Forward masking of faces by spatially quantized random and structured masks: On the roles of wholistic configuration, local features, and spatial-frequency spectra in perceptual identification

The forward masking of faces by spatially quantized masking images was studied. Masks were used in order to exert different types of degrading effects on the early representations in facial information processing. Three types of source images for masks were used: Same-face images (with regard to targets), different-face images, and random Gaussian noise that was spectrally similar to facial images. They were all spatially quantized over the same range of quantization values. Same-face masks had virtually no masking effect at any of the quantization values. Different-face masks had strong masking effects only with fine-scale quantization, but led to the same efficiency of recognition as in the same-face mask condition with the coarsest quantization. Moreover, compared with the noise-mask condition, coarsely quantized different-face masks led to a relatively facilitated level of recognition efficiency. The masking effect of the noise mask did not vary significantly with the coarseness of quantization. The results supported neither a local feature processing account, nor a generalized spatial-frequency processing account, but were consistent with the microgenetic configuration-processing theory of face recognition. Also, the suitability of a spatial quantization technique for image configuration processing research has been demonstrated.     

Evaluating methods for approximating stochastic differential equations

Models of decision making and response time (RT) are often formulated using stochastic differential equations (SDEs). Researchers often investigate these models using a simple Monte Carlo method based on Euler's method for solving ordinary differential equations. The accuracy of Euler's method is investigated and compared to the performance of more complex simulation methods. The more complex methods for solving SDEs yielded no improvement in accuracy over the Euler method. However, the matrix method proposed by Diederich and Busemeyer (2003) yielded significant improvements. The accuracy of all methods depended critically on the size of the approximating time step. The large (∼10 ms) step sizes often used by psychological researchers resulted in large and systematic errors in evaluating RT distributions.     

Aerobic Fitness Is Associated With Cognitive Control Strategy in Preadolescent Children

The authors used a conditional accuracy function (CAF) method to compute the mean accuracy of multiple reaction time ranges, to investigate the association between aerobic fitness and the utilization of cognitive control strategy during preadolescence. Thirty-eight higher- and lower-fit children were grouped according to their cardiorespiratory capacity (VO_2max) and completed a modified flanker task. Seventeen young adults were recruited as a reference group of maturation. The results showed that higher-fit children exhibited an adult-like performance pattern, and demonstrated increased overall response accuracy compared to lower-fit children, with a disproportionally larger increase in individual responses when the time allowed for discriminative processing was constrained. These findings suggest that aerobic fitness is associated with enhanced cognitive control and development of a more proactive control strategy during flanker task in preadolescent children.     

Different trends in perceptual pattern microgenesis as a function of the spatial range of local brightness averaging

Summary Stimulus patterns, quantized into small squares with the brightness level averaged within each square, were presented for recognition with various exposure durations. Qualitatively different recognition functions were obtained with varying spatial levels of quantization. The method used, if further elaborated, seems appropriate for the empirical differentiation between global and local levels of form and between integration and differentiation stages of a perceptual/attentional process.     

A fast procedure for studying conditional accuracy functions

This paper describes a procedure for obtaining conditional accuracy functions(CAFs) from naive observers and a restricted number of trials. The method permits the experimenter to counter the subjects’ tendency to favor accuracy in tasks in which stimulus discrimination is easy. Each time a block of 12 trials contains less than three errors, observers are instructed, by means of a speed-up signal, to respond faster. The subject is continuously informed about her/his effective reaction time. The data show that the desired speed-accuracy tradeoff was obtained within each of the 7 observers. The mean percent error was around 25%.     

Testing the accuracy of the retrospective recall method used in expertise research

Expertise typically develops slowly over years, and controlled experiments to study its development may be impractical. Researchers often use a correlational, retrospective recall method in which participants recall career data, sometimes over many years before. However, recall accuracy is uncertain. The present study investigated the accuracy of recalled career data for up to 38 years, in over 600 international chess players. Participants’ estimates of their entry year into international chess, total career games played, and number of games in a typical year were compared with the known true values. Entry year typically was recalled fairly accurately, and accuracy did not diminish systematically with time since list entry from 10 years earlier to 25 or more years earlier. On average, games-count estimates were reasonably accurate. However, some participants were very inaccurate, and some were more inaccurate in their total-games counts and entry-year estimates. The retrospective recall method yields usable data but may have some accuracy problems. Possible remedies are outlined.     

定长CD-CAT中两种新的题目曝光控制方法

提出了两种适用于定长CD-CAT的题目曝光控制方法（HIRP、HIRT）,这些方法在保证较高分类准确率的同时还有较合理的题目曝光率,新方法由二分化方法和RP及RT方法进行结合并适当调整而得到。模拟研究比较了其与RP、RT、SM、SMIE、RHA和SDBS的表现,结果表明: （1）HIRP的分类准确率和题目曝光率均好于SM、SMIE和SDBS;（2）HIRT的题目曝光率较RP、SM、SMIE、RHA和SDBS稍差,但分类准确率更高;（3）HIRP的分类准确率低于RT和RP,但题目曝光控制要更好。     

Rater training revisited: An updated meta‐analytic review of frame‐of‐reference training

The present study updates Woehr and Huffcutt's (1994) rater training meta‐analysis and demonstrates that frame‐of‐reference (FOR) training is an effective method of improving rating accuracy. The current meta‐analysis includes over four times as many studies as included in the Woehr and Huffcutt meta‐analysis and also provides a snapshot of current rater training studies. The present meta‐analysis also extends the previous meta‐analysis by showing that not all operationalizations of accuracy are equally improved by FOR training; Borman's differential accuracy appears to be the most improved by FOR training, along with behavioural accuracy, which provides a snapshot into the cognitive processes of the raters. We also investigate the extent to which FOR training protocols differ, the implications of protocol differences, and if the criteria of interest to FOR researchers have changed over time.     

Regularized ELM bagging model for Tropical Cyclone Tracks prediction in South China Sea

This paper aims to improve the prediction accuracy of Tropical Cyclone Tracks (TCTs) over the South China Sea (SCS) with 24 h lead time. The model proposed in this paper is a regularized extreme learning machine (ELM) ensemble using bagging. The method which turns the original problem into quadratic programming (QP) problem is proposed in this paper to solve lasso and elastic net problem in ELM. The forecast error of TCTs data set is the distance between real position and forecast position. Compared with the stepwise regression method widely used in TCTs, 8.26 km accuracy improvement is obtained by our model based on the dataset with 70/1680 testing/training records. By contrast, the improvement using this model is 16.49 km based on a smaller dataset with 30/720 testing/training records. Results show that the regularized ELM bagging has a general better generalization capacity on TCTs data set.     

ELM-HTM guided bio-inspired unsupervised learning for anomalous trajectory classification

Artificial intelligent systems often model the solutions of typical machine learning problems, inspired by biological processes, because of the biological system is faster and much adaptive than deep learning. The utility of bio-inspired learning methods lie in its ability to discover unknown patterns, and its less dependence on mathematical modeling or exhaustive training. In this paper, we propose a new bio-inspired learning model for a single-class classifier to detect abnormality in video object trajectories. The method uses a simple but dynamic extreme learning machine (ELM) and hierarchical temporal memory (HTM) together referred to as ELM-HTM in an unsupervised way to learn and classify time series patterns. The method has been tested on trajectory sequences in traffic surveillance to find abnormal behaviors such as high-speed, unusual stops, driving in wrong directions, loitering, etc. Experiments have also been performed with 3D air signatures captured using sensors and used for biometric authentication(forged/genuine). The results indicate a significant gain over training time and classification accuracy. The proposed method outperforms in predicting long-time patterns by observing small steps with an average accuracy gain of 15% as compared to the state-of-the-art HTM. The method has applications in detecting abnormal activities in videos by learning the movement patterns as well as in biometric authentication.     

结构化面试中评分量表对评分准确性的影响

采用2(组内变量:量尺大小(25分和9分))×2(组间变量:评分方法(相对和绝对))的混合实验设计探讨评分量表对115名大学生新手评委评分准确性的影响。对于评分准确性,采用Cronbach1955年提出的四个指标,Elevation(EL)、Differential elevation(DE)、Stereotype accuracy(SA)、Differential Accuracy(DA)。结果发现,评分方法只在SA上主效应显著,量尺大小在只在DA上主效应边缘显著,评分方法和量尺大小在DE、SA和DA三个指标上均有交互作用。总体上看,在结构化面试评分中,对于评分准确性,相对评分量表优于绝对评分量表,小量尺量表优于大量尺量表。     

Psychometric Modeling of response speed and accuracy with mixed and conditional regression

Human performance in cognitive testing and experimental psychology is expressed in terms of response speed and accuracy. Data analysis is often limited to either speed or accuracy, and/or to crude summary measures like mean response time (RT) or the percentage correct responses. This paper proposes the use of mixed regression for the psychometric modeling of response speed and accuracy in testing and experiments. Mixed logistic regression of response accuracy extends logistic item response theory modeling to multidimensional models with covariates and interactions. Mixed linear regression of response time extends mixed ANOVA to unbalanced designs with covariates and heterogeneity of variance. Related to mixed regression is conditional regression, which requires no normality assumption, but is limited to unidimensional models. Mixed and conditional methods are both applied to an experimental study of mental rotation. Univariate and bivariate analyzes show how within-subject correlation between response and RT can be distinguished from between-subject correlation, and how latent traits can be detected, given careful item design or content analysis. It is concluded that both response and RT must be recorded in cognitive testing, and that mixed regression is a versatile method for analyzing test data.I am grateful to Rogier Donders for putting his data at my disposal.     

The retrieval of sentences from memory: A speed-accuracy study

A speed-accuracy tradeoff method was used to study the retrieval dynamics for recognition memory of parts of sentences. All sentences contained a subject, verb, object, location, and time. Recognition accuracy increased from chance at a processing time of about 0.5 sec to asymptotic accuracy at about 3 sec. The asymptotic accuracy levels for subject-verb, subject-object or verb-object recognition probes exceeded those of pair probes containing times or locations. This result suggests that the former may be more closely associated in semantic memory. The only difference among speed-accuracy curves was in asymptotic accuracy. The chance intercept and the rate of increase in accuracy were similar for all pair probes. A second finding was that the speed-accuracy curves for triple probes (e.g., subject-verb-object) were virtually identical to those of the comparable pair probes. These results appear to contradict a serial search hypothesis for the access of information from semantic memory. They support a parallel, direct-access hypothesis.     

Speed-Accuracy Response Models: Scoring Rules based on Response Time and Accuracy

Starting from an explicit scoring rule for time limit tasks incorporating both response time and accuracy, and a definite trade-off between speed and accuracy, a response model is derived. Since the scoring rule is interpreted as a sufficient statistic, the model belongs to the exponential family. The various marginal and conditional distributions for response accuracy and response time are derived, and it is shown how the model parameters can be estimated. The model for response accuracy is found to be the two-parameter logistic model. It is found that the time limit determines the item discrimination, and this effect is illustrated with the Amsterdam Chess Test II.     

A Joint Modeling Approach for Reaction Time and Accuracy in Psycholinguistic Experiments

In the psycholinguistic literature, reaction times and accuracy can be analyzed separately using mixed (logistic) effects models with crossed random effects for item and subject. Given the potential correlation between these two outcomes, a joint model for the reaction time and accuracy may provide further insight. In this paper, a Bayesian hierarchical framework is proposed that allows estimation of the correlation between time intensity and difficulty at the item level, and between speed and ability at the subject level. The framework is shown to be flexible in that reaction times can follow a (log-) normal or (shifted) Weibull distribution. A simulation study reveals the reduction in bias gains possible when using joint models, and an analysis of an example from a Dutch–English word recognition study illustrates the proposed method.     

The influence of trend estimation method on forecasting curriculum-based measurement of reading performance

Estimating a trend line through words read correct per minute scores collected across successive weeks is a preferred method to evaluate student response to instruction with curriculum-based measurement of reading (CBM-R). This is due in part, because the slope of that line of best fit is used to predict the trajectory of student performance if the current intervention is maintained. In turn, trend lines should predict future scores with a high degree of accuracy when an intervention is maintained. We evaluated the forecasting accuracy of a trend estimation method currently used in practice (i.e., ordinary least squares), and five alternate methods recently evaluated in CBM-R simulation studies, using actual student data. Results suggest that alternate trend estimation methods predicted future performance with a similar level of accuracy as ordinary least squares trend lines across most conditions, with the exception of slopes estimated via Bayesian analysis. Bayesian trend lines estimated using informed prior distributions yielded noticeably less biased and more precise predictions when applied to short data series relative to all other estimation methods across most conditions. Outcomes from the current study highlight the need to further explore the viability of Bayesian analysis to evaluate individual time series data.     

A vocal response time system for use with sentence verification tasks

A software system for the reliable detection of vocal response onset is described. The system was designed specifically for the measurement of vocal response times to speech stimuli presented aurally in a sound field in the presence of some background noise. The response time extraction method described here is robust to masking noise and extraneous sounds that may be included in the subject’s recorded response. In addition, the response words do not have to be limited to a small set because the system is able to differentiate the onset of any speech sounds, including low-energy fricatives. The method described here may be implemented with any computer sound system because it relies only on the sound conversion clock for timing accuracy and uses postprocessing of the signal after acquisition for response extraction. The response time extraction technique as currently implemented does not recognize subject’s responses but could be incorporated into an automatic speech recognition system.     

The rolling totals method of computing sums,sums of squares,and sums of cross-products

The rolling totals method of computing sums, sums of squares, and sums of cross-products appears to have several advantages over usual methods, in that it saves time and requires less equipment. Only an IBM sorter and a tabulator equipped with Card Cycle Total Transfer Device are used. The method provides an immediate independent visual check on the accuracy of the sums of cross-products of each successive variable as it is run. Since controlling is done by sorting, the necessity for re-wiring after each run on the tabulator is eliminated. The wiring, illustrated by a diagram, is simple and straightforward.ABITIBI POWER AND PAPER COMPANY     

自适应分组认知诊断测验设计及其选题策略

应用OMST在线装配模式,提出自适应分组认知诊断测验（CD-AMGT）。由于知识状态的先决关系是偏序关系,而且构成格（lattice),利用知识状态当前估计值在格中的上下确界对被试真实知识状态的可能范围进行界定,由此装配下一分组,分组中结合PWKL策略或SHE策略进行选题以兼顾诊断精度、效率和安全性。模拟实验表明,CD-AMGT与PWKL、SHE对比,当题目类型丰富时,以分类准确率略微降低为代价,其题库使用均匀性和计算用时均表现出较大优势。