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Complex Networks
Though the reductionist approachto biology and medicine has led to several imp- tant advances, further progresses with respect to the remaining challenges require integration of representation, characterization and modeling of the studied systems along a wide range of spatial and time scales. Such an approach, intrinsically - lated to systems biology, is poised to ultimately turning biology into a more precise and synthetic discipline, paving the way to extensive preventive and regenerative medicine [1], drug discovery [20] and treatment optimization [24]. A particularly appealing and effective approach to addressing the complexity of interactions inherent to the biological systems is provided by the new area of c- plex networks [34, 30, 8, 13, 12]. Basically, it is an extension of graph theory [10], focusing on the modeling, representation, characterization, analysis and simulation ofcomplexsystemsbyconsideringmanyelementsandtheirinterconnections.C- plex networks concepts and methods have been used to study disease [17], tr- scription networks [5, 6, 4], protein-protein networks [22, 36, 16, 39], metabolic networks [23] and anatomy [40].
A First Course in Network Science
A practical introduction to network science for students across business, cognitive science, neuroscience, sociology, biology, engineering and other disciplines.
Complex Networks
This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on Complex Networks, CompleNet 2010, which was held in Rio de Janeiro, Brazil, in October 2010. The 21 revised papers presented were carefully reviewed and selected from 48 submissions. The topics covered include: community structure, network metrics, network models, effect of topology to epidemics, algorithms to classify networks, self-organized algorithms applied to complex networks, as well as many applications of complex networks in biology, image analysis, software development, traffic congestion, language and speech, sensor networks, and synchronization.
Models of Science Dynamics
Models of Science Dynamics aims to capture the structure and evolution of science, the emerging arena in which scholars, science and the communication of science become themselves the basic objects of research. In order to capture the essence of phenomena as diverse as the structure of co-authorship networks or the evolution of citation diffusion patterns, such models can be represented by conceptual models based on historical and ethnographic observations, mathematical descriptions of measurable phenomena, or computational algorithms. Despite its evident importance, the mathematical modeling of science still lacks a unifying framework and a comprehensive study of the topic. This volume fill...
Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing
The purpose of the 10th ACIS International Conference on Software Engineering Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD rd 2009), held in Daegu, Korea on May 27–29, 2009, the 3 International Workshop st on e-Activity (IWEA 2009) and the 1 International Workshop on Enterprise Architecture Challenges and Responses (WEACR 2009) is to aim at bringing together researchers and scientist, businessmen and entrepreneurs, teachers and students to discuss the numerous fields of computer science, and to share ideas and information in a meaningful way. Our conference officers selected the best 24 papers from those papers accepted for presentation at the conference in ...
Recent Trends in Analysis of Images, Social Networks and Texts
This book constitutes revised selected papers of the 9th International Conference on Analysis of Images, Social Networks and Texts, AIST 2020, held in Moscow, Russia, in october 2020. Due to the COVID-19 pandemic the conference was held online. The 14 full papers, 9 short papers and 4 poster papers were carefully reviewed and selected from 108 qualified submissions. The papers are organized in topical sections on natural language processing; computer vision; social network analysis; data analysis and machine learning; theoretical machine learning and optimization; process mining; posters.
Legal Knowledge and Information Systems
As with almost every other part of our daily lives, information technology is now indispensable in the legal sphere. The variety of applications has grown, keeping pace with developments in the wider field of artificial intelligence: logic and argument have been joined by statistical methods and data, and knowledge engineering has been enriched by machine learning. This book presents the papers delivered at the 29th International Conference on Legal Knowledge and Information Systems – JURIX 2016, held in Nice, France, in December 2016. From the 56 submissions received for the conference, 11 were selected for publication as full papers, 10 as short papers, and 10 as posters, which are inclu...
Obstetric Violence and Systemic Disparities
The final volume in this landmark 3-volume series The Anthropology of Obstetrics and Obstetricians: The Practice, Maintenance, and Reproduction of a Biomedical Profession looks at the challenges, and even violence, that obstetricians face across the world. Part I of this volume addresses obstetric violence and systemic racial, ethnic, gendered, and socio-structural disparities in obstetricians’ practices in the Dominican Republic, Mexico, Peru, and the US. Part II addresses decolonizing and humanizing obstetric training and practice in the UK, Russia, Brazil, New Zealand, and the US. Part 3 presents the ethnographic challenges that the chapter authors in Volumes II and III of this series f...
Large-scale Graph Analysis: System, Algorithm and Optimization
This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently. More concretely, it proposes a workload-aware cost model to guide the development of high-performance algorithms. On the basis of the cost model, the book subsequently presents a system-level optimization resulting in a partition-aware graph-computing engine, PAGE. In addition, it presents three efficient and scalable advanced graph algorithms – the subgraph enumeration, cohesive subgraph detection, and graph extraction algorithms. This book offers a valuable reference guide for junior researchers, covering the latest advances in large-scale graph analysis; and for senior researchers, sharing state-of-the-art solutions based on advanced graph algorithms. In addition, all readers will find a workload-aware methodology for designing efficient large-scale graph algorithms.
Experiments in Cultural Language Evolution
Explores the cultural side of language evolution. This book proposes a framework based on linguistic selection and self-organization. It investigates how particular types of language systems can emerge in the population of language game playing agents and how they can continue to evolve in order to cope with changes in ecological conditions.
