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}

The Organizational Culture Strategy SMEs During Economic Crises

The importance of organizational culture in the operation and performance of businesses has been widely acknowledged, but there is inconsistency in findings about the impact of culture on organizational performance across studies. This study aimed to achieve two objectives: first, to establish the relationship between the quality of accounting information systems (AIS), organizational culture, and the financial performance of small and medium enterprises (SMEs) in Vietnam; and second, to survey the organizational culture strategy of Vietnamese SMEs in the context of economic crises. The study survey was conducted in May 2023 and involved 242 SMEs in Vietnam. The research model was tested using Smart PLS. The results suggest that AIS has a positive relationship with both organizational culture and the financial performance of SMEs. However, organizational culture only affects financial performance related to organizational adaptability during a crisis. Moreover, a flexible, external adaptation, and balanced cultural approach strategy has a significant impact on the financial performance of SMEs. During a crisis, managers expect employees to adapt in order to achieve strategic goals and plans while simultaneously balancing stability, engagement, and employee satisfaction to achieve organizational effectiveness. Doi: 10.28991/ESJ-2023-07-06-015 Full Text: PD

Approximation of mild solutions of the linear and nonlinear elliptic equations

In this paper, we investigate the Cauchy problem for both linear and semi-linear elliptic equations. In general, the equations have the form $$\frac{\partial^{2}}{\partial t^{2}}u\left(t\right)=\mathcal{A}u\left(t\right)+f\left(t,u\left(t\right)\right),\quad t\in\left[0,T\right],$$ where $\mathcal{A}$ is a positive-definite, self-adjoint operator with compact inverse. As we know, these problems are well-known to be ill-posed. On account of the orthonormal eigenbasis and the corresponding eigenvalues related to the operator, the method of separation of variables is used to show the solution in series representation. Thereby, we propose a modified method and show error estimations in many accepted cases. For illustration, two numerical examples, a modified Helmholtz equation and an elliptic sine-Gordon equation, are constructed to demonstrate the feasibility and efficiency of the proposed method.Comment: 29 pages, 16 figures, July 201

Application of monte carlo simulation method to estimate the reliability of design problem of the bored pile according to limited state

This paper applies Monte Carlo simulation method to estimate the reliability of bored pile for designing problem at “Tax Office of Phu Nhuan District”. Surveyed random variables are physico-mechanical properties of soil and loads are assumed that they follow the normal distribution. Limit state functions developed from design requirements of Ultimate limit state (ULS) and Serviceability limit state (SLS). Results show that the probability of failure is 0 and the reliability index of ULS is 9.493 and of SLS is 37.076 when examining coefficient of variation of soil and loads of 10%. The paper also considers the safety level when evaluating different coefficients of variation in the range of 10 ~30%. The authors suggest applying the reliability method to design calculation for other construction to help the engineers have a visual perspective, increase safety and avoid wastage

Maritime Data Mining for Marine Safety Based on Deep Learning: Southern Vietnam Case Study

High-speed passenger vessels, integrated river and sea vessels, container vessels, oil tankers, and other underwater vehicles operating in maritime traffic are among the types of vessels that must be equipped with AIS and VHF. The safety of navigation is one of the major problems in the maritime sector, particularly in Vietnam. Furthermore, marine traffic in the seaport zone is a common and difficult issue to manage in areas with a high volume of vessel traffic, mostly in places where the infrastructure supporting navigation is inadequately developed to meet the rapidly growing demands of the contemporary world. Therefore, it is necessary to create an integrated maritime management system to improve the efficiency of data exploitation and support maritime safety. To address this challenge, this study suggests a Maritime Traffic State Prediction (MTSP) model to predict traffic conditions in the channels where real-time data collection is insufficient in some specific locations. We recommend a deep learning method using Long Short-Term Memory (LSTM) networks to predict the safe path of the vessel in case of missing data segments. The findings have shown that the proposed approach encourages the mining of historical vessel data for maritime traffic, is ready to be applied, and can easily be implemented in a computer program or a web-based app