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Coronavirus disease 2019(COVID-19) poses a challenge to hospitals for the prevention and control of public health emergencies. As the main battlefield of preventing and controlling COVID-19, large public hospitals should develop service protocols of diagnosis and treatment for outpatient, emergency, hospitalization, surgery, and discharge. The construction of medical protocols should be based on the risk factors of key points and focused on pre-inspection triage and screening, to establish a rapid response mechanism to deal with exogenous and endogenous risk factors. Implementation of all-staff training and assessment, strengthening the information system, and use of medical internet service are important. This study explores the construction of medical protocols in large public hospitals during the pandemic, and provides a reference for the orderly diagnosis and treatment in hospitals during the pandemic.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.
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Inclusive digital financial services should welcome older populations and make them beneficiaries of the digital and financial revolution. To understand older adults' experience of using digital financial tools, we conducted an online survey of 268 older internet users aged 60 or above from urban areas of 14 Chinese provinces after China's nationwide COVID-19 lockdown in 2021. Our results revealed that older internet surfers were active in digital financial activities and engaged most with activities that were highly compatible with their lifestyles. Active users significantly differed from inactive users in sociodemographics, confirming that a digital divide related to social stratification exists among older internet users. Digital finance active users were also distinguished from inactive users' attitudes and perceptions toward digital finance. Logistic regression results indicated that perceived usefulness, access to proper devices for digital finance, risk perceptions, and perceived exclusion if not using technology were associated with their adoption of these advanced tools. Older adults reported the perceived inconvenience of in-person financial services during the lockdown. They also expressed a willingness to participate in relevant training if provided. The findings of this study could help aging-related practitioners to understand older adults' engagement in digital finance and guide policy and project design in the area of financial inclusion of the aging population.
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Health is the centre of human enlightenment. Due to the recent Covid outbreak and several environmental pollutions, checking one's vitals regularly has become a necessity. Ours is an IoT-based device that measures a user's heart rate, blood oxygen level and body temperature. The device is compact and portable, making it easy for users to wear. The readings are measured and shown on an OLED display with the help of sensors. The data is also available on the cloud. A webpage and a mobile application were developed to view the data from the cloud. Individual graphs of the vitals with time are available on the mobile application. This can be used for progress measurement and statistical analyses. Authorized personnel can access the patient's vitals. This creates a scope for Tele-medication in rural and underdeveloped regions. Besides, one can also view his/her vitals for personal health routine. © 2022 IEEE.
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Teleconsultation is a type of medical practice similar to face-to-face consultations, and it allows a health professional to give a consultation remotely through information and communication technologies. In the context of the management of the coronavirus epidemic, the use of teleconsultation practices can facilitate healthcare access and limit the risk of avoidable propagation in medical cabinets. This paper presents the monitoring of international teleconsultation referrals in the era of Covid-19 to facilitate and prevent the suspension of access to care, the most common architecture for teleconsultation, communication technologies and protocols, vital body signals, video transmission, and the conduct of teleconsultation. The aim is to develop a teleconsultation platform to diagnose the patient in real time, transmit data from the remote location to the doctor, and provide a teleconsultation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Three patients diagnosed with COVID-19 were all young women in their thirties who have suffered from Internet violence in their personal life after hospitalization. They showed significant emotional distress such as, depression state, acute stress disorder, and dissociative disorder. The current study adopts short-term, individualized and comprehensive psychological interventions, including psychological support, encouragement, listening, safety confirmation, catharsis, psychological suggestion, and stimulation of internal potential to treat patients. The third case was provided with psychological interventions combined with antipsychotic treatment. After timely psychological interventions all three patients achieved sound results.Copyright © 2021 Chinese Medical Journals Publishing House Co.Ltd.
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This paper contributes to the Covid-19 literature by exploring the concept of post-traumatic growth (PTG) utilizing a mixed methods approach. The study examines to what extent the participants experienced positive growth and renewal arising from the prolonged period of lockdowns and emergency online learning. Exploring the experiences of 552 female undergraduate students in a private Saudi Arabian university, an online survey was utilized to gather the data. All the students had experienced online education as a result of the pandemic. The findings indicate the participants underwent a diversity of personal growth experiences. In addition, they also developed different coping mechanisms. The study provides insights into the responses of the students to the issues they were facing during the pandemic. It identifies ways in which participants experienced personal growth as well as a shift in perspective about their lives. There are implications for educators, counselors and policymakers emerging from this study. AD -, Kingdom of Saudi Arabia ;, Netherlands ;, Kingdom of Saudi Arabia
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The coronavirus pandemic has been globally impacting the health and prosperity of people. A persistent increase in the number of positive cases has boost the stress among governments across the globe. There is a need of approach which gives more accurate predictions of outbreak. This paper presents a novel approach called diffusion prediction model for prediction of number of coronavirus cases in four countries: India, France, China and Nepal. Diffusion prediction model works on the diffusion process of the human contact. Model considers two forms of spread: when the spread takes time after infecting one person and when the spread is immediate after infecting one person. It makes the proposed model different over other state-of-the art models. It is giving more accurate results than other state-of-the art models. The proposed diffusion prediction model forecasts the number of new cases expected to occur in next 4 weeks. The model has predicted the number of confirmed cases, recovered cases, deaths and active cases. The model can facilitate government to be well prepared for any abrupt rise in this pandemic. The performance is evaluated in terms of accuracy and error rate and compared with the prediction results of support vector machine, logistic regression model and convolution neural network. The results prove the efficiency of the proposed model.
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Coronavirus (COVID-19) is a very contagious infection that has drawn the world's attention. Modeling such diseases can be extremely valuable in predicting their effects. Although classic statistical modeling may provide adequate models, it may also fail to understand the data's intricacy. An automatic COVID-19 detection system based on computed tomography (CT) scan or X-ray images is effective, but a robust system design is challenging. In this study, we propose an intelligent healthcare system that integrates IoT-cloud technologies. This architecture uses smart connectivity sensors and deep learning (DL) for intelligent decision-making from the perspective of the smart city. The intelligent system tracks the status of patients in real time and delivers reliable, timely, and high-quality healthcare facilities at a low cost. COVID-19 detection experiments are performed using DL to test the viability of the proposed system. We use a sensor for recording, transferring, and tracking healthcare data. CT scan images from patients are sent to the cloud by IoT sensors, where the cognitive module is stored. The system decides the patient status by examining the images of the CT scan. The DL cognitive module makes the real-time decision on the possible course of action. When information is conveyed to a cognitive module, we use a state-of-the-art classification algorithm based on DL, i.e., ResNet50, to detect and classify whether the patients are normal or infected by COVID-19. We validate the proposed system's robustness and effectiveness using two benchmark publicly available datasets (Covid-Chestxray dataset and Chex-Pert dataset). At first, a dataset of 6000 images is prepared from the above two datasets. The proposed system was trained on the collection of images from 80% of the datasets and tested with 20% of the data. Cross-validation is performed using a tenfold cross-validation technique for performance evaluation. The results indicate that the proposed system gives an accuracy of 98.6%, a sensitivity of 97.3%, a specificity of 98.2%, and an F1-score of 97.87%. Results clearly show that the accuracy, specificity, sensitivity, and F1-score of our proposed method are high. The comparison shows that the proposed system performs better than the existing state-of-the-art systems. The proposed system will be helpful in medical diagnosis research and healthcare systems. It will also support the medical experts for COVID-19 screening and lead to a precious second opinion.
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Internet of Things (IoT) and smart medical devices have improved the healthcare systems by enabling remote monitoring and screening of the patients' health conditions anywhere and anytime. Due to an unexpected and huge increasing in number of patients during coronavirus (novel COVID-19) pandemic, it is considerably indispensable to monitor patients' health condition continuously before any serious disorder or infection occur. According to transferring the huge volume of produced sensitive health data of patients who do not want their private medical information to be revealed, dealing with security issues of IoT data as a major concern and a challenging problem has remained yet. Encountering this challenge, in this paper, a remote health monitoring model that applies a lightweight block encryption method for provisioning security for health and medical data in cloud-based IoT environment is presented. In this model, the patients' health statuses are determined via predicting critical situations through data mining methods for analyzing their biological data sensed by smart medical IoT devices in which a lightweight secure block encryption technique is used to ensure the patients' sensitive data become protected. Lightweight block encryption methods have a crucial effective influence on this sort of systems due to the restricted resources in IoT platforms. Experimental outcomes show that K-star classification method achieves the best results among RF, MLP, SVM, and J48 classifiers, with accuracy of 95%, precision of 94.5%, recall of 93.5%, and f-score of 93.99%. Therefore, regarding the attained outcomes, the suggested model is successful in achieving an effective remote health monitoring model assisted by secure IoT data in cloud-based IoT platforms.
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Remote healthcare is a well-accepted telemedicine service that renders efficient and reliable healthcare to patients suffering from chronic diseases, neurological disorders, diabetes, osteoporosis, sensory organs, and other ailments. Artificial intelligence, wireless communication, sensors, organic polymers, and wearables enable affordable, non-invasive healthcare to patients in all age groups. Telehealth services and telemedicine are beneficial to people residing in remote locations or patients with limited mobility, rehabilitation treatment, and post-operative recovery. Remote healthcare applications and services proved to be significant during the COVID-19 pandemic for both patients and doctors. This study presents a detailed study of the use of artificial intelligence and the internet of things in applications of remote healthcare in many domains of health, along with recent patents. This research also presents network diagrams of documents from the Scopus database using the tool VOSViewer. The paper highlights gap which can be undertaken by future researchers. © 2023 IEEE.
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the CoVid-19 pandemic drastically changed different aspects of the daily lives of millions of people, generating an increase in the use of the internet for maintaining social contact, teleworking or online studies. this study explores the extent to which the internet connection pattern changed during the CoVid-19 confinement in a sample of adults from four latin american countries, considering gender and age. a descriptive study was carried out, including a non-probabilistic convenience sample design. the final sample was comprised of 1488 participants. this analysis shows that internet habits changed in terms of frequency, duration, and time of use. We observe differences when it comes to gender and age. in women, the increases in use are greater for the different variables analyzed, especially for the frequency of connection at night. in terms of age, the younger the age, the greater the increase in internet connection time throughout the day and connection time at night. (PsycInfo Database Record (c) 2023 APA, all rights reserved) (Spanish) la pandemia de CoVid-19 cambio drasticamente diferentes aspectos de la vida cotidiana de millones de personas, generando un incremento del uso de internet para el mantenimiento del contacto social, el teletrabajo o los estudios online. en este articulo se evalua en que medida presento cambios el patron de conexion a internet durante el confinamiento por CoVid-19 en una muestra de adultos de cuatro paises de america latina, considerando el sexo y la edad. se propuso un estudio descriptivo, con diseno no probabilistico de muestreo por conveniencia. la muestra final quedo compuesta por 1488 participantes. el analisis muestra que los habitos de conexion a internet se modificaron en terminos de frecuencia, duracion y horarios, observandose diferencias en funcion del sexo y la edad. en mujeres son mayores los incrementos de uso para las distintas variables analizadas, especialmente para la frecuencia de conexion nocturna. en cuanto a la edad, a menor edad se observa un mayor aumento del tiempo de conexion a internet a lo largo del dia y de conexion en horario nocturno. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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The COVID-19 pandemic has caused disruption to the economy due to the increasing infection that affects the workforce in different sectors. The Philippine government has imposed lockdowns to control the spread of infection. This urged the different sectors to implement flexible work schedules or work from home setup. A work-from-home (WFH) setup burdens both the employee and employer by installing different equipment set-ups such as WiFi-equipped laptops, computers, tablets, or smartphones. However, the internet stability in some of the areas in the Philippines is not yet reliable. In this study, an application is used collect survey information and provide an estimate of the telework internet cost requirement of a given government employee or a given government employee implementing a work-from-home set up in their respective household. This involves survey results from different respondents who are currently on a work-from-home setup and significant factors from the survey have been analyzed using machine learning (ML) algorithms. Among the machine learning algorithms used, the ensemble bagged trees model outperformed the other ML models. This work can be extended by incorporating a wider scope of datasets from different industry doing work from home set-up. In addition, in terms of education, it is also recommended to determine the WFH set up not just with the government employee and employer but to also extend this into the education side. © 2022 IEEE.
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The tremendous growth of tourism in Albania in recent decades, made important the understanding of the role that digital marketing and mobile technology is playing in this field. Tourism in Albania is one of the most important economic sectors of the country, and is growing year after year. It is emphasized that digitalization is a new form of communication between producers and consumers of tourism services, becoming a source of competitive advantages for tourism organizations. The main goal of the study is to give us a clear overview of the use of the Internet, information technologies and digital marketing in Albania. For the realization of this study, we used a methodology that combines primary data with secondary ones. The research was conducted through questionnaires that were sent to Albanian travel agencies via email. The questionnaire contains 17 questions, and was sent to 150 travel agencies, of which 102 agencies responded. Regarding the study, digital marketing plays an important role in improving the image of Albanian tourism throughout the world. It has created facilities in the way of doing marketing and reducing the costs of businesses. Through digital marketing, travel agencies have managed to promote our country online, personalize services and, above all, be closer to customers. The research found that the most effective digital marketing tools used by the agencies are Instagram and Facebook.
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After the outbreak of corona virus, all counties are paying special attention to their healthcare infrastructure. During second phase of covid-19, entire world has seen health care crisis. Large number of people died globally. Entire world was affected mentally or physically. There is a great need to strengthen the healthcare infrastructure, to vaccinate the population against covid virus infection and to take proper precaution to avoid spread of the virus, so that the world will not see such deadly days again. This paper discusses how technologies like Internet of Things (IoT), Artificial Intelligence (AI), Drones etc can help in remote monitoring of patients, judicious hospital admission, conscious distribution of lifesaving drugs etc. Investment in technology with not only help in the reduction of spread of the virus but will also help in fighting with all other future pandemics. All the countries must have to invest more on latest technologies in their healthcare to make themselves ready for such future pandemics. When the things will improve, the new normal will be very much different from the life that was before pandemic. IoT, AI and other technologies will become the non-separatable part of our life. © 2023 Bharati Vidyapeeth, New Delhi.
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In recent years, the COVID-19 has made it difficult for people to interact with each other face-to-face, but various kinds of social interactions are still needed. Therefore, we have developed an online interactive system based on the image processing method, that allows people in different places to merge the human region of two images onto the same image in real-time. The system can be used in a variety of situations to extend its interactive applications. The system is mainly based on the task of Human Segmentation in the CNN (convolution Neural Network) method. Then the images from different locations are transmitted to the computing server through the Internet. In our design, the system ensures that the CNN method can run in real-time, allowing both side users can see the integrated image to reach 30 FPS when the network is running smoothly. © 2023 IEEE.
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As intelligent driving vehicles came out of concept into people’s life, the combination of safe driving and artificial intelligence becomes the new direction of future transportation development. Autonomous driving technology is developing based on control algorithms and model recognitions. In this paper, a cloud-based interconnected multi-sensor fusion autonomous vehicle system is proposed that uses deep learning (YOLOv4) and improved ORB algorithms to identify pedestrians, vehicles, and various traffic signs. A cloud-based interactive system is built to enable vehicle owners to master the situation of their vehicles at any time. In order to meet multiple application of automatic driving vehicles, the environment perception technology of multi-sensor fusion processing has broadened the uses of automatic driving vehicles by being equipped with automatic speech recognition (ASR), vehicle following mode and road patrol mode. These functions enable automatic driving to be used in applications such as agricultural irrigation, road firefighting and contactless delivery under new coronavirus outbreaks. Finally, using the embedded system equipment, an intelligent car was built for experimental verification, and the overall recognition accuracy of the system was over 96%. Author
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Sustainable agriculture is the backbone of food security systems and a driver of human well-being in global economic development (Sustainable Development Goal SDG 3). With the increase in world population and the effects of climate change due to the industrialization of economies, food security systems are under pressure to sustain communities. This situation calls for the implementation of innovative solutions to increase and sustain efficacy from farm to table. Agricultural social networks (ASNs) are central in agriculture value chain (AVC) management and sustainability and consist of a complex network inclusive of interdependent actors such as farmers, distributors, processors, and retailers. Hence, social network structures (SNSs) and practices are a means to contextualize user scenarios in agricultural value chain digitalization and digital solutions development. Therefore, this research aimed to unearth the roles of agricultural social networks in AVC digitalization, enabling an inclusive digital economy. We conducted automated literature content analysis followed by the application of case studies to develop a conceptual framework for the digitalization of the AVC toward an inclusive digital economy. Furthermore, we propose a transdisciplinary framework that guides the digitalization systematization of the AVC, while articulating resilience principles that aim to attain sustainability. The outcomes of this study offer software developers, agricultural stakeholders, and policymakers a platform to gain an understanding of technological infrastructure capabilities toward sustaining communities through digitalized AVCs.
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Covid pandemic brought a significant change in the way people learn, entertain, interact and conduct business. With people working and socializing remotely, social media usage skyrocketed and provided a fertile ground to cybercriminals to exploit the platforms and its users. This paper will explore the rising trend of cybercrime on social media, including specific types of cybercrime such as phishing scams, impersonation and misinformation. The paper will also discuss about the parties mostly affected by cybercrimes. Additionally, the paper will delve into the impact of increase in cybercrime on digital marketing, including the challenges faced by businesses. Overall the paper aims to provide a comprehensive overview of the current state of cybercrime media during the covid pandemic and how it is impacting the overall society and digital markets all together.
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PurposeThis study evaluates the impact of online menus and perceived convenience of online food ordering on consumer purchase intention and shows how a desire for food creates a relationship between an online menu and a customer's purchase intention. Suggestions for management are proposed to design an effective menu to improve business performance in the competitive market in Vietnam.Design/methodology/approachThe paper follows a quantitative method. Quantitative research aims to analyze and critically evaluate the research question(s) to discover new factors.FindingsFindings indicate a positive relationship between menu visual appeal (MV), menu informativeness (MI), desire for food (DF), the perceived convenience (PC) of ordering food online and intention to purchase (PI). The attractiveness of images and information is a significant factor affecting diners' desire to eat, while the demand for food and the convenience of ordering food online are also factors affecting purchase intention.Practical implicationsThe study confirms the importance of online menus to purchase intention. Economically, when supply and demand are reasonable, the market is stable and technology develops. In terms of social, hygiene, attractiveness and price factors, it is helpful to have an overview. Research is the premise for further studies with factors from menu to customer trust.Originality/valueThe study provides a solid foundation for further studies on restaurant menu elements as well as a new perspective on how restaurants improve their dishes.
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BackgroundWhen COVID-19 hit Singapore in 2020, the public was advised to avoid visiting the hospitals unless for essential services. Advance Care Planning (ACP) services in hospital and community had to be stopped to reduce exposure for the public. However, it was not feasible for ACP services to stop with no foresight of when it could resume. Ironically, ACP should all the more be advocated amidst the pandemic.Henceforth, the team planned and implemented a tele-ACP workflow in February 2020 to ensure accessibility in continuity of care and reduce waiting time for ACP appointments.MethodsTele-ACP is conducted only via Zoom, given its security and encryption features. Criteria of patients include ability to read basic English, having electronic device with internet access, and having no severe hearing or speech impairment.Pre-ACP appointment: Zoom details including a guide were sent to patients and/or NHS.On appointment day: Before session starts, ACP Facilitator will ensure that patient and/or NHS are at a space where there is privacy. Internet stability will also be checked.Post-ACP appointment: Signatures will be obtained electronically or via post, while ensuring personal data is well-protected.ResultsFrom February 2020 to November 2022, 105 tele-ACPs (14 General ACPs and 91 Preferred Plan of Care) were completed. 45 were completed in 2020 and 2021 each, while 15 were done in 2022 (as of November). The average duration for tele vs in-person ACPs is both about 90 minutes, indicating that the effort and time spent are not any less despite ACP discussions being done virtually.ConclusionsLooking at the number of tele-ACPs completed and how it is still actively carried out despite COVID-19 situation being stable and restrictions lifted, tele-ACP is clearly in healthy demand. This shows that tele-ACP is here to stay, being both sustainable and transferable to multiple settings.