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1.
Journal of Investigative Medicine ; 69(1):245, 2021.
Article in English | EMBASE | ID: covidwho-2316417
2.
BMJ Mil Health ; 2023 May 12.
Article in English | MEDLINE | ID: covidwho-2320267

ABSTRACT

INTRODUCTION: Identifying barriers to care in veteran populations is critical, as veterans face increased social isolation, relationship strains and financial insecurities. For Canadian veterans experiencing barriers to accessing healthcare, telehealth may be a promising alternative with comparable effectiveness to in-person services; however, the potential benefits and limitations of telehealth require further examination to determine its long-term utility, and to inform health policy and planning. The goal of the present research was to identify predictors and barriers to telehealth usage in Canadian veterans in the context of the COVID-19 pandemic. METHODS: Data were drawn from baseline data of a longitudinal survey examining the psychological functioning of Canadian veterans during the COVID-19 pandemic. Participants were 1144 Canadian veterans aged 18-93 years (Mage=56.24, SD=12.92; 77.4% men). We assessed reported telehealth use (ie, for mental healthcare, physical healthcare), healthcare access (ie, difficulty accessing care, avoidance of care) and mental health and stress since the beginning of the COVID-19 pandemic, sociodemographic variables and open-ended responses about telehealth experiences. RESULTS: Findings suggest that sociodemographic factors and previous telehealth use were significantly associated with telehealth use during the COVID-19 pandemic. Qualitative evidence highlighted both the benefits (eg, reducing barriers of access) and drawbacks (eg, not all services can be delivered) of telehealth services. CONCLUSIONS: This paper provided a deeper understanding of Canadian veterans' experiences with accessing telehealth care during the COVID-19 pandemic. While for some, the use of telehealth mitigated perceived barriers (eg, safety concerns of leaving home), others felt that not all health services could be appropriately carried out through telehealth. Altogether, findings support the use of telehealth services in increasing care accessibility for Canadian veterans. Continued use of quality telehealth services may be a valuable form of care that extends the reach of healthcare professionals.

3.
4th International Workshop on Artificial Intelligence and Education, WAIE 2022 ; : 76-80, 2022.
Article in English | Scopus | ID: covidwho-2268134
5.
International Journal of Emerging Markets ; 2023.
Article in English | Scopus | ID: covidwho-2268131
6.
Sustainability (Switzerland) ; 15(1), 2023.
Article in English | Scopus | ID: covidwho-2246404
7.
Sustainability (Switzerland) ; 15(1), 2023.
Article in English | Scopus | ID: covidwho-2245376
8.
Intelligent Information and Database Systems, Aciids 2022, Pt Ii ; 13758:395-407, 2022.
Article in English | Web of Science | ID: covidwho-2244208
9.
Cogent Business & Management ; 10(1), 2023.
Article in English | Web of Science | ID: covidwho-2243760
10.
Health Policy and Technology ; 12(1), 2023.
Article in English | EMBASE | ID: covidwho-2242537
11.
13.
2022 RIVF International Conference on Computing and Communication Technologies, RIVF 2022 ; : 268-273, 2022.
Article in English | Scopus | ID: covidwho-2236689

ABSTRACT

One-stage object detection methods have proven their advantage in terms of both speed and accuracy for addressing vision tasks in real-time scenarios, including Recyclable Waste detection, which has become a prevalent topic during the COVID-19 pandemic. Previous research into this subject has faced many obstacles, mainly due to the requirement of detecting highly deformable and often translucent objects in cluttered scenes without the context information usually present in human-centric datasets. In this paper, we aim to explore the performance of state-of-the-art one-stage object detectors on ZeroWaste dataset, the first in-the-wild industrial-grade waste detection benchmark. Our experiments showed that recent one-stage detectors, namely the YOLO-based detectors, can obtain very competitive results on the benchmark. YOLOv7, thanks to its many improvements, is the current best performer at 33.2% mAP on the ZeroWaste benchmark, to the best of our knowledge. Implementation details are available at our GitHub repository. © 2022 IEEE.

14.
9th NAFOSTED Conference on Information and Computer Science, NICS 2022 ; : 328-332, 2022.
Article in English | Scopus | ID: covidwho-2236241

ABSTRACT

With the present Coronavirus disease (COVID-19) pandemic, Internet of Things (IoT)-based health monitoring devices are precious to COVID-19 patients. We present a real-time IoT-based health monitoring system that monitors patients' heart rate and oxygen saturation, the most significant measures necessary for critical care. Specifically, the proposed IoT-based system is built with Arduino Uno-based hardware and a web application for retrieving the patients' health information. In addition, we implement the Autoregressive Integrated Moving Average (ARIMA) method in the back-end server to predict future patient measurements based on current and past measurements. Compared to commercially available devices, the system's results are adequately accurate, with an acceptable RMSE for predicted value. © 2022 IEEE.

15.
2022 International Conference on Advanced Computing and Analytics, ACOMPA 2022 ; : 34-39, 2022.
Article in English | Scopus | ID: covidwho-2233767

ABSTRACT

Ho Chi Minh City, particularly Vietnamese cities in general, is so busy and crowded since tremendous numbers of motorbikes move on roads. Ho Chi Minh City leaders have encountered several challenges in fully understanding and effectively dealing with problems of urban traffic for the past few decades. Software-based solutions are proper and dramatically necessary, currently. This paper presents the deployment of an AI-based application at the Ho Chi Minh City Department of Transportation. The paper mainly concentrates on traffic counting problems during the outbreak of the Covid-19 pandemic from June 2021. The performance of the AI-based application was compared with medical declaration data and achieved an accuracy of 93.80%. © 2022 IEEE.

16.
International Review of Financial Analysis ; 86, 2023.
Article in English | Scopus | ID: covidwho-2233685

ABSTRACT

This study investigates the implications of the COVID-19 pandemic for sovereign debt in the G-7 and E-7 economies and explores the notion of sovereign bonds as a safe haven. Using a set of panel regression and dynamic connectedness TVP-VAR approaches, our results reveal that the impact of COVID-19 global case numbers on sovereign bonds has been contingent on the level of the country's financial and economic development. More precisely, our findings suggest that G-7 countries, where economic development is typically higher, have seen a negative effect of the COVID-19 pandemic on sovereign bond yield: sovereign 10-year bond yields declined as the number of COVID-19 global confirmed cases increased in G-7 countries. However, in E-7 countries, where economic growth and development are typically lower, sovereign bond yields responded positively to the initial increase in COVID-19 global confirmed case numbers, but this positive effect is not statistically significant. We also find that the G-7 and E-7 economies have a strong time-varying connectedness in relation to their bond markets and this effect is more pronounced in G-7 economies. Daily Infectious Disease Equity Market Volatility is likely to be the strongest predictor of total connectedness. Concomitantly, we shed new light on the predictive power of the number of COVID-19 confirmed cases and deaths, and the Daily Infectious Disease Equity Market Volatility Tracker on the interdependence of these sovereign bond markets. Overall, this paper highlights the heterogeneous effect of the COVID-19 pandemic on sovereign bond yields in G-7 and E-7 countries and the notion that the developed economies, with their developed sovereign bond markets, are still seen as a safe haven during times of crisis. © 2023 The Authors

18.
International Journal of Evaluation and Research in Education ; 12(1):274-283, 2023.
Article in English | Scopus | ID: covidwho-2203610
19.
14th Asian Conference on Intelligent Information and Database Systems , ACIIDS 2022 ; 13758 LNAI:395-407, 2022.
Article in English | Scopus | ID: covidwho-2173832
20.
14th Asian Conference on Intelligent Information and Database Systems , ACIIDS 2022 ; 13758 LNAI:382-394, 2022.
Article in English | Scopus | ID: covidwho-2173831
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