ABSTRACT
The fast human-to-human spread of COVID-19 has caused significant lifestyle changes for many individuals. At the end of January 2020, the pandemic began, and many nations responded with varying degrees of testing, sanitation, lockdown, and quarantine centers. New normals of testing, sanitization, social separation, and lockdown are being implemented, and people are gradually returning to work and other daily routines. The COVID-19 infected population is monitored by testing individuals regularly. But it's a resource-heavy endeavor to test everyone without good reason. An optimum strategy is required to efficiently identify persons who are most likely to test positive for COVID-19. Sanitation is utilized for both persons and public spaces to eliminate germs. However, the disruption of governmental operations and economic development makes the use of lockdown and quarantine centers a resource-intensive endeavor. Conversely, it degrades the standard of living across a society. Furthermore, keeping people inside their houses or quarantine centers for an unlimited amount of time would not allow the government to care for everyone. These variables impact virus propagation, human health and happiness, available resources, and the economy's health, making their management resource-intensive. counting and density estimation are both attempts to create clever and efficient algorithms that can interpret the data provided by images to carry out Efficiency. GANs have been proven to have promising applications in overcoming the data dearth problem in COVID-19 lung image analysis. The Convolutional Neural Network (CNN) models built for the diagnosis of COVID-19 have benefited from the GAN-generated data used to refine their training. Moreover, GANs have helped improve the performance of CNNs by super-resolving pictures and performing segmentation. This work highlights the Reinforcement deep learning model over the fundamental constraints of the possible transformation of GANs-based approaches. This work proposes the model be developed with a new intelligent approach using RL to quantify these different types of testing considered for social distancing, face mask detection, limiting the gathering, and locking the location using the Q Learning technique. Different RL algorithms are implemented, and agents are equipped with these algorithms so that they may interact with the environment and learn the optimum method for doing so. © 2023 IEEE.
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Extreme disruptive scenarios such as pandemic lockdown force people to alter regular daily routines, impacting their energy consumption pattern. The implication of such a disruptive scenario for a more extended period on energy consumption is uncertain. This study aimed to investigate the impact of COVID-19 lockdown on residential electricity consumption in 100 houses from the southwestern UK. For the study, we analysed highly granular (1-minutely) electricity consumption data for April-September 2020 compared to the same months in 2019 for the same houses. Our study showed statistically significant differences during the lockdown period (the analysed six months) in energy demand. The minutely average electricity demand was 1.4-10% lower during April-September 2020 than in 2019. Our analysis showed that not all houses had similar type of changes during the lockdown. Some houses demonstrated a 38% increase in electricity demand, whereas some houses showed a 54% reduction during the lockdown period compared to 2019. Some houses showed significantly higher electricity use during the morning and afternoon than in 2019, which might be due to working and schooling from homes during the lockdown. © International Building Performance Simulation Association, 2022
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The COVID-19 era has reshaped the world regarding the contact-less economy, healthcare systems, remote work environment, people's lifestyle and their daily routines, etc. The consumer products (CP) industry is being impacted due to the behaviours of consumers during self-quarantine. This accelerates adopting digital transformation and upgrading the business models for the contact-less CP industry. Accordingly, this study provides a step toward the contact-less CP industry during and post-pandemic. First, we have proposed a conceptual framework for the contact-less CP industry that aims to bring together the key advanced technologies (e.g., Digital Twin (DT), blockchain, AI, cloud computing, 5G, and robots). The combination of the advanced technologies provides data monitoring, transparency, traceability, automation, and data sharing among consumers and CP partners. The proposed framework will enable a more contact-less personalized interaction that will work towards higher levels of consumer satisfaction while maintaining contact-less economy growth. Then, we have described how the proposed framework can be applied for contact-less delivery services for the CP industry during and post-pandemic. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The study describes elements of the daily spatial and time systems relating to online home-based primary education during the pandemic school closures. It was conducted from the children's perspective (semi-structured interviews with children), which is only marginally discussed in research on the effects of home-based education during the COVID-19 pandemic. The data were analysed using thematic analysis. The spatial recontextualization of the household and home, brought about through the transference of school functions to the home environment, cannot be viewed in isolation from the temporal recontextualization. The results point to a fundamental shift in the nature and functionality of educational space and time during the pandemic school closures and online home-based education. It changed not only the home and its time–space structures but also the educational space–time structures. These changes are described and discussed in relation to time-geography concepts and cultural analysis. Moreover, our data show that the children were able to develop strategies for adapting to and coping with the new educational situation and spatial–temporal context during the pandemic-driven shift to home-based education. [ FROM AUTHOR]
ABSTRACT
The sudden outbreak of COVID-19 and consequent quarantine policies have substantially altered family lives worldwide. Potential associations between parental negative emotional expressions towards the pandemic, family factors, and child psychological adjustment remain under-explored. Accordingly, the goal of the present study was to examine the relation between maternal panic over COVID-19 and children's depressive symptoms, with a focus on the potential moderating role of children's daily routines during a period of strict quarantine. Participants were N = 1,589 children (M age = 13.13 years, SD = 1.54; 50.7% girls) and their mothers, from Zhengzhou, Henan Province, in Mainland China. Data were collected in April of 2020, when school closure policies were in effect. Mothers reported their panic over COVID-19 and children reported their depressive symptoms and daily routines during the quarantine period. Overall, results indicated a significant positive association between maternal panic over COVID-19 and child depressive symptoms. However, maintaining regular daily routines was found to be a significant moderator of this association, with higher levels of daily routines attenuating the link between maternal panic reactions and child psychological distress (i.e., buffering effect). The results highlight the protective role of regular daily routines in promoting psychological adjustment among Chinese children during the COVID-19 pandemic. Supplementary Information: The online version contains supplementary material available at 10.1007/s12144-022-04129-0.
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In the era of Covid 19 pandemic, governments have imposed nationwide lockdowns which make a huge change to people daily routines. This last affect indirectly on the well-being of people’s mental health, especially the vulnerable population. And due to social media, many conversations about these phenomena occur online, especially those related to people’s emotions. Then the field of sentiment analysis is requested. In this paper, we aimed to extract correlations within this epidemic and its psychologic effects. In fact, our goal is to extract features that may improve sentiment analysis accuracy which is a crucial step to fulfill the main objective of our research: developing an intelligent recommendation system that will benefit persons, through a positive accompaniment and the early alert, in case of complex situations as mental illness. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Negative psychological effects of the coronavirus disease (COVID-19) have been identified in adults and children, such as anxiety and sleep disorders. However, research about the impact of this pandemic on children from ethnical minorities is scarce. We tested the effects of COVID-19 outbreak on psychological aspects and daily routines among Arab Israeli Children. An online cross-sectional survey was conducted among Arab Israeli parents, including behavioral and emotional aspects questionnaire and questions addressing using of screens, sleep, and physical activities. The results showed that, during the COVID-19 outbreak, 55.8% of the children asked to sleep in their parents' bed and 45% expressed fears they did not have before. Most of the children showed increased irritability, constant mood swings and nervousness about limits and messages, and 41.4% showed sleep difficulties. Concerning adaptive behaviors, more than 50% of the parents reported that their child became wiser, lazier, and was able to adapt the limits and restriction of the COVID-19 outbreak. Moreover, the children tended to increase their use of screens, used to sleep more time, and were less active physically. The results suggest that children are vulnerable to the COVID-19 outbreak psychological effects and highlight the need to reduce the psychological burden of this pandemic and the necessity of immediate intervention.
Subject(s)
COVID-19 , Coronavirus , Adult , Arabs , Child , Cross-Sectional Studies , Humans , Pandemics , SARS-CoV-2ABSTRACT
Now a days in EFL procedure of education the ability of reading became as significant belief and personal-efficacy reading as a basic understanding for students. By monitoring the acknowledged participates under the ballpark figure of large studying and methods of understanding, the impact of their observation is premeditated on reading of each one’s personal-efficacy. On a daily routine all these things are comparatively considered which are put into effect by teachers of handful in number. Approach towards exhibiting Extensive reading (ER) is inspected to be “more expensive, difficult, and time-consuming”. Method of recognition of elements in a various way for effective impact in putting its efforts to utilize for its empowerment. Paper has been segregated into two contexts: Association with attitude is considered as primary one and attitude is considered as secondary one. Whether knowledge work is understood by student or not is considered as the impact of ER by the first review. Procedure which are convenient is taken as the observations of student and is analysed as second one. The examinations are quantifiable to utilize the observations as information in terms of subjective way taken from students who belong to first academic year of reading course in a systematic way and 603 details of undergraduate students from KLEF of Guntur were chosen as participants for extant examination. In ER programme of includes and excludes “comprehension reading work” is treated as fundamental in the proposal of disclosures. In case of any, “the programme appeared to positively affect contributing students”. Techniques of classification like “decision tree and Mixed Model Database Miner (MMDBM)” are employed in this paper which leads to improvements of post-test to pre-test in ER group. Observations of students in ER results as optimistic and algorithm of MMDBM which leads to accuracy in higher rate in pre-test and post-test detection. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Early research finds that all across the world suffered from a virus named Covid-19. It affects each individual's life, business, and economy. The impact of the pandemic in the healthcare sector and daily routine life are highly disturbing and during this period use of IoT increases. This paper focuses on healthcare, daily life, education, and businesses during the covid-19 and technology impact in everyone's life. To take the perception of students and professionals, 65 respondents give their perception, in which a few of them are understudies and others are working employees. Based on survey results it is observed that how IOT impact businesses and everyone's daily life. © 2022 IEEE.
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BACKGROUND: In face of large-scale disasters, persons with fewer assets are at greater risk of persistent poorer mental health than persons with more assets. Everyday daily routine disruptions and financial hardship could mediate this association. METHODS: This prospective population-representative study in Hong Kong aimed to investigate the relation between assets during the acute phase of COVID-19 (February-August 2020, T1) and persistent probable depression from T1 to March-August 2021 (T2), as well as the mediating effects of daily routine disruptions and financial hardship on the assets-depression association. RESULTS: Low assets at T1 prospectively related to persistent probable depression from T1 to T2. Primary routine disruptions (i.e., healthy eating and sleep) at T1 and financial hardship at T2 were found to fully mediate the association between T1 assets and persistent probable depression. LIMITATIONS: Persistent probable depression reported on the PHQ-9 should be further verified with clinical diagnoses/interviews. CONCLUSIONS: The COVID-19 pandemic was accompanied by a global economic downturn. Persons who have fewer assets could be at greater risk of depression during this period. Our findings suggest a need to provide behavioral and financial assistance to persons with fewer assets in the short run and a need to ensure that everyone has adequate assets to mitigate the mental health consequences of the COVID-19 pandemic in the long run.
Subject(s)
COVID-19 , Disasters , COVID-19/epidemiology , Cohort Studies , Depression/epidemiology , Humans , Pandemics , Prospective StudiesABSTRACT
Purpose: This study investigated information needs on COVID-19 by identifying topics discussed on social questions and answers (Q&A) about daily routines, problems, and health issues for survival. A layered model of contexts for everyday life information seeking (ELIS) was adapted for interpreting topics to better understand the contexts in which users could relate information needs. Design/methodology/approach: Questions and answers posted on Naver Knowledge-iN were collected and analyzed during the first nine months following the outbreak. Time distribution, topic modeling, and association rule mining were applied to examine the topics on COVID-19 and their temporal variation. Findings: Numerous topics related to the cognitive context (symptoms and masks) and situational contexts (international affairs, financial support, study, and work) were discovered. Topics related to social context were discussed moderately, but the number of questions on this topic increased with time. Strong associations were observed between terms related to symptoms, indicating their importance as a COVID-19 topic in health. Originality/value: This study investigated topics of information needs using social Q&A data in which not only information inquiry but also information sharing coexist. The findings can help bridge the theory of ELIS to topic modeling in practice. The insights gained from this study can be used by information service providers for developing guidance and programs about how to survive during a pandemic. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0547. © 2022, Emerald Publishing Limited.
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Core muscles play a fundamental role both in exercises and daily routines. Strong core muscles can enhance the Trunk stability and transition of strength. However, due to the weakness, most rookies can hardly feel the recruitment of core muscles and start compensating or using the wrong form. This may lead to cumulative fatigue in the short term and improper postures or spinal injuries in a long time. Thus, monitoring and protecting the unit for early core-muscle training is necessary. The study focuses on fitness rookies and designs an innovative waistband. High-density electromyography (HD-sEMG) can provide real-time monitoring of muscle conditions once it censors fatigue. The band will remind the user to take a break. And the shape memory polymer (SMP) can protect the waist and back from potential injury if necessary. With the continuous impact of the coronavirus, trainers spend more time at home and face the limitation of space and equipment. Nonetheless, isometric and simplified isotonic training will be enough for starters for core-muscle exercise. The study lists core-muscle strength exercises for athletes and core-muscle stability prescriptions for medical care, then reorganize them for rookies at home. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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In 2020, many nurses were confronted with heightened work-related and personal stressors imposed by the COVID-19 pandemic. As daily routines were upended, we wanted to understand the impact on nurses' participation in continuous learning. We retrospectively analyzed the learning logs of 194 nurses enrolled in a 12-month distance learning course, one cohort from March 2019 to February 2020 and one from March 2020 to February 2021 during the COVID-19 pandemic. The frequency of monthly logins for the COVID-19 pandemic cohort was compared for nurses with and without prior distance learning experience. Login frequency was also compared for nurses who cared directly for COVID-19 patients and those who did not. Monthly login frequency for March 2020 was significantly higher than for March 2019, while log in frequency for April 2020 was significantly lower than for April 2019. We attribute this to an increase in COVID-19 cases, hospitalizations, and deaths in April 2020. From March 2020 to August 2020, login frequency was significantly higher for nurses without previous distance learning experience, suggesting their distance learning strategies were not yet established. During September and October 2020, login frequency was significantly higher in the group with distance learning experience, from which we inferred active procrastination. We found no significant differences in the login frequencies of nurses who cared for COVID-19 patients and those who did not. The results of our study suggest that stressors imposed by the COVID-19 pandemic had a significant negative impact on distance learning progress. Screening in advance for previous distance learning experience and providing mentoring and learning supports are recommended to mitigate interference with distance learning progress during times of heightened professional and personal stress. © 2021 IEEE.
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The Coronavirus pandemic has made Irreversible changes in our society and the business world. Almost all aspects of the business and daily routine have shifted to the digital platforms and various forms of personal, indirect communications and suit the current environment in guarding us against coronavirus. The outbreak also brought a refreshing load of creativity in the people who found new ways to solve everyday problems. The key to solving problems is effective communication. With the help of mobile devices and computers, people were able to change their environment so that their expression of thoughts and their tasks of daily routine got aligned with social media platforms. People express themselves as if they are not going to get another chance to express themselves. They use doodles, poetic tweets, and many other forms of colloquial language. Using mixed language such as Hinglish became a norm for the commoner. In this research work, an attempt has been made to review techniques that can be used to work trust models from which meaning insights can be drawn in times such as covid-19 pandemic. From this study it can be inferred that no single approach of modeling complex scenarios such trust in times of covid-19 can be done. There is an urgent need to take inspiration from multiple techniques and approaches to assess the trust level in the digital society. © 2021 IEEE.
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The coronavirus disease (COVID-19) pandemic has challenged multiple aspects of our lives. Social distancing among other preventive measures for reducing the contagion probability have supposed a significant challenge for many establishments. Restaurants, schools, conferences are establishments founded by the congregation of participants, distributed in tables or chairs over a certain scenario. These enterprises now face an optimization problem in their daily routine, where they seek to maximize the interpersonal distance while also allocating the maximum number of assistants. The optimization of these distribution paradigms, such as the CLP (Chair Location Problem), has been defined as NP-Hard, therefore, the use of metaheuristic techniques, such as Genetic Algorithms is recommended for obtaining an optimal solution within a polynomial time. In this paper, a GA is proposed for solving the CLP, attaining an optimal solution that maximizes the interpersonal distance among assistants while also guaranteeing a minimum distance separation for reducing the contagion probability. Results of the proposed methodology and multiple fitness evaluation strategies prove its viability for attaining a valid distribution for these establishments, thus satisfying the main objectives of this research. © 2022, Springer Nature Switzerland AG.
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This study examined the mediating effects of coping resources in the prospective associations between daily routine disruptions in the acute phase of COVID-19 and persistent probable anxiety and depression. A prospective, population-representative cohort of 1318 Hong Kong Chinese respondents completed a baseline survey between February and July 2020 (T1) and a 1-year follow-up survey between March and August 2021 (T2). Respondents reported demographics and disruptions to primary and secondary daily routines at T1, coping resources (i.e., self-efficacy and meaning making) at T2, and anxiety and depressive symptoms at T1 and T2. We found that 8.1% and 10.0% of respondents reached cutoff scores for probable anxiety and depression respectively at both T1 and T2. Logistic regression showed that T1 daily routine disruptions were positively associated with heightened risk of persistent probable anxiety and depression amid COVID-19. Path analysis showed that 15.3% and 13.1% of the associations of daily routine disruptions with persistent probable anxiety and depression were explained by coping resources, respectively, while the direct routine-outcome associations remained significant. Daily routine disruptions predict higher odds of persistent probable anxiety and depression directly and partially through reducing coping resources. Sustainment of regular daily routines should be advocated and fostered to enhance coping resources and reduce the risk of poorer adjustment among the affected populations amid public health crises.
Subject(s)
COVID-19 , Adaptation, Psychological , Anxiety/epidemiology , Anxiety/psychology , COVID-19/epidemiology , Cohort Studies , Depression/epidemiology , Depression/psychology , Humans , Prospective StudiesABSTRACT
We explored the role of perceived coronavirus disease (COVID-19) threats and people's sustainment of primary (e.g., personal hygiene) and secondary (e.g., exercising) routines for two indicators of individual functioning at work, that is, job satisfaction and work concentration. We conducted an online questionnaire study with Hong Kong and German employees (N = 576). Using Structural Equation Modeling, we found support for secondary daily routines to be positively associated with job satisfaction and work concentration. In contrast, threats from the COVID-19 pandemic did not show negative associations with work outcomes. But economic threats were negatively associated with secondary routines, and had an indirect (negative) effect on job satisfaction mediated by these routines. A deeper look into the specific secondary activities revealed that sustaining exercising routines (e.g., regularly taking a walk) was particularly relevant. Our results might be used for designing programs to support people in sticking or returning to beneficial everyday activities. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
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Humans start their day by looking in the mirror at least once before leaving their homes every morning. In addition, they waste some considerable time of their busy workload in front of the mirror. To make this time more productive and useful, there ought to be a system that can be readily conducted, user-friendly, and smart according to the constant progress on the Internet of Things. The intelligent mirror is a new addition to the smart device family, which is a straightforward concept. There will be a screen placed behind a two-way mirror, and this Intelligent Mirror turns our room or bathroom mirror into a personal assistant with artificial intelligence. The purpose is to develop a smart mirror that can automate working humans' busy daily routines and manage their tasks when they spend their time in front of a mirror. To make the most of this moment, users can securely access all the relevant details of the day by looking in the mirror simultaneously. The intelligent mirror, which a single voice command can activate, will significantly help disabled persons and the general. Raspberry Pi has been used to build the proposed intelligent mirror, linked to the digital world via the Internet. The mirror can communicate with the user through voice commands and reply appropriately. The monitoring of emotions and health measuring function will provide a distinctive experience to the users. The mirror will reflect important elements such as weather, date & time, covid-19 situation reports, local news, To-do list, water reminder, home workouts, and meal plans. The mirror can also handle specialized functions such as automating and controlling home IoT devices. © 2021 IEEE.
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“Old Age People Emotional Stress Prediction during Outbreak using Machine learning methods” discusses that there are two types of stress in elderly people: physical stress and emotional stress. It is very easy to detect physical stress, such as walking problems, breathing problems, problems in doing their daily routine work, etc., but it is very tough to detect emotional stress, and treatment is even more difficult. There are some common reasons for stress, such as financial problems after retirement, taking care of a sick spouse or the death of a spouse, and many more. The common symptoms of stress are loss of appetite, anxiety, insomnia, etc. But the situation gets worse during an outbreak. If an outbreak comes in the form of a pandemic such as a coronavirus, resulting in the death of loved ones, these things increase the level of emotional stress in elderly people. To predict their emotional stress, authors are using machine learning algorithms, Support vector machine for classification and for prediction Logistic Regression have been applied. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Covid19 has heightened physical and mental challenges for people with Autism Spectrum Disorder (ASD). One of the main difficulties that parents of children with ASD faced during the pandemic was to plan and structure a daily routine for their kids. The disruption of the routine, together with the difficulty of combining work and the care of children has resulted in behavioral problems and stress, and anxiety for children and their parents. For these reasons, the main goal of this work was to develop an adaptive robot that helps children with autism to plan and self-manage their day, allowing children to become more independent. While most interactive tools for children with ASD are meant for professional use in therapy, Pepe robot is developed as a support tool for these children to use along the way, with adaptability, agencies, senses, and playfulness at the core of the design. By collecting information from the performance of the kid, it is able to adapt its behavior to the child's (and parent's) needs and desires, and therefore progress with the child. Building upon the principles of Positive Behavioral Support, emotional crises are prevented by embracing a long-run negotiation process, by which the child gets gradually closer to the end goal of self-autonomy. Intended to be adapted to the accentuated needs of these children, the robot combines traditional and computational elements to make the most out of the experience. This project included in-depth user research together with parents and experts, an interdisciplinary design approach, and a prototyping phase in which a prototype was tested with children with ASD. © 2021 Owner/Author.