Oscillate Boiling from Electrical Microheaters

Oscillate boiling offers excellent heat transfer at temperatures above the Leidenfrost temperature. Here we realize an electrical microheater with an integrated thermal probe and resolve the thermal cycle during the high-frequency bubble oscillations. Thermal rates of $10^8\,$K/s were found indicating its applicability for compact and rapid heat transfer from micro electrical devices

Textual Manifold-based Defense Against Natural Language Adversarial Examples

Recent studies on adversarial images have shown that they tend to leave the underlying low-dimensional data manifold, making them significantly more challenging for current models to make correct predictions. This so-called off-manifold conjecture has inspired a novel line of defenses against adversarial attacks on images. In this study, we find a similar phenomenon occurs in the contextualized embedding space induced by pretrained language models, in which adversarial texts tend to have their embeddings diverge from the manifold of natural ones. Based on this finding, we propose Textual Manifold-based Defense (TMD), a defense mechanism that projects text embeddings onto an approximated embedding manifold before classification. It reduces the complexity of potential adversarial examples, which ultimately enhances the robustness of the protected model. Through extensive experiments, our method consistently and significantly outperforms previous defenses under various attack settings without trading off clean accuracy. To the best of our knowledge, this is the first NLP defense that leverages the manifold structure against adversarial attacks. Our code is available at \url{https://github.com/dangne/tmd}

Simultaneous Micro-EDM and Micro-ECM in Low-resistivity Deionized Water

Ph.DDOCTOR OF PHILOSOPH

Combination of Domain Knowledge and Deep Learning for Sentiment Analysis of Short and Informal Messages on Social Media

Sentiment analysis has been emerging recently as one of the major natural language processing (NLP) tasks in many applications. Especially, as social media channels (e.g. social networks or forums) have become significant sources for brands to observe user opinions about their products, this task is thus increasingly crucial. However, when applied with real data obtained from social media, we notice that there is a high volume of short and informal messages posted by users on those channels. This kind of data makes the existing works suffer from many difficulties to handle, especially ones using deep learning approaches. In this paper, we propose an approach to handle this problem. This work is extended from our previous work, in which we proposed to combine the typical deep learning technique of Convolutional Neural Networks with domain knowledge. The combination is used for acquiring additional training data augmentation and a more reasonable loss function. In this work, we further improve our architecture by various substantial enhancements, including negation-based data augmentation, transfer learning for word embeddings, the combination of word-level embeddings and character-level embeddings, and using multitask learning technique for attaching domain knowledge rules in the learning process. Those enhancements, specifically aiming to handle short and informal messages, help us to enjoy significant improvement in performance once experimenting on real datasets.Comment: A Preprint of an article accepted for publication by Inderscience in IJCVR on September 201

THE STATUS OF STUDENTS’ POSITIVE QUALITIES IN TABLE TENNIS 1 COURSE AT SAIGON UNIVERSITY, VIETNAM

The purpose of the article is to construct a scale to evaluate the positivity of students in the course Table Tennis 1 at Saigon University, Vietnam. Using common methods in the field of physical education (analysis and synthesis of documents, interviews, statistics). Through reference documents, references and interviews with experts, specialists and lecturers, the article has identified 32 criteria for evaluating the positivity of students in the course Table Tennis 1 at Saigon University. The results of applying 32 evaluation criteria show that the situation of students’ positivity in the course Table Tennis 1 at Saigon University is good in terms of awareness of learning table tennis and the need for positive learning table tennis; average in terms of motivation for positive learning table tennis and positive behavior when learning table tennis; about expressing interest when learning table tennis at a good level according to students and average according to lecturers.  Article visualizations