CHIEv

Researchers and practitioners in the fields of testing, security assessment and web development seeking to evaluate a given web application often have to rely on the existence of a model of the respective system, which is then used as input to task-specific tools. Such models may include information on HTTP endpoints and their parameters, available user actions/event listeners and required assets. Unfortunately, this data is often unavailable in practice, as only rigorous development practices or manual analysis guarantee their existence and correctness. Crawlers based on static analysis have traditionally been used to extract required information from existing sites. Regrettably, these tools can not accurately account for the dynamic behavior introduced by technologies such as JavaScript that are prevalent on modern sites. While methods based on dynamic analysis exist, they are often not fully capable of identifying event listeners and their effects. In an earlier work, we presented XIEv, an approach for dynamic analysis of web applications that produces an execution trace usable for the extraction of navigation graphs, identification of bugs at runtime and enumeration of resources. It offers improved recognition and selection of event listeners as well as a greater range of observed effects compared to existing approaches. While the evaluation of our research prototype implementation confirmed the capabilities of XIEv, it was generally out-performed by static crawlers in terms of speed. This work introduces CHIEv, an approach that augments XIEv by enabling concurrent processing as well as incorporating the results of a static crawler in real-time. Our results indicate a significant increase in performance, particularly when applied to larger sites.

What affects the magnitude of age-related dual-task costs in working memory? The role of stimulus domain and access to semantic representations

Although there is evidence that the effect of including a concurrent processing demand on the storage of information in working memory is disproportionately larger for older than younger adults, not all studies show this age-related impairment, and the critical factors responsible for any such impairment remain elusive. Here we assess whether domain overlap between storage and processing activities, and access to semantic representations, are important determinants of performance in a sample of younger and older adults ( N = 119). We developed four versions of a processing task by manipulating the type of stimuli involved (either verbal or non-verbal) and the decision that participants had to make about the stimuli presented on the screen. Participants either had to perform a spatial judgement, in deciding whether the verbal or non-verbal item was presented above or below the centre of the screen, or a semantic judgement, in deciding whether the stimulus refers to something living or not living. The memory task was serial-ordered recall of visually presented letters. The study revealed a large increase in age-related memory differences when concurrent processing was required. These differences were smaller when storage and processing activities both used verbal materials. Dual-task effects on processing were also disproportionate for older adults. Age differences in processing performance appeared larger for tasks requiring spatial decisions rather than semantic decisions. We discuss these findings in relation to three competing frameworks of working memory and the extant literature on cognitive ageing.

The Time-Based Resource-Sharing Model of Working Memory

The time-based resource-sharing model considers working memory as the workspace in which mental representations are built, maintained, and transformed for completing goal-oriented tasks. Its main component is made of an episodic buffer and a procedural system that form an executive loop in which processing and storage share domain-general attentional resources on a temporal basis. Because working memory representations decay with time when attention is diverted, the cognitive load of a given activity is the proportion of time during which it occupies attention and prevents it from counteracting this decay through attentional refreshing. Consequently, recall in working memory tasks is an inverse function of the cognitive load of concurrent processing. Besides this system, an independent domain-specific maintenance system exists for verbal, but not visuospatial, information. Within this framework, working memory development mainly results from increasing processing speed that affects both the duration of the distraction of attention by concurrent tasks and refreshing efficiency.

Concurrent Ternary Galois-based Computation using Nano-apex Multiplexing Nibs of Regular Three-dimensional Networks, Part I: Basics

New implementations within concurrent processing using three-dimensional lattice networks via nano carbon-based field emission controlled-switching is introduced in this article. The introduced nano-based three-dimensional networks utilize recent findings in nano-apex field emission to implement the concurrent functionality of lattice networks. The concurrent implementation of ternary Galois functions using nano threedimensional lattice networks is performed by using carbon field-emission switching devices via nano-apex carbon fibers and nanotubes. The presented work in this part of the article presents important basic background and fundamentals with regards to lattice computing and carbon field-emission that will be utilized within the follow-up works in the second and third parts of the article. The introduced nano-based three-dimensional lattice implementations form new and important directions within three-dimensional design in nanotechnologies that require optimal specifications of high regularity, predictable timing, high testability, fault localization, self-repair, minimum size, and minimum power consumption.

Parallel programming of saccades in the macaque frontal eye field: are sequential motor plans coactivated?

We use sequences of saccadic eye movements to continually explore our visual environments. Previous behavioral studies have established that saccades in a sequence may be programmed in parallel by the oculomotor system. In this study, we tested the neural correlates of parallel programming of saccade sequences in the frontal eye field (FEF), using single-unit electrophysiological recordings from macaques performing a sequential saccade task. It is known that FEF visual neurons instantiate target selection whereas FEF movement neurons undertake saccade preparation, where the activity corresponding to a saccade vector gradually ramps up. The question of whether FEF movement neurons are involved in concurrent processing of saccade plans is as yet unresolved. In the present study, we show that, when a peripheral target is foveated after a sequence of two saccades, presaccadic activity of FEF movement neurons for the second saccade can be activated while the first is still underway. Moreover, the onset of movement activity varied parametrically with the behaviorally measured time available for parallel programming. Although at central fixation coactivated FEF movement activity may vectorially encode the retinotopic location of the second target with respect to the fixation point or the remapped location of the second target, with respect to the first our evidence suggests the possibility of early encoding of the remapped second saccade vector. Taken together, the results indicate that movement neurons, although located terminally in the FEF visual-motor spectrum, can accomplish concurrent processing of multiple saccade plans, leading to rapid execution of saccade sequences. NEW & NOTEWORTHY The execution of purposeful sequences underlies much of goal-directed behavior. How different brain areas accomplish sequencing is poorly understood. Using a modified double-step task to generate a rapid sequence of two saccades, we demonstrate that downstream movement neurons in the frontal eye field (FEF), a prefrontal oculomotor area, allow for coactivation of the first and second movement plans that constitute the sequence. These results provide fundamental insights into the neural control of action sequencing.