الصفحة 29
الصفحة 29
Delusions in Context
This open access book offers an exploration of delusions--unusual beliefs that can significantly disrupt people's lives. Experts from a range of disciplinary backgrounds, including lived experience, clinical psychiatry, philosophy, clinical psychology, and cognitive neuroscience, discuss how delusions emerge, why it is so difficult to give them up, what their effects are, how they are managed, and what we can do to reduce the stigma associated with them. Taken as a whole, the book proposes that there is continuity between delusions and everyday beliefs. It is essential reading for researchers working on delusions and mental health more generally, and will also appeal to anybody who wants to gain a better understanding of what happens when the way we experience and interpret the world is different from that of the people around us.
Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics : Techniques and Applications
Examines and demonstrates state-of-the-art approaches for IoT and Machine Learning based biomedical and health related applications. This book aims to provide computational methods for accumulating, updating and changing knowledge in intelligent systems and particularly learning mechanisms that help us to induce knowledge from the data. It is helpful in cases where direct algorithmic solutions are unavailable, there is lack of formal models, or the knowledge about the application domain is inadequately defined. In the future IoT has the impending capability to change the way we work and live. These computing methods also play a significant role in design and optimization in diverse engineering disciplines. With the influence and the development of the IoT concept, the need for AI (artificial intelligence) techniques has become more significant than ever.
Deep learning architecture and application
As one of the fastest-growing topics in machine learning, deep learning algorithms have achieved unprecedented success in recent years. Novel paradigms (such as contrastive learning and few-shot learning) in deep learning and rising neural network architectures (e.g., transformer and masked autoencoder) are dramatically changing the field of data-driven algorithms. More importantly, deep learning models are redefining the next generation of industrial applications spanning image recognition, speech processing, language translation, healthcare, and other sciences. For example, recent advances in deep representation learning are allowing us to learn about protein 3D structures, which sheds new light on fundamental medicine and biology along with potentially bringing in billions of dollars (e.g., in the pharmaceutical market).
Decision science for future earth : Theory and practice
Provides a theoretical framework and case studies on decision science for regional sustainability by integrating the natural and social sciences. The cases discussed include solution-oriented transdisciplinary studies on the environment, disasters, health, governance and human cooperation.
Death in a consumer culture
Organised into five sections covering: The death industry; death rituals; death and consumption; death and the body; and alternate endings, The book explores topics from celebrity death tourism, pet and online memorialization; family history research, to alternatives to traditional corpse disposal methods and patient-assisted suicide. Work from scholars in history, religious studies, sociology, psychology, anthropology, and cultural studies sits alongside research in marketing and consumer culture.
Deadly Dermatologic Diseases : Clinicopathologic Atlas and Text
Includes understanding of the biologic behavior of pigmented lesions, cutaneous lymphomas, vascular lesions, and soft tissue tumors.It discusses a wide variety of entities–neoplastic, vascular, infectious, metabolic–each of which may eventuate in death of the patient. In addition, numerous tumors and dermatoses frequently associated with internal malignancies are reviewed. High-quality histologic photomic- graphs and clinical pictures accompany many of the discussions.
De Barrett à Zollinger-Ellison Quelques cas historiques en gastroentérologie = From Barrett to Zollinger-Ellison Some historical cases in gastroenterology
Portrays the character traits, the little quirks or the great faults of this illustrious character. In a text combining science, history and humor, we are presented with the essentials of what should not be forgotten.
Daylighting Design Planning Strategies and Best Practice Solutions
The primary objective of daylight systems is to make maximum use of daylight for certain building types and climates. The book documents the various dimensions of the optimum use of daylight with particular reference to window orientation, light distribution, and prism technology, and discusses the health and economic related aspects.
Data-Driven Policy Impact Evaluation : How Access to Microdata is Transforming Policy Design
Provides statistical tools for evaluating the effects of public policies advocated by governments and public institutions. Experts from academia, national statistics offices and various research centers present modern econometric methods for an efficient data-driven policy evaluation and monitoring, assess the causal effects of policy measures and report on best practices of successful data management and usage. Topics include data confidentiality, data linkage, and national practices in policy areas such as public health, education and employment. It offers scholars as well as practitioners from public administrations, consultancy firms and nongovernmental organizations insights into counterfactual impact evaluation methods and the potential of data-based policy and program evaluation.
Data science, AI, and machine learning in drug development
The confluence of big data, AI, and machine learning has led to a paradigm shift in how innovative medicines are developed and healthcare delivered. To fully capitalize on these technological advances, it is essential to systematically harness data from diverse sources and leverage digital technologies and advanced analytics to enable data-driven decisions. Data science stands at a unique moment of opportunity to lead such a transformative change. Intended to be a single source of information, Data Science, AI, and Machine Learning in Drug Research and Development covers a wide range of topics on the changing landscape of drug R&D, emerging applications of big data, AI and machine learning in drug development, and the build of robust data science organizations to drive biopharmaceutical digital transformations
Data science in theory and practice : Techniques for big data analytics and complex data sets
Delivers a comprehensive treatment of the mathematical and statistical models useful for analyzing data sets arising in various disciplines, like banking, finance, health care, bioinformatics, security, education, and social services. Written in five parts, the book examines some of the most commonly used and fundamental mathematical and statistical concepts that form the basis of data science. The authors go on to analyze various data transformation techniques useful for extracting information from raw data, long memory behavior, and predictive modeling. Readers will also learn from topics like: Analyses of foundational theoretical subjects, including the history of data science, matrix algebra and random vectors, and multivariate analysis A comprehensive examination of time series forecasting, including the different components of time series and transformations to achieve stationarity Introductions to both the R and Python programming languages, including basic data types and sample manipulations for both languages An exploration of algorithms, including how to write one and how to perform an asymptotic analysis A comprehensive discussion of several techniques for analyzing and predicting complex data sets
Data science and data analytics : Opportunities and challenges
Gives the concept of data science, tools, and algorithms that exist for many useful applications / Provides many challenges and opportunities in data science and data analytics that help researchers to identify research gaps or problems / Identifies many areas and uses of data science in the smart era / Applies data science to agriculture, healthcare, graph mining, education, security, etc.
Data Integration in the Life Sciences ; 5th International Workshop, DILS 2008, Evry, France, June 25-27, 2008. Proceedings
This book constitutes the refereed proceedings of the 5th International Workshop on Data Integration in the Life Sciences, DILS 2008, held in Evry, France in June 2008.
Data Driven Methods for Civil Structural Health Monitoring and Resilience : Latest Developments and Applications
Provides a comprehensive overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This allows existing structures to be turned into smart structures, thereby allowing them to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis. Artificial-intelligence-based methodologies are becoming increasingly more attractive for civil engineering and SHM applications
Data and Text Processing for Health and Life Sciences
This book is a step-by-step introduction on how shell scripting can help solve many of the data processing tasks that Health and Life specialists face everyday with minimal software dependencies. The examples presented in the book show how simple command line tools can be used and combined to retrieve data and text from web resources, to filter and mine literature, and to explore the semantics encoded in biomedical ontologies. To store data this book relies on open standard text file formats, such as TSV, CSV, XML, and OWL, that can be open by any text editor or spreadsheet application.
Dail and Hammars Pulmonary Pathology : Vol. I: Nonneoplastic Lung Disease
Dail and Hammar’s Pulmonary Pathology has established itself as the definitive reference in the field. This authoritative reference work has been thoroughly updated to cover newly recognized entities and the latest advances in molecular diagnostic techniques.
Cybersecurity of Digital Service Chains : Challenges, Methodologies, and Tools
This book presents the main scientific results from the H2020 GUARD project. The GUARD project aims at filling the current technological gap between software management paradigms and cybersecurity models, the latter still lacking orchestration and agility to effectively address the dynamicity of the former. This book provides a comprehensive review of the main concepts, architectures, algorithms, and non-technical aspects developed during three years of investigation; the description of the Smart Mobility use case developed at the end of the project gives a practical example of how the GUARD platform and related technologies can be deployed in practical scenarios.
Cyber-physical systems : Foundations and techniques
Covers the various aspects associated with Cyber-Physical Systems (CPS) such as algorithms, application areas, and the improvement of existing technology such as machine learning, big data and robotics. The scope of CPS is tremendous. In CPS, one sees the applications of various emerging technologies such as artificial intelligence (AI), Internet of Things (IoT), machine learning (ML), deep learning (DL), big data (BD), robotics, quantum technology, etc. In almost all sectors, whether it is education, health, human resource development, skill improvement, startup strategy, etc., one sees an enhancement in the quality of output because of the emergence of CPS into the field.
Cyber Security : Critical Infrastructure Protection
Focus on critical infrastructure protection. The chapters present detailed analysis of the issues and challenges in cyberspace and provide novel solutions in various aspects. The first part of the book focus on digital society, addressing critical infrastructure and different forms of the digitalization, strategic focus on cyber security, legal aspects on cyber security, citizen in digital society, and cyber security training. The second part focus on the critical infrastructure protection in different areas of the critical infrastructure. The chapters cover the cybersecurity situation awareness, aviation and air traffic control, cyber security in smart societies and cities, cyber security in smart buildings, maritime cyber security, cyber security in energy systems, and cyber security in healthcare. The third part presents the impact of new technologies upon cyber capability building as well as new challenges brought about by new technologies. These new technologies are among others are quantum technology, firmware and wireless technologies, malware analysis, virtualization.
Cyanobacterial Harmful Algal Blooms : State of the Science and Research Needs
Humans can be exposed to cyanobacterial toxins by drinking water that contains the toxins, swimming in water that contains high concentrations of cyanobacterial cells, or breathing air that contains cyanobacterial cells or toxins (while watering a lawn with contaminated water, for example). Health effects associated with exposure to high concentrations of cyanobacterial toxins include: - stomach and intestinal illness; -trouble breathing; - allergic responses; - skin irritation; - liver damage; and neurotoxic reactions, such as tingling fingers and toes. Scientists are exploring the human health effects associated with long-term exposure to low levels of cyanobacterial toxins. Some studies have suggested that such exposure could be associated with chronic illnesses, such as liver cancer and digestive-system cancer. This monograph contains the proceedings of the International Symposium on Cyanobacterial Harmful Algal Blooms held in Research Triangle Park, NC, September 6-10, 2005.
