Working memory updating (WMU) has been identified as a cognitive function of prime importance for everyday tasks and has also been found to be a significant predictor of higher mental abilities. Yet, little is known about the constituent processes of WMU. We suggest that operations required in a typical WMU task can be decomposed into 3 major component processes: retrieval, transformation, and ...

Previous research on the relation between working memory capacity (WMC) and shooting behavior suggests that individuals with low working memory spans are more prone to shooting errors than are individuals with high working memory spans. The present study investigated how WMC interacts with the proportion of “shoot” to “don’t shoot” decisions to affect overall shooting performance. Participants ...

The influence of spatially distinct host subpopulations on helminth community structure and pattern was examined in a migratory avian host species. Forty helminth species represented by 24,082 individuals were collected from 184 blue-winged teal (Anas discors; BWT) from 2 primary migratory corridors in Florida (eastern migratory corridor; EMC) and Louisiana and Texas (western migratory corridor...

In recent years, there has been considerable progress on fast randomized algorithms that approximate probabilistic inference with tight tolerance and confidence guarantees. The idea here is to formulate inference as a counting task over an annotated propositional theory, called weighted model counting (WMC), which can be partitioned into smaller tasks using universal hashing. An inherent limita...

In the last three lectures we have been discussing the online learning algorithms where we receive the instance x and then its label y for t = 1, ..., T . Specifically in the last lecture we talked about online learning from experts and online prediction. We saw many algorithms like Halving algorithm, Weighted Majority (WM) algorithm and lastly Weighted Majority Continuous (WMC) algorithm. We a...

In order to address the gaps in study of short-term urban road congestion prediction based on Baidu map real-time condition data, a model for Pearson Correlation Coefficient (PCC) and Weighted Markov Chains (WMC) is constructed by combining historical temporal correlation data with spatial between sections. The use PCC method filter out spatially significantly related sections from upstream dow...

In recent years, there has been considerable progress on fast randomized algorithms that approximate probabilistic inference with tight tolerance and confidence guarantees. The idea here is to formulate inference as a counting task over an annotated propositional theory, called weighted model counting (WMC), which can be partitioned into smaller tasks using universal hashing. An inherent limita...

The aim of the present study was to investigate the moderated mediation model of the relationship between the behavioral inhibition system (BIS), need for closure (NFC) and working memory capacity (WMC) in the decision making process. It was assumed that NFC works as a motivational mechanism that enables individuals high in BIS to deal with uncertainty; therefore, NFC mediates the effect of BIS...

Complex span tasks are predictive of many aspects of behavior, in both experimental and applied areas of cognitive psychology. Our view is that these tasks measure primarily working memory capacity (WMC), which we argue is the ability to control attention. The development of the Attention Network Test (ANT) provided the opportunity to study the relationship between WMC and specific types of att...

The speed-accuracy trade-off (SAT) procedure was used to investigate the relationship between working memory capacity (WMC) and the dynamics of temporal order memory retrieval. High- and low-span participants (HSs, LSs) studied sequentially presented five-item lists, followed by two probes from the study list. Participants indicated the more recent probe. Overall, accuracy was higher for HSs co...