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At the beginning of 2020, the World Health Organization (WHO) started a coordinated global effort to counterattack the potential exponential spread of the SARS-Cov2 virus, responsible for the coronavirus disease, officially named COVID-19. This comprehensive initiative included a research roadmap published in March 2020, including nine dimensions, from epidemiological research to diagnostic tools and vaccine development. With an unprecedented case, the areas of study related to the pandemic received funds and strong attention from different research communities (universities, government, industry, etc.), resulting in an exponential increase in the number of publications and results achieved in such a small window of time. Outstanding research cooperation projects were implemented during the outbreak, and innovative technologies were developed and improved significantly. Clinical and laboratory processes were improved, while managerial personnel were supported by a countless number of models and computational tools for the decision-making process. This chapter aims to introduce an overview of this favorable scenario and highlight a necessary discussion about ethical issues in research related to the COVID-19 and the challenge of low-quality research, focusing only on the publication of techniques and approaches with limited scientific evidence or even practical application. A legacy of lessons learned from this unique period of human history should influence and guide the scientific and industrial communities for the future. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
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MIDRC was created to facilitate machine learning research for tasks including early detection, diagnosis, prognosis, and assessment of treatment response related to the COVID-19 pandemic and beyond. The purpose of the Technology Development Project (TDP) 3c is to create resources to assist researchers in evaluating the performance of their machine learning algorithms. An interactive decision tree has been developed, organized by the type of task that the machine learning algorithm is being trained to perform. The user can select information such as: (a) the type of task, (b) the nature of the reference standard, and (c) the type of the algorithm output. Based on the user responses, they can obtain recommendations regarding appropriate performance evaluation approaches and metrics, including literature references, short video tutorials, and links to available software. Five tasks have been identified for the decision tree: (a) classification, (b) detection/localization, (c) segmentation, (d) time-to-event analysis, and (e) estimation. As an example, the classification branch of the decision tree includes binary and multi-class classification tasks and provides suggestions for methods and metrics as well as software recommendations, and literature references for situations where the algorithm produces either binary or non-binary (e.g., continuous) output and for reference standards with negligible or non-negligible variability and unreliability. The decision tree has been made publicly available on the MIDRC website to assist researchers in conducting task-specific performance evaluations, including classification, detection/localization, segmentation, estimation, and time-to-event tasks. © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.
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Purpose --The main purpose of this research work is to evaluate the efforts of TVET efforts' in developing and transferring useful technologies in Addis-Ababa, Ethiopia. TVET Institutions are engaged in developing and transferring technologies like hand washing devices, sanitizer sprayers, ventilators, beds, disinfection devices, sanitizers, antiviral finish fabrics, masks and hand-free devices that is used to prevent contamination of the human body while working with materials of different kinds. These equipment's posse's characteristic simple operational and quality properties like usability, functionality, efficiency, etc. The evaluation of these developed and transferred technologies help to prevent transmission of COVID-19 at community level. Design/methodology/approach -- The methodology used in this research was descriptive and purposive sampling type. The sample pool consisted of 5 TVET institutions. 40 respondents participated in this questionnaire study. The response was recorded through interview questionnaires based on the 5-point Likert Scale. Data analysis and Cronbach's alpha reliability tests were computed using SPSS and Minitab software. Practical Implications: The coronavirus is the deadly pandemic and highly contagious disease the human mankind has witnessed since 1918 flue pandemic. However, the coronavirus spread in Ethiopia at the community level has prompted many TVET (Technical Vocational and Education Training) institutions and universities to ramp up their efforts to develop and transfer technologies. Hence TVET organizations need therefore to develop and transfer technologies that are useful to prevent the spread of COVID-19. This research will help to gather the technical information pertaining to design, quality and performance of Hand washing equipment's, face masks, Hand sanitizers and other equipment's. Findings - The results prove TVET Institutions' efforts were successful in developing and transferring the technologies required to combating COVID-19. Cronbach's alpha (reliability test) value is 0.77 for the TVET colleges, indicating the data is excellent, unique and consistent. The position of the TVET institution is excellent as regards to the efforts put in developing and transferring technologies used for combating COVID-19 in and around Addis Ababa. The responses received were unique in nature. Originality/value -- COVID-19 has posed many challenges to public and has resulted in many deaths in Addis Ababa and entire Ethiopia. This work is unique and would make valuable contribution and gather information on the design and technical aspects of developed and transferred technologies by TVET Institutions used for combating COVID-19. [ FROM AUTHOR] Copyright of Journal of Pharmaceutical Negative Results is the property of ResearchTrentz and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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Since 1979, China has experienced dazzling economic progress thanks to economic reforms and Special Economic Zone (SEZ) projects. Disciplined labor processes and government involvement have been key factors in its financial and technological success. Cities such as Shanghai and Shenzhen have become fundamental pillars in scientific and technological development, based on the creation of new energies, robotics, health, telecommunications, biotechnology, genetics, space exploration, artificial intelligence, quantum computing, making the Asian giant a global technological hub. The objective of this research is to analyze the technological impact of Shanghai and Shenzhen, considered as Special Economic Zones of High Technological Development (ZEEADT) because they are fundamental pillars in the continuity of China as the first world economic power. As a result of this efficiency, the Asian country has continued to grow and strengthen even during the economic slowdown caused by COVID-19.
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Increasing dependency on digital technologies introduces queries related to well-being–when and how digital technology poses a threat, or when it is the most appreciated by users? People have some expectations before using technology, which sometimes may be met, but there might be a mismatch at other times. Nevertheless, the digitalization of services advances and companies modify existing or produce new technologies that do not satisfy users' demands, putting their well-being at risk. Through an empirical inquiry, the present research explores experiences with technologies to shed more light on the main factors that enrich or diminish technology value and influence well-being. Exploiting the circumstances created by the COVID-19 pandemic that fast-forwarded technology use and development, an online inquiry was conducted to assess positive and negative experiences of technologies, focusing on the contexts of work, learning, entertainment, information-seeking, and health. The findings from 578 participants indicate that depending on the role of technologybeing a substitute for certain activities or an opportunity to perform them differently–consequences on well-being can more or less follow expectations. The results are discussed in the context of past research and practical implications for, e.g. technology design or managerial changes that could help overcome users' current challenges. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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With the Internet of Things and medical technology development, patients use wearable telemedicine devices to transmit health data to hospitals. The need for data sharing for public health has become more urgent under the COVID-19 pandemic. Previously, security protection technology was difficult to solve the increasing security risks and challenges of telemedicine. To address the above hindrances, Federated learning (FL) solves the difficulty for companies and institutions to share user data securely. The global server iterative aggregates the model parameters from the local server instead of uploading the user's data directly to the cloud server. We propose a new model of federated distillation learning called FedTD, which allows the different models between local hospital servers and global servers. Unlike traditional federated learning, we combine the knowledge distillation method to solve the non-Independent Identically Distribution (non-IID) problem of patient medical data. It provides a security solution for sharing patients' medical information among hospitals. We tested our approach on the COVID-19 Radiography and COVID-Chestxray datasets to improve the model performance and reduce communication costs. Extensive experiments show that our FedTD significantly outperforms the state-of-the-art. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Advanced technologies are leading to a vital change in city life and turning the urban planning development plans. The new technical development initiatives have evolutionary transform the urban infrastructure by optimizing planning of resources use and through information technology systems. Post COVID-19 raised interesting question that if another pandemic or major threat in the future, would urban areas be sufficiently prepared to respond based on the lessons learned from the COVID-19 pandemic? This paper highlights the Expo City Dubai case in light of smart city and smart tourism destination. The emphasis is on dual approach of usage of smart technologies as residential areas and tourist place in term of planning and provision of facilities. This research figure out the planning instruments applied in smart strategies in Expo City by focusing on how sustainability indicators are considered under the smart paradigm. The discussion revealed that Expo City is fulfilling the requirements of being a smart destination by displaying novel technical applications of 5G, Artificial Intelligence, Big Data, Internet of Things (IoT) and robotics. The final discussion contextualizes by proposing potential areas of synthesis, applications for planning practice, and areas of future research in sustainable urban city planning. © 2022 IEEE.
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Spurred by fall in passenger numbers following the COVID-19 pandemic, railways today have made rapid progress in improving operational efficiency and labor saving measures. DX (digital transformation) technology, which has been applied to automatic train operation, inter alia, is therefore attracting attention. Another focal point for railways is the realization of global decarbonization, illustrated by "2050 Carbon Neutral" goal declared by the Suga Cabinet and "COP26." This paper introduces the outlines of three technologies related to these topics, namely, a "Method for evaluating wheel slide protection (WSP) performance by hybrid simulator," a "Method applying neural networks to detect abnormal noise during train operation," and "High efficiency of diesel electric railcars." © 2022 Ken-yusha Inc.. All rights reserved.
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New technology developments and its processes generate large quantities of data every day. Organizations are faced a number of problems for managing these big data. IoT (Internet of Things) devices are now used for collecting data rapidly and safely in high capacity storage devices and internet clouds. Big data has many characteristics including unstructured which does not conform to a data model. In an organization about 85% data is in unstructured format. The semi-structured data does not conform to a data model but it has some structure. The structured data is in an organized form and can be easily used by a computer program. From the year 2019 a new big data formation happened with COVID-19 pandemic in the world society. Corona virus and COVID-19 pandemic have fully affected the people and this pandemic situation has frightened the people worldwide. It has to find excellent big data analytical methods to control and solve the future problems related to this pandemic. This paper presents big data quality dimensions, big data analytics in COVID-19 pandemic, and physical and mental post-COVID health issues. © 2022 IEEE.
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The medical and healthcare field is more interesting and studied in the era of science and technology development. Hair washing helps remove dirt and healthy hair and reduces the risk of scalp diseases, and according to Vietnamese traditional medicine, massage according to acupressure points is one of the methods of treating pain and fatigue, and it helps to recover from the treatment process, reducing stress, etc. In the stage of the COVID-19 epidemic, the shortage of medical staff occurs in many hospitals that are overloaded with patient care, especially bedridden patients, who need special care and hair washing, and massage head can help them relax and help recover from some diseases. This study proposes an approach to identify acupressure points on the head, and it is used for the hair washes and head massage robot for the patient's head. Hair wash and head massage robot by using water jets is proposed, which avoids the spread of some diseases by direct contact, and it reduces the shortage of medical care workers at hospitals. The study proposes a CNN to recognize the home point of the robot mounted on the face with the accuracy of, combined with signals from sensors, to determine the necessary dimensions of the human head. The ANN is used to predict the massage trajectories for the robot to suit each different patient. The overall results are evaluated with an accuracy of 97.56% with the training dataset and 95.12% with the test data. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The global COVID-19 pandemic has driven innovations in methods to sustain initiatives for the design, development, evaluation, and implementation of clinical support technology in long-term care settings while removing risk of infection for residents, family members, health care workers, researchers and technical professionals. We adapted traditional design and evaluation methodology for a mobile clinical decision support app - designated Mobile Application Information System for Integrated Evidence ("MAISIE") - to a completely digital design methodology that removes in-person contacts between the research team, developer, and nursing home staff and residents. We have successfully maintained project continuity for MAISIE app development with only minor challenges while working remotely. This digital design methodology can be implemented in projects where software can be installed without in-person technical support and remote work is feasible. Team skills, experience, and relationships are key considerations for adapting to digital environments and maintaining project momentum.
Subject(s)
COVID-19 , Decision Support Systems, Clinical , Mobile Applications , Health Personnel , Humans , Long-Term Care , PandemicsABSTRACT
Artificial intelligence (AI) development and its application in human life are continuing at an astounding rate. Among the variety of examples of AI being used for a variety of tasks, its contribution to epidemic control has recently captured a great deal of interest at the time of the recent Covid-19 pandemic, a crisis that occurred due to the Coronavirus spread. As the entire world has been concerning over urgent efforts addressing the damaging effects since the outbreak, Artificial Intelligence emerged as a great possible solution. This study is aimed at examining how artificial intelligence gets us ready to combat and control COVID-19 and other future pandemics, as this is unlikely to be the last of the epidemics. Moreover, several key technological solutions are outlined that could help combat future pandemics and make us prepared. As a result, technology development can be promoted to overcome any possible unexpected subsequent crisis. © 2021 IEEE.
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The utilization of technology in education has been increasing during the unprecedented time of the Covid-19 pandemics. It has not only affected the opinions of teachers, but also students' perceptions have been impacted. This paper identified and compared students' perceptions of Indian and Hungarian universities towards technology use, benefits, and development. A stepwise regression filtered out six significant variables that explained the perception of Indian students (R2=.91), and three variables identified the perception of Hungarian students towards technology (R2=.61). Indian students' perception has been recognized with six technology variables: 'Sharing of resources expertise and advice', 'ICT tools/techniques promoting workshops policy', 'Up to date learning materials', 'Desktop Computers equipped with internet access', 'E-library', and 'E-Reader'. Three variables such as 'Improving analytical skills', 'Download/Browse material', 'High-quality lessons' also impacted the viewpoints of Hungarian students. © 2021 IEEE.
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The article is devoted to the analysis of new directions of application of blockchain technology that have emerged in the conditions of the Covid-19 pandemic, generalization of existing experience in using blockchain and definition of tasks for blockchain technology development. The paper analyzes the properties of blockchain technology, manifested in the created systems, which can solve several management problems in the process of combating the Covid-19 pandemic. The article describes the Covid-19 pandemic fight and their possible actions. The paper provides analysis and systematization of new areas of blockchain application, such as tracking contact with infected people, verification of vaccine authenticity, maintaining of the clinical trial data integrity, identifying counterfeit medicines and personal protective equipment, identifying foci of infection. The authors describe examples of specific solutions, showed that the blockchain technology can play an innovative role in solving a few problems that appeared during the pandemic. The existing limitations are revealed both in the blockchain technology itself and in the conditions of its application, which do not allow to fully realize the full potential of the technology. The description of new areas of application of blockchain technology is important both for the organizers of the COVID-19 pandemic response, and for researchers and developers of systems using blockchain technology. © 2022, Springer Nature Switzerland AG.