Neural Correlates of Familiar and Unfamiliar Action in Infancy

Behavioral evidence shows that experience with an action shapes action perception. Neural mirroring has been suggested as a mechanism underlying this behavioral phenomenon. Suppression of EEG power in the mu frequency band, an index of motor activation, typically reflects neural mirroring. However, contradictory findings exist regarding the association between mu suppression and motor familiarity in infant EEG studies. In this study, we investigated the neural underpinnings reflecting the role of familiarity on action perception. We measured neural processing of familiar (grasp) and novel (tool-use) actions in 9-and-12-month-old infants. Specifically, we measured infants’ distinct motor/visual activity and explored functional connectivity associated with these processes. Mu suppression was stronger for grasping than tool-use, while significant mu and occipital alpha (indexing visual activity) suppression were evident for both actions. Interestingly, selective visual-motor functional connectivity was found during observation of familiar action, a pattern not observed for novel action. Thus, the neural correlates of perception of familiar actions may be best understood in terms of a functional neural network, rather than isolated regional activity.Our findings provide novel insights on analytic approaches for identifying motor-specific neural activity while also considering neural networks involved in observing motorically familiar versus actions.

The Effect of Education on Information Systems Success

Research into the relationship between education and information systems (IS) success (use, satisfaction, and impact) has produced mixed results. Such results seem counterintuitive, given the many benefits that education brings to the workplace. However, workplace research from Human Resources (HR) has similarly found that education has little direct effect on job performance. Instead, education has indirect effects on job performance through job expertise, which is what drives behavior and job performance. The present research integrated the Delone & McLean IS Success Model with the Job Performance Model, and found similar results: in a survey of 465 professionals working in business analytics (BA), user education level had no direct effect on IS success (BA tool use, satisfaction, and impact). Instead, education level had a positive effect on expertise with the BA tool, which in turn positively affected BA tool use. These results build upon those from HR, and suggest that education has an indirect effect on IS success, rather than a direct effect.

Implementasi Sistem Informasi Manajemen Laboratorium Kebidanan Pada Fakultas Ilmu Kesehatan Universitas Ibrahimy

The Faculty of Health Sciences (FIK) is one of the faculty under the Situbondo Ibrahimy University that develops education in health sector, which in its implementation of the learning process do a lot of practicum both in the laboratory or in the classroom. One of the laboratories is midwifery laboratory. Midwifery laboratory of FIK serves the lending of tools, rooms and packages to students and lecturers, both to be used for the learning process, or to the needs of research and community service. The lending transaction process, with many packages containing a variety of tools, requires an effective and efficient recording data system. The purpose of this research is to help the staffs of midwifery laboratory to serve all the processes of lending, returning, procuring and repairing equipment. This information system provides information about student activity in practicing and using tools in the midwifery laboratory, as well as the availability of tools with student ratios so that they can become decision support for faculty leaders in the procurement and monitoring of tool use in the laboratory.

Rapidly Learning Generalizable and Robot-Agnostic Tool-Use Skills for a Wide Range of Tasks

Many real-world applications require robots to use tools. However, robots lack the skills necessary to learn and perform many essential tool-use tasks. To this end, we present the TRansferrIng Skilled Tool Use Acquired Rapidly (TRI-STAR) framework for task-general robot tool use. TRI-STAR has three primary components: 1) the ability to learn and apply tool-use skills to a wide variety of tasks from a minimal number of training demonstrations, 2) the ability to generalize learned skills to other tools and manipulated objects, and 3) the ability to transfer learned skills to other robots. These capabilities are enabled by TRI-STAR’s task-oriented approach, which identifies and leverages structural task knowledge through the use of our goal-based task taxonomy. We demonstrate this framework with seven tasks that impose distinct requirements on the usages of the tools, six of which were each performed on three physical robots with varying kinematic configurations. Our results demonstrate that TRI-STAR can learn effective tool-use skills from only 20 training demonstrations. In addition, our framework generalizes tool-use skills to morphologically distinct objects and transfers them to new platforms, with minor performance degradation.