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A Changing World : Challenges for Landscape Research
Written primarily for researchers and advanced students in environmental and social sciences, this latest book in Springer’s Landscape Series looks at some of the emerging fields and new challenges in landscape research. These include: the role of value systems in perceiving, appreciating, and managing landscapes the ‘space’ and ‘place’ concept in landscape research GIS and remote sensing techniques for gathering and processing spatially and temporally explicit land cover, vegetation, and land use data methods of landscape history landscape genetics and genetic methods to test landscape connectivity and dispersal of plant and animal species
25 Years of P53 Research
Communication, awareness and access to information: Given the complexity of the field and the fact that data pertaining to each particular aspects of p53 biology or deregulation are scattered in many different publications, it is extremely difficult to access the full scale of relevant information of any specific p53-related topic. This book may help in this task by putting into perspective both general considerations on the p53 pathway and more specific information on various aspects of p53. In the longer term, however, open access to p53 complexity will require the development of knowledge bases accessible through the web and using simple navigation tools to guide users towards the specific information they need. Several efforts are currently being developed in that direction. They need to be strenghtened and better integrated within the rapidly growing galaxy of web-based information sources on molecular and individual variations in cancer. 2. Reference functional assays and structural analysis: Given the huge diversity of cellular and animal models for wild-type or mutant p53 functions, it will be important to set up standard, universally accepted assays to measure critical p53 protein functions.
Liberal Democracy : Prosperity through Freedom
Aims to show which factors have been decisive in the rise of successful countries. Never before have so many people been so well off. However, prosperity is not a law of nature; it has to be worked for. A liberal economy stands at the forefront of this success – not as a political system, but as a set of economic rules promoting competition, which in turn leads to innovation, research and enormous productivity.
Law, Humanities and the COVID Crisis
Seeks to address the immediacy of COVID-19 by focusing on the implications of the virus in a wider interdisciplinary context Law, Humanities and the COVID Crisis</i> sets out a framework for understanding the COVID-19 virus beyond its epidemiological constraints, asking us to question the very definition of what it means to be human. Researchers from around the world offer their critical reflections on the past, present, and future of this period of sociocultural upheaval and the tremendous suffering that has laid bare fundamental imbalances in our society.
Law and Justice in a globalized world
Consists of a selection of papers presented at the Asia-Pacific Research Conference on Social Sciences and Humanities. It contains essays on current legal issues in law and justice, and their role and transformation in a globalizing world. Topics covered include human rights, criminal law, law of the sea, good governance, democracy, foreign investment, and regional integration. The conference focused on Asia and the Pacific, two regions where law has taken an important position in creating and shaping the regional integrations, new legal institutions, and norms.
Common Law, Civil Law, and Colonial Law : Essays in Comparative Legal History from the Twelfth to the Twentieth Centuries
This volume is a selection of essays taken from the excellent range of papers presented at the British Legal History Conference hosted by the Institute for Legal and Constitutional Research at the University of St Andrews, 10-13 July 2019. The theme of the conference gives this book its title: 'comparative legal history'. The topic came easily to the organisers because of their association with the St Andrews-based European Research Council Advanced grant project 'Civil law, common law, customary law: consonance, divergence and transformation in Western Europe from the late eleventh to the thirteenth centuries'.
Asylum Determination in Europe : Ethnographic Perspectives
The book includes a legal overview of European asylum determination procedures, followed by sections on the diverse actors involved, the means by which they communicate, and the ways in which they make life and death decisions on a daily basis. It offers a contextually rich account that moves beyond doctrinal law to uncover the gaps and variances between formal policy and legislation, and law as actually practiced.
An assessment framework for compliance with international space law and norms : Promoting equitable access and Use of space for emerging actors
proposes a framework for assessing countries’ levels of compliance with international space law and norms. It begins by exploring the development of two movements – the evidence-based policymaking and programming movement, and the rise of ratings and rankings research – and their growth across various disciplines. The analysis suggests that such efforts are useful in gauging the behavior of countries in space according to how well they adhere to existing space law and norms. To date, there is no comprehensive, periodic, and systematic measure of countries’ efforts to comply with space law and norms; this work endeavors to fill that gap by offering a framework in which to assess compliance.
Many-Core Computing : Hardware and software
Provides a timely and coherent account of the recent advances in many-core computing research. Starting with programming models, operating systems and their applications; it presents runtime management techniques, followed by system modelling, verification and testing methods, and architectures and systems. Computing has moved away from a focus on performance-centric serial computation, instead towards energy-efficient parallel computation. This provides continued performance increases without increasing clock frequencies, and overcomes the thermal and power limitations of the dark-silicon era. As the number of parallel cores increases, we transition into the many-core computing era. There is considerable interest in developing methods, tools, architectures and applications to support many-core computing.
Managing Cyber Threats : Issues, Approaches, and Challenges
Brings together the latest techniques for managing cyber threats, developed by some of the world’s leading experts in the area. The book includes broad surveys on a number of topics, as well as specific techniques. It provides an excellent reference point for researchers and practitioners in the government, academic, and industrial communities who want to understand the issues and challenges in this area of growing worldwide importance.
Managed Software Evolution
This open access book presents the outcomes of the “Design for Future – Managed Software Evolution” .The different lifecycles of software and hardware platforms lead to interoperability problems in such systems. Instead of separating the development, adaptation and evolution of software and its platforms, as well as aspects like operation, monitoring and maintenance, they should all be integrated into one overarching process. Accordingly, the book is split into three major parts, the first of which includes an introduction to the nature of software evolution, followed by an overview of the specific challenges and a general introduction to the case studies used in the project. The second part of the book consists of the main chapters on knowledge carrying software, and cover tacit knowledge in software evolution, continuous design decision support, model-based round-trip engineering for software product lines, performance analysis strategies, maintaining security in software evolution, learning from evolution for evolution, and formal verification of evolutionary changes. In turn, the last part of the book presents key findings and spin-offs. The individual chapters there describe various case studies, along with their benefits, deliverables and the respective lessons learned. An overview of future research topics rounds out the coverage.
Malware Detection
Malware Detection, based on the Special ARO/DHS Workshop on Malware Detection at Rosslyn, VA, in 2005, captures the state of the art research in the area of malicious code detection, prevention and mitigation.
Machine Learning Refined : Foundations, Algorithms, and Applications
Provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology.
Machine learning approach for cloud data analytics in IoT
Covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications. Elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.
Machine Learning and Robot Perception
Presents some of the most recent research results in the area of machine learning and robot perception. The chapters represent new ways of solving real-world problems. This book will appeal to researchers, senior undergraduate/postgraduate students, application engineers and scientists.
Machine Learning and Probabilistic Graphical Models for Decision Support Systems
Presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter.
Machine learning and deep learning in medical data analytics and healthcare applications
Introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments.
Machine Learning and Data Mining for Computer Security : Methods and Applications
Presents research conducted in academia and industry on methods and applications of machine learning and data mining for problems in computer security and will be of interest to researchers and practitioners, as well students.
Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks
Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.
Machine Learning and Big Data Analytics Paradigms : Analysis, Applications and Challenges
Intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.
