James J. Buckley Books

Young readers are introduced to the all-time biggest stars in NBA history and are welcomed to the world of flashy dunkers, super shooters, and three-point masters of the past and present. Full-color photos.

What happens when a school administrator becomes involved in solving the crime perpetrated against one of his teachers? Ed Pearson finds out as he uncovers clue after clue about what may have occurred to the faculty member whose body lies for days undiscovered. Although at first, the press jokingly refers to him as their local Sherlock Holmes, they eventually realize that without his help, the murder case will not be solved.

Set in 1850, the story follows Thad Perkins, a US seaman entangled in a web of espionage under President Millard Fillmore's new spy network. As he navigates dangerous assassination attempts, Thad's life and the safety of those around him become increasingly at risk, with some becoming unintended victims in the chaos. The narrative explores themes of loyalty, danger, and the high stakes of covert operations during a tumultuous period in American history.

The book provides a comprehensive exploration of fuzzy concepts, structured into multiple sections covering fuzzy probability, estimation, hypothesis testing, and statistical models. It begins with foundational knowledge of fuzzy sets and progresses to advanced topics, including fuzzy correlation and regression, fuzzy ANOVA models, and applications of random fuzzy numbers in Monte Carlo studies. Notably, it introduces new algorithms and optimization techniques for solving fuzzy problems, enhancing the reader's understanding of both theory and practical applications in fuzzy statistics.

This book delves into the principles and methodologies of simulating fuzzy systems, offering a comprehensive exploration of both theoretical foundations and practical applications. It introduces various fuzzy logic concepts and their integration into simulation frameworks, highlighting the advantages of fuzzy systems in handling uncertainty and imprecision. The text is enriched with case studies and examples that demonstrate the effectiveness of fuzzy simulations in diverse fields, making it a valuable resource for researchers and practitioners seeking to enhance their understanding of fuzzy system applications.

The book is structured into four main parts focusing on fuzzy statistics. The first part introduces fuzzy estimation, including the construction of fuzzy estimators for normal distributions. The second part delves into fuzzy hypothesis testing, applying fuzzy estimators in statistical tests. The third part covers fuzzy regression and prediction, starting with fuzzy correlation and progressing through simple and multiple linear regression. Each section builds on the previous one, emphasizing the use of crisp data from random samples to develop fuzzy models.

The book is structured into five key parts, starting with introductory chapters that lay the groundwork for understanding fuzzy sets. It progresses to modeling fuzzy queuing systems using fuzzy probabilities and rates, followed by optimization models. The final sections summarize the findings and propose future research directions, along with numerical methods for calculating fuzzy probabilities and optimizing fuzzy values. Essential concepts of fuzzy sets are covered early on, ensuring readers can grasp the necessary tools for the subsequent chapters.

The book explores the innovative use of fuzzy numbers for estimating probabilities and parameters in statistics, moving beyond traditional point estimates. It introduces constrained fuzzy arithmetic to ensure probabilities sum to one and discusses fuzzy random variables with fuzzy distributions. A key focus is on fuzzy normal random variables, which incorporate fuzzy means and variances. Applications span various fields, including queuing theory, Markov chains, inventory control, decision theory, and reliability theory, highlighting the versatility of this approach in practical scenarios.