The'Flynn effect'refers to the massive increase in IQ test scores over the course of the
twentieth century. Does it mean that each generation is more intelligent than the last? Does …

Humans can learn a language through physical interaction with their environment and
semiotic communication with other people. It is very important to obtain a computational …

A novel method for integrating driving behavior and traffic context through signal
symbolization is presented in this paper. This symbolization framework is proposed as a …

We propose an unsupervised double articulation analyzer for human motion data. Double
articulation is a two-layered hierarchical structure underlying in natural language, human …

We present a method to analyze a relationship between eye movements and saliency
dynamics in videos for estimating attentive states of users while they watch the videos. The …

Modeling the driver behavior is expected to play a fundamental role in designing systems of
driver monitoring, warning, assist control and training. In this paper, we present an …

We propose an unsupervised motion segmentation method for enabling a robot to imitate
and perform various unit motions by observing unsegmented human motion. Natural …

Much of the discussion concerning smart grids focuses on the potential benefits of
technological advances to power suppliers. However, there are many possible advantages …

We describe a means of human robot interaction based not on natural language but on"
quasi symbols," which represent sensory-motor dynamics in the task and/or environment. It …

Movement of the thighs is an important factor for studying gait cycle. In this paper, a hybrid
hidden Markov model (HMM)/Kalman filter (KF) scheme is proposed to track the hip angle …