A new stability results for the backward heat equation

In this paper, we regularize the nonlinear inverse time heat problem in the unbounded region by Fourier method. Some new convergence rates are obtained. Meanwhile, some quite sharp error estimates between the approximate solution and exact solution are provided. Especially, the optimal convergence of the approximate solution at t = 0 is also proved. This work extends to many earlier results in (f2,f3, hao1,Quan,tau1, tau2, Trong3,x1).Comment: 13 page

Denoising Diffusion Medical Models

In this study, we introduce a generative model that can synthesize a large number of radiographical image/label pairs, and thus is asymptotically favorable to downstream activities such as segmentation in bio-medical image analysis. Denoising Diffusion Medical Model (DDMM), the proposed technique, can create realistic X-ray images and associated segmentations on a small number of annotated datasets as well as other massive unlabeled datasets with no supervision. Radiograph/segmentation pairs are generated jointly by the DDMM sampling process in probabilistic mode. As a result, a vanilla UNet that uses this data augmentation for segmentation task outperforms other similarly data-centric approaches.Comment: Accepted to IEEE ISBI 202

CONCEPT MAPPING INFLUENCING STUDENTS’ ABILITY TO SUMMARIZE READING PASSAGES

Concept mapping has been advocated as a facilitative tool for enhancing meaningful learning of reading comprehension of students in several ways. In particular, this strategy positively influences how students comprehend texts and summarize important ideas or information given in a particular text passage. However, research into the effects of concept mapping on students’ ability to summarize passages has not been explored in the context of teaching and learning English as a foreign language inVietnam. This paper therefore examines the effects of concept mapping on students’ ability to summarize reading passages within a community college context in the Mekong Delta. Using an experimental study, pretest, posttest, and questionnaire were undertaken with twenty six sophomores over the second semester of a reading course. The findings show that concept mapping had positive effects on students’ ability to summarize reading passages and that students perceived the use of this reading strategy as being a facilitative tool for meaningful learning. The paper concludes by discussing the pedagogical implications and insights into the relationship between concept mapping and summarizing skills in reading comprehension in wider contexts.  Article visualizations

Continually learning new languages

Multilingual speech recognition with neural networks is often implemented with batch-learning, when all of the languages are available before training. An ability to add new languages after the prior training sessions can be economically beneficial, but the main challenge is catastrophic forgetting. In this work, we combine the qualities of weight factorization, transfer learning and Elastic Weight Consolidation in order to counter catastrophic forgetting and facilitate learning new languages quickly. Such combination allowed us to eliminate catastrophic forgetting while still achieving performance for the new languages comparable with having all languages at once, in experiments of learning from an initial 10 languages to achieve 27 languagesComment: Submitted to ICCASP 202