TabNet Based Prediction Model for ICU admission in Covid-19 patients

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the responsible virus for coronavirus disease 2019 (COVID-19). It was reported the first time in Wuhan (China) by late December 2019. The COVID-19 pandemic has become a global health risk due to the urgent need for an Intensive Care Unit (ICU) that exceeded its capacity. To cope with this exponential spread the fast adoption of Artificial Intelligence (AI) tools and advanced technology is crucial. For this reason, many research works in AI are conducted. In the current paper, we intend to report AI applications and solutions based on machine learning, deep learning, and data mining algorithms for detecting, predicting, and diagnosing COVID-19. Furthermore, this study aims to develop a new deep learning-based method capable of predicting whether a COVID-19 patient requires admission to an intensive care unit using clinical tabular data from Kaggle. This model will contribute to the optimization of ICU resources. The experimental results showed that combining Synthetic Minority Oversampling Technique (SMOTE) and TabNet classifier improved the prediction performance and surpassed the state-of-the-art models: MLP, RF, LR, and KNN. © 2022 IEEE.

Torch Relay Commemorative Photography × Ultra-realistic Communication Technology Kirari!

Due to the spread of COVID-19, the number of people who experienced the exhibits was less than planned. Nevertheless, we were able to deliver surprises and smiles to the participants at the venues where we could provide the experiences. We believe that these interactions with the advanced technologies of our laboratories, which are not normally accessible to the public, enabled many people to experience firsthand NTT's innovativeness. Going forward, we will continue to work on creating new experiences using ICT and connect people with each other. © 2022 Nippon Telegraph and Telephone Corp.. All rights reserved.

The Role of Edge Computing in Pandemic and Epidemic Situations with Its Solutions

Managing sensory data captured in leveraging is a challenge, especially during a pandemic when trying to capture the psychological, emotional, and physiology standards. The advanced technology of edge computing and IIoMT together help to reach promising outcome results from the home environment using psychological feelings and somatic health equivalent data. The basic application of Deep Learning leads to the asset-constraint of edge computing, which provides a way to move the data that is collected from IIoMT devices to various locations. All kinds of data related to health can exist in a particular place of user edge while assuring the security, privacy, and low latency of the inference system. In this article, an Internet of Medical system is developed that uses Deep Learning to detect risky types of health-related symptoms and generates reports and alerts for pandemic and epidemic situations, which helps in decision-making support. In these pandemic and epidemic situations, a lot of applications have been identified and implemented with their descriptions for the upcoming support for the real-time trials. We have developed smart applications in edge computing manuals. The overall output clearly allows us to view the fixed smart systems during the pandemic with the Smart Health Management system (SHMs). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

Maritime Disruption Impact Evaluation Using Simulation and Big Data Analytics

Disruptions in maritime networks may cause significant financial burden and damage to business. Recently, some international ports have been experiencing unprecedented congestions due to the COVID19 pandemic and other disruptions. It is paramount for the maritime industry to further enhance the capability to assess and predict impacts of disruptions. With more data available from industrial digitization and more advanced technologies developed for big data analytics and simulation, it is possible to build up such capability. In this study, we developed a discrete event simulation model backed with big data analytics for realistic and valid inputs to assess impacts of the Suez Canal blockage to the Port of Singapore. The simulation results reveal an interesting finding that, the blockage occurred in the Suez Canal can hardly cause significant congestion in the Port of Singapore. The work can be extended to evaluate impacts of other types of disruptions, even occurring concurrently. © 2022 IEEE.

"Expo City Dubai": A Convergence of Smart Touristic and Residential Experience

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.

Impact of FinTech on the Sustainable Development of Bahrain During Covid-19 Pandemic

Fintech involves advanced technology-based solutions for the customers while not being dependent on the banking system and rather focuses on the other virtual currency options. The emergence of these methods especially cryptocurrencies and blockchains after the financial crisis of 2008–9 is more important for the sustainability and development of a country since Fintech is also an advancement in mediums of money flow. The present research has explored the effect of Fintech on sustainable development (economic, society, and environment) while focusing on the existing literature. The previous literature and theories represent that there is a significant influence of Fintech on sustainable development however, the influence differs in different countries and situations. Based on this, the study has identified that there has been no research on the role of the Covid 19 pandemic among Fintech and sustainable development of Bahrain and suggested quantitative research for the future. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Conceptual Framework of Contact-Less Consumer Products Industry During and Post-pandemic Era

The COVID-19 era has reshaped the world regarding the contact-less economy, healthcare systems, remote work environment, people's lifestyle and their daily routines, etc. The consumer products (CP) industry is being impacted due to the behaviours of consumers during self-quarantine. This accelerates adopting digital transformation and upgrading the business models for the contact-less CP industry. Accordingly, this study provides a step toward the contact-less CP industry during and post-pandemic. First, we have proposed a conceptual framework for the contact-less CP industry that aims to bring together the key advanced technologies (e.g., Digital Twin (DT), blockchain, AI, cloud computing, 5G, and robots). The combination of the advanced technologies provides data monitoring, transparency, traceability, automation, and data sharing among consumers and CP partners. The proposed framework will enable a more contact-less personalized interaction that will work towards higher levels of consumer satisfaction while maintaining contact-less economy growth. Then, we have described how the proposed framework can be applied for contact-less delivery services for the CP industry during and post-pandemic. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

A systematic and critical review of Internet of Things in contemporary hospitality: a roadmap and avenues for future research

Purpose>Internet of Things (IoT) is a key enabler of big data and it is critical toward a new age of firm's architecture and proper decision-making for the industry. IoT adoption by the hospitality and tourism (H&T) industries is still rare and with contrasting evidence. The purpose of this study is to highlight the concept of IoT, its benefits, its challenges and its applications in the hospitality industry.Design/methodology/approach>This study presents an in-depth and critical review of the 78 articles published on IoT in hospitality, spanning more than seven years (from 2015 to March 2022). The eligible 78 articles were collected from the "Web of Science database” and H&T Social Sciences Citation Index-listed journals.Findings>This systematic review exhibits that IoT in hospitality has advanced in the past seven years. IoT has brought many advantages and challenges in hospitality. However, hospitality IoT research is scarce, necessitating a profound and more thorough investigation of many significant matters.Practical implications>This systematic review provides significant implications and recommendations for hospitality sectors, IoT developers and manufacturers, governments and policymakers. This review ends with an in-depth research agenda with several research questions and a framework to achieve theoretical and empirical advances in future IoT research.Originality/value>To the best of the authors' knowledge, the current research is one of the first to systematically and critically review IoT with its concept, benefits, challenges and applications in a hospitality context. This major review provides a comprehensive idea of the focus of the past studies and what must be concentrated in future research.

Secure Data Sharing in Medical Cyber-Physical system—a Review

With the increase in advanced technologies, the health industry has developed a lot recently. Medical cyber-physical system (MCPS) plays a vital role in this. It consists of various medical devices which are networked together for smooth and efficient working. The patient’s EHR is collected and stored on the cloud which is then easily accessible by doctors. The health industry has always been on top of cyber-attacks. With the onset of the Covid-19 pandemic, there was a sudden surge in telemedicine adoption, remote working and makeshift sites for virus testing and treatment, and under-preparedness, all contributing to new vulnerabilities and giving cybercriminals a new opportunity. In the medical world, we need our medical systems to be secure, reliable, efficient, and should ensure economic data storage and sharing for both patients and medical institutes. Motivated by these facts, we did a review on various MCPS techniques and algorithms that already existed. In this paper, we tried to summarize those techniques and provide a comparative study for the same. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Second-Year Review of the NSF-DoD REU Site: HYPER

The challenges associated with achieving hypersonic flight, developing advanced propulsion systems, and designing reusable launch platforms are strongly interdisciplinary. Exposing undergraduate students to interdisciplinary research is recognized as a means to equip society's future engineers and scientists with the broad skillset necessary to contribute to these areas. The jointly funded NSF-DoD REU site Advanced Technologies for Hypersonic Propulsive, Energetic and Reusable Platforms (HYPER) unites multidisciplinary interests to study advanced structures and systems with application to hypersonics, space, propulsion, and energy. Over the course of two 10-week summer sessions (2019 and 2021), participants have gained hands-on training in contemporary challenges such as: (1) utilizing advanced manufacturing techniques for high-value components, (2) integrating in situ monitoring of stress-strain evolution, (3) developing novel methods for improved internal cooling and heat transfer effectiveness, (4) mitigating flutter through advanced rotor dynamic control, etc. Eleven research projects have been crafted to engage students in PhD-level topics. Many of these challenges rely on approaches that cut across disciplines and research techniques (e.g., experiments and computer simulation). The present reporting serves as a synopsis of challenges, advances, and lessons learned conducting the research thus far. The site HYPER has six core objectives that relate to: (1) preparing students for graduate school and/or research-oriented careers, (2) fostering technical skills in student participants, (3) improving participants' communication skills, (4) marketing to and recruiting a diverse group of participants, and more. Assessment of the program outcomes according to these objectives are reported here with data gathered after two years. Program outcomes were conducted with an external evaluator affiliated within the University of Central Florida's Program Evaluation and Educational Research Group (PEER). Results demonstrate a very effective site with strongly positive outcomes for all participants. Insights are provided so this research effort may be confirmed by other independent sites. It should be noted that the 2020 session was postponed out of an abundance of caution based on the uncertain and evolving conditions facilitated by the COVID-19 pandemic. © American Society for Engineering Education, 2022.

CSDLEEG: Identifying Confused Students Based on EEG Using Multi-View Deep Learning

Distance learning has dramatically increased in recent years because of advanced technology. In addition, numerous universities had to offer courses in online mode in 2020 and 2021 because of the COVID-19 pandemic. However, there are more challenges in distance learning than in the traditional learning method (e.g., feedback and interaction). Recently, researchers started using simple EEG headsets to identify confused students during online courses based on machine learning approaches. However, they faced unpleasant accuracy using traditional machine learning algorithms or nondeep neural networks. In this paper, we present a data-driven approach based on a multi-view deep learning technique called CSDLEEG to identify confused students. We employ the students' demographic information and EEG signals to feed our novel neural networks. The results show that our proposed approach is superior to state-of-the-art methods for 98% accuracy and 98% F1-score. © 2022 IEEE.

Nonspecific ileitis: Impact of histopathology and gastrointestinal ultrasound in achieving the diagnosis of Crohn's disease.

Background and Aim: Nonspecific ileitis is inflammation of the ileum without specific diagnostic features. A minority may go on to develop Crohn's disease, but optimal pathways of further investigation have not been established. This study aimed to identify a cohort of patients with nonspecific ileitis and to determine the value of ileal histology and gastrointestinal ultrasound in identifying/excluding Crohn's disease. Patients and Methods: In a retrospective analysis, all patients having nonspecific ileitis at colonoscopy from January 2010 to August 2021 were identified. Clinical associations with those subsequently diagnosed with Crohn's disease were examined with specific reference to ileal histology and gastrointestinal ultrasound. Results: Of 29 638 procedures, 147 patients (0.5%) had nonspecific ileitis. Crohn's disease was subsequently diagnosed in 8 patients (5.4%) at a median of 148 (range 27-603) days after colonoscopy. The presence of chronic inflammation on ileal biopsies was more common in those subsequently diagnosed with Crohn's disease (63% vs 20%; P = 0.0145). On gastrointestinal ultrasound, none of the 26 patients with normal bowel wall thickness (<3 mm) were subsequently diagnosed with Crohn's disease, and repeat ultrasound in 15 patients 1 year later showed no change. Of the nine patients with abnormal sonographic findings, three were diagnostic for Crohn's disease. Repeat ultrasound revealed Crohn's disease in two, while four had resolution of the abnormal findings. Conclusion: Although ileal histology was of limited value in identifying patients with nonspecific ileitis who were subsequently diagnosed with Crohn's disease, gastrointestinal ultrasound was highly informative. Prospective studies are needed to confirm the value of gastrointestinal ultrasound as a diagnostic and monitoring tool in this setting.

Potential Application of Picosecond Pulsed Electric Field (PPEF): Advanced Bioelectrical Technology for Potential COVID-19 Treatment

As human knowledge has increased, the efficacy and precision of tools to solve clinical problems have also increased. The challenge of COVID-19 has posed a significant threat to human life and reflects the need to upgrade existing technologies and make treatments more precise. Since the corona virus particle is in the nanometer range, the need for a device with accuracy beyond the nanometer range is apparent to control and eliminate it. Using Picosecond Pulsed Electric Fields (PPEF) could be a good antiviral picotechnology candidate. PPEF energy can (1) increase the innate immunity function of polymorphonuclear neutrophils, (2) destroy bacteria and other pathogens, and (3) potentially inactivate viral particles. This characteristic of PPEFs has already been used in the food industry. Both PPEF and nanosecond PEF technology is being used to treat cancer in research animals and has reached the stage of pre-clinical and clinical human trials with use in clinical practice soon to follow. Applying advanced PPEF technology against COVID-19 should provide new opportunities for effective human antiviral treatment. .

A Deep Learning Approach for COVID-19 Infection Probability Prediction

COVID-19 is one of the major health crises worldwide. Though number of vaccines is introduced by many countries but still it is challenging to detect the disease at early stage. Many advanced technologies are introduced for this purpose to stop the spread. Machine learning based COVID detection can be a supportive tool for both physicians as well as patients for early prediction of this illness. Different automated technologies are also found from the literature for this purpose. Deep learning approach is used for predicting the infection probability by analyzing the five types of COVID symptoms. The experiment is carried out with 2889 samples collected from a publicly available database. A deep neural network (DNN) classifier is designed for this purpose and the result is also compared with support vector machine (SVM). From the result it is observed that around 97% classification accuracy is observed with DNN classifier and it is better than SVM. © 2021 IEEE.

RETHINKING KNOWLEDGE MANAGEMENT POST COVID-19

As countries around the world are adjusting in the post COVID-19 era, a new “normal” has emerged. Industries are reassessing their entire business model, assessing new ways to use advanced technology tools, reinforcing the impact of growing online commerce and preparing the return to their business. Opportunities to push digitalization and automation has accelerated by rapid learning about what it takes to drive productivity in organizations when staff are unavailable and without the resources they would normally access. The pandemic has also shaped a new working life/environment with a combination of remote and on-site working, a hybrid model, in which some employees are on premises, while others work from home. With the explosion of workforce conversations on digital collaboration tools, knowledge now flows dynamically across the digital communications channels that define the new working relationships. This implies that the organizations’ approaches to knowledge management need to consider how emerging technologies, such as Artificial Intelligence and collaborative platforms, can support problem-solving and help workers innovate and uncover new insights. The paper aims to perform an analysis of the impact which innovative technologies may have on the implementation and application of KM initiatives and activities in the post-COVID era. Moreover, as knowledge management and working life are strongly connected to each other, their relation is also further analyzed. In particular, the paper will investigate the new trends in working life, such as Work 4.0, and discuss their criticality and applicability. To summarise, the paper will highlight the changes that have been inevitably induced by the pandemic in organizations and in the ways employees work, not only acquiring and creating new knowledge using technology, but continuously disseminating it throughout the organization. Copyright © 2021 by the American Institute Federation of Aeronautics and Astronautics, Inc. All rights reserved

Research on the Transformation of Traditional Foreign Trade Enterprises to Cross-Border ECommerce

There has been increasingly widespread economic trade activities on the Internet - cross-border e-commerce with global reach, a profound commercial revolution in international trade. In 2020, COVID-19 has broken out and brought a huge impact to the global economy and a severe test to China's traditional foreign trade enterprises. However, cross-border ecommerce unleashes its huge potential, showing a leading role in the innovative development of foreign trades. Supported by advanced technologies, cross-border e-commerce has become an important driving force in the transformation and upgrading of China's traditional foreign trade enterprises, with low operating costs, high efficiency, flexible operation and high profitability. This paper analyzed the connotation and characteristics of cross-border e-commerce, and elaborated on the problems faced by Chinese traditional foreign trade enterprises in the process of transforming into cross-border e-commerce, and put forward corresponding countermeasures and suggestions for the problems faced. © 2021 IEEE.

Analysis on the Development of Smart Logistics of Agricultural Products under Epidemic Situation

The sudden outbreak of COVID-19 has not only affected people's normal life, but also brought certain impact on logistics. People's demand for agricultural products suddenly increased in a short time, and agricultural products logistics didn't have time to respond. Many new problems have been exposed, because there are many intermediate links in agricultural products logistics, so on the basis of higher logistics cost, it also increases the problem that logistics cannot guarantee timely supply. In addition, the price of agricultural products is low, and the cost of advanced technology is high, so it is impossible to use modern technology to trace the source of agricultural products. During the epidemic period, because the severity of the epidemic varies from place to place, it is particularly important to trace the source of products;at the same time, due to the sudden outbreak of the epidemic, it also brought challenges to emergency logistics, and the response of emergency logistics in various places was slow. However, the epidemic has brought difficulties to logistics and also created opportunities for the development of smart logistics. In order to avoid human contact, information registration systems have been adopted in various places, and unmanned driving, automatic warehousing, automatic distribution and logistics robots have been put into use, which has promoted the sharing of information by smart logistics using the Internet and the intelligentization of logistics operation process. © 2021 IEEE

Understanding the role and capabilities of Internet of Things-enabled Additive Manufacturing through its application areas

The purpose of this paper is to highlight the importance of the effective utilisation of internet-based technologies in Additive Manufacturing (AM) through its practical implications in various areas. The key technologies that comprise the Industry 4.0 paradigm and have been previously implemented into the AM process possess immense potential to bring about miraculous manufacturing changes. The ongoing pandemic situation, too, has pushed the industries into the deployment of advanced technologies to deal effectively with the major challenges that followed COVID-19 and to keep up with customers' expectations. Therefore, manufacturing industries need to adopt the latest internet-based technologies into AM, especially for lean and optimised manufacturing and perceived proficiency of advanced printing technologies. This paper identifies goals of sustainable manufacturing that can be accomplished as a result of implementation of Internet of Things (IoT) in 3D printing technology. Also, since the Internet of Things-enabled AM process is an entirely new concept, limited sources are available in this field. Pubmed, Scopus, and Google Scholar databases are used to conduct literature reviews. The study conducted is the most up-to-date information on Internet of Things-enabled AM and is rigorously analyzed to identify prospective application areas. Thus, IoT-enabled AM helps in producing sustainable solutions for humanity and in meeting customers' demands in the stipulated period, thereby contributing to mass personalisation, which is the ultimate goal of Industry 4.0. © 2021 Kingfa Scientific and Technological Co. Ltd.

Students Talk: The Experience of Advanced Technology Students at Two-Year Colleges during COVID-19

There have been many questions and concerns raised by educators about how advanced technology students will adapt to remote learning during the COVID era. What will technician students' academic engagement and persistence be like, and how will online learning affect their educational outcomes? What do technician students like about remote learning and what do they find challenging? What does online learning mean for hands-on applied and experiential learning, which are hallmarks of technical education programs? This paper explores pilot state-level survey data from advanced technology students at two-year colleges. Five primary areas covered in the survey include enrollment status, access to technology, experience using a Learning Management System and learning online, impact on applied and experiential learning, and students' background information. Key findings include decreased interaction between peers, increased reliance on instructors, and a significant decline in experiential learning such as labs, group projects, demonstrations, problem-based learning, and service-learning. The majority of students report feeling worried about making progress toward their degree, and about half worried about completing the semester. Two benefits students identified was having access to course materials all the time through the LMS and the flexibility of remote learning. Findings also show that technician students are quite diverse by way of age, partner status, having a family, race-ethnicity, employment status, and educational background. About one-third of students who responded are women. This paper concludes with several recommendations about the application of these research findings to address challenges technician students face learning online, including specific actions that instructors and programs can pursue to help retain students and provide support to facilitate completion of degree programs. © American Society for Engineering Education, 2021