Programming/Languages

This book constitutes the proceedings of the 14th International Conference on Business Process Management, BPM 2016, held in Rio de Janeiro, Brazil, in September 2016. The focus of the conference covers a range of papers focusing on automated discovery, conformance checking, modeling foundations, understandability of process representations, runtime management and predictive monitoring. The topics selected by the authors demonstrate an increasing interest of the research community in the area of process mining, resonated by an equally fast-growing uptake by different industry sectors.

Interest in multilevel statistical models for social science and public health studies has been aroused dramatically since the mid-1980s. New multilevel modeling techniques are giving researchers tools for analyzing data that have a hierarchical or clustered structure. Multilevel models are now applied to a wide range of studies in sociology, population studies, education studies, psychology, economics, epidemiology, and public health. This book covers a broad range of topics about multilevel modeling. The goal of the authors is to help students and researchers who are interested in analysis of multilevel data to understand the basic concepts, theoretical frameworks and application methods of multilevel modeling. The book is written in non-mathematical terms, focusing on the methods and application of various multilevel models, using the internationally widely used statistical software, the Statistics Analysis System (SAS®). Examples are drawn from analysis of real-world research data. The authors focus on twolevel models in this book because it is most frequently encountered situation in real research. These models can be readily expanded to models with three or more levels when applicable. A wide range of linear and non-linear multilevel models are introduced and demonstrated.

Comprehension of texts and understanding of questions is a cornerstone of successful human communication. Whilst reading comprehension has been thoroughly investigated in the last decade, there is surprisingly little research on children’s comprehension of picture stories, particularly for bilinguals. This can be partially explained by the lack of cross-culturally robust, cross-linguistic instruments targeting early narration. This book presents an inference-based model of narrative comprehension and a tool that grew out of a large-scale European project on multilingualism. Covering a range of language settings, the book uses the Multilingual Assessment Instrument for Narratives to answer the question which narrative comprehension skills (bilingual) children can be expected to master at a certain age, and explores how such comprehension is affected (or not affected) by linguistic and extra-linguistic factors. Linking theory to method, the book will appeal to researchers in linguistics and psychology and graduate students interested in narrative, multilingualism, and language acquisition.

Physics-Based Deformable Models presents a systematic physics-based framework for modeling rigid, articulated, and deformable objects, their interactions with the physical world, and the estimate of their shape and motion from visual data. This book presents a large variety of methods and associated experiments in computer vision, graphics and medical imaging that help the reader better to understand the presented material. In addition, special emphasis has been given to the development of techniques with interactive or close to real-time performance. Physics-Based Deformable Models is suitable as a secondary text for graduate level courses in Computer Graphics, Computational Physics, Computer Vision, Medical Imaging, and Biomedical Engineering. In addition, this book is appropriate as a reference for researchers and practitioners in the above-mentioned fields.

This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Most analyses were done with the MIXED procedure of the SAS software package, but the data analyses are presented in a software-independent fashion.

Control theories have dominated criminological theory and research since the 1969 publication of Hirschi's seminal work on the social bond. Social control and self-control theorists are unique in suggesting that patterns in criminal behaviors are better explained by variations in social constraints rather than by individual motivational impulses, thus indicating that their main concerns are the explication and clarification of the techniques, processes, and institutions of informal social control. The four major sections of this volume focus on: the similarities and differences among the major contributors to the early developmental stage of social control theory; the central importance of parents, peers, and schools in the creation of informal control mechanisms and their link to crime and delinquency; the theoretical underpinnings of self-control theory, including empirical tests and criticisms; and theoretical integrations of social control and self-control theories with various motivational theories of crime and delinquency.

C# Programming 2012.