Smart Visual Sensing for Overcrowding in COVID-19 Infected Cities Using Modified Deep Transfer Learning

Currently, COVID-19 is circulating in crowded places as an infectious disease. COVID-19 can be prevented from spreading rapidly in crowded areas by implementing multiple strategies. The use of unmanned aerial vehicles (UAVs) as sensing devices can be useful in detecting overcrowding events. Accordingly, in this article, we introduce a real-time system for identifying overcrowding due to events such as congestion and abnormal behavior. For the first time, a monitoring approach is proposed to detect overcrowding through the UAV and social monitoring system (SMS). We have significantly improved identification by selecting the best features from the water cycle algorithm (WCA) and making decisions based on deep transfer learning. According to the analysis of the UAV videos, the average accuracy is estimated at 96.55%. Experimental results demonstrate that the proposed approach is capable of detecting overcrowding based on UAV videos' frames and SMS's communication even in challenging conditions. © 2005-2012 IEEE.

Automation and redistribution of work: the impact of social distancing on live TV production

The TV industry has long been under pressure to adapt its workflows to use advanced Internet technologies. It also must face competition from social media, video blogs, and livestreaming platforms, which are enabled by lightweight production tools and new distribution channels. The social-distancing regulations introduced due to the COVID-19 pandemic added to the list of challenging adaptations. One of the remaining bastions of legacy TV production is the live broadcast of sporting events and news. These production practices rely on tight collaboration in small spaces, such as control rooms and outside broadcast vans. This paper focuses on current socio-technical changes, especially those changes and adaptations in collaborative practices and workflows in TV production. Some changes necessary during the pandemic may be imposed, temporary adjustments to the ongoing situation, but some might induce permanent changes in key work practices in TV production. Further, these imposed changes are aligned with already ongoing changes in the industry, which are now being accelerated. We characterize the changes along two main dimensions: redistribution of work and automation. © 2021 The Author(s). Published with license by Taylor & Francis Group, LLC.

Impact of the state of alarm after COVID-19 on the habitual consumption of video games in primary schoolchildren

The health situation resulting from COVID-19 is affecting lifestyles starting from the earliest stages of life. Therefore, the aim was to analyse primary schoolchildren's habitual video game consumption after the end of the state of alarm caused by COVID-19. To this end, a cross-sectional study comprising 125 primary schoolchildren was designed. To measure their video game consumption, the Questionnaire on video game consumption habits was used. The Student's t-test revealed significant differences in all dimensions in favour of the boys (p < .001, for all). Additionally, those aged 11-12 years yielded higher scores in the degree of attraction to video games (p < .05), level of concern about video games (p < .05), and rate of habitual video game consumption (p < .05). In conclusion, the results of this study are in line with scientific literature, indicating greater video game consumption in boys and older schoolchildren.

Will videoteleconsultation have been just a stop-gap in French orthopedics-traumatology? A national survey of 280 surgeons

Introduction: Il n'existe pas, à ce jour, d'étude évaluant la satisfaction des chirurgiens orthopédistes français au sujet de la consultation vidéo et téléphonique. Pour autant, celle-ci a été encouragée en période de pandémie à coronavirus. Aussi nous avons mené une étude prospective afin d'évaluer: 1) le profil des praticiens ayant eu recours à la vidéotéléconsultation (VTC) au cours de la pandémie au SARS-CoV-2 ainsi que les facteurs susceptibles d'influencer son utilisation, 2) la satisfaction des chirurgiens français ayant réalisé des VTC, 3) les avantages, les limites et l'avenir de la VTC. Hypothèse: Notre hypothèse était que la VTC était suffisamment satisfaisante en orthopédie-traumatologie pour être utilisée dans la pratique clinique courante hors période Covid. Matériel et méthode: Il s'agit d'une enquête nationale réalisée sous la forme d'une Évaluation des Pratiques Professionnelles (EPP). Les chirurgiens orthopédistes et traumatologues français ont été contactés à l'aide d'un questionnaire numérisé par l'intermédiaire de la liste mail d'une partie des sociétés professionnelles et savantes françaises, avec une estimation des chirurgiens atteignables de 2000 praticiens. L'enquête portait sur l'utilisation, les modalités, et la satisfaction vis-à-vis de la VTC des chirurgiens orthopédistes français, et leur profil. Le questionnaire nous permettait d'établir le Net Promoter Score (NPS) évaluant sur en nombre absolu, de -100 à 100, la propension à recommander un service. Résultats: Au total, sur une estimation de 2000 praticiens contactés, 280 (14,0%) ont répondu à notre enquête. L'âge moyen était de 47,7 ± 10,0 (30-84) ans. Le taux d'utilisation de la VTC passait de 8,9% (n = 25/280) avant la pandémie à 55,3% (n = 155/280) au cours de celle-ci. Parmi les 155 praticiens ayant pratiqué la VTC la satisfaction globale retrouvait un NPS de -46,4. Au total 51% (n = 79/155) ont répondu être favorables à poursuivre les VTC hors période COVID. Parmi les utilisateurs de VTC, 50,3% (n = 78/155) décrivaient une perte de temps lors de l'examen clinique en VTC par rapport à une visite en présentiel, et 57,4% (n = 89/155) lors de la visualisation des examens complémentaires. Pour 98,1 % des utilisateurs (n = 152/155), la VTC n'était pas aussi satisfaisante que la consultation en présentiel pour l'examen clinique du patient, et seulement 18,1% (n = 28/155) ont programmé des interventions après une VTC isolée. Conclusion: À ce jour, dans le cadre de l'orthopédie-traumatologie en France, la VTC n'a su satisfaire les chirurgiens en raison d'un examen clinique virtuel et non physique, mais elle reste une solution de recours en cas de pandémie. Niveau de preuve IV;Série prospective sans groupe contrôle. © 2022 Elsevier Masson SAS

The Potential Barriers and Benefits of an Online Physical Activity Program during the COVID-19 Restrictions: Latrobe Virtual Streetgames. A Qualitative Study

COVID-19 saw the global reduction of many physical activity programs. To maintain engagement, many programs adjusted their delivery to online formats. To explore the impact that a youth targeted virtual community exercise program had on its participants during the COVID-19 pandemic. Seven participants of Virtual Streetgames took part in a semi-structured one-on-one interview, with questions around the impact of COVID-19, in addition to their view on the virtual program. Three major themes were identified. "Dawning of a new world" described the changes that occurred due to the pandemic. "Traveling together" identified the difficultly to maintain regular wellbeing activities. "Making a difference" contextualized how the virtual delivery was able to influence participants. The COVID-19 pandemic had a significant impact on the participants physical, mental and social health. The use of an online physical activity program had some positive impacts on health, however it did not seem to warrant the same level of engagement when compared to face-to-face. The study helped identify those who are at risk of both short and long-term health impacts due to the COVID-19 pandemic. Additionally, it provided information on how virtual innovative interventions can influence wellbeing outcomes. A AJHE Self-Study quiz is online for this article via the SHAPE America Online Institute (SAOI)

Knowledge discovery of zakat administration worldwide from YouTube and Zoom via text mining

Purpose: Zakat (Islamic almsgiving) plays a considerable role in dealing with the socioeconomic issues in times of COVID-19 pandemic, and such roles have been widely discussed in virtual events. This paper aims to discover knowledge of the current global zakat administration from virtual events of zakat (e.g. webinars) on YouTube and Zoom via text mining approach. Design/methodology/approach: The authors purposefully sampled 12 experts from four different virtual zakat events on YouTube and Zoom. The automated text transcription software is used to pull the information from the sampled videos into text documents. A qualitative analysis is operated using text mining approach via machine learning tool (i.e. Orange Data Mining). Four research questions are developed under the Word Cloud visualisation, hierarchal clustering, topic modelling and graph and network theory. Findings: The machine learning identifies the most important words, the relationship between the experts and their top words and discovers hidden themes from the sample. This finding is practically substantial for zakat stakeholders to understand the current issues of global zakat administration and to learn the applicable lessons from the current issues of zakat management worldwide. Research limitations/implications: This study does not establish a positivist generalisation from the findings because of the nature and objective of the study. Practical implications: A policy implication is drawn pertaining to the legislation of zakat as an Islamic financial policy instrument for combating poverty in Muslim society. Social implications: This work supports the notion of "socioeconomic zakat”, implying that zakat as a religious obligation is important in shaping the social and economic processes of a Muslim community. Originality/values: This work marks the novelty in making sense of the unstructured data from virtual events on YouTube and Zoom in the Islamic social finance research. © 2022, Emerald Publishing Limited.

Which mediated social interactions satisfy the need to belong?

This investigation uses the two-process model of needs to explore differences between face-To-face communication and interpersonal media in terms of belongingness need satisfaction. Using experience sampling methods, Study 1 (N = 117) explored change in feelings of loneliness and connection from interpersonal media use within a day. Study 2 (N = 1,747) examined the association between loneliness and life satisfaction as mediated by patterns of interpersonal media use in the year following the COVID-19 outbreak. Study 3 (N = 303) experimentally manipulated social belonging to examine changes in interpersonal media use and resulting feelings of connection and disconnection. Overall, when individuals were more connected, their behaviors were more consistent with the two-process model, compared to when they felt disconnected. Additionally, although some interpersonal media use was better than no social contact at all, interpersonal media are not equally capable of satisfying belongingness needs. © 2022 The Author(s). Published by Oxford University Press on behalf of International Communication Association.

Individual Surveillance Around Parked Aircraft at Nighttime: Thermal Infrared Vision-Based Human Action Recognition

The COVID-19 crisis has led to an unusually large number of commercial aircraft being currently parked or stored. For airlines, airports, and civil aviation authorities around the world, monitoring, and protecting these parked aircraft to prevent them from causing human-made damage are becoming urgent problems that are receiving increasing attention. In this study, we use thermal infrared monitoring videos to establish a framework for individual surveillance around parked aircraft by proposing a human action recognition (HAR) algorithm. As the focus of this article, the proposed HAR algorithm seamlessly integrates a preprocessing module in which a novel data structure is constructed to introduce spatiotemporal information of the action;a convolutional neural network-based module for spatial feature extraction;a triple-layer convolutional long short-term memory network for temporal feature extraction;and two fully connected layers for classification. Moreover, because no infrared dataset is available for the HAR task on airport grounds at nighttime, we present a dataset called IIAR-30, which consists of eight action categories that frequently occur on airport grounds and 2000 video clips. The experimental results on the IIAR-30 dataset demonstrated that the recognition accuracy of the proposed method was higher than 96%. We also further evaluated the effectiveness of the proposed method by comparing it with five baselines and four other methods. © 2022 IEEE.

Blended peer-assisted learning using a video conference system for anatomy education: student learners' and student facilitators' perspectives

Anatomy education that traditionally relies on face-to-face delivery is disrupted by the outbreak of COVID-19. Due to suspension of face-to-face instruction in schools, our institution adopted a video conferencing system with peer-assisted learning (VCS-PAL). The study objectives are to: 1) report our institutional experience in adopting blended VCS-PAL in anatomy teaching;2) describe perceptions towards this pedagogy during the pandemic among student facilitators and learners. In the mixed-method educational research, 139 year-2 biomedical engineering and pharmacy students were surveyed regarding their VCS-PAL learning experience. A total of 85 returned the survey, with a response rate of 60.7% (85/139). Most students found the live demonstration of plastinated specimens helpful in learning anatomy (82%). The general feedback from both student learners and student facilitators are positive. The blended VCS-PAL approach in anatomy education provides an excellent adjustment opportunity amidst the outbreak of the COVID-19 pandemic.

Fighting for a future free from violence: A framework for real-time detection of "Signal for Help”

In April 2020, by the start of isolation all around the world to counter the spread of COVID-19, an increase in violence against women and kids has been observed such that it has been named The Shadow Pandemic. To fight against this phenomenon, a Canadian foundation proposed the "Signal for Help” gesture to help people in danger to alert others of being in danger, discreetly. Soon, this gesture became famous among people all around the world, and even after COVID-19 isolation, it has been used in public places to alert them of being in danger and abused. However, the problem is that the signal works if people recognize it and know what it means. To address this challenge, we present a workflow for real-time detection of "Signal for Help” based on two lightweight CNN architectures, dedicated to hand palm detection and hand gesture classification, respectively. Moreover, due to the lack of a "Signal for Help” dataset, we create the first video dataset representing the "Signal for Help” hand gesture for detection and classification applications which includes 200 videos. While the hand-detection task is based on a pre-trained network, the classifying network is trained using the publicly available Jesture dataset, including 27 classes, and fine-tuned with the "Signal for Help” dataset through transfer learning. The proposed platform shows an accuracy of 91.25% with a video processing capability of 16 fps executed on a machine with an Intel i9-9900K@3.6 GHz CPU, 31.2 GB memory, and NVIDIA GeForce RTX 2080 Ti GPU, while it reaches 6 fps when running on Jetson Nano NVIDIA developer kit as an embedded platform. The high performance and small model size of the proposed approach ensure great suitability for resource-limited devices and embedded applications which has been confirmed by implementing the developed framework on the Jetson Nano Developer Kit. A comparison between the developed framework and the state-of-the-art hand detection and classification models shows a negligible reduction in the validation accuracy, around 3%, while the proposed model required 4 times fewer resources for implementation, and inference has a speedup of about 50% on Jetson Nano platform, which make it highly suitable for embedded systems. The developed platform as well as the created dataset are publicly available. © 2022

Introduction to the Media International Australia special issue on "TikTok cultures in the Asia Pacific”

The editors of this Feature Topic are founding members of the TikTok Cultures Research Network that focuses on culturally-situated and qualitatively-grounded scholarship on TikTok in the Asia Pacific region. This Feature Topic collection for Media International Australia is our second in a string of Special Issues on TikTok, each primed to interrogate the platform from different scholarly vantage points while remaining committed to surfacing, highlighting, and strengthening research from, by, and about contexts in the margins. In this Feature Topic issue, we focus on the Asia Pacific region to understand the socio-cultural impacts, creative circumventions, and agentic employments of TikTok since its installation. Given the timing of symposium and intellectual inquiries, these studies have also naturally considered the cascading impacts and consequences of the COVID-19 pandemic on platform use, meaning making, and the habitable spaces we make for ourselves and for each other in times of crisis. © The Author(s) 2022.

Clinical Rounds

Dogs can detect human stress... Children with COVID-19 at higher risk of T1D... ED-ICU not associated with substantially increased costs... Strategies to reduce pediatric deaths by guns... Electronic gaming and pediatric dysrhythmias

YouTube and formal math learning. Perceptions of students in COVID-19 times

Educational mathematics videos on the Internet are a widespread resource among high school students. Research on the use of Video Lectures (VL) in university studies supports their effectiveness and identifies which criteria affect their usefulness and students' intention to use them. In the context of the COVID-19 pandemic, this study presents the perceptions of 220 secondary students regarding the usefulness of and intention to use VL. Based on a catalogue of mathematics VL and a hybrid methodology that combines the Technology Acceptance Model (TAM) with focus groups of students and their teachers, the results reveal that VL are perceived as a useful resource. Students and teachers demonstrated their intention to continue using them to learn and teach mathematics in the classroom. No significant differences between secondary years were found, but differences according to gender were, with the Perceived Usefulness (PU) being higher in the female than in the male participants. The presence of a teacher onscreen, as well as the duration and accuracy of the contents are fundamental criteria for all school years. The inclusion of animations, music, and humorous bits are important for younger students. The teachers attribute particular importance to the technical quality of VL.

New Normal Remote Communication for Collaboration

Remote communication is not new for the architecture, engineering and construction (AEC) industry and academia. Organisations started using what was common, called "conference rooms” with sophisticated technological equipment prepared for "conference calls” when face-to-face meetings were not possible, and the industries culture and work practices were rooted in face-to-face meetings. This was current practice until the beginning of 2020, with the emergence of the global COVID-19 pandemic. The pandemic forced people to have safe distances between them, to be isolated for long periods of time, and several restrictions to travel not being possible to meet face-to-face. This situation rapidly created a new need to find ways to communicate as alternatives to traditional face-to-face meetings, for "conference call rooms” anywhere and accessible at any time by everyone. The extended duration of the pandemic made organisations adapt to that new normal and remarkable new opportunities arose in a new way. This article explores recent situations in academia and industry that can highlight potential guidance towards the new normal in remote communication for learning–teaching and the AEC industry sectors. In conclusion, appropriate use of these electronic processes provides opportunities to significantly improve remote communication in future. It is expected that the number of opportunities to develop international relationships and partnerships can be boosted to another level of accessibility. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Txt2Vid: Ultra-Low Bitrate Compression of Talking-Head Videos via Text

Video represents the majority of internet traffic today, driving a continual race between the generation of higher quality content, transmission of larger file sizes, and the development of network infrastructure. In addition, the recent COVID-19 pandemic fueled a surge in the use of video conferencing tools. Since videos take up considerable bandwidth ( ∼ 100 Kbps to a few Mbps), improved video compression can have a substantial impact on network performance for live and pre-recorded content, providing broader access to multimedia content worldwide. We present a novel video compression pipeline, called Txt2Vid, which dramatically reduces data transmission rates by compressing webcam videos ('talking-head videos') to a text transcript. The text is transmitted and decoded into a realistic reconstruction of the original video using recent advances in deep learning based voice cloning and lip syncing models. Our generative pipeline achieves two to three orders of magnitude reduction in the bitrate as compared to the standard audio-video codecs (encoders-decoders), while maintaining equivalent Quality-of-Experience based on a subjective evaluation by users ( n=242 ) in an online study. The Txt2Vid framework opens up the potential for creating novel applications such as enabling audio-video communication during poor internet connectivity, or in remote terrains with limited bandwidth. The code for this work is available at https://github.com/tpulkit/txt2vid.git. © 1983-2012 IEEE.

Passive Video Quality Assessment Using Lab and Remote Testing

In this chapter, research about the assessment of video quality for gaming content will be provided. At first, a dataset that was used for the development of the ITU-T Rec. G.1072 will be presented. The dataset was created in a laboratory environment using the passive test paradigm described in Chap. 3. Next, some results of the collected video quality ratings will be illustrated. While QoE assessment studies traditionally make use of controlled laboratory environments, there are also other possibilities to conduct user studies without a laboratory environment. Especially during the COVID-19 pandemic, which prevented many researchers from performing lab studies, the concept of supervised and unsupervised remote studies got lots of attention. By using such a remote study design, two studies assessing video quality ratings of similar conditions as in the previously mentioned dataset were conducted. These two studies allow to address three research topics that will be the focus of the remainder of this chapter. At first, it will be investigated whether video quality ratings obtained using the remote study design are comparable to those collected in the lab environment. Second, a comparison between video quality ratings collected using a stimulus duration of 20 s instead of 30 s will be performed, which tries to answer whether it is enough to use a shorter stimulus duration as proposed in ITU-T Rec. P.809. Lastly, the differences between using a discrete 5-point ACR scale and the extended continuous 7-point scales will be investigated. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Increase the Number of Views and Shares of COVID-19 Videos: Content Relevance and Emotional Consistency with Virus Variant Topics.

(1) Background: The coronavirus variants have posed serious challenges for the prevention and control of the COVID-19 pandemic. Individuals selectively watch and forward videos that help them reduce the damage caused by the virus. Therefore, the factors influencing video viewing and sharing in the context of the COVID-19 pandemic caused by virus variation must be explored. (2) Method: Based on a combination of uncertainty reduction theory and functional emotion theory, this paper designed hypotheses regarding how content relevance and emotional consistency affect video views and shares. We used the support vector machine (SVM) classification algorithm to measure the content relevance between videos and virus variant topics. We performed sentiment analysis of video text to evaluate the emotional consistency between videos and virus variant topics. Then, we used empirical analysis to build the model. (3) Results: The trained SVM classifier was effective in judging whether the video text was related to virus variant topics (F = 88.95%). The content relevance between COVID-19 videos and virus variant topics was generally low. The results showed that the higher the content relevance, the more views (IRR = 1.005, p = 0.017) and shares (IRR = 1.008, p = 0.009) the video received. Individuals were more willing to view (IRR = 1.625, p < 0.001) and share (IRR = 1.761, p < 0.001) COVID-19 videos with high emotional consistency with virus variant topics. (4) Conclusions: The results of empirical analysis showed that content relevance and emotional consistency between videos and virus variant topics significantly positively impacted video views and shares. The trained SVM classifier can support public health departments in monitoring and assessing the COVID-19 pandemic. Our study provides management advice while helping individuals reduce harm and inform next-step decisions.

Contribution of Live Video to Physicians' Remote Assessment of Suspected COVID-19 Patients in an Emergency Medical Communication Centre: A Retrospective Study and Web-Based Survey.

The COVID-19 pandemic had a major impact on emergency medical communication centres (EMCC). A live video facility was made available to second-line physicians in an EMCC with a first-line paramedic to receive emergency calls. The objective of this study was to measure the contribution of live video to remote medical triage. The single-centre retrospective study included all telephone assessments of patients with suspected COVID-19 symptoms from 01.04.2020 to 30.04.2021 in Geneva, Switzerland. The organisation of the EMCC and the characteristics of patients who called the two emergency lines (official emergency number and COVID-19 number) with suspected COVID-19 symptoms were described. A prospective web-based survey of physicians was conducted during the same period to measure the indications, limitations and impact of live video on their decisions. A total of 8957 patients were included, and 2157 (48.0%) of the 4493 patients assessed on the official emergency number had dyspnoea, 4045 (90.6%) of 4464 patients assessed on the COVID-19 number had flu-like symptoms and 1798 (20.1%) patients were reassessed remotely by a physician, including 405 (22.5%) with live video, successfully in 315 (77.8%) attempts. The web-based survey (107 forms) showed that physicians used live video to assess mainly the breathing (81.3%) and general condition (78.5%) of patients. They felt that their decision was modified in 75.7% (n = 81) of cases and caught 7 (7.7%) patients in a life-threatening emergency. Medical triage decisions for suspected COVID-19 patients are strongly influenced by the use of live video.

A new YOLO-based method for real-time crowd detection from video and performance analysis of YOLO models.

As seen in the COVID-19 pandemic, one of the most important measures is physical distance in viruses transmitted from person to person. According to the World Health Organization (WHO), it is mandatory to have a limited number of people in indoor spaces. Depending on the size of the indoors, the number of persons that can fit in that area varies. Then, the size of the indoor area should be measured and the maximum number of people should be calculated accordingly. Computers can be used to ensure the correct application of the capacity rule in indoors monitored by cameras. In this study, a method is proposed to measure the size of a prespecified region in the video and count the people there in real time. According to this method: (1) predetermining the borders of a region on the video, (2) identification and counting of people in this specified region, (3) it is aimed to estimate the size of the specified area and to find the maximum number of people it can take. For this purpose, the You Only Look Once (YOLO) object detection model was used. In addition, Microsoft COCO dataset pre-trained weights were used to identify and label persons. YOLO models were tested separately in the proposed method and their performances were analyzed. Mean average precision (mAP), frame per second (fps), and accuracy rate metrics were found for the detection of persons in the specified region. While the YOLO v3 model achieved the highest value in accuracy rate and mAP (both 0.50 and 0.75) metrics, the YOLO v5s model achieved the highest fps rate among non-Tiny models.

The impact of the covid-19 pandemic on diabetes care: the perspective of healthcare providers across Europe.

AIMS: Covid-19 caused changes on the delivery of diabetes care. This study aimed to explore perceptions of healthcare providers across Europe concerning 1) the impact of covid-19 on delivery of diabetes care; 2) impact of changes in diabetes care on experienced workload; 3) experiences with video consultation in diabetes care. METHODS: Cross-sectional survey among healthcare providers in the Netherlands, United Kingdom, Turkey, Ukraine and Sweden, with a focus on primary care. RESULTS: The survey was completed by 180 healthcare providers. During the COVID-19 pandemic 57.1% of respondents provided less diabetes care and 72.8% observed a negative impact on people with diabetes. More than half of respondents (61.9%) expressed worries to some extent about getting overloaded by work. Although the vast majority considered their work meaningful (85.6%). Almost half of healthcare providers (49.4%) thought that after the pandemic video-consultation could be blended with face-to-face contact. CONCLUSIONS: Less diabetes care was delivered and a negative impact on people with diabetes was observed by healthcare providers. Despite healthcare providers' feeling overloaded, mental wellbeing seemed unaffected. Video consultations were seen as having potential. Given the remaining covid-19 risks and from the interest of proactive management of people with diabetes, these findings urge for further exploration of incorporating video consultation in diabetes care.