Intelligent English Teaching Based on the Pedagogy of Performing Another Culture and ChatGPT Technology

In the background of digital education, the intelligent capabilities of ChatGPT-based technology in teaching have emerged as a powerful tool for facilitating teachers’ preparation for lesson, improving students’ learning motivation and effectiveness, and promoting the development of intelligent curriculum. This study put forward a novel model of ChatGPT-based English teaching grounded in the “Pedagogy of Performing Another Culture” proposed by Galal Walker. From the three aspects of teaching design, application scenarios, and learning effect evaluation, this model explores the application of ChatGPT in the four fundamental language domains of listening, speaking, reading, and writing, with the objective of enhancing students’ language proficiency and cultural sensitivity, while also fostering their digital learning capabilities. To uphold academic integrity and ethical use of ChatGPT in English teaching, a C++-based ChatGPT application has been designed and tailored to the specific needs of English language learners. The school-based intelligent courses based on ChatGPT are available for students to carry out more diverse and effective English learning, promoting the rational use of ChatGPT in learning

An approach for smooth trajectory planning of high-speed pick-and-place parallel robots using quintic B-splines

This paper presents a new, highly effective approach for optimal smooth trajectory planning of high-speed pick-and-place parallel robots. The pick-and-place path is decomposed into two orthogonal coordinate axes in the Cartesian space and quintic B-spline curves are used to generate the motion profile along each axis for achieving C4-continuity. By using symmetrical properties of the geometric path defined, the proposed motion profile becomes essentially dominated by two key factors, representing the ratios of the time intervals for the end-effector to move from the initial point to the adjacent virtual and/or the via-points on the path. These two factors can then be determined by maximizing a weighted sum of two normalized single-objective functions and expressed by curve fitting as functions of the width/height ratio of the pick-and-place path, so allowing them to be stored in a look-up table to enable real-time implementation. Experimental results on a 4-DOF SCARA type parallel robot show that the residual vibration of the end-effector can be substantially reduced thanks to the very continuous and smooth joint torques obtained

Embroidering Guanyin: Constructions of the Divine through Hair

Hair embroidery was a particular technique practiced by lay Buddhist women to create devotional images. The embroiderers used their own hair as threads and applied them on silk to stitch figures. This paper will analyze the religious connotation of hair embroidery, the ritual process and the techniques for making hair embroidery in the Ming (1368-1644) and Qing (1644-1911) dynasties. By tracing its appearance in both literary texts and actual surviving objects, this essay will ask how and in what circumstances human hair was applied to embroidery? What was the significance of transferring one’s own hair onto an icon? How did hair embroidery combine women’s bodies (their hair) with a womanly skill (embroidery) to make a unique gendered practice in late imperial China

Diffusion Models for Probabilistic Deconvolution of Galaxy Images

Telescopes capture images with a particular point spread function (PSF). Inferring what an image would have looked like with a much sharper PSF, a problem known as PSF deconvolution, is ill-posed because PSF convolution is not an invertible transformation. Deep generative models are appealing for PSF deconvolution because they can infer a posterior distribution over candidate images that, if convolved with the PSF, could have generated the observation. However, classical deep generative models such as VAEs and GANs often provide inadequate sample diversity. As an alternative, we propose a classifier-free conditional diffusion model for PSF deconvolution of galaxy images. We demonstrate that this diffusion model captures a greater diversity of possible deconvolutions compared to a conditional VAE.Comment: Accepted to the ICML 2023 Workshop on Machine Learning for Astrophysic