61 research outputs found
Choreographic and Somatic Approaches for the Development of Expressive Robotic Systems
As robotic systems are moved out of factory work cells into human-facing
environments questions of choreography become central to their design,
placement, and application. With a human viewer or counterpart present, a
system will automatically be interpreted within context, style of movement, and
form factor by human beings as animate elements of their environment. The
interpretation by this human counterpart is critical to the success of the
system's integration: knobs on the system need to make sense to a human
counterpart; an artificial agent should have a way of notifying a human
counterpart of a change in system state, possibly through motion profiles; and
the motion of a human counterpart may have important contextual clues for task
completion. Thus, professional choreographers, dance practitioners, and
movement analysts are critical to research in robotics. They have design
methods for movement that align with human audience perception, can identify
simplified features of movement for human-robot interaction goals, and have
detailed knowledge of the capacity of human movement. This article provides
approaches employed by one research lab, specific impacts on technical and
artistic projects within, and principles that may guide future such work. The
background section reports on choreography, somatic perspectives,
improvisation, the Laban/Bartenieff Movement System, and robotics. From this
context methods including embodied exercises, writing prompts, and community
building activities have been developed to facilitate interdisciplinary
research. The results of this work is presented as an overview of a smattering
of projects in areas like high-level motion planning, software development for
rapid prototyping of movement, artistic output, and user studies that help
understand how people interpret movement. Finally, guiding principles for other
groups to adopt are posited.Comment: Under review at MDPI Arts Special Issue "The Machine as Artist (for
the 21st Century)"
http://www.mdpi.com/journal/arts/special_issues/Machine_Artis
Resource management in Big Data initiatives: processes and dynamic capabilities
© 2016 The Authors. Effective management of organizational resources in big data initiatives is of growing importance. Although academic and popular literatures contain many examples of big data initiatives, very few are repeated in the same organization. This suggests either big data delivers benefits once only per organization or senior managers are reluctant to commit resources to big data on a sustained basis. This paper makes three contributions to the Special Issue’s theme of enhancing organizational resource management. One is to establish an archetype business process for big data initiatives. The second contribution directs attention to creating a dynamic capability with big data initiatives. The third identifies drawbacks of resource base theory (RBT) and it’s underpinning assumptions in the context of big data. The paper discusses lessons learnt from the case study and draws out implications for practice and business research. The paper’s intellectual and practical contributions are based on an in-depth case study of the European Poles of Excellence (EIPE) big data initiative and evidence from the extant literature
Concrete gravity dams model parameters updating using static measurements
The structural control of concrete gravity dams is of primary importance. In this context, numerical models play a fundamental role both to assess the vulnerability of gravity dams and to control their behaviour during normal operativity and after extreme events. In this regard, data monitoring represents an important source of information for numerical model calibrations. This study proposes a novel probabilistic procedure, defined in the Bayesian framework, to calibrate the parameters of finite elements models of dams. To this aim, monitoring data and the results of material tests are used as reference information. The computational burden is reduced by using a new hybrid-predictive model of the dam displacements. An application on an Italian dam shows the feasibility of the proposed procedure
- …