Original research is reported on image digitizing, robot choreography, movement analysis, databases for dance, computerized dance notation, and computerized lightboards for dance performance. Articles in this publication are as follows: (1) "The Evolution of Dance Technology" (Judith A. Gray); (2) "Toward a Language for Human Movement" (Thomas W. Calvert); (3) "A Computational Alternative to Effort Notation" (Norman I. Badler); (4) "Programming a Robot to Dance" (Margo K. Apostolos); (5) "The Use of a Motion Detector in Dance Instruction and Performance" (Alice Trexler, Ronald K. Thornton); (6) "Kahnotation: Computerized Notation for Tap Dance" (Stanley Kahn); (7) "A Computerized Procedure for Recording and Analyzing Dance Teacher Mobility" (Judith A. Gray); (8) "A Computer Program for the Entry of Benesh Movement Notation" (Fred M. Hagist, George Politis); (9) "A Computer-Assisted Investigation into the Effects of Heel Contact in Ballet Allegros" (Paula A. Dozzi); (10) "A Computerized Methodology Using Laban Movement Analysis To Determine Movement Profiles in Dance" (Mary A. Brennen, and others); (11) "The Computerized Production of Educational Material on Benesh Movement Notation" (Rhonda S. Ryman, Robyn Hughes-Ryman); (12) "Absolute (0,0,0): Dance Influenced by Technological Environments and Computers" (Dianna L. Petty); (13) "Capturing and Processing Dance Images with Computers" (Judith A. Gray); (14) "Computerized Lighting Design for Dance: An Interview with David Elliot" (Judith A. Gray); and (15) "The University's Role in the Future of Dance Technology" (Judith A. Gray). (JD)

Dancing humanoids, robotic art installations, and music generated by mathematically precise methods are no longer science fiction; in fact they are the subject of this book. This first-of-its-kind anthology assembles technical research that makes such creations possible. In order to mechanize something as enigmatic and personal as dance, researchers must delve deeply into two distinct academic disciplines: control theory and art. Broadly, this research uses techniques from the world of art to inspire methods in control, enables artistic endeavours using advanced control theory and aids in the analysis of art using metrics devised by a systems theoretic approach. To ensure that artistic influences are well represented, the individual chapters are focused so that they relate their contribution to the arts meaningfully and explicitly. Specially composed introductions set up the contributions either in terms of inspiration by artistic principles or their contribution to the arts through new analysis tools. To facilitate this, the majority of the chapters are authored jointly by experts in control theory and by artists, including dancers, choreographers, puppeteers and painters. Connections between controls and art then permeate the text so that these important relationships play a central role in the book. Controls and Art surveys current projects in this area—including a disco dancing robot, a reactive museum exhibit and otherworldly music—and illuminates open problems and topics for research in this emerging interdisciplinary field. It will draw attention both from experts in robotics and control interested in developing the artistic side of their creations and from academics studying dance, theater, music and the visual arts with an interest in avant-garde means of production.

The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.