Search results for: COVID-19 pandemic
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1075

Search results for: COVID-19 pandemic

535 DenseNet and Autoencoder Architecture for COVID-19 Chest X-Ray Image Classification and Improved U-Net Lung X-Ray Segmentation

Authors: Jonathan Gong

Abstract:

Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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534 Rapid Detection System of Airborne Pathogens

Authors: Shigenori Togashi, Kei Takenaka

Abstract:

We developed new processes which can collect and detect rapidly airborne pathogens such as the avian flu virus for the pandemic prevention. The fluorescence antibody technique is known as one of high-sensitive detection methods for viruses, but this needs up to a few hours to bind sufficient fluorescence dyes to viruses for detection. In this paper, we developed a mist-labeling can detect substitution viruses in a short time to improve the binding rate of fluorescent dyes and substitution viruses by the micro reaction process. Moreover, we developed the rapid detection system with the above 'mist labeling'. The detection system set with a sampling bag collecting patient’s breath and a cartridge can detect automatically pathogens within 10 minutes.

Keywords: viruses, sampler, mist, detection, fluorescent dyes, microreaction

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533 Tagging a corpus of Media Interviews with Diplomats: Challenges and Solutions

Authors: Roberta Facchinetti, Sara Corrizzato, Silvia Cavalieri

Abstract:

Increasing interconnection between data digitalization and linguistic investigation has given rise to unprecedented potentialities and challenges for corpus linguists, who need to master IT tools for data analysis and text processing, as well as to develop techniques for efficient and reliable annotation in specific mark-up languages that encode documents in a format that is both human and machine-readable. In the present paper, the challenges emerging from the compilation of a linguistic corpus will be taken into consideration, focusing on the English language in particular. To do so, the case study of the InterDiplo corpus will be illustrated. The corpus, currently under development at the University of Verona (Italy), represents a novelty in terms both of the data included and of the tag set used for its annotation. The corpus covers media interviews and debates with diplomats and international operators conversing in English with journalists who do not share the same lingua-cultural background as their interviewees. To date, this appears to be the first tagged corpus of international institutional spoken discourse and will be an important database not only for linguists interested in corpus analysis but also for experts operating in international relations. In the present paper, special attention will be dedicated to the structural mark-up, parts of speech annotation, and tagging of discursive traits, that are the innovational parts of the project being the result of a thorough study to find the best solution to suit the analytical needs of the data. Several aspects will be addressed, with special attention to the tagging of the speakers’ identity, the communicative events, and anthropophagic. Prominence will be given to the annotation of question/answer exchanges to investigate the interlocutors’ choices and how such choices impact communication. Indeed, the automated identification of questions, in relation to the expected answers, is functional to understand how interviewers elicit information as well as how interviewees provide their answers to fulfill their respective communicative aims. A detailed description of the aforementioned elements will be given using the InterDiplo-Covid19 pilot corpus. The data yielded by our preliminary analysis of the data will highlight the viable solutions found in the construction of the corpus in terms of XML conversion, metadata definition, tagging system, and discursive-pragmatic annotation to be included via Oxygen.

Keywords: spoken corpus, diplomats’ interviews, tagging system, discursive-pragmatic annotation, english linguistics

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532 Going the Distance – Building Peer Support during a Time of Crisis

Authors: Lisa Gray, Henry Kronner, Tameca Harris-Jackson, Mimi Sodhi, Ruth Gerritsen-McKane, Donette Considine

Abstract:

The MSW Peer Mentorship Program (PMP) was developed as one of several approaches to foster student success. The key purposes of the PMP are to help new graduate students transition to a graduate program, facilitate relationship building between students, grow and sustain student satisfaction, and build a strong connection to the MSW program. This pilot program also serves as an additional source of support for students during the era of the Covid-19 pandemic. Further, the long-term goals of the program are to assist in student retention. Preliminary findings suggest that both mentors and mentees enrolled in PMP find the peer mentoring relationship to have a positive impact on their graduate learning experience.

Keywords: covid-19, mentorship, peer support, student success

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531 The Impact of COVID-19 on Women’s Health in Bangladesh

Authors: Dil Ware Alam, Faiza Zebeen, Sumaya Binte Masud

Abstract:

COVID-19) has impacted the whole world, including Bangladesh. The epidemic has reduced access to health care, particularly for women, creating challenges for an increasingly disadvantaged population. Women's health and well-being in Bangladesh are susceptible to a rise in domestic violence and need to be addressed quickly. The planet has been greatly influenced by Coronavirus disease 2019 (COVID-19), and Bangladesh is no difference. The pandemic has resulted in a decline in the availability of health care, notably for women's health problems, leading to an increase in difficulties for an increasingly marginalized group. Maternity care, maternal health programs, medical interventions, nutritional counseling and mental health care, are not discussed, and women's health and well-being in Bangladesh is vulnerable with a spike in domestic violence and needs to be resolved urgently.

Keywords: Covid-19, mental health, reproductive health, Bangladesh

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530 4P-Model of Information Terrorism

Authors: Nataliya Venelinova

Abstract:

The paper proposes a new interdisciplinary model of reconsidering the role of mass communication effects by coverage of terrorism. The idea of 4P model is based on the synergy, created by the information strategy of threat, predominantly used by terrorist groups, the effects of mediating the symbolic action of the terrorist attacks or the taking of responsibility of any attacks, and the reshaped public perception for security after the attacks being mass communicated. The paper defines the mass communication cycle of terrorism, which leads not only to re-agenda setting of the societies, but also spirally amplifying the effect of propagating fears by over-informing on terrorism attacks. This finally results in the outlining of the so called 4P-model of information terrorism: mass propaganda, panic, paranoia and pandemic.

Keywords: information terrorism, mass communication cycle, public perception, security

Procedia PDF Downloads 166
529 Digitalized Public Sector Practices: Opportunities for Open Innovation in Rwanda

Authors: Reem Abou Refaie, Christoph Meinel

Abstract:

The paper explores the impact of the COVID-19 crisis on the internal as well as external digitalized work practices of public service providers as part of a Public-Private Partnership Model. It focuses on the effect of uncertainty on generating Open Innovation practices. Our inquiry relies on semi-structured interviews (n=14) from a case study of Rwanda’s Public Service Delivery System in the context of research cooperation with IremboGov, the country’s One-Stop-Shop Platform for public services. It presents four propositions on harnessing opportunities for OI in the context of the public sector beyond the pandemic response. Practitioners can find characterizations of OI opportunities and gain insights on fostering OI in Public Sector Organizations.

Keywords: open innovation, digital transformation, public sector, Rwanda

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528 Circular Economy in Relation to Waste Management Development

Authors: Kwok Tak Kit

Abstract:

Construction and demolition (C&D) waste generated in the process of urbanization which only contribute to approx. 25–35 per cent of municipal solid waste (MSW), and the action to reduce the generation of other MSW is considered more critical. Developed and cities produce a higher percentage of inorganic waste rather than organic waste. Most of the MSW was disposed in landfill, and a large number of the landfills are not effectively and efficiently operated to receive the untreated incoming waste. It is also a global problem that the demands for enhancement of basic infrastructure for waste collection, treatment, and disposal, including rehabilitation of the dump sites, is the urgent priority. This paper is to review the factors taken into consideration of waste management development in relation to circular economy development on development countries and green recovery in the post-pandemic era for further researches use.

Keywords: waste management, waste reduction, circular economy, developed countries, sustainable design goals

Procedia PDF Downloads 132
527 The Role of Validity and Reliability in the Development of Online Testing

Authors: Ani Demetrashvili

Abstract:

The purpose of this paper is to show how students trust online tests and determine validity and reliability in the development of online testing. The pandemic situation changed every field in the world, and it changed education as well. Educational institutions moved into the online space, which was the only decision they were able to make at that time. Online assessment through online proctoring was a totally new challenge for educational institutions, and they needed to deal with it successfully. Participants were chosen from the English language center. The validity of the questionnaire was identified according to the Likert scale and Cronbach’s alpha; later, data from the participants was analyzed as well. The article summarizes literature that is available about online assessment and is interesting for people who are interested in this kind of assessment. Based on the research findings, students favor in-person testing over online assessment due to their lack of experience and skills in the latter.

Keywords: online assessment, online proctoring

Procedia PDF Downloads 33
526 COVID-19, Employee Perspectives, and the Shifting Nature of Work

Authors: Jonathan H. Westover, Maureen S. Andrade, Angela Schill, Jeff Peterson, Samuel Choi

Abstract:

The purpose of this research is to understand employee perspectives on their work characteristics and conditions, particularly related to the COVID-19 pandemic and the future of work. Working conditions impact job satisfaction. People tend to measure job satisfaction by comparing aspects of the job they have with those they want. Job satisfaction is related to the value that one places on specific aspects of a job, such as autonomy, pay and benefits, challenge, growth, or meaningful work, and the degree to which such elements are present. The value one places on these various job characteristics may differ based on gender, age, personality, occupation, context, or other factors. This study will examine various job characteristics and working conditions with an emphasis on COVID-19 to determine how managers and leaders and better support and develop their employees.

Keywords: COVID-19, employee perspectives nature of work, future of work

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525 COVID-19: A Thread to the Security System of Foreign Investment

Authors: Mehdi Ghaemi

Abstract:

In principle, foreign investment security is enshrined in International Investment Agreements (IIAs) and Bilateral Investment Treaties (BITs) in the form of protection standards such as the Full Protection and Security Standard (FPS). Accordingly, the host countries undertake to provide the necessary security for the economic activities of foreign investment. With the outbreak of coronavirus, the international community called COVID-19 a threat to international peace security, as well as to the public interest and national security of nations; and to deal with, they proposed several solutions, generally including quarantine, creating social distances, and restricting businesses. This article first studies the security of foreign investment in international investment law. In the following, it analyzes the consequences of the COVID-19 pandemic for foreign investment security so that if there is a threat to that security, solutions could be offered to reduce it.

Keywords: foreign investment, FPS standard, host country, public health, COVID-19

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524 Working From Home: On the Relationship Between Place Attachment to Work Place, Extraversion and Segmentation Preference to Burnout

Authors: Diamant Irene, Shklarnik Batya

Abstract:

In on to its widespread effects on health and economic issues, Covid-19 shook the work and employment world. Among the prominent changes during the pandemic is the work-from-home trend, complete or partial, as part of social distancing. In fact, these changes accelerated an existing tendency of work flexibility already underway before the pandemic. Technology and means of advanced communications led to a re-assessment of “place of work” as a physical space in which work takes place. Today workers can remotely carry out meetings, manage projects, work in groups, and different research studies point to the fact that this type of work has no adverse effect on productivity. However, from the worker’s perspective, despite numerous advantages associated with work from home, such as convenience, flexibility, and autonomy, various drawbacks have been identified such as loneliness, reduction of commitment, home-work boundary erosion, all risk factors relating to the quality of life and burnout. Thus, a real need has arisen in exploring differences in work-from-home experiences and understanding the relationship between psychological characteristics and the prevalence of burnout. This understanding may be of significant value to organizations considering a future hybrid work model combining in-office and remote working. Based on Hobfoll’s Theory of Conservation of Resources, we hypothesized that burnout would mainly be found among workers whose physical remoteness from the workplace threatens or hinders their ability to retain significant individual resources. In the present study, we compared fully remote and partially remote workers (hybrid work), and we examined psychological characteristics and their connection to the formation of burnout. Based on the conceptualization of Place Attachment as the cognitive-emotional bond of an individual to a meaningful place and the need to maintain closeness to it, we assumed that individuals characterized with Place Attachment to the workplace would suffer more from burnout when working from home. We also assumed that extrovert individuals, characterized by the need of social interaction at the workplace and individuals with segmentationpreference – a need for separation between different life domains, would suffer more from burnout, especially among fully remote workers relative to partially remote workers. 194 workers, of which 111 worked from home in full and 83 worked partially from home, aged 19-53, from different sectors, were tested using an online questionnaire through social media. The results of the study supported our assumptions. The repercussions of these findings are discussed, relating to future occupational experience, with an emphasis on suitable occupational adjustment according to the psychological characteristics and needs of workers.

Keywords: working from home, burnout, place attachment, extraversion, segmentation preference, Covid-19

Procedia PDF Downloads 187
523 The Incubation of University Spin-Offs: An Exploratory Study of a Deep Tech Venture

Authors: Jerome D. Donovan

Abstract:

The pandemic has resulted in a dramatic re-consideration of the reliance on international student fees to support university models in Australia. A key resulting initiative for the Australian Federal Government has been shifting the way universities consider their research model, emphasising the importance of commercialising research. This study specifically examines this shift from the perspective of a university spin-off, examining how university support structures and incubation models have assisted in the translation of fundamental research into a high-growth university spin-off. A focused case study approach is adopted in this study, using an auto-ethnographic research method to document the experiences and insights drawn from being a co-founder in a university spin-off in a time where research commercialisation has emerged as a central focus in Australian universities.

Keywords: research commercialisation, spin-offs, university incubation, entrepreneurship

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522 Agile Succession Planning in the Post-Covid World

Authors: Ashneel Kumar Singh

Abstract:

The COVID-19 pandemic has dramatically transformed the global workforce, leading to significant challenges in staffing and employment. The shift to remote work, the health risks posed by the virus, and the phenomenon known as ‘The Great Termination’ have all contributed to the disruption of traditional succession planning methods. This paper explores how agile succession planning can be effectively implemented in the post-COVID world to retain top talent and ensure organizational resilience. Through a review of the literature and practical examples, the paper discusses the difficulties of succession planning in the current environment and the importance of adopting an agile approach and offers recommendations for businesses to navigate the complexities of succession planning in a rapidly changing landscape.

Keywords: agile succession planning, adopt a culture of continuous learning, create a multi-successor planning approach, the great termination

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521 A Systematic Review of Chronic Neurologic Complications of COVID-19; A Potential Risk Factor for Narcolepsy, Parkinson's Disease, and Multiple Sclerosis.

Authors: Sulemana Saibu, Moses Ikpeme

Abstract:

Background: The severity of the COVID-19 pandemic, brought on by the SARS-CoV-2 coronavirus, has been unprecedented since the 1918 influenza pandemic. SARS-CoV-2 cases of CNS and peripheral nervous system disease, including neurodegenerative disorders and chronic immune-mediated diseases, may be anticipated based on knowledge of past coronaviruses, particularly those that caused the severe acute respiratory syndrome and Middle East respiratory syndrome outbreaks. Although respiratory symptoms are the most common clinical presentation, neurological symptoms are becoming increasingly recognized, raising concerns about their potential role in causing Parkinson's disease, Multiple sclerosis, and Narcolepsy. This systematic review aims to summarize the current evidence by exploring the association between COVID-19 infection and how it may overlap with etiological mechanisms resulting in Narcolepsy, Parkinson's disease, and Multiple sclerosis. Methods: A systematic search was conducted using electronic databases ((PubMed/MedLine, Embase, PsycINFO, ScieLO, Web of Science, ProQuest (Biotechnology, Virology, and AIDS), Scopus, and CINAHL)) to identify studies published between January 2020 and December 2022 that investigated the association between COVID-19 and Parkinson's disease, multiple sclerosis, and Narcolepsy. Per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the review was performed and reported. Study quality was assessed using the Critical Appraisal Skills Programme Checklist and the Joanna Briggs Institute Critical appraisal tools. Results: A total of 21 studies out of 1025 met the inclusion criteria, including 8 studies reporting Parkinson's disease, 11 on multiple sclerosis, and 2 on Narcolepsy. In COVID-19 individuals compared to the general population, Narcolepsy, Parkinson's disease, and multiple sclerosis were shown to have a higher incidence. The findings imply that COVID-19 may worsen the signs or induce multiple sclerosis and Parkinson's disease and may raise the risk of developing Narcolepsy. Further research is required to confirm these connections because the available data is insufficient. Conclusion: According to the existing data, COVID-19 may raise the risk of Narcolepsy and have a causative relationship with Parkinson's disease, multiple sclerosis, and other diseases. More study is required to confirm these correlations and pinpoint probable mechanisms behind these interactions. Clinicians should be aware of how COVID-19 may affect various neurological illnesses and should treat patients who are affected accordingly.

Keywords: COVID-19, parkinson’s disease, multiple sclerosis, narcolepsy, neurological disorders, sars-cov-2, neurodegenerative disorders, chronic immune-mediated diseases

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520 A Review of How COVID-19 Has Created an Insider Fraud Pandemic and How to Stop It

Authors: Claire Norman-Maillet

Abstract:

Insider fraud, including its various synonyms such as occupational, employee or internal fraud, is a major financial crime threat whereby an employee defrauds (or attempts to defraud) their current, prospective, or past employer. ‘Employee’ covers anyone employed by the company, including contractors, directors, and part time staff; they may be a solo bad actor or working in collusion with others, whether internal or external. Insider fraud is even more of a concern given the impacts of the Coronavirus pandemic, which has generated multiple opportunities to commit insider fraud. Insider fraud is something that is not necessarily thought of as a significant financial crime threat; the focus of most academics and practitioners has historically been on that of ‘external fraud’ against businesses or entities where an individual or group has no professional ties. Without the face-to-face, ‘over the shoulder’ capabilities of staff being able to keep an eye on their employees, there is a heightened reliance on trust and transparency. With this, naturally, comes an increased risk of insider fraud perpetration. The objective of the research is to better understand how companies are impacted by insider fraud, and therefore how to stop it. This research will make both an original contribution and stimulate debate within the financial crime field. The financial crime landscape is never static – criminals are always creating new ways to perpetrate financial crime, and new legislation and regulations are implemented as attempts to strengthen controls, in addition to businesses doing what they can internally to detect and prevent it. By focusing on insider fraud specifically, the research will be more specific and will be of greater use to those in the field. To achieve the aims of the research, semi-structured interviews were conducted with 22 individuals who either work in financial services and deal with insider fraud or work within insider fraud perpetration in a recruitment or advisory capacity. This was to enable the sourcing of information from a wide range of individuals in a setting where they were able to elaborate on their answers. The principal recruitment strategy was engaging with the researcher’s network on LinkedIn. The interviews were then transcribed and analysed thematically. Main findings in the research suggest that insider fraud has been ignored owing to the denial of accepting the possibility that colleagues would defraud their employer. Whilst Coronavirus has led to a significant rise in insider fraud, this type of crime has been a major risk to businesses since their inception, however have never been given the financial or strategic backing required to be mitigated, until it's too late. Furthermore, Coronavirus should have led to companies tightening their access rights, controls and policies to mitigate the insider fraud risk. However, in most cases this has not happened. The research concludes that insider fraud needs to be given a platform upon which to be recognised as a threat to any company and given the same level of weighting and attention by Executive Committees and Boards as other types of economic crime.

Keywords: fraud, insider fraud, economic crime, coronavirus, Covid-19

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519 ‘Nature Will Slow You Down for a Reason’: Virtual Elder-Led Support Services during COVID-19

Authors: Grandmother Roberta Oshkawbewisens, Elder Isabelle Meawasige, Lynne Groulx, Chloë Hamilton, Lee Allison Clark, Dana Hickey, Wansu Qiu, Jared Leedham, Nishanthini Mahendran, Cameron Maclaine

Abstract:

In March of 2020, the world suddenly shifted with the onset of the COVID-19 pandemic; in-person programs and services were unavailable and a scramble to shift to virtual service delivery began. The Native Women’s Association of Canada (NWAC) established virtual programming through the Resiliency Lodge model and connected with Indigenous women, girls, Two-Spirit, transgender, and gender-diverse people across Turtle Island and Inuit Nunangat through programs that provide a safe space to slow down and reflect on their lives, environment, and well-being. To continue to grow the virtual Resiliency Lodge model, NWAC needed to develop an understanding of three questions: how COVID-19 affects Elder-led support services, how Elder-led support services have adapted during the pandemic, and what Wise Practices need to be implemented to continue to develop, refine, and evaluate virtual Elder-led support services specifically for Indigenous women, girls, two-Spirit, transgender, and gender-diverse people. Through funding from the Canadian Institute of Health Research (CIHR), NWAC gained deeper insight into these questions and developed a series of key findings and recommendations that are outlined throughout this report. The goals of this project are to contribute to a more robust participatory analysis that reflects the complexities of Elder-led virtual cultural responses and the impacts of COVID-19 on Elder-led support services; develop culturally and contextually meaningful virtual protocols and wise practices for virtual Indigenous-led support; and develop an Evaluation Strategy to improve the capacity of the Resiliency Lodge model. Significant findings from the project include Resiliency Lodge programs, especially crafting and business sessions, have provided participants with a sense of community and contributed to healing and wellness; Elder-led support services need greater and more stable funding to offer more workshops to more Indigenous women, girls, Two-Spirit, transgender, and gender-diverse people; and Elder- and Indigenous-led programs play a significant role in healing and building a sense of purpose and belonging among Indigenous people. Ultimately, the findings and recommendations outlined in this research project help to guide future Elder-led virtual support services and emphasize the critical need to increase access to Elder-led programming for Indigenous women, girls, Two-Spirit, transgender, and gender-diverse people.

Keywords: indigenous women, traditional healing, virtual programs, covid-19

Procedia PDF Downloads 133
518 The Outcome of Using Machine Learning in Medical Imaging

Authors: Adel Edwar Waheeb Louka

Abstract:

Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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517 An Examination of Crisis Communication in Sport: Lessons from Sport Organizations Responding to Coronavirus Disease Outbreak

Authors: Geumchan Hwang

Abstract:

Professional sport leagues in Europe and North America are shut down due to novel coronavirus disease (COVID-19) outbreak. Football leagues in Europe (e.g., La Liga, English Premier League, Bundesliga, Serie A, and Ligue 1) and big four professional sport leagues in North America (e.g., National Football League, Major League Baseball, National Basketball Association, and National Hockey League) are indefinitely suspended or delayed. COVID-19 outbreak has a growing negative impact on economics of sport leagues. For example, loss of revenue in Europe’s top five leagues due to the COVID-19 pandemic was estimated at € 4 billion and loss of revenue in the NBA was estimated at $650 million as of March 2020. In the unprecedented difficult situation, sport teams and leagues try to communicate with sport fans through diverse media platforms. In sport, however, very few studies have been done regarding how sport organizations effectively communicate with sport fans during pandemics, such as COVID-19 outbreak. Understanding sport organizations’ crisis communication is important to develop effective crisis management strategies for sport organizations. Therefore, the purpose of the study is to examine how sport organizations communicate with sport fans via online platforms in COVID-19 outbreak and how sport fans evaluate their communication strategies. 9 official sport league sites (i.e., five major football leagues in Europe and four major sport leagues in North America) and COVID-19 news articles published between January and June in 2020 will be analyzed in terms of coronavirus information, teams and players’ live update, fan interaction, fan support, and community engagement. In addition, comments posted on social media sites (i.e., Facebook and Twitter) of major sport leagues will be also analyzed to examine how sport fans perceive online messages provided by sport leagues as an effective communication strategy. To measure the effectiveness of crisis communication performance, five components (i.e., prompt, compassionate, honest, informative, and interactive) of crisis communication will be collected from leagues’ official websites information and social media posts. Upon completing data collection, content analysis method will be used to evaluate effectiveness of crisis communication among 9 professional sport leagues. The results of the study will provide athletic directors, administrators, and public relations managers in sport organizations with practical information regarding how athlete celebrities and sport organizations should interact with their fans in pandemic situations. In particular, this study will contribute to developing specific crisis management plan for sport organizations. For instance, football teams and leagues in Europe will be able to create standard manuals to minimize damages caused by disease outbreak, such as COVID-19 outbreak.

Keywords: COVID-19, communication, sport leagues, fans

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516 DeClEx-Processing Pipeline for Tumor Classification

Authors: Gaurav Shinde, Sai Charan Gongiguntla, Prajwal Shirur, Ahmed Hambaba

Abstract:

Health issues are significantly increasing, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly. We introduce DeClEx, a pipeline that ensures that data mirrors real-world settings by incorporating Gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state-of-the-art pre-trained models while achieving a threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification, and explainability in a single pipeline called DeClEx.

Keywords: machine learning, healthcare, classification, explainability

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515 Homeless Population Modeling and Trend Prediction Through Identifying Key Factors and Machine Learning

Authors: Shayla He

Abstract:

Background and Purpose: According to Chamie (2017), it’s estimated that no less than 150 million people, or about 2 percent of the world’s population, are homeless. The homeless population in the United States has grown rapidly in the past four decades. In New York City, the sheltered homeless population has increased from 12,830 in 1983 to 62,679 in 2020. Knowing the trend on the homeless population is crucial at helping the states and the cities make affordable housing plans, and other community service plans ahead of time to better prepare for the situation. This study utilized the data from New York City, examined the key factors associated with the homelessness, and developed systematic modeling to predict homeless populations of the future. Using the best model developed, named HP-RNN, an analysis on the homeless population change during the months of 2020 and 2021, which were impacted by the COVID-19 pandemic, was conducted. Moreover, HP-RNN was tested on the data from Seattle. Methods: The methodology involves four phases in developing robust prediction methods. Phase 1 gathered and analyzed raw data of homeless population and demographic conditions from five urban centers. Phase 2 identified the key factors that contribute to the rate of homelessness. In Phase 3, three models were built using Linear Regression, Random Forest, and Recurrent Neural Network (RNN), respectively, to predict the future trend of society's homeless population. Each model was trained and tuned based on the dataset from New York City for its accuracy measured by Mean Squared Error (MSE). In Phase 4, the final phase, the best model from Phase 3 was evaluated using the data from Seattle that was not part of the model training and tuning process in Phase 3. Results: Compared to the Linear Regression based model used by HUD et al (2019), HP-RNN significantly improved the prediction metrics of Coefficient of Determination (R2) from -11.73 to 0.88 and MSE by 99%. HP-RNN was then validated on the data from Seattle, WA, which showed a peak %error of 14.5% between the actual and the predicted count. Finally, the modeling results were collected to predict the trend during the COVID-19 pandemic. It shows a good correlation between the actual and the predicted homeless population, with the peak %error less than 8.6%. Conclusions and Implications: This work is the first work to apply RNN to model the time series of the homeless related data. The Model shows a close correlation between the actual and the predicted homeless population. There are two major implications of this result. First, the model can be used to predict the homeless population for the next several years, and the prediction can help the states and the cities plan ahead on affordable housing allocation and other community service to better prepare for the future. Moreover, this prediction can serve as a reference to policy makers and legislators as they seek to make changes that may impact the factors closely associated with the future homeless population trend.

Keywords: homeless, prediction, model, RNN

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514 The Affordances and Challenges of Online Learning and Teaching for Secondary School Students

Authors: Hahido Samaras

Abstract:

In many cases, especially with the pandemic playing a major role in fast-tracking the growth of the digital industry, online learning has become a necessity or even a standard educational model nowadays, reliably overcoming barriers such as location, time and cost and frequently combined with a face-to-face format (e.g., in blended learning). This being the case, it is evident that students in many parts of the world, as well as their parents, will increasingly need to become aware of the pros and cons of online versus traditional courses. This fast-growing mode of learning, accelerated during the years of the pandemic, presents an abundance of exciting options especially matched for a large number of secondary school students in remote places of the world where access to stimulating educational settings and opportunities for a variety of learning alternatives are scarce, adding advantages such as flexibility, affordability, engagement, flow and personalization of the learning experience. However, online learning can also present several challenges, such as a lack of student motivation and social interactions in natural settings, digital literacy, and technical issues, to name a few. Therefore, educational researchers will need to conduct further studies focusing on the benefits and weaknesses of online learning vs. traditional learning, while instructional designers propose ways of enhancing student motivation and engagement in virtual environments. Similarly, teachers will be required to become more and more technology-capable, at the same time developing their knowledge about their students’ particular characteristics and needs so as to match them with the affordances the technology offers. And, of course, schools, education programs, and policymakers will have to invest in powerful tools and advanced courses for online instruction. By developing digital courses that incorporate intentional opportunities for community-building and interaction in the learning environment, as well as taking care to include built-in design principles and strategies that align learning outcomes with learning assignments, activities, and assessment practices, rewarding academic experiences can derive for all students. This paper raises various issues regarding the effectiveness of online learning on students by reviewing a large number of research studies related to the usefulness and impact of online learning following the COVID-19-induced digital education shift. It also discusses what students, teachers, decision-makers, and parents have reported about this mode of learning to date. Best practices are proposed for parties involved in the development of online learning materials, particularly for secondary school students, as there is a need for educators and developers to be increasingly concerned about the impact of virtual learning environments on student learning and wellbeing.

Keywords: blended learning, online learning, secondary schools, virtual environments

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513 China’s Health Silk Road in Southeast Asia and Europe during COVID-19

Authors: Wanda Luen-Wun Siu, Xiaowen Zhang

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The COVID-19 pandemic has presented an opportune time for China to deploy its health diplomacy around the world. This paper focused on China’s health diplomacy along the path of its Health Silk Road, with particular emphasis on the Middle East and Europe amid COVID-19. This paper employed a retrospective literature review, analyzed China’s health diplomacy in such regions to cultivate bilateral and multilateral relationships. And findings argued that such health diplomacy is a success, and Beijing has assumed a leadership role in the world’s health governance. This research contributes to the literature in health diplomacy and suggests that amid the ever changing international order, China has exerted great effort in its health diplomacy and established itself as a responsible world power.

Keywords: china’s health silk road, COVID-19, europe, middle east

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512 Burden of Cardiovascular Diseases in Dubrovnik- Neretva County 2018-2021

Authors: Tarnai Tena, Strinić Dean

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Chronic non-communicable diseases are today the leading cause of mortality, morbidity and mortality disability at the world level and in Croatia. Among them are the most represented precisely cardiovascular diseases (CVD), so today we are talking about their global card epidemic. From 2018 to 2021, cardiovascular diseases are the leading cause of death for both women and men in the Dubrovnik- Neretva County. With regard to the COVID-19 pandemic, which has taken over, without forgetting how much these patients are additionally affected, we are still talking about the primary cause of sickness and death in the population of this county and region. In this record, we present collected data processed according to gender and disease classification. We also bring a kind of overview because, for years, we have been following how the population of one of the origins of the Mediterranean diet has been struggling with cardiovascular diseases.

Keywords: cardiovascular disease, burden, COVID-19, epidemiology, ishemic heart disease, cardiovascular medicine

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511 The Impact of Political Polarization on the COVID-19 Vaccine Hesitancy in the United States: A Qualitative Study

Authors: Peiran Ma

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This study explored the role of political polarization in an individual's decision of receiving the COVID-19 vaccine. A total of 15 participants participated in individual interviews and focus group discussions about the relationships among domestic political polarization, vaccine hesitancy, and behavioral responses to the COVID-19 pandemic. Political affiliation affected an individual’s decision on the COVID-19 vaccination, such that people who identified as Liberals and Democrats were more accepting of the vaccine. On the other hand, the level of influence declined over time (2020-2022) when the general conception of COVID-19 immunization shifted from political to personal. Results provided qualitative support to the previously identified positive relationship between divided political opinions and COVID-19 vaccine hesitancy and highlighted the decreasing trend in the power of political polarization in vaccination and the existence of other factors.

Keywords: COVID-19, vaccine hesitancy, political polarization, partisanship, ideology

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510 Students’ Speech Anxiety in Blended Learning

Authors: Mary Jane B. Suarez

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Public speaking anxiety (PSA), also known as speech anxiety, is innumerably persistent in any traditional communication classes, especially for students who learn English as a second language. The speech anxiety intensifies when communication skills assessments have taken their toll in an online or a remote mode of learning due to the perils of the COVID-19 virus. Both teachers and students have experienced vast ambiguity on how to realize a still effective way to teach and learn speaking skills amidst the pandemic. Communication skills assessments like public speaking, oral presentations, and student reporting have defined their new meaning using Google Meet, Zoom, and other online platforms. Though using such technologies has paved for more creative ways for students to acquire and develop communication skills, the effectiveness of using such assessment tools stands in question. This mixed method study aimed to determine the factors that affected the public speaking skills of students in a communication class, to probe on the assessment gaps in assessing speaking skills of students attending online classes vis-à-vis the implementation of remote and blended modalities of learning, and to recommend ways on how to address the public speaking anxieties of students in performing a speaking task online and to bridge the assessment gaps based on the outcome of the study in order to achieve a smooth segue from online to on-ground instructions maneuvering towards a much better post-pandemic academic milieu. Using a convergent parallel design, both quantitative and qualitative data were reconciled by probing on the public speaking anxiety of students and the potential assessment gaps encountered in an online English communication class under remote and blended learning. There were four phases in applying the convergent parallel design. The first phase was the data collection, where both quantitative and qualitative data were collected using document reviews and focus group discussions. The second phase was data analysis, where quantitative data was treated using statistical testing, particularly frequency, percentage, and mean by using Microsoft Excel application and IBM Statistical Package for Social Sciences (SPSS) version 19, and qualitative data was examined using thematic analysis. The third phase was the merging of data analysis results to amalgamate varying comparisons between desired learning competencies versus the actual learning competencies of students. Finally, the fourth phase was the interpretation of merged data that led to the findings that there was a significantly high percentage of students' public speaking anxiety whenever students would deliver speaking tasks online. There were also assessment gaps identified by comparing the desired learning competencies of the formative and alternative assessments implemented and the actual speaking performances of students that showed evidence that public speaking anxiety of students was not properly identified and processed.

Keywords: blended learning, communication skills assessment, public speaking anxiety, speech anxiety

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509 Fostering a Sense of Belonging in Hybrid Teams

Authors: Jam Harley

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The COVID-19 epidemic accelerated the speed of change in the workplace. Overnight, several individuals shifted from co-location in an office to hybrid or remote work. The pandemic also expedited and intensified the need to address persistent leadership and management concerns, including digital transformation, remote management, leading through fast change, anxiety, and uncertainty. Nonetheless, many leaders have failed to address the problems left behind by the epidemic. In a fundamental work devoted to comprehending what constitutes a human need, Maslow reiterates similar descriptors in his explanation of belongingness as the human need to be accepted, acknowledged, respected, and appreciated by a community of other individuals. This study aims to investigate the lived experiences of dispersed hybrid team members in order to find leadership best practices that improve team performance and retention through an increased individual’s sense of belonging.

Keywords: organizational change, belonging, diversity, equity

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508 Household Choice of Working from Home before and after COVID-19

Authors: Ravipa Rojasavachai, Li Yang

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Working from home has become a global phenomenon after the coronavirus outbreak, and most employees have a choice to choose between working from home or the office. In this paper, we examine the demographics and socio-economics factors influencing individuals’ decision to choose working from home rather than the office before and after the coronavirus outbreak based on Australian household data. We find that all factors impact the working from home choice before the coronavirus outbreak, but the number of children turns to an uninfluenced factor on individuals’ choices after the outbreak. We also find that female employees have a higher probability of choosing to work from home after the coronavirus outbreak. This is because they have less concern for their career opportunities and higher wage premium of working from home due to the changing in cultural norms and advanced working from home technologies in companies after the coronavirus outbreak.

Keywords: work from home, telework, remote working, COVID-19, pandemic, wage

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507 The Role of the Indonesian Armed Forces to Combat Terrorism Acts During the COVID 19 Pandemic Era

Authors: Aulia Rosa Nasution

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This research aims to analyze the involvement of the Indonesian Armed Forces in overcoming terrorism acts under legal perspectives based on Acts No. 34 of 2004, which regulates the role and mechanism of the Indonesian Armed Forces in combating terrorism. The main question of this research is, firstly, the military authority in combating terrorism acts, secondly, the implementation of Acts Number 34/2000, and thirdly, law enforcement to combat terrorism under national and international law. The methodology of this research is juridical normative based on the legal instruments and legal principles, and international norms. The result of this study explains the involvement of the Indonesian Army in combating terrorism as a part of the nonmilitary operation which has been implemented in Indonesia as part of national defence and security.

Keywords: acts of terrorism, Indonesian armed forces, legal protection

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506 Women Entrepreneurial Resiliency Amidst COVID-19

Authors: Divya Juneja, Sukhjeet Kaur Matharu

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Purpose: The paper is aimed at identifying the challenging factors experienced by the women entrepreneurs in India in operating their enterprises amidst the challenges posed by the COVID-19 pandemic. Methodology: The sample for the study comprised 396 women entrepreneurs from different regions of India. A purposive sampling technique was adopted for data collection. Data was collected through a self-administered questionnaire. Analysis was performed using the SPSS package for quantitative data analysis. Findings: The results of the study state that entrepreneurial characteristics, resourcefulness, networking, adaptability, and continuity have a positive influence on the resiliency of women entrepreneurs when faced with a crisis situation. Practical Implications: The findings of the study have some important implications for women entrepreneurs, organizations, government, and other institutions extending support to entrepreneurs.

Keywords: women entrepreneurs, analysis, data analysis, positive influence, resiliency

Procedia PDF Downloads 107