Management of university-level training programs according to the AUN-QA approach: theoretical basis, management content, and influencing factors

The issue of education quality in general and university training program management, in particular, is one of the major concerns of current education systems in the world and in Vietnam. Many studies have shown a dialectical relationship between education quality and training program management. The university training program is to train human resources with high skills, thinking abilities, and creative abilities. In training activities, it is necessary to innovate contents, programs, teaching, and learning methods, build a list of training occupations, and a system of assurance and accreditation of college training quality, towards integration with the university educational community of countries in the region and the world. The identification and clarification of the theoretical basis of training program management according to the AUN-QA approach are even more urgent when many Vietnamese universities are conducting training quality accreditation under this system. Along with that, it is necessary to clarify the management contents and impact factors of the management process of university-level training programs according to the AUN-QA approach. Qualitative analyzes were used as one of the main tools of this study. However, in some important contents, some important issues need to be clarified, this study will conduct some surveys to create more objectivity and accuracy in the conclusions

Management of university-level training programs according to the AUN-QA approach: theoretical basis, management content, and influencing factors

The issue of education quality in general and university training program management, in particular, is one of the major concerns of current education systems in the world and in Vietnam. Many studies have shown a dialectical relationship between education quality and training program management. The university training program is to train human resources with high skills, thinking abilities, and creative abilities. In training activities, it is necessary to innovate contents, programs, teaching, and learning methods, build a list of training occupations, and a system of assurance and accreditation of college training quality, towards integration with the university educational community of countries in the region and the world. The identification and clarification of the theoretical basis of training program management according to the AUN-QA approach are even more urgent when many Vietnamese universities are conducting training quality accreditation under this system. Along with that, it is necessary to clarify the management contents and impact factors of the management process of university-level training programs according to the AUN-QA approach. Qualitative analyzes were used as one of the main tools of this study. However, in some important contents, some important issues need to be clarified, this study will conduct some surveys to create more objectivity and accuracy in the conclusions

Advanced control strategy of back-to-back PWM converters in PMSG wind power system

This paper proposes a control scheme of back-to-back PWM converters for the permanent magnet synchronous generator (PMSG) wind turbine system. The DC-link voltage can be controlled at the machine-side converter (MSC), while the grid-side converter (GSC) controls the grid active power for a maximum power point tracking (MPPT). At the grid fault condition, the DC-link voltage controller is designed using a feedback linearization (FL) theory. For the MPPT, a proportional control loop is added to the torque control to reduce the influence of the inertia moment in the wind turbines, which can improve its dynamic performance. The validity of this control algorithm has been verified by the simulation of the 2-MW PMSG wind turbine system

Patient satisfaction with health care services at a National Institute of Ophthalmology

Little is known about how patients in developing countries, such as Vietnam, are satisfied with eye care services. The purpose of this study was to assess the satisfaction with health services and its associated factors among patients attending a national institute of ophthalmology in Vietnam. In a cross-sectional study utilizing quantitative methods, 500 inpatients and their relatives attending a national institute of ophthalmology in Vietnam were approached for data collection. The results indicated that under 50% of the patients were satisfied with eye care services. However, when classified by level of satisfaction, only 6.8% were very satisfied with all domains of care. There was no significant difference in satisfaction by gender and income, while significant differences by department, residence, and education were found. Patients who were from rural areas, were better educated, and used the services of the glaucoma department, were more satisfied with eye care than those from urban areas, were less educated, and used the services of treatment-on-demand department. Multivariable regression detected 2 main factors, gender and location, associated with patient satisfaction. Patients who were female and came from rural and remote areas were more likely to be satisfied than patients who were male and living in urban areas. The study suggests that to continue to improve health care quality, it is important to eliminate differences in providing eye care services regardless of whether patients are male or female, and whether they come from a rural or urban area. Copyright © 2017 John Wiley & Sons, Ltd

A low-cost system for monitoring pH, dissolved oxygen and algal density in continuous culture of microalgae

In a continuous and closed system of culturing microalgae, constantly monitoring and controlling pH, dissolved oxygen (DO) and microalgal density in the cultivation environment are paramount, which ultimately influence on the growth rate and quality of the microalgae products. Apart from the pH and DO parameters, the density of microalgae can be used to contemplate what light condition in the culture chamber is or when nutrients should be supplemented, which both also decide productivity of the cultivation. Moreover, the microalgal density is considered as an indicator indicating when the microalgae can be harvested. Therefore, this work proposes a low-cost monitoring equipment that can be employed to observe pH, DO and microalgal density over time in a culture environment. The measurements obtained by the proposed monitoring device can be utilized for not only real-time observations but also controlling other sub-systems in a continuous culture model including stirring, ventilating, nutrient supplying and harvesting, which leads to more efficiency in the microalgal production. More importantly, it is proposed to utilize the off-the-shelf materials to fabricate the equipment with a total cost of about 513 EUR, which makes it practical as well as widespread. The proposed monitoring apparatus was validated in a real-world closed system of cultivating a microalgae strain of Chlorella vulgaris. The obtained results indicate that the measurement accuracies are 0.3%, 3.8% and 8.6% for pH, DO and microalgae density quantities, respectively. © 2022 The Author(s

A systematic review of effort-reward imbalance among health workers

The purpose of this article is to systematically collate effort-reward imbalance (ERI) rates among health workers internationally and to assess gender differences. The effort-reward (ER) ratio ranges quite widely from 0.47 up to 1.32 and the ERI rate from 3.5% to 80.7%. Many studies suggested that health workers contribute more than they are rewarded, especially in Japan, Vietnam, Greece, and Germany—with ERI rates of 57.1%, 32.3%, 80.7%, and 22.8% to 27.6%, respectively. Institutions can utilize systems such as the new appraisal and reward system, which is based on performance rather than the traditional system, seniority, which creates a more competitive working climate and generates insecurity. Additionally, an increased workload and short stay patients are realities for workers in a health care environment, while the structure of human resources for health care remains inadequate. Gender differences within the ER ratio can be explained by the continued impact of traditional gender roles on attitudes and motivations that place more pressure to succeed for men rather than for women. This systematic review provides some valued evidence for public health strategies to improve the ER balance among health workers in general as well as between genders in particular. An innovative approach for managing human resources for health care is necessary to motivate and value contributions made by health workers. Copyright © 2018 John Wiley & Sons, Ltd

3D Transformer based on deformable patch location for differential diagnosis between Alzheimer's disease and Frontotemporal dementia

Alzheimer's disease and Frontotemporal dementia are common types of neurodegenerative disorders that present overlapping clinical symptoms, making their differential diagnosis very challenging. Numerous efforts have been done for the diagnosis of each disease but the problem of multi-class differential diagnosis has not been actively explored. In recent years, transformer-based models have demonstrated remarkable success in various computer vision tasks. However, their use in disease diagnostic is uncommon due to the limited amount of 3D medical data given the large size of such models. In this paper, we present a novel 3D transformer-based architecture using a deformable patch location module to improve the differential diagnosis of Alzheimer's disease and Frontotemporal dementia. Moreover, to overcome the problem of data scarcity, we propose an efficient combination of various data augmentation techniques, adapted for training transformer-based models on 3D structural magnetic resonance imaging data. Finally, we propose to combine our transformer-based model with a traditional machine learning model using brain structure volumes to better exploit the available data. Our experiments demonstrate the effectiveness of the proposed approach, showing competitive results compared to state-of-the-art methods. Moreover, the deformable patch locations can be visualized, revealing the most relevant brain regions used to establish the diagnosis of each disease

Deep Grading based on Collective Artificial Intelligence for AD Diagnosis and Prognosis

Accurate diagnosis and prognosis of Alzheimer's disease are crucial to develop new therapies and reduce the associated costs. Recently, with the advances of convolutional neural networks, methods have been proposed to automate these two tasks using structural MRI. However, these methods often suffer from lack of interpretability, generalization, and can be limited in terms of performance. In this paper, we propose a novel deep framework designed to overcome these limitations. Our framework consists of two stages. In the first stage, we propose a deep grading model to extract meaningful features. To enhance the robustness of these features against domain shift, we introduce an innovative collective artificial intelligence strategy for training and evaluating steps. In the second stage, we use a graph convolutional neural network to better capture AD signatures. Our experiments based on 2074 subjects show the competitive performance of our deep framework compared to state-of-the-art methods on different datasets for both AD diagnosis and prognosis.Comment: arXiv admin note: substantial text overlap with arXiv:2206.0324

Brain Structure Ages -- A new biomarker for multi-disease classification

Age is an important variable to describe the expected brain's anatomy status across the normal aging trajectory. The deviation from that normative aging trajectory may provide some insights into neurological diseases. In neuroimaging, predicted brain age is widely used to analyze different diseases. However, using only the brain age gap information (\ie the difference between the chronological age and the estimated age) can be not enough informative for disease classification problems. In this paper, we propose to extend the notion of global brain age by estimating brain structure ages using structural magnetic resonance imaging. To this end, an ensemble of deep learning models is first used to estimate a 3D aging map (\ie voxel-wise age estimation). Then, a 3D segmentation mask is used to obtain the final brain structure ages. This biomarker can be used in several situations. First, it enables to accurately estimate the brain age for the purpose of anomaly detection at the population level. In this situation, our approach outperforms several state-of-the-art methods. Second, brain structure ages can be used to compute the deviation from the normal aging process of each brain structure. This feature can be used in a multi-disease classification task for an accurate differential diagnosis at the subject level. Finally, the brain structure age deviations of individuals can be visualized, providing some insights about brain abnormality and helping clinicians in real medical contexts