Swing positions. The various illustrations show the golf swing sequence: set-up position (P1), club parallel to ground (P2), left arm parallel to ground (P3), top of the backswing (P4), left arm parallel to ground (P5), club shaft parallel to ground (P6), impact (P7), club shaft parallel to ground on through swing (P8), right arm parallel to ground on through swing (P9) and finish position (P10).
Context in source publication
... et al.  focus their analysis on the wrist movement while performing a swing. The authors describe an autonomous kinematic analysis platform, using the Microsoft Kinect camera system 1 , for wrist angle measurement that is capa- ble of evaluating a user's uncocking swing motion (i.e. downswing, see Fig. 2) and providing instructional feedback. According to the authors, the graphical user interface (GUI) provides five types of intuitive feedback: (1) verbal and (2) textual instructions for improving the user's uncocking motion based on the feedback comments and scores defined in a special module embedded in the platform (the generation ...
... However, utilizing these techniques in a real-time learning environment without historical traces of new students raise some issues like the cold-start problem [2,3]. In [2,4] authors present a hybrid technique using the ontological domain representation for adaptive learning to avoid these disadvantages. However, it is also based on the student's historical parameters such as schooling, learning, and proficiency level. ...
... The expression (4) shows that the performance of the student depends on receiving rewards of the recommended task which is further used to motivate as well as increase the learning proficiency. Therefore, (4) shows that a student can get progress only if he gives the correct answer to the difficult task rather than his previous estimated competency level. ...
Traditional intelligent systems recommend a teaching sequence to individual students without monitoring their ongoing learning attitude. It causes frustrations for students to learn a new skill and move them away from their target learning goal. As a step to make the best teaching strategy, in this paper a Personalized Skill-Based Math Recommender (PSBMR) framework has been proposed to automatically recommend pedagogical instructions based on a student's learning progress over time. The PSBMR utilizes an adversarial bandit in contrast to the classic multi-armed bandit (MAB) problem to estimate the student's ability and recommend the task as per his skill level. However, this paper proposes an online learning approach to model a student concept learning profile and used the Exp3 algorithm for optimal task selection. To verify the framework, simulated students with different behavioral complexity have been modeled using the Q-matrix approach based on item response theory. The simulation study demonstrates the effectiveness of this framework to act fairly with different groups of students to acquire the necessary skills to learn basic mathematics.
Industry 4.0 (or 4th industrial revolution) facilitates horizontal and vertical digital information flow along value chains up to the end-customer and is highly relevant in a broad variety of industries. Augmented reality (AR) is a key technology in Industry 4.0, which connects the virtual and real-world environments using such digital information flows. In doing so, the technology relies upon the systems that includes hardware and software components. Particularly, optics and photonics are of much importance in the display and processing of information in these systems. However, a particular challenge is that the AR-based systems have not been adopted in the industry as much as other technologies even after several decades of their existence. Based on review of academic literature, an industrial survey and experiments conducted in the industry, this article aims to identify success factors and challenges of AR systems and metrics of photonic components that can form the basis of an AR* framework for photonics-based system design for future research.
This article reports a study aiming to determine the perceptions of older adults needing formal care about the usefulness, satisfaction, and ease of use of CaMeLi, a virtual companion based on an embodied conversational agent, and the perceptions of formal caregivers about the potential of virtual companions to support care provision. An observational study involving older adults needing formal care was conducted to assess CaMeLi using a multi-method approach (i.e., an auto-reported questionnaire—the Usefulness, Satisfaction, and Ease of use questionnaire; a scale for the usability assessment based on the opinion of observers—the International Classification of Functioning Disability and Health-based Usability Scale; and critical incident registration). Moreover, a focus group was conducted to collect data regarding the perceived utility of virtual companions to support care provision. The observational study was conducted with 46 participants with an average age of 63.6 years, and the results were associated with a high level of usefulness, satisfaction, and ease of use of CaMeLi. Furthermore, the focus group composed of four care providers considered virtual companions a promising solution to support care provision and to prevent loneliness and social isolation. The results of both the observational study and the focus group revealed good perceptions regarding the role of virtual companions to support the care provision for older adults.
This in practice paper describes the experience of seven lecturers in a hybrid and flipped version of an introductory mathematics course for higher education. In a Mexican university, lecturers adapted to this innovation supported by an adjusted Massive Open Online Course. The experience revealed the relevance of leaving conventional assessment processes to make way for an understanding of lecturers as a collaborative team, trying to transform their own perspective about the learning of mathematics. This experience is an example of the reconceptualisation of the teaching of STEM education that contributes towards a non-formal educational context, promoting lecturers’ education and dialogic transformative learning.