Collaborative Consultation Doctors Model: Unifying CNN and ViT for COVID-19 Diagnostic

The COVID-19 pandemic presents significant challenges due to its high transmissibility and mortality risk. Traditional diagnostic methods, such as RT-PCR, have limitations that hinder timely and accurate screening. In response, AI-powered computer-aided imaging analysis techniques have emerged as a promising alternative for COVID-19 diagnosis. In this paper, we propose a novel approach that combines the strengths of Convolutional Neural Network (CNN) and Vision Transformer (ViT) to enhance the performance of COVID-19 diagnosis models. CNN excels at capturing spatial features in medical images, while ViT leverages self-attention mechanisms inspired by human radiologists. Additionally, our approach draws inspiration from subclinical diagnosis, a collaborative process involving attending physicians and specialists, which has proven effective in achieving accurate and comprehensive diagnoses. To this end, we employ an early fusion strategy integrating CNN and ViT, then fed into a residual neural network. By fusing these complementary features, our approach achieves state-of-the-art performance in accurately identifying COVID-19 cases on two benchmark datasets: Chest X-ray and Clean-CC-CCII. This research has the potential to enable timely and accurate screening, aiding in the early detection and management of COVID-19 cases. Our findings contribute to the growing knowledge of AI-powered diagnostic techniques and demonstrate the potential for advanced imaging analysis methods to support medical professionals in combating the ongoing pandemic

Asian Values and Human Rights: A Vietnamese Perspective

This paper examines the impact of the ideology of ‘Asian Values' on the legal norms and practices that frame the recognition and protection of human rights in Vietnam. Specifically, the paper focusses on the extent to which Asian Values has been deployed to discourage the adoption of international human rights norms and practices in the context of Vietnam’s rapid economic development since the mid- 1980s. The paper first sketches the adoption of Asian Values in Vietnam’s politics and society. Cultural and political factors that have shaped the conception of human rights are reviewed. Human rights language and norms, as manifest in political ideologies, policies and laws are then analysed, with particular reference to the different versions of Vietnam’s Constitution. It is shown that both the Communist Party of Vietnam (CPV) and the State of Vietnam have clearly articulated Asian Values in formulating their conceptions of human rights. This outcome is argued to result from the fact that Vietnamese political leaders, alike with Lee Kwan Yew in Singapore, the progenitor of Asian Rights, have been strongly influenced by Confucian ideals of governance. Confucianism is not, however, the only basis for political ideas in Vietnam. Although Vietnam is a market economy it remains a one- party state  controlled  by  the  CPV.  The  Marxist-Leninist  principles  on  which the current State of Vietnam was based at its inception in 1975 remain intact. This ideology was however layered onto generations of collectivist principles embodied in the dominant agrarian society. The influence of Asian Values, on the recognition of and support for human rights in Vietnam has, however, been largely negative rather than positive, especially in relation to recognising civil and political rights as codified in universal human rights instruments. Thus, the protection and promotion of human rights in Vietnam, going forward, essentially mandates eliminating the influence of Asian Values in the ideology of political leaders and in the wider society. Key words: Human rights, Asian Values, democracy, constitution, Communist Party, Vietna

The role of environmental regulations and innovation in TFP convergence: Evidence from manufacturing SMEs in Viet Nam

This is a pioneer study investigating the relationship between environmental compliance and TFP convergence for SMEs. It examines the impacts of environmental compliance, and its combination with innovation, on TFP convergence of manufacturing SMEs. We applied the dynamic panel regression method to estimate stochastic TFP. We find evidence of a Ø-convergence but a σ-divergence. Impacts of environmental practices of firms - pollution abatement and control expenditure, and environmental treatment - are only significant through their interaction with innovation. The Ø-convergence in firms' TFP is influenced by their industrial identity, while firms' size and investment have marginal impact

Disturbance observer-based controller for inverted pendulum with uncertainties: Linear matrix inequality approach

A new approach based on linear matrix inequality (LMI) technique for stabilizing the inverted pendulum is developed in this article. The unknown states are estimated as well as the system is stabilized simultaneously by employing the observer-based controller. In addition, the impacts of the uncertainties are taken into consideration in this paper. Unlike the previous studies, the uncertainties in this study are unnecessary to satisfy the bounded constraints. These uncertainties will be converted into the unknown input disturbances, and then a disturbance observer-based controller will be synthesized to estimate the information of the unknown states, eliminate completely the effects of the uncertainties, and stabilize inverted pendulum system. With the support of lyapunov methodology, the conditions for constructing the observer and controller under the framework of linear matrix inequalities (LMIs) are derived in main theorems. Finally, the simulations for system with and without uncertainties are exhibited to show the merit and effectiveness of the proposed methods

Development and validation of the Vietnamese Primary Care Assessment Tool : provider version

Aim: To adapt the provider version of the Primary Care Assessment Tool (PCAT) for Vietnam and determine its internal consistency and validity. Background: There is a growing need to measure and explore the impact of various characteristics of health care systems on the quality of primary care. It would provide the best evidence for policy makers if these evaluations come from both the demand and supply sides of the health care sector. Comparatively more researchers have studied primary care quality from the consumer perspective than from the provider's perspective. This study aims at the latter. Method: Our study translated and adapted the PCAT provider version (PCAT PE) into a Vietnamese version, after which a cross-sectional survey was conducted to examine the feasibility, internal consistency and validity of the Vietnamese PCAT provider version (VN PCAT PE). All general doctors working at 152 commune health centres in Thua Thien Hue province had been selected to participate in the survey. Findings: The VN PCAT PE is an instrument for evaluation of primary care in Vietnam with 116 items comprising six scales representing four core primary care domains, and three additional scales representing three derivative domains. From the translation and cultural adaptation stage, two items were combined, two items were removed and one item was added. Six other items were excluded due to problems in item-total correlations. All items have a low non-response or 'don't know/don't remember' response rate, and there were no floor or ceiling effects. All scales had a Cronbach's alpha above 0.80, except for the Coordination scale, which still was above the minimum level of 0.70. Conclusion: The VN PCAT PE demonstrates adequate internal consistency and validity to be used as an effective tool for measuring the quality of primary care in Vietnam from the provider perspective

UIT-ADrone: A Novel Drone Dataset for Traffic Anomaly Detection

Anomaly detection plays an increasingly important role in video surveillance and is one of the issues that have attracted various communities, such as computer vision, machine learning, and data mining in recent years. Moreover, drones equipped with cameras have quickly been deployed to a wide range of applications, starting from border security applications to street monitoring systems. However, there is a notable lack of adequate drone-based datasets available to detect unusual events in the urban traffic environment, especially in roundabouts, due to the density of interaction between road users and vehicles. To promote the development of anomalous event detection with drones in the complex traffic environment, we construct a novel large-scale drone dataset to detect anomalies involving realistic roundabouts in Vietnam, covering a large variety of anomalous events. Traffic at a total of three different roundabouts in Ho Chi Minh City was recorded with a camera-equipped drone. The resulting dataset contains 51 videos with total data traffic of nearly 6.5 h, captured across 206K frames with ten abnormal event types. Based on this dataset, we comprehensively evaluate the current state-of-the-art algorithms and what anomaly detection can do in drone-based video surveillance. This study presents a detailed description of the proposed UIT-ADrone dataset, along with information regarding data distribution, protocols for evaluation, baseline experimental results on our dataset, and other benchmark datasets, discussions, and paves the way for future work