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The home health-care industry is under growing pressure to deliver services more effectively to meet the increasing demand from care recipients, particularly the elderly population. It is estimated that U.S. home health-care expenditures will rise from US[Formula Omitted]108.8 billion in 2019 to US$186.8 billion in 2027 [1] . A simultaneous ongoing shortage of physicians, registered nurses, certified nursing assistants, and social workers has created a major service delivery gap in the home health-care industry, especially in rural areas where timely access to quality health-care services is very limited [2] . The recent COVID-19 pandemic exacerbated this problem as it isolated many care recipients from their caregivers or friends.
ABSTRACT
THE 19th International Workshop on Data Mining in Bioinformatics (BIOKDD 2020) was held virtually on August 24, 2020 due to the COVID-19 pandemic. BIOKDD 2020 featured the special theme of "Battling COVID-19" which particularly welcomed paper submissions and invited talks related to COVID-19 research. As a whole-day workshop, altogether 15 submissions were accepted among a total of 35 submissions, and they were divided into 4 sessions: (1) Bioinformatics, (2) Data Curation, (3) Deep Learning with Biomedical Data, and (4) Data Mining & Statistical Methods. There are also 7 invited talks by domain experts. This special section features the extended versions of 6 quality papers presented in BIOKDD 2020.
ABSTRACT
The articles in this special section focus on current applications and innovations of artificial intelligence and machine learning in aerospace. Artificial intelligence (AI) and machine learning (ML) play an increasingly important role in aerospace applications and serve various military, commercial aviation, and space exploration sectors to ensure safety, dependability, and customer loyalty. AI/ML contributes to provide various automated systems used in aviation, such as fuel efficiency, smart maintenance, smart air traffic management, pilot training, passenger identification, threat identification, remote sensing, and fully autonomous aerial vehicles among other systems. AI/ML is concerned with algorithms and techniques that allow systems to “learn” and “reason” based on algorithms and techniques employing computational and statistical methods. It can significantly enhance speed, efficiency, workload, and safety to enable the integrating of more complex technologies, such as autonomous visionbased navigation and data ecosystems. Recently advanced data analytics provided the aviation industry a way to respond to COVID and advise airlines on when to swap aircraft for bigger or smaller planes and how the global health restrictions may change flight schedules. While there are many other innovative use cases of AI/ML in aviation and aerospace, the overarching conclusion is that the implementation must be driven by safety.
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The articles in this special issue focus on the emerging effects that social media can have on the real world. Social media has quickly become not just ubiquitous, but also integral to society. A large portion of social media's quick ascent was due to its modeling of real-world relationships, meaning the offline world informed the development and adoption of the online world. Recently, however, it has become apparent that this effect is not a one-way street. For example, the spread of mis- and disinformation, the spread of conspiracy theories, and the rise of extremism can all be attributed, in part, to social media. Most previous research has studied the real world and social media in isolation. However, these worlds are interconnected with each world having a substantial impact and influence on the other. For instance, hateful rhetoric disseminated via social media can encourage physical meetings that can quickly transform rhetoric into violent actions. Overall, it is of paramount importance, as a research community, to devote research resources into understanding and analyzing the exogenic effects of social media to the real world with the goal to further improves our lives.
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The papers in this special section focus on emerging Internet of Medical Things. Recent advances in advances in healthcare can be experienced with the development of smart sensorial things, Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), edge computing, Edge AI, 6G, cloud computing, and connected healthcare have attracted a great deal of attention and a wide range of views. However, the need to deliver real-time and accurate healthcare services to patients, while reducing costs is a challenging issue [1]. Especially, COVID-19 has recently demonstrated the importance of fast, comprehensive, and accurate intelligent healthcare involving different types of medical, physiological, and epidemiological investigation data to diagnose the virus. Smart health is a real-time, intelligent, ubiquitous healthcare service based on Internet of bioMedical Things (IoMT). With the rapid development of related technologies such as deep learning, edge computing and IoT, smart health is playing vital role in healthcare industry to increase the accuracy, reliability, and productivity of mobile sensory devices.
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The Symposium on Integrated Circuits and Systems Design (SBCCI) is an international forum dedicated to Integrated Circuits and Systems Design, Test and Electronic Design Automation (EDA), held annually in Brazil. The SBCCI has established itself as an important international forum for the presentation of advanced research results on leading-edge aspects of integrated circuits and systems design, such as analog circuits, mixed-signal and digital integrated circuits design, dedicated and reconfigurable architectures, EDA tools, design methods, embedded systems, SoC, and nanoarchitectures, as well as verification and test methods. This 33rd edition of SBCCI was initially planned to take place in Campinas, 100 km from São Paulo, but due to the COVID-19 pandemic, it was transformed into a virtual event.
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The articles in this special section focus on how we conduct work has and will change post COVID-19. Advances in pervasive computing are rapidly changing the way we work. Pervasive computing can improve the way workers connect into productive teams;it vastly improves the ability of organizations to collect and process data;and it provides new tools for using data in feedback loops that affect the physical or virtual world, both as personalized, small-scale interventions and as broad, largescale actions, and policy. These changes were accelerated by the COVID-19 pandemic, which resulted in a sudden and dramatic change in how we work. For many of us, the well-known mainstays of work—the eight-hour workday, the office building, the morning commute, the salient boundaries between work and personal life, in-person conversations with coworkers, and sending children to school or daycare—were gone or drastically different than they were before. And, for far too many people, the issues of inequity and racial injustice were even more pronounced than before;sections of the population bore the brunt of the difficulties far more than others. While we all hope that the COVID-19 crisis will soon subside, some of its effects are likely to remain;not all office buildings will open back in a full-time format, not all jobs lost will be available again, and the way we used to think about productivity and work-life balance may never be the same. There is also a continued risk of leaving behind workers who are unable to balance rapidly changing work responsibilities with increased demands placed on their personal lives.
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The FEBS Journal, a leading multidisciplinary journal in the life sciences, continues to grow in visibility and impact. Here, the Editor-in-Chief Seamus Martin discusses developments at the journal over the past year and the impact of the COVID-19 crisis on research activities.