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At least 127 records · Page 7

Solving the optimal attention allocation problem in manual control

Within the context of the optimal control model of human response, analytic expressions for the gradients of closed-loop performance metrics with respect to human operator attention allocation are derived. These derivatives serve as the basis for a gradient algorithm that determines the optimal attention that a human should allocate among several display indicators in a steady-state manual control task. Application of the human modeling techniques are made to study the hover control task for a CH-46 VTOL flight tested by NASA.

Kleinman, D. L.↗

Linear modelling of attentional resource allocation

Eight subjects time-shared performance of two compensatory tracking tasks under conditions when both were of constant difficulty, and when the control order of one task (designated primary) was varied over time within a trial. On line performance feedback was presented on half of the trials. The data are interpreted in terms of a linear model of the operator's attention allocation system, and suggest that this allocation is strongly suboptimal. Furthermore, the limitations in reallocating attentional resources between tasks, in response to difficulty fluctuations were not reduced by augmented performance feedback. Some characteristics of the allocation system are described, and reasons for its limitations suggested.

Pierce, B.↗

The Interaction of Focused Attention with Flow-field Sensitivity

Two studies were performed to determine whether a subject's response to naturalistic optical flow specifying egomotion would be affected by a concurrent attention task. In the first study subjects stood in a moving room in which various areas of the optical flow generated by room movement were visible. Subjects responded to room motion with strong compensatory sway when the entire room was visible. When the side walls of the room were completely obscured by stationary screens, leaving only the front wall visible, sway was significantly reduced, though it remained greater than in an eyes-closed control. In Exp. 2 subjects were presented with either the full room (large sway response) or the room with only the front wall visible (moderate response), each in combination with either a hard or easy verbal addition task. Preliminary results show that swaying in the fully visible room and in the room with only the front wall visible increased when combined with either the hard or easy tasks. These preliminary results suggest that at the least the pick-up of optical flow specifying egomotion is not affected by concurrent attentional activity.

Stoffregen, T.↗

Processing deficits in monitoring analog and digital displays: Implications for attentional theory and mental-state estimation research

Subjects performed short term memory tasks, involving both spatial and verbal components, and a visual monitoring task involving either analog or digital display formats. These two tasks (memory vs. monitoring) were performed both singly and in conjunction. Contrary to expectations derived from multiple resource theories of attentional processes, there was no evidence that when the two tasks involved the same cognitive codes (i.e., either both spatial or both verbal/linguistics) there was more of a dual task performance decrement than when the two tasks employed different cognitive codes/processes. These results are discussed in terms of their implications for theories of attentional processes and also for research in mental state estimation.

Payne, David G.↗

Attention in aviation

The relevance of four principles or mechanisms of human attention to the design of aviation systems and the performance of pilots in multitask environments, including workload prediction and measurement, control-display integration, and the use of voice and head-up displays is discussed. The principles are: the mental energy that supplies task performance (resources), the resulting cross-talk between tasks as they are made more similar (confusion), the combination of different task elements (integration), and the way in which one task is processed and another is ignored (selection or tunneling). The introduction of greater levels of complexity into the validation of attentional theories in order to approach the demands of the cockpit or ATC console is proposed.

Wickens, Christopher D.↗

A dynamic model of stress and sustained attention

Arguments are presented that an integrated view of stress and performance must consider the task demanding a sustained attention as a primary source of cognitive stress. A dynamic model is developed on the basis of the concept of adaptability in both physiological and psychological terms, that addresses the effects of stress on vigilance and, potentially, a wide variety of attention-demanding performance tasks. The model provides an insight into the failure of an operator under the driving influences of stress and opens a number of potential avenues through which solutions to the complex challenge of stress and performance might be posed.

Hancock, P. A.↗

The role of spatial attention in visual word processing

Subjects made lexical decisions on a target letter string presented above or below fixation. In Experiments 1 and 2, target location was cued 100 ms in advance of target onset. Responses were faster on validly than on invalidly cued trials. In Experiment 3, the target was sometimes accompanied by irrelevant stimuli on the other side of fixation; in such cases, responses were slowed (a spatial filtering effect). Both cuing and filtering effects on response time were additive with effects of word frequency and lexical status (words vs. nonwords). These findings are difficult to reconcile with claims that spatial attention is less involved in processing familiar words than in unfamiliar words and nonwords. The results can be reconciled with a late-selection locus of spatial attention only with difficulty, but are easily explained by early-selection models.

Mccann, Robert S.↗

Attention focusing and anomaly detection in systems monitoring

Any attempt to introduce automation into the monitoring of complex physical systems must start from a robust anomaly detection capability. This task is far from straightforward, for a single definition of what constitutes an anomaly is difficult to come by. In addition, to make the monitoring process efficient, and to avoid the potential for information overload on human operators, attention focusing must also be addressed. When an anomaly occurs, more often than not several sensors are affected, and the partially redundant information they provide can be confusing, particularly in a crisis situation where a response is needed quickly. The focus of this paper is a new technique for attention focusing. The technique involves reasoning about the distance between two frequency distributions, and is used to detect both anomalous system parameters and 'broken' causal dependencies. These two forms of information together isolate the locus of anomalous behavior in the system being monitored.

Doyle, Richard J.↗

The Stimulus Movement Effect: Allocation of Attention or Artifact?

In previous reports, including one by the author, learning has been shown to benefit by having discriminanda move rather than remain stationary. This stimulus movement effect might be attributed to several theoretical mechanisms, including attention, topological memory, and exposure duration. The series of experiments reported in this article was designed to Contrast these potential explanatory factors. Ten rhesus monkeys (Macaca mulatta) were tested on a variety of computerized tasks in which the stimuli remained stationary, flashed, or moved at systematically varied speeds. Performance was significantly best when the sample stimulus moved quickly and was poorest when the stimulus remained stationary. Further analysis of these data and other previously published data revealed that the distribution of the stimulus movement effect across trials supported an attention allocation interpretation.

Washburn, David A.↗

Attentional Capture by Superimposed Symbology: Boundary Conditions

We report new results from an ongoing set of experiments in which subjects view a computer-generated display consisting of a set of stationary symbols (e.g., a "HUD") superimposed on a dynamic view of a runway as it appears to the pilot during final approach. Previous work (McCann, Foyle, & Johnston, 1993) has shown that when subjects process a cueing stimulus and then identify a geometric target, performance is slower when the cue appears on the HUD and the target appears on the runway surface, compared to a control condition where the cue and target are both on the runway surface. This "shift cost" was taken as evidence that the HUD captures attention, which then has to be shifted to the "out-the-world" scene before the target can be identified. New experiments show that the shift cost is eliminated when the cue occupies a known, fixed location on the HUD. Implications for the conditions that produce attentional tunneling are discussed.

McCann, Robert S.↗

Does Involuntary Attentional Capture Curtail Stimulus Processing

Under certain conditions uninformative visual cues at non-target locations increase target RTs. The typical explanation is that visual attention has been involuntarily summoned to the cued location and is unavailable when needed at the target location. Here we present evidence that capture has not just oriented attention away from the target location, but has lead to the processing of stimuli at the location of the uninformative cue.

Remington, Roger W.↗

Performance Benefits with Scene-Linked HUD Symbology: An Attentional Phenomenon?

Previous research has shown that in a simulated flight task, navigating a path defined by ground markers while maintaining a target altitude is more accurate when an altitude indicator appears in a virtual "scenelinked" format (projected symbology moving as if it were part of the out-the-window environment) compared to the fixed-location, superimposed format found on present-day HUDs (Foyle, McCann & Shelden, 1995). One explanation of the scene-linked performance advantage is that attention can be divided between scene-linked symbology and the outside world more efficiently than between standard (fixed-position) HUD symbology and the outside world. The present study tested two alternative explanations by manipulating the location of the scene-linked HUD symbology relative to the ground path markers. Scene-linked symbology yielded better ground path-following performance than standard fixed-location superimposed symbology regardless of whether the scene-linked symbology appeared directly along the ground path or at various distances off the path. The results support the explanation that the performance benefits found with scene-linked symbology are attentional.

Levy, Jonathan L.↗

The Attentional Blink Does Not Prevent Character Identification

The standard RSVP Attentional Blink (AB) paradigm was modified so that RT to the second target could be measured. Character distortion, intended to prolong the letter-identification processing stage, had a marked effect at long lags (baseline condition), but virtually no effect at short lags where AB interference occurred. According to locus-of-slack logic, this pattern of results indicates that the attentional blink causes a processing bottleneck at some stage subsequent to letter identification.

Ruthruff, Eric↗

Sustained attention performance during sleep deprivation: evidence of state instability

Nathaniel Kleitman was the first to observe that sleep deprivation in humans did not eliminate the ability to perform neurobehavioral functions, but it did make it difficult to maintain stable performance for more than a few minutes. To investigate variability in performance as a function of sleep deprivation, n = 13 subjects were tested every 2 hours on a 10-minute, sustained-attention, psychomotor vigilance task (PVT) throughout 88 hours of total sleep deprivation (TSD condition), and compared to a control group of n = 15 subjects who were permitted a 2-hour nap every 12 hours (NAP condition) throughout the 88-hour period. PVT reaction time means and standard deviations increased markedly among subjects and within each individual subject in the TSD condition relative to the NAP condition. TSD subjects also had increasingly greater performance variability as a function of time on task after 18 hours of wakefulness. During sleep deprivation, variability in PVT performance reflected a combination of normal timely responses, errors of omission (i.e., lapses), and errors of commission (i.e., responding when no stimulus was present). Errors of omission and errors of commission were highly intercorrelated across deprivation in the TSD condition (r = 0.85, p = 0.0001), suggesting that performance instability is more likely to include compensatory effort than a lack of motivation. The marked increases in PVT performance variability as sleep loss continued supports the "state instability" hypothesis, which posits that performance during sleep deprivation is increasingly variable due to the influence of sleep initiating mechanisms on the endogenous capacity to maintain attention and alertness, thereby creating an unstable state that fluctuates within seconds and that cannot be characterized as either fully awake or asleep.

Non-NASA Center↗

Dynamic Filtering Improves Attentional State Prediction with fNIRS

Brain activity can predict a person's level of engagement in an attentional task. However, estimates of brain activity are often confounded by measurement artifacts and systemic physiological noise. The optimal method for filtering this noise - thereby increasing such state prediction accuracy - remains unclear. To investigate this, we asked study participants to perform an attentional task while we monitored their brain activity with functional near infrared spectroscopy (fNIRS). We observed higher state prediction accuracy when noise in the fNIRS hemoglobin [Hb] signals was filtered with a non-stationary (adaptive) model as compared to static regression (84% +/- 6% versus 72% +/- 15%).

Harrivel, Angela R.↗

A Dynamic Hierarchical Attention Framework for Multimodal Malware Detection

The increasing use of Android in the worldwide mobile ecosystem has come along with a significant increase in advanced malware, highlighting the critical necessity for efficient, scalable, and adaptable detection systems. Despite recent advancements in machine learning improving malware detection, the majority of current solutions are limited to one, two, or three data modalities, hence neglecting the comprehensive behavioral spectrum of contemporary multi-vector threats. This thesis presents the first comprehensive multimodal framework for Android malware detection, which combines textual, time-series (temporal), graph-based (structural), and visual information using an innovative hierarchical attention mechanism and Dynamic Fusion Controller (DFC). Our methodology consistently classifies and processes modalities as either sequential or structural, facilitating content-adaptive weighting and resilient cross-modal representation learning. We advance the implementation of cutting-edge time series techniques, such as MiniRocket, for malware detection, hence creating new opportunities for temporal analysis in cybersecurity. Comprehensive experimental assessment shows that our framework performs exceptionally well, with 99.46% classification accuracy and 97.15% detection accuracy, significantly outperforming existing approaches through effective multimodal integration and hierarchical attention mechanisms.

Nazmin, Tamanna↗

Generative design of de novo proteins based on secondary-structure constraints using an attention-based diffusion model

We report two generative deep-learning models that predict amino acid sequences and 3D protein structures on the basis of secondary-structure design objectives via either the overall content or the per-residue structure. Both models are robust regarding imperfect inputs and offer de novo design capacity because they can discover new protein sequences not yet discovered from natural mechanisms or systems. The residue-level secondary-structure design model generally yields higher accuracy and more diverse sequences. These findings suggest unexplored opportunities for protein designs and functional outcomes within the vast amino acid sequences beyond known proteins. Our models, based on an attention-based diffusion model and trained on a dataset extracted from experimentally known 3D protein structures, offer numerous downstream applications in the conditional generative design of various biological or engineering systems. Future work could include additional conditioning and an exploration of other functional properties of the generated proteins for various properties beyond structural objectives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An attention-based neural ordinary differential equation framework for modeling inelastic processes

To preserve strictly conservative behavior as well as model the variety of dissipative behavior displayed by solid materials, we propose a significant enhancement to the internal state variable-neural ordinary differential equation (ISV-NODE) framework. In this data-driven, physics-constrained modeling framework internal states are inferred rather than prescribed. The ISV-NODE consists of: (a) a stress model dependent on observable deformation and inferred internal state, and (b) a model of the evolution of the internal states. The enhancements to ISV-NODE proposed in this work are multifold: (a) a partially input convex neural network stress potential provides polyconvexity in terms of observed strain while leaving the inferred state unconstrained, and (b) an internal state flow model uses common latent features to inform novel attention-based gating and drives the flow of internal state only in dissipative regimes. We demonstrated that this architecture can accurately model dissipative and conservative behavior across an isotropic, isothermal elastic-viscoelastic-elastoplastic spectrum with three exemplars, while maintaining fundamental principles by design.

97 MATHEMATICS AND COMPUTING↗