1,198 research outputs found
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 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
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