Across 3 experiments, we examined the interplay of part-list cuing and forgetting, employing 3 different methods to induce episodic forgetting-list--method directed forgetting, context-dependent forgetting, and proactive interference. For each form of forgetting, participants were asked at test to recall the target items of a previously studied list in the presence or the absence of the list's ...

Abstract The control strategy of electric vehicles mainly depends on the power battery state-of-charge estimation. One most important issues is lithium-ion (SOC) Compare with extended Kalman filter algorithm, this paper proposed a novel adaptive square root together Thevenin equivalent circuit model which can solve problem filtering divergence caused by computer rounding errors. It uses Sage-Hu...

Measuring the effectiveness of advertising is a central research interest of both academic and industry researchers (Leckenby and Plununer 1983; Ostlund 1978; Stewart, Furse, and Kozak 1983). When effectiveness is measured in terms of leaming and memory, recall and recognition are common dependent variables (Stewart et al. 1985). We report the second in a series of experiments on recognition as...

Forgetting is a useful tool for tailoring ontologies by reducing the number of concepts and roles, while preserving sound and complete reasoning. Some attempts have been made to address the problem of forgetting in some relatively simple description logics (DLs) such as DL-Lite and extended EL . Ontologies in those works are mostly expressed as TBoxes rather than general knowledge bases (KBs). ...

Episodic forgetting can arise in a number of different situations. Recall of target material can be impaired if additional material is learned (interference), related information is repeatedly retrieved (retrieval-induced forgetting), or an instruction to intentionally forget the target material is provided (directed forgetting). The question arises which mechanisms underlie these different for...

In this paper, a recursive Gauss-Newton (RGN) algorithm is first developed for adaptive tracking of the amplitude, frequency and phase of a real sinusoid signal in additive white noise. The derived algorithm is then simplified for computational complexity reduction as well as improved with the use of multiple forgetting factor (MFF) technique to provide a flexible way of keeping track of the pa...

Variable selection for regression is a classical statistical problem, motivated by concerns that too many covariates invite overfitting. Existing approaches notably include a class of convex optimisation techniques, such as the Lasso algorithm. Such techniques are invariably reliant on assumptions that are unrealistic in streaming contexts, namely that the data is available off-line and the cor...

A gaze-contingent short-term memory paradigm was used to obtain forgetting functions for realistic objects in scenes. Experiment 1 had observers freely view nine-item scenes. After observers' gaze left a predetermined target, they could fixate from 1-7 intervening nontargets before the scene was replaced by a spatial probe at the target location. The task was then to select the target from four...

A demand for predictive models for on-line estimation of variables is increasing in industry. As industrial processes are timevarying, on-line learning algorithms should be adaptive to capture process changes. On-line ensemble methods have been shown to provide better generalization performance than single models in changing environments. However, most on-line ensembles do not include and exclu...

In this paper, we propose an alternative notion, called weak forgetting, of forgetting a set of predicates in a first-order theory. One important feature of this new notion is that the result of weak forgetting is always first-order expressible. In contrast, this is not the case for the traditional notion of forgetting, called strong forgetting, introduced by Lin and Reiter. As a consequence, t...