To follow the macroeconomic scenario in which the entities are inserted, financial reporting is constantly evolving. In addition to the topics that need to be considered, there is also an evolution in how the report itself is produced and analyzed where technological developments exert a permanent influence on the process. Several of the trending topics do not fall within the jurisdiction of the competent authorities. The needs of the users of the report also influence the form and content of the report as an element that also changes over time. Accounting and Financial Reporting Challenges for Government, Non-Profits, and the Private Sector addresses the latest accounting topics and their practical and educational relations with local and international regulations, standards, and practices. It deals with new challenges and trends in accounting and reporting for organizations from different institutional sectors, including private, public, and non-profit ones. Covering topics such as creative accounting, financial reporting, and stakeholder participation, this premier reference source is an excellent resource for accountants, government officials, business leaders, managers, policymakers, students and educators of higher education, librarians, researchers, and academicians.

Explainable artificial intelligence is proficient in operating and analyzing the unconstrainted environment in fields like robotic medicine, robotic treatment, and robotic surgery, which rely on computational vision for analyzing complex situations. Explainable artificial intelligence is a well-structured customizable technology that makes it possible to generate promising unbiased outcomes. The model's adaptability facilitates the management of heterogeneous healthcare data and the visualization of biological structures through virtual reality. Explainable artificial intelligence has newfound applications in the healthcare industry, such as clinical trial matching, continuous healthcare monitoring, probabilistic evolutions, and evidence-based mechanisms. Principles and Methods of Explainable Artificial Intelligence in Healthcare discusses explainable artificial intelligence and its applications in healthcare, providing a broad overview of state-of-the-art approaches for accurate analysis and diagnosis. The book also encompasses computational vision processing techniques that handle complex data like physiological information, electronic healthcare records, and medical imaging data that assist in earlier prediction. Covering topics such as neural networks and disease detection, this reference work is ideal for industry professionals, practitioners, academicians, researchers, scholars, instructors, and students.

Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data discusses the insight of data processing applications in various domains through soft computing techniques and enormous advancements in the field. The book focuses on the cross-disciplinary mechanisms and ground-breaking research ideas on novel techniques and data processing approaches in handling structured and unstructured healthcare data. It also gives insight into various information-processing models and many memories associated with it while processing the information for forecasting future trends and decision making. This book is an excellent resource for researchers and professionals who work in the Healthcare Industry, Data Science, and Machine learning.

5G IoT and Edge Computing for Smart Healthcare addresses the importance of a 5G IoT and Edge-Cognitive-Computing-based system for the successful implementation and realization of a smart-healthcare system. The book provides insights on 5G technologies, along with intelligent processing algorithms/processors that have been adopted for processing the medical data that would assist in addressing the challenges in computer-aided diagnosis and clinical risk analysis on a real-time basis. Each chapter is self-sufficient, solving real-time problems through novel approaches that help the audience acquire the right knowledge. With the progressive development of medical and communication - computer technologies, the healthcare system has seen a tremendous opportunity to support the demand of today's new requirements.

Data Science for COVID-19 presents leading-edge research on data science techniques for the detection, mitigation, treatment and elimination of COVID-19. Sections provide an introduction to data science for COVID-19 research, considering past and future pandemics, as well as related Coronavirus variations. Other chapters cover a wide range of Data Science applications concerning COVID-19 research, including Image Analysis and Data Processing, Geoprocessing and tracking, Predictive Systems, Design Cognition, mobile technology, and telemedicine solutions. The book then covers Artificial Intelligence-based solutions, innovative treatment methods, and public safety. Finally, readers will learn about applications of Big Data and new data models for mitigation.

Data Science for COVID-19, Volume 2: Societal and Medical Perspectives presents the most current and leading-edge research into the applications of a variety of data science techniques for the detection, mitigation, treatment and elimination of the COVID-19 virus. At this point, Cognitive Data Science is the most powerful tool for researchers to fight COVID-19. Thanks to instant data-analysis and predictive techniques, including Artificial Intelligence, Machine Learning, Deep Learning, Data Mining, and computational modeling for processing large amounts of data, recognizing patterns, modeling new techniques, and improving both research and treatment outcomes is now possible.

This book shows how behavior analysis can be applied to teaching reading and writing to primary school students and to special populations, such as children with intellectual and hearing disabilities and illiterate adults. Originally published in Portuguese, this contributed volume is now translated into English and presents for the first time to international researchers and students a comprehensive overview of a research program developed for more than three decades in Brazil which gave birth to a unique teaching program based on the concept of stimulus equivalence: the Learning to Read and Write in Small Steps. The book is divided into four parts. The first part presents the theoretical framework and the historical context in which the teaching program was developed by the group led by Drs. Julio Cesar de Rose and Deisy das Graças de Souza, currently organized in the National Institute of Science and Technology on Behavior, Cognition, and Learning (INCT/ECCE). The second part describes the modules that make up the Learning to Read and Write in Small Steps teaching program. The third part presents results of empirical research conducted with children with intellectual and hearing disabilities and illiterate adults. Finally, the fourth part presents contributions from other areas of knowledge – such as speech therapy, linguistics, and education – to the understanding of reading and writing and possible dialogues between them and behavior analysis. Contributions of Behavior Analysis to Reading and Writing Comprehension will be of interest to researchers and students in the fields of psychology and education interested in the application of behavior analysis to teaching and learning processes. It will also be a valuable resource for professionals directly working in educational institutions, such as elementary school teachers and psycho-pedagogues.   The translation of the original manuscript in Portuguese was done with the help of artificial intelligence. The present version has been revised technically and linguistically by the authors in collaboration with a professional translator.

Wireless sensor networks have gained significant attention industrially and academically due to their wide range of uses in various fields. Because of their vast amount of applications, wireless sensor networks are vulnerable to a variety of security attacks. The protection of wireless sensor networks remains a challenge due to their resource-constrained nature, which is why researchers have begun applying several branches of artificial intelligence to advance the security of these networks. Research is needed on the development of security practices in wireless sensor networks by using smart technologies. Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks provides emerging research exploring the theoretical and practical advancements of security protocols in wireless sensor networks using artificial intelligence-based techniques. Featuring coverage on a broad range of topics such as clustering protocols, intrusion detection, and energy harvesting, this book is ideally designed for researchers, developers, IT professionals, educators, policymakers, practitioners, scientists, theorists, engineers, academicians, and students seeking current research on integrating intelligent techniques into sensor networks for more reliable security practices.

THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.

Discussions around the preservation of privacy and confidential data of patients parallels discussions about innovation, effectiveness, and quality of care that the use of technology can provide in health services. The use of technology in the management of health services and in the provision of care in hospital establishments can pose ethical issues. An effective solution needs to be concocted before the use of this technology disturbs the privacy practices of today's healthcare systems. Emerging Trends and Innovations in Privacy and Health Information Management is a collection of innovative research on the methods and applications of the preservation of privacy and confidential data of patients. While highlighting topics including privacy laws, ethical issues, and healthcare security, this book is ideally designed for professionals and researchers working in the fields of health, social intervention, and information management.

Cerebral Dural Arteriovenous Fistulas serves as an authoritative, comprehensive resource for these vascular lesions, describing their anatomy, diagnosis, natural history, and thorough treatment options. Rooted in well-illustrated anatomy and depictions of dAVFs, readers can better understand their pathophysiology, historical discovery, and avenues for treatment, including embolization, surgery, and radiosurgery. Imaging modalities are also discussed extensively as well as the management of these lesions. This reference is appropriate for neurosurgeons, neurologists, interventional radiologists and intensivists that manage these patients, providing clarity, and at the same time, comprehensiveness.

In the field of second language (L2) acquisition, the number of studies focusing on L2 pronunciation instruction and perceptual/production training has increased as new classroom methodologies have been proposed and new goals for L2 pronunciation have been set. This book brings together different approaches to L2 pronunciation research in the classroom or in the language laboratory. 13 chapters, written by well-known researchers focusing on a variety of first and target languages, are divided into four parts: Pronunciation development and intelligibility: implications for teaching and training studies; L2 pronunciation teaching; L2 pronunciation training: implications for the classroom; and Pronunciation in the laboratory: High Variability Phonetic Training. Intended for researchers in the fields of second language acquisition, phonetics, phonology, psycholinguistics, speech therapies, speech technology, as well as second language teaching, this book not only summarizes the current research questions on L2 pronunciation teaching and training, but also predicts future scenarios for both researchers and practitioners in the field.

This book presents case studies that share important experiences regarding Integrated Water Resource Management (IWRM) in various countries. Following an introduction to theoretical concepts, responsibilities, and challenges, the subsequent chapters address, among other topics, an analysis of policies and regulations for water management in Brazil, the drivers that led California to adapt to the IWRM framework, and the international regulations for water markets and water banking in Australia and Chile. The implications of climate change for water resource systems in Mexico are discussed, as well as management strategies from California that could potentially serve as IWRM adaptation schemes in Mexico. Critical cases from Guanacaste (Costa Rica), and from Zayandehrud River Basin and Lake Urmia (Iran) are reviewed in terms of management practices and solutions. The book also provides an overview of the current availability and use of water resources in South Korea, and discusses the management of and international water law instruments for transboundary groundwater in Africa.