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1.
2022 IEEE Frontiers in Education Conference, FIE 2022 ; 2022-October, 2022.
Article in English | Scopus | ID: covidwho-2191732

ABSTRACT

The Covid pandemic is a clarion call for increased sensitivity to the interconnected nature of social problems facing our world today. A future-oriented education on critical issues, such as those outlined in the United Nations Sustainable Development Goals (UN SDGs) and designing potential solutions for such problems is an imperative skill that must be imparted to children to help them navigate their future in today's unpredictable world. Towards this goal, we have been conducting 3.5 month-long mentoring sessions for pre-university students in India to participate in a STEAM for Social Good innovation challenge conducted annually by the Government of India. Using digital and physical computing skills, we helped children explore creative solutions for social problems through a constructionist approach to learning, wherein they ideated and reflected upon the problems in their communities. The children learnt the Engineering Design Thinking process and worked in online groups of two or three, from concept to completion. Despite the constraints posed by the pandemic, they explored creative ways to think about design and innovation. They completed a variety of tasks by making, tinkering, engineering, assembling, and programming to grasp the intricate relationship between software and hardware. Subsequently, the children showcased their creative abilities through video storytelling to a panel of domain experts. In this paper, we present the children's perspective of their experiences through this journey, the evaluation metrics based on IEEE design principles, and our learnings from conducting this initiative as a university-school partnership model for 84 middle and high school students. The aspirational intent of this initiative is to make the children better social problem solvers and help them perceive social problems as opportunities to enhance life for themselves and their communities. © 2022 IEEE.

2.
11th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2022, co-located with the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence, IJCAI-ECAI 2022 ; 351:86-99, 2022.
Article in English | Scopus | ID: covidwho-2022582

ABSTRACT

The SARS-CoV-2 pandemic has galvanized the interest of the scientific community toward methodologies apt at predicting the trend of the epidemiological curve, namely, the daily number of infected individuals in the population. One of the critical issues, is providing reliable predictions based on interventions enacted by policy-makers, which is of crucial relevance to assess their effectiveness. In this paper, we provide a novel data-driven application incorporating sub-symbolic knowledge to forecast the spreading of an epidemic depending on a set of interventions. More specifically, we focus on the embedding of classical epidemiological approaches, i.e., compartmental models, into Deep Learning models, to enhance the learning process and provide higher predictive accuracy. © 2022 The authors and IOS Press.

3.
22nd International Conference on Computational Science and Its Applications , ICCSA 2022 ; 13380 LNCS:496-508, 2022.
Article in English | Scopus | ID: covidwho-2013912

ABSTRACT

Italy was one of the first country in Europe which was severely affected by COVID-19 pandemic. Several critical issues emerged during the different pandemic phases, especially in the health and mobility sector. Restrictions on public transport reduced the supply of transport, highlighting the need to rethink complementary transport systems. Since May 2020, in the post-lockdown phase, the provision of local public transport has been based on ordinary services, such as bus services, which are mainly intended to meet the needs of systematic travel between the places of residence and work on main development routes of the territory. These services have undergone reductions both in the on-board capacity and in some cases the complete elimination of transit routes. The rebalancing in favour of sustainable modes of transport and the reduction of the share of road mobility is pursued through the encouragement of ad-hoc measures aimed at balancing-off the supply-demand mechanism and improving the quality of services. The application of an on-demand responsive transit system has the ability to improve the transit needs in order to reach the places where personal or family services are provided or to enjoy the resources distributed within desired territory. In Italy since March 2020, new areas of weak demand for transport have been created, i.e. areas with a certain number of users that need to be transferred to and from places that have generally never had access to public transport or have had it restricted. The Demand Responsive Transport (DRT) system is, therefore, used in both urban and suburban areas, allowing even those who do not have their own means of transport (for example, disadvantaged social categories or users with a short stay in the area) or who are suitably equipped (people with reduced or no motor skills), to move around in areas easily. The present work focuses on an analysis of the current state of affairs, starting from the literature and regulations concerning the diffusion of the DRT systems in Italy, and offers some ideas for the optimisation of an integrated public transport service. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

4.
Polymer Reviews ; 2022.
Article in English | Scopus | ID: covidwho-1984894

ABSTRACT

Vaccine development is among the critical issues for ceasing the COVID-19 pandemic. This review discusses the current usage of biomaterials in vaccine development and provides brief descriptions of the vaccine types and their working mechanisms. New types of vaccine platforms (next-generation vaccines and DNA- or mRNA-based vaccines) are discussed in detail. The mRNA vaccine encoding the spike protein viral antigen can be produced in a cell-free system, suggesting that mRNA vaccines are safer than “classic vaccines” using live or inactivated virus. The mRNA vaccine efficacy is typically high at approximately 95%. However, most mRNA vaccines need to be maintained at −20 or −70 degrees for storage for long periods (half a year) and their transportation because of mRNA vaccine instability in general, although mRNA vaccines with unmodified and self-amplifying RNA (ARCT-154, Arcturus), which have a lyophilized form, have recently been reported to be kept at room temperature. mRNA vaccines are typically entrapped in lipid nanoparticles composed of ionizable lipids, polyethylene glycol (PEG)-lipids, phospholipids, and cholesterol. These components and their composition affect mRNA vaccine stability and efficacy and the size of the mRNA vaccine. The development of an improved mRNA vaccine entrapped in sophisticated biomaterials, such as novel lipid nanoparticles, using new types of biopolymers or lipids is necessary for high efficacy, safe transportation and long-term storage of the next generation of mRNA vaccines under mild conditions. © 2022 Taylor & Francis Group, LLC.

5.
6th International Conference on Trends in Electronics and Informatics, ICOEI 2022 ; : 1013-1016, 2022.
Article in English | Scopus | ID: covidwho-1901458

ABSTRACT

Online mode during COVID-19 has raised mental health issues among students along with the stigma around it that continues to exist. As a result of which, there are people who are not comfortable in disclosing their personal details to outsiders for help. This brings in the use of AI applications that can help in this critical issue requiring regular monitoring. In this paper, a survey is conducted to know about awareness about this topic. A review about many conversational AI chatbots is provided that are helpful for handling mental health issues such as stress, anxiety, and depression in a number of ways. These include voice and text based chatbots developed in the last decade. The strengths and limitations of these are also discussed. © 2022 IEEE.

6.
5th International Conference on Natural Language Processing and Information Retrieval, NLPIR 2021 ; : 109-114, 2021.
Article in English | Scopus | ID: covidwho-1784904

ABSTRACT

Digital Rumors, because of the ease and innovations in social networking technologies, has become an important issue. These rumors become a critical issue in a disaster, epidemic, or pandemic. Considering classification power of conventional and deep learning techniques, we propose a hybrid learning technique that identifies rumors effectively. For this, TF-IDF description has been used to build a stack of multiple conventional learning techniques;logistic regression, Naïve Bayes, and random forest. Whereas, word-embedding features have been used for purpose of deep learning;LSTM and LSTM-RNN. The combination of LSTM and RNN makes this study unique in the field of rumor detection. With LSTM and RNN gated architectures, huge series rumor tweets may be efficiently managed. To aggregate the decisions, the labels of deep learning and the stack of conventional learning have been combined using majority voting based ensemble classification. To evaluate the performance of the proposed technique, we used publically available standard COVID-19 RUMOR dataset. The proposed technique obtains 99.02% accuracy, which shows its effectiveness. The dataset utilized and the ensemble model created for rumor identification distinguish our work from existing methods. © 2021 ACM.

7.
15th IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1722939

ABSTRACT

As more activities are moving to digital platforms in the age of COVID-19 pandemic, cyber security becomes an increasingly critical issue. Thus, understanding how the recent pandemic has changed the Singapore cyber security landscape gains importance in unearthing potential weaknesses present in the infrastructure, which unfortunately is very challenging. In this paper, we propose, LionKeeper, an automated system for discovering the cyber security dynamics timely in Lion City - Singapore through social media data analytics. In particular, considering that the social media platforms like news websites provide immediate reports on local and global cybercrime incidents, in our system, we first crawl all the news articles from mainstream news sources such as CNA and Strait Times. Then, we analyze these news articles to identify those related to cybercrimes, the date and the location of cybercrime incidents, and employ a scoring system to detect the cyber security attack types and their significance. Additionally, based on the extracted information, we perform various analyses to generate meaningful insights for users to understand the cyber attack landscape dynamics before and during the COVID-19 pandemic automatically and intelligently. To the best of our knowledge, this is the first automated solution to understand the Singapore cyber landscape via social media analytics. © 2021 IEEE.

8.
3rd International Conference on Management Science and Industrial Engineering, MSIE 2021 ; : 186-191, 2021.
Article in English | Scopus | ID: covidwho-1633042

ABSTRACT

With the growth of aging societies, the health of the elderly is considered one of the critical issues. Regular physical activity is linked to improving physical and mental functions. Therefore, there is an urgent need to motivate the elderly to be physically active. The self-monitoring of physical activity may positively impact the awareness of exercise and health and increase activity levels. In this study, we conducted a 12-week trial with thirty Japanese elderly to investigate the effects of self-monitoring on their attitudes, awareness, and activity levels. During the trial, the participants wore activity trackers daily and responded to repeated questionnaires weekly. The Covid-19 pandemic has begun to appear a few weeks after starting this trial. Therefore, we explored the impact of this pandemic on the participants' activity and psychological status. Overall, the participants increased their perception of the benefits of self-monitoring and willingness to check the activity tracker's feedback. Despite there was a significant decrease (p < 0.05) in the participant number of steps due to the Covid-19 pandemic, the percentage of reduction was small (11%). The self-monitoring of activity may help the elderly maintain activity level during the pandemic. Furthermore, the participants agreed with the importance of monitoring physical activity and the necessity to maintain activity level during the Covid-19 pandemic. © 2021 Association for Computing Machinery. All rights reserved.

9.
1st International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2021 ; 1485 CCIS:524-535, 2021.
Article in English | Scopus | ID: covidwho-1565283

ABSTRACT

The COVID-19 pandemic is an ongoing global pandemic. With schools shut down abruptly in mid-March 2020, education has changed dramatically. With the phenomenal rise of online learning, teaching is undertaken remotely and on digital platforms, making schools, teachers, parents, and students face a steep learning curve. This unplanned and rapid move to online learning with little preparation results in a poor experience for everyone involved. Thus, this study explores how people perceive that online learning during the COVID-19 pandemic is challenging. We focus on tweets in English scraped from March to April 2020 with keywords related to the COVID-19 pandemic and online learning. We applied the latent Dirichlet allocation to discover the topics that occur in the data collection. We analyzed representative tweets from the qualitative perspective to explore and augment quantitative findings. Our findings reveal that most challenges identified align with previous studies. We also shed light on several critical issues, including mental health, the digital divide, and cyberbullying. Future work includes investigating these critical issues to enhance teaching and learning practices in the post-digital era. © 2021, Springer Nature Switzerland AG.

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