ABSTRACT
Companion bots such as chatbots in cyberspace or robots in real space gained popularity during the COVID-19 pandemic as a means of comforting humans and reducing their loneliness. These bots can also help enhance the lives of elderly people. In this paper, we present how to design and implement a quick prototype of companion bots for elderly people. A companion bot named "Hello Steve"that is able to send emails, open YouTube to provide entertainment, and remember the times an elderly person must take medicine and remind them is designed and implemented as a quick prototype. In addition, the bot combines the features of a mobile robot and a chatbot. The experimental results show the effectiveness of the design through its very high accuracy when navigating mobile-robot-like tasks and responding to chatbot-like tasks via voice commands. © 2023 MYU K.K.
ABSTRACT
The article presents an analysis of the communicative behavior of actors in cyberspace during Covid-19. The novelty of this study lies in the fact that an algorithm is presented for determining the perception and track opinions and attitude changes of metropolitan residents in terms of digital transformation. The material included Russian-language data from social networks, video hosting services, microblogs, messengers, blogs, news, reviews, and forums. The data was collected at the beginning of the third wave of Covid-19 in Russia from June 2, 2021 to June 29, 2021. The study enabled identification of digital transformation aspects that were positively perceived by the residents of Moscow (RF) and found their support;and it also made possible to identify resources the emergence and development of which could lead to an increase in social tension. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
There has been a new scientific policy that has been proposed in Japan that is named Society 5.0. This type of society is defined as "a human-centered society that balances economic advancement with the resolution of social problems by a system that highly integrates cyberspace and physical space". For the past couple of years, educational institutions have been using online video conferences for remote learning due to the coronavirus pandemic. This type of learning has some benefits such as convenience and flexibility. However, conversely, it is more isolating and discomforting for some. Additionally, remote online learning has been proposed to be the future of education, which might be disappointing to some students. Development in the metaverse and its hardware might be the solution for a better learning experience. This technology is also aligned with Society 5.0 as cyberspace will integrate more closely with physical space. The student would be able to feel as if they were in an actual classroom using the metaverse, which can be accessed by 3D Virtual World Applications. They would be able to see their peers and hear more of their peers to feel less isolated. © 2022 IEEE.
ABSTRACT
This study was motivated by the challenges experienced by parents and guardians in ensuring the safety of children in cyberspace. In the last two or three years, online education has become very popular all over the world due to the Covid 19 pandemic. Therefore parents, guardians and teachers must ensure the safety of children in cyber space. Children are more likely to go astray and there are plenty of online programs waiting to get them on wrong track and also children who are engaging in the online education can be distracted at any moment. Therefore, parents should keep a close check on their children's online activity. Apart from that due to the unawareness of children, they tempt to share their sensitive information, chance of being a victim of phishing attacks from outsiders. These problems can be overcome through the proposed web-based system. We use feature extraction, web tracking and analysis mechanisms, image processing and name entity recognition to implement this web-based system. © 2022 IEEE.
ABSTRACT
With COVID-19 as an initiation, the stage for human socioeconomic activities is rapidly shifting from physical space to cyberspace. Mobile networks have evolved as essential communication networks for connecting individuals and things to the cloud. Further evolution of mobile networks is essential to realize Digital Twin. In particular, low latency and guaranteed QoS using network slicing are extremely challenging requirements that legacy mobile networks until 4G have not been able to meet. In addition, the chronic shortage of spectrum accompanying the shift to broadband continues to encourage the use of small cells, which naturally make xHaul1 denotes a term that expresses either fronthaul, midhaul or backhaul. problem be more serious. The author has worked on this xHaul problem in both academia and industry for 20 years, developing a unique WLAN mesh protocol for backhaul. In order to bring the results of this research to practical use, PicoCELA Inc. as a vehicle for commercialization of the fruits, was incorporated. The edge device brought by PicoCELA with the WLAN mesh capability are linked to a cloud server and are serving various applications as a general-purpose platform to facilitate the introduction of Digital Twin. This paper reviews the history of WLAN mesh technology to date, identifies the technical issues that arise when using it in an enterprise scenario, and then provides an overview of how PicoCELA' s WLAN mesh addresses these issues. The PicoCELA solution as an edge platform is overviewed, followed by some real-world use cases. Finally, the outlook for mobile communications in the future is summarized. © 2022 IEEE.
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With the fast development of new technologies, such as Internet of Things, big data and Internet plus, Intelligent Transportation Systems (ITS) have made remarkable achievements and the intelligence in ITS has also been continuously increased, which a new field, i.e., Social Transportation, is emerging. In social transportation systems, physical and cyber elements are tightly conjoined, coordinated, and integrated with human and social characteristics. In this paper, we collect and analyze traffic data from physical world and social media data from cyberspace to sense the human mobility patterns during holidays under the COVID-19 pandemic. © 2022 IEEE.
ABSTRACT
The importance of the study is to demonstrate the criminal protection of personal data for individuals in general and patients in particular, and it aimed to demonstrate the adequacy of Jordanian legislation and comparing to provide legal protection of the individuals’ personal data, especially patients, in light of the Corona pandemic. The study also aims to illustrate the balance between two rights;the right of privacy for individuals’ data, especially patients infected with the Corona virus and the right of authorized parties to access this data in order to limit the spread of this virus. In order to achieve the study objectives, it discussed the nature of the concepts of privacy and personal data, and indicated the legislative treatments of the patients’ data, whether it was through the general criminal law, or through laws related to informatics, through medical charters, or even through the legislation related to the pandemic and to explain how these concepts contributed to the criminal protection of patients’ data. The study combined the analytical and comparative approach, and it concluded that the current legislation is not sufficient to protect a right worthy of legal protection, which is the right of privacy in personal data. The privacy of personal data has been exposed to many violations in the light of cyberspace, which requires legislators to hurry to issue special laws that surround personal data with a fence of criminal protection. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Cyberspace is essential for e-business, including small and medium enterprises (SMEs). In reality, SMEs have limited resources for cybersecurity. Furthermore, dealing with the fourth industrial revolution and the post-COVID-19 era, the challenges are not limited to cybersecurity only but also cyber resilience. Over 200 cyber resilience assessment frameworks have been proposed. Thus, SMEs need help to operate cyber resilience as a simple. This paper reviews the technical architectures behind the cyber resilience (CR) to detect processes and monitor assets continuously from incidents in the modeling level. The technical architectures of the CR model are built on five layers. The five layers are services, data, generative models, data analysis, and resilience scale. Machine learning and data mining based a probabilistic model approach works to solve the problem of the CR model. The approach is taken to ensure that the probabilistic model is adaptive in the face of uncertainty. The CR model helps to explain the technical architecture of each layer to realize the probabilistic model in practice. © 2022 IEEE.
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The phenomenon of problematic mobile phone use has become increasingly common among adolescents during the lockdowns mandated by the COVID-19 pandemic. However, research is still scarce on the impact of such use on delinquent cyberspace conduct (i.e. cyberbullying). This study applies the theoretical framework of general strain theory to examine how problematic mobile phone use affects the perpetration of cyberbullying. The results of this empirical examination of longitudinal survey data obtained from 2,161 adolescents in South Korea reveal that problematic mobile phone use is positively associated with engagement in cyberbullying. It is a type of strain that induces negative emotional states and results in the perpetration of cyberbullying. Furthermore, this study investigates the moderating roles of both traditional bullying experiences (i.e. traditional bullying and victimisation) in the association between problematic mobile phone use and the perpetration of cyberbullying. We found traditional bullying perpetration positively moderates the effects of problematic mobile phone use on cyberbullying. On the other hand, we found the moderating effect of traditional bullying victimisation of adolescents was insignificant. © 2022 Informa UK Limited, trading as Taylor & Francis Group.
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Unplanned encounters or casual collisions between colleagues have long been recognized as catalysts for creativity and innovation. The absence of such encounters has been a negative side effect of COVID-enforced remote work. However, there have also been positive side effects such as less time lost to commutes, lower carbon footprints, and improved work-life balance. This vision paper explores how serendipity for remote workers can be created by leveraging IoT technologies, edge computing, high-resolution video, network protocols for live interaction, and video/audio denaturing. We reflect on the privacy issues that technology-mediated serendipity raises and sketch a path towards honoring diverse privacy preferences. © 2022 Owner/Author.
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Technological advancements have made it easy and quick to generate and collect huge volumes of varieties of data from wide ranges of rich data sources. These big data may be of different levels of veracity, including precise data and imprecise or uncertain data. Embedded in the data are valuable information and useful knowledge that can be discovered by big data science and analysis for social good. In this paper, we propose a solution to analyze coronavirus disease 2019 (COVID-19) epidemiological data. In particular, the solution focuses on analyzing valuable information and useful knowledge (e.g., distribution, frequency, patterns) of health-related states and characteristics in populations. Discovered information and knowledge helps users (e.g., researcher, civilian) to understand the disease better, and thus take an active role in fighting, controlling, and/or combating the disease. Evaluation of our solution on real-life data demonstrates its practicality in analyzing COVID-19 epidemiological data and revealing demographic relationships among COVID-19 cases. © 2021 IEEE.
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After the sudden shift from face-to-face to face-to-display lecturing in Czech and Slovak universities as one of side effects of COVID-19, the authors completed an online survey mapping their reactions to this unexpected transformation on the peak of the second wave in May 2021. The main aim of this study was to learn to what degree they were prepared to their fully virtual environment adaptation. 172 educators participated in the study. Obtained results indicate that the universities were not properly equipped for a broad adaptation of online education. In the time of survey, not all of these problems have been solved. It may result in negative consequences in the future. © 2021 IEEE.
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The pandemic caused by the new coronavirus Covd-19 has suddenly and unpredictably changed the running of schools and their communities’ dynamics. In response to an emergency state marked by long periods of confinement, of children and young people at home, often of indefinite duration and sometimes intermittent, logistic and pedagogic adaptations were required. In a school for early childhood and basic education, where the arts strongly influence the educational project, both at the conceptual and methodological level and at the level of interdisciplinary practice itself, the challenge went on in several fronts: the ways of regular contact with children and young people for teaching interaction, the creation of projects that develop skills related to knowledge, expression and communication and, finally, the moments of sharing, in which the work carried out becomes public and is reflected and debated collectively. This article describes the adaptation of visual and performing arts to remote online learning, as well as results obtained by the creative application of computer and image technologies, between March 2020 and March 2021. For an educational project of proximity and creativity, how could we defend the fundamental value of arts in education through digital mediation? What processes, artistic objects and sharing models resulted from this reality? © 2021 Copyright held by the owner/author(s). Publication rights licensed to ACM.
ABSTRACT
Cyberspace has been recognized as a conducive environment for use of various hostile, direct, and indirect behavioural tactics to target individuals or groups. Denigration is one of the most frequently used cyberbullying ploys to actively damage, humiliate, and disparage the online reputation of target by sending, posting, or publishing cruel rumours, gossip, and untrue statements. Previous pertinent studies report detecting profane, vulgar, and offensive words primarily in the English language. This research puts forward a model to detect online denigration bullying in low-resource Hindi language using attention residual networks. The proposed model Hindi Denigrate Comment-Attention Residual Network (HDC-ARN) intends to uncover defamatory posts (denigrate comments) written in Hindi language which stake and vilify a person or an entity in public. Data with 942 denigrate comments and 1499 non-denigrate comments is scraped using certain hashtags from two recent trending events in India: Tablighi Jamaat spiked Covid-19 (April 2020, Event 1) and Sushant Singh Rajput Death (June 2020: Event 2). Only text-based features, that is, the actual content of the post, are considered. The pre-Trained word embedding for Hindi language from fastText is used. The model has three ResNet blocks with an attention layer that generates a post vector for a single input, which is passed through a sigmoid activation function to get the final output as either denigrate (positive class) or non-denigrate (negative class). An F-1 score of 0.642 is achieved on the dataset. © 2021 Association for Computing Machinery.
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We propose Computational Thinking (CT) as an innovative pedagogical approach with broad application. Research and current industry trends illustrate that students should have a solid computational thinking ability in order to have the skills required for future jobs in Artificial Intelligence. Due to current social issues regarding COVID-19 and natural disasters, we are rapidly moving towards a cyberspace era where many citizens will conduct their work online. Understanding the foundations and tools of computation - e.g., ion, decomposition, pattern recognition - is critical for any student to be prepared for the digital AI age. Believing students should be fully prepared for future jobs that involve computation, we developed a CT module on a Learning Management System (LMS). We have collected data of students who took our CT course module. We looked into the students' activity records and analyzed the number of students' views on the pages and the number of participants on each quiz. We counted the total number of engagements of the ten components in the CT course module. Ultimately, we believe that our modules had a greater impact on those students who were newer to computational thinking, over those who had prior experience and were enrolled in upper-level computational courses. © American Society for Engineering Education, 2021
ABSTRACT
Academic advising plays a vital role in students' academic success;however, it is time consuming and difficult to maintain. Moreover, due to the COVID-19 outbreak and the sudden shift of education to the cyberspace, it has become even more challenging and time consuming for advisors to handle the drastically increasing numbers of queries received through online communication channels. To advise an enormous number of newly admitted students, the need arises for solutions that can handle the demands of a large number of students effectively without affecting student's academic success. This paper proposes an efficient, fast, scalable, and cost-effective solution using a serverless chatbot. The proposed Academic Advising chatbot, which can be integrated with Microsoft Teams, implements advanced semantic analysis techniques from Natural Language Processing (NLP) and analyzes the context of the student's queries, and responds accordingly. © 2021 Association for Computing Machinery.