Has the U.S.-Vietnam Bilateral Trade Agreement Led to Higher FDI into Vietnam?

In December 2001, a Bilateral Trade Agreement (BTA) came into effect that normalized economic relations between the United States and Vietnam. The resulting surge in trade surpassed most expectations. The impact of the BTA on FDI, however, has been less visible, especially with regard to U.S. FDI into Vietnam. This paper uses new data that accounts for FDI by U.S. subsidiaries resident in third counties to show that U.S. firms have been much more aggressive investors in Vietnam than normally reported in typical bilateral FDI data using Balance of Payments definitions of capital flows. While the U.S. is widely reported as the 11th largest investor into Vietnam, the new data shows that U.S.-related FDI exceeded all other countries in 2004. Although a formal model is not developed, descriptive data supports strongly the conclusion that the BTA has had a major impact on FDI into Vietnam, especially with regard to FDI from U.S. multinationals.FDI; Trade Agreement

Innovation and Export of Vietnam’s SME Sector

Innovation has long been considered an important factor for creating and maintaining the competitiveness of nations and firms. The relationship between innovation and exporting has been investigated for many countries. However, there is a paucity of research in Vietnam with respect to this issue. In this paper we examine whether innovation performed by Vietnam’s small and medium enterprises (SMEs) enhances their exporting likelihood. Using the recently released Vietnam Small and Medium Enterprise Survey 2005, we find that innovation as measured directly by ‘new products’, ‘new production process’ and ‘improvement of existing products’ are important determinants of exports by Vietnamese SMEs.Vietnam; Export; Innovation; Small and Medium Enterprise

Simultaneous state and input estimation with application to a two-link robotic system

This paper addresses the problem of estimating simultaneously the state and input of a nonlinear system with application to a two link robotic manipulator - the Pendubot. The system nonlinearity comprises a Lipschitz function with respect to the state, and a nonlinear term which is a function of both the state and input. It is shown that under some conditions, an observer can be designed to estimate simultaneously the system&rsquo;s state and input. Simulation and experimental results, obtained around the inverted equilibrium position, are presented to demonstrate the validity of the approach.<br /

Dataset Diffusion: Diffusion-based Synthetic Dataset Generation for Pixel-Level Semantic Segmentation

Preparing training data for deep vision models is a labor-intensive task. To address this, generative models have emerged as an effective solution for generating synthetic data. While current generative models produce image-level category labels, we propose a novel method for generating pixel-level semantic segmentation labels using the text-to-image generative model Stable Diffusion (SD). By utilizing the text prompts, cross-attention, and self-attention of SD, we introduce three new techniques: class-prompt appending, class-prompt cross-attention, and self-attention exponentiation. These techniques enable us to generate segmentation maps corresponding to synthetic images. These maps serve as pseudo-labels for training semantic segmenters, eliminating the need for labor-intensive pixel-wise annotation. To account for the imperfections in our pseudo-labels, we incorporate uncertainty regions into the segmentation, allowing us to disregard loss from those regions. We conduct evaluations on two datasets, PASCAL VOC and MSCOCO, and our approach significantly outperforms concurrent work. Our benchmarks and code will be released at https://github.com/VinAIResearch/Dataset-DiffusionComment: Accepted to NeurIPS 2023. Our project page: https://dataset-diffusion.github.io

An approximate method for analysing non-linear systems subject to random excitation

A solution technique based on the representation of the response of the non-linear system by a polynomial of the response of the linearized system is presented. The relation between the original non-linear system and the linearized system is introduced by considering the so-called extended moment equations and their closed set is to be solved to determine unknowns. For the Vanderpol oscillator subject to white noise excitation, the technique gives good approximation to the response moments as well as the probability density function