4,279 research outputs found
Knowledge base, information search and intention to adopt innovation
Innovation is a process that involves searching for new information. This paper builds upon theoretical insights on individual and organizational learning and proposes a knowledge based model of how actors search for information when confronted with innovation. The model takes into account different search channels, both local and non local, and relates their use to the knowledge base of actors. The paper also provides an empirical validation of our model based on a study on the search channels used by a sample of Dutch consumers when buying new consumer electronic products.knowledge base, learning, information search, innovation, consumer behaviour
A Mimetic Strategy to Engage Voluntary Physical Activity In Interactive Entertainment
We describe the design and implementation of a vision based interactive
entertainment system that makes use of both involuntary and voluntary control
paradigms. Unintentional input to the system from a potential viewer is used to
drive attention-getting output and encourage the transition to voluntary
interactive behaviour. The iMime system consists of a character animation
engine based on the interaction metaphor of a mime performer that simulates
non-verbal communication strategies, without spoken dialogue, to capture and
hold the attention of a viewer. The system was developed in the context of a
project studying care of dementia sufferers. Care for a dementia sufferer can
place unreasonable demands on the time and attentional resources of their
caregivers or family members. Our study contributes to the eventual development
of a system aimed at providing relief to dementia caregivers, while at the same
time serving as a source of pleasant interactive entertainment for viewers. The
work reported here is also aimed at a more general study of the design of
interactive entertainment systems involving a mixture of voluntary and
involuntary control.Comment: 6 pages, 7 figures, ECAG08 worksho
Knowledge base, information search and intention to adopt innovation
Innovation is a process that involves searching for new information. This paper builds upon theoretical insights on individual and organizational learning and proposes a knowledge based model of how actors search for information when confronted with innovation. The model takes into account different search channels, both local and non local, and relates their use to the knowledge base of actors. The paper also provides an empirical validation of our model based on a study on the search channels used by a sample of Dutch consumers when buying new consumer electronic products
Coded Kalman Filtering Over Gaussian Channels with Feedback
This paper investigates the problem of zero-delay joint source-channel coding
of a vector Gauss-Markov source over a multiple-input multiple-output (MIMO)
additive white Gaussian noise (AWGN) channel with feedback. In contrast to the
classical problem of causal estimation using noisy observations, we examine a
system where the source can be encoded before transmission. An encoder,
equipped with feedback of past channel outputs, observes the source state and
encodes the information in a causal manner as inputs to the channel while
adhering to a power constraint. The objective of the code is to estimate the
source state with minimum mean square error at the infinite horizon. This work
shows a fundamental theorem for two scenarios: for the transmission of an
unstable vector Gauss-Markov source over either a multiple-input single-output
(MISO) or a single-input multiple-output (SIMO) AWGN channel, finite estimation
error is achievable if and only if the sum of logs of the unstable eigenvalues
of the state gain matrix is less than the Shannon channel capacity. We prove
these results by showing an optimal linear innovations encoder that can be
applied to sources and channels of any dimension and analyzing it together with
the corresponding Kalman filter decoder.Comment: Presented at 59th Allerton Conference on Communication, Control, and
Computin
Brain-Machine Interactions for Assessing the Dynamics of Neural Systems
A critical advance for braināmachine interfaces is the establishment of bi-directional communications between the nervous system and external devices. However, the signals generated by a population of neurons are expected to depend in a complex way upon poorly understood neural dynamics. We report a new technique for the identification of the dynamics of a neural population engaged in a bi-directional interaction with an external device. We placed in vitro preparations from the lamprey brainstem in a closed-loop interaction with simulated dynamical devices having different numbers of degrees of freedom. We used the observed behaviors of this composite system to assess how many independent parameters ā or state variables ā determine at each instant the output of the neural system. This information, known as the dynamical dimension of a system, allows predicting future behaviors based on the present state and the future inputs. A relevant novelty in this approach is the possibility to assess a computational property ā the dynamical dimension of a neuronal population ā through a simple experimental technique based on the bi-directional interaction with simulated dynamical devices. We present a set of results that demonstrate the possibility of obtaining stable and reliable measures of the dynamical dimension of a neural preparation
- ā¦