speeds), physical characteristics (global positioning system monitoring and counter-movement jump height), physiological (heart rate, core temperature, skin temperature and sweat loss), biochemical (serum concentrations of damage, stress and inflammation) and perceptual variables (perceived exertion and thermal sensation). Mean ball speed (114.5±7.1 vs. 114.1±7.2 km · h−1; P = 0.63; d = 0.09), accuracy (43.1±10.6 vs. 44.2±12.5 AU; P = 0.76; d = 0.14) and total run-up speed (19.1±4.1 vs. 19.3±3.8 km · h−1; P = 0.66; d = 0.06) did not differ between pre-cooling and control respectively; however 20-m sprint speed between overs was 5.9±7.3% greater at Over 4 after pre-cooling (P = 0.03; d = 0.75). Pre-cooling reduced skin temperature after the intervention period (P = 0.006; d = 2.28), core temperature and pre-over heart rates throughout (P = 0.01−0.04; d = 0.96−1.74) and sweat loss by 0.4±0.3 kg (P = 0.01; d = 0.34). Mean rating of perceived exertion and thermal sensation were lower during pre-cooling trials (P = 0.004−0.03; d = 0.77−3.13). Despite no observed improvement in bowling performance, pre-cooling maintained between-over sprint speeds and blunted physiological and perceptual demands to ease the thermoregulatory demands of medium-fast bowling in hot conditions.
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This investigation examined physiological and performance effects of cooling on recovery of medium-fast bowlers in the heat. Eight, medium-fast bowlers completed two randomised trials, involving two sessions completed on consecutive days (Session 1: 10-overs and Session 2: 4-overs) in 31 ± 3°C and 55 ± 17% relative humidity. Recovery interventions were administered for 20 min (mixed-method cooling vs. control) after Session 1. Measures included bowling performance (ball speed, accuracy, run-up speeds), physical demands (global positioning system, counter-movement jump), physiological (heart rate, core temperature, skin temperature, sweat loss), biochemical (creatine kinase, C-reactive protein) and perceptual variables (perceived exertion, thermal sensation, muscle soreness). Mean ball speed was higher after cooling in Session 2 (118.9 ± 8.1 vs. 115.5 ± 8.6 km · h−1; P = 0.001; d = 0.67), reducing declines in ball speed between sessions (0.24 vs. −3.18 km · h−1; P = 0.03; d = 1.80). Large effects indicated higher accuracy in Session 2 after cooling (46.0 ± 11.2 vs. 39.4 ± 8.6 arbitrary units [AU]; P = 0.13; d = 0.93) without affecting total run-up speed (19.0 ± 3.1 vs. 19.0 ± 2.5 km · h−1; P = 0.97; d = 0.01). Cooling reduced core temperature, skin temperature and thermal sensation throughout the intervention (P = 0.001–0.05; d = 1.31–5.78) and attenuated creatine kinase (P = 0.04; d = 0.56) and muscle soreness at 24-h (P = 0.03; d = 2.05). Accordingly, mixed-method cooling can reduce thermal strain after a 10-over spell and improve markers of muscular damage and discomfort alongside maintained medium-fast bowling performance on consecutive days in hot conditions.
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This paper presents an efficient noniterative method for distribution state estimation using conditional multivariate complex Gaussian distribution (CMCGD). In the proposed method, the mean and standard deviation (SD) of the state variables is obtained in one step considering load uncertainties, measurement errors, and load correlations. In this method, first the bus voltages, branch currents, and injection currents are represented by MCGD using direct load flow and a linear transformation. Then, the mean and SD of bus voltages, or other states, are calculated using CMCGD and estimation of variance method. The mean and SD of pseudo measurements, as well as spatial correlations between pseudo measurements, are modeled based on the historical data for different levels of load duration curve. The proposed method can handle load uncertainties without using time-consuming approaches such as Monte Carlo. Simulation results of two case studies, six-bus, and a realistic 747-bus distribution network show the effectiveness of the proposed method in terms of speed, accuracy, and quality against the conventional approach.
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In visual object detection and recognition, classifiers have two interesting characteristics: accuracy and speed. Accuracy depends on the complexity of the image features and classifier decision surfaces. Speed depends on the hardware and the computational effort required to use the features and decision surfaces. When attempts to increase accuracy lead to increases in complexity and effort, it is necessary to ask how much are we willing to pay for increased accuracy. For example, if increased computational effort implies quickly diminishing returns in accuracy, then those designing inexpensive surveillance applications cannot aim for maximum accuracy at any cost. It becomes necessary to find trade-offs between accuracy and effort. We study efficient classification of images depicting real-world objects and scenes. Classification is efficient when a classifier can be controlled so that the desired trade-off between accuracy and effort (speed) is achieved and unnecessary computations are avoided on a per input basis. A framework is proposed for understanding and modeling efficient classification of images. Classification is modeled as a tree-like process. In designing the framework, it is important to recognize what is essential and to avoid structures that are narrow in applicability. Earlier frameworks are lacking in this regard. The overall contribution is two-fold. First, the framework is presented, subjected to experiments, and shown to be satisfactory. Second, certain unconventional approaches are experimented with. This allows the separation of the essential from the conventional. To determine if the framework is satisfactory, three categories of questions are identified: trade-off optimization, classifier tree organization, and rules for delegation and confidence modeling. Questions and problems related to each category are addressed and empirical results are presented. For example, related to trade-off optimization, we address the problem of computational bottlenecks that limit the range of trade-offs. We also ask if accuracy versus effort trade-offs can be controlled after training. For another example, regarding classifier tree organization, we first consider the task of organizing a tree in a problem-specific manner. We then ask if problem-specific organization is necessary.
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Artificial Neural Networks (ANNs) have recently been proposed as an alterative method for salving certain traditional problems in power systems where conventional techniques have not achieved the desired speed, accuracy or efficiency. This paper presents application of ANN where the aim is to achieve fast voltage stability margin assessment of power network in an energy control centre (ECC), with reduced number of appropriate inputs. L-index has been used for assessing voltage stability margin. Investigations are carried out on the influence of information encompassed in input vector and target out put vector, on the learning time and test performance of multi layer perceptron (MLP) based ANN model. LP based algorithm for voltage stability improvement, is used for generating meaningful training patterns in the normal operating range of the system. From the generated set of training patterns, appropriate training patterns are selected based on statistical correlation process, sensitivity matrix approach, contingency ranking approach and concentric relaxation method. Simulation results on a 24 bus EHV system, 30 bus modified IEEE system, and a 82 bus Indian power network are presented for illustration purposes.
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This thesis investigates the design and implementation of a label-free optical biosensing system utilizing a robust on-chip integrated platform. The goal has been to transition optical micro-resonator based label-free biosensing from a laborious and delicate laboratory demonstration to a tool for the analytical life scientist. This has been pursued along four avenues: (1) the design and fabrication of high-$Q$ integrated planar microdisk optical resonators in silicon nitride on silica, (2) the demonstration of a high speed optoelectronic swept frequency laser source, (3) the development and integration of a microfluidic analyte delivery system, and (4) the introduction of a novel differential measurement technique for the reduction of environmental noise.
The optical part of this system combines the results of two major recent developments in the field of optical and laser physics: the high-$Q$ optical resonator and the phase-locked electronically controlled swept-frequency semiconductor laser. The laser operates at a wavelength relevant for aqueous sensing, and replaces expensive and fragile mechanically-tuned laser sources whose frequency sweeps have limited speed, accuracy and reliability. The high-$Q$ optical resonator is part of a monolithic unit with an integrated optical waveguide, and is fabricated using standard semiconductor lithography methods. Monolithic integration makes the system significantly more robust and flexible compared to current, fragile embodiments that rely on the precarious coupling of fragile optical fibers to resonators. The silicon nitride on silica material system allows for future manifestations at shorter wavelengths. The sensor also includes an integrated microfluidic flow cell for precise and low volume delivery of analytes to the resonator surface. We demonstrate the refractive index sensing action of the system as well as the specific and nonspecific adsorption of proteins onto the resonator surface with high sensitivity. Measurement challenges due to environmental noise that hamper system performance are discussed and a differential sensing measurement is proposed, implemented, and demonstrated resulting in the restoration of a high performance sensing measurement.
The instrument developed in this work represents an adaptable and cost-effective platform capable of various sensitive, label-free measurements relevant to the study of biophysics, biomolecular interactions, cell signaling, and a wide range of other life science fields. Further development is necessary for it to be capable of binding assays, or thermodynamic and kinetics measurements; however, this work has laid the foundation for the demonstration of these applications.