Brief information on the doctoral thesis Governing function of the Socialist Republic of Viet Nam

The study systematically reviewed research related to the research topic, illustrated problems that have been studied and identified new, arising issues of the economic management function of the state in Vietnam that need to be researched and addressed now and in the future

Economic management function of the state of the socialist Republic of Vietnam

Mankind history has recorded the birth, development, survival struggle, and decline of various forms of states. Along with that process, the role and function of the State in socio-economic development have been strongly highlighted, represented not only social classes but also the characteristics of institutions, structures, and organizations of society in each period, and in accordance with the development of human cognition. The state in a socialist-oriented market economy has similar connotations and differences in comparison with states in general. However, due to the lack of clear definitions to distinguish the two concepts of "economic function" and "economic management function," the design, implementation, monitoring, and evaluation of the effectiveness of state management policies are ineffective, as right now there exist many fuzzy and overlapping gaps in theory. Not only that, the gap between the designed policy and the actualization of policy decisions is quite far from reality. Therefore, from the time the policies are established and issued until those policies take effects, there are many issues worth discussing

Knowledge Creation And Green Entrepreneurship: A Study Of Two Vietnamese Green Firms

This paper aims to advance the understanding and practice of knowledge-based management in Vietnam by studying two Vietnamese agricultural companies. It provides illustrative examples of how knowledge-based management, pursuing a vision that fosters creativity and innovation by employees, could ultimately fulfil the profitability objective of the business and at the same time add value to the community’s quality of life. Using the SECI model as the parameter for analysis, we found that knowledge creation processes were affected by a combination of leadership, teamwork and Ba, corporate culture, and human resource management. Our conclusion emphasises the need for future research to further examine the practice of knowledge-based management in cross-industry segments in Vietnam and in other countries with similar conditions

Exotic States Emerged By Spin-Orbit Coupling, Lattice Modulation and Magnetic Field in Lieb Nano-ribbons

The Lieb nano-ribons with the spin-orbit coupling, the lattice modulation and the magnetic field are exactly studied. They are constructed from the Lieb lattice with two open boundaries in a direction. The interplay between the spin-orbit coupling, the lattice modulation and the magnetic field emerges various exotic ground states. With certain conditions of the spin-orbit coupling, the lattice modulation, the magnetic field and filling the ground state becomes half metallic or half topological. In the half metallic ground state, one spin component is metallic, while the other spin component is insulating. In the half topological ground state, one spin component is topological, while the other spin component is topological trivial. The model exhibits very rich phase diagram

Enhance Incomplete Utterance Restoration by Joint Learning Token Extraction and Text Generation

This paper introduces a model for incomplete utterance restoration (IUR). Different from prior studies that only work on extraction or abstraction datasets, we design a simple but effective model, working for both scenarios of IUR. Our design simulates the nature of IUR, where omitted tokens from the context contribute to restoration. From this, we construct a Picker that identifies the omitted tokens. To support the picker, we design two label creation methods (soft and hard labels), which can work in cases of no annotation of the omitted tokens. The restoration is done by using a Generator with the help of the Picker on joint learning. Promising results on four benchmark datasets in extraction and abstraction scenarios show that our model is better than the pretrained T5 and non-generative language model methods in both rich and limited training data settings. The code will be also available.Comment: This is the early version of the paper accepted by NAACL 2022. It includes 10 pages, 2 figure

HYBRID END-TO-END APPROACH INTEGRATING ONLINE LEARNING WITH FACE-IDENTIFICATION SYSTEM

To date, facial recognition has been one of the most intriguing, interesting research topics over years. It requires some specific face-based algorithms such as facial detection, facial alignment, facial representation, and facial recognition as well; however, all of these algorithms derive from heavy deep learning architectures that cause limitations for development, scalability, flawed accuracy, and deployment into publicity with mere CPU servers. It also calls for large datasets containing hundreds of thousands of records for training purposes. In this paper, we propose a full pipeline for an effective face recognition application which only uses a small Vietnamese celebrity dataset and CPU for training that can solve the leakage of data and the need for GPU devices. It is based on a face vector-to-string tokens algorithm then saves face’s properties into Elasticsearch for future retrieval, so the problem of online learning in Facial Recognition is also tackled. Comparison with another popular algorithm on the dataset, our proposed pipeline not only outweighs the accuracy counterpart, but it also achieves a very speedy time inference for a real-time face recognition application