1,720,958 research outputs found
Industry 4.0:use of digitalization in healthcare
Full text linkThe primary objective of this chapter is to examine the AI applications for healthcare 4.0. Using a wide range of contemporary technologies, such as digitization, artificial intelligence, user response data (ergonomics), human psychology, the internet of things, machine learning, big data mining, and augmented reality, one of the great success stories of our day is healthcare. Worldwide life expectancy has increased due to the tremendous advancements in medical research. But when people live longer, healthcare systems must deal with more people needing their services, more money spent on them, and a staff that finds it more challenging to care for patients. A healthy, productive society depends heavily on the healthcare industry, making it one of the most critical industries in the larger big data environment. Artificial intelligence (AI), which builds on automation, has the potential to transform healthcare and assist in addressing some of the issues mentioned above. AI can support healthcare professionals, including physicians and nurses, in their day-to-day jobs. Artificial intelligence (AI) can improve patient outcomes by enhancing the quality of life and preventive care and producing more accurate diagnoses and treatment regimens. This book provides an overview of the most recent advancements in artificial intelligence (AI) applications in biomedicine, encompassing pharmaceutical processing, disease diagnosis, patient monitoring, biomedical information, and biomedical research. A summary of the most recent developments in the use of AI in healthcare is also provided, along with a road map for creating safe, dependable, and efficient AI systems and a discussion of potential future directions for AI-assisted healthcare systems. Numerous uses of AI exist in the medical field. Healthcare 4.0 has brought about a paradigm shift in the healthcare industry, drawing inspiration from Industry 4.0. Therefore, how the digital revolution in healthcare will affect the quality of medical care is still being determined. This study results will help the new researchers and healthcare institutions
Use of AI applications for the drone industry
Full text linkThe unmanned aerial vehicle (UAV) industry, commonly referred to as the drone industry, has grown rapidly in recent years and changed many industries' operational procedures. Drones are adaptable AUs that have the ability to operate independently or remotely. The drone business has developed into a vibrant, diverse sector with applications in many other industries. Drone technology is set to grow and become more integrated into daily life and corporate operations as long as regulations keep up with technological advancements. Artificial intelligence (AI) technologies are increasingly used in various industries, notably drone companies. AI can improve drone technology's effectiveness, dependability, and efficiency, creating new opportunities for the drone industry to service multiple applications and sectors
E-government privacy and security challenges in the context of internet of things
Full text linkThe internet of things (IoT) is becoming more significant in everyday life as a mechanism for making major decisions in different fields as smart devices and data in real time are connected and updated. IoT is being used in a variety of ways to provide digital services to the public. Online payment, property purchase, and sailing are just a few examples. On the other hand, users' complaints about the safety and privacy of their personal information are growing. The internet of things (IoT) is becoming more popular and significantly enhances e-government. This chapter primarily focuses on how potential users can obtain information to use the internet of things and its related services within the e-government sectors. There are several technological, administrative, and political challenges to IoT adoption problems in e-government and legal problems that must be solved to develop effective and required applications. It's crucial to explore these problems and potential solutions
Addressing security issues and challenges in smart logistics using smart technologies
Full text linkSmart logistics systems (SLSs) gather, store, and transmit sensitive data, such as customer information, shipping information, and financial records. Unauthorized persons having access to sensitive data can cause data breaches, which can result in theft and misuse. Sensors, RFID tags, and other tracking and monitoring devices found in the Internet of Things (IoT) are crucial to the success of smart logistics. Intruders might potentially obtain unauthorized access and risk data integrity by exploiting security flaws in these devices. Cybersecurity concerns can arise from insiders who have permission to access an SLS, such as workers or contractors. These people may endanger the system's security inadvertently, resulting in data breaches, illegal access, or sabotage. Insider risks may be reduced by implementing appropriate access restrictions, monitoring systems for anomalous activity, and regularly performing security training. Cybersecurity procedures are designed to protect electronic data and systems from unauthorized access and theft. To safeguard oneself and one's business, a variety of cybersecurity measures can be used. We focus on some of the most significant cybersecurity measures by looking at requests for information like “Explain the cybersecurity measures.” Efficiency and speed are increasingly valued as a result of technological advancements. Modern means of transportation are included in this category. There has been a lot of focus on these vehicles from IT companies. Statistically speaking, they are far safer than regular cars. Innovations in autonomous and crewless vehicles have, like any new technology, given rise to cyberattack dangers. Hackers believe they can break into any targeted vehicle's system, and access the owner's private data without permission Therefore, the companies that produce hackers perceive numerous entry points and think they can break the security of any targeted vehicle system, steal the owner's personal identification information, and cause mechanical damage. Therefore, businesses developing autonomous vehicles must implement a robust cybersecurity architecture to protect against cyberattacks. They must better understand the nature of cybersecurity threats to autonomous vehicle systems. The dangers associated with cybersecurity are numerous for both individuals and corporations. Malicious actors, software flaws, and hardware flaws are only a few examples of the causes of these dangers. Human error, such as negligent internet browsing or clicking on dangerous links, can also result in cybersecurity issues. Many people agree that autonomous vehicles (AVs) have positive outcomes, but they worry about this technology's potential hazards and side effects. This chapter aims to peer-review the cybersecurity issues and challenges in the context of emerging technologies in transportation from the public's perspective. The results of our study will help the new research group and transportation companies
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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