The world of Heven was populated, centuries ago, by Melanesian settlers from distant Earth. It is a peaceful, quiet world – yet it harbours ancient secrets. Kal just wants to fly. But flying is the one thing forbidden on Heven – a world dominated by the mysterious, ever present clouds in the skies. What do they hide? For Kal, finding the answer might mean his death – but how far will you go to realise your dreams? Set against the breathtaking vista of a world filled with mystery and magic, Cloud Permutations is a planetary romance with a unique South Pacific flavour, filled with mythic monsters, ancient alien artefacts, floating islands and a quest to find a legendary tower. . . whatever the cost. REVIEWS: “A meditation on the making and meaning of cultural myths” – World Literature Today “Wonderful novella. . . his writing is as powerful and lovingly handled as any old master” – Tangent “Wonderful and touching” – Rising Shadow Review “An impressive science fiction tale. . . It is Tidhar’s refreshing telling that makes it special.” – Locus

“Tidhar changes genres with every outing, but his astounding talents guarantee something new and compelling no matter the story he tells.” – Library Journal A nun enters a poker tournament as she wrestles with her faith in God; a boy travels across a mysterious, cloud-covered planet in search of a mythical space port; in Nazi-occupied London a screenwriter searches for an old flame with deadly consequences; three wise men from the East travel to Judea to give a newborn baby an unexpected power. Collected for the first time in one volume, this omnibus edition from World Fantasy Award winner Lavie Tidhar gathers four mind-bending novellas: The Big Blind, Cloud Permutations, The Vanishing Kind, and Jesus and the Eightfold Path. “Lavie Tidhar is one of the great writers of my generation.” – Silvia Moreno-Garcia, author of Mexican Gothic

This two-volume set constitutes the refereed proceedings of the workshops which complemented the 19th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in Würzburg, Germany, in September 2019. The 70 full papers and 46 short papers presented in the two-volume set were carefully reviewed and selected from 200 submissions. The two volumes (CCIS 1167 and CCIS 1168) present the papers that have been accepted for the following workshops: Workshop on Automating Data Science, ADS 2019; Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence and eXplainable Knowledge Discovery in Data Mining, AIMLAI-XKDD 2019; Workshop on Decentralized Machine Learning at the Edge, DMLE 2019; Workshop on Advances in Managing and Mining Large Evolving Graphs, LEG 2019; Workshop on Data and Machine Learning Advances with Multiple Views; Workshop on New Trends in Representation Learning with Knowledge Graphs; Workshop on Data Science for Social Good, SoGood 2019; Workshop on Knowledge Discovery and User Modelling for Smart Cities, UMCIT 2019; Workshop on Data Integration and Applications Workshop, DINA 2019; Workshop on Machine Learning for Cybersecurity, MLCS 2019; Workshop on Sports Analytics: Machine Learning and Data Mining for Sports Analytics, MLSA 2019; Workshop on Categorising Different Types of Online Harassment Languages in Social Media; Workshop on IoT Stream for Data Driven Predictive Maintenance, IoTStream 2019; Workshop on Machine Learning and Music, MML 2019; Workshop on Large-Scale Biomedical Semantic Indexing and Question Answering, BioASQ 2019. The chapter "Supervised Human-guided Data Exploration" is published open access under a Creative Commons Attribution 4.0 International license (CC BY).

We are living at the dawn of what has been termed ‘the fourth paradigm of science,’ a scientific revolution that is marked by both the emergence of big data science and analytics, and by the increasing adoption of the underlying technologies in scientific and scholarly research practices. Everything about science development or knowledge production is fundamentally changing thanks to the ever-increasing deluge of data. This is the primary fuel of the new age, which powerful computational processes or analytics algorithms are using to generate valuable knowledge for enhanced decision-making, and deep insights pertaining to a wide variety of practical uses and applications. This book addresses the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the systemic implications for smart sustainable urbanism. In concrete terms, it explores the interdisciplinary and transdisciplinary field of smart sustainable urbanism and the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics. This new era of science and technology embodies an unprecedentedly transformative and constitutive power—manifested not only in the form of revolutionizing science and transforming knowledge, but also in advancing social practices, producing new discourses, catalyzing major shifts, and fostering societal transitions. Of particular relevance, it is instigating a massive change in the way both smart cities and sustainable cities are studied and understood, and in how they are planned, designed, operated, managed, and governed in the face of urbanization. This relates to what has been dubbed data-driven smart sustainable urbanism, an emerging approach based on a computational understanding of city systems and processes that reduces urban life to logical and algorithmic rules and procedures, while also harnessing urban big data to provide a more holistic and integrated view or synoptic intelligence of the city. This is increasingly being directed towards improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. This timely and multifaceted book is aimed at a broad readership. As such, it will appeal to urban scientists, data scientists, urbanists, planners, engineers, designers, policymakers, philosophers of science, and futurists, as well as all readers interested in an overview of the pivotal role of big data science and analytics in advancing every academic discipline and social practice concerned with data–intensive science and its application, particularly in relation to sustainability.

The two volume set LNCS 3102/3103 constitutes the refereed proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2004, held in Seattle, WA, USA, in June 2004. The 230 revised full papers and 104 poster papers presented were carefully reviewed and selected from 460 submissions. The papers are organized in topical sections on artificial life, adaptive behavior, agents, and ant colony optimization; artificial immune systems, biological applications; coevolution; evolutionary robotics; evolution strategies and evolutionary programming; evolvable hardware; genetic algorithms; genetic programming; learning classifier systems; real world applications; and search-based software engineering.

Geometric Data Analysis designates the approach of Multivariate Statistics that conceptualizes the set of observations as a Euclidean cloud of points. Combinatorial Inference in Geometric Data Analysis gives an overview of multidimensional statistical inference methods applicable to clouds of points that make no assumption on the process of generating data or distributions, and that are not based on random modelling but on permutation procedures recasting in a combinatorial framework. It focuses particularly on the comparison of a group of observations to a reference population (combinatorial test) or to a reference value of a location parameter (geometric test), and on problems of homogeneity, that is the comparison of several groups for two basic designs. These methods involve the use of combinatorial procedures to build a reference set in which we place the data. The chosen test statistics lead to original extensions, such as the geometric interpretation of the observed level, and the construction of a compatibility region. Features: Defines precisely the object under study in the context of multidimensional procedures, that is clouds of points Presents combinatorial tests and related computations with R and Coheris SPAD software Includes four original case studies to illustrate application of the tests Includes necessary mathematical background to ensure it is self–contained This book is suitable for researchers and students of multivariate statistics, as well as applied researchers of various scientific disciplines. It could be used for a specialized course taught at either master or PhD level.

Strahan's fifth anthology contains 29 wide-ranging tales. Neil Gaiman's "The Truth Is a Cave in the Black Mountains" is a deceptively simple folktale-styled story of the price one may pay for gold. "The Sultan of the Clouds" by Geoffrey Landis untangles a complex knot of childish power. Sarah Rees Brennan's "The Spy Who Never Grew Up" gives a beloved childhood icon a sinister update; Diana Peterfreund's "The Care and Feeding of Your Baby Killer Unicorn" turns unicorn lore on its head; and Rachel Swirsky's "The Lady Who Plucked Red Flowers Beneath the Queen's Window" puts a fantasy spin on the temporal culture shock of immortality. This year the fantasy tales outdo the SF in depth of storytelling and characterization, though all the inclusions are strong, with few ideas left by the wayside.