This book should be useful to anyone interested in identifying the causes of civil conflict and doing something to end it. It even suggests a pathway for the lay reader. Civil conflict is a persistent source of misery to humankind. Its study, however, lacks a comprehensive theory of its causes. Nevertheless, the question of cooperation or conflict is at the heart of political economy. This book introduces Machine Learning to explore whether there even is a unified theory of conflict, and if there is, whether it is a ‘good’ one. A good theory is one that not only identifies the causes of conflict, but also identifies those causes that predict conflict. Machine learning algorithms use out of sample techniques to choose between competing hypotheses about the sources of conflict according to their predictive accuracy. This theoretically agnostic ‘picking’ has the added benefit of offering some protection against many of the problems noted in the current literature; the tangled causality between conflict and its correlates, the relative rarity of civil conflict at a global level, missing data, and spectacular statistical assumptions. This book argues that the search for a unified theory of conflict must begin among these more predictive sources of civil conflict. In fact, in the book, there is a clear sense that game theoretic rational choice models of bargaining/commitment failure predict conflict better than any other approach. In addition, the algorithms highlight the fact that conflict is path dependent - it tends to continue once started. This is intuitive in many ways but is roundly ignored as a matter of science. It should not. Further, those causes of conflict that best predict conflict can be used as policy levers to end or prevent conflict. This book should therefore be of interest to military and civil leaders engaged in ending civil conflict. Last, though not least, the book highlights how the sources of conflict affect conflict. This additional insight may allow the crafting of policies that match a country’s specific circumstance.

Predicting our future as individuals is central to the role of much emerging technology, from hiring algorithms that predict our professional success (or failure) to biomarkers that predict how long (or short) our healthy (or unhealthy) life will be. Yet, much in Western culture, from scripture to mythology to philosophy, suggests that knowing one’s future may not be in the subject’s best interests and might even lead to disaster. If predicting our future as individuals can be harmful as well as beneficial, why are we so willing to engage in so much prediction, from cradle to grave? This book offers a philosophical answer, reflecting on seminal texts in Western culture to argue that predicting our future renders much of our existence the automated effect of various causes, which, in turn, helps to alleviate the existential burden of autonomously making sense of our lives in a more competitive, demanding, accelerated society. An exploration of our tendency in a technological era to engineer and so rid ourselves of that which has hitherto been our primary reason for being – making life plans for a successful future, while faced with epistemological and ethical uncertainties – Predicted Humans will appeal to scholars of philosophy and social theory with interests in questions of moral responsibility and meaning in an increasingly technological world.

This two-volume set LNCS 9225 and LNCS 9226 constitutes - in conjunction with the volume LNAI 9227 - the refereed proceedings of the 11th International Conference on Intelligent Computing, ICIC 2015, held in Fuzhou, China, in August 2015. The total of 191 full and 42 short papers presented in the three ICIC 2015 volumes was carefully reviewed and selected from 671 submissions. The papers are organized in topical sections such as evolutionary computation and learning; compressed sensing, sparse coding and social computing; neural networks, nature inspired computing and optimization; pattern recognition and signal processing; image processing; biomedical informatics theory and methods; differential evolution, particle swarm optimization and niche technology; intelligent computing and knowledge discovery and data mining; soft computing and machine learning; computational biology, protein structure and function prediction; genetic algorithms; artificial bee colony algorithms; swarm intelligence and optimization; social computing; information security; virtual reality and human-computer interaction; healthcare informatics theory and methods; unsupervised learning; collective intelligence; intelligent computing in robotics; intelligent computing in communication networks; intelligent control and automation; intelligent data analysis and prediction; gene expression array analysis; gene regulation modeling and analysis; protein-protein interaction prediction; biology inspired computing and optimization; analysis and visualization of large biological data sets; motif detection; biomarker discovery; modeling; simulation; and optimization of biological systems; biomedical data modeling and mining; intelligent computing in biomedical signal/image analysis; intelligent computing in brain imaging; neuroinformatics; cheminformatics; intelligent computing in computational biology; computational genomics; special session on biomedical data integration and mining in the era of big data; special session on big data analytics; special session on artificial intelligence for ambient assisted living; and special session on swarm intelligence with discrete dynamics.

With the growth in our reliance on information systems and computer science, information modeling and knowledge bases have become a focus for academic attention and research. The amount and complexity of information, the number of levels of abstraction and the size of databases and knowledge bases all continue to increase, and new challenges and problems arise every day. This book is part of the series Information Modelling and Knowledge Bases, which concentrates on a variety of themes such as the design and specification of information systems, software engineering and knowledge and process management. Attention is also paid to theoretical disciplines including cognitive science, artificial intelligence, logic, linguistics and analytical philosophy. Selected papers cover many areas of information modeling and knowledge bases, namely theory of concepts, database semantics, knowledge representation, software engineering, WWW information management, context-based information retrieval, ontological technology, image databases, temporal and spatial databases, document data management, process management, cultural modeling, social networks, personalization, interfaces, data mining and many others. The book will be of interest to all those involved in research and application in these academic areas.

This two-volume set of LNCS 11643 and LNCS 11644 constitutes - in conjunction with the volume LNAI 11645 - the refereed proceedings of the 15th International Conference on Intelligent Computing, ICIC 2019, held in Nanchang, China, in August 2019. The 217 full papers of the three proceedings volumes were carefully reviewed and selected from 609 submissions. The ICIC theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. The theme for this conference is “Advanced Intelligent Computing Methodologies and Applications.” Papers related to this theme are especially solicited, including theories, methodologies, and applications in science and technology.

Algorithms—Advances in Research and Application: 2012 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Algorithms. The editors have built Algorithms—Advances in Research and Application: 2012 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Algorithms in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Algorithms—Advances in Research and Application: 2012 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

This book constitutes the refereed proceedings of the 33rd International Conference on Databases Theory and Applications, ADC 2022, held in Sydney, Australia, in September 2022. The conference is co-located with the 48th International Conference on Very Large Data Bases, VLDB 2022. The 9 full papers presented together with 8 short papers were carefully reviewed and selected from 36 submissions. ADC focuses on database systems, data-driven applications, and data analytics.

VLSI 2010 Annual Symposium will present extended versions of the best papers presented in ISVLSI 2010 conference. The areas covered by the papers will include among others: Emerging Trends in VLSI, Nanoelectronics, Molecular, Biological and Quantum Computing. MEMS, VLSI Circuits and Systems, Field-programmable and Reconfigurable Systems, System Level Design, System-on-a-Chip Design, Application-Specific Low Power, VLSI System Design, System Issues in Complexity, Low Power, Heat Dissipation, Power Awareness in VLSI Design, Test and Verification, Mixed-Signal Design and Analysis, Electrical/Packaging Co-Design, Physical Design, Intellectual property creating and sharing.

This book is indexed in Chemical Abstracts ServiceThe interactions of proteins with other molecules are important in many cellular activities. Investigations have been carried out to understand the recognition mechanism, identify the binding sites, analyze the the binding affinity of complexes, and study the influence of mutations on diseases. Protein interactions are also crucial in structure-based drug design.This book covers computational analysis of protein-protein, protein-nucleic acid and protein-ligand interactions and their applications. It provides up-to-date information and the latest developments from experts in the field, using illustrations to explain the key concepts and applications. This volume can serve as a single source on comparative studies of proteins interacting with proteins/DNAs/RNAs/carbohydrates and small molecules.