This volume contains a collection of papers in control theory and applications presented at a conference in honor of Clyde Martin on the occasion of his 60th birthday, held in Lubbock, Texas, November 14-15, 2003.

New Directions in Criminological Theory focuses on new approaches to theory construction, with particular emphasis on reformulations and new applications of existing paradigms. It includes an assessment of labeling theory, demonstrating how the approach could become part of a more comprehensive explanation of crime. A case is made for studying crime in terms of the social context in which crimes are conceived, interpreted, and negotiated. The debate between crime-general and crime-specific approaches is further amplified. A rethinking of Hirschi's control theory is presented. The volume includes theoretical discussions of spouse abuse, of punishment, and of power-control models. Additional chapters examine theoretical advances in corporate illegality, employee theft, and the alcohol/crime syndrome.These original contributions include: Charles F. Wellford and Ruth A. Triplett, 'The Future of Labeling Theory'; Austin T. Turk, 'A Proposed Resolution of Key Issues in the Political Sociology of Law'; David Weisburd and Lisa Maher, 'Contrasting Crime-General and Crime-Specific Theory'; Sally Simpson, 'Strategy, Structure, and Corporate Crime'; Edward W. Sieh, 'Employee theft'; Robert Nash Parker, 'Alcohol and Theories of Homicide'; Kimberly L. Kemph, 'The Empirical Status of Hirschi's Control Theory'; Jeffrey Fagan, 'The Social Control of Spouse Assualt'; Marc Le Blanc and Aaron Caplan, 'Theoretical Formalization, A Necessity'; Michael J. Lynch, 'Control Theory and Punishment'; Gary F. Jensen, 'Power-Control vs. Social-Control Theories of Common Delinquency'; John Hagan, A.R. Gillis, and John Simpson, 'The Power of Control in Sociological Theories of Delinquency.'

This book gathers authoritative contributions in the field of Soft Computing. Based on selected papers presented at the 7th World Conference on Soft Computing, which was held on May 29–31, 2018, in Baku, Azerbaijan, it describes new theoretical advances, as well as cutting-edge methods and applications. New theories and algorithms in fuzzy logic, cognitive modeling, graph theory and metaheuristics are discussed, and applications in data mining, social networks, control and robotics, geoscience, biomedicine and industrial management are described. This book offers a timely, broad snapshot of recent developments, including thought-provoking trends and challenges that are yielding new research directions in the diverse areas of Soft Computing.

Revitalizing Victimization Theory: Revisions, Applications, and New Directions revises some of the major perspectives in victimization theory, applies theoretical perspectives to the victimization of vulnerable populations, and carves out new theoretical territory that is clearly needed but has yet to be developed. With the exception of a handful of isolated works in the mid-twentieth century, theory and research on victimization did not come into its own until the late 1970s with the articulation of lifestyle and routine activity theories. Research conducted within this tradition continues to be an important part of the overall criminological enterprise, and a large body of empirical knowledge has been generated. Nevertheless, theoretical advances in the study of victimization have largely stalled within the field of criminology. Indeed, little in the way of new theoretical headway has been made in well over a decade. This is an ideal time to revitalize victimization theory, and this volume does just that. It is an ambitious project that will hopefully reignite the kinds of theoretical discussions that once held the attention of the field. The work included here will shape the future of victimization theory and research in years to come. This volume should be of interest to a wide range of criminologists and have the potential to be used in graduate seminars and upper-level undergraduate courses.

This work examines viability theory and its applications to control theory and differential games. The emphasis is on the construction of feedbacks and dynamical systems by myopic optimization methods. Systems of first-order partial differential inclusions, whose solutions are feedbacks, are constructed and investigated. Basic results are then extended to the case of fuzzy control problems, distributed control problems, and control systems with delays and memory. Aimed at graduate students and research mathematicians, both pure and applied, this book offers specialists in control and nonlinear systems tools to take into account general state constraints. Viability theory also allows researchers in other disciplinesâartificial intelligence, economics, game theory, theoretical biology, population genetics, cognitive sciencesâto go beyond deterministic models by studying them in a dynamical or evolutionary perspective in an uncertain environment. "The book is a compendium of the state of knowledge about viability...Mathematically, the book should be accessible to anyone who has had basic graduate courses in modern analysis and functional analysisâ¦The concepts are defined and many proofs of the requisite results are reproduced here, making the present book essentially self-contained." (Bulletin of the AMS) "Because of the wide scope, the book is an ideal reference for people encountering problems related to viability theory in their researchâ¦It gives a very thorough mathematical presentation. Very useful for anybody confronted with viability constraints." (Mededelingen van het Wiskundig Genootschap)

Thepastthree decadeshaveseenrapiddevelopmentin the areaofmodelpred- tive control with respect to both theoretical and application aspects. Over these 30 years, model predictive control for linear systems has been widely applied, especially in the area of process control. However, today’s applications often require driving the process over a wide region and close to the boundaries of - erability, while satisfying constraints and achieving near-optimal performance. Consequently, the application of linear control methods does not always lead to satisfactory performance, and here nonlinear methods must be employed. This is one of the reasons why nonlinear model predictive control (NMPC) has - joyed signi?cant attention over the past years,with a number of recent advances on both the theoretical and application frontier. Additionally, the widespread availability and steadily increasing power of today’s computers, as well as the development of specially tailored numerical solution methods for NMPC, bring thepracticalapplicabilityofNMPCwithinreachevenforveryfastsystems.This has led to a series of new, exciting developments, along with new challenges in the area of NMPC.