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1.
30th European Signal Processing Conference, EUSIPCO 2022 ; 2022-August:1233-1237, 2022.
Article in English | Scopus | ID: covidwho-2102361

ABSTRACT

This paper evaluates a wide range of audio-based deep learning frameworks applied to the breathing, cough, and speech sounds for detecting COVID-19. In general, the audio recording inputs are transformed into low-level spectrogram features, then they are fed into pre-trained deep learning models to extract high-level embedding features. Next, the dimension of these high-level embedding features are reduced before fine-tuning using Light Gradient Boosting Machine (LightGBM) as a back-end classification. Our experiments on the Second DiCOVA Challenge achieved the highest Area Under the Curve (AUC), F1 score, sensitivity score, and specificity score of 89.03%, 64.41%, 63.33%, and 95.13%, respectively. Based on these scores, our method outperforms the state-of-the-art systems, and improves the challenge baseline by 4.33%, 6.00% and 8.33% in terms of AUC, F1 score and sensitivity score, respectively. © 2022 European Signal Processing Conference, EUSIPCO. All rights reserved.

2.
International Journal of Intelligent Unmanned Systems ; 2022.
Article in English | Web of Science | ID: covidwho-1997105

ABSTRACT

Purpose In the COVID-19 outbreak periods, people's life has been deranged, leading to disrupt the world. Firstly, the number of deaths is growing and has the potential to surpass the highest level at any time. Secondly, the pandemic broke many countries' fortified lines of epidemic prevention and gave people a more honest view of its seriousness. Finally, the pandemic has an impact on life, and the economy led to a shortage in medical, including a lack of clinicians, facilities and medical equipment. One of those, a simple ventilator is a necessary piece of medical equipment since it might be useful for a COVID-19 patient's treatment. In some cases, the COVID-19 patients require to be treated by modern ventilators to reduce lung damage. Therefore, the addition of simple ventilators is a necessity to relieve high work pressure on medical bureaucracies. Some low-income countries aim to build a simple ventilator for primary care and palliative care using locally accessible and low-cost components. One of the simple principles for producing airflow is to squeeze an artificial manual breathing unit (AMBU) iterative with grippers, which imitates the motion of human fingers. Unfortunately, the squeezing angle of grippers is not proportional to the exhaust air volume from the AMBU bag. This paper aims to model the AMBU bag by a mathematical equation that enables to implement on a simple controller to operate a bag-valve-mask (BVM) ventilator with high accuracy performance. Design/methodology/approach This paper provides a curvature function to estimate the air volume exhausting from the AMBU bag. Since the determination of the curvature function is sophisticated, the coefficients of the curvature function are approximated by a quadratic function through the experimental identification method. To obtain the high accuracy performance, a linear regression model and a least square method are employed to investigate the characteristic of the BVM ventilator's grippers angle with respect to the airflow volume produced by the AMBU bag. Findings This paper investigates the correlation between the exhausting airflow of the AMBU bag and the grippers angle of the BVM ventilator. Originality/value The experimental results validated that the regression model of the characteristic of the exhausting airflow of the AMBU bag with respect to the grippers' angle has been fitted with a coefficient over 98% within the range of 350-750 ml.

3.
16th International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2022 ; 497 LNNS:59-70, 2022.
Article in English | Scopus | ID: covidwho-1919721

ABSTRACT

The pain, namely “Covid-19 epidemic", has caused many sacrifices, loss, and loneliness. Only those who have experienced traumatic losses can fully understand the pain that is hard to erase by the epidemic. This study focuses on designing a remote medical assistance vehicle used in quarantine areas in Vietnam to support epidemic prevention with simple, cheap, easy-to-use, and multi-function criteria. The proposed system includes a 3-layer vehicle for transporting supplies controlled remotely via Radio Frequency (RF) signals to help limit cross-infection for medical staff and volunteers. The main component is the RF transceiver circuit, which transmits and receives data wirelessly over 2.4 GHZ RF using IC Nrf24l01, Nordic standard SPI interface for remote control. DC motor driver circuit BTS7960 43A controls the motor to prevent overvoltage and current drop. Moreover, the vehicle integrates an electric sprayer to support disinfecting spray a Xiaomi camera to stream video and communicate directly with patients and healthy in isolation. Ultrasonic sensors and infrared sensors aim to scan obstacles through reflected waves. The reflected signals received from the barrier objects are used as input to the microcontroller. The microcontroller is then used to determine the distance of objects around the vehicle. If an obstacle is detected, the disinfectant sprayer can stop for several seconds to ensure the safety of medical staff if there is a pass. The system has a built-in light sensor that works at night. The system is deployed at a low cost and is evaluated through some experiments. It is expected to be easy to use and is an innovative solution for hospitals. Once the outbreak is over, the product can still be used in infectious disease areas. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

4.
International Review of Economics and Finance ; 80:186-210, 2022.
Article in English | Scopus | ID: covidwho-1768212

ABSTRACT

This paper studies how the spillovers between investor attention and green bond performance vary across normal and extreme market conditions. Using the quantile connectedness model, we document a substantial increase in the spillovers between green bond returns and investor attention at the lower and upper tail of the distributions. These spillovers are time-varying, asymmetric, and significantly influenced by stock, oil, bond market volatility, and economic policy uncertainty. Moreover, using the time-varying robust Granger causality test, we find that the Granger-causality relationship between the attention indices and the green bond returns seems to be more pronounced after the onset of the COVID-19 pandemic. © 2022

5.
Global Journal of Environmental Science and Management ; 6(Special Issue):1-10, 2020.
Article in English | GIM | ID: covidwho-1727148

ABSTRACT

Currently, the pandemic caused by a novel coronavirus, namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the most serious issues worldwide. SARS-CoV-2 was first observed in Wuhan, China, on December 31, 2019;this disease has been rapidly spreading worldwide. Iran was the first Middle East country to report a coronavirus death, it has been severely affected. Therefore, it is crucial to forecast the pandemic spread in Iran. This study aims to develop a prediction model for the daily total confirmed cases, total confirmed new cases, total deaths, total new deaths, growth rate in confirmed cases, and growth rate in deaths. The model utilizes SARS-CoV-2 daily data, which are mainly collected from the official website of the European Centre for Disease Prevention and Control from February 20 to May 04, 2020 and other appropriated references. Autoregressive integrated moving average (ARIMA) is employed to forecast the trend of the pandemic spread. The ARIMA model predicts that Iran can easily exhibit an increase in the daily total confirmed cases and the total deaths, while the daily total confirmed new cases, total new deaths, and growth rate in confirmed cases/deaths becomes stable in the near future. This study predicts that Iran can control the SARS-CoV-2 disease in the near future. The ARIMA model can rapidly aid in forecasting patients and rendering a better preparedness plan in Iran.

6.
3rd International Conference on Intelligent Medicine and Image Processing, IMIP 2021 ; : 107-113, 2021.
Article in English | Scopus | ID: covidwho-1476847

ABSTRACT

The Covid19 pandemic has overturned all human activities, including education and training activities. The transition from traditional learning to online learning during the Covid19 pandemic has been a must for all schools. This paper aims to describe how a Vietnamese secondary school has taken appropriate steps of preparation and transformation to adapt to the pandemic period and a new normal life in the teaching and learning activities of STEAM subjects. As subjects requiring mainly direct interaction between students and teachers, the Vietnamese secondary school has had good preparation and has made rapid improvements to ensure the continuous teaching and learning STEAM subjects on an online platform. Importantly, the school has applied the digital transformation appropriately to meet learning requirements for STEAM subjects in the new normal life. © 2021 ACM.

7.
Aims Bioengineering ; 8(3):192-207, 2021.
Article in English | Web of Science | ID: covidwho-1310150

ABSTRACT

Ventilators are drawn to many researchers during the Covid-19 pandemic because it's essential equipment that's accustomed to treat severe Covid-19 patients. In low-income countries, there's a shortage of pricy respiratory devices resulting in exceeding the provision of taking care of Covid-19's patients in ICU. This paper attempts to design and implement an appropriate respiratory device referred to as a bag valve mask (BVM) ventilator for those who are Covid-19 patients in medical care, those patients have a requirement of safe transport and also palliative care. The BVM ventilator comprises a man-made manual breath unit (AMBU) bag and paddles for squeezing the AMBU bag which is popular in medical aid settings. The BVM ventilator is required to travel airflow through the system to the patient's lung with the specified volume for every breath cycle within a threshold air pressure. Since the AMBU bag is straightforward to be deformed over time, it's difficult to get mathematical modelling for constructing a reliable controller. Therefore, a model-free control (MFC) control approach is utilized successfully to style a controller for our BVM ventilator model with a PEEP valve and a HEPA filter. Some experimental scenarios are administered to gauge the effectiveness of the proposed controller for the BVM ventilator to control the airflow and control air pressure mode.

8.
Asian Pacific Journal of Tropical Medicine ; 14(5):239-240, 2021.
Article in English | EMBASE | ID: covidwho-1273567
9.
Asian Pacific Journal of Tropical Medicine ; 14(4):159-164, 2021.
Article in English | Scopus | ID: covidwho-1206390

ABSTRACT

Objective: To assess the acceptance of coronavirus disease (COVID-19) vaccine among healthcare workers at two general hospitals in Vietnam when it is available. Methods: A cross-sectional study was conducted using a convenience sampling from January to February 2021 among 410 healthcare workers at two general hospitals in Vietnam via a self-administered questionnaire. A multivariable regression analysis was performed to determine predictors of vaccine acceptance including the demographic factors, COVID-19 knowledge, and vaccine beliefs based on the domains of Health Belief Model. Results: Among 410 healthcare workers, 76.10% showed vaccination willingness. Predictors of acceptance were determined that the group reporting as 'vaccine acceptance' was more likely to be positive towards the perceived susceptibility and severity of COVID-19 (OR 2.45;95% CI 1.48-4.06, P<0.05), perceived benefits of vaccination, and cues to action (OR 4.36;95% CI 2.35-8.09, and OR 5.49;95% CI 2.84-10.61, respectively, all P<0.001), but less likely to have the perceived barriers to vaccination (OR 0.19;95% CI 0.09-0.38;P<0.001) compared with the no acceptance group. Besides, people who had a good knowledge regarding the severity of illness were 3.37 times more likely to have identified as vaccine acceptance (OR 3.37;95% CI 1.04-10.86, P<0.05). The demographic factors were also associated with willingness to receive the vaccine, with participants who were staff and received COVID-19 information from relatives were less likely to accept the vaccine over those who were doctors and not receiving information from relatives (OR 0.36;95% CI 0.13-0.96, and OR 0.37;95% CI 0.17-0.78, respectively, all P<0.05). Conclusions: A rate of willingness to get vaccinated against COVID-19 was relatively high with discrepancies between occupation, receiving information from relatives, knowledge toward the severity of illness, and the elements of Health Belief Model. The findings will provide information for the management authorities to develop relevant interventions to promote COVID-19 vaccination uptake. © 2021 Asian Pacific Journal of Tropical Medicine Produced by Wolters KluwerMedknow. All rights reserved.

10.
Journal of Asian Finance, Economics and Business ; 8(4):1067-1078, 2021.
Article in English | Scopus | ID: covidwho-1192102

ABSTRACT

This research examines the mediation of intrinsic motivation (IP) in the relationship between psychological capital (Psycap) and innovative performance (IP) in the educational environment of the transitioning economy. A test was based on a convenient sample of 440 University lecturers participating in a hardcopy survey was collected from ten universities and colleges in Southern Vietnam, from April 2020 to December 2020, while social isolation is strictly enforced by the government (Covid-19). The hypotheses are then proposed and conducted using confirmatory factor analysis (CFA) and the structural equation modeling technique (SEM). The testing structural model results reveal that all the hypotheses are satisfied at the 5% significance level. Intrinsic motivation is a partial mediator in the linkage between psychological capital and innovative performance. These findings suggest that the importance of Psychological Capital (PsyCap) of workers promotes job performance in general, especially in individuals’ creativity in a transitioning market, Vietnam. In addition, Based on the research results, several solutions are also proposed to promote innovative performance in the conditions of education in Vietnam. Besides, the author also gave a few comments on the findings as well as the limitations that this study encountered, especially how the survey samples were collected. © 2021. The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

11.
Multiple Sclerosis Journal ; 26(3 SUPPL):434, 2020.
Article in English | EMBASE | ID: covidwho-1067122

ABSTRACT

Background: Neurological examination is a powerful tool for diagnosing and measuring progression of neurodegenerative diseases. However, examinations are resource intensive and thus not practical for comprehensive measurement of neurological disability in chronic diseases. A remote digital solution may be more practical and particularly relevant now due to the ongoing COVID-19 pandemic. Objectives: To clinically validate a digital adaptation of the Symbol Digit Modalities Test (SDMT) developed as part of a smartphone test suite replicating aspects of a neurological exam. Methods: Participants consisted of healthy volunteers (HV;n=39) and multiple sclerosis (MS;n=154) patients, with a longitudinal subcohort that performed tests at home (n=15). During clinic visits, the smartphone test suite was administered alongside a full neurological exam. The smartphone SDMT featured randomization of symbol-digit code and testing sequence. The subjects also underwent written SDMT and brain MRI. Results: Performance differed significantly between HV and MS cohorts (p<.0001). Performance on smartphone and written SDMT had strong evidence of association (R2=0.71, concordance coefficient CCC=0.69, p<.0001). Smartphone SDMT had higher criterion validity than written SDMT measured by correlation with T2 lesion load and brain atrophy. Correlations with NeurEx subdomains identified neurological functions involved in performance of each of the 3 functional cognitive tests. Correcting for these contributing non-cognitive disabilities generated linear regression models strongly predicting the amount of MS-related brain injury measured by volumetric MRI (R2 = 0.75, p < 0.0001 vs R2 = 0.62, p < 0.0001). Of the longitudinal cohort, 87% of patients demonstrated practice effects measured by non-linear regression. Averaging multiple sequential post-learning results significantly decreased threshold for identifying true test deteriorations on a patient level. Conclusions: Smartphone SDMT allows for less resource intensive remote administration. The clinometric properties of smartphone SDMT compare to or outperform written SDMT. This study expands the validation of multiple neurological tests administered via smartphone and bring us closer to a patient-autonomous neurological examination.

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