Practical Load Balancing:Ride the Performance Tiger. 1st ed Peter Membrey, Eelco Plugge, David Hows, Peter Membrey, Eelco Plugge
Understanding the fatigue behaviour of structural components under variable load amplitude is an essential prerequisite for safe and reliable light-weight design. For designing and dimensioning, the expected stress (load) is compared with the capacity to withstand loads (fatigue strength). In this process, the safety necessary for each particular application must be ensured. A prerequisite for ensuring the required fatigue strength is a reliable load assumption. The authors describe the transformation of the stress- and load-time functions which have been measured under operational conditions to spectra or matrices with the application of counting methods. The aspects which must be considered for ensuring a reliable load assumption for designing and dimensioning are discussed in detail. Furthermore, the theoretical background for estimating the fatigue life of structural components is explained, and the procedures are discussed for numerous applications in practice. One of the prime intentions of the authors is to provide recommendations which can be implemented in practical applications. The authors are experienced engineers in the automotive industry / at a German Technical University.
This book explores robust multimodal cognitive load measurement with physiological and behavioural modalities, which involve the eye, Galvanic Skin Response, speech, language, pen input, mouse movement and multimodality fusions. Factors including stress, trust, and environmental factors such as illumination are discussed regarding their implications for cognitive load measurement. Furthermore, dynamic workload adjustment and real-time cognitive load measurement with data streaming are presented in order to make cognitive load measurement accessible by more widespread applications and users. Finally, application examples are reviewed demonstrating the feasibility of multimodal cognitive load measurement in practical applications. This is the first book of its kind to systematically introduce various computational methods for automatic and real-time cognitive load measurement and by doing so moves the practical application of cognitive load measurement from the domain of the computer scientist and psychologist to more general end-users, ready for widespread implementation. Robust Multimodal Cognitive Load Measurement is intended for researchers and practitioners involved with cognitive load studies and communities within the computer, cognitive, and social sciences. The book will especially benefit researchers in areas like behaviour analysis, social analytics, human-computer interaction (HCI), intelligent information processing, and decision support systems.
Thermal Load control Using PV modules:A Practical Approach Sweta Bijali Maity, Raj Kumar Maity
Load Assumption for Fatigue Design of Structures and Components:Counting Methods, Safety Aspects, Practical Application. 1st ed. 2017 Michael Köhler, Sven Jenne, Kurt Pötter, Harald Zenner
This book is packed from cover to cover with exercises that will really inspire learners, covering a huge variety of language areas. Its aimed at learners who are studying at about Level 1 and can be used by teachers with all types of English classes, as well as students for home study, since the answers to all of the activities, plus notes for solving the exercises, are included at the back of the book. The book is divided into sections according to type of language skills being practised, namely grammar, vocabulary, spelling, reading, speaking & listening, and research skills. This book includes lots of unique material that has been written especially for our learners, including exercises on its or its, adverbs, syllables, understanding maps, and Calculator Code Words. Theres loads of stuff here for learners of English to get their teeth into - wherever you may be studying! This book is all about helping learners to improve their English skills - reading, writing, speaking and listening We hope you will really enjoy using this book as a self-study tool or with your learners, if you are a teacher.
The key component in forecasting demand and consumption of resources in a supply network is an accurate prediction of real-valued time series. Indeed, both service interruptions and resource waste can be reduced with the implementation of an effective forecasting system. Significant research has thus been devoted to the design and development of methodologies for short term load forecasting over the past decades. A class of mathematical models, called Recurrent Neural Networks, are nowadays gaining renewed interest among researchers and they are replacing many practical implementations of the forecasting systems, previously based on static methods. Despite the undeniable expressive power of these architectures, their recurrent nature complicates their understanding and poses challenges in the training procedures. Recently, new important families of recurrent architectures have emerged and their applicability in the context of load forecasting has not been investigated completely yet. This work performs a comparative study on the problem of Short-Term Load Forecast, by using different classes of state-of-the-art Recurrent Neural Networks. The authors test the reviewed models first on controlled synthetic tasks and then on different real datasets, covering important practical cases of study. The text also provides a general overview of the most important architectures and defines guidelines for configuring the recurrent networks to predict real-valued time series. Dr. Filippo Maria Bianchi is a postdoctoral researcher in the Department of Physics and Technology at the Arctic University of Norway, Tromsø, Norway. Dr. Michael C. Kampffmeyer is a research fellow at the same institution. Dr. Robert Jenssen is an associate professor at the same institution. Dr. Enrico Maiorino is a research fellow in the Channing Division of Network Medicine at Harvard Medical School, Boston, MA, USA. Dr. Antonello Rizzi is an assistant professor in the Department of Information Engineering, Electronics and Telecommunications at the Sapienza University of Rome, Italy.
Practical AWS Networking:Build and manage complex networks using services such as Amazon VPC, Elastic Load Balancing, Direct Connect, and Amazon Route 53 Mitesh Soni
The first and second editions of Repacking Your Bags helped people develop their own unique visions of the good life and take practical steps at home and at work to make sense of their lives and live in an authentically meaningful way. Written as a travel guide it helped people to put together a ´´trip checklist´´ that provided the elements of the good life: work, love, place, and purpose. But Leider and Shapiro came to realize that repacking is not something we do once or twice in reaction to a sense of disillusionment or frustration in our lives. Developing one’s own vision of the good life is a matter of constant and evolving choice, as the inevitable shifts and surprises life has to offer continually unfold before us. With each step along the way, it remains necessary to reexamine what has brought us here, to continue asking ourselves if the choices that have sustained us so far are continuing to do so - or if they’re just weighing us down. This edition has been thoroughly revised to make it applicable for listeners today. The changes include:Refocused message on the new life and work realities and the survival skills required to succeedMore practices and experiences for ´´lightening your load´´Fresh new stories of ´´people just like me´´, the listenerA new ´´Repacking Journal´´Addition of Leider’s immensely popular Calling Cards exercise for discovering your gifts, passions and values, with access to a Calling Cards online profilePLEASE NOTE: When you purchase this title, the accompanying reference material will be available in your My Library section along with the audio. 1. Language: English. Narrator: Walter Dixon. Audio sample: http://samples.audible.de/bk/gdan/000782de/bk_rhde_002536_sample.mp3. Digital audiobook in aax.