This book presents a comprehensive treatment of visual analysis of behaviour from computational-modelling and algorithm-design perspectives. Topics: covers learning-group activity models, unsupervised behaviour profiling, hierarchical behaviour discovery, learning behavioural context, modelling rare behaviours, and “man-in-the-loop” active learning; examines multi-camera behaviour correlation, person re-identification, and “connecting-the-dots” for abnormal behaviour detection; discusses Bayesian information criterion, Bayesian networks, “bag-of-words” representation, canonical correlation analysis, dynamic Bayesian networks, Gaussian mixtures, and Gibbs sampling; investigates hidden conditional random fields, hidden Markov models, human silhouette shapes, latent Dirichlet allocation, local binary patterns, locality preserving projection, and Markov processes; explores probabilistic graphical models, probabilistic topic models, space-time interest points, spectral clustering, and support vector machines.

This book describes various ABA terms with examples and illustrations. It is good for students who study ABA, people who are pursuing BCBA(R), BCaBA(R) or RBT(R), people who use ABA for their profession, parents who are raising children with Autism and other related disorders and anyone who is interested in learning ABA.

The Handbook of Visual Analysis is a rich methodological resource for students, academics, researchers and professionals interested in investigating the visual representation of socially significant issues. The Handbook: Offers a wide-range of methods for visual analysis: content analysis, historical analysis, structuralist analysis, iconography, psychoanalysis, social semiotic analysis, film analysis and ethnomethodology Shows how each method can be applied for the purposes of specific research projects Exemplifies each approach through detailed analyses of a variety of data, including, newspaper images, family photos, drawings, art works and cartoons Includes examples from the authors' own research and professional practice The Handbook of Visual Analysis, which demonstrates the importance of visual data within the social sciences offers an essential guide to those working in a range of disciplines including: media and communication studies, sociology, anthropology, education, psychoanalysis, and health studies.

This four-volume set LNCS 6761-6764 constitutes the refereed proceedings of the 14th International Conference on Human-Computer Interaction, HCII 2011, held in Orlando, FL, USA in July 2011, jointly with 8 other thematically similar conferences. The revised papers presented were carefully reviewed and selected from numerous submissions. The papers accepted for presentation thoroughly cover the entire field of Human-Computer Interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas. The papers of this first volume are organized in topical sections on HCI design, model-based and patterns-based design and development, cognitive, psychological and behavioural issues in HCI, development methods, algorithms, tools and environments, and image processing and retrieval in HCI.

A dictionary of terms used in Applied Behavior Analysis and qutism.

In the early 1980s there had been a marked increase in the application of behavioural methods in schools. However, much of this work was weak conceptually and limited in its remit. Behaviour analysis has more to offer education than ‘smarties’ and time-out. Originally published in 1986, this collection of twenty papers, many of them experimental, serves to demonstrate the power of behaviour analysis in a wide variety of applications. The editors stress the importance of antecedent control, as well as consequence management strategies, and illustrate their relevance in solving problems in everyday situations at school and in the home. The Editors, whose own work is well represented in this collection, are acknowledged as leading researchers in this field.

Single system, or single case, design studies are a convenient method for evaluating practice, allowing professionals to track clients' response to treatment and change over time. They also allow researchers to gather data where it might be difficult to conduct a study involving treatment and control groups; in a school setting, or a community mental health agency, for example, random assignment may be impossible, whereas individual student or client progress across time can be more easily monitored. This pocket guide reviews a wide range of techniques for analyzing single system design data, including visual analysis methods, graphical methods, and statistical methods. From basic visual observation to complex ARIMA statistical models for use with interrupted time series designs, numerous data analysis methods are described and illustrated in this unique and handy book. The author frankly describes limitations and strengths of the data analysis methods so that readers can select an appropriate method and use the results responsibly in order to improve practice and client well-being. This accessible yet in-depth introduction will serve as a highly practical resource for doctoral students and researchers alike.

EBOOK: Psychology: The Science of Mind and Behaviour, 4e