Discover how healthy buildings, culture, and people lead to high profits
Organizations and employees now spend an average of $18,000 per year per employee for health costs, a 61% increase in 10 years. Every indicator projects these costs will double before 2030. This is an unsustainable path. These costs are the tip to an even bigger iceberg, the hidden costs of time out of the office, distraction, disengagement, and turnover. The Healthy Workplace Nudge explains the findings of research on 100 large organizations that have tackled the problems of employee health costs and disengagement in five fresh ways:
In addition to proving highly effective, these approaches represent a fraction of the cost sunk into traditional wellness and engagement programs. The book explains how to create a workplace that is good for people, releases them to what they do best and enjoy most, and produces great and profitable work.
• Find actionable strategies and tactics you can put into use today
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Published in 1997, This book offers an up-to-date guide to the Green parties of Western Europe as the optimism of the 1980s confronts the 'Green fatigue' of the 1990s. The approach is both thematic and comparative. Green politics in Europe is located in its historical and cultural context. There is a comparative analysis of the principal ideological questions, policy issues and strategic dilemmas that have confronted the European Greens. There are national profiles of Green politics throughout the European Union. The conclusion addresses the critical issue of political change in post industrial societies. It discusses the contribution of Green parties to the 'New Politics' and assesses their likely impact on post-modern politics
This handbook offers a comprehensive treatise on Grammatical Evolution (GE), a grammar-based Evolutionary Algorithm that employs a function to map binary strings into higher-level structures such as programs. GE's simplicity and modular nature make it a very flexible tool. Since its introduction almost twenty years ago, researchers have applied it to a vast range of problem domains, including financial modelling, parallel programming and genetics. Similarly, much work has been conducted to exploit and understand the nature of its mapping scheme, triggering additional research on everything from different grammars to alternative mappers to initialization.
The book first introduces GE to the novice, providing a thorough description of GE along with historical key advances. Two sections follow, each composed of chapters from international leading researchers in the field. The first section concentrates on analysis of GE and its operation, giving valuable insight into set up and deployment. The second section consists of seven chapters describing radically different applications of GE.
The contributions in this volume are beneficial to both novices and experts alike, as they detail the results and researcher experiences of applying GE to large scale and difficult problems.
- Grammar design
- Mapping in GE
- Theory of disruption in GE
- Structured GE
- GE and semantics
- Multi- and Many-core heterogeneous parallel GE
- Comparing methods to creating constants in GE
- Financial modelling with GE
- Synthesis of parallel programs on multi-cores
- Design, architecture and engineering with GE
- Computational creativity and GE
- GE in the prediction of glucose for diabetes
- GE approaches to bioinformatics and system genomics
- GE with coevolutionary algorithms in cybersecurity
- Business analytics and GE for the prediction of patient recruitment in multicentre clinical trials
This book constitutes the refereed proceedings of the 7th International Conference on Theory and Practice of Natural Computing, TPNC 2017, held in Dublin, Ireland, in December 2018. The 35 full papers presented in this book, together with one invited talk, were carefully reviewed and selected from 69 submissions. The papers are organized around the following topical sections: applications of natural computing as algorithms, bioinformatics, control, cryptography, design, economics. The more theoretical contributions handle with artificial chemistry, artificial immune systems, artificial life, cellular automata, cognitive computing, cognitive engineering, cognitive robotics, collective behaviour, complex systems, computational intelligence, computational social science, computing with words, developmental systems, DNA computing, DNA nanotechnology, evolutionary algorithms, evolutionary computing, evolutionary game theory, fractal geometry, fuzzy control, fuzzy logic, fuzzy sets, fuzzy systems, genetic algorithms, genetic programming, granular computing, heuristics, intelligent agents, intelligent systems, machine intelligence, molecular programming, neural computing, neural networks, quantum communication, quantum computing, rough sets, self-assembly.
Michael O'Neill's Return of the Gift is a volume about what is given and what is lost. Writing unsentimentally and with insight about powerful subjects such as the death of his mother, caring for his father, and his own recent diagnosis of cancer, the poet speaks of and to his personal and historical life and also explores themes of elegy and friendship. Memories are woven vividly throughout a thematically varied yet coherent collection, in which a witty and moving pleasure in living and language is always to the fore.
Seriously clichEd millionaire playboy Major Connor MacLeod, is nonetheless no ordinary forty year old millionaire playboy. A highly decorated army officer, a world and Olympic champion sportsman, a scholar with degrees in science, engineering, and history, he has lived his twenty years of public life at full throttle. Frenemies typically describe him as arrogant, reckless, irresponsible and positively suicidal, but he has proven, to date, to be the proverbial unstoppable force.
But all good things must come to an end.
Conn has "inherited" a method of passing from this time and dimension to another; one that he believes to be a lot like, but is most definitely not, 9th Century Europe. When he steps from this world to another, will he have finally bitten off more than he can chew?
Natural Computing in Computational Finance is a innovative volume containing fifteen chapters which illustrate cutting-edge applications of natural computing or agent-based modeling in modern computational finance. Following an introductory chapter the book is organized into three sections. The first section deals with optimization applications of natural computing demonstrating the application of a broad range of algorithms including, genetic algorithms, differential evolution, evolution strategies, quantum-inspired evolutionary algorithms and bacterial foraging algorithms to multiple financial applications including portfolio optimization, fund allocation and asset pricing. The second section explores the use of natural computing methodologies such as genetic programming, neural network hybrids and fuzzy-evolutionary hybrids for model induction in order to construct market trading, credit scoring and market prediction systems. The final section illustrates a range of agent-based applications including the modeling of payment card and financial markets. Each chapter provides an introduction to the relevant natural computing methodology as well as providing a clear description of the financial application addressed.
The book was written to be accessible to a wide audience and should be of interest to practitioners, academics and students, in the fields of both natural computing and finance.
Recent years have seen the widespread application of Natural Computing algorithms (broadly defined in this context as computer algorithms whose design draws inspiration from phenomena in the natural world) for the purposes of financial modelling and optimisation. A related stream of work has also seen the application of learning mechanisms drawn from Natural Computing algorithms for the purposes of agent-based modelling in finance and economics. In this book we have collected a series of chapters which illustrate these two faces of Natural Computing. The first part of the book illustrates how algorithms inspired by the natural world can be used as problem solvers to uncover and optimise financial models. The second part of the book examines a number agent-based simulations of financial systems.
This book follows on from Natural Computing in Computational Finance (Volume 100 in Springer's Studies in Computational Intelligence series) which in turn arose from the success of EvoFIN 2007, the very first European Workshop on Evolutionary Computation in Finance & Economics held in Valencia, Spain in April 2007.
Dynamic environments abound, encompassing many real-world problems in fields as diverse as finance, engineering, biology and business. A vibrant research literature has emerged which takes inspiration from evolutionary processes to develop problem-solvers for these environments.
'Foundations in Grammatical Evolution for Dynamic Environments' is a cutting edge volume illustrating current state of the art in applying grammar-based evolutionary computation to solve real-world problems in dynamic environments. The book provides a clear introduction to dynamic environments and the types of change that can occur. This is followed by a detailed description of evolutionary computation, concentrating on the powerful Grammatical Evolution methodology. It continues by addressing fundamental issues facing all Evolutionary Algorithms in dynamic problems, such as how to adapt and generate constants, how to enhance evolvability and maintain diversity. Finally, the developed methods are illustrated with application to the real-world dynamic problem of trading on financial time-series.
The book was written to be accessible to a wide audience and should be of interest to practitioners, academics and students, who are seeking to apply grammar-based evolutionary algorithms to solve problems in dynamic environments. 'Foundations in Grammatical Evolution for Dynamic Environments' is the second book dedicated to the topic of Grammatical Evolution.
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