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In The New Rules of Lifting for Women, authors Lou Schuler, Cassandra Forsythe and Alwyn Cosgrove present a comprehensive strength, conditioning and nutrition plan destined to revolutionize the way women work out. All the latest studies prove that strength training, not aerobics, provides the key to losing fat and building a fit, strong body. This book refutes the misconception that women will "bulk up" if they lift heavy weights. Nonsense! It's tough enough for men to pack on muscle, and they have much more of the hormone necessary to build muscle: natural testosterone. Muscles need to be strengthened to achieve a lean, healthy look. Properly conditioned muscles increase metabolism and promote weight loss -- it's that simple. The program demands that women put down the "Barbie" weights, step away from the treadmill and begin a strength and conditioning regime for the natural athlete in every woman. The New Rules of Lifting for Women will change the way women see fitness, nutrition and their own bodies.
OUR DEAR YOUNG MEN AND YOUNG WOMEN, we have great confidence in you. You are beloved sons and daughters of God and He is mindful of you. You have come to earth at a time of great opportunities and also of great challenges. The standards in this booklet will help you with the important choices you are making now and will yet make in the future. We promise that as you keep the covenants you have made and these standards, you will be blessed with the companionship of the Holy Ghost, your faith and testimony will grow stronger, and you will enjoy increasing happiness.
Classifier systems are an intriguing approach to a broad range of machine learning problems, based on automated generation and evaluation of condi tion/action rules. Inreinforcement learning tasks they simultaneously address the two major problems of learning a policy and generalising over it (and re lated objects, such as value functions). Despite over 20 years of research, however, classifier systems have met with mixed success, for reasons which were often unclear. Finally, in 1995 Stewart Wilson claimed a long-awaited breakthrough with his XCS system, which differs from earlier classifier sys tems in a number of respects, the most significant of which is the way in which it calculates the value of rules for use by the rule generation system. Specifically, XCS (like most classifiersystems) employs a genetic algorithm for rule generation, and the way in whichit calculates rule fitness differsfrom earlier systems. Wilson described XCS as an accuracy-based classifiersystem and earlier systems as strength-based. The two differin that in strength-based systems the fitness of a rule is proportional to the return (reward/payoff) it receives, whereas in XCS it is a function of the accuracy with which return is predicted. The difference is thus one of credit assignment, that is, of how a rule's contribution to the system's performance is estimated. XCS is a Q learning system; in fact, it is a proper generalisation of tabular Q-learning, in which rules aggregate states and actions. In XCS, as in other Q-learners, Q-valuesare used to weightaction selection.
The Second Edition of the bestselling Measurement, Instrumentation, and Sensors Handbook brings together all aspects of the design and implementation of measurement, instrumentation, and sensors. Reflecting the current state of the art, it describes the use of instruments and techniques for performing practical measurements in engineering, physics, chemistry, and the life sciences and discusses processing systems, automatic data acquisition, reduction and analysis, operation characteristics, accuracy, errors, calibrations, and the incorporation of standards for control purposes. Organized according to measurement problem, the Electromagnetic, Optical, Radiation, Chemical, and Biomedical Measurement volume of the Second Edition: Contains contributions from field experts, new chapters, and updates to all 98 existing chapters Covers sensors and sensor technology, time and frequency, signal processing, displays and recorders, and optical, medical, biomedical, health, environmental, electrical, electromagnetic, and chemical variables A concise and useful reference for engineers, scientists, academic faculty, students, designers, managers, and industry professionals involved in instrumentation and measurement research and development, Measurement, Instrumentation, and Sensors Handbook, Second Edition: Electromagnetic, Optical, Radiation, Chemical, and Biomedical Measurement provides readers with a greater understanding of advanced applications.
Gallup presents the remarkable findings of its revolutionary study of more than 80,000 managers in First, Break All the Rules, revealing what the world’s greatest managers do differently. With vital performance and career lessons and ideas for how to apply them, it is a must-read for managers at every level. The greatest managers in the world seem to have little in common. They differ in sex, age, and race. They employ vastly different styles and focus on different goals. Yet despite their differences, great managers share one common trait: They do not hesitate to break virtually every rule held sacred by conventional wisdom. They do not believe that, with enough training, a person can achieve anything he sets his mind to. They do not try to help people overcome their weaknesses. They consistently disregard the golden rule. And, yes, they even play favorites. This amazing book explains why. Gallup presents the remarkable findings of its massive in-depth study of great managers across a wide variety of situations. Some were in leadership positions. Others were front-line supervisors. Some were in Fortune 500 companies; others were key players in small entrepreneurial companies. Whatever their situations, the managers who ultimately became the focus of Gallup’s research were invariably those who excelled at turning each employee’s talent into performance. In today’s tight labor markets, companies compete to find and keep the best employees, using pay, benefits, promotions, and training. But these well-intentioned efforts often miss the mark. The front-line manager is the key to attracting and retaining talented employees. No matter how generous its pay or how renowned its training, the company that lacks great front-line managers will suffer. The authors explain how the best managers select an employee for talent rather than for skills or experience; how they set expectations for him or her — they define the right outcomes rather than the right steps; how they motivate people — they build on each person’s unique strengths rather than trying to fix his weaknesses; and, finally, how great managers develop people — they find the right fit for each person, not the next rung on the ladder. And perhaps most important, this research — which initially generated thousands of different survey questions on the subject of employee opinion — finally produced the twelve simple questions that work to distinguish the strongest departments of a company from all the rest. This book is the first to present this essential measuring stick and to prove the link between employee opinions and productivity, profit, customer satisfaction, and the rate of turnover. There are vital performance and career lessons here for managers at every level, and, best of all, the book shows you how to apply them to your own situation.
New Rules of Lifting, you aren't getting the best possible results. Book jacket.
This volume contains the proceedings of the Eurpoean Conference on Machine Learning (ECML-93), continuing the tradition of the five earlier EWSLs (European Working Sessions on Learning). The aim of these conferences is to provide a platform for presenting the latest results in the area of machine learning. The ECML-93 programme included invited talks, selected papers, and the presentation of ongoing work in poster sessions. The programme was completed by several workshops on specific topics. The volume contains papers related to all these activities. The first chapter of the proceedings contains two invited papers, one by Ross Quinlan and one by Stephen Muggleton on inductive logic programming. The second chapter contains 18 scientific papers accepted for the main sessions of the conference. The third chapter contains 18 shorter position papers. The final chapter includes three overview papers related to the ECML-93 workshops.
This volume brings together recent theoretical work in Learning Classifier Systems (LCS), which is a Machine Learning technique combining Genetic Algorithms and Reinforcement Learning. It includes self-contained background chapters on related fields (reinforcement learning and evolutionary computation) tailored for a classifier systems audience and written by acknowledged authorities in their area - as well as a relevant historical original work by John Holland.
The JURIX conferences are an established international forum for academics, practitioners, government and industry to present and discuss advanced research at the interface between law and computer science. Subjects addressed in this book cover all aspects of this diverse field: theoretical – focused on a better understanding of argumentation, reasoning, norms and evidence; empirical – targeted at a more general understanding of law and legal texts in particular; and practical papers aimed at enabling a broader technical application of theoretical insights. This book presents the proceedings of the 27th International Conference on Legal Knowledge and Information Systems: JURIX 2014, held in Kraków, Poland, in December 2014. The book includes the 14 full papers, 8 short papers, 6 posters and 2 demos – the first time that poster submissions have been included in the proceedings. The book will be of interest to all those whose work involves legal theory, argumentation and practice and who need a current overview of the ways in which current information technology is relevant to legal practice.