12,992 research outputs found

    Splittings and the asymptotic topology of the lamplighter group

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    It is known that splittings of finitely presented groups over 2-ended groups can be characterized geometrically. We show that this characterization does not extend to all finitely generated groups. Answering a question of Kleiner we show that the Cayley graph of the lamplighter group is coarsely separated by quasi-circles.Comment: 11 page

    Empirical lecturers’ and students’ satisfaction assessment in e-learning systems based on the usage metrics

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    Nowadays, in the pandemic of COVID-19, e-learning systems have been widely used to facilitate teaching and learning processes between lecturers and students. Assessing lecturers’ and students’ satisfaction with e-learning systems has become essential in improving the quality of education for higher learning institutions. Most existing approaches have attempted to assess users’ satisfaction based on System Usability Scale (SUS). On the other hand, different studies proposed usage-based metrics (completion rate, task duration, and mouse or cursor distance) which assess users’ satisfaction based on how they use and interact with the system. However, the cursor or mouse distance metric does not consider the effectiveness of navigation in e-learning systems, and such approaches measure either lecturers’ or students’ satisfaction independently. Towards this end, we propose a lostness metric to replace the click or cursor distance metric for assessing lecturers’ and students’ satisfaction with using e-learning systems. Furthermore, to obtain a deep analysis of users’ satisfaction, we tandem the usage-based metric (i.e., completion rate, task duration, and lostness) and the SUS metric. The evaluation results indicate that the proposed approach can precisely predict users’ satisfaction with e-learning systems

    Sensory Motor Remapping of Space in Human-Machine Interfaces

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    Studies of adaptation to patterns of deterministic forces have revealed the ability of the motor control system to form and use predictive representations of the environment. These studies have also pointed out that adaptation to novel dynamics is aimed at preserving the trajectories of a controlled endpoint, either the hand of a subject or a transported object. We review some of these experiments and present more recent studies aimed at understanding how the motor system forms representations of the physical space in which actions take place. An extensive line of investigations in visual information processing has dealt with the issue of how the Euclidean properties of space are recovered from visual signals that do not appear to possess these properties. The same question is addressed here in the context of motor behavior and motor learning by observing how people remap hand gestures and body motions that control the state of an external device. We present some theoretical considerations and experimental evidence about the ability of the nervous system to create novel patterns of coordination that are consistent with the representation of extrapersonal space. We also discuss the perspective of endowing human–machine interfaces with learning algorithms that, combined with human learning, may facilitate the control of powered wheelchairs and other assistive devices

    Distortion of wreath products in some finitely presented groups

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    Wreath products such as Z wr Z are not finitely-presentable yet can occur as subgroups of finitely presented groups. Here we compute the distortion of Z wr Z as a subgroup of Thompson's group F and as a subgroup of Baumslag's metabelian group G. We find that Z wr Z is undistorted in F but is at least exponentially distorted in G.Comment: 9 pages, 5 figure

    Incorporating Feedback from Multiple Sensory Modalities Enhances Brain–Machine Interface Control

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    The brain typically uses a rich supply of feedback from multiple sensory modalities to control movement in healthy individuals. In many individuals, these afferent pathways, as well as their efferent counterparts, are compromised by disease or injury resulting in significant impairments and reduced quality of life. Brain–machine interfaces (BMIs) offer the promise of recovered functionality to these individuals by allowing them to control a device using their thoughts. Most current BMI implementations use visual feedback for closed-loop control; however, it has been suggested that the inclusion of additional feedback modalities may lead to improvements in control. We demonstrate for the first time that kinesthetic feedback can be used together with vision to significantly improve control of a cursor driven by neural activity of the primary motor cortex (MI). Using an exoskeletal robot, the monkey\u27s arm was moved to passively follow a cortically controlled visual cursor, thereby providing the monkey with kinesthetic information about the motion of the cursor. When visual and proprioceptive feedback were congruent, both the time to successfully reach a target decreased and the cursor paths became straighter, compared with incongruent feedback conditions. This enhanced performance was accompanied by a significant increase in the amount of movement-related information contained in the spiking activity of neurons in MI. These findings suggest that BMI control can be significantly improved in paralyzed patients with residual kinesthetic sense and provide the groundwork for augmenting cortically controlled BMIs with multiple forms of natural or surrogate sensory feedback
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