ABSTRACT
After the outbreak of corona virus, all counties are paying special attention to their healthcare infrastructure. During second phase of covid-19, entire world has seen health care crisis. Large number of people died globally. Entire world was affected mentally or physically. There is a great need to strengthen the healthcare infrastructure, to vaccinate the population against covid virus infection and to take proper precaution to avoid spread of the virus, so that the world will not see such deadly days again. This paper discusses how technologies like Internet of Things (IoT), Artificial Intelligence (AI), Drones etc can help in remote monitoring of patients, judicious hospital admission, conscious distribution of lifesaving drugs etc. Investment in technology with not only help in the reduction of spread of the virus but will also help in fighting with all other future pandemics. All the countries must have to invest more on latest technologies in their healthcare to make themselves ready for such future pandemics. When the things will improve, the new normal will be very much different from the life that was before pandemic. IoT, AI and other technologies will become the non-separatable part of our life. © 2023 Bharati Vidyapeeth, New Delhi.
ABSTRACT
Face is one of the most widely employed traits for person recognition, even in many large-scale applications. Despite technological advancements in face recognition systems, they still face obstacles caused by pose, expression, occlusion, and aging variations. Owing to the COVID-19 pandemic, contactless identity verification has become exceedingly vital. To constrain the pandemic, people have started using face mask. Recently, few studies have been conducted on the effect of face mask on adult face recognition systems. However, the impact of aging with face mask on child subject recognition has not been adequately explored. Thus, the main objective of this study is analyzing the child longitudinal impact together with face mask and other covariates on face recognition systems. Specifically, we performed a comparative investigation of three top performing publicly available face matchers and a post-COVID-19 commercial-off-The-shelf (COTS) system under child cross-Age verification and identification settings using our generated synthetic mask and no-mask samples. Furthermore, we investigated the longitudinal consequence of eyeglasses with mask and no-mask. The study exploited no-mask longitudinal child face dataset (i.e., extended Indian Child Longitudinal Face Dataset) that contains 26,258 face images of 7,473 subjects in the age group of [2, 18] over an average time span of 3.35 years. Due to the combined effects of face mask and face aging, the FaceNet, PFE, ArcFace, and COTS face verification system accuracies decrease by approximately , , , and , respectively. © 2022 ACM.
ABSTRACT
Information Technology (IT) solutions have become a critical enabling tool in businesses and communities. As a result, organisations invest heavily in technology solutions to transform businesses. Motivated by rapid technological advancements, there have been radical changes in IT infrastructure management, IT applications, and IT services delivery. The recent COVID-19 pandemic also encouraged the rapid adoption of technology solutions. However, despite numerous prescriptive models and 'best practice frameworks' available in the field, and an increased uptake of ITG in organisations, achieving key ITG outcomes is consistently ranked as one of the top concerns of management. After establishing a theoretical foundation for effective ITG practices (via literature review), this study begins a pilot examination to determine if tech deployment failure can be attributed to poor ITG. © 2022 Authors. All rights reserved.
ABSTRACT
The recent pandemic, covid-19 has largely affected people's lives, health, and productivity. The first case of Covid-19 was recorded on December 31, 2019, in Wuhan, China. Since then, the number of cases has increased exponentially, and subsequently, numerous precautions have been taken to prevent and cure the virus. By May 26, 2021, totally, 168 million cases were reported worldwide, with 3.49 million deaths, and the pandemic is currently underway, with people continuing to get affected and fighting for their lives from this deadly virus. The World Health Organization (WHO) has also released various precautions and vaccines to combat the pandemic, but these are insufficient to reduce the number of infected cases or save people's lives. The proposed research study discusses about the utilization of artificial intelligence (AI), machine learning (ML), and data science techniques for gaining a better understanding of covid-19 virus. This technological advancement can easily make proper judgments about covid-19, as well as the predictions on confirmed & recovered cases and deaths were made by using this technology. The datasets also include previous and current information about covid-19. The proposed research study also discusses about a tool called "Prophet.” Prophet is a Facebook open-source tool, which uses the Sklearn model API. The proposed study initially creates a prophet instance and then use its fit and predict methods. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The COVID19 pandemic has led to the proliferation of the use of online shopping applications among millions of customers worldwide. The enormous potential in technological advancements, particularly mobile technology, has directly impacted mobile commerce, where the shopping process has become so convenient. While the benefits of mobile commerce are multi-fold, the current privacy practices and the extent of user data residue in shopping apps have been less explored. In this paper, we conducted an in-depth, systematic analysis of two of the most popular mobile shopping apps - Amazon and Etsy. Our analysis led to the recovery of user data and shopping activity artifacts from Amazon and Etsy buyer and seller apps on Android/iOS devices. Based on the user data and artifacts found, we have also discussed the implications of default privacy settings, the importance of online safety policies prior to product listings, and implications for research and practice. © 2023 IEEE Computer Society. All rights reserved.
ABSTRACT
The world is continuously moving at a fast pace and so is the technological advancements in it. It is a rule of the planet that there should be continuous improvements and advancements in all realms for the welfare of the mankind. In the recent times due to the pandemic and the Covid-19 virus, the style of living and completing one's work has changes drastically. The world has become highly virtual in nature. For each work that needs to be completed there are devices all around us and all of us are connected virtually, be it studies, office work, gaming or loads of other errands. There are various components that are crucial to the efficient operation of the virtual world. One important factor among these components is the network that helps us in connecting with one another. The whole system of the virtual world is highly reliable on the speed, bandwidth, and many other factors of the network that the users are using. The mobile network era started with One-G or just the G and currently is moving towards a 5G network. In this paper we will discuss about the 5G network, the technology it uses, the challenges that it is facing and the huge difference that it will bring about in the virtual and technological world. © 2022 IEEE.
ABSTRACT
Recent days have changed tremendously, and rules are strictly being deployed to maintain social distancing, avoid crowding and frequent hand washing. Frequent washing of hands using our domestic water by a mass crowd result in water wastage which is a huge loss for our society. A better solution to sanitize the hands with reduced water wastage is attempted in this study. With technological advancements in engineering, several solutions and cope-up methods are being given to combat the spread of COVID-19 in this pandemic era. As an attempt, this study develops a Fog based Contactless Handwash kit which uses the Mis Spray method to sanitize the hands. The mist consists of water vapour and herbal sanitizer which is skin-friendly to humans. This kit is suggested to be deployed in public places to avoid the spreading of the virus since it is in a complete contactless manner. It is developed with an Atmega based microcontroller, NodeMCu,ultrasonic sensor and mist spray module economically. The outcomes of the developed handwash kit serve to optimally favour the preventing behaviour in this pandemic time. This study gives way for further research studies on the automatic sanitizing methods to combat the spread of the virus and its variants. © 2022 IEEE.
ABSTRACT
The recent pandemic, covid-19 has largely affected people's lives, health, and productivity. The first case of Covid-19 was recorded on December 31, 2019, in Wuhan, China. Since then, the number of cases has increased exponentially, and subsequently, numerous precautions have been taken to prevent and cure the virus. By May 26, 2021, totally, 168 million cases were reported worldwide, with 3.49 million deaths, and the pandemic is currently underway, with people continuing to get affected and fighting for their lives from this deadly virus. The World Health Organization (WHO) has also released various precautions and vaccines to combat the pandemic, but these are insufficient to reduce the number of infected cases or save people's lives. The proposed research study discusses about the utilization of artificial intelligence (AI), machine learning (ML), and data science techniques for gaining a better understanding of covid-19 virus. This technological advancement can easily make proper judgments about covid-19, as well as the predictions on confirmed & recovered cases and deaths were made by using this technology. The datasets also include previous and current information about covid-19. The proposed research study also discusses about a tool called "Prophet.” Prophet is a Facebook open-source tool, which uses the Sklearn model API. The proposed study initially creates a prophet instance and then use its fit and predict methods. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Hands-on practice laboratory experience is an essential component for effective engineering education. Thanks to the recent technological advancement, remote and virtual laboratories are becoming more and more popular. The study presented in the current paper is focused on developing a student board that can be used by both teachers and students in the education process. For this board, several PSoC™ 6 applications have been developed, to provide students hands-on experience with various electronic basic concepts, which they can later practice by developing their own applications. Although many applications can be demonstrated using this board, in this paper the design and development of two practical applications is presented - LabVIEW Control of RGB Led Intensity and Signal Generation and Acquisition with LabVIEW Display. Those two applications are both using the PSoC 6 microcontroller and were prototyped on the NI ELVIS II device. The developed board has the main advantage of being an inexpensive mixed signal platform to teach important concepts in electronics embedded system laboratories, and it will suit well the educational needs of the post-COVID era. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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COVID-19 is an infectious disease caused by SARS-CoV-2 virus. It has disrupted the normal life of people, medical infrastructure, and economy globally. Remote health monitoring is a better option in pandemic diseases such as COVID and Ebola virus. Remote health monitoring can be enhanced by effectively using various recent advancements in technology. Technological advancements such as Wireless Body Area Networks (WBAN), Internet of Things (IoT), Artificial Intelligence (AI), and medical robotics for improving the effectiveness of remote health monitoring in COVID-19 pandemic are reviewed and presented in this chapter. Building expert systems using WBAN, IoT, AI, and robotics is an optimal choice to remote monitor COVID and reduce infection spread and mortality. Detailed architecture, use cases, impacts, workflow, applications, and future directions toward building a better expert system is highlighted in this chapter. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
ABSTRACT
The supply chain in the construction industry faces numerous constraints such as a lack of coordination, communication, collaboration, and technological advancement. Supply chain management is critical when products are transferred from one organization to another until they reach end users or consumers without being damaged, counterfeited, or delayed. Despite extensive research, little is known about the factors that will lead to better construction supply chain management. The reason for this examination is to make a bibliometric investigation in light of the verifiable solidification of distributions and branches of knowledge. It intends to recognize research trends, authers, nations, and organizations utilizing VOSviewer. The construction project all over the world have been uncovered in different manner by the COVID-19 pandemic. This paper makes sense of how it is feasible to proceed with development work in this present circumstance. The relevant literature in the field of Blockchain in construction supply chain management is retrieved using the Scopus, Web of Science database as the research object. If the construction work carry on, the economic downturn will be decreased and unemployment will also be decreased. The mapping of Blockchain Construction Supply Chain Management scientific production enabled the visualization of networks of co-occurrence of keywords. © 2022 IEEE.
ABSTRACT
Technological advancements, such as the usage of augmented reality (AR) technology, are increasingly supporting the creation and implementation of more interactive learning media in the field of education. The conditions and scenario of the Covid-19 epidemic are also driving an increase in digital and online schooling. The more diverse the apps generated, the more they must analyze the user experience of the application's design and operation. The User Experience Questionnaire (UEQ) tool may be used to measure user experience in apps. With 26 questionnaire points, this test has six rating scales: Attractiveness, perspicuity, efficiency, dependability, stimulation, and novelty. The UEQ Quality findings reveal that the Attractiveness scale is 2.04, the Pragmatic Quality scale is 1.68, and the Hedonic Quality scale is 1.17, all of which indicate good assessment results, implying that users prefer the program in terms of user experience. Users have utilized comparable programs based on this data, yet updates are still absent. Attractiveness, Perspicuity, Efficiency, and Stimulation are good scales. Based on the findings of the respondents' data processing, it was determined that the application's convenience was adequate in the user's opinion. According to the statistics, the user loved the program. © 2022 IEEE.
ABSTRACT
Technology is massive support in the current times in living our lives. Technology surrounds every day and every bit of our daily lives. The technological advancements and their acceptance also justify the need for a complete understanding across generations. We live in a society where older people are also an integral part of society. When we check them and their needs, especially during the COVID-19 pandemic and in these new normal times, we can see that their need and quick adaptation to the surrounding seem more obligatory. Therefore, the merger of technology with age is critical. Assessing their need and looking at their well-being and better living becomes the priority for every stakeholder living in our society. Technology comes as a powerful, liberating way of backing older adults. This research follows a systematic review of journal papers published between 2000–2022 and tries to check how other researchers looking for this merger of technology and ageing are reporting in this synthesis. A detailed scientific plan is followed in extraction and analysing the seminal work done in this area in the considered time period. The research identified and reported many diverse areas where researchers worked on understanding the merger between technology and ageing. The study reported the critical areas of the technology amalgamation with age and identified the gaps in the existing theories where the future direction of work can take place. The study also highlighted specific vital takeaways for the practitioner that can be considered the next big step in this advanced technology adoption in this new normal era. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
ABSTRACT
Education plays a significant role in every country in this world. Nowadays, lecturers are burdened with many roles such as researcher, administrator, counsellor, and many others. The position of a lecturer is very important for the success of institutions. To provide a professional service, they should be mentally and physically fit. High levels of work stress were associated with lower work-life balance and increased conflicts in their jobs. The Covid-19 pandemic has made it tough for teachers duties of teaching online while working from home. So, it is important to see what factors matter to the lecturers in Malaysia in balancing their work and life. Therefore, this study seeks to identify the factors affecting work-life balance among lecturers in Malaysia. The dependent variable in this study was work-life balance while the independent variables were made up of three major factors;i.e., individual, organizational, and environmental with six sub-factors, namely emotional intelligence, spiritual intelligence, work overload, organizational support, technological advancement, and telecommuting. For this research, a total of 435 lecturers participated and were contacted by email for answering the online survey questionnaire, and the Statistical Package for Social Sciences Software (SPSS) was used to conduct multiple regression analysis in evaluating the relationships between the variables. The findings of this study revealed that the individual factors, organizational factors, and environmental factors were partially supported because only one sub-factor was significant in each factor. Work overload is the most influencing factor affecting the lecturer's work-life balance in Malaysia, while emotional intelligence is the least influencing factor. In addition, the result depicts that only emotional intelligence, work overload, and technological advancement made a significant impact on work-life balance. Whereas spiritual intelligence, organizational support, and significantly explain the variance in work-life balance significantly. The findings of the study provide the Ministry of Higher Education and policymakers with key information to increase and maintain the lecturers’ work-life balance. At the same time, this study improves their skills in managing their emotions and their time to meet their deadlines which can help foster and reinforce a separation between work and home environment. © 2022, Association Res Militaris. All rights reserved.
ABSTRACT
The first case of COVID-19 was found in December 2019 which was followed by an exponential growth in the of people infected worldwide. On March 11, 2020 world Heath organisation declared the outbreak of coronavirus a global pandemic and this situation continues till date, i.e. May 2021. The scarcity of resources and knowledge about treating COVID-19 and with an increasing number of infected persons and deaths has made government bodies worldwide struggle to save the lives of people as well as to keep healthcare professionals safe from the virus. For almost a year, people have had to adapt to the new normal and follow some safety guidelines to keep themselves from getting infected. In such difficult times, technological advancements have played a vital role, be it diagnosis, treatment, contact tracing containment of the spread or even helping people with the new normal lifestyle. In this paper, we have discussed the type of technologies that have emerged to fight against COVID-19. We have also discussed the strengths, weaknesses opportunities and threats with the help of SWOT analysis of the technology used in various fields mentioned. © 2022 IEEE.
ABSTRACT
Methods to collect data in construction engineering and management (CEM) research are evolving, informed by recent technological advancements. One such method is research charrettes that allow effective interactions and knowledge sharing between expert industry practitioners and academic researchers, all colocated in a single venue, enabling rich data collection and live communication. A pivot point in technological evolution occurred with the COVID-19 pandemic, forcing a global shift to remote work. Hence, planned in-person research charrettes had to shift to remote sessions, relying on virtual conferencing platforms and online data collection mechanisms. Technology-enabled charrettes have allowed the authors to collect significantly richer data sets and ensure a more diverse representation of participants, while saving tremendous amounts of time. With the continuing emergence of technological applications, the world might not go back to functioning fully in person. The authors believe remote research charrettes (RRCs) will still be used in a post-COVID-19 world because of their superior performance. This paper builds on a previous publication that described traditional research charrettes as a method to enhance CEM research a decade ago;it offers a significantly updated and improved RRC method based on the knowledge gained from transitioning a dozen in-person charrettes into RRCs. It also presents performance comparisons between RRCs and traditional charrettes by quantifying metrics indicating how RRCs are more time-efficient and cost-saving, harness more participants from more diverse locations, and enable the collection of richer data sets and four times more industry comments and expert feedback. This paper also provides guidance on the integration of technology with traditional research charrettes, hence contributing to the CEM body of knowledge. © 2022 This work is made available under the terms of the Creative Commons Attribution 4.0 International license.
ABSTRACT
Twitter users post tweets on many topics, emotions, and events. The technological advancement and ease of tweeting quicken people's interaction with social network sites. Engagement with tweets led to product promotion in many corporate companies. Many studies focused on understanding tweeting patterns for marketing, retweeting, getting noticed, and receiving feedback. The time of a tweet was used for marketing strategies. Domain-based tweet timestamp patterns helped corporates in their tweet schedules and attracted more customers for their products. We collected 2.3 million depressive, anti-depressive, and COVID-19 tweets for one year. Our analysis of these tweets results in detailed tweet patterns in different timings in a day and days in a week. The depressive tweets follow the diurnal pattern, whereas the anti-depressive tweets follow a similar trend with intermediate aberrations. We also classified the tweet keywords into three different types with their frequency and amplitude of tweet patterns. Analyzing multi-domain tweets to discover time series patterns related to human health will be helpful for the planning and execution of medical disaster preparedness and emergency teams. © 2022 ACM.
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Purpose Adopting digital technology could facilitate the public health response to the COVID-19 pandemic. Some analysts argue that countries that adopted digital technology in their health sector have managed to control the virus better (Whitelaw et al., 2020). For instance, countries with more comprehensive contact tracing have significantly lower fatality rates (Yalaman et al., 2021). Moreover, World Health Organization (WHO) believes this technology is a crucial enabler for countries to meet the current challenge (WHO. Regional Office for the Western Pacific & University of Melbourne, 2021). In this regard, this study aims to quantitatively find the relationship between the technological advancement of countries and COVID-19 health outcomes, using seven technological indices that measure technological advancement. Design/methodology/approach The authors used the multiple linear regression method to answer the research questions. The first analysis focuses on a cross section of all countries worldwide, and the second focuses on European countries for which weekly death statistics exist after the pandemic. Findings The findings support those countries with more technological abilities managed to control the virus's mortality better, as evidenced by the negative link between the mortality rate of COVID-19 and the technological factors at the national level. Results also reveal that technology adoption decreases the death risk due to COVID-19 in countries with more elderly people. The authors may argue that technological advancement positively correlates with the number of deaths and diagnosed cases because the authors can better collect data or because the virus spreads due to higher economic and business activities. However, such technological advancement significantly decreases the death risk (lower mortality rate in the first analysis and lower mortality rate for elderly people in the second analysis). Research limitations/implications Three important conclusions could be made from the results: a lower mortality rate is generally expected for countries adopting advanced technology;technological advancement significantly decreases the death risk for elderly people;and a higher technology adoption level does not necessarily result in fewer diagnosed cases of/death due to COVID-19. Originality/value Although some studies have focused on e-health applications in the public health response to the COVID-19 pandemic, no studies, to the best of the authors' knowledge, have tried to quantify its efficacy, most especially on the global level.
ABSTRACT
Latest technological advancements in the modern world led to innovations which if tackled properly yields value-added outcomes or may result in disruptions if mishandled. One such technology is NoSQL databases that evolved in hundreds of numbers. Though these support a wide number of features such as consistency, availability, fault-tolerance, scalability, and security, there is no single store that bundles all together. Particularly, due to drastic data rise that accounted up to the big data, it has become essential to compromise with security while focusing on consistency and vice versa in similar directions. Another aspect to be considered lies in the ability to handle streaming data which required a special kind of storage to process data on fly. This gains wide support if integrated with various learning platforms such as deep and machine learning to yield an added outcome. However, the application of pre-processing techniques and the identification of training versus test data split irrespective of the dataset is an essential activity to be carried out to infer better results. Also, the selection of an appropriate algorithm to identify the outliers in voluminous data is essential to quantify the results. Toward this end, an efficient hybrid machine learning algorithm polynomial-Bayesian-support vector machine (PBS) is developed to overcome aforementioned big data analysis-based difficulties and results are evaluated to make an inference about the effectiveness of the proposed work. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Recent technological advancements have opened the path for smart gadgets, including wearable devices. Wearable sensors can predict human body motions and track a variety of medical symptoms associated with chronic diseases. The proposed study utilizes IoT sensors to monitor human bodily states, with the obtained data being saved in a cloud context. The data saved in the cloud environment is analyzed further using data analysis algorithms to enable clinicians' efficient monitoring and prompt response. Moreover, data fluctuation may assist physicians in notifying them of emergencies, preserving a precious human life. The proposal might be implemented efficiently in emergency medical settings when patients need continual monitoring and the greatest attention from medical professionals. The suggested idea might be used to deploy several life-threatening conditions such as spinal muscular atrophy, hypertrophic cardiomyopathy, and Covid patient monitoring. © 2022 IEEE.